Author: "Hao, Chun" / Topic: business.industry - Searchworks@Jio Institute Digital Library Search Results

170 results on '"Hao, Chun"'

1. Predictive analytics for customer repurchase: Interdisciplinary integration of buy till you die modeling and machine learning

Author: Yen-Chun Chou, Howard Hao-Chun Chuang, Ting-Peng Liang, and Ping Chou
Subjects: Information Systems and Management, General Computer Science, Computer science, 0211 other engineering and technologies, 02 engineering and technology, Management Science and Operations Research, Machine learning, computer.software_genre, Industrial and Manufacturing Engineering, Lasso (statistics), 0502 economics and business, Feature (machine learning), Interpretability, 050210 logistics & transportation, 021103 operations research, Artificial neural network, business.industry, 05 social sciences, Probabilistic logic, Predictive analytics, Recurrent neural network, Analytics, Modeling and Simulation, Artificial intelligence, business, computer
Abstract: Predicting customer repurchase propensity/frequency has received broad research interests from marketing, operations research, statistics, and computer science. In the field of marketing, Buy till You Die (BTYD) models are perhaps the most representative techniques for customer repurchase prediction. Those probabilistic models are parsimonious and typically involve only recency and frequency of customer activities. Contrary to BTYD models, a distinctly different class of predictive models for customer repurchase is machine learning. This class of models include a wide variety of computational and statistical learning algorithms. Unlike BTYD models built on low-dimensional inputs and behavioral assumptions, machine learning is more data-driven and excels at fitting predictive models to a large array of features from customer transactions. Using a large online retailing data, we empirically assess the prediction performance of BTYD modeling and machine learning. More importantly, we investigate how the two approaches can complement each other for repurchase prediction. We use the BG/BB model given the discrete and non-contractual problem setting and incorporate BG/BB estimates into high-dimensional Lasso regression. In addition to showing significant improvement over BG/BB and Lasso without BG/BB, the integrated Lasso-BG/BB provides interpretability and identifies BG/BB predictions as the most influential feature among ∼100 predictors. The lately developed CART-artificial neural networks exhibit similar patterns. Robustness checks further show the proposed Lasso-BG/BB outperforms two sophisticated recurrent neural networks, validating the complementarity of machine learning and BTYD modeling. We conclude by articulating how our interdisciplinary integration of the two modeling paradigms contributes to the theory and practice of predictive analytics.
Published: 2022

2. Role of open cerclage wiring in patients with comminuted fractures of the femoral shaft treated with intramedullary nails

Author: Wei Ren Su, Kai-Lan Hsu, Fa-Chuan Kuan, Ming Long Yeh, Chih-Kai Hong, Hao-Chun Chuang, and Tzu-Hao Wang
Subjects: medicine.medical_specialty, Nonunion, Bone healing, Diseases of the musculoskeletal system, Bone Nails, law.invention, Intramedullary rod, Fixation (surgical), law, Medicine, Humans, Orthopedics and Sports Medicine, In patient, Fractures, Comminuted, Retrospective Studies, Fracture Healing, Orthopedic surgery, integumentary system, business.industry, Perioperative, medicine.disease, Surgery, Fracture Fixation, Intramedullary, Treatment Outcome, RC925-935, Nail (fastener), business, Femoral Fractures, RD701-811, Research Article
Abstract: Introduction The role of open cerclage wiring in comminuted femoral shaft fracture treatment with intramedullary nails remains unclear. Here, we analyzed the effect of open cerclage wiring and the risk factors for nonunion after interlocking nailing in comminuted femoral shaft fracture treatment. We hypothesized that open cerclage wiring can be applied in patients with severe comminuted femoral shaft fractures without affecting bone healing. Patients and methods This retrospective cohort study used data from consecutive patients who underwent interlocking nail fixation of a comminuted femoral shaft fracture between January 1, 2009, and December 31, 2016. First, eligible patients were divided into the wire and no wire groups according to the surgical technique used, and their union rate was recorded. The patients were then divided into the union and nonunion groups, and their perioperative data were analyzed. Results In total, 71 comminuted femoral shaft fractures treated with interlocking nail fixation were included: 38 fractures (53.5%) augmented with the open wiring technique and 33 reduced with closed or mini-open techniques without wiring. The wire group demonstrated significant improvements in fracture reduction compared with the no wire group, whereas no significant difference was observed in the union rate between the wire and no wire groups (p = 0.180). Moreover, 46 (65%) of 71 fractures achieved union smoothly, and no significant difference was observed in any perioperative data between the union and nonunion groups. Discussion Augmentation with open cerclage wiring is indicated for comminuted femoral shaft fractures treated with intramedullary nails, even when the fragments are large or greatly displaced. Thus, open cerclage wiring can be used for fracture treatment without decreasing the union rate.
Published: 2021

3. Radiographic greater tuberosity spurs and narrow acromiohumeral intervals are associated with advanced retraction of the supraspinatus tendon in patients with symptomatic rotator cuff tears

Author: Fa Chuan Kuan, Chen Hao Chiang, Yueh Chen, Chih-Kai Hong, Hao Chun Chuang, Kai Lan Hsu, and Wei Ren Su
Subjects: Shoulder, medicine.medical_specialty, lcsh:Diseases of the musculoskeletal system, Radiography, Rotator cuff tear, lcsh:Orthopedic surgery, tendon retraction, Statistical significance, medicine, Orthopedics and Sports Medicine, Rotator cuff, greater tuberosity spur, business.industry, Odds ratio, musculoskeletal system, humanities, Confidence interval, Tendon, Surgery, lcsh:RD701-811, medicine.anatomical_structure, Tears, Rotator Cuff Pathology, lcsh:RC925-935, business, radiography, Greater Tuberosity
Abstract: Background Degenerative signs on shoulder radiographs, including spur formation and narrow acromiohumeral intervals (AHIs), have been recognized as indicative of atrophic and fat-infiltrated rotator cuff muscles. Past studies have demonstrated that patients with poor quality muscles are prone to retraction of the supraspinatus tendon and failure to repair. However, the association between radiographic signs and tendon retraction has never been elucidated in previous literature. The present study aimed to investigate the association between the degenerative signs on shoulder radiographs and the severity of supraspinatus retraction. Methods Images of 67 individuals, who had undergone an arthroscopic rotator cuff repair, were retrospectively reviewed. The greater tuberosity (GT) morphology, subacromial spur, AHI, and acromial thickness were evaluated on the radiographs, whereas the retraction of the supraspinatus tendon was assessed via an MRI in accordance with the Patte classification. Simple regression analyses between the radiographic signs and Patte stages were performed, and factors reaching statistical significance were then included in the multiple ordinal logistic regression. Statistically significant predictors from the multiple regression analysis were constructed into combinations, for which the sensitivity and specificity were calculated. Results The GT morphology (P = .004), AHI (P = .083), subacromial spur (P = .008), and age (P = .004) were associated with supraspinatus retraction in the simple regression analyses. These four parameters were incorporated into the multiple ordinal logistic regression, where the GT spur (adjusted odds ratio 8.63, 95% confidence interval 2.16-34.53, P = .002) and AHI (AOR 0.79, 95% CI 0.63-0.98, P = .032) were demonstrated to be predictive of the Patte stage of supraspinatus retraction. The acromial spur implied a higher risk of severe retraction although this finding was not statistically significant (AOR 2.89, 95% CI 0.90-9.29, P = .075). The presence of concurrent GT spur and narrow AHI was highly specific (sensitivity 27.3% / specificity 91.1%) for advanced supraspinatus retraction. Conclusion The presence of a radiographic GT spur, narrow AHI, and subacromial spur indicated advanced retraction of the supraspinatus tendon. When patients with clinical suspicion of rotator cuff tear present with combinations of these radiographic signs, a prompt MRI examination and a referral to a shoulder specialist are recommended.
Published: 2021

4. Harvested Energy Scavenging and Transfer capabilities in Opportunistic Ring Routing

Author: Sobia Baig, Yiyi Li, Bachirou Guene Lougou, Junaid Anees, Yabibal Getahun Dessie, and Hao-Chun Zhang
Subjects: Routing protocol, energy harvesting, General Computer Science, Clustering algorithms, Computer science, 02 engineering and technology, 01 natural sciences, ring routing, 0202 electrical engineering, electronic engineering, information engineering, Overhead (computing), General Materials Science, wireless sensor networks, Hierarchical routing, Network architecture, business.industry, Network packet, opportunistic routing, 010401 analytical chemistry, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, General Engineering, 020206 networking & telecommunications, Energy consumption, 0104 chemical sciences, TK1-9971, Energy conservation, Electrical engineering. Electronics. Nuclear engineering, business, Wireless sensor network, routing protocols, Computer network
Abstract: Energy conservation has always been a prominent design goal for hierarchical routing protocols supporting sink mobility. Advertising the current position of mobile sink introduces control packet overhead which ultimately results in an increase in energy consumption and shorter network lifetime. Energy harvesting through ambient sources have enabled the utilization of rechargeable devices for Wireless Sensor Networks to perpetually remain operational. The modifications in the hierarchical structure of wireless sensor networks along with energy scavenging approaches could possibly minimize the control packet overhead and also provide a significant improvement in energy conservation. In this paper, we propose a novel Harvested Energy Scavenging and Transfer capabilities in Opportunistic Ring Routing protocol which uses a distinguishing approach of hybrid (ring + cluster) topology in which the network architecture is initially supported by the formation of a virtual ring structure and then a two-tier routing topology is used in the virtual ring as an overlay by grouping nodes into clusters. The rate of energy gain from solar harvesting and radio frequency transfer is the criterion for selecting cluster heads. The role of cluster heads is exploited to advertise the mobile sink current position as well as forward the aggregated data towards mobile sink using energy transfer based opportunistic routing. The simulation results reveal that our scheme considerably outperforms the existing benchmarks in terms of control packet overhead, energy conservation, network lifetime, packet delivery ratio and average end-end delay.
Published: 2021

5. Quantification of petal patterns and colours of genus Sinningia (GESNERIACEAE)

Author: Tzu-Ting Hung, Yan-Fu Kuo, and Hao-Chun Hsu
Subjects: biology, Spots, business.industry, Soil Science, Pattern recognition, biology.organism_classification, Gesneriaceae, Control and Systems Engineering, Genus, Sinningia, Petal, Artificial intelligence, business, Agronomy and Crop Science, Food Science
Abstract: Plants belonging to genus Sinningia are popular ornamental plants with diverse petal patterns and fascinating petal colours. The patterns and colours of petals are crucial horticultural properties that determine a plant's commercial value. Generally, the patterns and colours of petals are evaluated by experienced horticulturalists. However, manual evaluation can be subjective and the decision criterion could fluctuate due to fatigue. This work proposed a method to automatically quantify the petal patterns and colours by investigating 11 species of Sinningia. The images of the ventral petal of flower specimens were captured using flatbed scanners. The regions of interest (ROI) were defined and segmented from ventral images. Subsequently, a fully convolutional network was applied to the ROI for automatically segmenting variegated parts (i.e., spots, strips, and plaques) from the background. The patterns and colours of petals were then analysed. The proposed method can be used for the automation of petal pattern rating, which generally is performed using naked-eye observations.
Published: 2020

6. Guillain–Barré syndrome in a heart transplantation recipient

Author: Hao-Chun Cheng, Chung-Yi Chang, Wei-Chun Liu, Heng-Hsin Tung, Nian-Chen Chiang, Ching-Wen Wei, Chin-Yu Liu, and Hsin-Huei Chang
Subjects: Heart transplantation, medicine.medical_specialty, Guillain-Barre syndrome, business.industry, medicine.medical_treatment, General Medicine, Disease, medicine.disease, Transplantation, Respiratory failure, Intervention (counseling), Epidemiology, medicine, Differential diagnosis, Intensive care medicine, business, General Nursing
Abstract: A rare case of a heart transplantation recipient with Guillain-Barre syndrome occurred, which was associated with peripheral nervous system damage. Based on a review of epidemiological research, the symptom development process, and diagnostic tools, the authors highlight the extreme rarity of this postinfectious immune disease. After diagnosis, plasma exchange and immunoregulatory therapy should be performed because they result in rapid recovery. If there is delayed diagnosis and treatment, there is a high risk of disability or death. When patients experience acute limb paralysis as the main symptom, nurse practitioners (NPs) should focus on the patient's history, particularly with regard to infectious agents. Closely monitoring the patient to detect respiratory failure and the need for early respiratory intervention can help the patient to avoid the severe complication of permanent brain injury. For NPs, performance of early differential diagnosis is important, especially among patients who have immunosuppressive dependence after transplantation.
Published: 2020

7. Cervical Tuberculosis Combined With Papillary Thyroid Carcinoma With Lateral Neck Metastasis

Author: Hao-Chun Hu and Hui-Yu Lin
Subjects: medicine.medical_specialty, Tuberculosis, business.industry, Extrapulmonary tuberculosis, medicine.disease, Lateral neck, Metastasis, Thyroid carcinoma, medicine.anatomical_structure, Otorhinolaryngology, Cervical lymph nodes, Medicine, Radiology, Head and neck, business
Abstract: Extrapulmonary tuberculosis in the head and neck region accounts for 10% of all tuberculosis cases. Cervical lymph nodes are the most common sites of head and neck tuberculosis and often mimics neck metastasis leading to overstaging and overtreatment. Fine needle aspiration has proven effective in diagnosing cervical tuberculosis. If a diagnosis of tuberculosis is confirmed, then the first-line treatment is oral antituberculosis medication.
Published: 2021

8. Optimized Manpower and Location Scheduling Query for Shop Promotion Based on Records of Bicycle Sharing System

Author: Hsin-Yu Chen, Yu-Hsiang Wang, Chung-Yu Yeh, Yi-Chung Chen, Hao-Chun Yang, and Yu-Rong Lin
Subjects: Estimation, Schedule, Operations research, Job shop scheduling, Computer science, business.industry, media_common.quotation_subject, Visitor pattern, Big data, Scheduling (computing), Promotion (rank), Key (cryptography), business, media_common
Abstract: With the increasing development of big data analytics, more and more researchers have started to apply related technologies to various business projects. However, so far most of these projects have only considered the data of the shop, such as daily visitor estimation or daily sales estimation. The substantial promotion of the shop and the scheduling of promotion manpower, however, remain topics that have rarely been discussed. Therefore, this study proposes a new query to discuss these two issues simultaneously. In this new query, we conduct the following steps: (1) Using the borrowed records of the bicycle sharing system for the location of the query shop, we find out what other locations are most frequently visited by people in the vicinity of the query shop, and consider these locations as key sources of customers; (2) Using NNs to predict the traffic at these key sources; (3) Using GA to find out how to schedule the staff to distribute flyers at these key sources if the shop needs to have such arrangement. The final experimental simulation verifies the effectiveness of the proposed method.
Published: 2021

9. Forecasting of Typhoon-Induced Wind-Wave by Using Convolutional Deep Learning on Fused Data of Remote Sensing and Ground Measurements

Author: Hao-Chun Chang and Chih-Chiang Wei
Subjects: Internationality, 010504 meteorology & atmospheric sciences, 020209 energy, radar mosaics, 02 engineering and technology, TP1-1185, 01 natural sciences, Biochemistry, Convolutional neural network, Wind speed, Article, Analytical Chemistry, Wind wave, Wave height, 0202 electrical engineering, electronic engineering, information engineering, Range (statistics), Electrical and Electronic Engineering, Instrumentation, 0105 earth and related environmental sciences, Remote sensing, Artificial neural network, business.industry, Cyclonic Storms, Deep learning, Chemical technology, Commerce, deep learning, neural networks, Atomic and Molecular Physics, and Optics, typhoon, Typhoon, Remote Sensing Technology, Artificial intelligence, business, wind speed, Geology, wave height
Abstract: Taiwan is an island, and its economic activities are primarily dependent on maritime transport and international trade. However, Taiwan is also located in the region of typhoon development in the Northwestern Pacific Basin. Thus, it frequently receives strong winds and large waves brought by typhoons, which pose a considerable threat to port operations. To determine the real-time status of winds and waves brought by typhoons near the coasts of major ports in Taiwan, this study developed models for predicting the wind speed and wave height near the coasts of ports during typhoon periods. The forecasting horizons range from 1 to 6 h. In this study, the gated recurrent unit (GRU) neural networks and convolutional neural networks (CNNs) were combined and adopted to formulate the typhoon-induced wind and wave height prediction models. This work designed two wind speed prediction models (WIND-1 and WIND-2) and four wave height prediction models (WAVE-1 to WAVE-4), which are based on the WIND-1 and WIND-2 model outcomes. The Longdong and Liuqiu Buoys were the experiment locations. The observatory data from the ground stations and buoys, as well as radar reflectivity images, were adopted. The results indicated that, first, WIND-2 has a superior wind speed prediction performance to WIND-1, where WIND-2 can be used to identify the temporal and spatial changes in wind speeds using ground station data and reflectivity images. Second, WAVE-4 has the optimal wave height prediction performance, followed by WAVE-3, WAVE-2, and WAVE-1. The results of WAVE-4 revealed using the designed models with in-situ and reflectivity data directly yielded optimal predictions of the wind-based wave heights. Overall, the results indicated that the presented combination models were able to extract the spatial image features using multiple convolutional and pooling layers and provide useful information from time-series data using the GRU memory cell units. Overall, the presented models could exhibit promising results.
Published: 2021
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10. Assessment of sagittal spinopelvic parameters in a Taiwanese population with spondylolysis by the EOS imaging system: a retrospective radiological analysis

Author: Wei Lun Chang, Cheng Li Lin, Pei Fang Su, Yu Hsiang Tseng, Yueh Chen, Po Hsin Chou, and Hao Chun Chuang
Subjects: Pelvic tilt, Adult, medicine.medical_specialty, Sports medicine, Radiography, Population, Spondylolysis, Diseases of the musculoskeletal system, Spinopelvic parameter, 03 medical and health sciences, 0302 clinical medicine, Rheumatology, Medicine, Humans, Orthopedics and Sports Medicine, education, Retrospective Studies, Orthodontics, 030222 orthopedics, education.field_of_study, Lumbar Vertebrae, business.industry, Research, Middle Aged, medicine.disease, Spondylolisthesis, Sagittal plane, medicine.anatomical_structure, RC925-935, Orthopedic surgery, Spinopelvic alignment, Lordosis, business, 030217 neurology & neurosurgery
Abstract: Background The impact of sagittal spinopelvic alignment on spondylolysis is well established in Caucasian populations. However, prior studies suggest that people from different ethnological backgrounds showed divergence, and a few studies that focused on Asian populations reported conflicting results. The aim of this study is to use the EOS imaging system to evaluate the spinopelvic parameters of spondylolysis patients, and their relationship with spondylolisthesis, disc degeneration, and age in a Taiwanese population. Methods Radiographic sagittal spinopelvic parameters for 45 spondylolysis patients and 32 healthy people were evaluated, including pelvic incidence (PI), sacral slope (SS), pelvic tilt (PT), thoracic kyphosis (TK), and lumbar lordosis (LL). The spinopelvic parameters were compared between spondylolytic and control groups. These parameters were further compared between spondylolytic subjects with and without spondylolisthesis, with and without high-grade disc degeneration, and young ( Results The PI and LL of the spondylolytic group (52.6°±12.0° and 41.3°±15.2°) were significantly higher than those of the healthy control group (47.16°±7.95° and 28.22°±10.65°). Further analysis of the spondylolytic patients revealed that those with high-grade disc degeneration were more prone to spondylolisthesis (92.3 %) compared to those without (50 %; p = 0.001). The middle-aged group had significantly higher rates of spondylolisthesis (80 %) and high-grade disc degeneration (52.4 %) compared with those for the young group (45 and 16.7 %, respectively; p = 0.017 and 0.047, respectively). No statistically significant difference in the sagittal spinopelvic parameters was found when spondylolytic patients were divided according to the occurrence of spondylolisthesis or high-grade disc degeneration. Conclusions In a Taiwanese population, PI and LL were significantly larger in spondylolytic patients. Disc degeneration and age were associated with the occurrence of spondylolisthesis. Ethnological differences should thus be taken into account when making clinical decisions regarding spondylolysis in a Taiwanese population.
Published: 2021

11. Deep Learning Application for Vocal Fold Disease Prediction Through Voice Recognition: Preliminary Development Study

Author: Hao Chun Hu, Tzu Pei Tsai, Chuen Heng Wang, Hsiao Yun Cho, Chang Jung Lu, Yi Ting Chen, Shyue Yih Chang, Kai Jun Li, and Oscar Kuang Sheng Lee
Subjects: pathological voice, Speech recognition, Computer applications to medicine. Medical informatics, R858-859.7, convolutional neural network, Health Informatics, Physical examination, Disease, Vocal Cords, Convolutional neural network, 03 medical and health sciences, 0302 clinical medicine, dysphonia, Deep Learning, Artificial Intelligence, Throat, medicine, Paralysis, otorhinolaryngologic diseases, Humans, Active listening, 030223 otorhinolaryngology, Nose, Original Paper, medicine.diagnostic_test, business.industry, Deep learning, medicine.anatomical_structure, Voice Recognition, 030220 oncology & carcinogenesis, voice pathology identification, Quality of Life, Artificial intelligence, medicine.symptom, Public aspects of medicine, RA1-1270, business, vocal fold disease
Abstract: BackgroundDysphonia influences the quality of life by interfering with communication. However, a laryngoscopic examination is expensive and not readily accessible in primary care units. Experienced laryngologists are required to achieve an accurate diagnosis.ObjectiveThis study sought to detect various vocal fold diseases through pathological voice recognition using artificial intelligence.MethodsWe collected 189 normal voice samples and 552 samples of individuals with voice disorders, including vocal atrophy (n=224), unilateral vocal paralysis (n=50), organic vocal fold lesions (n=248), and adductor spasmodic dysphonia (n=30). The 741 samples were divided into 2 sets: 593 samples as the training set and 148 samples as the testing set. A convolutional neural network approach was applied to train the model, and findings were compared with those of human specialists.ResultsThe convolutional neural network model achieved a sensitivity of 0.66, a specificity of 0.91, and an overall accuracy of 66.9% for distinguishing normal voice, vocal atrophy, unilateral vocal paralysis, organic vocal fold lesions, and adductor spasmodic dysphonia. Compared with the accuracy of human specialists, the overall accuracy rates were 60.1% and 56.1% for the 2 laryngologists and 51.4% and 43.2% for the 2 general ear, nose, and throat doctors.ConclusionsVoice alone could be used for common vocal fold disease recognition through a deep learning approach after training with our Mandarin pathological voice database. This approach involving artificial intelligence could be clinically useful for screening general vocal fold disease using the voice. The approach includes a quick survey and a general health examination. It can be applied during telemedicine in areas with primary care units lacking laryngoscopic abilities. It could support physicians when prescreening cases by allowing for invasive examinations to be performed only for cases involving problems with automatic recognition or listening and for professional analyses of other clinical examination results that reveal doubts about the presence of pathologies.
Published: 2021

12. Integrated transcriptomics explored the cancer-promoting genes CDKN3 in esophageal squamous cell cancer

Author: Juan Pu, Kai Liao, Yan Pan, Yanyan Liu, Hao Chun Guo, Wanpeng Wang, Suqin Zhou, and Ran Yu
Subjects: Male, Esophageal Neoplasms, Gene Expression, Transcriptome, 0302 clinical medicine, Esophageal squamous cell carcinoma (ESCC), Anesthesiology, Gene expression, Integrated transcriptomics, Databases, Genetic, Medicine, RD78.3-87.3, Protein Interaction Maps, Cyclin-Dependent Kinase Inhibitor Proteins, Aged, 80 and over, 0303 health sciences, Kinase, General Medicine, Middle Aged, Immunohistochemistry, 030220 oncology & carcinogenesis, Lymphatic Metastasis, Module mining, Dual-Specificity Phosphatases, Female, Esophageal Squamous Cell Carcinoma, Cardiology and Cardiovascular Medicine, Research Article, Pulmonary and Respiratory Medicine, Adult, RD1-811, Bioinformatics, 03 medical and health sciences, Esophagus, Biomarkers, Tumor, Humans, Clinical significance, RNA, Messenger, Gene, 030304 developmental biology, Aged, Neoplasm Staging, Messenger RNA, business.industry, Gene Expression Profiling, Computational Biology, Fold change, Cancer research, Surgery, business, Cyclin - dependent kinase inhibitor 3 (CDKN3)
Abstract: Background and objectives Each individual studies is limited to multi-factors and potentially lead to a significant difference of results among them. The present study aim to explore the critical genes related to the development of Esophageal squamous cell carcinoma (ESCC) by integrated transcriptomics and to investigate the clinical significance by experimental validation. Methods Datasets of protein-coding genes expression which involved in ESCC were downloaded from Gene Expression Omnibus (GEO) database. The “Robustrankaggreg” package in language was used for data integration, and the different expression genes (DEGs) were identified based the cut-off criteria as follows: adjust p-value x2 test. The P value of less than 0.05 was considered statistically significant. Results A total of 244 DEGs were identified by comparing gene expression patterns between ESCC patients and the controls based on integrating dataset of GSE77861, GSE77861, GSE100942, GSE26886, GSE17351, GSE38129, GSE33426, GSE20347 and GSE23400; The Cyclin-dependent kinase inhibitor 3 (CDKN3) were identified the top 1 seed gene of top cluster by use of protein-protein Interaction network and plug-in Molecular Complex Detection; The level of CDKN3 mRNA was significantly increased in ESCC patients compared to controls; The positive expression rate of CDKN3 protein in ESCC tissue samples was 32 and 61.4% in control, respectively. The correlations between the expression level of CDKN3 and lymph node metastasis or clinical staging of ESCC patients are statistically significant. Conclusion Integrated transcriptomics is an efficient approach to system biology. By this procedure, our study improved the understanding of the transcriptome status of ESCC.
Published: 2021

13. The radiographic morphology of the greater tuberosity is associated with muscle degeneration in patients with symptomatic rotator cuff tears

Author: Chih Kai Hong, Hao Chun Chuang, Kai Lan Hsu, Fa Chuan Kuan, Wei Ren Su, and Cheng Li Lin
Subjects: Adult, Male, Supraspinatus muscle, Shoulder surgery, medicine.medical_treatment, Infraspinatus muscle, Rotator Cuff Injuries, Arthroscopy, Rotator Cuff, 03 medical and health sciences, 0302 clinical medicine, Atrophy, medicine, Humans, Orthopedics and Sports Medicine, Rotator cuff, Postoperative Period, Aged, Retrospective Studies, 030222 orthopedics, Sclerosis, business.industry, 030229 sport sciences, General Medicine, Humerus, Middle Aged, musculoskeletal system, medicine.disease, Magnetic Resonance Imaging, Muscle atrophy, Muscular Atrophy, medicine.anatomical_structure, Adipose Tissue, Tears, Female, Surgery, medicine.symptom, Nuclear medicine, business, Greater Tuberosity
Abstract: Background Atrophy and fatty infiltration of the rotator cuff muscles portend poor findings in terms of postoperative function and the probability of retears. We assumed that sclerosis and spurs of the greater tuberosity (GT) on radiographs are associated with this rotator cuff muscle degeneration. Methods We retrospectively reviewed the preoperative radiographs and magnetic resonance (MR) images of 91 shoulders (average age of patients, 59.7 years; age range, 36-79 years) arthroscopically repaired between 2012 and 2016. The radiographic morphology of the GT was defined as normal, sclerotic, or spurring. Atrophy and fatty infiltration of the rotator cuff muscles were evaluated using the occupation ratio and Goutallier classification, respectively, via the MR images. Diagnoses of rotator cuff tears were made during arthroscopic shoulder surgery. Results Significant associations between the radiographic GT morphology and the severity of both supraspinatus muscle atrophy ( P = .002) and infraspinatus muscle atrophy ( P = .047) were found. The mean occupation ratios of both the sclerotic GT group and the spurring GT group were significantly reduced compared with the mean occupation ratio of the normal GT group. Patients with GT spurs were found to be prone to severe supraspinatus fatty degeneration ( P = .020). Conclusions For patients with rotator cuff tears, the presence of GT spurs or sclerosis on radiographs predicted the occurrence of supraspinatus and infraspinatus muscle atrophy, as well as supraspinatus fatty infiltration, based on MR images. The clinical relevance is that MR imaging is suggested for patients with radiographic GT sclerosis or spurs to detect advanced rotator cuff lesions.
Published: 2019

14. Office-Based Autologous Fat Injection Laryngoplasty for Glottic Insufficiency in Patients Under 50 Years Old

Author: Shu-Yi Lin, Hao-Chun Hu, Tao-Hsin Tung, Shyue-Yih Chang, and Yi-Ting Hung
Subjects: Adult, Male, medicine.medical_specialty, Transplantation, Autologous, Autologous Fat Injection, Laryngeal Diseases, Laryngoplasty, 030507 speech-language pathology & audiology, 03 medical and health sciences, Speech and Hearing, 0302 clinical medicine, Phonation, otorhinolaryngologic diseases, medicine, Humans, In patient, 030223 otorhinolaryngology, Retrospective Studies, Office based, business.industry, Maximum phonation time, Middle Aged, LPN and LVN, Voice assessment, Surgery, Treatment Outcome, Adipose Tissue, Otorhinolaryngology, Female, Voice handicap, 0305 other medical science, business, Neurological problems
Abstract: Summary Objective We sought to determine the outcomes of office-based autologous fat injection laryngoplasty in the treatment of patients under 50 years old with glottic insufficiency but without neurological problems or acquired organic lesions in the vocal fold. Methods We conducted a retrospective chart review of consecutive patients under 50 years of age who underwent office-based autologous fat injection laryngoplasty for glottic insufficiency. None of the patients presented neurological problems or acquired organic lesions in the vocal fold. Videolaryngostroboscopic data, objective voice assessment, perceptual measurements of vocal quality, and subjective ratings of voice quality were evaluated before and after treatment. Results The 23 patients (7 men and 16 women) in this study presented significant improvements in phonatory function in terms of maximum phonation time, jitter, grade, asthenia, and Voice Handicap Index-10 (VHI-10) values at 3 months. Significant improvements in terms of jitter, noise-to-harmonic ratio, grade, roughness, breathiness, asthenia, and the VHI-10 values were also observed at 6 months. Conclusions Glottic insufficiency in younger patients without neurological problems or acquired organic lesions in the vocal fold can be treated effectively using office-based autologous fat injection laryngoplasty. Significant improvements in phonatory function were observed even 6 months after surgery.
Published: 2019

15. Differentiating between morphologically similar species in genus Cinnamomum (Lauraceae) using deep convolutional neural networks

Author: Yan-Fu Kuo, Hao-Wen Yang, Ming-Jer Tsai, Hao-Chun Hsu, and Chih-Kai Yang
Subjects: 0106 biological sciences, biology, business.industry, Cinnamomum osmophloeum, Forestry, Pattern recognition, 04 agricultural and veterinary sciences, Lauraceae, Horticulture, biology.organism_classification, 01 natural sciences, Convolutional neural network, Computer Science Applications, Support vector machine, Score fusion, Genus, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Artificial intelligence, Forest industry, business, Agronomy and Crop Science, 010606 plant biology & botany, Mathematics, Cinnamomum
Abstract: Plant adulteration is a rising problem in the forest industry. Cinnamomum osmophloeum Kanehira (Lauraceae) is an evergreen plant that yields cinnamaldehyde. Although two other species—C. burmannii (Nees & T. Nees) Blume and C. insularimontanum Hayata— morphologically resemble C. osmophloeum, they produce a minimum amount of cinnamaldehyde, and thus have lower economical values. The adulteration of C. osmophloeum using C. burmannii has been reported. However, even for experts, differentiating between the three species on the basis of their appearance is challenging due to their high degree of similarity in appearance. This study proposed to identify the three Cinnamomum species using leaf images and deep convolutional neural networks (CNN). In this study, leaf images of the three species were acquired using flatbed scanners. Leaf patches around the blade center of the leaves were extracted. Classifiers based on deep CNN models, VGG16, Inception-V3, and NASNet, were then developed using the leaf images or patches as inputs. Score fusion was then applied to improve the performance of the developed CNN classifiers. The fused CNN classifiers reached a test accuracy as high as 96.7%. A performance comparison indicated that three developed deep CNN classifiers outperformed support vector machine classifiers.
Published: 2019

16. Evolution of impedance values in two different electrode array designs following activation of cochlear implants 1 day after surgery: A study of 58 patients

Author: Joshua Kuang-Chao Chen, Mei-Jui Huang, Li‐Ching Chen, Tao-Hsin Tung, Chia‐Hsin Yeh, William Kuan-Hua Chen, Lieber Po-Hung Li, and Hao-Chun Hu
Subjects: Adult, Aged, 80 and over, Male, Adolescent, business.industry, Taiwan, Infant, Middle Aged, Prosthesis Design, Cochlear Implantation, Electrodes, Implanted, Cochlear Implants, Otorhinolaryngology, Child, Preschool, Electric Impedance, Electrode array, Humans, Medicine, Female, Child, business, Electrical impedance, Aged, Retrospective Studies, Biomedical engineering
Published: 2019

17. Targeting allosteric site of AKT by 5,7-dimethoxy-1,4-phenanthrenequinone suppresses neutrophilic inflammation

Author: Fang Rong Chang, Chih-Ching Wu, Po-Jen Chen, Hao-Chun Hu, Tsong-Long Hwang, Chang-Yu Pan, Cheng-Yu Lin, Yann-Lii Leu, I-Ling Ko, Yung-Fong Tsai, Yang Chang Wu, and Chia Lin Lee
Subjects: MAPK/ERK pathway, Models, Molecular, 0301 basic medicine, Research paper, Lipopolysaccharide, Neutrophils, p38 mitogen-activated protein kinases, Anti-Inflammatory Agents, Molecular Conformation, HL-60 Cells, Inflammation, Pharmacology, Lung injury, General Biochemistry, Genetics and Molecular Biology, chemistry.chemical_compound, Structure-Activity Relationship, 03 medical and health sciences, 0302 clinical medicine, Acute lung injury, Cell Adhesion, medicine, Humans, Protein Interaction Domains and Motifs, Protein kinase B, business.industry, Chemistry, AKT, Neutrophil, Quinones, Degranulation, Chemotaxis, 5,7-dimethoxy-1,4-phenanthrenequinone, General Medicine, Phenanthrenes, Respiratory burst, Chemotaxis, Leukocyte, 030104 developmental biology, Neutrophil Infiltration, 030220 oncology & carcinogenesis, Cancer research, Phosphorylation, medicine.symptom, business, Reactive Oxygen Species, Proto-Oncogene Proteins c-akt, Allosteric Site, Protein Binding
Abstract: Background: Acute lung injury (ALI) is a severe life-threatening inflammatory disease. Neutrophil activation is a major pathogenic factor in ALI. Protein kinase B (PKB)/AKT regulates diverse cellular responses, but the significance in neutrophilic inflammation and ALI remains unknown. Methods: Human neutrophils and neutrophil-like differentiated HL-60 (dHL-60) cells were used to examine the anti-inflammatory effects of 5,7-dimethoxy-1,4-phenanthrenequinone (CLLV-1). The therapeutic potential of CLLV-1 was determined in a mouse model of lipopolysaccharide (LPS)-induced ALI. Findings: CLLV-1 inhibited respiratory burst, degranulation, adhesion, and chemotaxis in human neutrophils and dHL-60 cells. CLLV-1 inhibited the phosphorylation of AKT (Thr308 and Ser473), but not of ERK, JNK, or p38. Furthermore, CLLV-1 blocked AKT activity and covalently reacted with AKT Cys310 in vitro. The AKT309-313 peptide-CLLV-1 adducts were determined by NMR or mass spectrometry assay. The alkylation agent-conjugated AKT (reduced form) level was also inhibited by CLLV-1. Significantly, CLLV-1 ameliorated LPS-induced ALI, neutrophil infiltration, and AKT activation in mice. Interpretation: Our results identify CLLV-1 as a covalent allosteric AKT inhibitor by targeting AKT Cys310. CLLV-1 shows potent anti-inflammatory activity in human neutrophils and LPS-induced mouse ALI. Our findings provide a mechanistic framework for redox modification of AKT that may serve as a novel pharmacological target to alleviate neutrophilic inflammation. Funding Statement: This research was financial supported by the grants from the Ministry of Science Technology (MOST 106-2320-B-255-003-MY3 and MOST 104-2320-B-255-004-MY3), Ministry of Education (EMRPD1G0231 and EMRPD1H0381), and Chang Gung Memorial Hospital (CMRPF1F0011~3, CMRPF1F0061~3, CMRPF1G0241~3, and BMRP450), Taiwan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Declaration of Interests: The authors declare that no competing interests exist. Ethics Approval Statement: The procedure of neutrophil isolation was approved by the Institutional Review Board at Chang Gung Memorial Hospital. ALI was induced by intra-tracheal spray of 2 mg/kg LPS (Escherichia coli 0111:B4) in seven to eight weeks old C57BL/6 male mice, according to the guidelines and approved by Institutional Animal Care and Use Committee of Chang Gung University, Taiwan.
Published: 2019

18. Improvements in primary frequency regulation of the grid‐connected variable speed wind turbine

Author: Hao-Chun Zhang, Xintong Ma, Said I. Abouzeid, and Yufeng Guo
Subjects: Wind power, Renewable Energy, Sustainability and the Environment, Computer science, business.industry, 020209 energy, 020208 electrical & electronic engineering, Automatic frequency control, 02 engineering and technology, Fuzzy control system, Frequency deviation, Turbine, Variable speed wind turbine, Electric power system, Control theory, 0202 electrical engineering, electronic engineering, information engineering, Voltage droop, business
Abstract: Primary frequency regulation capability of the wind turbine generators is an appealing topic in order to consider safe increasing of the wind power integration into power grids. This study introduces improvements in the primary frequency contribution of the grid-connected variable speed wind turbine generators, which operate under de-loaded conditions. A new dynamic droop control approach based on the fuzzy logic system is proposed. In this control approach, the droop setting is continuously adjusted in response to the de-loaded rotor speed, the frequency deviation, and the rate of change of frequency. In addition, a new dynamic de-loading technique based on the Sugeno-Fuzzy inference system is proposed where the de-loading percentage of the wind turbine generator is decided continuously according to the frequency deviation. The effectiveness of the proposed dynamic de-loading and dynamic droop control approaches is verified through extensive comparative studies. The simulation results confirmed that the proposed control approaches have the ability to provide transient and steady-state power-sharing and improve effectively the frequency stabilisation of the power system within the stable and secure limits of the wind turbine.
Published: 2019

19. Microanalysis Using Acoustically Actuated Droplets Pinned Onto a Thread

Author: Tzu-Hsien Yang, Pawel L. Urban, Gurpur Rakesh D. Prabhu, Hao-Chun Yang, and Cheng-Hao Chang
Subjects: enzyme assay, Materials science, open-source electronics, General Computer Science, Spectrometer, business.industry, General Engineering, Acoustic levitation, Thread (computing), Sound intensity, Physics::Fluid Dynamics, Optics, Reagent, Light beam, microdroplet assay, General Materials Science, lcsh:Electrical engineering. Electronics. Nuclear engineering, business, lcsh:TK1-9971, Excitation, Microscale chemistry, automation
Abstract: An acoustic wave-assisted microscale assay platform is demonstrated. Liquid droplets containing samples and reagents are dispensed and pinned onto a hydrophobic thread, and actuated by sound waves. The transport of droplets is achieved by modulating sound emitted by two sources. The resulting sound intensity gradient pushes the droplets in one direction. The available distance of droplet actuation is related to droplet size. The moving droplets merge at the end of their actuation range, and the merged droplet travels further due to its greater size. Fluorometric analysis of the merged droplet is accomplished by positioning an excitation light source above a defined interrogation zone along the thread. The emitted light is analyzed by a miniature spectrometer positioned orthogonally to the excitation light beam. The sound sources and detection system are controlled by universal electronic modules (Raspberry Pi, Arduino). The system is operated automatically with the aid of a custom-developed graphical user interface. Here, we demonstrate its application in enzyme assays (trypsin, β-galactosidase). In-droplet enzymatic reaction progress curves are readily obtained. The actuated droplets can be put in motion and stopped without a significant delay. Only microliter-range volumes of sample and reagent are consumed in every analysis, while sub-milliliter volumes of chemical waste are produced.
Published: 2019

20. Identifying Fagaceae and Lauraceae species using leaf images and convolutional neural networks

Author: Chih-Kai Yang, Ming-Jer Tsai, Hao-Chun Hsu, Tsan-Yu Wu, Yan-Fu Kuo, and Kuan-Ting Yeh
Subjects: Ecology, business.industry, Applied Mathematics, Ecological Modeling, Pattern recognition, Lauraceae, Biology, biology.organism_classification, Convolutional neural network, Computer Science Applications, Fagaceae, Computational Theory and Mathematics, Similarity (network science), Modeling and Simulation, Artificial intelligence, Pruning algorithm, business, Ecology, Evolution, Behavior and Systematics, Woody plant
Abstract: Lauraceae and Fagaceae are two large woody plant families that are predominant in the low- and middle-altitude regions in Taiwan. The highly interspecific similarity between some species of the family brings limitations on the management and utilization. This work proposed an approach for identifying 15 Lauraceae species and 20 Fagaceae species using leaf images and convolutional neural networks (CNNs). Leaf specimens of 35 species were collected from the northern, central, and southern parts of Taiwan. Images of the leaves were acquired using flat-bed scanners. Three CNN architectures—DenseNet-121, MobileNet V2, and Xception—were trained. Xception achieved the highest mean test accuracy of 99.39%, and MobileNet V2 required the shortest mean test time of 17.1 ms per image using a GPU. The saliency maps revealed that the characteristics learned by models matched the leaf features used by botanists. A pruning algorithm, gate decorator, was applied to the trained models for reducing the number of parameters and number of floating-point operations of the MobileNet V2 by 55.4% and 69.1%, respectively, while the model accuracy was maintained at 92.03%. Thus, MobileNet V2 has the potential to be used for identifying the Lauraceae and Fagaceae species on mobile devices.
Published: 2022

21. Tocilizumab in Treatment for Patients With COVID-19

Author: Jean François Rossi, Hao Chun Chiang, and Bernard Klein
Subjects: 2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), SARS-CoV-2, business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), MEDLINE, Antibodies, Monoclonal, Humanized, Virology, COVID-19 Drug Treatment, chemistry.chemical_compound, Tocilizumab, chemistry, Internal Medicine, Humans, Medicine, business
Published: 2021

22. Fracture of the inferior pole of the patella: tension band wiring versus transosseous reattachment

Author: Fa-Chuan Kuan, Hao Chun Chuang, Chih Hsun Chang, Kai Lan Hsu, Chih-Kai Hong, and Wei Ren Su
Subjects: Adult, Male, Patellar fracture, Transosseous reattachment, medicine.medical_specialty, Diseases of the musculoskeletal system, 03 medical and health sciences, Fracture Fixation, Internal, Fractures, Bone, 0302 clinical medicine, Tension band wire, Risk Factors, Medicine, Humans, Orthopedics and Sports Medicine, 030212 general & internal medicine, Risk factor, Fixation (histology), Retrospective Studies, Orthopedic surgery, Inferior pole, 030222 orthopedics, business.industry, Tension band wiring, Retrospective cohort study, Patella, Middle Aged, medicine.disease, Surgery, Radiography, RC925-935, Radiological weapon, Female, Patella fracture, business, RD701-811, Bone Wires, Research Article
Abstract: Background The optimal surgical technique for the fixation of inferior pole patellar fracture remains controversial. The aims of this study were (1) to compare clinical and radiological outcomes following fixation of inferior pole patellar fracture by using tension band wire (TBW) and transosseous reattachment (TOR) without excision of the bony fragment and (2) to determine the risk factors for postoperative radiological loss of reduction. Methods For this retrospective cohort study, consecutive patients with inferior pole patellar fracture between January 2010 and December 2017 were recruited. The patients were grouped according to their fixation method (TBW or TOR), and demographic data, clinical outcomes, and postoperative Insall–Salvati (IS) ratio were analyzed. Then, the patients were grouped according to radiological loss of reduction, the possible risk factors for loss of reduction were identified, and odds ratios were calculated. Result This study included 55 patients with inferior pole patellar fracture; 30 patients were treated using TBW and 25 were treated using TOR. Clinical failure occurred in two patients in the TBW group (7%) and three in the TOR group (12%). The rate of radiological loss of reduction was significant higher in the TOR group, whereas removal of implants was significantly more common in the TBW group. Patella baja was noted immediately after surgery in the TOR group, but the IS ratios of the two groups were similar after 3 months. Fracture displacement of more than 30 mm was the only independent risk factor for postoperative radiological loss of reduction. Conclusion For treating inferior pole patellar fracture, both TWB and TOR were effective and had a low clinical failure rate. In 60% of patients undergoing TBW fixation, however, additional surgery was required to remove the implants. Patella baja occurred immediately following TOR, but the patellar height was similar to that in the TBW group after 3 months. Surgeons should be aware of the high risk of postoperative radiological loss of reduction, especially when the fracture displacement is more than 30 mm.
Published: 2021

23. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition) 1

Author: Klionsky, Daniel, Abdel-Aziz, Amal Kamal, Abdelfatah, Sara, Abdellatif, Mahmoud, Abdoli, Asghar, Abel, Steffen, Abeliovich, Hagai, Abildgaard, Marie, Abudu, Yakubu Princely, Acevedo-Arozena, Abraham, Adamopoulos, Iannis, Adeli, Khosrow, Adolph, Timon, Adornetto, Annagrazia, Aflaki, Elma, Agam, Galila, Agarwal, Anupam, Aggarwal, Bharat, Agnello, Maria, Agostinis, Patrizia, Agrewala, Javed, Agrotis, Alexander, Aguilar, Patricia, Ahmad, S Tariq, Ahmed, Zubair, Ahumada-Castro, Ulises, Aits, Sonja, Aizawa, Shu, Akkoc, Yunus, Akoumianaki, Tonia, Akpinar, Hafize Aysin, Al-Abd, Ahmed, Al-Akra, Lina, Al-Gharaibeh, Abeer, Alaoui-Jamali, Moulay, Alberti, Simon, Alcocer-Gómez, Elísabet, Alessandri, Cristiano, Ali, Muhammad, Alim Al-Bari, M Abdul, Aliwaini, Saeb, Alizadeh, Javad, Almacellas, Eugènia, Almasan, Alexandru, Alonso, Alicia, Alonso, Guillermo, Altan-Bonnet, Nihal, Altieri, Dario, Álvarez, Élida, Alves, Sara, Alves Da Costa, Cristine, Alzaharna, Mazen, Amadio, Marialaura, Amantini, Consuelo, Amaral, Cristina, Ambrosio, Susanna, Amer, Amal, Ammanathan, Veena, An, Zhenyi, Andersen, Stig, Andrabi, Shaida, Andrade-Silva, Magaiver, Andres, Allen, Angelini, Sabrina, Ann, David, Anozie, Uche, Ansari, Mohammad, Antas, Pedro, Antebi, Adam, Antón, Zuriñe, Anwar, Tahira, Apetoh, Lionel, Apostolova, Nadezda, Araki, Toshiyuki, Araki, Yasuhiro, Arasaki, Kohei, Araújo, Wagner, Araya, Jun, Arden, Catherine, Arévalo, Maria-Angeles, Arguelles, Sandro, Arias, Esperanza, Arikkath, Jyothi, Arimoto, Hirokazu, Ariosa, Aileen, Armstrong-James, Darius, Arnauné-Pelloquin, Laetitia, Aroca, Angeles, Arroyo, Daniela, Arsov, Ivica, Artero, Rubén, Asaro, Dalia Maria Lucia, Aschner, Michael, Ashrafizadeh, Milad, Ashur-Fabian, Osnat, Atanasov, Atanas, Au, Alicia, Auberger, Patrick, Auner, Holger, Aurelian, Laure, Autelli, Riccardo, Avagliano, Laura, Ávalos, Yenniffer, Aveic, Sanja, Aveleira, Célia Alexandra, Avin-Wittenberg, Tamar, Aydin, Yucel, Ayton, Scott, Ayyadevara, Srinivas, Azzopardi, Maria, Baba, Misuzu, Backer, Jonathan, Backues, Steven, Bae, Dong-Hun, Bae, Ok-Nam, Bae, Soo Han, Baehrecke, Eric, Baek, Ahruem, Baek, Seung-Hoon, Baek, Sung Hee, Bagetta, Giacinto, Bagniewska-Zadworna, Agnieszka, Bai, Hua, Bai, Jie, Bai, Xiyuan, Bai, Yidong, Bairagi, Nandadulal, Baksi, Shounak, Balbi, Teresa, Baldari, Cosima, Balduini, Walter, Ballabio, Andrea, Ballester, Maria, Balazadeh, Salma, Balzan, Rena, Bandopadhyay, Rina, Banerjee, Sreeparna, Banerjee, Sulagna, Bánréti, Ágnes, Bao, Yan, Baptista, Mauricio, Baracca, Alessandra, Barbati, Cristiana, Bargiela, Ariadna, Barilà, Daniela, Barlow, Peter, Barmada, Sami, Barreiro, Esther, Barreto, George, Bartek, Jiri, Bartel, Bonnie, Bartolome, Alberto, Barve, Gaurav, Basagoudanavar, Suresh, Bassham, Diane, Bast, Robert, Basu, Alakananda, Batoko, Henri, Batten, Isabella, Baulieu, Etienne, Baumgarner, Bradley, Bayry, Jagadeesh, Beale, Rupert, Beau, Isabelle, Beaumatin, Florian, Bechara, Luiz, Beck, George, Beers, Michael, Begun, Jakob, Behrends, Christian, Behrens, Georg, Bei, Roberto, Bejarano, Eloy, Bel, Shai, Behl, Christian, Belaid, Amine, Belgareh-Touzé, Naïma, Bellarosa, Cristina, Belleudi, Francesca, Belló Pérez, Melissa, Bello-Morales, Raquel, Beltran, Jackeline Soares de Oliveira, Beltran, Sebastián, Benbrook, Doris Mangiaracina, Bendorius, Mykolas, Benitez, Bruno, Benito-Cuesta, Irene, Bensalem, Julien, Berchtold, Martin, Berezowska, Sabina, Bergamaschi, Daniele, Bergami, Matteo, Bergmann, Andreas, Berliocchi, Laura, Berlioz-Torrent, Clarisse, Bernard, Amélie, Berthoux, Lionel, Besirli, Cagri, Besteiro, Sebastien, Betin, Virginie, Beyaert, Rudi, Bezbradica, Jelena, Bhaskar, Kiran, Bhatia-Kissova, Ingrid, Bhattacharya, Resham, Bhattacharya, Sujoy, Bhattacharyya, Shalmoli, Bhuiyan, Md Shenuarin, Bhutia, Sujit Kumar, Bi, Lanrong, Bi, Xiaolin, Biden, Trevor, Bijian, Krikor, Billes, Viktor, Binart, Nadine, Bincoletto, Claudia, Birgisdottir, Asa, Bjorkoy, Geir, Blanco, Gonzalo, Blas-Garcia, Ana, Blasiak, Janusz, Blomgran, Robert, Blomgren, Klas, Blum, Janice, Boada-Romero, Emilio, Boban, Mirta, Boesze-Battaglia, Kathleen, Boeuf, Philippe, Boland, Barry, Bomont, Pascale, Bonaldo, Paolo, Bonam, Srinivasa Reddy, Bonfili, Laura, Bonifacino, Juan, Boone, Brian, Bootman, Martin, Bordi, Matteo, Borner, Christoph, Bornhauser, Beat, Borthakur, Gautam, Bosch, Jürgen, Bose, Santanu, botana, luis, Botas, Juan, Boulanger, Chantal, Boulton, Michael, Bourdenx, Mathieu, Bourgeois, Benjamin, Bourke, Nollaig, Bousquet, Guilhem, Boya, Patricia, Bozhkov, Peter, Bozi, Luiz, Bozkurt, Tolga, Brackney, Doug, Brandts, Christian, Braun, Ralf, Braus, Gerhard, Bravo-Sagua, Roberto, Bravo-San Pedro, José, Brest, Patrick, Bringer, Marie-Agnès, Briones-Herrera, Alfredo, Broaddus, V Courtney, Brodersen, Peter, Brodsky, Jeffrey, Brody, Steven, Bronson, Paola, Bronstein, Jeff, Brown, Carolyn, Brown, Rhoderick, Brum, Patricia, Brumell, John, Brunetti-Pierri, Nicola, Bruno, Daniele, Bryson-Richardson, Robert, Bucci, Cecilia, Buchrieser, Carmen, Bueno, Marta, Buitrago-Molina, Laura Elisa, Buraschi, Simone, Buch, Shilpa, Buchan, J Ross, Buckingham, Erin, Budak, Hikmet, Budini, Mauricio, Bultynck, Geert, Burada, Florin, Burgoyne, Joseph, Burón, M Isabel, Bustos, Victor, Büttner, Sabrina, Butturini, Elena, Byrd, Aaron, Cabas, Isabel, Cabrera-Benitez, Sandra, Cadwell, Ken, Cai, Jingjing, Cai, Lu, Cai, Qian, Cairó, Montserrat, Calbet, Jose, Caldwell, Guy, Caldwell, Kim, Call, Jarrod, Calvani, Riccardo, Calvo, Ana, Calvo-Rubio Barrera, Miguel, Camara, Niels OS, Camonis, Jacques, Camougrand, Nadine, Campanella, Michelangelo, Campbell, Edward, Campbell-Valois, François-Xavier, Campello, Silvia, Campesi, Ilaria, Campos, Juliane, Camuzard, Olivier, Cancino, Jorge, Candido de Almeida, Danilo, Canesi, Laura, Caniggia, Isabella, Canonico, Barbara, Cantí, Carles, Cao, Bin, Caraglia, Michele, Caramés, Beatriz, Carchman, Evie, Cardenal-Muñoz, Elena, Cardenas, Cesar, Cardenas, Luis, Cardoso, Sandra, Carew, Jennifer, Carle, Georges, Carleton, Gillian, Carloni, Silvia, Carmona-Gutierrez, Didac, Carneiro, Leticia, Carnevali, Oliana, Carosi, Julian, Carra, Serena, Carrier, Alice, Carrier, Lucie, Carroll, Bernadette, Carter, A Brent, Carvalho, Andreia Neves, Casanova, Magali, Casas, Caty, Casas, Josefina, Cassioli, Chiara, Castillo, Eliseo, Castillo, Karen, Castillo-Lluva, Sonia, Castoldi, Francesca, Castori, Marco, Castro, Ariel, Castro-Caldas, Margarida, Castro-Hernandez, Javier, Castro-Obregon, Susana, Catz, Sergio, Cavadas, Claudia, Cavaliere, Federica, Cavallini, Gabriella, Cavinato, Maria, Cayuela, Maria, Cebollada Rica, Paula, Cecarini, Valentina, Cecconi, Francesco, Cechowska-Pasko, Marzanna, Cenci, Simone, Ceperuelo-Mallafré, Victòria, Cerqueira, João, Cerutti, Janete, Cervia, Davide, Cetintas, Vildan Bozok, Cetrullo, Silvia, Chae, Han-Jung, Chagin, Andrei, Chai, Chee-Yin, Chakrabarti, Gopal, Chakrabarti, Oishee, Chakraborty, Tapas, Chakraborty, Trinad, Chami, mounia, Chamilos, Georgios, Chan, David, Chan, Edmond, Chan, Edward, Chan, H.Y. Edwin, Chan, Helen, Chan, Hung, Chan, Matthew, Chan, Yau Sang, Chandra, Partha, Chang, Chih-Peng, Chang, Chunmei, Chang, Hao-Chun, Chang, Kai, Chao, Jie, Chapman, Tracey, Charlet-Berguerand, Nicolas, Chatterjee, Samrat, Chaube, Shail, Chaudhary, Anu, Chauhan, Santosh, Chaum, Edward, Checler, Frédéric, Cheetham, Michael, Chen, Chang-Shi, Chen, Guang-Chao, Chen, Jian-Fu, Chen, Liam, Chen, Leilei, Chen, Lin, Chen, Mingliang, Chen, Mu-Kuan, Chen, Ning, Chen, Quan, Chen, Ruey-Hwa, Chen, Shi, Chen, Wei, Chen, Weiqiang, Chen, Xin-Ming, Chen, Xiong-Wen, Chen, Xu, Chen, Yan, Chen, Ye-Guang, Chen, Yingyu, Chen, Yongqiang, Chen, Yu-Jen, Chen, Yue-Qin, Chen, Zhefan Stephen, Chen, Zhi, Chen, Zhi-Hua, Chen, Zhijian, Chen, Zhixiang, Cheng, Hanhua, Cheng, Jun, Cheng, Shi-Yuan, Cheng, Wei, Cheng, Xiaodong, Cheng, Xiu-Tang, Cheng, Yiyun, Cheng, Zhiyong, Chen, Zhong, Cheong, Heesun, Cheong, Jit Kong, Chernyak, Boris, Cherry, Sara, Cheung, Chi Fai Randy, Cheung, Chun Hei Antonio, Cheung, King-Ho, Chevet, Eric, Chi, Richard, Chiang, Alan Kwok Shing, Chiaradonna, Ferdinando, Chiarelli, Roberto, Chiariello, Mario, Chica, Nathalia, Chiocca, Susanna, Chiong, Mario, Chiou, Shih-Hwa, Chiramel, Abhilash, Chiurchiù, Valerio, Cho, Dong-Hyung, Choe, Seong-Kyu, Choi, Augustine, Choi, Mary, Choudhury, Kamalika Roy, Chow, Norman, Chu, Charleen, Chua, Jason, Chua, John Jia En, Chung, Hyewon, Chung, Kin Pan, Chung, Seockhoon, Chung, So-Hyang, Chung, Yuen-Li, Cianfanelli, Valentina, Ciechomska, Iwona, Cifuentes, Mariana, Cinque, Laura, Cirak, Sebahattin, Cirone, Mara, Clague, Michael, Clarke, Robert, Clementi, Emilio, Coccia, Eliana, Codogno, Patrice, Cohen, Ehud, Cohen, Mickael, Colasanti, Tania, Colasuonno, Fiorella, Colbert, Robert, Colell, Anna, Čolić, Miodrag, Coll, Nuria, Collins, Mark, Colombo, María, Colón-Ramos, Daniel, Combaret, Lydie, Comincini, Sergio, Cominetti, Márcia, Consiglio, Antonella, Conte, Andrea, Conti, Fabrizio, Contu, Viorica Raluca, Cookson, Mark, Coombs, Kevin, Coppens, Isabelle, Corasaniti, Maria Tiziana, Corkery, Dale, Cordes, Nils, Cortese, Katia, Costa, Maria do Carmo, Costantino, Sarah, Costelli, Paola, Coto-Montes, Ana, Crack, Peter, Crespo, Jose, Criollo, Alfredo, Crippa, Valeria, Cristofani, Riccardo, Csizmadia, Tamas, Cuadrado, Antonio, Cui, Bing, Cui, Jun, Cui, Yixian, Cui, Yong, Culetto, Emmanuel, Cumino, Andrea, Cybulsky, Andrey, Czaja, Mark, Czuczwar, Stanislaw, D'Adamo, Stefania, D'Amelio, Marcello, D'Arcangelo, Daniela, D'Lugos, Andrew, D'Orazi, Gabriella, da Silva, James, Dafsari, Hormos Salimi, Dagda, Ruben, Dagdas, Yasin, Daglia, Maria, Dai, Xiaoxia, Dai, Yun, Dai, Yuyuan, Dal Col, Jessica, Dalhaimer, Paul, Dalla Valle, Luisa, Dallenga, Tobias, Dalmasso, Guillaume, Damme, Markus, Dando, Ilaria, Dantuma, Nico, Darling, April, Das, Hiranmoy, Dasarathy, Srinivasan, Dasari, Santosh, Dash, Srikanta, Daumke, Oliver, Dauphinee, Adrian, Davies, Jeffrey, Dávila, Valeria, Davis, Roger, Davis, Tanja, Dayalan Naidu, Sharadha, De Amicis, Francesca, De Bosscher, Karolien, De Felice, Francesca, De Franceschi, Lucia, De Leonibus, Chiara, de Mattos Barbosa, Mayara, De Meyer, Guido, De Milito, Angelo, De Nunzio, Cosimo, De Palma, Clara, De Santi, Mauro, De Virgilio, Claudio, De Zio, Daniela, Debnath, Jayanta, DeBosch, Brian, Decuypere, Jean-Paul, Deehan, Mark, Deflorian, Gianluca, DeGregori, James, Dehay, Benjamin, Del Rio, Gabriel, Delaney, Joe, Delbridge, Lea, Delorme-Axford, Elizabeth, Delpino, M Victoria, Demarchi, Francesca, Dembitz, Vilma, Demers, Nicholas, Deng, Hongbin, Deng, Zhiqiang, Dengjel, Joern, Dent, Paul, Denton, Donna, DePamphilis, Melvin, Der, Channing, Deretic, Vojo, Descoteaux, Albert, Devis, Laura, Devkota, Sushil, Devuyst, Olivier, Dewson, Grant, Dharmasivam, Mahendiran, Dhiman, Rohan, di Bernardo, Diego, Di Cristina, Manlio, Di Domenico, Fabio, Di Fazio, Pietro, Di Fonzo, Alessio, Di Guardo, Giovanni, Di Guglielmo, Gianni, Di Leo, Luca, Di Malta, Chiara, Di Nardo, Alessia, Di Rienzo, Martina, Di Sano, Federica, Diallinas, George, Diao, Jiajie, Diaz-Araya, Guillermo, Díaz-Laviada, Inés, Dickinson, Jared, Diederich, Marc, Dieudé, Mélanie, Dikic, Ivan, Ding, Shiping, Ding, Wen-Xing, Dini, Luciana, Dinić, Jelena, Dinic, Miroslav, Dinkova-Kostova, Albena, Dionne, Marc, Distler, Jörg, Diwan, Abhinav, Dixon, Ian, Djavaheri-Mergny, Mojgan, Dobrinski, Ina, Dobrovinskaya, Oxana, Dobrowolski, Radek, Dobson, Renwick, Đokić, Jelena, Dokmeci Emre, Serap, Donadelli, Massimo, Dong, Bo, Dong, Xiaonan, Dong, Zhiwu, Dorn Ii, Gerald, Dotsch, Volker, Dou, Huan, Dou, Juan, Dowaidar, Moataz, Dridi, Sami, Drucker, Liat, Du, Ailian, Du, Caigan, Du, Guangwei, Du, Hai-Ning, Du, Li-Lin, du Toit, André, Duan, Shao-Bin, Duan, Xiaoqiong, Duarte, Sónia, Dubrovska, Anna, Dunlop, Elaine, Dupont, Nicolas, Durán, Raúl, Dwarakanath, Bilikere, Dyshlovoy, Sergey, Ebrahimi-Fakhari, Darius, Eckhart, Leopold, Edelstein, Charles, Efferth, Thomas, Eftekharpour, Eftekhar, Eichinger, Ludwig, Eid, Nabil, Eisenberg, Tobias, Eissa, N Tony, Eissa, Sanaa, Ejarque, Miriam, El Andaloussi, Abdeljabar, El-Hage, Nazira, El-Naggar, Shahenda, Eleuteri, Anna Maria, El-Shafey, Eman, Elgendy, Mohamed, Eliopoulos, Aristides, Elizalde, María, Elks, Philip, Elsasser, Hans-Peter, Elsherbiny, Eslam, Emerling, Brooke, Emre, N., Eng, Christina, Engedal, Nikolai, Engelbrecht, Anna-Mart, Engelsen, Agnete, Enserink, Jorrit, Escalante, Ricardo, Esclatine, Audrey, Escobar-Henriques, Mafalda, Eskelinen, Eeva-Liisa, Espert, Lucile, Eusebio, Makandjou-Ola, Fabrias, Gemma, Fabrizi, Cinzia, Facchiano, Antonio, Facchiano, Francesco, Fadeel, Bengt, Fader, Claudio, Faesen, Alex, Fairlie, W Douglas, Falcó, Alberto, Falkenburger, Bjorn, Fan, Daping, Fan, Jie, Fan, Yanbo, Fang, Evandro, Fang, Yanshan, Fang, Yognqi, Fanto, Manolis, Farfel-Becker, Tamar, Faure, Mathias, Fazeli, Gholamreza, Fedele, Anthony, Feldman, Arthur, Feng, Du, Feng, Jiachun, Feng, Lifeng, Feng, Yibin, Feng, Yuchen, Feng, Wei, Fenz Araujo, Thais, Ferguson, Thomas, Fernández, Álvaro, Fernandez-Checa, Jose, Fernández-Veledo, Sonia, Fernie, Alisdair, Ferrante, Anthony, Ferraresi, Alessandra, Ferrari, Merari, Ferreira, Julio, Ferro-Novick, Susan, Figueras, Antonio, Filadi, Riccardo, Filigheddu, Nicoletta, Filippi-Chiela, Eduardo, Filomeni, Giuseppe, Fimia, Gian Maria, Fineschi, Vittorio, Finetti, Francesca, Finkbeiner, Steven, Fisher, Edward, Fisher, Paul, Flamigni, Flavio, Fliesler, Steven, Flo, Trude, Florance, Ida, Florey, Oliver, Florio, Tullio, Fodor, Erika, Follo, Carlo, Fon, Edward, Forlino, Antonella, Fornai, Francesco, Fortini, Paola, Fracassi, Anna, Fraldi, Alessandro, Franco, Brunella, Franco, Rodrigo, Franconi, Flavia, Frankel, Lisa, Friedman, Scott, Fröhlich, Leopold, Frühbeck, Gema, Fuentes, Jose, Fujiki, Yukio, Fujita, Naonobu, Fujiwara, Yuuki, Fukuda, Mitsunori, Fulda, Simone, Furic, Luc, Furuya, Norihiko, Fusco, Carmela, Gack, Michaela, Gaffke, Lidia, Galadari, Sehamuddin, Galasso, Alessia, Galindo, Maria, Gallolu Kankanamalage, 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Sylvie, Giustiniani, Julien, Gluschko, Alexander, Goder, Veit, Goginashvili, Alexander, Golab, Jakub, Goldstone, David, Golebiewska, Anna, Gomes, Luciana, Gomez, Rodrigo, Gómez-Sánchez, Rubén, Gomez-Puerto, Maria Catalina, Gomez-Sintes, Raquel, Gong, Qingqiu, Goni, Felix, González-Gallego, Javier, Gonzalez-Hernandez, Tomas, Gonzalez-Polo, Rosa, Gonzalez-Reyes, Jose, González-Rodríguez, Patricia, Goping, Ing Swie, Gorbatyuk, Marina, Gorbunov, Nikolai, Görgülü, Kıvanç, Gorojod, Roxana, Gorski, Sharon, Goruppi, Sandro, Gotor, Cecilia, Gottlieb, Roberta, Gozes, Illana, Gozuacik, Devrim, Graef, Martin, Gräler, Markus, Granatiero, Veronica, Grasso, Daniel, Gray, Joshua, Green, Douglas, Greenhough, Alexander, Gregory, Stephen, Griffin, Edward, Grinstaff, Mark, Gros, Frederic, Grose, Charles, Gross, Angelina, Gruber, Florian, Grumati, Paolo, Grune, Tilman, Gu, Xueyan, Guan, Jun-Lin, Guardia, Carlos, Guda, Kishore, Guerra, Flora, Guerri, Consuelo, Guha, Prasun, Guillén, Carlos, Gujar, Shashi, Gukovskaya, Anna, Gukovsky, Ilya, Gunst, Jan, Günther, Andreas, Guntur, Anyonya, Guo, Chuanyong, Guo, Chun, Guo, Hongqing, Guo, Lian-Wang, Guo, Ming, Gupta, Pawan, Gupta, Shashi Kumar, Gupta, Swapnil, Gupta, Veer Bala, Gupta, Vivek, Gustafsson, Asa, Gutterman, David, H B, Ranjitha, Haapasalo, Annakaisa, Haber, James, Hać, Aleksandra, Hadano, Shinji, Hafrén, Anders, Haidar, Mansour, Hall, Belinda, Halldén, Gunnel, Hamacher-Brady, Anne, Hamann, Andrea, Hamasaki, Maho, Han, Weidong, Hansen, Malene, Hanson, Phyllis, Hao, Zijian, Harada, Masaru, Harhaji-Trajkovic, Ljubica, Hariharan, Nirmala, Haroon, Nigil, Harris, James, Hasegawa, Takafumi, Hasima Nagoor, Noor, Haspel, Jeffrey, Haucke, Volker, Hawkins, Wayne, Hay, Bruce, Haynes, Cole, Hayrabedyan, Soren, Hays, Thomas, He, Congcong, He, Qin, He, Rong-Rong, He, You-Wen, He, Yu-Ying, Heakal, Yasser, Heberle, Alexander, Hejtmancik, J Fielding, Helgason, Gudmundur Vignir, Henkel, Vanessa, Herb, Marc, Hergovich, Alexander, Herman-Antosiewicz, Anna, Hernández, Agustín, Hernandez, Carlos, Hernandez-Diaz, Sergio, Hernandez-Gea, Virginia, Herpin, Amaury, Herreros, Judit, Hervás, Javier, Hesselson, Daniel, Hetz, Claudio, Heussler, Volker, Higuchi, Yujiro, Hilfiker, Sabine, Hill, Joseph, Hlavacek, William, Ho, Emmanuel, Ho, Idy, Ho, Philip Wing-Lok, Ho, Shu-Leong, Ho, Wan Yun, Hobbs, G Aaron, Hochstrasser, Mark, Hoet, Peter, Hofius, Daniel, Hofman, Paul, Höhn, Annika, Holmberg, Carina, Hombrebueno, Jose, Yi-Ren Hong, Chang-Won Hong, Hooper, Lora, Hoppe, Thorsten, Horos, Rastislav, Hoshida, Yujin, Hsin, I-Lun, Hsu, Hsin-Yun, Hu, Bing, Hu, Dong, Hu, Li-Fang, Hu, Ming Chang, Hu, Ronggui, Hu, Wei, Hu, Yu-Chen, Hu, Zhuo-Wei, Hua, Fang, Hua, Jinlian, Hua, Yingqi, Huan, Chongmin, Huang, Canhua, Huang, Chuanshu, Huang, Chuanxin, Huang, Chunling, Huang, Haishan, Huang, Kun, Huang, Michael, Huang, Rui, Huang, Shan, Huang, Tianzhi, Huang, Xing, Huang, Yuxiang Jack, Huber, Tobias, Hubert, Virginie, Hubner, Christian, Hughes, Stephanie, Hughes, William, Humbert, Magali, Hummer, Gerhard, Hurley, James, Hussain, Sabah, Hussain, Salik, Hussey, Patrick, Hutabarat, Martina, Hwang, Hui-Yun, Hwang, Seungmin, Ieni, Antonio, Ikeda, Fumiyo, Imagawa, Yusuke, Imai, Yuzuru, Imbriano, Carol, Imoto, Masaya, Inman, Denise, Inoki, Ken, Iovanna, Juan, Iozzo, Renato, Ippolito, Giuseppe, Irazoqui, Javier, Iribarren, Pablo, Ishaq, Mohd, ISHIKAWA, Makoto, Ishimwe, Nestor, Isidoro, Ciro, Ismail, Nahed, Issazadeh-Navikas, Shohreh, Itakura, Eisuke, Ito, Daisuke, Ivankovic, Davor, Ivanova, Saška, Iyer, Anand Krishnan V, Izquierdo, José, Izumi, Masanori, Jäättelä, Marja, Jabir, Majid Sakhi, Jackson, William, Jacobo-Herrera, Nadia, Jacomin, Anne-Claire, Jacquin, Elise, Jadiya, Pooja, Jaeschke, Hartmut, Jagannath, Chinnaswamy, Jakobi, Arjen, Jakobsson, Johan, Janji, Bassam, Jansen-Dürr, Pidder, Jansson, Patric, Jantsch, Jonathan, Januszewski, Sławomir, Jassey, Alagie, Jean, Steve, Jeltsch-David, Hélène, Jendelova, Pavla, Jenny, Andreas, Jensen, Thomas, Jessen, Niels, Jewell, Jenna, Ji, Jing, Jia, Lijun, Jia, Rui, Jiang, Liwen, Jiang, Qing, Jiang, Richeng, Jiang, Teng, Jiang, Xuejun, Jiang, Yu, Jimenez-Sanchez, Maria, Jin, Eun-Jung, Jin, Fengyan, Jin, Hongchuan, Jin, Li, Jin, Luqi, Jin, Meiyan, Jin, Si, Jo, Eun-Kyeong, Joffre, Carine, Johansen, Terje, Johnson, Gail, Johnston, Simon, Jokitalo, Eija, Jolly, Mohit Kumar, Joosten, Leo, Jordan, Joaquin, Joseph, Bertrand, Ju, Dianwen, Ju, Jeong-Sun, Ju, Jingfang, Juárez, Esmeralda, Judith, Delphine, Juhász, Gábor, Jun, Youngsoo, Jung, Chang Hwa, Jung, Sung-Chul, Jung, Yong Keun, Jungbluth, Heinz, Jungverdorben, Johannes, Just, Steffen, Kaarniranta, Kai, Kaasik, Allen, Kabuta, Tomohiro, Kaganovich, Daniel, Kahana, Alon, Kain, Renate, Kajimura, Shinjo, Kalamvoki, Maria, Kalia, Manjula, Kalinowski, Danuta, Kaludercic, Nina, Kalvari, Ioanna, Kaminska, Joanna, Kaminskyy, Vitaliy, Kanamori, Hiromitsu, Kanasaki, Keizo, Kang, Chanhee, Kang, Rui, Kang, Sang Sun, Kaniyappan, Senthilvelrajan, 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Kazuyuki, Kuenen, Sabine, Kuerschner, Lars, Kukar, Thomas, Kumar, Ajay, Kumar, Ashok, Kumar, Deepak, Kumar, Dhiraj, Kumar, Sharad, Kume, Shinji, Kumsta, Caroline, Kundu, Chanakya, Kundu, Mondira, Kunnumakkara, Ajaikumar, Kurgan, Lukasz, Kutateladze, Tatiana, Kutlu, Ozlem, Kwak, SeongAe, Kwon, Ho Jeong, Kwon, Taeg Kyu, Kwon, Yong Tae, Kyrmizi, Irene, La Spada, Albert, Labonté, Patrick, Ladoire, Sylvain, Laface, Ilaria, Lafont, Frank, Lagace, Diane, Lahiri, Vikramjit, Lai, Zhibing, Laird, Angela, Lakkaraju, Aparna, Lamark, Trond, Lan, Sheng-Hui, Landajuela, Ane, Lane, Darius, Lane, Jon, Lang, Charles, Lange, Carsten, Langel, Ülo, Langer, Rupert, Lapaquette, Pierre, Laporte, Jocelyn, LaRusso, Nicholas, Lastres-Becker, Isabel, Lau, Wilson Chun Yu, Laurie, Gordon, Lavandero, Sergio, Law, Betty Yuen Kwan, Law, Helen Ka-wai, Layfield, Rob, Le, Weidong, Le Stunff, Herve, Leary, Alexandre, Lebrun, Jean-Jacques, Leck, Lionel, Leduc-Gaudet, Jean-Philippe, Lee, Changwook, Lee, Chung-Pei, Lee, 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Chengyu, Liang, Qiangrong, Liang, Weicheng, Liang, Yongheng, Liang, YongTian, Liao, Guanghong, Liao, Lujian, Liao, Mingzhi, Liao, Yung-Feng, Librizzi, Mariangela, Lie, Pearl, Lilly, Mary, Lim, Hyunjung, Lima, Thania, Limana, Federica, Lin, Chao, Lin, Chih-Wen, Lin, Dar-Shong, Lin, Fu-Cheng, Lin, Jiandie, Lin, Kurt, Lin, Kwang-Huei, Lin, Liang-Tzung, LIN, Pei-Hui, Lin, Qiong, Lin, Shaofeng, Lin, Su-Ju, Lin, Wenyu, Lin, Xueying, Lin, Yao-Xin, Lin, Yee-Shin, Linden, Rafael, Lindner, Paula, Ling, Shuo-Chien, Lingor, Paul, Linnemann, Amelia, Liou, Yih-Cherng, Lipinski, Marta, Lipovšek, Saška, Lira, Vitor, Lisiak, Natalia, Liton, Paloma, Liu, Chao, Liu, Ching-Hsuan, Liu, Chun-Feng, Liu, Cui Hua, Liu, Fang, Liu, Hao, Liu, Hsiao-Sheng, Liu, Hua-feng, Liu, Huifang, Liu, Jia, Liu, Jing, Liu, Julia, Liu, Leyuan, Liu, Longhua, Liu, Meilian, Liu, Qin, Liu, Wei, Liu, Wende, Liu, Xiao-Hong, Liu, Xiaodong, Liu, Xingguo, Liu, Xu, Liu, Xuedong, Liu, Yanfen, Liu, Yang, Liu, Yueyang, Liu, Yule, 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Marshall, Richard, Marten, Mark, Martens, Sascha, Martin, Alexandre, Martin, Katie, Martin, Sara, Martin, Shaun, Martín-Segura, Adrián, Martín-Acebes, Miguel, Martin-Burriel, Inmaculada, Martin-Rincon, Marcos, Martin-Sanz, Paloma, Martina, José, Martinet, Wim, Martinez, Aitor, Martinez, Ana, Martinez, Jennifer, Martinez Velazquez, Moises, Martinez-Lopez, Nuria, Martinez-Vicente, Marta, Martins, Daniel, Martins, Joilson, Martins, Waleska, Martins-Marques, Tania, Marzetti, Emanuele, Masaldan, Shashank, Masclaux-Daubresse, Celine, Mashek, Douglas, Massa, Valentina, Massieu, Lourdes, Masson, Glenn, Masuelli, Laura, Masyuk, Anatoliy, Masyuk, Tetyana, Matarrese, Paola, Matheu, Ander, Matoba, Satoaki, Matsuzaki, Sachiko, Mattar, Pamela, Matte, Alessandro, Mattoscio, Domenico, Mauriz, José, Mauthe, Mario, Mauvezin, Caroline, Maverakis, Emanual, Maycotte, Paola, Mayer, Johanna, Mazzoccoli, Gianluigi, Mazzoni, Cristina, Mazzulli, Joseph, McCarty, Nami, Mcdonald, Christine, McGill, Mitchell, 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Yang, Jingyu, Yang, Ling, Yang, Liu, Yang, Ming, Yang, Pei-Ming, Yang, Qian, Yang, Seungwon, Yang, Shu, Yang, Shun-Fa, Yang, Wannian, Yang, Wei Yuan, Yang, Xiaoyong, Yang, Xuesong, Yang, Yi, Yang, Ying, Yao, Honghong, Yao, Shenggen, Yao, Xiaoqiang, Yao, Yong-Gang, Yao, Yong-Ming, Yasui, Takahiro, Yazdankhah, Meysam, Yen, Paul, Yi, Cong, Yin, Xiao-Ming, Yin, Yanhai, Yin, Zhangyuan, Yin, Ziyi, Ying, Meidan, Ying, Zheng, Yip, Calvin, Yiu, Stephanie Pei Tung, Yoo, Young, Yoshida, Kiyotsugu, Yoshii, Saori, Yoshimori, Tamotsu, Yousefi, Bahman, Yu, Boxuan, Yu, Haiyang, Yu, Jun, Yu, Li, Yu, Ming-Lung, Yu, Seong-Woon, Yu, Victor, Yu, W Haung, Yu, Zhengping, Yu, Zhou, Yuan, Junying, Yuan, Ling-Qing, Yuan, Shilin, Yuan, Shyng-Shiou, Yuan, Yanggang, Yuan, Zengqiang, Yue, Jianbo, Yue, Zhenyu, Yun, Jeanho, Yung, Raymond, Zacks, David, Zaffagnini, Gabriele, Zambelli, Vanessa, Zanella, Isabella, Zang, Qun, Zanivan, Sara, Zappavigna, Silvia, Zaragoza, Pilar, Zarbalis, Konstantinos, Zarebkohan, Amir, Zarrouk, Amira, Zeitlin, Scott, Zeng, Jialiu, Zeng, Ju-deng, Žerovnik, Eva, Zhan, Lixuan, Zhang, Bin, Zhang, Donna, Zhang, Hanlin, Zhang, Hong, Zhang, Honghe, Zhang, Huafeng, Zhang, Huaye, Zhang, Hui, Zhang, Hui-Ling, Zhang, Jianbin, Zhang, Jianhua, Zhang, Jing-Pu, Zhang, Kalin, Zhang, Leshuai, Zhang, Lin, Zhang, Lisheng, Zhang, Lu, Zhang, Luoying, Zhang, Menghuan, Zhang, Peng, Zhang, Sheng, Zhang, Wei, Zhang, Xiangnan, Zhang, Xiao-Wei, Zhang, Xiaolei, Zhang, Xiaoyan, Zhang, Xin, Zhang, Xinxin, Zhang, Xu Dong, Zhang, Yang, Zhang, Yanjin, Zhang, Yi, Zhang, Ying-Dong, Zhang, Yingmei, Zhang, Yuan-Yuan, Zhang, Yuchen, Zhang, Zhe, Zhang, Zhengguang, Zhang, Zhibing, Zhang, Zhihai, Zhang, Zhiyong, Zhang, Zili, Zhao, Haobin, Zhao, Lei, Zhao, Shuang, Zhao, Tongbiao, Zhao, Xiao-Fan, Zhao, Ying, Zhao, Yongchao, Zhao, Yongliang, Zhao, Yuting, Zheng, Guoping, Zheng, Kai, Zheng, Ling, Zheng, Shizhong, Zheng, Xi-Long, Zheng, Yi, Zheng, Zu-Guo, Zhivotovsky, Boris, Zhong, Qing, Zhou, Ao, Zhou, Ben, Zhou, Cefan, ZHOU, Gang, Zhou, Hao, Zhou, Hong, Zhou, Hongbo, Zhou, Jie, Zhou, Jing, Zhou, Jiyong, Zhou, Kailiang, Zhou, Rongjia, Zhou, Xu-jie, Zhou, Yanshuang, Zhou, Yinghong, Zhou, Yubin, Zhou, Zheng-Yu, Zhou, Zhou, Zhu, Binglin, Zhu, Changlian, Zhu, Guo-Qing, Zhu, Haining, Zhu, Hongxin, Zhu, Hua, Zhu, Wei-Guo, Zhu, Yanping, Zhu, Yushan, Zhuang, Haixia, Zhuang, Xiaohong, Zientara-Rytter, Katarzyna, Zimmermann, Christine, Ziviani, Elena, Zoladek, Teresa, Zong, Wei-Xing, Zorov, Dmitry, Zorzano, Antonio, Zou, Weiping, Zou, Zhen, Zou, Zhengzhi, Zuryn, Steven, Zwerschke, Werner, Brand-Saberi, Beate, Dong, X Charlie, Kenchappa, Chandra Shekar, Li, Zuguo, Lin, Yong, Oshima, Shigeru, Rong, Yueguang, Sluimer, Judith, Stallings, Christina, Tong, Chun-Kit, Ahmad, S. Tariq, Alim Al-Bari, M. Abdul, Bechara, Luiz R.G., Behrens, Georg M.N., Bhuiyan, Md. Shenuarin, Broaddus, V. Courtney, Buchan, J. Ross, Burón, M. Isabel, Carter, A. Brent, Chan, Matthew T.V., Choi, Augustine M.K., D’Adamo, Stefania, D’Amelio, Marcello, D’Arcangelo, Daniela, D’Lugos, Andrew, D’Orazi, Gabriella, De Meyer, Guido R.Y., Delpino, M. Victoria, Distler, Jörg H.W., Dixon, Ian M.C., Dobson, Renwick C.J., 2nd Dorn, Gerald, Eissa, N. Tony, Engelsen, Agnete S.T., Fairlie, W. Douglas, Ferreira, Julio C.B., H.B., Ranjitha, Hanson, Phyllis I., Hejtmancik, J. Fielding, Ho, Idy H.T., Hobbs, G. Aaron, Hoet, Peter H.M., Huang, Michael L.H., Iyer, Anand Krishnan V., Johnson, Gail V.W., Joosten, Leo A.B., Karim, Md. Razaul, Kaufmann, Stefan H.E., Ko, Ben C.B., Leck, Lionel Y.W., Lima, Thania R.R., Livingston, J. Andrew, Martin, Alexandre P.J., Montes, L. Ruth, Murphy, J. Patrick, Ng, Charlene C.W., Nicolao, M. Celeste, O’Donovan, Tracey, O’Leary, Seónadh, O’Rourke, Eyleen, O’Sullivan, Mary, O’Sullivan, Timothy, Omary, M. Bishr, Pereira, Gustavo J.S., Ratnayaka, J. Arjuna, Riazuddin, S. Amer, Rouschop, Kasper M.A., Sanderson, J. Thomas, Scaglione, K. Matthew, Schapira, Anthony H.V., Scovassi, A. Ivana, St. Clair, Daret, Sunahara, Karen K.S., Symons, J. David, Triola, Gemma, van Wijk, Sjoerd J.L., Vanrell, M. Cristina, Vasconcelos, M. Helena, Whitton, J. Lindsay, Williams, Robin S.B., Wong, W. Wei-Lynn, Wu, William K.K., Yakhine-Diop, Sokhna M.S., Yu, W. Haung, Zhang, Kalin Y.B., Dong, X. Charlie, Ain Shams University [ASU], Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University [JGU], Medical University Graz, Centre de Recherche des Cordeliers [CRC (UMR_S_1138 / U1138)], Institut Pasteur d'Iran, Leibniz Institute of Plant Biochemistry [IPB], The University of Texas M.D. Anderson Cancer Center [Houston], Institut de pharmacologie moléculaire et cellulaire [IPMC], Lipides - Nutrition - Cancer [Dijon - U1231] [LNC], Centre méditerranéen de médecine moléculaire [C3M], Institut de Biologie Valrose [IBV], Petites Molécules de neuroprotection, neurorégénération et remyélinisation, Signalisation Hormonale, Physiopathologie Endocrinienne et Métabolique, Institut Cochin [IC UM3 (UMR 8104 / U1016)], Institut NeuroMyoGène [INMG], Paris-Centre de Recherche Cardiovasculaire [PARCC (UMR_S 970/ U970)], Marqueurs cardiovasculaires en situation de stress [MASCOT (UMR_S_942 / U942)], Institut de Recherche sur le Cancer et le Vieillissement [IRCAN], Centre de Recherche en Cancérologie de Marseille [CRCM], Centre for Integrative Biology - CBI [Inserm U964 - CNRS UMR7104 - IGBMC], Oncogenesis, Stress, Signaling [OSS], Institut Necker Enfants-Malades [INEM - UM 111 (UMR 8253 / U1151)], Institut de Biologie Intégrative de la Cellule [I2BC], Microbes, Intestin, Inflammation et Susceptibilité de l'Hôte [M2iSH], Centre de Recherches en Cancérologie de Toulouse [CRCT], Physiopathologie et traitement des maladies du foie, Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 [CIIL], Institut de Génétique et de Biologie Moléculaire et Cellulaire [IGBMC], Laboratoire Bio-PeroxIL. Biochimie du peroxysome, inflammation et métabolisme lipidique [Dijon] [BIO-PEROXIL], Centre de recherche sur l'Inflammation [CRI (UMR_S_1149 / ERL_8252 / U1149)], Unité de génétique et biologie des cancers [U830], Laboratoire d'Optique et Biosciences [LOB], Institut des Maladies Métaboliques et Casdiovasculaires [UPS/Inserm U1297 - I2MC], Différenciation et communication neuronale et neuroendocrine [DC2N], Institut de Recherche en Cancérologie de Montpellier [IRCM - U1194 Inserm - UM], Centre d'Immunologie de Marseille - Luminy [CIML], Physiopathologie et imagerie des troubles neurologiques [PhIND], Laboratory of Fundamental and Applied Bioenergetics = Laboratoire de bioénergétique fondamentale et appliquée [LBFA], Imagine - Institut des maladies génétiques (IHU) [Imagine - U1163], Institut Mondor de Recherche Biomédicale [IMRB], Franco-czech Laboratory for clinical research on obesity, University of Michigan [Ann Arbor], University of Michigan System, Institut de pharmacologie moléculaire et cellulaire (IPMC), Centre National de la Recherche Scientifique (CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Université Côte d'Azur (UCA), Lipides - Nutrition - Cancer [Dijon - U1231] (LNC), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Centre méditerranéen de médecine moléculaire (C3M), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA), Institut de Biologie Valrose (IBV), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Sud - Paris 11 (UP11), Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université de Paris (UP), Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), Nutrition, Métabolisme, Aquaculture (NuMéA), Université de Pau et des Pays de l'Adour (UPPA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institut NeuroMyoGène (INMG), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Institut de Recherche sur le Cancer et le Vieillissement (IRCAN), COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015 - 2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre de Recherche en Cancérologie de Marseille (CRCM), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Aix Marseille Université (AMU), Centre for Integrative Biology - CBI (Inserm U964 - CNRS UMR7104 - IGBMC), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institute of genetics and molecular and cellular biology-Centre National de la Recherche Scientifique (CNRS), Chemistry, Oncogenesis, Stress and Signaling (COSS), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-CRLCC Eugène Marquis (CRLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Necker Enfants-Malades (INEM - UM 111 (UMR 8253 / U1151)), Unité de Nutrition Humaine (UNH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Microbes, Intestin, Inflammation et Susceptibilité de l'Hôte (M2iSH), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre de Recherche en Nutrition Humaine d'Auvergne (CRNH d'Auvergne)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Centre International de Recherche en Infectiologie - UMR (CIRI), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de Recherches en Cancérologie de Toulouse (CRCT), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physiologie et Génomique des Poissons (LPGP), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 (CIIL), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Centre National de la Recherche Scientifique (CNRS), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Laboratoire Bio-PeroxIL. Biochimie du peroxysome, inflammation et métabolisme lipidique [Dijon] (BIO-PEROXIL), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Centre de recherche sur l'Inflammation (CRI (UMR_S_1149 / ERL_8252 / U1149)), Institut Jean-Pierre Bourgin (IJPB), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de génétique et biologie des cancers (U830), Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Optique et Biosciences (LOB), École polytechnique (X)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut des Maladies Métaboliques et Cardiovasculaires (I2MC), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Différenciation et communication neuronale et neuroendocrine (DC2N), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Recherche en Cancérologie de Montpellier (IRCM - U1194 Inserm - UM), CRLCC Val d'Aurelle - Paul Lamarque-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Centre d'Immunologie de Marseille - Luminy (CIML), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie et imagerie des troubles neurologiques (PhIND), Université de Caen Normandie (UNICAEN), Laboratory of Fundamental and Applied Bioenergetics = Laboratoire de bioénergétique fondamentale et appliquée (LBFA), Université Grenoble Alpes (UGA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epithelial biology and disease - Liliane Bettencourt Chair of Developmental Biology (Equipe Inserm U1163), Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Biomécanique cellulaire et respiratoire (BCR), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Charles University [Prague]-Institut National de la Santé et de la Recherche Médicale (INSERM), This work was supported by the National Institute of General Medical Sciences [GM131919]., Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM), Marqueurs cardiovasculaires en situation de stress (MASCOT (UMR_S_942 / U942)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Université Sorbonne Paris Nord, Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie des Adaptations Nutritionnelles (PhAN), Université de Nantes (UN)-Institut National de la Recherche Agronomique (INRA), Département Plateforme (PF I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut Gustave Roussy (IGR), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Chinese Academy of Medical Sciences [Suzhou, Chine] (CAMS), Karolinska Institutet [Stockholm], Karolinska University Hospital [Stockholm], Department of Women's and Children's Health [Stockholm, Sweden], Centre National de la Recherche Scientifique (CNRS)-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-École polytechnique (X), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, FHU OncoAge - Pathologies liées à l’âge [CHU Nice] (OncoAge), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Institut de Pharmacologie Moléculaire et Cellulaire [UNIV Côte d'Azur] (UPMC), Institut Universitaire du Cancer de Toulouse - Oncopole (IUCT Oncopole - UMR 1037), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM), Life Sciences Institute [Ann Arbor, MI, USA], University of Michigan System-University of Michigan System, European Institute of Oncology IRCCS [Milan, Italy] (EIO), Ain Shams University (ASU), Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), Réseau International des Instituts Pasteur (RIIP), Leibniz Institute of Plant Biochemistry (IPB), Hebrew University of Jerusalem, Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Côte d'Azur (UCA), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Aix Marseille Université (AMU)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Oncogenesis, Stress, Signaling (OSS), Institut des Maladies Métaboliques et Casdiovasculaires (UPS/Inserm U1297 - I2MC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Charles University [Prague] (CU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Klionsky, D. J., Abdel-Aziz, A. K., Abdelfatah, S., Abdellatif, M., Abdoli, A., Abel, S., Abeliovich, H., Abildgaard, M. H., Abudu, Y. P., Acevedo-Arozena, A., Adamopoulos, I. E., Adeli, K., Adolph, T. E., Adornetto, A., Aflaki, E., Agam, G., Agarwal, A., Aggarwal, B. B., Agnello, M., Agostinis, P., Agrewala, J. N., Agrotis, A., Aguilar, P. V., Ahmad, S. T., Ahmed, Z. M., Ahumada-Castro, U., Aits, S., Aizawa, S., Akkoc, Y., Akoumianaki, T., Akpinar, H. A., Al-Abd, A. M., Al-Akra, L., Al-Gharaibeh, A., Alaoui-Jamali, M. A., Alberti, S., Alcocer-Gomez, E., Alessandri, C., Ali, M., Alim Al-Bari, M. A., Aliwaini, S., Alizadeh, J., Almacellas, E., Almasan, A., Alonso, A., Alonso, G. D., Altan-Bonnet, N., Altieri, D. C., Alvarez, E. M. C., Alves, S., Alves da Costa, C., Alzaharna, M. M., Amadio, M., Amantini, C., Amaral, C., Ambrosio, S., Amer, A. O., Ammanathan, V., An, Z., Andersen, S. U., Andrabi, S. A., Andrade-Silva, M., Andres, A. M., Angelini, S., Ann, D., Anozie, U. C., Ansari, M. Y., Antas, P., Antebi, A., Anton, Z., Anwar, T., Apetoh, L., Apostolova, N., Araki, T., Araki, Y., Arasaki, K., Araujo, W. L., Araya, J., Arden, C., Arevalo, M. -A., Arguelles, S., Arias, E., Arikkath, J., Arimoto, H., Ariosa, A. R., Armstrong-James, D., Arnaune-Pelloquin, L., Aroca, A., Arroyo, D. S., Arsov, I., Artero, R., Asaro, D. M. L., Aschner, M., Ashrafizadeh, M., Ashur-Fabian, O., Atanasov, A. G., Au, A. K., Auberger, P., Auner, H. W., Aurelian, L., Autelli, R., Avagliano, L., Avalos, Y., Aveic, S., Aveleira, C. A., Avin-Wittenberg, T., Aydin, Y., Ayton, S., Ayyadevara, S., Azzopardi, M., Baba, M., Backer, J. M., Backues, S. K., Bae, D. -H., Bae, O. -N., Bae, S. H., Baehrecke, E. H., Baek, A., Baek, S. -H., Baek, S. H., Bagetta, G., Bagniewska-Zadworna, A., Bai, H., Bai, J., Bai, X., Bai, Y., Bairagi, N., Baksi, S., Balbi, T., Baldari, C. T., Balduini, W., Ballabio, A., Ballester, M., Balazadeh, S., Balzan, R., Bandopadhyay, R., Banerjee, S., Banreti, A., Bao, Y., Baptista, M. S., Baracca, A., Barbati, C., Bargiela, A., Barila, D., Barlow, P. G., Barmada, S. J., Barreiro, E., Barreto, G. E., Bartek, J., Bartel, B., Bartolome, A., Barve, G. R., Basagoudanavar, S. H., Bassham, D. C., Bast, R. C., Basu, A., Batoko, H., Batten, I., Baulieu, E. E., Baumgarner, B. L., Bayry, J., Beale, R., Beau, I., Beaumatin, F., Bechara, L. R. G., Beck, G. R., Beers, M. F., Begun, J., Behrends, C., Behrens, G. M. N., Bei, R., Bejarano, E., Bel, S., Behl, C., Belaid, A., Belgareh-Touze, N., Bellarosa, C., Belleudi, F., Bello Perez, M., Bello-Morales, R., Beltran, J. S. D. O., Beltran, S., Benbrook, D. M., Bendorius, M., Benitez, B. A., Benito-Cuesta, I., Bensalem, J., Berchtold, M. W., Berezowska, S., Bergamaschi, D., Bergami, M., Bergmann, A., Berliocchi, L., Berlioz-Torrent, C., Bernard, A., Berthoux, L., Besirli, C. G., Besteiro, S., Betin, V. M., Beyaert, R., Bezbradica, J. S., Bhaskar, K., Bhatia-Kissova, I., Bhattacharya, R., Bhattacharya, S., Bhattacharyya, S., Bhuiyan, M. S., Bhutia, S. K., Bi, L., Bi, X., Biden, T. J., Bijian, K., Billes, V. A., Binart, N., Bincoletto, C., Birgisdottir, A. B., Bjorkoy, G., Blanco, G., Blas-Garcia, A., Blasiak, J., Blomgran, R., Blomgren, K., Blum, J. S., Boada-Romero, E., Boban, M., Boesze-Battaglia, K., Boeuf, P., Boland, B., Bomont, P., Bonaldo, P., Bonam, S. R., Bonfili, L., Bonifacino, J. S., Boone, B. A., Bootman, M. D., Bordi, M., Borner, C., Bornhauser, B. C., Borthakur, G., Bosch, J., Bose, S., Botana, L. M., Botas, J., Boulanger, C. M., Boulton, M. E., Bourdenx, M., Bourgeois, B., Bourke, N. M., Bousquet, G., Boya, P., Bozhkov, P. V., Bozi, L. H. M., Bozkurt, T. O., Brackney, D. E., Brandts, C. H., Braun, R. J., Braus, G. H., Bravo-Sagua, R., Bravo-San Pedro, J. M., Brest, P., Bringer, M. -A., Briones-Herrera, A., Broaddus, V. C., Brodersen, P., Brodsky, J. L., Brody, S. L., Bronson, P. G., Bronstein, J. M., Brown, C. N., Brown, R. E., Brum, P. C., Brumell, J. H., Brunetti-Pierri, N., Bruno, D., Bryson-Richardson, R. J., Bucci, C., Buchrieser, C., Bueno, M., Buitrago-Molina, L. E., Buraschi, S., Buch, S., Buchan, J. R., Buckingham, E. M., Budak, H., Budini, M., Bultynck, G., Burada, F., Burgoyne, J. R., Buron, M. I., Bustos, V., Buttner, S., Butturini, E., Byrd, A., Cabas, I., Cabrera-Benitez, S., Cadwell, K., Cai, J., Cai, L., Cai, Q., Cairo, M., Calbet, J. A., Caldwell, G. A., Caldwell, K. A., Call, J. A., Calvani, R., Calvo, A. C., Calvo-Rubio Barrera, M., Camara, N. O. S., Camonis, J. H., Camougrand, N., Campanella, M., Campbell, E. M., Campbell-Valois, F. -X., Campello, S., Campesi, I., Campos, J. C., Camuzard, O., Cancino, J., Candido de Almeida, D., Canesi, L., Caniggia, I., Canonico, B., Canti, C., Cao, B., Caraglia, M., Carames, B., Carchman, E. H., Cardenal-Munoz, E., Cardenas, C., Cardenas, L., Cardoso, S. M., Carew, J. S., Carle, G. F., Carleton, G., Carloni, S., Carmona-Gutierrez, D., Carneiro, L. A., Carnevali, O., Carosi, J. M., Carra, S., Carrier, A., Carrier, L., Carroll, B., Carter, A. B., Carvalho, A. N., Casanova, M., Casas, C., Casas, J., Cassioli, C., Castillo, E. F., Castillo, K., Castillo-Lluva, S., Castoldi, F., Castori, M., Castro, A. F., Castro-Caldas, M., Castro-Hernandez, J., Castro-Obregon, S., Catz, S. D., Cavadas, C., Cavaliere, F., Cavallini, G., Cavinato, M., Cayuela, M. L., Cebollada Rica, P., Cecarini, V., Cecconi, F., Cechowska-Pasko, M., Cenci, S., Ceperuelo-Mallafre, V., Cerqueira, J. J., Cerutti, J. M., Cervia, D., Cetintas, V. B., Cetrullo, S., Chae, H. -J., Chagin, A. S., Chai, C. -Y., Chakrabarti, G., Chakrabarti, O., Chakraborty, T., Chami, M., Chamilos, G., Chan, D. W., Chan, E. Y. W., Chan, E. D., Chan, H. Y. E., Chan, H. H., Chan, H., Chan, M. T. V., Chan, Y. S., Chandra, P. K., Chang, C. -P., Chang, C., Chang, H. -C., Chang, K., Chao, J., Chapman, T., Charlet-Berguerand, N., Chatterjee, S., Chaube, S. K., Chaudhary, A., Chauhan, S., Chaum, E., Checler, F., Cheetham, M. E., Chen, C. -S., Chen, G. -C., Chen, J. -F., Chen, L. L., Chen, L., Chen, M., Chen, M. -K., Chen, N., Chen, Q., Chen, R. -H., Chen, S., Chen, W., Chen, X. -M., Chen, X. -W., Chen, X., Chen, Y., Chen, Y. -G., Chen, Y. -J., Chen, Y. -Q., Chen, Z. S., Chen, Z., Chen, Z. -H., Chen, Z. J., Cheng, H., Cheng, J., Cheng, S. -Y., Cheng, W., Cheng, X., Cheng, X. -T., Cheng, Y., Cheng, Z., Cheong, H., Cheong, J. K., Chernyak, B. V., Cherry, S., Cheung, C. F. R., Cheung, C. H. A., Cheung, K. -H., Chevet, E., Chi, R. J., Chiang, A. K. S., Chiaradonna, F., Chiarelli, R., Chiariello, M., Chica, N., Chiocca, S., Chiong, M., Chiou, S. -H., Chiramel, A. I., Chiurchiu, V., Cho, D. -H., Choe, S. -K., Choi, A. M. K., Choi, M. E., Choudhury, K. R., Chow, N. S., Chu, C. T., Chua, J. P., Chua, J. J. E., Chung, H., Chung, K. P., Chung, S., Chung, S. -H., Chung, Y. -L., Cianfanelli, V., Ciechomska, I. A., Cifuentes, M., Cinque, L., Cirak, S., Cirone, M., Clague, M. J., Clarke, R., Clementi, E., Coccia, E. M., Codogno, P., Cohen, E., Cohen, M. M., Colasanti, T., Colasuonno, F., Colbert, R. A., Colell, A., Colic, M., Coll, N. S., Collins, M. O., Colombo, M. I., Colon-Ramos, D. A., Combaret, L., Comincini, S., Cominetti, M. R., Consiglio, A., Conte, A., Conti, F., Contu, V. R., Cookson, M. R., Coombs, K. M., Coppens, I., Corasaniti, M. T., Corkery, D. P., Cordes, N., Cortese, K., Costa, M. D. C., Costantino, S., Costelli, P., Coto-Montes, A., Crack, P. J., Crespo, J. L., Criollo, A., Crippa, V., Cristofani, R., Csizmadia, T., Cuadrado, A., Cui, B., Cui, J., Cui, Y., Culetto, E., Cumino, A. C., Cybulsky, A. V., Czaja, M. J., Czuczwar, S. J., D'Adamo, S., D'Amelio, M., D'Arcangelo, D., D'Lugos, A. C., D'Orazi, G., da Silva, J. A., Dafsari, H. S., Dagda, R. K., Dagdas, Y., Daglia, M., Dai, X., Dai, Y., Dal Col, J., Dalhaimer, P., Dalla Valle, L., Dallenga, T., Dalmasso, G., Damme, M., Dando, I., Dantuma, N. P., Darling, A. L., Das, H., Dasarathy, S., Dasari, S. K., Dash, S., Daumke, O., Dauphinee, A. N., Davies, J. S., Davila, V. A., Davis, R. J., Davis, T., Dayalan Naidu, S., De Amicis, F., De Bosscher, K., De Felice, F., De Franceschi, L., De Leonibus, C., de Mattos Barbosa, M. G., De Meyer, G. R. Y., De Milito, A., De Nunzio, C., De Palma, C., De Santi, M., De Virgilio, C., De Zio, D., Debnath, J., Debosch, B. J., Decuypere, J. -P., Deehan, M. A., Deflorian, G., Degregori, J., Dehay, B., Del Rio, G., Delaney, J. R., Delbridge, L. M. D., Delorme-Axford, E., Delpino, M. V., Demarchi, F., Dembitz, V., Demers, N. D., Deng, H., Deng, Z., Dengjel, J., Dent, P., Denton, D., Depamphilis, M. L., Der, C. J., Deretic, V., Descoteaux, A., Devis, L., Devkota, S., Devuyst, O., Dewson, G., Dharmasivam, M., Dhiman, R., di Bernardo, D., Di Cristina, M., Di Domenico, F., Di Fazio, P., Di Fonzo, A., Di Guardo, G., Di Guglielmo, G. M., Di Leo, L., Di Malta, C., Di Nardo, A., Di Rienzo, M., Di Sano, F., Diallinas, G., Diao, J., Diaz-Araya, G., Diaz-Laviada, I., Dickinson, J. M., Diederich, M., Dieude, M., Dikic, I., Ding, S., Ding, W. -X., Dini, L., Dinic, J., Dinic, M., Dinkova-Kostova, A. T., Dionne, M. S., Distler, J. H. W., Diwan, A., Dixon, I. M. C., Djavaheri-Mergny, M., Dobrinski, I., Dobrovinskaya, O., Dobrowolski, R., Dobson, R. C. J., Dokic, J., Dokmeci Emre, S., Donadelli, M., Dong, B., Dong, X., Dong, Z., Dorn II, G. W., Dotsch, V., Dou, H., Dou, J., Dowaidar, M., Dridi, S., Drucker, L., Du, A., Du, C., Du, G., Du, H. -N., Du, L. -L., du Toit, A., Duan, S. -B., Duan, X., Duarte, S. P., Dubrovska, A., Dunlop, E. A., Dupont, N., Duran, R. V., Dwarakanath, B. S., Dyshlovoy, S. A., Ebrahimi-Fakhari, D., Eckhart, L., Edelstein, C. L., Efferth, T., Eftekharpour, E., Eichinger, L., Eid, N., Eisenberg, T., Eissa, N. T., Eissa, S., Ejarque, M., El Andaloussi, A., El-Hage, N., El-Naggar, S., Eleuteri, A. M., El-Shafey, E. S., Elgendy, M., Eliopoulos, A. G., Elizalde, M. M., Elks, P. M., Elsasser, H. -P., Elsherbiny, E. S., Emerling, B. M., Emre, N. C. T., Eng, C. H., Engedal, N., Engelbrecht, A. -M., Engelsen, A. S. T., Enserink, J. M., Escalante, R., Esclatine, A., Escobar-Henriques, M., Eskelinen, E. -L., Espert, L., Eusebio, M. -O., Fabrias, G., Fabrizi, C., Facchiano, A., Facchiano, F., Fadeel, B., Fader, C., Faesen, A. C., Fairlie, W. D., Falco, A., Falkenburger, B. H., Fan, D., Fan, J., Fan, Y., Fang, E. F., Fang, Y., Fanto, M., Farfel-Becker, T., Faure, M., Fazeli, G., Fedele, A. O., Feldman, A. M., Feng, D., Feng, J., Feng, L., Feng, Y., Feng, W., Fenz Araujo, T., Ferguson, T. A., Fernandez, A. F., Fernandez-Checa, J. C., Fernandez-Veledo, S., Fernie, A. R., Ferrante, A. W., Ferraresi, A., Ferrari, M. F., Ferreira, J. C. B., Ferro-Novick, S., Figueras, A., Filadi, R., Filigheddu, N., Filippi-Chiela, E., Filomeni, G., Fimia, G. M., Fineschi, V., Finetti, F., Finkbeiner, S., Fisher, E. A., Fisher, P. B., Flamigni, F., Fliesler, S. J., Flo, T. H., Florance, I., Florey, O., Florio, T., Fodor, E., Follo, C., Fon, E. A., Forlino, A., Fornai, F., Fortini, P., Fracassi, A., Fraldi, A., Franco, B., Franco, R., Franconi, F., Frankel, L. B., Friedman, S. L., Frohlich, L. F., Fruhbeck, G., Fuentes, J. M., Fujiki, Y., Fujita, N., Fujiwara, Y., Fukuda, M., Fulda, S., Furic, L., Furuya, N., Fusco, C., Gack, M. U., Gaffke, L., Galadari, S., Galasso, A., Galindo, M. F., Gallolu Kankanamalage, S., Galluzzi, L., Galy, V., Gammoh, N., Gan, B., Ganley, I. G., Gao, F., Gao, H., Gao, M., Gao, P., Gao, S. -J., Gao, W., Gao, X., Garcera, A., Garcia, M. N., Garcia, V. E., Garcia-Del Portillo, F., Garcia-Escudero, V., Garcia-Garcia, A., Garcia-Macia, M., Garcia-Moreno, D., Garcia-Ruiz, C., Garcia-Sanz, P., Garg, A. D., Gargini, R., Garofalo, T., Garry, R. F., Gassen, N. C., Gatica, D., Ge, L., Ge, W., Geiss-Friedlander, R., Gelfi, C., Genschik, P., Gentle, I. E., Gerbino, V., Gerhardt, C., Germain, K., Germain, M., Gewirtz, D. A., Ghasemipour Afshar, E., Ghavami, S., Ghigo, A., Ghosh, M., Giamas, G., Giampietri, C., Giatromanolaki, A., Gibson, G. E., Gibson, S. B., Ginet, V., Giniger, E., Giorgi, C., Girao, H., Girardin, S. E., Giridharan, M., Giuliano, S., Giulivi, C., Giuriato, S., Giustiniani, J., Gluschko, A., Goder, V., Goginashvili, A., Golab, J., Goldstone, D. C., Golebiewska, A., Gomes, L. R., Gomez, R., Gomez-Sanchez, R., Gomez-Puerto, M. C., Gomez-Sintes, R., Gong, Q., Goni, F. M., Gonzalez-Gallego, J., Gonzalez-Hernandez, T., Gonzalez-Polo, R. A., Gonzalez-Reyes, J. A., Gonzalez-Rodriguez, P., Goping, I. S., Gorbatyuk, M. S., Gorbunov, N. V., Gorgulu, K., Gorojod, R. M., Gorski, S. M., Goruppi, S., Gotor, C., Gottlieb, R. A., Gozes, I., Gozuacik, D., Graef, M., Graler, M. H., Granatiero, V., Grasso, D., Gray, J. P., Green, D. R., Greenhough, A., Gregory, S. L., Griffin, E. F., Grinstaff, M. W., Gros, F., Grose, C., Gross, A. S., Gruber, F., Grumati, P., Grune, T., Gu, X., Guan, J. -L., Guardia, C. M., Guda, K., Guerra, F., Guerri, C., Guha, P., Guillen, C., Gujar, S., Gukovskaya, A., Gukovsky, I., Gunst, J., Gunther, A., Guntur, A. R., Guo, C., Guo, H., Guo, L. -W., Guo, M., Gupta, P., Gupta, S. K., Gupta, S., Gupta, V. B., Gupta, V., Gustafsson, A. B., Gutterman, D. D., H. B, R., Haapasalo, A., Haber, J. E., Hac, A., Hadano, S., Hafren, A. J., Haidar, M., Hall, B. S., Hallden, G., Hamacher-Brady, A., Hamann, A., Hamasaki, M., Han, W., Hansen, M., Hanson, P. I., Hao, Z., Harada, M., Harhaji-Trajkovic, L., Hariharan, N., Haroon, N., Harris, J., Hasegawa, T., Hasima Nagoor, N., Haspel, J. A., Haucke, V., Hawkins, W. D., Hay, B. A., Haynes, C. M., Hayrabedyan, S. B., Hays, T. S., He, C., He, Q., He, R. -R., He, Y. -W., He, Y. -Y., Heakal, Y., Heberle, A. M., Hejtmancik, J. F., Helgason, G. V., Henkel, V., Herb, M., Hergovich, A., Herman-Antosiewicz, A., Hernandez, A., Hernandez, C., Hernandez-Diaz, S., Hernandez-Gea, V., Herpin, A., Herreros, J., Hervas, J. H., Hesselson, D., Hetz, C., Heussler, V. T., Higuchi, Y., Hilfiker, S., Hill, J. A., Hlavacek, W. S., Ho, E. A., Ho, I. H. T., Ho, P. W. -L., Ho, S. -L., Ho, W. Y., Hobbs, G. A., Hochstrasser, M., Hoet, P. H. M., Hofius, D., Hofman, P., Hohn, A., Holmberg, C. I., Hombrebueno, J. R., Yi-Ren Hong, C. -W. H., Hooper, L. V., Hoppe, T., Horos, R., Hoshida, Y., Hsin, I. -L., Hsu, H. -Y., Hu, B., Hu, D., Hu, L. -F., Hu, M. C., Hu, R., Hu, W., Hu, Y. -C., Hu, Z. -W., Hua, F., Hua, J., Hua, Y., Huan, C., Huang, C., Huang, H., Huang, K., Huang, M. L. H., Huang, R., Huang, S., Huang, T., Huang, X., Huang, Y. J., Huber, T. B., Hubert, V., Hubner, C. A., Hughes, S. M., Hughes, W. E., Humbert, M., Hummer, G., Hurley, J. H., Hussain, S., Hussey, P. J., Hutabarat, M., Hwang, H. -Y., Hwang, S., Ieni, A., Ikeda, F., Imagawa, Y., Imai, Y., Imbriano, C., Imoto, M., Inman, D. M., Inoki, K., Iovanna, J., Iozzo, R. V., Ippolito, G., Irazoqui, J. E., Iribarren, P., Ishaq, M., Ishikawa, M., Ishimwe, N., Isidoro, C., Ismail, N., Issazadeh-Navikas, S., Itakura, E., Ito, D., Ivankovic, D., Ivanova, S., Iyer, A. K. V., Izquierdo, J. M., Izumi, M., Jaattela, M., Jabir, M. S., Jackson, W. T., Jacobo-Herrera, N., Jacomin, A. -C., Jacquin, E., Jadiya, P., Jaeschke, H., Jagannath, C., Jakobi, A. J., Jakobsson, J., Janji, B., Jansen-Durr, P., Jansson, P. J., Jantsch, J., Januszewski, S., Jassey, A., Jean, S., Jeltsch-David, H., Jendelova, P., Jenny, A., Jensen, T. E., Jessen, N., Jewell, J. L., Ji, J., Jia, L., Jia, R., Jiang, L., Jiang, Q., Jiang, R., Jiang, T., Jiang, X., Jiang, Y., Jimenez-Sanchez, M., Jin, E. -J., Jin, F., Jin, H., Jin, L., Jin, M., Jin, S., Jo, E. -K., Joffre, C., Johansen, T., Johnson, G. V. W., Johnston, S. A., Jokitalo, E., Jolly, M. K., Joosten, L. A. B., Jordan, J., Joseph, B., Ju, D., Ju, J. -S., Ju, J., Juarez, E., Judith, D., Juhasz, G., Jun, Y., Jung, C. H., Jung, S. -C., Jung, Y. K., Jungbluth, H., Jungverdorben, J., Just, S., Kaarniranta, K., Kaasik, A., Kabuta, T., Kaganovich, D., Kahana, A., Kain, R., Kajimura, S., Kalamvoki, M., Kalia, M., Kalinowski, D. S., Kaludercic, N., Kalvari, I., Kaminska, J., Kaminskyy, V. O., Kanamori, H., Kanasaki, K., Kang, C., Kang, R., Kang, S. S., Kaniyappan, S., Kanki, T., Kanneganti, T. -D., Kanthasamy, A. G., Kanthasamy, A., Kantorow, M., Kapuy, O., Karamouzis, M. V., Karim, M. R., Karmakar, P., Katare, R. G., Kato, M., Kaufmann, S. H. E., Kauppinen, A., Kaushal, G. 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P., Sahay, G., Sahebkar, A., Sahin, M., Sahin, O., Sahni, S., Saito, N., Saito, S., Saito, T., Sakai, R., Sakai, Y., Sakamaki, J. -I., Saksela, K., Salazar, G., Salazar-Degracia, A., Salekdeh, G. H., Saluja, A. K., Sampaio-Marques, B., Sanchez, M. C., Sanchez-Alcazar, J. A., Sanchez-Vera, V., Sancho-Shimizu, V., Sanderson, J. T., Sandri, M., Santaguida, S., Santambrogio, L., Santana, M. M., Santoni, G., Sanz, A., Sanz, P., Saran, S., Sardiello, M., Sargeant, T. J., Sarin, A., Sarkar, C., Sarkar, S., Sarrias, M. -R., Sarmah, D. T., Sarparanta, J., Sathyanarayan, A., Sathyanarayanan, R., Scaglione, K. M., Scatozza, F., Schaefer, L., Schafer, Z. T., Schaible, U. E., Schapira, A. H. V., Scharl, M., Schatzl, H. M., Schein, C. H., Scheper, W., Scheuring, D., Schiaffino, M. V., Schiappacassi, M., Schindl, R., Schlattner, U., Schmidt, O., Schmitt, R., Schmidt, S. D., Schmitz, I., Schmukler, E., Schneider, A., Schneider, B. E., Schober, R., Schoijet, A. C., Schott, M. B., Schramm, M., Schroder, B., Schuh, K., Schuller, C., Schulze, R. J., Schurmanns, L., Schwamborn, J. C., Schwarten, M., Scialo, F., Sciarretta, S., Scott, M. J., Scotto, K. W., Scovassi, A. I., Scrima, A., Scrivo, A., Sebastian, D., Sebti, S., Sedej, S., Segatori, L., Segev, N., Seglen, P. O., Seiliez, I., Seki, E., Selleck, S. B., Sellke, F. W., Selsby, J. T., Sendtner, M., Senturk, S., Seranova, E., Sergi, C., Serra-Moreno, R., Sesaki, H., Settembre, C., Setty, S. R. G., Sgarbi, G., Sha, O., Shacka, J. J., Shah, J. A., Shang, D., Shao, C., Shao, F., Sharbati, S., Sharkey, L. M., Sharma, D., Sharma, G., Sharma, K., Sharma, P., Sharma, S., Shen, H. -M., Shen, H., Shen, J., Shen, M., Shen, W., Shen, Z., Sheng, R., Sheng, Z., Sheng, Z. -H., Shi, J., Shi, X., Shi, Y. -H., Shiba-Fukushima, K., Shieh, J. -J., Shimada, Y., Shimizu, S., Shimozawa, M., Shintani, T., Shoemaker, C. J., Shojaei, S., Shoji, I., Shravage, B. V., Shridhar, V., Shu, C. -W., Shu, H. -B., Shui, K., Shukla, A. K., Shutt, T. E., Sica, V., Siddiqui, A., Sierra, A., Sierra-Torre, V., Signorelli, S., Sil, P., Silva, B. J. D. A., Silva, J. D., Silva-Pavez, E., Silvente-Poirot, S., Simmonds, R. E., Simon, A. K., Simon, H. -U., Simons, M., Singh, A., Singh, L. P., Singh, R., Singh, S. V., Singh, S. K., Singh, S. B., Singh, S., Singh, S. P., Sinha, D., Sinha, R. A., Sinha, S., Sirko, A., Sirohi, K., Sivridis, E. L., Skendros, P., Skirycz, A., Slaninova, I., Smaili, S. S., Smertenko, A., Smith, M. D., Soenen, S. J., Sohn, E. J., Sok, S. P. M., Solaini, G., Soldati, T., Soleimanpour, S. A., Soler, R. M., Solovchenko, A., Somarelli, J. A., Sonawane, A., Song, F., Song, H. K., Song, J. -X., Song, K., Song, Z., Soria, L. R., Sorice, M., Soukas, A. A., Soukup, S. -F., Sousa, D., Sousa, N., Spagnuolo, P. A., Spector, S. A., Srinivas Bharath, M. M., S, t. Clair D., Stagni, V., Staiano, L., Stalnecker, C. A., Stankov, M. V., Stathopulos, P. B., Stefan, K., Stefan, S. M., Stefanis, L., Steffan, J. S., Steinkasserer, A., Stenmark, H., Sterneckert, J., Stevens, C., Stoka, V., Storch, S., Stork, B., Strappazzon, F., Strohecker, A. M., Stupack, D. G., Su, H., Su, L. -Y., Su, L., Suarez-Fontes, A. M., Subauste, C. S., Subbian, S., Subirada, P. V., Sudhandiran, G., Sue, C. M., Sui, X., Summers, C., Sun, G., Sun, J., Sun, K., Sun, M. -X., Sun, Q., Sun, Y., Sun, Z., Sunahara, K. K. S., Sundberg, E., Susztak, K., Sutovsky, P., Suzuki, H., Sweeney, G., Symons, J. D., Sze, S. C. W., Szewczyk, N. J., Tabecka-Lonczynska, A., Tabolacci, C., Tacke, F., Taegtmeyer, H., Tafani, M., Tagaya, M., Tai, H., Tait, S. W. G., Takahashi, Y., Takats, S., Talwar, P., Tam, C., Tam, S. Y., Tampellini, D., Tamura, A., Tan, C. T., Tan, E. -K., Tan, Y. -Q., Tanaka, M., Tang, D., Tang, J., Tang, T. -S., Tanida, I., Tao, Z., Taouis, M., Tatenhorst, L., Tavernarakis, N., Taylor, A., Taylor, G. A., Taylor, J. M., Tchetina, E., Tee, A. R., Tegeder, I., Teis, D., Teixeira, N., Teixeira-Clerc, F., Tekirdag, K. A., Tencomnao, T., Tenreiro, S., Tepikin, A. V., Testillano, P. S., Tettamanti, G., Tharaux, P. -L., Thedieck, K., Thekkinghat, A. A., Thellung, S., Thinwa, J. W., Thirumalaikumar, V. P., Thomas, S. M., Thomes, P. G., Thorburn, A., Thukral, L., Thum, T., Thumm, M., Tian, L., Tichy, A., Till, A., Timmerman, V., Titorenko, V. I., Todi, S. V., Todorova, K., Toivonen, J. M., Tomaipitinca, L., Tomar, D., Tomas-Zapico, C., Tomic, S., Tong, B. C. -K., Tong, C., Tong, X., Tooze, S. A., Torgersen, M. L., Torii, S., Torres-Lopez, L., Torriglia, A., Towers, C. G., Towns, R., Toyokuni, S., Trajkovic, V., Tramontano, D., Tran, Q. -G., Travassos, L. H., Trelford, C. B., Tremel, S., Trougakos, I. P., Tsao, B. P., Tschan, M. P., Tse, H. -F., Tse, T. F., Tsugawa, H., Tsvetkov, A. S., Tumbarello, D. A., Tumtas, Y., Tunon, M. J., Turcotte, S., Turk, B., Turk, V., Turner, B. J., Tuxworth, R. I., Tyler, J. K., Tyutereva, E. V., Uchiyama, Y., Ugun-Klusek, A., Uhlig, H. H., Ulamek-Koziol, M., Ulasov, I. V., Umekawa, M., Ungermann, C., Unno, R., Urbe, S., Uribe-Carretero, E., Ustun, S., Uversky, V. N., Vaccari, T., Vaccaro, M. I., Vahsen, B. F., Vakifahmetoglu-Norberg, H., Valdor, R., Valente, M. J., Valko, A., Vallee, R. B., Valverde, A. M., Van den Berghe, G., van der Veen, S., Van Kaer, L., van Loosdregt, J., van Wijk, S. J. L., Vandenberghe, W., Vanhorebeek, I., Vannier-Santos, M. A., Vannini, N., Vanrell, M. C., Vantaggiato, C., Varano, G., Varela-Nieto, I., Varga, M., Vasconcelos, M. H., Vats, S., Vavvas, D. G., Vega-Naredo, I., Vega-Rubin-de-Celis, S., Velasco, G., Velazquez, A. P., Vellai, T., Vellenga, E., Velotti, F., Verdier, M., Verginis, P., Vergne, I., Verkade, P., Verma, M., Verstreken, P., Vervliet, T., Vervoorts, J., Vessoni, A. T., Victor, V. M., Vidal, M., Vidoni, C., Vieira, O. V., Vierstra, R. D., Vigano, S., Vihinen, H., Vijayan, V., Vila, M., Vilar, M., Villalba, J. M., Villalobo, A., Villarejo-Zori, B., Villarroya, F., Villarroya, J., Vincent, O., Vindis, C., Viret, C., Viscomi, M. T., Visnjic, D., Vitale, I., Vocadlo, D. J., Voitsekhovskaja, O. V., Volonte, C., Volta, M., Vomero, M., Von Haefen, C., Vooijs, M. A., Voos, W., Vucicevic, L., Wade-Martins, R., Waguri, S., Waite, K. A., Wakatsuki, S., Walker, D. W., Walker, M. J., Walker, S. A., Walter, J., Wandosell, F. G., Wang, B., Wang, C. -Y., Wang, C., Wang, D., Wang, F., Wang, G., Wang, H., Wang, H. -G., Wang, J., Wang, K., Wang, L., Wang, M. H., Wang, M., Wang, N., Wang, P., Wang, Q. J., Wang, Q., Wang, Q. K., Wang, Q. A., Wang, W. -T., Wang, W., Wang, X., Wang, Y., Wang, Y. -Y., Wang, Z., Warnes, G., Warnsmann, V., Watada, H., Watanabe, E., Watchon, M., Wawrzynska, A., Weaver, T. E., Wegrzyn, G., Wehman, A. M., Wei, H., Wei, L., Wei, T., Wei, Y., Weiergraber, O. H., Weihl, C. C., Weindl, G., Weiskirchen, R., Wells, A., Wen, R. H., Wen, X., Werner, A., Weykopf, B., Wheatley, S. P., Whitton, J. L., Whitworth, A. J., Wiktorska, K., Wildenberg, M. E., Wileman, T., Wilkinson, S., Willbold, D., Williams, B., Williams, R. S. B., Williams, R. L., Williamson, P. R., Wilson, R. A., Winner, B., Winsor, N. J., Witkin, S. S., Wodrich, H., Woehlbier, U., Wollert, T., Wong, E., Wong, J. H., Wong, R. W., Wong, V. K. W., Wong, W. W. -L., Wu, A. -G., Wu, C., Wu, J., Wu, K. K., Wu, M., Wu, S. -Y., Wu, S., Wu, W. K. K., Wu, X., Wu, Y. -W., Wu, Y., Xavier, R. J., Xia, H., Xia, L., Xia, Z., Xiang, G., Xiang, J., Xiang, M., Xiang, W., Xiao, B., Xiao, G., Xiao, H., Xiao, H. -T., Xiao, J., Xiao, L., Xiao, S., Xiao, Y., Xie, B., Xie, C. -M., Xie, M., Xie, Y., Xie, Z., Xilouri, M., Xu, C., Xu, E., Xu, H., Xu, J., Xu, L., Xu, W. W., Xu, X., Xue, Y., Yakhine-Diop, S. M. S., Yamaguchi, M., Yamaguchi, O., Yamamoto, A., Yamashina, S., Yan, S., Yan, S. -J., Yan, Z., Yanagi, Y., Yang, C., Yang, D. -S., Yang, H., Yang, H. -T., Yang, J. -M., Yang, J., Yang, L., Yang, M., Yang, P. -M., Yang, Q., Yang, S., Yang, S. -F., Yang, W., Yang, W. Y., Yang, X., Yang, Y., Yao, H., Yao, S., Yao, X., Yao, Y. -G., Yao, Y. -M., Yasui, T., Yazdankhah, M., Yen, P. M., Yi, C., Yin, X. -M., Yin, Y., Yin, Z., Ying, M., Ying, Z., Yip, C. K., Yiu, S. P. T., Yoo, Y. H., Yoshida, K., Yoshii, S. R., Yoshimori, T., Yousefi, B., Yu, B., Yu, H., Yu, J., Yu, L., Yu, M. -L., Yu, S. -W., Yu, V. C., Yu, W. H., Yu, Z., Yuan, J., Yuan, L. -Q., Yuan, S., Yuan, S. -S. F., Yuan, Y., Yuan, Z., Yue, J., Yue, Z., Yun, J., Yung, R. L., Zacks, D. N., Zaffagnini, G., Zambelli, V. O., Zanella, I., Zang, Q. S., Zanivan, S., Zappavigna, S., Zaragoza, P., Zarbalis, K. S., Zarebkohan, A., Zarrouk, A., Zeitlin, S. O., Zeng, J., Zeng, J. -D., Zerovnik, E., Zhan, L., Zhang, B., Zhang, D. D., Zhang, H., Zhang, H. -L., Zhang, J., Zhang, J. -P., Zhang, K. Y. B., Zhang, L. W., Zhang, L., Zhang, M., Zhang, P., Zhang, S., Zhang, W., Zhang, X., Zhang, X. -W., Zhang, X. D., Zhang, Y., Zhang, Y. -D., Zhang, Y. -Y., Zhang, Z., Zhao, H., Zhao, L., Zhao, S., Zhao, T., Zhao, X. -F., Zhao, Y., Zheng, G., Zheng, K., Zheng, L., Zheng, S., Zheng, X. -L., Zheng, Y., Zheng, Z. -G., Zhivotovsky, B., Zhong, Q., Zhou, A., Zhou, B., Zhou, C., Zhou, G., Zhou, H., Zhou, J., Zhou, K., Zhou, R., Zhou, X. -J., Zhou, Y., Zhou, Z. -Y., Zhou, Z., Zhu, B., Zhu, C., Zhu, G. -Q., Zhu, H., Zhu, W. -G., Zhu, Y., Zhuang, H., Zhuang, X., Zientara-Rytter, K., Zimmermann, C. M., Ziviani, E., Zoladek, T., Zong, W. -X., Zorov, D. B., Zorzano, A., Zou, W., Zou, Z., Zuryn, S., Zwerschke, W., Brand-Saberi, B., Dong, X. C., Kenchappa, C. S., Lin, Y., Oshima, S., Rong, Y., Sluimer, J. C., Stallings, C. L., Tong, C. -K., and Centre National de la Recherche Scientifique (CNRS)
Subjects: 0301 basic medicine, Programmed cell death, Settore BIO/06, Autophagosome, Autolysosome, [SDV]Life Sciences [q-bio], lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], Autophagy-Related Proteins, Review, Computational biology, [SDV.BC]Life Sciences [q-bio]/Cellular Biology, Biology, Settore MED/04, 03 medical and health sciences, stress, Chaperone-mediated autophagy, ddc:570, Autophagy, LC3, Animals, Humans, cancer, Settore BIO/10, flux, lysosome, macroautophagy, neurodegeneration, phagophore, vacuole, Set (psychology), Molecular Biology, 030102 biochemistry & molecular biology, business.industry, Interpretation (philosophy), Autophagosomes, Cell Biology, Multicellular organism, 030104 developmental biology, Knowledge base, Biological Assay, Lysosomes, business, Biomarkers, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract: Contains fulltext : 232759.pdf (Publisher’s version ) (Closed access) In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
Published: 2021

24. Perfluorodioxolane Polymers for Gas Separation Membrane Applications

Author: Timothy C. Merkel, Fang Minfeng, Michele Galizia, Yoshiyuki Okamoto, Milad Yavari, Hao-Chun Chiang, Hien Nguyen, and Haiqing Lin
Subjects: Materials science, Filtration and Separation, 02 engineering and technology, Review, lcsh:Chemical technology, 010402 general chemistry, 01 natural sciences, chemistry.chemical_compound, Chemical Engineering (miscellaneous), Microelectronics, lcsh:TP1-1185, Gas separation, lcsh:Chemical engineering, Solubility, gas separation, membrane, chemistry.chemical_classification, business.industry, Process Chemistry and Technology, amorphous perfluorodioxolane polymers, lcsh:TP155-156, Polymer, 021001 nanoscience & nanotechnology, 0104 chemical sciences, Amorphous solid, Membrane, chemistry, Chemical engineering, Tetrafluoroethylene, Hexafluoropropylene, 0210 nano-technology, business
Abstract: Since the discovery of polytetrafluoroethylene (PTFE) in 1938, fluorinated polymers have drawn attention in the chemical and pharmaceutical field, as well as in optical and microelectronics applications. The reasons for this attention are their high thermal and oxidative stability, excellent chemical resistance, superior electrical insulating ability, and optical transmission properties. Despite their unprecedented combination of desirable attributes, PTFE and copolymers of tetrafluoroethylene (TFE) with hexafluoropropylene and perfluoropropylvinylether are crystalline and exhibit poor solubility in solvents, which makes their processability very challenging. Since the 1980s, several classes of solvent-soluble amorphous perfluorinated polymers showing even better optical and gas transport properties were developed and commercialized. Amorphous perfluoropolymers exhibit, however, moderate selectivity in gas and liquid separations. Recently, we have synthesized various new perfluorodioxolane polymers which are amorphous, soluble, chemically and thermally stable, while exhibiting much enhanced selectivity. In this article, we review state-of-the-art and recent progress in these perfluorodioxolane polymers for gas separation membrane applications.
Published: 2020

25. Does using high-tensile strength tape improve the fixation strength in tendon graft fixation with needleless suture wrapping techniques compared to a suture?

Author: Wei Ren Su, Hao Chun Chuang, Yueh Chen, Fa Chuan Kuan, Chen Hao Chiang, Kai Lan Hsu, and Chih Kai Hong
Subjects: Swine, Tendons, 03 medical and health sciences, Fixation (surgical), 0302 clinical medicine, lcsh:Orthopedic surgery, Tensile Strength, Ultimate tensile strength, medicine, Animals, Orthopedic Procedures, Tendon graft, Orthodontics, Fibrous joint, 030222 orthopedics, Sutures, business.industry, Suture Techniques, 030229 sport sciences, Plastic Surgery Procedures, Biomechanical Phenomena, lcsh:RD701-811, medicine.anatomical_structure, Models, Animal, Surgery, business
Abstract: Purpose: To compare the biomechanical properties of a high-tensile strength suture and high-tensile strength tape in tendon graft fixation using two needleless suture wrapping techniques, the modified Prusik knot and modified rolling hitch. Methods: Two needleless suture wrapping techniques, the modified rolling hitch (MR) and modified Prusik knot (MP), were utilized. Meanwhile, two kinds of suture materials, a No. 2 braided nonabsorbable high-strength suture (S) and a 1.3 mm high-tensile strength tape (T), were used. A total of 40 porcine tendons were used, which were randomly divided into four groups. Each group was assigned to one of the following groups: MRS, MRT, MPS, and MPT. Each specimen was pretensioned to 100 N for three cycles, cyclically loaded from 50 to 200 N for 200 cycles, and finally loaded to failure. Results: The MRT group (34.1 ± 3.5%) had a significantly higher value compared with the MRS (29.7 ± 2.3%), MPS (27.1 ± 3.6%) and MPT (29.5 ± 4.0%) groups in term of elongation after cyclic loadings ( p = 0.002). In terms of ultimate failure load, there were no significant differences in the MRS (401 ± 27 N), MRT (380 ± 27 N), MPS (398 ± 44 N) and MPT (406 ± 49 N) values ( p = 0.539). All specimens failed due to suture breakage at the knots. Conclusion: Compared with the high-tensile strength suture, using the high-tensile strength tape lead to greater elongation after cyclic loading when the modified rolling hitch was used. No differences in terms of elongation after cyclic loading and load to failure were found between the high-tensile strength suture and tape using the modified Prusik knot.
Published: 2020

26. Behavior Score-Embedded Brain Encoder Network for Improved Classification of Alzheimer Disease Using Resting State fMRI

Author: Chi-Chun Lee, Jeremy Lefort-Besnard, Li-Wei Kuo, Hao-Chun Yang, and Wan-Ting Hsieh
Subjects: Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Clinical Dementia Rating, Machine Learning (cs.LG), 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, Alzheimer Disease, FOS: Electrical engineering, electronic engineering, information engineering, medicine, Dementia, Humans, Psychological testing, Cognitive Dysfunction, Electrical Engineering and Systems Science - Signal Processing, Resting state fMRI, medicine.diagnostic_test, business.industry, Brain, Pattern recognition, Magnetic resonance imaging, medicine.disease, Autoencoder, Magnetic Resonance Imaging, 030227 psychiatry, Artificial intelligence, Alzheimer's disease, business, Tomography, X-Ray Computed, 030217 neurology & neurosurgery
Abstract: The ability to accurately detect onset of dementia is important in the treatment of the disease. Clinically, the diagnosis of Alzheimer Disease (AD) and Mild Cognitive Impairment (MCI) patients are based on an integrated assessment of psychological tests and brain imaging such as positron emission tomography (PET) and anatomical magnetic resonance imaging (MRI). In this work using two different datasets, we propose a behavior score-embedded encoder network (BSEN) that integrates regularly adminstrated psychological tests information into the encoding procedure of representing subject's restingstate fMRI data for automatic classification tasks. BSEN is based on a 3D convolutional autoencoder structure with contrastive loss jointly optimized using behavior scores from MiniMental State Examination (MMSE) and Clinical Dementia Rating (CDR). Our proposed classification framework of using BSEN achieved an overall recognition accuracy of 59.44% (3-class classification: AD, MCI and Healthy Control), and we further extracted the most discriminative regions between healthy control (HC) and AD patients., 4 pages, 1 figure
Published: 2020

27. Automatic Identification of First-Order Veins and Corolla Contours in Three-Dimensional Floral Images

Author: Yi-Hsiang Wang, Yan-Fu Kuo, Wen-Chieh Chou, Hao-Chun Hsu, and Chia-Hao Liang
Subjects: business.industry, pollination type, three-dimensional image, first-order veins, Pattern recognition, Plant Science, Gesneriaceae, lcsh:Plant culture, venation, First order, Thresholding, Ligeriinae, Didymocarpinae, Gloxiniinae, corolla contours, floral traits, Methods, lcsh:SB1-1110, Artificial intelligence, Detection rate, business, Mathematics
Abstract: Defining and quantifying corolla traits are essential for studying corolla shape variation. Three-dimensional (3D) images of corollas contain comprehensive information regarding corolla structures and are optimal for studying corolla shapes. Conventionally, corolla traits are identified and quantified manually from 3D images. Manual identification is time consuming and labor intensive. In this study, approaches are proposed to automatically identify first-order veins and corolla contours in 3D corolla images. The first-order veins of the corollas were identified using Hessian of Gaussian and Dijkstra’s algorithm. The contours of the corollas were identified using vector harmony and node distance thresholding. A total of 130 3D images of 28 species in the subtribe Ligeriinae were collected and used to test the proposed approaches. The successful detection rate reached 86.54%. Two derived traits, contour–vein ratio and corolla angle, were defined and quantified using the first-order veins and corolla contour results to investigate the relationship between corolla shapes and pollination types of the subtribe Ligeriinae. Analyses revealed that the mean corolla contour, mean absolute corolla angle, and mean contour–vein ratio of the ornithophilic species were significantly smaller compared with the other species. The mean corolla contour, mean corolla angle, and mean contour–vein ratio of the melittophilic species were significantly larger compared with those of the ornithophilic species. The proposed method was also applied to certain Gesneriaceae species in the subtribes Gloxiniinae, Streptocarpinae, and Didymocarpinae. The results revealed that the method could be applied to most fresh sympetalous flowers for identifying first-order veins and corolla contours.
Published: 2020

28. Pulmonary pleomorphic carcinoma with pembrolizumab monotherapy

Author: Chia-Lin Hsu, Chong-Jen Yu, Hao-Chun Chang, and Yih-Leong Chang
Subjects: Pulmonary and Respiratory Medicine, Oncology, medicine.medical_specialty, medicine.medical_treatment, Case Report, Pembrolizumab, Case Reports, Pleomorphic carcinoma, pleomorphic carcinoma, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Medicine, Lung cancer, lcsh:RC705-779, business.industry, Immunotherapy, lcsh:Diseases of the respiratory system, medicine.disease, body regions, 030228 respiratory system, 030220 oncology & carcinogenesis, Adenocarcinoma, pembrolizumab, business
Abstract: Adenocarcinoma (ADC) is the most common form of lung cancer; however, some other types of lung cancer can sometimes mimic ADC. It then takes experienced pathologists and special stains to make the correct diagnosis. Here, we present a patient with pulmonary pleomorphic carcinoma who was misdiagnosed with ADC, and was treated with pembrolizumab for 13 months. The diagnosis and treatment (including immunotherapy) are also reviewed., Adenocarcinoma (ADC) is the most common form of lung cancer; however, some other types of lung cancer, such as pulmonary pleomorphic carcinoma (PC), can sometimes mimic ADC. Here, we present a patient with initial diagnosis of pulmonary ADC later diagnosed with PC.
Published: 2020

29. Oxidative stress mediates age-related hypertrophy of ligamentum flavum by inducing inflammation, fibrosis, and apoptosis through activating Akt and MAPK pathways

Author: Yan Jye Shyong, Yuan-Fu Liu, Kun-Ling Tsai, Cheng Li Lin, I-Ming Jou, Kuen Jer Tsai, Hao-Chun Chuang, Che-Chia Hsu, Ting Yuan Tu, and Shu-Shien Shih
Subjects: MAPK/ERK pathway, Adult, Male, Aging, Vimentin, Inflammation, Apoptosis, medicine.disease_cause, Muscle hypertrophy, Spinal Stenosis, Fibrosis, medicine, Humans, oxidative stress, Protein kinase B, Cells, Cultured, Aged, biology, business.industry, fibrosis, Age Factors, Cell Biology, Hydrogen Peroxide, Hypertrophy, Middle Aged, medicine.disease, Ligamentum Flavum, inflammation, biology.protein, Cancer research, Female, medicine.symptom, Inflammation Mediators, Mitogen-Activated Protein Kinases, business, Apoptosis Regulatory Proteins, ligamentum flavum hypertrophy, Proto-Oncogene Proteins c-akt, Oxidative stress, Intervertebral Disc Displacement, Signal Transduction, Research Paper
Abstract: The role of oxidative stress in ligamentum flavum (LF) hypertrophy has not been elucidated. We hypothesize that oxidative stress induces inflammatory responses and the subsequent fibrotic processes in LF, via activation of the Akt and MAPK pathways. Specimens of LFs were collected during surgeries for lumbar disc herniation (LDH) or lumbar spinal stenosis (LSS). Part of the LF specimens underwent analyses for ROS, fibrotic markers, and inflammatory mediators, with the remainder minced for cell cultures. The cell cultures were treated with H2O2, after which the cells were lysed and analyzed via western blotting. The specimens of the LSS patients showed increased infiltration of inflammatory cells and were stained positively for MMP-3, MMP-9, vimentin, and fibronectin. The LF of the LSS patients had increased oxidative stress and inflammation compared to that of the LDH patients. In vitro analyses demonstrated that oxidative stress rapidly activated the Akt and MAPK pathways. Inflammatory mediators, iNOS and NF-κB, and fibrotic markers, including TGF-β, β-catenin, α-SMA and vimentin, were significantly upregulated after induction of oxidative stress. Oxidative stress activated the intrinsic apoptotic pathway. These findings revealed that oxidative stress is one of the etiological factors of LF hypertrophy, which might provide new insights into treatment approaches.
Published: 2020

30. Conditional Domain Adversarial Transfer for Robust Cross-Site ADHD Classification Using Functional MRI

Author: Wan-Ting Hsieh, Ya-Lin Huang, Chi-Chun Lee, and Hao-Chun Yang
Subjects: medicine.diagnostic_test, Generalization, business.industry, Computer science, Machine learning, computer.software_genre, Domain (software engineering), Visualization, 03 medical and health sciences, 0302 clinical medicine, Discriminative model, 030225 pediatrics, medicine, Artificial intelligence, Scale (map), Representation (mathematics), business, Functional magnetic resonance imaging, computer, 030217 neurology & neurosurgery
Abstract: There is a growing number of large scale cross-site database collection of resting-state functional magnetic resonance imaging (rs-fMRI) for studying neurobehavioral diseases, such as ADHD. Although a large amount of data benefits machine learning-based classification methods, the idiosyncratic variability of each site can deteriorate cross-site generalization ability. This challenge creates a bottleneck in requiring a large number of labeled samples of each site. Hence in this research, we utilize an approach of conditional adversarial domain adaptation network (CDAN) to learn a discriminative fMRI representation that is site-invariant for unsupervised transfer of ADHD classification. We evaluate our framework on a multi-site ADHD dataset and achieve improvement in transferring between sites. Further visualization reveals that there indeed exists a substantial site discrepancy and statistically analysis indicates that male’s rs-fMRI could be more vulnerable toward site-specific effects.
Published: 2020

31. Primary signet ring cell carcinoma of colon and rectum often presents as long segment stenosis in young patients

Author: Jau-Min Wong, Shu Chen Wei, Ko-Han Chao, Meng Tzu Weng, Chia-Tung Shun, Been-Ren Lin, I-Lun Shih, Chien-Chih Tung, Ming-Jium Shieh, and Hao-Chun Chang
Subjects: medicine.medical_specialty, Stenosis, medicine.anatomical_structure, business.industry, Signet ring cell carcinoma, medicine, Rectum, Radiology, medicine.disease, Long segment, business
Abstract: Background: Primary signet ring cell carcinoma of the colon and rectum (PSRCCR) is rare, usually diagnosed at advanced stage with poor outcomes. We aimed to find possible diagnostic clues in order to help diagnosis. Methods: A retrospective study of PSRCCR patients from 1993 to 2018 was reviewed at a single tertiary center. Colorectal adenocarcinoma patients as control group with 1:4 ratio was also enrolled. Results: 18 patients with PSRCCR were identified. The prevalence rate was 0.16% (18 of 11,515). The mean age was 50.2 years-old in PSRCCR group and 63 years-old in non-SRCC colorectal cancer patients ( p < 0.001). Diagnosis tool depends on CFS were much less in PSRCCR group than control group (44.4 % vs 93 %, p < 0.001). SRCC patients had higher level of CEA (68.3 vs 17.7 ng/mL, p =0.004) and lower level of Albumin (3.4 vs 4.3 g/dL, p < 0.001). The majority of PSRCCR tumor configuration was ulcerative and infiltrative. More PSRCCR pathology presented as high-grade carcinoma (66.7 vs 1.4 %, p < 0.001) and lymphovascular invasion (77.8 vs 44.4 %, p = 0.011) than control group. More PSRCCR patients were diagnosed at advanced stage (88.8 vs 40.3 %, p = 0.001). Higher mortality was also noticed in PSRCCR group than control group (72.2 vs 20.8 %, p < 0.001). Conclusion: For young patients with long segment colonic stenosis and ulcerative/ infiltrative mucosa but endoscopic biopsy failed to identify malignant cells, earlier operation or non-colon site biopsy is suggested for diagnosing the PSRCCR.
Published: 2020

32. Postrhinoplasty Infection With Residual Expanded Polytetrafluoroethylene-Coated Silicone Implantation

Author: Hsing-Mei Wu, Ying-Shuo Hsu, Chung-Yu Hao, Yu-Hsun Chiu, and Hao-Chun Hu
Subjects: Reoperation, Prosthesis-Related Infections, medicine.medical_treatment, Silicones, Biocompatible Materials, Expanded polytetrafluoroethylene, Prosthesis Design, Rhinoplasty, Prosthesis Implantation, chemistry.chemical_compound, Silicone, medicine, Humans, Polytetrafluoroethylene, Device Removal, business.industry, Middle Aged, Foreign Bodies, Anti-Bacterial Agents, Otorhinolaryngology, chemistry, Surgery, Female, business, Biomedical engineering
Published: 2020

33. A Global Method for a Two-Dimensional Cutting Stock Problem in the Manufacturing Industry

Author: Yu-Fang Chang, Yun-Cheng Wang, Yao-Huei Huang, Chun-Kai Gao, and Hao-Chun Lu
Subjects: Computer science, business.industry, Cutting stock problem, Manufacturing, InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, Data_FILES, business, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), Manufacturing engineering
Published: 2020

34. Perfluoropolymers for gas separation membrane applications

Author: Hao-Chun Chiang, Yoshiyuki Okamoto, and Timothy C. Merkel
Subjects: chemistry.chemical_classification, Chemical resistance, Polytetrafluoroethylene, Materials science, business.industry, Nanotechnology, Polymer, Amorphous solid, chemistry.chemical_compound, chemistry, Microelectronics, Tetrafluoroethylene, Gas separation, Hexafluoropropylene, business
Abstract: Since the discovery of polytetrafluoroethylene (PTFE) in 1937, fluorinated polymers have attracted interest in the chemical and pharmaceutical industry, as well as in opto- and microelectronics. The reasons of this attention are their high thermal and oxidative stability, exceptional chemical resistance, superior electrical insulating ability and optical properties. Despite their unprecedented combination of thermal, mechanical, optical and transport properties, PTFE and copolymers of tetrafluoroethylene (TFE) with hexafluoropropylene and perfluoropropylvinylether are crystalline and exhibit poor solubility in solvents, which makes their processability very challenging. Since 1989, new classes of solvent-soluble amorphous perfluorinated polymers exhibiting even better optical and transport properties were developed and commercialized. In this contribution, we outline the state-of-the-art and recent progress in perfluoropolymers for gas separation membrane applications.
Published: 2020

35. Construction and mechanism analysis on nanoscale thermal cloak by in-situ annealing silicon carbide film

Author: Jian Zhang, Ziliang Huang, Hao-chun Zhang, Yiyi Li, and Wen-bo Sun
Subjects: Materials science, business.industry, Graphene, Phonon, Cloak, General Physics and Astronomy, Cloaking, law.invention, chemistry.chemical_compound, Thermal conductivity, chemistry, law, Thermal, Silicon carbide, Optoelectronics, Crystalline silicon, business
Abstract: In recent years, there is a strong interest in thermal cloaking at the nanoscale, which has been achieved by using graphene and crystalline silicon films to build the nanoscale thermal cloak according to the classical macroscopic thermal cloak model. Silicon carbide, as a representative of the third-generation semiconductor material, has splendid properties, such as the high thermal conductivity and the high wear resistance. Therefore, in the present study, we build a nanoscale thermal cloak based on silicon carbide. The cloaking performance and the perturbation of the functional area to the external temperature filed are analyzed by the ratio of thermal cloaking and the response temperature, respectively. It is demonstrated that silicon carbide can also be used to build the nanoscale thermal cloak. Besides, we explore the influence of inner and outer radius on cloaking performance. Finally, the potential mechanism of the designed nanoscale thermal cloak is investigated by calculating and analyzing the phonon density of states (PDOS) and mode participation rate (MPR) within the structure. We find that the main reason for the decrease in the thermal conductivity of the functional area is phonon localization. This study extends the preparation method of nanoscale thermal cloaks and can provide a reference for the development of other nanoscale devices.
Published: 2022

36. Addressing endogeneity in operations management research: Recent developments, common problems, and directions for future research

Author: Guanyi Lu, David Xiaosong Peng, Howard Hao-Chun Chuang, and Xin Ding
Subjects: business.industry, Strategy and Management, media_common.quotation_subject, 05 social sciences, Instrumental variable, Management Science and Operations Research, Industrial and Manufacturing Engineering, Empirical research, 0502 economics and business, Health care, Economics, 050211 marketing, Operations management, Quality (business), Endogeneity, business, 050203 business & management, media_common
Abstract: Addressing endogeneity can be a challenging task given the different sources of endogeneity and their impacts on empirical results. While premier business journals typically expect authors to rigorously address endogeneity, this expectation is relatively new to many Operations Management (OM) scholars, as exemplified by a recent editorial in Journal of Operations Management that calls for more rigorous treatment for endogeneity. This study serves two purposes. First, we summarize recent OM literature with respect to the treatment for endogeneity by reviewing studies published in leading OM journals between 2012 and 2017. The review provides evidence that endogeneity problems have received increasing attention from OM scholars. However, we also find some common problems that may render the chosen techniques for addressing endogeneity less effective and potentially lead to biased analysis results. Second, since instrumental variable regression is the most prevalent technique for dealing with endogeneity in the OM literature according to our review, we provide an empirical illustration tailored to OM researchers for using instrumental variable regression in the post-design (data analysis) phase. Using variables from a publicly available healthcare dataset, our analysis sheds light on the importance of examining instruments' quality and triangulating results based on more than one test/estimator.
Published: 2018

37. Long-term results of palatal implantation for severe obstructive sleep apnea patients with prominent retropalatal collapse

Author: Szu-Chi Chen, Hao-Chun Hu, Tao-Hsin Tung, Lieber Po-Hung Li, and Chin-Lung Kuo
Subjects: Adult, Male, Visual Analog Scale, Visual analogue scale, Prosthesis Implantation, 03 medical and health sciences, 0302 clinical medicine, Respiratory disturbance index, medicine, Humans, 030223 otorhinolaryngology, Collapse (medical), Sleep Apnea, Obstructive, lcsh:R5-920, Continuous Positive Airway Pressure, Sleep surgery, business.industry, Epworth Sleepiness Scale, Snoring, General Medicine, Long term results, Middle Aged, medicine.disease, Obstructive sleep apnea, Subjective data, Anesthesia, Palate, Soft, medicine.symptom, business, lcsh:Medicine (General), 030217 neurology & neurosurgery
Abstract: Background: Most previous reports on palatal implantation for patients with severe obstructive sleep apnea have been anecdotal. Our objective in this study was to assess the long-term outcomes of palatal implantations from objective as well as subjective perspectives when applied to patients with severe obstructive sleep apnea and prominent retropalatal collapse. Methods: This retrospective review was conducted in a single institution using subjective data (Epworth Sleepiness Scale and visual analog scales of snoring sounds and sleep quality) and objective data (respiratory disturbance index, minimum O2 saturation, sleep efficiency, and snoring index using a polysomnograph) before and after surgery. A total of ten patients were enrolled in this study. The median time between pre-operative sleep-related tests and the operation date was 1.0 months and the median time between operation date and post-operative sleep-related tests was 33.0 months. Results: Significant improvements were observed in the visual analog scale scores of snoring (p = 0.004), visual analog scale scores of sleep quality (p = 0.005), and Epworth Sleepiness Scale (p = 0.012). Eight of the ten patients reported a reduction of at least 50% on the visual analog scale of snoring sounds, which was the criterion of subjective surgical success. We also observed significant improvements in the respiratory disturbance index (p = 0.009) and minimum O2 saturation (p = 0.033). Two of the ten patients presented a reduction in respiratory disturbance index of ≥50% and a subsequent respiratory disturbance index of
Published: 2018

38. Dermatomyositis Induced by Filler Rhinoplasty Using Liquid Silicone

Author: Yu-Hsun Chiu, Hsiao-Yun Cho, and Hao-Chun Hu
Subjects: Filler (packaging), Time Factors, Erythema, business.industry, medicine.medical_treatment, Silicones, Dentistry, Dermatomyositis, Middle Aged, medicine.disease, Rhinoplasty, Autoimmune Diseases, chemistry.chemical_compound, Silicone, Otorhinolaryngology, chemistry, Dermal Fillers, medicine, Humans, Surgery, Female, medicine.symptom, business, Immunosuppressive Agents
Published: 2019

39. A predictive investigation of first-time customer retention in online reservation services

Author: Yen-Chun Chou and Howard Hao-Chun Chuang
Subjects: Service (business), E-services, Customer retention, business.industry, Computer science, Strategy and Management, 05 social sciences, Reservation, 02 engineering and technology, Service provider, Ensemble learning, Data science, Test case, Analytics, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, 050211 marketing, 020201 artificial intelligence & image processing, Business and International Management, business
Abstract: This paper reports a predictive investigation of first-time customer retention in an emerging service business—online reservation services. We work with an online platform that enables customers to make reservations for various types of restaurants. With numerous first-time users on the platform, the focal company is eager to effectively identify recurring customers. However, the business problem is challenging due to that each first-time customer has one and only one booking record hinders the use of well-established marketing models that demand multiple booking records for a customer. By analyzing more than 100,000 observations, we extract booking-related features that are useful in predicting first-time customer retention. Our feature extraction is potentially applicable to other service sectors (e.g., hotel, travel) with similar booking information fields (e.g., reservation timing, party size). We further conduct a comparative study in which surprisingly, the seemingly simplistic generalized additive model (GAM) for our test cases consistently outperforms computationally intensive ensemble learning methods, even the cutting-edge XGBoost. Our analysis indicates that there is no silver bullet for applied predictive modeling and GAM should definitely be included in the arsenal of business researchers. We conclude by discussing the implications of our study for online service providers and business data analytics.
Published: 2018

40. Flexible random lasers with tunable lasing emissions

Author: Hao Chun Kuo, Ting Wei Yeh, Yung Chi Yao, Meng-Tsan Tsai, Ya Ju Lee, Thi Bich Hanh Nguyen, Zu Po Yang, and Chun Yang Chou
Subjects: Materials science, Random laser, Active laser medium, business.industry, Scattering, Physics::Optics, 02 engineering and technology, Substrate (electronics), 021001 nanoscience & nanotechnology, Laser, 01 natural sciences, Light scattering, law.invention, 010309 optics, law, 0103 physical sciences, Optoelectronics, General Materials Science, 0210 nano-technology, business, Lasing threshold, Localized surface plasmon
Abstract: In this study, we experimentally demonstrated a flexible random laser fabricated on a polyethylene terephthalate (PET) substrate with a high degree of tunability in lasing emissions. Random lasing oscillation arises mainly from the resonance coupling between the emitted photons of gain medium (Rhodamine 6G, R6G) and the localized surface plasmon (LSP) of silver nanoprisms (Ag NPRs), which increases the effective cross-section for multiple light scattering, thus stimulating the lasing emissions. More importantly, it was found that the random lasing wavelength is blue-shifted monolithically with the increase in bending strains exerted on the PET substrate, and a maximum shift of ∼15 nm was achieved in the lasing wavelength, when a 50% bending strain was exerted on the PET substrate. Such observation is highly repeatable and reversible, and this validates that we can control the lasing wavelength by simply bending the flexible substrate decorated with the Ag NPRs. The scattering spectrum of the Ag NPRs was obtained using a dark-field microscope to understand the mechanism for the dependence of the wavelength shift on the exerted bending strains. As a result, we believe that the experimental demonstration of tunable lasing emissions based on the revealed structure is expected to open up a new application field of random lasers.
Published: 2018

41. Association between Insufficient Interleukin-6 (IL-6) Inhibition and Worsening Outcomes in COVID-19 and Idiopathic Multicentric Castleman Disease (iMCD), and a Mathematical Model to Predict Optimal Dosing to Completely Block IL-6 Activity

Author: Zhao-Yang Lu, Jean-François Rossi, Bernard Klein, Chiang Hao-Chun, David C. Fajgenbaum, Karan Kanhai, Frits van Rhee, and Kalle Levon
Subjects: medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), biology, business.industry, Immunology, Cell Biology, Hematology, 803.Emerging Diagnostic Tools and Techniques, Biochemistry, Gastroenterology, Internal medicine, Block (telecommunications), biology.protein, Medicine, Dosing, Multicentric Castleman Disease, business, Interleukin 6
Abstract: Dysregulated inflammatory responses are characterized by inappropriate levels of inflammatory markers, speed of generation, degree, and major site of production, such as a vital organ. COVID-19 severity and mortality are strongly associated with interleukin (IL)-6 levels. High IL-6 levels are also observed in idiopathic Multicentric Castleman Disease (iMCD). Previously, we developed the first anti-IL-6 monoclonal antibody (mAb) treatments and showed that C-reactive protein (CRP) production could be fully controlled by IL-6 in humans. Using mathematical modeling, with CRP as an IL-6 surrogate marker, we predicted the ability of an anti-IL-6 mAb to block plasma IL-6 activity and showed IL-6 inhibition was dependent on the extent of whole-body IL-6 production. We postulate that in patients (pts) in whom IL-6 concentration at the site of inflammation is higher than in the plasma, full blockade of plasma IL-6 activity, shown by complete CRP inhibition, is the minimum requirement to achieve clinical efficacy. CRP inhibition with tocilizumab (TCZ) in pts with COVID-19. We identified 35 published studies evaluating the efficacy or potential role of anti-IL-6 therapy in pts with severe COVID-19. Surprisingly, only one (Luo et al. J Med Virol 2020;92:814) reported dynamics of CRP reduction for individual patients throughout treatment. We fitted a hypothetical curve of CRP reduction required to completely block IL-6, based on the half-life of CRP, and added data points of CRP serum levels from pts treated with anti-IL-6 receptor (IL-6R) therapy, TCZ, in this study. Complete reduction of CRP was not achieved in all patients: 3 pts who died had CRP levels ≥12.8 mg/l. Of 2 pts whose disease worsened, CRP levels were 93.5 mg/l and 6.3 mg/l. However, pts whose condition stabilized (n=9), or whose symptoms improved (n=1), had CRP levels close to the theoretical curve that is likely required to fully block IL-6 (CRP levels ≤5.0 mg/l). Half of these pts had been given repeated doses of TCZ. Siltuximab (SIL) treatment (NCT01024036 trial) for pts with iMCD. To assess the impact of baseline CRP levels on response to anti-IL-6 therapy, SIL, patients were divided into low and high CRP groups based on a baseline CRP level threshold of 40 mg/l (corresponding to ~40 pg/ml of IL-6; Fig 1). In patients with low baseline CRP levels (40 mg/l; n=17), CRP levels were significantly reduced on day 8 (n=17; P Inhibition of IL-6 activity by anti-IL-6 (SIL 700 mg) and anti-IL-6R (TCZ 800 mg) as monotherapy, intensified, or combined therapy. To evaluate the effect of therapy on IL-6 activity, our algorithm modeled inhibition of IL-6-(IL-6R/soluble IL-6R)-gp130 transducer complexes. This serves as a proxy for IL-6 bioactivity and accounts for the buffering capacity of gp130, which can be overwhelmed in inflammatory situations with high IL-6 concentrations. Due to uncertainty over the concentration of mAbs in alveoli relative to plasma, we modeled the effects of SIL and TCZ at local concentrations of 100%, 10%, and 1% (Fig 2) of those in plasma. Our model demonstrated that anti-IL-6 was associated with stronger inhibition of CRP than anti-IL-6R. However, only the association of both anti-IL-6 and anti-IL-6R mAbs was associated with a total blockade of CRP, which is probably necessary when IL-6 levels are associated with high risk to the patient. Different administration schedules to intensify anti-IL-6 therapy were modeled, including the repeated or combined use of anti-IL-6 and anti-IL-6R mAbs. The results form a basis to optimize treatment strategies to avoid the cytokine storm in several diseases, including cancer, iMCD, and autoimmune disorders. The feasibility of the theoretically defined approaches needs to be evaluated, particularly the potential side-effect profile for a combined treatment approach. In conclusion, in clinical practice, IL-6 inhibition should be individualized based on pathophysiology and regular CRP monitoring. Figure 1 Figure 1. Disclosures Rossi: E-SANA Inc: Other: Co-founder of E-SANA Inc ; EUSA Pharma: Consultancy; LEO Pharma: Consultancy; NPO Petrovax Pharm: Consultancy. Levon: E-SANA Inc: Other: Co-founder of E-SANA Inc. Kanhai: EUSA Pharma: Current Employment. Fajgenbaum: EUSA Pharma: Research Funding; N/A: Other: Holds pending provisional patents for 'Methods of treating idiopathic multicentric Castleman disease with JAK1/2 inhibition' and 'Discovery and validation of a novel subgroup and therapeutic target in idiopathic multicentric Castleman disease'; Pfizer: Other: Study drug for clinical trial of sirolimus. OffLabel Disclosure: Siltuximab is approved for the treatment of iMCD. Tocilizumab is approved for the treatment of Rheumatoid arthritis, Giant cell arteritis, Cytokine release syndrome, Systemic juvenile idiopathic arthritis and Polyarticular juvenile idiopathic arthritis. Combination therapy using Siltuximab and Tocilizumab has not yet been approved.
Published: 2021

42. Cooperative control framework of the wind turbine generators and the compressed air energy storage system for efficient frequency regulation support

Author: Hao-Chun Zhang, Said I. Abouzeid, and Yufeng Guo
Subjects: Frequency response, Wind power, Compressed air energy storage, business.industry, Computer science, 020209 energy, media_common.quotation_subject, 020208 electrical & electronic engineering, Mode (statistics), Energy Engineering and Power Technology, 02 engineering and technology, Inertia, Turbine, Automotive engineering, Limit (music), 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, business, MATLAB, computer, media_common, computer.programming_language
Abstract: This paper presents a cooperative control framework of the wind energy conversion system (WECS) and the compressed air energy storage (CAES). The proposed framework is mainly based on the coordination between the two units to improve the overall frequency response and mitigate the impacts of wind power uncertainty. Besides, the presented coordination aims to resolve the contradiction issue between the speed recovery system and the frequency regulation signal in the WECS. Accordingly, the CAES is involved in the frequency regulation under simultaneous charging and discharging mode to act as a complement unit of the WECS which assist to take the benefits of WECS fast inertia support and recompense the WECS limitations from obeying the load demand. The effectiveness of the proposed coordination has been examined under different scenarios and load profiles by using MATLAB/SIMULINK simulation. The results have confirmed the ability of the proposed coordination to improve the system frequency response compared to the uncoordinated control operations. Furthermore, the proposed control is able to limit effectively the impacts of the load and wind power fluctuations in the system frequency.
Published: 2021

43. Study on the Reduction of Radon Exhalation Rates of Concrete with Different Activated Carbon

Author: Yang Wang, Chun Yong Yang, Gui Qiang Li, Hao Chun Yan, and Yong Gui Zhang
Subjects: Materials science, Shell (structure), chemistry.chemical_element, Radon exhalation, 02 engineering and technology, 01 natural sciences, Adsorption, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, medicine, General Materials Science, Coal, Composite material, 010308 nuclear & particles physics, business.industry, Mechanical Engineering, food and beverages, Radon gas, Durability, respiratory tract diseases, chemistry, Mechanics of Materials, 020201 artificial intelligence & image processing, business, Carbon, Activated carbon, medicine.drug
Abstract: Four different material of activated carbon, i.e., coconut shell, fruit shell, wood and coal, were used to be mixed with concrete, the radon exhalation rates of concrete then was measured. At the same time, the pore distribution of activated carbon and some performances of concrete were tested. The results show that coconut shell carbon has the best effect for reduction radon exhalation rates of concrete, fruit shell carbon comes second. The adsorption mechanisms of activated carbon towards the radon gas in the solid and in the air are similar. Activated carbon have less effect on the strength of concrete, however, they have greater influence on the constructability and durability.
Published: 2017

44. Validation of accuracy and stability of numerical simulation for 2-D heat transfer system by an entropy production approach

Author: Muhammad Hassan, Kossi Aniya Amedome Min-Dianey, Ali Anwar Brohi, Saadullah Farooqi, Muhammad Rafique, and Hao-Chun Zhang
Subjects: convergence, Finite volume method, accuracy, Computer simulation, Renewable Energy, Sustainability and the Environment, Entropy production, business.industry, lcsh:Mechanical engineering and machinery, 020209 energy, 02 engineering and technology, stability, Computational fluid dynamics, Thermal conduction, entropy production, Stability (probability), heat transfer, Heat transfer, 0202 electrical engineering, electronic engineering, information engineering, Applied mathematics, lcsh:TJ1-1570, Multidimensional systems, business, Mathematics
Abstract: The entropy production in 2-D heat transfer system has been analyzed systematically by using the finite volume method, to develop new criteria for the numerical simulation in case of multidimensional systems, with the aid of the CFD codes. The steady-state heat conduction problem has been investigated for entropy production, and the entropy production profile has been calculated based upon the current approach. From results for 2-D heat conduction, it can be found that the stability of entropy production profile exhibits a better agreement with the exact solution accordingly, and the current approach is effective for measuring the accuracy and stability of numerical simulations for heat transfer problems.
Published: 2017

45. Response to comments on 'Interlocking nailing of femoral shaft fractures with an extremely narrow medullary canal is associated with iatrogenic fractures.'

Author: Fa Chuan Kuan, Kai Lan Hsu, Ming Long Yeh, Hao Chun Chuang, and Wei Ren Su
Subjects: medicine.medical_specialty, Medullary cavity, Femoral shaft, business.industry, Iatrogenic Disease, Fracture Fixation, Intramedullary, Surgery, medicine, Humans, General Earth and Planetary Sciences, Diaphyses, Femur, business, Interlocking, General Environmental Science
Published: 2020

46. Rounded Insertion Technique for Cochlear Implantation Surgery to Treat Cystic Inner Ear Malformation

Author: Mei-Jui Huang, Chi-Ching Lin, Joshua Kuang-Chao Chen, William Kuan-Hua Chen, and Hao-Chun Hu
Subjects: Male, medicine.medical_specialty, medicine.medical_treatment, Auditory canal, 03 medical and health sciences, 0302 clinical medicine, Inner ear malformation, Cochlear implant, Chart review, otorhinolaryngologic diseases, medicine, Electrode array, Humans, 030223 otorhinolaryngology, Cochlear implantation, Child, Cochlea, Retrospective Studies, business.industry, medicine.disease, Cochlear Implantation, Hypoplasia, Surgery, Electrodes, Implanted, Treatment Outcome, Otorhinolaryngology, 030220 oncology & carcinogenesis, Child, Preschool, Ear, Inner, Feasibility Studies, Female, sense organs, business
Abstract: OBJECTIVE This article outlines the advantages and applicability of the rounded insertion technique of cochlear implants in patients with cystic inner ear malformation. This technique enables the insertion of the maximum number of electrodes and prevents the unwanted entry of electrodes into the internal auditory canal. METHODS We conducted a retrospective chart review of consecutive patients with cochlear hypoplasia (CH) and/or common cavity (CC) who underwent CI (cochlear implantation) via rounded insertion technique. The position of the electrode array in each patient was confirmed postoperatively via X-ray, and the number of functional electrodes was confirmed during the mapping process. RESULTS This study included five male and two female patients (median age: 3 years; age range: 2-7 years). Among the seven patients, four received a cochlear implant on the right side, one on the left side, and two bilaterally. Of the nine ears, six were cases of CH, and three were CC. All cochlear implant surgeries via rounded insertion technique were completed without complications. The maximum number of electrode contacts with fair function in the cystic cochlea was confirmed via postoperative X-ray and the subsequent mapping process. CONCLUSION This consecutive series of patients demonstrated the safety and reliability of rounded insertion technique for CI in patients with CH and/or CC. LEVEL OF EVIDENCE 4 Laryngoscope, 130:2229-2233, 2020.
Published: 2019

47. FLASH: Content-based Power-saving Design for Scrolling Operations in Browser Applications on Mobile OLED Devices

Author: Hao-Chun Chang, Liang-Yan Yu, Chun-Han Lin, and Yu-Chieh Yang
Subjects: Computer science, business.industry, 020208 electrical & electronic engineering, 02 engineering and technology, 020202 computer hardware & architecture, Energy conservation, Flash (photography), Transformation (function), User experience design, Embedded system, Scrolling, Web page, 0202 electrical engineering, electronic engineering, information engineering, OLED, business, Mobile device
Abstract: As modern people become highly dependent on mobile applications and services, saving the power consumption of browser applications plays an important role for the battery lifetime of mobile devices. This paper investigates how to reduce the power consumption of mobile OLED displays under scrolling operations when displaying web pages. We first propose a content-based analysis to efficiently determine the visual appeal in a web page. Then, two algorithms are presented to dynamically generate power-saving transformation programs for a web page. We next propose a scrolling operation detection to activate the transformation without reducing the user experience. Finally, the results of the extensive experiments conducted on a commercial smart-phone with four real-world web pages to evaluate the performance of the proposed design are very encouraging.
Published: 2019

48. An Event-contrastive Connectome Network for Automatic Assessment of Individual Face Processing and Memory Ability

Author: Wan-Ting Hsieh, Chon-Wen Shyi, Fu-Sheng Tsai, Hao-Chun Yang, and Chi-Chun Lee
Subjects: medicine.diagnostic_test, Computer science, business.industry, Functional connectivity, 05 social sciences, Feature extraction, Process (computing), Pattern recognition, Facial recognition system, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, Face (geometry), Connectome, medicine, 0501 psychology and cognitive sciences, Artificial intelligence, business, Functional magnetic resonance imaging, 030217 neurology & neurosurgery
Abstract: Human adapt their behaviors by continuously monitoring one another to function socially in our society. The ability to process face identity from memory is a crucial basic capability. In this work, we propose an event-contrastive connectome network (E-cCN) in representing brain’s functional connectivity with contrastive loss to handle layers of fMRI data variabilities exists under different controlled stimuli events to achieve improved automatic assessing of an individual’s face processing and memory ability. Our proposed connectome network achieves an overall recognition accuracy of 80.20% and 82.05% in binary classification of separating high versus low scoring subjects on tasks of Taiwanese Face Memory Test (TFMT) and component inverse efficiency score (cIE) respectively. Further, our network embedding representation demonstrate distinct connectivity patterns in key face processing brain regions (ROIs) when comparing between high and low face processing and memory ability.
Published: 2019

49. The Classification of Mammogram Using Convolutional Neural Network with Specific Image Preprocessing for Breast Cancer Detection

Author: El-Wui Loh, Hao-Chun Lu, and Shih-Chen Huang
Subjects: 0209 industrial biotechnology, medicine.diagnostic_test, Computer science, business.industry, Deep learning, Pattern recognition, 02 engineering and technology, medicine.disease, Convolutional neural network, 020901 industrial engineering & automation, Breast cancer, Histogram, 0202 electrical engineering, electronic engineering, information engineering, medicine, Median filter, Preprocessor, Mammography, 020201 artificial intelligence & image processing, Adaptive histogram equalization, Artificial intelligence, business
Abstract: The incidence rate of breast cancer continued to rise in the last few decades. Current screening strategy of breast cancer is based on classic X-ray imaging. The sensitivity and specificity of the diagnosis are largely depend on the experiences of the radiologists, and uncertain diagnosis is quite frequent because of resolution limitations and the concerns of lawsuits arisen from wrong diagnosis or undetected lesions. The convolutional neural network is an effective technique for classification in deep learning model. In this study, we utilized median filter, contrast-limited adaptive histogram equalization, and data augmentation to preprocess over 9,000 mammograms, and trained a classified model by using convolutional neural network. The experiment results demonstrated that the accuracy of model with preprocessed images significantly outperformed the model without preprocessed images.
Published: 2019

50. Coordinated control of the conventional units, wind power, and battery energy storage system for effective support in the frequency regulation service

Author: Yufeng Guo, Said I. Abouzeid, and Hao-Chun Zhang
Subjects: Service (business), Wind power, Computer science, business.industry, Control (management), Energy Engineering and Power Technology, Battery energy storage system, Automotive engineering, Variable speed wind turbine, Battery storage system, Modeling and Simulation, Frequency regulation, Electrical and Electronic Engineering, business
Published: 2019

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