1,156 results on '"Mao K."'
Search Results
2. Development and Validation of a Nomogram for Predicting the Severity of the First Episode of Hyperlipidemic Acute Pancreatitis
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Lin Y, Liu Y, Lin Q, Wang M, Jiang P, Mao K, Chen F, Ding J, and Li D
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early prediction ,nomogram ,hyperlipidemic acute pancreatitis ,risk factor ,prognosis ,Pathology ,RB1-214 ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Yongxu Lin,1,2 Yaling Liu,3 Qiuyan Lin,1,2 Mingrong Wang,1,2 Pingying Jiang,1,2 Kaiyi Mao,1,2 Fenglin Chen,1,2 Jian Ding,3 Dan Li1,2 1Department of Gastroenterology, Fujian Medical University Union Hospital, Fuzhou, People’s Republic of China; 2Fujian Clinical Research Center for Digestive System Tumors and Upper Gastrointestinal Diseases, Fuzhou, People’s Republic of China; 3Department of Gastroenterology, the First Affiliated Hospital, Fujian Medical University, Fuzhou, People’s Republic of ChinaCorrespondence: Dan Li, No. 29 Xinquan Road, Fuzhou, 350001, People’s Republic of China, Email doctorlidan99@fjmu.edu.cn Jian Ding, No. 20 Chazhong Road, Fuzhou, 350005, People’s Republic of China, Email docdingjian@163.comPurpose: Early detection of hyperlipidemic acute pancreatitis (HLAP) with exacerbation tendency is crucial for clinical decision-making and improving prognosis. The aim of this study was to establish a reliable model for the early prediction of HLAP severity.Patients and Methods: A total of 225 patients with first-episode HLAP who were admitted to Fujian Medical University Union Hospital from June 2012 to June 2023 were included. Patients were divided into mild acute pancreatitis (MAP) or moderate-severe acute pancreatitis and severe acute pancreatitis (MSAP+SAP) groups. Independent predictors for progression to MSAP or SAP were identified through univariate analysis and least absolute shrinkage and selection operator regression. A nomogram was established through multivariate logistic regression analysis to predict this progression. The calibration, receiver operating characteristic(ROC), and clinical decision curves were employed to evaluate the model’s consistency, differentiation, and clinical applicability. Clinical data of 93 patients with first-episode HLAP who were admitted to the First Affiliated Hospital of Fujian Medical University from October 2015 to October 2022 were collected for external validation.Results: White blood cell count, lactate dehydrogenase, albumin, serum creatinine, serum calcium, D-Dimer were identified as independent predictors for progression to MSAP or SAP in patients with HLAP and used to establish a predictive nomogram. The internally verified Harrell consistency index (C-index) was 0.908 (95% CI 0.867– 0.948) and the externally verified C-index was 0.950 (95% CI 0.910– 0.990). The calibration, ROC, and clinical decision curves showed this nomogram’s good predictive ability.Conclusion: We have established a nomogram that can help identify HLAP patients who are likely to develop MSAP or SAP at an early stage, with high discrimination and accuracy.Keywords: early prediction, nomogram, hyperlipidemic acute pancreatitis, risk factor, prognosis
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- 2024
3. Clinical and Laboratory Characteristics in Children with Alagille Syndrome: Experience of a Single Center
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Li D, Mao K, Sun J, Liu J, and Zhang C
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alagille syndrome ,cholestasis ,genetic testing ,Medicine (General) ,R5-920 - Abstract
Dalei Li, Kangwei Mao, Jun Sun, Jiangyang Liu, Chenxi Zhang Department of Pediatric Internal Medicine, The First People’s Hospital of Lianyungang & Xuzhou Medical University Affiliated Hospital of Lianyungang & The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, 222061, People’s Republic of ChinaCorrespondence: Kangwei Mao, Department of Pediatric Internal Medicine, The First People’s Hospital of Lianyungang & Xuzhou Medical University Affiliated Hospital of Lianyungang & The First Affiliated Hospital of Kangda College of Nanjing Medical University, No. 6 Zhenhua East Road, Haizhou District, Lianyungang, Jiangsu, 222061, People’s Republic of China, Email maokangwei@163.comBackground: This study aimed to explore the clinical predictors of Alagille syndrome (ALGS) in children and to provide a basis for early diagnosis.Methods: We retrospectively analyzed the clinical data of 14 children diagnosed with ALGS at the First People’s Hospital of Lianyungang City from March 2016 to March 2021 and followed up the children.Results: Among the 14 patients, 9 (64.28%) had cholestasis, 12 (85.71%) had heart malformations, 13 (92.85%) had characteristic facial features, 2 (14.28%) had pruritus, and 2 (14.28%) had a positive family history. Among the 13 patients who were examined by pediatric ophthalmologists, 3 patients had ocular lesions. Among the 13 patients who underwent spine radiography, 2 had typical butterfly vertebrae. Among the 6 patients with hepatic pathology, 2 had intracellular cholestasis, 2 had reduced or no small bile duct in the portal area, 2 had small bile duct hyperplasia with massive fibrous hyperplasia and extensive inflammatory cell infiltration, and 2 underwent biliary tract exploration. Genetic testing of 12 children with ALGS revealed JAG1 gene mutations in 7 cases and NOTCH2 gene mutations in 2 cases. The abovementioned two mutant genes were not detected in any of the 3 cases. Among the 12 followed-up patients, 7 were in stable condition, 5 underwent liver transplantation, and 1 died of severe pneumonia.Conclusion: Cholestatic liver disease, cardiac malformations, and abnormal facial development are predictors of ALGS in children and can be definitively diagnosed by genetic testing.Keywords: Alagille syndrome, cholestasis, genetic testing
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- 2023
4. Calcium amendments affect heavy metal bioavailability in acidic and calcareous soils
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Li, L., Mao, K., Ippolito, J. A., Xing, W., Chen, X., Zhu, W., and Cheng, Y.
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- 2022
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5. Multi-objective search-based mobile testing
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Mao, K., Harman, M., Capra, L., and Jia, Y.
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004 - Abstract
Despite the tremendous popularity of mobile applications, mobile testing still relies heavily on manual testing. This thesis presents mobile test automation approaches based on multi-objective search. We introduce three approaches: Sapienz (for native Android app testing), Octopuz (for hybrid/web JavaScript app testing) and Polariz (for using crowdsourcing to support search-based mobile testing). These three approaches represent the primary scientific and technical contributions of the thesis. Since crowdsourcing is, itself, an emerging research area, and less well understood than search-based software engineering, the thesis also provides the first comprehensive survey on the use of crowdsourcing in software testing (in particular) and in software engineering (more generally). This survey represents a secondary contribution. Sapienz is an approach to Android testing that uses multi-objective search-based testing to automatically explore and optimise test sequences, minimising their length, while simultaneously maximising their coverage and fault revelation. The results of empirical studies demonstrate that Sapienz significantly outperforms both the state-of-the-art technique Dynodroid and the widely-used tool, Android Monkey, on all three objectives. When applied to the top 1,000 Google Play apps, Sapienz found 558 unique, previously unknown crashes. Octopuz reuses the Sapienz multi-objective search approach for automated JavaScript testing, aiming to investigate whether it replicates the Sapienz’ success on JavaScript testing. Experimental results on 10 real-world JavaScript apps provide evidence that Octopuz significantly outperforms the state of the art (and current state of practice) in automated JavaScript testing. Polariz is an approach that combines human (crowd) intelligence with machine (computational search) intelligence for mobile testing. It uses a platform that enables crowdsourced mobile testing from any source of app, via any terminal client, and by any crowd of workers. It generates replicable test scripts based on manual test traces produced by the crowd workforce, and automatically extracts from these test traces, motif events that can be used to improve search-based mobile testing approaches such as Sapienz.
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- 2017
6. Transferrin-Decorated Protein-Lipid Hybrid Nanoparticle Efficiently Delivers Cisplatin and Docetaxel for Targeted Lung Cancer Treatment
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Mao K, Zhang W, Yu L, Yu Y, Liu H, and Zhang X
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lung cancer ,hybrid nanoparticles ,nanostructured lipid nanoparticles ,protein nanoparticles ,transferrin ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Kaiping Mao,1 Weina Zhang,2 Lan Yu,3 Yi Yu,1 Haixia Liu,1 Xiaotao Zhang3 1Department of Thoracic surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, People’s Republic of China; 2Department of Plastic surgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, People’s Republic of China; 3Department of Cancer Stereotactic Radiotherapy, Affiliated Qingdao Central Hospital of Qingdao University, Qingdao, 266042, People’s Republic of ChinaCorrespondence: Xiaotao Zhang Tel +86 532-68667866Email sabr@vip.163.comPurpose: Non-small cell lung cancer (NSCLC) therapy faces the barriers including drug resistance. A transferrin-functionalized protein-lipid hybrid nanoparticle (PLHN) was designed loading both cisplatin (CIS) and docetaxel (DTX) for the lung cancer treatment.Methods: CIS and DTX were loaded into the hybrid nanoparticle and then decorated with transferrin (Tf). The Tf-functionalized protein-lipid hybrid nanoparticle (Tf-CIS/DTX-PLHN) was investigated by determining the release behavior, cytotoxicity in vitro, and anticancer efficiency in vivo.Results: Tf-CIS/DTX-PLHN showed a nano-size of 189.5 ± 5.9 nm, and a surface tested to be − 16.9 ± 2.1 mV. Tf-CIS/DTX-PLHN exhibited obviously better antitumor ability in vitro and in vivo compared with the non Tf contained CIS and DTX co-loaded lipid nanoparticles (CIS/DTX-LN), single drug loaded nanoparticles, and free drugs.Conclusion: Since remarkable enhanced efficiency of Tf and synergistic effect of the drugs, it could inhibit the lung tumor growth and help with the lung cancer treatment.Keywords: lung cancer, hybrid nanoparticles, nanostructured lipid nanoparticles, protein nanoparticles, transferrin
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- 2021
7. Sub-seasonal soil moisture anomaly forecasting using combinations of deep learning, based on the reanalysis soil moisture records
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Wang, X. Corzo, G. Lü, H. Zhou, S. Mao, K. Zhu, Y. Duarte, S. Liu, M. Su, J. and Wang, X. Corzo, G. Lü, H. Zhou, S. Mao, K. Zhu, Y. Duarte, S. Liu, M. Su, J.
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Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persistence compared to other climate system quantities, which makes it especially influential in shaping land-atmosphere feedback, thus supplying a unique insight into drought forecasting. Relying on the soil moisture memory, this study investigates the combination of multiple deep-learning modules for sub-seasonal drought indices hindcast in the Huai River basin of China, using long-term ERA5-Land soil moisture records with a noise-assisted data analysis tool. The inter-compared deep-learning models include a hybrid model and a committee machine framework. The results show that the performance of the committee machine framework can be improved with the help of series decomposition and the forecasting skill is not impaired with the lead time increases. Overall, this study highlights the potential of combining deep-learning models with soil moisture memory analysis to improve sub-seasonal drought forecasting.
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- 2024
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8. Sub-seasonal soil moisture anomaly forecasting using combinations of deep learning, based on the reanalysis soil moisture records
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Wang, X. (author), Corzo, Gerald (author), Lü, Haishen (author), Zhou, Shiliang (author), Mao, K. (author), Zhu, Yonghua (author), Duarte Prieto, F.S. (author), Liu, Mingwen (author), Su, Jianbin (author), Wang, X. (author), Corzo, Gerald (author), Lü, Haishen (author), Zhou, Shiliang (author), Mao, K. (author), Zhu, Yonghua (author), Duarte Prieto, F.S. (author), Liu, Mingwen (author), and Su, Jianbin (author)
- Abstract
Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persistence compared to other climate system quantities, which makes it especially influential in shaping land-atmosphere feedback, thus supplying a unique insight into drought forecasting. Relying on the soil moisture memory, this study investigates the combination of multiple deep-learning modules for sub-seasonal drought indices hindcast in the Huai River basin of China, using long-term ERA5-Land soil moisture records with a noise-assisted data analysis tool. The inter-compared deep-learning models include a hybrid model and a committee machine framework. The results show that the performance of the committee machine framework can be improved with the help of series decomposition and the forecasting skill is not impaired with the lead time increases. Overall, this study highlights the potential of combining deep-learning models with soil moisture memory analysis to improve sub-seasonal drought forecasting., Physical and Space Geodesy, Water Resources
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- 2024
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9. A new method for testing polymer gear wear rate and performance
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Mao, K., Chetwynd, D.G., and Millson, M.
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- 2020
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10. The volatile leaf oil of Juniperus microsperma and its taxonomy
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Adams, R P, Mao, K-S, Liu, J-Q, and BioStor
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- 2013
11. AMPH-1 As A Critical Tumor Suppressor That Inhibits Osteosarcoma Progression
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Zhang H, Liu Y, Xu K, Mao K, Han W, Xu F, Wan W, and Sun Y
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amph-1 ,osteosarcoma ,erk signaling pathway ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Haiyun Zhang,1,* Yujie Liu,2,* Kehan Xu,2,* Kai Mao,1 Weidong Han,1 Feifan Xu,1 Wei Wan,2 Yajun Sun3 1Department of Laboratory Medicine, The Sixth People’s Hospital of Nantong, Jiangsu 226000, People’s Republic of China; 2Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, 200003, People’s Republic of China; 3Department of Laboratory Medicine, The Fourth People’s Hospital of Nantong, Jiangsu 226000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yajun Sun; Wei WanDepartment of Laboratory Medicine, The Fourth People’s Hospital of Nantong, Chenggang Road, Jiangsu 226000, People’s Republic of ChinaEmail yajun_sun1@163.com; wei_wan66@163.comIntroduction: Amphiphysin 1 (AMPH-1) is involved in endocytosis, and its expression is upregulated in osteosarcoma compared with osteofibrous dysplasia.Methods: We investigated the role of AMPH-1 in osteosarcoma cells via both gain-of-function and loss-of-function experiments.Results: Knockdown of AMPH-1 in osteosarcoma cells promoted cell cycle progression and cell proliferation and attenuated apoptosis. Notably, silencing AMPH-1 increased osteosarcoma progression in a mouse tumor model. The results obtained upon AMPH-1 knockdown and AMPH-1 overexpression indicates that AMPH-1 is involved in regulating MEK/ERK signaling.Conclusion: These data suggest that AMPH-1 plays an important role in osteosarcoma and may represent a novel therapeutic target for osteosarcoma treatment.Keywords: AMPH-1, osteosarcoma, ERK signaling pathway
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- 2019
12. Development and external validation of prognostic nomograms in hepatocellular carcinoma patients: a population based study
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Xiao Z, Yan Y, Zhou Q, Liu H, Huang P, Lai C, Zhang J, Wang J, and Mao K
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Surveillance ,Epidemiology and end results ,Overall survival ,Cancer-specific survival ,Decision curve analysis ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Zhiyu Xiao1,2,*, Yongcong Yan1,2,*, Qianlei Zhou1,2,*, Haohan Liu1,2, Pinbo Huang1,2, Qiming Zhou1,2, Changliang Lai1,2, Jianlong Zhang1,2, Jie Wang1,2, Kai Mao1,21Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People’s Republic of China; 2Department of Hepatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, People’s Republic of China*These authors contributed equally to this work Background: We attempted to construct and validate novel nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in patients with hepatocellular carcinoma (HCC).Methods: Models were established using a discovery set (n=10,262) obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Based on univariate and multivariate Cox regression analyses, we identified independent risk factors for OS and CSS. Concordance indexes (c-indexes) and calibration plots were used to evaluate model discrimination. The predictive accuracy and clinical values of the nomograms were measured by decision curve analysis (DCA).Results: Our OS nomogram with a c-index of 0.753 (95% confidence interval (CI), 0.745–0.761) was based on age, sex, race, marital status, histological grade, TNM stage, tumor size, and surgery performed, and it performed better than TNM stage. Our CSS nomogram had a c-index of 0.748 (95% CI, 0.740–0.756). The calibration curves fit well. DCA showed that the two nomograms provided substantial clinical value. Internal validation produced c-indexes of 0.758 and 0.752 for OS and CSS, respectively, while external validation in the Sun Yat-sen Memorial Hospital (SYMH) cohort produced a c-indexes of 0.702 and 0.686 for OS and CSS, respectively.Conclusions: We have developed nomograms that enable more accurate individualized predictions of OS and CSS to help doctors better formulate individual treatment and follow-up management strategies.Keywords: surveillance, epidemiology and end results, overall survival, cancer-specific survival, decision curve analysis
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- 2019
13. Analysis and Simulation of Transient Contact Stress and Temperature Field of Polymer Gear
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Wang Zhen, Wang Yanjun, Wang Jingjing, and Mao K
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Polymer gear ,Contact stress ,Temperature field ,Finite element analysis ,Mechanical engineering and machinery ,TJ1-1570 - Abstract
The contact pressure of the tooth surface of the polymer gear is analyzed by using the method of Hertz contact theory and finite element contact analysis. The calculation method of the tooth surface friction coefficient and the friction heat flux density of the gear tooth during the meshing process is studied. The simulation method of temperature field and stress in the instantaneous contact temperature of the gear teeth during the meshing transmission of PEEK polymer gear is discussed. The direct coupling method is used to analyze the heat-structure of the gears,and the transient temperature field and stress are obtained. The results of the initial ambient temperature are discussed. The results show that the increase of the initial ambient temperature has a great influence on the temperature field and the stress at the time of meshing.
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- 2018
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14. Study on Optimization of Cooling System for Mass Pier Column of Shenzhong Passage Non-navigable Bridge
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Xu, DS, primary, Zhou, T, additional, and Mao, K, additional
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- 2023
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15. Molecular phylogeny of mega-diverse Carabus attests late Miocene evolution of alpine environments in the Himalayan-Tibetan Orogen
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Schmidt, J., Opgenoorth, L., Mao, K., Baniya, C.B., Hofmann, Sylvia, Schmidt, J., Opgenoorth, L., Mao, K., Baniya, C.B., and Hofmann, Sylvia
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The timing, sequence, and scale of uplift of the Himalayan-Tibetan Orogen (HTO) are controversially debated. Many geoscientific studies assume paleoelevations close to present-day elevations and the existence of alpine environments across the HTO already in the late Paleogene, contradicting fossil data. Using molecular genetic data of ground beetles we reconstruct the paleoenvironmental history of the HTO, focusing on its southern margin (Himalayas, South Tibet). Based on a comprehensive sampling of extratropical Carabus, and ~ 10,000 bp of mitochondrial and nuclear DNA we applied Bayesian and Maximum likelihood phylogenetics. We show that Carabus arrived in the HTO at the Oligocene-Miocene boundary. During the early Miocene, five lineages diversified in different parts of the HTO, initially in its southern center and on its eastern margin. Evolution of subalpine-alpine taxa occurred during the late Miocene. There were apparently no habitats for Carabus before the late Oligocene. Until the Late Oligocene elevations must have been low throughout the HTO. Temperate forests emerged in South Tibet in the late Oligocene at the earliest. Alpine environments developed in the HTO from the late Miocene and, in large scale, during the Pliocene-Quaternary. Findings are consistent with fossil records but contrast with uplift models recovered from stable isotope paleoaltimetry.
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- 2023
16. 85P Ripretinib dose escalation after disease progression for Chinese patients with advanced gastrointestinal stromal tumor: A multi-center retrospective analysis
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Zhou, Y., primary, Zhang, X., additional, Sun, X., additional, Zhang, Y., additional, Mao, K., additional, Liu, H., additional, Liu, N., additional, Zhou, Y., additional, Meng, Y., additional, Tan, B., additional, and Wang, L., additional
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- 2023
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17. The wear and thermal mechanical contact behaviour of machine cut polymer gears
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Mao, K., Langlois, P., Hu, Z., Alharbi, K., Xu, X., Milson, M., Li, W., Hooke, C.J., and Chetwynd, D.
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- 2015
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18. CAMRESBRT: Randomized Phase II Trial of Camrelizumab with Stereotactic Body Radiotherapy vs. Camrelizumab Alone in Recurrent or Metastatic Head and Neck Squamous Cell Carcinoma
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Lei, Q., primary, Wang, Y., additional, Sui, J., additional, Luo, Q., additional, Jin, F., additional, Long, B., additional, Shu, X., additional, Li, S., additional, Huang, L., additional, Zhong, M., additional, and Mao, K., additional
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- 2022
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19. Experimental Investigations of Polymer Composite Gear Performance
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Mao, K., primary, Goodship, V., additional, Madhav, N., additional, Ramakrishnan, R., additional, and Langlois, P., additional
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- 2017
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20. An investigation on the wear behaviour of dissimilar polymer gear engagements
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Li, W., Wood, A., Weidig, R., and Mao, K.
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- 2011
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21. Wear Performance of Commercial Polyoxymethylene Copolymer and Homopolymer Injection Moulded Gears
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Xu, X., primary, Gao, F., additional, Lopera Valle, A., additional, Makenji, K., additional, Nedolisa, C., additional, Zhao, Y., additional, Goodship, V., additional, and Mao, K., additional
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- 2021
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22. Polymer gear surface thermal wear and its performance prediction
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Mao, K., Li, W., Hooke, C.J., and Walton, D.
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- 2010
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23. Integrative Analysis of Multi-Omics Data Identified klrc3 as Key Nodes in a Gene Regulatory Network Related to Immune Phenotypes in Lung Adenocarcinoma
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Li Z, Xue Q, Mao K, and Ding B
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Lung ,business.industry ,Computational biology ,Biology ,medicine.disease ,Phenotype ,medicine.anatomical_structure ,Immune system ,Text mining ,medicine ,Key (cryptography) ,Adenocarcinoma ,Multi omics ,business ,Gene ,oncology_oncogenics - Abstract
In a recent study, the PD-1 inhibitor has been widely used in clinical trials and shown to improve various cancers. However, PD-1/PD-L1 inhibitors showed a low response rate and showed to be effective for a small number of cancer patients. Thus, it is important to identify key genes, which can enhance the PD-1/PD-L1 response for promoting immunotherapy. Here, we used ssGSEA and unsupervised clustering analysis to identify three clusters to show different immune cell infiltration status, prognosis, and biological action. The cluster C showed a better survival rate, high immune cells infiltration, and immunotherapy effect enriched in a variety of immune active pathways, including T and B cell signal receptors. Besides, it showed more immune subtypes C2 and C3. Further, we used WGCNA analysis to confirm the cluster C correlated genes. The red module highly correlated with cluster C for 111 genes which were enriched in a variety of immune-related pathways. To pick candidate genes in SD/PD and CR/PR patients, we used the Least Absolute Shrinkage and SVM-RFE algorithms. In conclusion, our LASSO analysis and SVM-RFE based research identified targets with better prognosis, activated immune-related pathways, and better immunotherapy. The KLRC3 was identified as the key gene which can efficiently respond to immunotherapy with greater efficacy and better prognosis.
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- 2021
24. Control design of parallel-connected PWM DC-AC converters for sustainable energy applications
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Chang, E C, primary, Lin, G W, additional, Lin, Y T, additional, Mao, K C, additional, and Wu, R C, additional
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- 2021
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25. MicroRNA-143-3p suppresses tumorigenesis by targeting catenin-δ1 in colorectal cancer
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Ding X, Du J, Mao K, Wang X, Ding Y, and Wang F
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microRNA-143-3p ,CTNND1 ,tumorigenesis ,colorectal cancer ,lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,lcsh:RC254-282 - Abstract
Xiaohua Ding,1 Jiying Du,1 Kai Mao,2 Xiaoyu Wang,1 Yuange Ding,1 Fanping Wang1,31School of Inspection and Imaging, Sanquan College of Xinxiang Medical University, 453003, Henan, China; 2Department Two of Thoracic Diseases, Xinxiang Central Hospital, 453003, Henan, China; 3School of Laboratory Medicine, Xinxiang Medical University, 453003, Henan, China Background: Colorectal cancer (CRC) is the third most common malignancy in the United States. Mounting microRNAs (miRNAs) have been identified as oncogenes or tumor suppressors in various cancers including CRC.Materials and methods: The levels of microRNA-143-3p (miR-143-3p) and catenin-δ1 (CTNND1) were determined by RT-qPCR assay. Cell proliferative ability was assessed by Cell Counting Kit-8 assay. Cell migratory and invasive capacities were measured by transwell migration and invasion assay. Luciferase reporter assay was conducted to explore whether miR-143-3p could bind with CTNND1 3'UTR. CTNND1 protein level was determined through Western blot assay. Mouse xenograft models of CRC were established to test the functions and molecular basis of miR-143-3p in the development of CRC invivo.Results: Low amounts of miR-143-3p were expressed in CRC tissues and cells. Functional analysis revealed that miR-143-3p overexpression suppressed cell proliferation, migration and invasion in CRC. Molecular mechanism exploration indicated that miR-143-3p directly targeted CTNND1. Moreover, enforced expression of CTNND1 contributed to cell proliferation, migration and invasion in CRC, and CTNND1 silencing exerted opposite effects. Restoration experiments disclosed that CTNND1 upregulation weakened the inhibitory effects of miR-143-3p on CRC cell proliferation, migration and invasion. Additionally, miR-143-3p inhibited the growth of HCT116-derived xenograft tumors by targeting CTNND1 invivo.Conclusion: miR-143-3p hampered the development and progression of CRC by targeting CTNND1 invitro and invivo, deepening our understanding of the functions and molecular basis of miR-143-3p in the tumorigenesis of CRC and providing some candidate prognostic markers or therapeutic targets for CRC. Keywords: microRNA-143-3p, CTNND1, colorectal cancer, tumorigenesis
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- 2019
26. Friction and wear behaviour of acetal and nylon gears
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Mao, K., Li, W., Hooke, C.J., and Walton, D.
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- 2009
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27. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)
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Klionsky, DJ, Abdel-Aziz, AK, Abdelfatah, S, Abdellatif, M, Abdoli, A, Abel, S, Abeliovich, H, Abildgaard, MH, Abudu, YP, Acevedo-Arozena, A, Adamopoulos, IE, Adeli, K, Adolph, TE, Adornetto, A, Aflaki, E, Agam, G, Agarwal, A, Aggarwal, BB, Agnello, M, Agostinis, P, Agrewala, JN, Agrotis, A, Aguilar, PV, Ahmad, ST, Ahmed, ZM, Ahumada-Castro, U, Aits, S, Aizawa, S, Akkoc, Y, Akoumianaki, T, Akpinar, HA, Al-Abd, AM, Al-Akra, L, Al-Gharaibeh, A, Alaoui-Jamali, MA, Alberti, S, Alcocer-Gómez, E, Alessandri, C, Ali, M, Alim Al-Bari, MA, Aliwaini, S, Alizadeh, J, Almacellas, E, Almasan, A, Alonso, A, Alonso, GD, Altan-Bonnet, N, Altieri, DC, Álvarez, ÉMC, Alves, S, Alves da Costa, C, Alzaharna, MM, Amadio, M, Amantini, C, Amaral, C, Ambrosio, S, Amer, AO, Ammanathan, V, An, Z, Andersen, SU, Andrabi, SA, Andrade-Silva, M, Andres, AM, Angelini, S, Ann, D, Anozie, UC, Ansari, MY, Antas, P, Antebi, A, Antón, Z, Anwar, T, Apetoh, L, Apostolova, N, Araki, T, Araki, Y, Arasaki, K, Araújo, WL, Araya, 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Y, Oshima, S, Rong, Y, Sluimer, JC, Stallings, CL, and Tong, C-K
- Abstract
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
28. Depositional architecture and evolution of basin-floor fan systems since the Late Miocene in the Northwest Sub-Basin, South China Sea
- Author
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Chen, H., Stow, D., Xie, X., Ren, J., Mao, K., Gao, Y., Chen, B., Zhang, W., Vandorpe, T., and Van Rooij, D.
- Abstract
The sediment budget of the Northwest Sub-basin, South China Sea since the Late Miocene (11.6 Ma, average thickness > 1000 m) accounts for more than two-thirds of the total infill since the initial ocean spreading of the sub-basin (32 Ma). The sediment sources and architectural pattern of these deposits, however, are poorly known. Using high-resolution 2D reflection seismic data with age constraint from IODP boreholes, we have documented two interdigitating basin-floor fan systems that developed since the Late Miocene. These were fed by two of the largest deep-water canyon systems worldwide, from the west (the Central Canyon/Xisha Trough) and the northeast (the Pearl River Canyon), as well as from smaller headless canyons and gullies across the surrounding slopes. Based on careful analysis of seismic facies, their geometry and occurrence, we identify the principal deep-water architectural elements, including the multi-scale channels, channel-levee complexes, lobes, sheets and drapes, mass-transport deposits, volcanic intrusions, turbidity-current sediment-wave fields, and a contourite drift/terrace.
- Published
- 2021
29. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition).
- Author
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Quadrilatero J., Walker D.W., Walker M.J., Walker S.A., Walter J., Wandosell F.G., Wang B., Wang C., Wang C.-Y., 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.-Y., Wang 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., W... [Ovid has truncated this field to avoid Excel character limitations], 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., 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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 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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.P., Kaushik S., Kawasaki K., Kazan K., Ke P.-Y., Keating D.J., Keber U., Kehrl J.H., Keller K.E., Keller C.W., Kemper J.K., Kenific C.M., Kepp O., Kermorgant S., Kern A., Ketteler R., Keulers T.G., Khalfin B., Khalil H., Khambu B., Khan S.Y., Khandelwal V.K.M., Khandia R., Kho W., Khobrekar N.V., Khuansuwan S., Khundadze M., Killackey S.A., Kim D., Kim D.R., Kim D.-H., Kim D.-E., Kim E.Y., Kim E.-K., Kim H.-R., Kim H.-S., Hyung-Ryong Kim, Kim J.K., Kim J.-H., Kim J., Kim J.H., Kim K.I., Kim P.K., Kim S.-J., Kimball S.R., Kimchi A., Kimmelman A.C., Kimura T., King M.A., Kinghorn K.J., Kinsey C.G., Kirkin V., Kirshenbaum L.A., Kiselev S.L., Kishi S., Kitamoto K., Kitaoka Y., Kitazato K., Kitsis R.N., Kittler J.T., Kjaerulff O., Klein P.S., Klopstock T., Klucken J., Knaevelsrud H., Knorr R.L., Ko B.C.B., Ko F., Ko J.-L., Kobayashi H., Kobayashi S., Koch I., Koch J.C., Koenig U., Kogel D., Koh Y.H., Koike M., Kohlwein S.D., Kocaturk N.M., Komatsu M., Konig J., Kono T., Kopp B.T., Korcsmaros T., Korkmaz G., Korolchuk V.I., Korsnes M.S., Koskela A., Kota J., Kotake Y., Kotler M.L., Kou Y., Koukourakis M.I., Koustas E., Kovacs A.L., Kovacs T., Koya D., Kozako T., Kraft C., Krainc D., Kramer H., Krasnodembskaya A.D., Kretz-Remy C., Kroemer G., Ktistakis N.T., Kuchitsu K., Kuenen S., Kuerschner L., Kukar T., Kumar A., Kumar D., Kumar S., Kume S., Kumsta C., Kundu C.N., Kundu M., Kunnumakkara A.B., Kurgan L., Kutateladze T.G., Kutlu O., Kwak S., Kwon H.J., Kwon T.K., Kwon Y.T., Kyrmizi I., La Spada A., Labonte P., Ladoire S., Laface I., Lafont F., Lagace D.C., Lahiri V., Lai Z., Laird A.S., Lakkaraju A., Lamark T., Lan S.-H., Landajuela A., Lane D.J.R., Lane J.D., Lang C.H., Lange C., Langel U., Langer R., Lapaquette P., Laporte J., LaRusso N.F., Lastres-Becker I., Lau W.C.Y., Laurie G.W., Lavandero S., Law B.Y.K., Law H.K.-W., Layfield R., Le W., Le Stunff H., Leary A.Y., Lebrun J.-J., Leck L.Y.W., Leduc-Gaudet J.-P., Lee C., Lee C.-P., Lee D.-H., Lee E.B., Lee E.F., Lee G.M., Lee H.-J., Lee H.K., Lee J.M., Lee J.S., Lee J.-A., Lee J.-Y., Lee J.H., Lee M., Lee M.G., Lee M.J., Lee M.-S., Lee S.-J., Lee S.Y., Lee S.B., Lee W.H., Lee Y.-R., Lee Y.-H., Lee Y., Lefebvre C., Legouis R., Lei Y.L., Lei Y., Leikin S., Leitinger G., Lemus L., Leng S., Lenoir O., Lenz G., Lenz H.J., Lenzi P., Leon Y., Leopoldino A.M., Leschczyk C., Leskela S., Letellier E., Leung C.-T., Leung P.S., Leventhal J.S., Levine B., Lewis P.A., Ley K., Li B., Li D.-Q., Li J., Li K., Li L., Li M., Li P.-L., Li M.-Q., Li Q., Li S., Li T., Li W., Li X., Li Y.-P., Li Y., Lian J., Liang C., Liang Q., Liang W., Liang Y., Liao G., Liao L., Liao M., Liao Y.-F., Librizzi M., Lie P.P.Y., Lilly M.A., Lim H.J., Lima T.R.R., Limana F., Lin C., Lin C.-W., Lin D.-S., Lin F.-C., Lin J.D., Lin K.M., Lin K.-H., Lin L.-T., Lin P.-H., Lin Q., Lin S., Lin S.-J., Lin W., Lin X., Lin Y.-X., Lin Y.-S., Linden R., Lindner P., Ling S.-C., Lingor P., Linnemann A.K., Liou Y.-C., Lipinski M.M., Lipovsek S., Lira V.A., Lisiak N., Liton P.B., Liu C., Liu C.-H., Liu C.-F., Liu C.H., Liu F., Liu H.-S., Liu H.-F., Liu H., Liu J., Liu L., Liu M., Liu Q., Liu W., Liu X.-H., Liu X., Liu Y., Livingston J.A., Lizard G., Lizcano J.M., Ljubojevic-Holzer S., LLeonart 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[Ovid has truncated this field to avoid Excel character limitations], 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., 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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.P., Kaushik S., Kawasaki K., Kazan K., Ke P.-Y., Keating D.J., Keber U., Kehrl J.H., Keller K.E., Keller C.W., Kemper J.K., Kenific C.M., Kepp O., Kermorgant S., Kern A., Ketteler R., Keulers T.G., Khalfin B., Khalil H., Khambu B., Khan S.Y., Khandelwal V.K.M., Khandia R., Kho W., Khobrekar N.V., Khuansuwan S., Khundadze M., Killackey S.A., Kim D., Kim D.R., Kim D.-H., Kim D.-E., Kim E.Y., Kim E.-K., Kim H.-R., Kim H.-S., Hyung-Ryong Kim, Kim J.K., Kim J.-H., Kim J., Kim J.H., Kim K.I., Kim P.K., Kim S.-J., Kimball S.R., Kimchi A., Kimmelman A.C., Kimura T., King M.A., Kinghorn K.J., Kinsey C.G., Kirkin V., Kirshenbaum L.A., Kiselev S.L., Kishi S., Kitamoto K., Kitaoka Y., Kitazato K., Kitsis R.N., Kittler J.T., Kjaerulff O., Klein P.S., Klopstock T., Klucken J., Knaevelsrud H., Knorr R.L., Ko B.C.B., Ko F., Ko J.-L., Kobayashi H., Kobayashi S., Koch I., Koch J.C., Koenig U., Kogel D., Koh Y.H., Koike M., Kohlwein S.D., Kocaturk N.M., Komatsu M., Konig J., Kono T., Kopp B.T., Korcsmaros T., Korkmaz G., Korolchuk V.I., Korsnes M.S., Koskela A., Kota J., Kotake Y., Kotler M.L., Kou Y., Koukourakis M.I., Koustas E., Kovacs A.L., Kovacs T., Koya D., Kozako T., Kraft C., Krainc D., Kramer H., Krasnodembskaya A.D., Kretz-Remy C., Kroemer G., Ktistakis N.T., Kuchitsu K., Kuenen S., Kuerschner L., Kukar T., Kumar A., Kumar D., Kumar S., Kume S., Kumsta C., Kundu C.N., Kundu M., Kunnumakkara A.B., Kurgan L., Kutateladze T.G., Kutlu O., Kwak S., Kwon H.J., Kwon T.K., Kwon Y.T., Kyrmizi I., La Spada A., Labonte P., Ladoire S., Laface I., Lafont F., Lagace D.C., Lahiri V., Lai Z., Laird A.S., Lakkaraju A., Lamark T., Lan S.-H., Landajuela A., Lane D.J.R., Lane J.D., Lang C.H., Lange C., Langel U., Langer R., Lapaquette P., Laporte J., LaRusso N.F., Lastres-Becker I., Lau W.C.Y., Laurie G.W., Lavandero S., Law B.Y.K., Law H.K.-W., Layfield R., Le W., Le Stunff H., Leary A.Y., Lebrun J.-J., Leck L.Y.W., Leduc-Gaudet J.-P., Lee C., Lee C.-P., Lee D.-H., Lee E.B., Lee E.F., Lee G.M., Lee H.-J., Lee H.K., Lee J.M., Lee J.S., Lee J.-A., Lee J.-Y., Lee J.H., Lee M., Lee M.G., Lee M.J., Lee M.-S., Lee S.-J., Lee S.Y., Lee S.B., Lee W.H., Lee Y.-R., Lee Y.-H., Lee Y., Lefebvre C., Legouis R., Lei Y.L., Lei Y., Leikin S., Leitinger G., Lemus L., Leng S., Lenoir O., Lenz G., Lenz H.J., Lenzi P., Leon Y., Leopoldino A.M., Leschczyk C., Leskela S., Letellier E., Leung C.-T., Leung P.S., Leventhal J.S., Levine B., Lewis P.A., Ley K., Li B., Li D.-Q., Li J., Li K., Li L., Li M., Li P.-L., Li M.-Q., Li Q., Li S., Li T., Li W., Li X., Li Y.-P., Li Y., Lian J., Liang C., Liang Q., Liang W., Liang Y., Liao G., Liao L., Liao M., Liao Y.-F., Librizzi M., Lie P.P.Y., Lilly M.A., Lim H.J., Lima T.R.R., Limana F., Lin C., Lin C.-W., Lin D.-S., Lin F.-C., Lin J.D., Lin K.M., Lin K.-H., Lin L.-T., Lin P.-H., Lin Q., Lin S., Lin S.-J., Lin W., Lin X., Lin Y.-X., Lin Y.-S., Linden R., Lindner P., Ling S.-C., Lingor P., Linnemann A.K., Liou Y.-C., Lipinski M.M., Lipovsek S., Lira V.A., Lisiak N., Liton P.B., Liu C., Liu C.-H., Liu C.-F., Liu C.H., Liu F., Liu H.-S., Liu H.-F., Liu H., Liu J., Liu L., Liu M., Liu Q., Liu W., Liu X.-H., Liu X., Liu Y., Livingston J.A., Lizard G., Lizcano J.M., Ljubojevic-Holzer S., LLeonart 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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., and Wakatsuki S.
- Abstract
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.Copyright © 2020 Informa UK Limited, trading as Taylor & Francis Group.
- Published
- 2021
30. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.
- Author
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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.P., Kaushik S., Kawasaki K., Kazan K., Ke P.-Y., Keating D.J., Keber U., Kehrl J.H., Keller K.E., Keller C.W., Kemper J.K., Kenific C.M., Kepp O., Kermorgant S., Kern A., Ketteler R., Keulers T.G., Khalfin B., Khalil H., Khambu B., Khan S.Y., Khandelwal V.K.M., Khandia R., Kho W., Khobrekar N.V., Khuansuwan 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Lenzi P., Leon Y., Leopoldino A.M., Leschczyk C., Leskela S., Letellier E., Leung C.-T., Leung P.S., Leventhal J.S., Levine B., Lewis P.A., Ley K., Li B., Li D.-Q., Li J., Li K., Li L., Li M., Li P.-L., Li M.-Q., Li Q., Li S., Li T., Li W., Li X., Li Y.-P., Li Y., Lian J., Liang C., Liang Q., Liang W., Liang Y., Liao G., Liao L., Liao M., Liao Y.-F., Librizzi M., Lie P.P.Y., Lilly M.A., Lim H.J., Lima T.R.R., Limana F., Lin C., Lin C.-W., Lin D.-S., Lin F.-C., Lin J.D., Lin K.M., Lin K.-H., Lin L.-T., Lin P.-H., Lin Q., Lin S., Lin S.-J., Lin W., Lin X., Lin Y.-X., Lin Y.-S., Linden R., Lindner P., Ling S.-C., Lingor P., Linnemann A.K., Liou Y.-C., Lipinski M.M., Lipovsek S., Lira V.A., Lisiak N., Liton P.B., Liu C., Liu C.-H., Liu C.-F., Liu C.H., Liu F., Liu H.-S., Liu H.-F., Liu H., Liu J., Liu L., Liu M., Liu Q., Liu W., Liu X.-H., Liu X., Liu Y., Livingston J.A., Lizard G., Lizcano J.M., Ljubojevic-Holzer S., LLeonart M.E., Llobet-Navas D., Llorente A., Lo C.H., Lobato-Marquez D., 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[Ovid has truncated this field to avoid Excel character limitations], 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., 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Khandelwal V.K.M., Khandia R., Kho W., Khobrekar N.V., Khuansuwan S., Khundadze M., Killackey S.A., Kim D., Kim D.R., Kim D.-H., Kim D.-E., Kim E.Y., Kim E.-K., Kim H.-R., Kim H.-S., Hyung-Ryong Kim, Kim J.K., Kim J.-H., Kim J., Kim J.H., Kim K.I., Kim P.K., Kim S.-J., Kimball S.R., Kimchi A., Kimmelman A.C., Kimura T., King M.A., Kinghorn K.J., Kinsey C.G., Kirkin V., Kirshenbaum L.A., Kiselev S.L., Kishi S., Kitamoto K., Kitaoka Y., Kitazato K., Kitsis R.N., Kittler J.T., Kjaerulff O., Klein P.S., Klopstock T., Klucken J., Knaevelsrud H., Knorr R.L., Ko B.C.B., Ko F., Ko J.-L., Kobayashi H., Kobayashi S., Koch I., Koch J.C., Koenig U., Kogel D., Koh Y.H., Koike M., Kohlwein S.D., Kocaturk N.M., Komatsu M., Konig J., Kono T., Kopp B.T., Korcsmaros T., Korkmaz G., Korolchuk V.I., Korsnes M.S., Koskela A., Kota J., Kotake Y., Kotler M.L., Kou Y., Koukourakis M.I., Koustas E., Kovacs A.L., Kovacs T., Koya D., Kozako T., Kraft C., Krainc D., Kramer H., Krasnodembskaya A.D., Kretz-Remy C., 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Leitinger G., Lemus L., Leng S., Lenoir O., Lenz G., Lenz H.J., Lenzi P., Leon Y., Leopoldino A.M., Leschczyk C., Leskela S., Letellier E., Leung C.-T., Leung P.S., Leventhal J.S., Levine B., Lewis P.A., Ley K., Li B., Li D.-Q., Li J., Li K., Li L., Li M., Li P.-L., Li M.-Q., Li Q., Li S., Li T., Li W., Li X., Li Y.-P., Li Y., Lian J., Liang C., Liang Q., Liang W., Liang Y., Liao G., Liao L., Liao M., Liao Y.-F., Librizzi M., Lie P.P.Y., Lilly M.A., Lim H.J., Lima T.R.R., Limana F., Lin C., Lin C.-W., Lin D.-S., Lin F.-C., Lin J.D., Lin K.M., Lin K.-H., Lin L.-T., Lin P.-H., Lin Q., Lin S., Lin S.-J., Lin W., Lin X., Lin Y.-X., Lin Y.-S., Linden R., Lindner P., Ling S.-C., Lingor P., Linnemann A.K., Liou Y.-C., Lipinski M.M., Lipovsek S., Lira V.A., Lisiak N., Liton P.B., Liu C., Liu C.-H., Liu C.-F., Liu C.H., Liu F., Liu H.-S., Liu H.-F., Liu H., Liu J., Liu L., Liu M., Liu Q., Liu W., Liu X.-H., Liu X., Liu Y., Livingston J.A., Lizard G., Lizcano J.M., Ljubojevic-Holzer S., LLeonart 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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., Wang C.-Y., 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.-Y., Wang 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., and W... [Ovid has truncated this field to avoid Excel character limitations]
- Abstract
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.Copyright © 2020 Informa UK Limited, trading as Taylor & Francis Group.
- Published
- 2021
31. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)
- Author
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Yu, Seong-Woon, Yu, Victor C, Yu, W Haung, Yu, Zhengping, Yu, Zhou, Yuan, Junying, Yuan, Ling-Qing, Yuan, Shilin, Yuan, Shyng-Shiou F, Yuan, Yanggang, Yuan, Zengqiang, Yue, Jianbo, Yue, Zhenyu, Yun, Jeanho, Yung, Raymond L, Zacks, David N, Zaffagnini, Gabriele, Zambelli, Vanessa O, Zanella, Isabella, Zang, Qun S, Zanivan, Sara, Zappavigna, Silvia, Zaragoza, Pilar, Zarbalis, Konstantinos S, Zarebkohan, Amir, Zarrouk, Amira, Zeitlin, Scott O, Zeng, Jialiu, Zeng, Ju-Deng, Žerovnik, Eva, Zhan, Lixuan, Zhang, Bin, Zhang, Donna D, Zhang, Hanlin, Zhang, Hong, Zhang, Honghe, Zhang, Huafeng, Zhang, Huaye, Zhang, Hui, Zhang, Hui-Ling, Zhang, Jianbin, Zhang, Jianhua, Zhang, Jing-Pu, Zhang, Kalin Y B, Zhang, Leshuai W, 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 M, Ziviani, Elena, Zoladek, Teresa, Zong, Wei-Xing, Zorov, Dmitry B, 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 C, Stallings, Christina L, and Tong, Chun-Kit
- Abstract
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
32. The milling tool wear monitoring using the acoustic spectrum
- Author
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Ai, C. S., Sun, Y. J., He, G. W., Ze, X. B., Li, W., and Mao, K.
- Published
- 2012
- Full Text
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33. Mafa expression enhances glucose-responsive insulin secretion in neonatal rat beta cells
- Author
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Aguayo-Mazzucato, C., Koh, A., El Khattabi, I., Li, W.-C., Toschi, E., Jermendy, A., Juhl, K., Mao, K., Weir, G. C., Sharma, A., and Bonner-Weir, S.
- Published
- 2011
- Full Text
- View/download PDF
34. An initial approach to the link of multi-layer coatings contact stresses and the surface engineered gears
- Author
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Mao, K., Sun, Y., and Bell, T.
- Published
- 2007
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- View/download PDF
35. A numerical method for polymer composite gear flash temperature prediction
- Author
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Mao, K.
- Published
- 2007
- Full Text
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36. Gear tooth contact analysis and its application in the reduction of fatigue wear
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Mao, K.
- Published
- 2007
- Full Text
- View/download PDF
37. A new approach for polymer composite gear design
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Mao, K.
- Published
- 2007
- Full Text
- View/download PDF
38. Novel Nomograms to Predict Lymph Node Metastasis and Liver Metastasis in Patients with Early Colon Carcinoma
- Author
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Yan, Y., primary, Mao, K., additional, Lin, J., additional, Chen, R., additional, Wang, J., additional, and Xiao, Z., additional
- Published
- 2021
- Full Text
- View/download PDF
39. A Novel Staging System to Forecast the Cancer-Specific Survival of Gallbladder Cancer Patients
- Author
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Yan, Y., primary, Mao, K., additional, Lin, J., additional, Liu, H., additional, He, C., additional, Wang, J., additional, and Xiao, Z., additional
- Published
- 2021
- Full Text
- View/download PDF
40. Development and External Validation of Prognostic Nomograms in Hepatocellular Carcinoma Patients: A Population Based Study
- Author
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Yan, Y., primary, Mao, K., additional, He, C., additional, Chen, R., additional, Wang, J., additional, and Xiao, Z., additional
- Published
- 2021
- Full Text
- View/download PDF
41. 1013P PTPN13 inactivation by hepatitis B virus X regulates metabolic reprogramming for hepatocellular carcinoma progression
- Author
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Yan, Y., primary, Mao, K., additional, He, C., additional, Liu, H., additional, Zhang, J., additional, Wang, J., additional, and Xiao, Z., additional
- Published
- 2020
- Full Text
- View/download PDF
42. 68P Analysis of DNA damage repair (DDR) pathway genes in biliary tract cancer and correlation with immunogenic biomarker
- Author
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Xiao, Z., primary, Zhang, J., additional, Zhou, Q., additional, He, C., additional, Mao, K., additional, Chen, T., additional, Xie, W., additional, and Huang, M., additional
- Published
- 2020
- Full Text
- View/download PDF
43. 1970P A multivariate logistic regression model for detection of upper tract urinary carcinoma in patients with hematuria
- Author
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Xu, Y., primary, Ma, T., additional, Liang, Y., additional, Mao, K., additional, and Zhang, X., additional
- Published
- 2020
- Full Text
- View/download PDF
44. The ties problem resulting from counting-based error estimators and its impact on gene selection algorithms
- Author
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Zhou, Xin and Mao, K. Z.
- Published
- 2006
45. Effect of sliding friction on contact stresses for multi-layered elastic bodies with rough surfaces
- Author
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Mao, K., Bell, T., and Sun, Y.
- Subjects
Friction -- Research ,Strains and stresses -- Research ,Surface roughness -- Research ,Science and technology - Abstract
The stress distributions associated with frictionless and smooth surfaces in contact are rarely experienced in practice. Factors such as layers, friction, surface roughness, lubricant films, and third body particulate are known to influence the state of stress and the resulting rolling contact fatigue life. A numerical technique for evaluating the subsurface stresses arising from the two-dimensional sliding contact of two elastic bodies with real rough surfaces has been developed, where an elastic body contacts with a multi-layer surface under both normal and tangential forces. The presence of friction and asperities within the contact region causes a large, highly stress region exposed to the surface. The significance of these near-surface stresses is related to modes of surface distress leading to surface eventual failure (Mao et al., 1997).
- Published
- 1997
46. LS Bound based gene selection for DNA microarray data
- Author
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Zhou, Xin and Mao, K. Z.
- Published
- 2005
47. Modeling plasma nitriding
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Bell, T., Sun, Y., Mao, K., and Buchhagen, P.
- Subjects
Metalwork -- Research -- Models ,Nitriding -- Models -- Research - Abstract
A recently developed software package has potential for use in engineering design and the selection of optimum nitriding parameters. Nitriding is one of the most widely used surface engineering techniques. […]
- Published
- 1996
48. Quantitative assessment of cerebella ataxia through automated upper limb functional tests
- Author
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Mao, K., Jiang, X., Krishna, Ragil, Pathirana, Pubudu, Horne, Malcolm, Power, Laura, Szmulewicz, David, Mao, K., Jiang, X., Krishna, Ragil, Pathirana, Pubudu, Horne, Malcolm, Power, Laura, and Szmulewicz, David
- Abstract
Neurological disorders typically exhibit movement disabilities and disorders such as cerebellar ataxia (CA) can cause coordination inaccuracies often manifested as disabilities associated with gait, balance and speech. Since the severity assessment of the disorder is based on the expert clinical opinion, it is likely to be subjective. Automated versions of two upper limb tests: Finger to Nose test (FNT) and Diadochokinesia (DDK) test are investigated in this paper. Inertial Measurement Units (IMU) (BioKinTM ) are employed to capture the disability by measuring limb movements. Translational and rotational accelerations considered as kinematic parameters provided the features relevant to characteristic movements intrinsic to the disability. Principal Component Analysis (PCA) and multi-class Linear Discriminant classifier (LDA) were instrumental in dominant features correlating with the clinical scores. The relationship between clinicians assessment and the objective analysis is examined using Pearson Correlation. This study found that although FNT predominantly consist of translational movements, rotation was the dominant feature while for the case of DDK that predominantly consist of rotational movements, acceleration was the dominant feature. The degree of correlation in each test was also enhanced by combining the features in different tests.
- Published
- 2019
49. Word2Cluster: A new multi-label text clustering algorithm with an adaptive clusters number
- Author
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Mao, K, Niu, J, Liu, X, Yu, S, Zhao, L, Mao, K, Niu, J, Liu, X, Yu, S, and Zhao, L
- Abstract
Text clustering has been widely used in many Natural Language Processing (NLP) applications such as text summarization and news recommendation. However, most of the current algorithms need to predefine a clustering number, which is difficult to obtain. Moreover, the mutli-label clustering is useful in multiple clustering tasks in many applications, but related works are rarely available. Although several studies have attempted to solve above two problems, there is a need for methods that can solve the two issues simultaneously. Therefore, we propose a new text clustering algorithm called Word2Cluster. Word2Cluster can automatically generate an adaptive number of clusters and support multi-label clustering. To test the performance of Wrod2Cluster, we build a Chinese text dataset, Hotline, according to real world applications. To evaluate the clustering results better, we propose an improved evaluation method based on basic accuracy, precision and recall for multi-label text clustering. Experimental results on a Chinese text dataset (Hotline) and a public English text dataset (Reuters) demonstrate that our algorithm can achieve better F1-measure and runs faster than the state-of- the-art baselines.
- Published
- 2019
50. The peri-albumen layer: a novel structure in the envelopes of an avian egg
- Author
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Sultana, F., Yokoe, A., Ito, Y., Mao, K. M., and Yoshizaki, N.
- Published
- 2003
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