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The spectral quality of magnetic resonance spectroscopic imaging (MRSI) can be affected by strong magnetic field inhomogeneities, posing a challenge for 3D-MRSI’s widespread clinical use with standard scanner-equipped 2nd-order shim coils. To overcome this, we designed an empirical unified shim–RF head coil (32-ch RF receive and 51-ch shim) for 3D-MRSI improvement. We compared its shimming performance and 3D-MRSI brain coverages against the standard scanner shim (2nd-order spherical harmonic (SH) shim coils) and integrated parallel reception, excitation, and shimming (iPRES) 32-ch AC/DC head coil. We also simulated a theoretical 3rd-, 4th-, and 5th-order SH shim as a benchmark to assess the UNIfied shim–RF coil (UNIC) improvements. In this preliminary study, the whole-brain coverage was simulated by using B0 field maps of twenty-four healthy human subjects (n = 24). Our results demonstrated that UNIC substantially improves brain field homogeneity, reducing whole-brain frequency standard deviations by 27% compared to the standard 2nd-order scanner shim and 17% compared to the iPRES shim. Moreover, UNIC enhances whole-brain coverage of 3D-MRSI by up to 34% compared to the standard 2nd-order scanner shim and up to 13% compared to the iPRES shim. UNIC markedly increases coverage in the prefrontal cortex by 147% and 47% and in the medial temporal lobe and temporal pole by 29% and 13%, respectively, at voxel resolutions of 1.4 cc and 0.09 cc for 3D-MRSI. Furthermore, UNIC effectively reduces variations in shim quality and brain coverage among different subjects compared to scanner shim and iPRES shim. Anticipated advancements in higher-order shimming (beyond 6th order) are expected via optimized designs using dimensionality reduction methods.

The plasticizer is crucial in the plant-based soft capsule. However, meeting the quality requirements of these capsules with a single plasticizer is challenging. To address this issue, this study first investigated the impact of a plasticizer mixture containing sorbitol and glycerol in varying mass ratios and the performance of the pullulan soft film and capsule. The multiscale analysis demonstrates that the plasticizer mixture exhibits superior effectiveness in enhancing the performance of the pullulan film/capsule compared to a single plasticizer. Furthermore, thermogravimetric analysis, Fourier transform infrared spectroscopy, X-ray diffraction, and scanning electron microscopy indicate that the plasticizer mixture enhances the compatibility and thermal stability of the pullulan films without altering their chemical composition. Among the different mass ratios examined, a 15:15 ratio of sorbitol to glycerol (S/G) is identified as the most optimal, leading to superior physicochemical properties and meeting the requirements for brittleness and disintegration time set by the Chinese Pharmacopoeia. This study provides significant insights into the effect of the plasticizer mixture on the performance of pullulan soft capsules and offers a promising application formula for future use.

Xu Yang,1 Mi Yao,2 Delu Yin,3 Na Zhang,1 Jing Li,1 Yan Jiang,1 Rundong Fu,1 Yi Qian1 1Department of General Practice, Donghuashi Community Health Service Center, Beijing, People’s Republic of China; 2Department of General Practice, Peking University Health Science Center, Beijing, People’s Republic of China; 3Department of Health Development, Capital Institute of Pediatrics, Beijing, People’s Republic of ChinaCorrespondence: Xu Yang, Department of General Practice, Donghuashi Community Health Service Center, 33 Donghuashi Street, Dongcheng District, Beijing, 100062, People’s Republic of China, Tel +86 13693088802, Fax +86 1067120077, Email xuyang8799@163.comBackground: Chronic obstructive pulmonary disease (COPD) has a high incidence rate in China, but the diagnosis rate remains insufficient. This study aimed to explore and compare COPD screening tools for primary healthcare institutions in China.Purpose: Exploring COPD Screening Tools and Their Combined Use for Primary Healthcare Institutions in China.Patients and Methods: From September 2022 to March 2023, a screening for COPD was conducted among residents aged 35 years and above in primary healthcare institutions in Beijing, China. The screening involved the use of the CAPTURE scale, COPD-SQ scale, and peak expiratory flow rate test. Any positive results from these screening tests were followed by further pulmonary function testing to confirm the diagnosis. Sensitivity, specificity, positive predictive value, negative predictive value, and receiver operating characteristic (ROC) curves were calculated for each screening tool alone and in combination.Results: A total of 986 individuals completed the screening tests. The positive rates for the CAPTURE scale, COPD-SQ scale, and peak flow meter screening were 41.78%, 29.11%, and 52.03%, respectively. Of the participants, 166 (24.09%) underwent pulmonary function tests, with an average age of 61.69± 13.68 years. The peak flow meter screening showed the highes

Lili Gao,1,2 Ying Lu,1 Na Zhang,3 Yi Wang,1,4 Weimin Yang,5 Xiaopeng Deng1 1Department of Construction and Real Estate, Southeast University, Nanjing, People’s Republic of China; 2Department of Architecture and Civil Engineering, City University of Hong Kong, Hong Kong, China; 3School of Civil Engineering and Architecture, Zhejiang University of Technology, Hangzhou, People’s Republic of China; 4College of Design and Engineering, National University of Singapore, Singapore, Singapore; 5School of Digital Commerce, Jiangsu Vocational Institute of Commerce, Nanjing, People’s Republic of ChinaCorrespondence: Ying Lu; Xiaopeng Deng, Department of Construction and Real Estate, Southeast University, No. 2 Southeast Road, Nanjing, 211100, People’s Republic of China, Email luying_happy@126.com; dxp@seu.edu.cnIntroduction: Expatriates are facing more stressors, such as cross-cultural adjustment, global political instability, family separation, health concern. The black swan events of the pandemic and the Russian-Ukrainian war have posed significant challenges in the current international environment. Adapting to an expatriate environment as soon as possible is critical to expatriate success. This study aims to examine the factors that affect expatriate adjustment through psychological resilience.Methods: Guided by person-environment (p-e) fit theory, an expatriate adjustment framework based on psychological resilience is proposed, and 309 valid sample data are used for structural equation model (SEM) analysis.Results: The results show that expatriate adjustment is a psychological process based on the development of resilience. Social support plays a buffering role in dealing with environmental deviations induced stressors. The person-environment transactional process is the most critical adjustment process.Discussion: The development of expatriate adjustment is divided into four stages (shock, buffer, adjustment, mastery) consistent with resilience development. Projec

Using plant-based polysaccharide gels to produce hard capsules is a novel application of this technology in the medicinal field, which has garnered significant attention. However, the current manufacturing technology, particularly the drying process, limits its industrialization. The work herein employed an advanced measuring technique and a modified mathematical model to get more insight into the drying process of the capsule. Low field magnetic resonance imaging (LF-MRI) technique is adopted to reveal the distribution of moisture content in the capsule during drying. Furthermore, a modified mathematical model is developed by considering the dynamic variation of the effective moisture diffusivity (Deff) according to Fick’s second law, which enables accurate prediction of the moisture content of the capsule with a prediction accuracy of ±15%. The predicted Deff ranges from 3 × 10−10 to 7 × 10−10 m2·s−1, which has an irregular variation with a time extension. Moreover, as temperature increases or relative humidity decreases, there is an increased acceleration of moisture diffusion. The work provides a fundamental understanding of the drying process of the plant-based polysaccharide gel, which is crucial for enhancing the industrial preparation of the HPMC-based hard capsules.

Background: Predicting the mutation status of the epidermal growth factor receptor (EGFR) gene based on an integrated positron emission tomography/computed tomography (PET/CT) image of non-small cell lung cancer (NSCLC) is a noninvasive, low-cost method which is valuable for targeted therapy. Although deep learning has been very successful in robotic vision, it is still challenging to predict gene mutations in PET/CT-derived studies because of the small amount of medical data and the different parameters of PET/ CT devices.Methods: We used the advanced EfficientNet-V2 model to predict the EGFR mutation based on fused PET/CT images. First, we extracted 3-dimensional (3D) pulmonary nodules from PET and CT as regions of interest (ROIs). We then fused each single PET and CT image. The network model was used to predict the mutation status of lung nodules by the new data after fusion, and the model was weighted adaptively. The EfficientNet-V2 model used multiple channels to represent nodules comprehensively.Results: We trained the EfficientNet-V2 model through our PET/CT fusion algorithm using a dataset of 150 patients. The prediction accuracy of EGFR and non-EGFR mutations was 86.25% in the training dataset, and the accuracy rate was 81.92% in the validation set.Conclusions: Combined with experiments, the demonstrated PET/CT fusion algorithm outperformed radiomics methods in predicting EGFR and non-EGFR mutations in NSCLC.

Semantic face image manipulation has received increasing attention in recent years. StyleGAN-based approaches to face morphing are among the leading techniques; however, they often suffer from noticeable blurring and artifacts as a result of the uniform attention in the latent feature space. In this paper, we propose to develop a transformer-based alternative to face morphing and demonstrate its superiority to StyleGAN-based methods. Our contributions are threefold. First, inspired by GANformer, we introduce a bipartite structure to exploit long-range interactions in face images for iterative propagation of information from latent variables to salient facial features. Special loss functions are designed to support the optimization of face morphing. Second, we extend the study of transformer-based face morphing to demorphing by presenting an effective defense strategy with access to a reference image using the same generator of MorphGANFormer. Such demorphing is conceptually similar to unmixing of hyperspectral images but operates in the latent (instead of pixel) space. Third, for the first time, we address a fundamental issue of vulnerability-detectability trade-off for face morphing studies. It is argued that neither doppelganger norrandom pair selection is optimal, and a Lagrangian multiplier-based approach should be used to achieve an improved trade-off between recognition vulnerability and attack detectability., Comment: 13 pages, 13 figures

Chan Dai,1 Huoying Chen,2 Mengya Jiao,1 Na Zhang,1 Xuhuan Tang,1 Anqi Fan,3 Shiwang Liu,1 Zhigang Qian,1 Chenchen Wang,1 Yong Xu,1 Zheng Tan,1,4 Fanfan Zeng,5 Fang Zheng1,4 1Department of Immunology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People’s Republic of China; 2Department of Laboratory Medicine, The Second Affiliated Hospital of Guilin Medical University, Guilin, Guizhou, People’s Republic of China; 3College of Life Science, Yangtze University, Jingzhou, Hubei, People’s Republic of China; 4Key Laboratory of Organ Transplantation, Ministry of Education, NHC Key Laboratory of Organ Transplantation, Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Wuhan, Hubei, People’s Republic of China; 5Department of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People’s Republic of ChinaCorrespondence: Fang Zheng, Department of Immunology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, Hubei, People’s Republic of China, Email zhengfangtj@hust.edu.cn Fanfan Zeng, Department of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, Hubei, People’s Republic of China, Email zengfanfan@126.comPurpose: IL-33 is constitutively expressed in skin tissues. Alopecia, a T cells-driven disorder of the hair follicles (HFs), is a common complication in the development of psoriasis. However, the role of IL-33 in psoriatic alopecia remains uncovered. Here, we investigated the roles of IL-33 in inducing pathological changes of hair follicles in psoriasis.Patients and Methods: Clinical samples and imiquimod (IMQ)-induced psoriatic mice samples were used to investigate the pathological changes and T-cell infiltration of HFs. By using immunohistochemistry staining, the distribut

As a transformative general-purpose technology, AI has empowered various industries and will continue to shape our lives through ubiquitous applications. Despite the enormous benefits from wide-spread AI deployment, it is crucial to address associated downside risks and therefore ensure AI advances are safe, fair, responsible, and aligned with human values. To do so, we need to establish effective AI governance. In this work, we show that the strategic interaction between the regulatory agencies and AI firms has an intrinsic structure reminiscent of a Stackelberg game, which motivates us to propose a game-theoretic modeling framework for AI governance. In particular, we formulate such interaction as a Stackelberg game composed of a leader and a follower, which captures the underlying game structure compared to its simultaneous play counterparts. Furthermore, the choice of the leader naturally gives rise to two settings. And we demonstrate that our proposed model can serves as a unified AI governance framework from two aspects: firstly we can map one setting to the AI governance of civil domains and the other to the safety-critical and military domains, secondly, the two settings of governance could be chosen contingent on the capability of the intelligent systems. To the best of our knowledge, this work is the first to use game theory for analyzing and structuring AI governance. We also discuss promising directions and hope this can help stimulate research interest in this interdisciplinary area. On a high, we hope this work would contribute to develop a new paradigm for technology policy: the quantitative and AI-driven methods for the technology policy field, which holds significant promise for overcoming many shortcomings of existing qualitative approaches.

How can we teach a computer to recognize 10,000 different actions? Deep learning has evolved from supervised and unsupervised to self-supervised approaches. In this paper, we present a new contrastive learning-based framework for decision tree-based classification of actions, including human-human interactions (HHI) and human-object interactions (HOI). The key idea is to translate the original multi-class action recognition into a series of binary classification tasks on a pre-constructed decision tree. Under the new framework of contrastive learning, we present the design of an interaction adjacent matrix (IAM) with skeleton graphs as the backbone for modeling various action-related attributes such as periodicity and symmetry. Through the construction of various pretext tasks, we obtain a series of binary classification nodes on the decision tree that can be combined to support higher-level recognition tasks. Experimental justification for the potential of our approach in real-world applications ranges from interaction recognition to symmetry detection. In particular, we have demonstrated the promising performance of video-based autism spectrum disorder (ASD) diagnosis on the CalTech interview video database., Comment: Accepted by ACM Multimedia Systems Conference 2023

The study of high-entropy materials has attracted enormous interest since they could show new functional properties that are not observed in their related parent phases. Here, we report single crystal growth, structure, thermal transport, and magnetic property studies on a novel high-entropy oxide with the spinel structure (MgMnFeCoNi)Al2O4. We have successfully grown high-quality single crystals of this high-entropy oxide using the optical floating zone growth technique for the first time. The sample was confirmed to be a phase pure high-entropy oxide using x-ray diffraction and energy-dispersive spectroscopy. Through magnetization measurements, we found (MgMnFeCoNi)Al2O4 exhibits a cluster spin glass state, though the parent phases show either antiferromagnetic ordering or spin glass states. Furthermore, we also found that (MgMnFeCoNi)Al2O4 has much greater thermal expansion than its CoAl2O4 parent compound using high resolution neutron Larmor diffraction. We further investigated the structure of this high-entropy material via Raman spectroscopy and extended x-ray absorption fine structure spectroscopy (EXAFS) measurements. From Raman spectroscopy measurements, we observed (MgMnFeCoNi)Al2O4 to display a combination of the active Raman modes in its parent compounds with the modes shifted and significantly broadened. This result, together with the varying bond lengths probed by EXAFS, reveals severe local lattice distortions in this high-entropy phase. Additionally, we found a substantial decrease in thermal conductivity and suppression of the low temperature thermal conductivity peak in (MgMnFeCoNi)Al2O4, consistent with the increased lattice defects and strain. These findings advance the understanding of the dependence of thermal expansion and transport on the lattice distortions in high-entropy materials.

Data augmentation has been proven effective for training high-accuracy convolutional neural network classifiers by preventing overfitting. However, building deep neural networks in real-world scenarios requires not only high accuracy on clean data but also robustness when data distributions shift. While prior methods have proposed that there is a trade-off between accuracy and robustness, we propose IPMix, a simple data augmentation approach to improve robustness without hurting clean accuracy. IPMix integrates three levels of data augmentation (image-level, patch-level, and pixel-level) into a coherent and label-preserving technique to increase the diversity of training data with limited computational overhead. To further improve the robustness, IPMix introduces structural complexity at different levels to generate more diverse images and adopts the random mixing method for multi-scale information fusion. Experiments demonstrate that IPMix outperforms state-of-the-art corruption robustness on CIFAR-C and ImageNet-C. In addition, we show that IPMix also significantly improves the other safety measures, including robustness to adversarial perturbations, calibration, prediction consistency, and anomaly detection, achieving state-of-the-art or comparable results on several benchmarks, including ImageNet-R, ImageNet-A, and ImageNet-O., Comment: NeurIPS 2023

This paper unveils CG-Eval, the first-ever comprehensive and automated evaluation framework designed for assessing the generative capabilities of large Chinese language models across a spectrum of academic disciplines. CG-Eval stands out for its automated process, which critically assesses models based on their proficiency in generating precise and contextually relevant responses to a diverse array of questions within six key domains: Science and Engineering, Humanities and Social Sciences, Mathematical Calculations, Medical Practitioner Qualification Examination, Judicial Examination, and Certified Public Accountant Examination. Alongside this, we introduce Gscore, an innovative composite index developed from a weighted sum of multiple metrics. Gscore uniquely automates the quality measurement of a model's text generation against reference standards, providing a detailed and nuanced assessment of model performance. This automation not only enhances the efficiency and scalability of the evaluation process but also ensures objective and consistent assessment across various models. The detailed test data and results, highlighting the robust capabilities and comparative performance of the evaluated models, are accessible at http://cgeval.besteasy.com/.

Unconstrained face recognition is an active research area among computer vision and biometric researchers for many years now. Still the problem of face recognition in low quality photos has not been well-studied so far. In this paper, we explore the face recognition performance on low quality photos, and we try to improve the accuracy in dealing with low quality face images. We assemble a large database with low quality photos, and examine the performance of face recognition algorithms for three different quality sets. Using state-of-the-art facial image enhancement approaches, we explore the face recognition performance for the enhanced face images. To perform this without experimental bias, we have developed a new protocol for recognition with low quality face photos and validate the performance experimentally. Our designed protocol for face recognition with low quality face images can be useful to other researchers. Moreover, experiment results show some of the challenging aspects of this problem., Comment: 8 pages, 11 figures

MOBIO is a bi-modal database that was captured almost exclusively on mobile phones. It aims to improve research into deploying biometric techniques to mobile devices. Research has been shown that face and speaker recognition can be performed in a mobile environment. Facial landmark localization aims at finding the coordinates of a set of pre-defined key points for 2D face images. A facial landmark usually has specific semantic meaning, e.g. nose tip or eye centre, which provides rich geometric information for other face analysis tasks such as face recognition, emotion estimation and 3D face reconstruction. Pretty much facial landmark detection methods adopt still face databases, such as 300W, AFW, AFLW, or COFW, for evaluation, but seldomly use mobile data. Our work is first to perform facial landmark detection evaluation on the mobile still data, i.e., face images from MOBIO database. About 20,600 face images have been extracted from this audio-visual database and manually labeled with 22 landmarks as the groundtruth. Several state-of-the-art facial landmark detection methods are adopted to evaluate their performance on these data. The result shows that the data from MOBIO database is pretty challenging. This database can be a new challenging one for facial landmark detection evaluation., Comment: 13 pages, 10 figures

Deep learning has received increasing interests in face recognition recently. Large quantities of deep learning methods have been proposed to handle various problems appeared in face recognition. Quite a lot deep methods claimed that they have gained or even surpassed human-level face verification performance in certain databases. As we know, face image quality poses a great challenge to traditional face recognition methods, e.g. model-driven methods with hand-crafted features. However, a little research focus on the impact of face image quality on deep learning methods, and even human performance. Therefore, we raise a question: Is face image quality still one of the challenges for deep learning based face recognition, especially in unconstrained condition. Based on this, we further investigate this problem on human level. In this paper, we partition face images into three different quality sets to evaluate the performance of deep learning methods on cross-quality face images in the wild, and then design a human face verification experiment on these cross-quality data. The result indicates that quality issue still needs to be studied thoroughly in deep learning, human own better capability in building the relations between different face images with large quality gaps, and saying deep learning method surpasses human-level is too optimistic., Comment: 11 pages, 11 figures

Optimal management of the perennial bioenergy crops, miscanthus and switchgrass, requires an understanding of their responsiveness to nitrogen (N) fertilizer at different maturity stages across locations and growing conditions. Earlier studies that have examined the yield response of these crops to N and stand age using field experiments or meta-analysis techniques provide mixed evidence. We extend earlier studies by applying a multi-level mixed-effects (MLME) meta-regression model to conduct a more extensive multivariate regression of yield response of these crops to N and stand age, while controlling for climate and location conditions and unobserved factors related to study design. Our findings are based on 1403 and 2811 yield observations for miscanthus and switchgrass, respectively, from experiments conducted between 2002 and 2019 across the rainfed region in the United States. We find statistically significant evidence that an additional year of maturity increases miscanthus and switchgrass yields but at a decreasing rate; yields peak at the 7th and 6th year respectively, for the observed range of applied N rates and stands. We also find that an increase in N application increases yield by a statistically significant level, but at a declining rate; the magnitude of the yield response to N is, however, small and varies with the age of the crop. The impact of N is larger on older compared to younger and middle-aged stands of miscanthus. In contrast, the impact of N on switchgrass is larger on middle-aged compared to younger and older stands of switchgrass. We do not find a statistically significant effect of soil productivity on yield for either crop. This analysis provides a basis for developing N application recommendations and optimal rotation age for miscanthus and switchgrass and shows that these energy crops can grow just as productively on low productivity land as on high productivity land.

Autism is a prevalent neurodevelopmental disorder characterized by impairments in social and communicative behaviors. The possible connections between autism and facial expression recognition have been studied in the literature recently. However, most works are based on facial images or short videos. Few works aim at Autism Diagnostic Observation Schedule (ADOS) videos due to their complexity (e.g., interaction between interviewer and interviewee) and length (e.g., usually last for hours). In this paper, we attempt to fill this gap by developing a novel discriminative few shot learning method to analyze hour-long video data and exploring the fusion of facial dynamics for the trait classification of ASD. Leveraging well-established computer vision tools from spatio-temporal feature extraction and marginal fisher analysis to few-shot learning and scene-level fusion, we have constructed a three-category system to classify an individual into Autism, Autism Spectrum, and Non-Spectrum. For the first time, we have shown that certain interview scenes carry more discriminative information for ASD trait classification than others. Experimental results are reported to demonstrate the potential of the proposed automatic ASD trait classification system (reaching 91.72% accuracy on Caltech ADOS video dataset) and the benefits of few-shot learning and scene-level fusion strategy by extensive ablation studies.

Samarium orthoferrite, SmFeO3 (SFO), is a multifunctional material with promised applications. In this paper, SFO thin films were prepared by sol–gel method onto a quartz substrate at different annealing temperatures (T = 700, 750, 800 and 850 °C) and onto LaNiO3 (LNO) buffered quartz substrate using T = 800 °C. The phase formation, microstructure, electronic, optical, magnetic and ferroelectric properties of the films were investigated and compared. Minimal annealing temperature (T) from thermogravimetric analysis was about 720 °C. From X-ray diffraction analysis, film T = 700 °C showed mixed phases of SFO and a trace amount of Sm2O3 while single phase of SFO was observed for films T = 750 – 850 °C. The lattice parameter c and microstrain reduced for films T = 700 – 800 °C and then increased for film T = 850 °C. From Atomic force microscopy analysis, the porosity, root mean square roughness and particle size of the films increased with the rise of T. All films exhibited high optical transmittance (∼79 – 95 %) in 800 – 550 nm wavelength range and showed two main optical absorptions peaks at about 285 and 385 nm. At lower energy transition, the band gap (Eg) reduced from ∼ 2.79 to 2.72 eV for films T = 700 – 800 °C and then increased to ∼ 2.79 eV for film T = 850 °C. The film’s magnetisation (Ms) tended to increase with T increment. The SFO/LNO film showed higher Ms and Eg than film T = 800 °C.

Yixuan Bai,1 Chenggang Lei,2 Na Zhang,1 Yuhui Liu,1 Zhengyu Hu,3 Yan Li,4 Ran Qi5 1Department of Digestive Internal Medicine, Affiliated Dalian Friendship Hospital of Dalian Medical University, Dalian, People’s Republic of China; 2Department of Hepatobiliary Surgery, Qingdao Municipal Hospital, Qingdao, People’s Republic of China; 3Department of General Surgery, Shanghai Tenth People’s Hospital, Affiliated to Tongji University School of Medicine, Shanghai, People’s Republic of China; 4Department of Gastroenterology, Shanghai Tenth People’s Hospital, Affiliated to Tongji University School of Medicine, Shanghai, People’s Republic of China; 5Department of General Surgery, Tongji Hospital of Tongji University, School of Medicine, Tongji University, Shanghai, People’s Republic of ChinaCorrespondence: Ran Qi, Department of General Surgery, Tongji Hospital of Tongji University, School of Medicine, Tongji University, 389 Xincun Road, Putuo District, Shanghai, 200092, People’s Republic of China, Email 2011070@tongji.edu.cnAim: The aim of this study was to identify clinical endoscopic indicators related to peri-ulcerative mucosal inflammation and to analyze whether the degree of peri-ulcerative mucosal inflammation appearance is an independent risk factor for gastric ulcer rebleeding.Methods: We conducted a retrospective study that included patients with gastric ulcer bleeding who were hospitalized at three medical centers in China from January 1, 2016 to December 31, 2019. Ulcer rebleeding that occurred within 30 days of successful initial hemostasis was analyzed to determine whether this event was related to the degree of peri-ulcerative mucosal inflammation appearance or other mucosal inflammation-related factors.Results: We enrolled 1111 patients and determined that GBS-Rebleeding-ROC (P< 0.001), age (P=0.01), use of NSAIDs (P=0.001), bile reflux (P< 0.001), and Helicobacter pylo

Yaowen Li,1,2 Yu Peng,1,2 Na Zhang,1,2 Huiping Liu,1,2 Jun Mao,1,2 Yisong Yan,3 Shuaishuai Wang,1,2 Guang Yang,4 Yanyan Liu,5 Jiabin Li,5 Xiaohui Huang1,2 1Department of Basic and Clinical Pharmacology, School of Pharmacy, Anhui Medical University, Hefei, People’s Republic of China; 2Anhui Province Key Laboratory of Major Autoimmune Diseases, School of Pharmacy, Anhui Institute of Innovative Drugs, Anhui Medical University, Hefei, People’s Republic of China; 3Department of Pharmacy, Anhui College of Traditional Chinese Medicine, Wuhu, Anhui, People’s Republic of China; 4Department of Pharmacy, The Third People’s Hospital of Tongling, Tongling, Anhui, People’s Republic of China; 5Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of ChinaCorrespondence: Xiaohui Huang, Department of Basic and Clinical Pharmacology, School of Pharmacy, Anhui Medical University, Meishan Road 81#, Hefei, Anhui, 230032, People’s Republic of China, Tel +86 138 5518 3138, Email math2088@163.comPurpose: We aimed to evaluate the synergistic effect of linezolid and fosfomycin on fosfomycin-sensitive and -resistant Enterococcus clinical isolates in vitro and in vivo and whether the emergence of fosfomycin resistance in Enterococcus is associated with changes in strain virulence, from the perspective of fitness cost.Methods: The synergistic effect of linezolid and fosfomycin was studied via in vitro checkerboard and static time-kill assays, as well as based on the in vivo survival rate and hemolymph load of a Galleria mellonella infection model. Fosfomycin resistance was induced via a stepwise increase in concentration. Changes in the virulence of the strains after drug resistance were investigated using the G. mellonella infection model and reverse transcription quantitative polymerase chain reaction (RT-qPCR). In vitro and in vivo growth curves and competitive experiments were used to study the fitness cost of th

This research explores followers’ characteristics from doctors’ perspectives and the leader-member exchange imperative in the Hospital of Chengdu University of Traditional Chinese Medicine’s performance. LMX theory is employed in this article. This study’s focus groups comprised 10 participants, including five leaders and five members from the hospital. This research found that doctor followers’ conscientiousness impacted the quality of LMX and their performance. Moreover, conscientiousness, agreeableness, and extraversion were linked to positive affect, while neuroticism ad narcissism was linked to negative affect. Finally, positive affection positively impacts LMX and vice versa. The present study included two potential research limitations. First, personality was measured by the Big Five Factors; thus, the previous researchers could not analyze it in the real world. Second, although the researcher did have two sources of data (such as the doctor leader and doctor member), it is a possibility that the data collection may have influenced some of the proposition’s relationships because the data collected was limited. On the other hand, the study found that followers’ conscientiousness determined that the quality of LMX significantly impacted LMX and their performance. Leaders’ conscientiousness and extroversion can positively impact LMX.

Achieving accurate and automated tumor segmentation plays an important role in both clinical practice and radiomics research. Segmentation in medicine is now often performed manually by experts, which is a laborious, expensive and error-prone task. Manual annotation relies heavily on the experience and knowledge of these experts. In addition, there is much intra- and interobserver variation. Therefore, it is of great significance to develop a method that can automatically segment tumor target regions. In this paper, we propose a deep learning segmentation method based on multimodal positron emission tomography-computed tomography (PET-CT), which combines the high sensitivity of PET and the precise anatomical information of CT. We design an improved spatial attention network(ISA-Net) to increase the accuracy of PET or CT in detecting tumors, which uses multi-scale convolution operation to extract feature information and can highlight the tumor region location information and suppress the non-tumor region location information. In addition, our network uses dual-channel inputs in the coding stage and fuses them in the decoding stage, which can take advantage of the differences and complementarities between PET and CT. We validated the proposed ISA-Net method on two clinical datasets, a soft tissue sarcoma(STS) and a head and neck tumor(HECKTOR) dataset, and compared with other attention methods for tumor segmentation. The DSC score of 0.8378 on STS dataset and 0.8076 on HECKTOR dataset show that ISA-Net method achieves better segmentation performance and has better generalization. Conclusions: The method proposed in this paper is based on multi-modal medical image tumor segmentation, which can effectively utilize the difference and complementarity of different modes. The method can also be applied to other multi-modal data or single-modal data by proper adjustment.

The vulnerability of face recognition systems to morphing attacks has posed a serious security threat due to the wide adoption of face biometrics in the real world. Most existing morphing attack detection (MAD) methods require a large amount of training data and have only been tested on a few predefined attack models. The lack of good generalization properties, especially in view of the growing interest in developing novel morphing attacks, is a critical limitation with existing MAD research. To address this issue, we propose to extend MAD from supervised learning to few-shot learning and from binary detection to multiclass fingerprinting in this paper. Our technical contributions include: 1) We propose a fusion-based few-shot learning (FSL) method to learn discriminative features that can generalize to unseen morphing attack types from predefined presentation attacks; 2) The proposed FSL based on the fusion of the PRNU model and Noiseprint network is extended from binary MAD to multiclass morphing attack fingerprinting (MAF). 3) We have collected a large-scale database, which contains five face datasets and eight different morphing algorithms, to benchmark the proposed few-shot MAF (FS-MAF) method. Extensive experimental results show the outstanding performance of our fusion-based FS-MAF. The code and data will be publicly available at https://github.com/nz0001na/mad maf.

Rapid identification of newly emerging or circulating viruses is an important first step toward managing the public health response to potential outbreaks. A portable virus capture device coupled with label-free Raman Spectroscopy holds the promise of fast detection by rapidly obtaining the Raman signature of a virus followed by a machine learning approach applied to recognize the virus based on its Raman spectrum, which is used as a fingerprint. We present such a machine learning approach for analyzing Raman spectra of human and avian viruses. A Convolutional Neural Network (CNN) classifier specifically designed for spectral data achieves very high accuracy for a variety of virus type or subtype identification tasks. In particular, it achieves 99% accuracy for classifying influenza virus type A vs. type B, 96% accuracy for classifying four subtypes of influenza A, 95% accuracy for differentiating enveloped and non-enveloped viruses, and 99% accuracy for differentiating avian coronavirus (infectious bronchitis virus, IBV) from other avian viruses. Furthermore, interpretation of neural net responses in the trained CNN model using a full-gradient algorithm highlights Raman spectral ranges that are most important to virus identification. By correlating ML-selected salient Raman ranges with the signature ranges of known biomolecules and chemical functional groups (for example, amide, amino acid, carboxylic acid), we verify that our ML model effectively recognizes the Raman signatures of proteins, lipids and other vital functional groups present in different viruses and uses a weighted combination of these signatures to identify viruses., Comment: 23 pages, 8 figures

Na Zhang,1,&ast; Hui Wu,2,&ast; Yingzhi Liang,1,&ast; Jianming Ye,1 Huan Zhang,3 Yuqing Miao,3 Yane Luo,1 Haiming Fan,3 Tianli Yue1,4 1College of Food Science and Technology, Northwest University, Xi’an, Shaanxi, 710069, People’s Republic of China; 2State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, 200237, People’s Republic of China; 3Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of the Ministry of Education, College of Chemistry and Materials Science, Northwest University, Xi’an, Shaanxi, 710069, People’s Republic of China; 4Laboratory of Quality and Safety Risk Assessment for Agro-Products (Yangling), Ministry of Agriculture, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yane Luo Email luoyane@nwu.edu.cnPurpose: Superparamagnetic iron oxide nanoparticles (SPIONs) have exhibited preeminent diagnosis and treatment performances, but their low internalization severely limits predesigned functions. The low cell internalization is now an urgent bottleneck problem for almost all nanomaterials. To achieve more internalization of SPIONS, recombinant M13 phage was designed for targeted delivery and smart release.Methods: M13 phages were designed to co-express exogenous SPARC binding peptide (SBP) and cathepsin B cleavage peptide (DFK), formed recombinant DFK-SBP-M13. 3.37± 0.06 nm of SPIONs were modified by 3, 4-dihydroxyhydrocinnamic acid (DHCA) to gain 10.80 ± 0.21 nm of DHCA-coated SPIONs, i.e., DHCA@SPIONs. Upon adjusting the proportions of DHCA@SPIONs and DFK-SBP-M13, the multi-carboxyl SPIONs assembled onto recombinant M13 phages via covalent bonding. The assemblies were co-cultured with MDA-MB-231 cells to interpret their internalization and smart release.Results: The “corn-like” SPIONs@DFK-SBP-M13 (261.47± 3.30 nm) assemblies have not been reported previously. The assembly was stable, dispersible

Qihui Chu,1,* Weiwei Mu,1,* Chuanjin Lan,2 Yang Liu,1 Tong Gao,1 Li Guan,1 Yuxiao Fang,1 Zipeng Zhang,1 Yingchao Liu,2 Yongjun Liu,1 Na Zhang1 1Department of Pharmaceutics, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, 250012, People’s Republic of China; 2Department of Neurosurgery, Shandong Provincial Hospital Affiliated with Shandong First Medical University, Jinan, 250021, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yongjun Liu; Na Zhang Email liuyongjun@sdu.edu.cn; zhangnancy9@sdu.edu.cnPurpose: Specific targeting receptors for efficiently capturing and applicable nanodevice for separating and instant observing of circulating tumour cells (CTC) are critical for early diagnosis of cancer. However, the existing CTC detection system based on epithelial cell adhesion molecule (EpCAM) was seriously limited by low expression and poor specificity of targeting receptors, and not instant observation in clinical application.Methods: Herein, an alternative glypican-3 (GPC3)-based immunomagnetic fluorescent system (C6/MMSN-GPC3) for high-specific isolation and instant observation of CTC from hepatocellular carcinoma (HCC) patients’ peripheral blood was developed. The high-specific HCC targeting receptor, GPC3, was employed for improving the sensitivity and accuracy in CTC detection. GPC3 monoclonal antibody (mAb) was linked to immunomagnetic mesoporous silica for specific targeting capture and separate CTC, and fluorescent molecule coumarin-6 (C6) was loaded for instant detection of CTC.Results: The cell recovery (%) of C6/MMSN-GPC3 increased in 106 HL-60 cells (from 49.7% to 83.0%) and in whole blood (from 42% to 80.3%) compared with MACS® Beads. In clinical samples, the C6/MMSN-GPC3 could capture more CTC in the 13 cases of HCC patients and the capture efficiency was improved b

Guang Yang,1,2 Yisong Yan,1,3 Jun Mao,1 Huiping Liu,1 Mingtao Chen,1 Na Zhang,1 Yaowen Li,1 Jiangjun Gu,2 Xiaohui Huang1 1Department of Basic and Clinical Pharmacology, School of Pharmacy, Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Department of Pharmacy, The Third People’s Hospital of Tongling, Tongling, Anhui, People’s Republic of China; 3Department of Pharmacy, Anhui College of Traditional Chinese Medicine, Wuhu, Anhui, People’s Republic of ChinaCorrespondence: Xiaohui HuangDepartment of Basic and Clinical Pharmacology, School of Pharmacy, Anhui Medical University, Meishan Road 81#, Hefei, Anhui, 230032, People’s Republic of ChinaTel +86 138 5518 3138Email math2088@163.comBackground: Linezolid (LNZ), an oxazolidinone antibiotic, has 100% oral bioavailability and favorable activities against gram-positive pathogens. The in vitro PK/PD model was developed based on concentrations obtained with routine doses in humans can be used to guide dose optimization in the clinic.Methods: In this study, we employed an in vitro PK/PD model to simulate the changes in the plasma concentration of linezolid in the human body against a clinical isolate of MRSA in vitro. A high-performance liquid chromatography (HPLC)-UV method was applied to measure the concentration of linezolid. Bacterial samples were collected at different times from the central compartment for count.Results: The chromatographic separation was carried out with an AichromBond-AQC18 column(250mm× 4.6mm, 5μm), using a mobile phase of water with 0.1% formic acid:acetonitrile 70:30 (v/v), followed by detection at 254 nm, and a single detection run was completed within 10 min. The method was validated by estimating the precision and accuracy for the inter- and intra-day analyses in the concentration range of 0.25– 32 mg/L. The method was linear over the investigated range of 0.125– 32 mg/L, with all correlation coef&filig;cients R2 = 0.9999. The intra-day and inter-day prec

Na Zhang,1,2 Jian-Feng Tu,1 Ying Lin,1 Jin-Ling Li,1 Xuan Zou,1 Yu Wang,1 Hewen Li,1 Xiao-Ya Wei,1 Li-Qiong Wang,1 Guang-Xia Shi,1 Shi-Yan Yan,1 Cun-Zhi Liu1 1International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 2School of Acupuncture-Moxibustion and Tuina, Shandong University of Chinese Medicine, Shandong, People’s Republic of ChinaCorrespondence: Guang-Xia Shi; Shi-Yan Yan Email shiguangxia2008@126.com; yanshiyan0927@sina.comBackground: Whether the clinical effect of acupuncture in chronic pain is effective has always been a hot topic of research, which has a great relationship with the overall reporting descriptions of acupuncture, especially the sham acupuncture intervention. To confirm the effectiveness of acupuncture, more clinical studies are often required. Therefore, it is necessary to report high-quality and complete descriptions of acupuncture in clinical trials. This study aims to assess the overall reporting quality of acupuncture for chronic pain in randomized controlled trials (RCTs).Methods: Three databases from inception to March 2020 were searched, to assess the quality of acupuncture reports included the RCTs based on the pain-specific supplement to Consolidated Standards for Reporting Trials (CONSORT) and Standards for Reporting Interventions in Controlled Trials of Acupuncture (STRICTA) guidelines. The quality of sham acupuncture descriptions was evaluated based on the Template for Intervention Description and Replication (TIDieR)-placebo checklist. Descriptive statistics and analysis of the results were carried out according to the percentage of each item.Results: A total of 74 RCTs were included which met the inclusion criteria. Based on the pain-specific CONSORT, the reporting rates of “Statistical methods”, “Participant flow”, and “Blinding” were “ 52.70%”, “ 70.27%”, and “ 77.03%”

Off-policy evaluation (OPE) is the task of estimating the expected reward of a given policy based on offline data previously collected under different policies. Therefore, OPE is a key step in applying reinforcement learning to real-world domains such as medical treatment, where interactive data collection is expensive or even unsafe. As the observed data tends to be noisy and limited, it is essential to provide rigorous uncertainty quantification, not just a point estimation, when applying OPE to make high stakes decisions. This work considers the problem of constructing non-asymptotic confidence intervals in infinite-horizon off-policy evaluation, which remains a challenging open question. We develop a practical algorithm through a primal-dual optimization-based approach, which leverages the kernel Bellman loss (KBL) of Feng et al.(2019) and a new martingale concentration inequality of KBL applicable to time-dependent data with unknown mixing conditions. Our algorithm makes minimum assumptions on the data and the function class of the Q-function, and works for the behavior-agnostic settings where the data is collected under a mix of arbitrary unknown behavior policies. We present empirical results that clearly demonstrate the advantages of our approach over existing methods., Comment: 33 Pages, 5 figures, extended version of a paper with the same title accepted by ICLR2021

Na Zhang,1,2 Li-Qiong Wang,1 Jin-Ling Li,1 Xin-Tong Su,1 Fang-Ting Yu,1 Guang-Xia Shi,1 Jing-Wen Yang,1 Cun-Zhi Liu1 1International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 2School of Acupuncture-Moxibustion and Tuina, Shandong University of Chinese Medicine, Shandong, People’s Republic of ChinaCorrespondence: Cun-Zhi LiuSchool of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, 11 Bei San Huan Dong Lu, Chaoyang District, Beijing 100029, People’s Republic of ChinaEmail lcz_tg@126.comObjective: Acupuncture therapy is an effective non-drug therapy for sciatica, but it has not yet formed an effective treatment strategy and recommendations. Our objective was to establish an expert consensus on acupuncture treatment of sciatica for clinical guidance based on the improved Delphi survey.Methods: A group of 80 clinical specialists was invited to participate in two rounds of semi-open clinical issue investigation. At the same time, the PubMed, Embase, and Cochrane Library databases were searched for systematic reviews on acupuncture treatment of sciatica, and the quality of evidence was evaluated. Then the three-round Delphi survey was undertaken with 30 experts based on the clinical issue investigation and systematic reviews.Results: In round 1 of the Delphi survey, the experts evaluated 17 items identified from the results of the clinical investigation and literature review. The criterion for achieving consensus was a threshold of 80% agreement. After the three-round Delphi survey, 16 items (94.12%) achieved consensus, including 5 domains: the principle of acupuncture treatment for sciatica; the “dose” of acupuncture; the clinical effects of acupuncture; the adverse effects, and others.Conclusion: This Delphi survey achieved an expert consensus on key items in the manag

Aolin Ren,1,* Na Zhang,1,* He Zhu,1 Kang Zhou,1 Yuan Cao,1 Jindong Liu1,2 1Department of Anesthesiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China; 2Jiangsu Province Key Laboratory of Anesthesiology, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jindong LiuDepartment of Anesthesiology, Affiliated Hospital of Xuzhou Medical University, Huaihai West Road #99, Xuzhou, Jiangsu, 221000, People’s Republic of ChinaEmail liujindong1818@163.com View the original paper by Dr Ren and colleagues This is in response to the Letter to the Editor

Chuyu Li,1– 3,* Na Zhang,1– 3,* Jing Zhou,1– 3 Wingting Leung,1– 3 Hans-Jürgen Gober,4 Zengshu Huang,1– 3 Xinyao Pan,1– 3 Lijia Chen,1– 3 Liang Guan,5,6 Ling Wang1– 3 1Laboratory for Reproductive Immunology, Hospital & Institute of Obstetrics and Gynecology, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China; 2The Academy of Integrative Medicine of Fudan University, Shanghai, People’s Republic of China; 3Shanghai Key Laboratory of Female Reproductive Endocrine-Related Diseases, Shanghai, People’s Republic of China; 4Department of Pharmacy, Neuromed Campus, Kepler University Hospital, Linz, 4020, Austria; 5Department of Nuclear Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, People’s Republic of China; 6Department of Nuclear Medicine, Ruijin Hospital North, School of Medicine, Shanghai Jiaotong University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Liang GuanRuijin Hospital of Shanghai Jiaotong University, 197 Ruijin 2nd Road, Huangpu District, Shanghai, 200025, People’s Republic of ChinaTel +86 18917762612Fax + 86-21-6433 3548Email drliangguan@outlook.comLing WangObstetrics & Gynecology Hospital of Fudan University, 419 Fangxie Road, Shanghai, 200011, People’s Republic of ChinaTel + 86-18221815182Fax + 86-021-63457331Email Dr.wangling@fudan.edu.cnBackground: Immunosuppression occurs during pregnancy, and the antithyroid antibody titre drops, rebounding after delivery. We aimed to determine variations in antithyroid antibody titres during pregnancy and after delivery.Methods: This retrospective study was conducted in a single centre. Antibody titres of 142 patients were measured to assess variations in the levels of thyroid-stimulating hormone receptor antibodies (TRAbs)

Aolin Ren, 1,* Na Zhang, 1,* He Zhu, 1 Kang Zhou, 1 Yuan Cao, 1 Jindong Liu 1, 2 1Department of Anesthesiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China; 2Jiangsu Province Key Laboratory of Anesthesiology, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jindong LiuDepartment of Anesthesiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou Medical University, Huaihai West Road #99, Xuzhou 221000, People’s Republic of ChinaTel +86 10 8580-2333Email liujindong1818@163.comBackground: Postoperative delirium (POD) is common and has negative effects on elderly patients. There is a critical need to identify patients at high risk of POD so that providers can better offer targeted interventions in the preoperative and intraoperative periods. We aimed to characterize the prevalence of preoperative anxiety and investigate whether preoperative anxiety predicted the onset of POD in elderly patients undergoing elective orthopedic surgery.Methods: We conducted a prospective observational cohort study of elderly patients (aged 65 years or older) undergoing elective orthopedic surgery. Preoperative anxiety was assessed using the Hospital Anxiety and Depression Scale-Anxiety (HADS-A), with clinically significant values defined as HADS-A> 7. POD was diagnosed according to the Confusion Assessment Method (CAM) criteria on the 5 postoperative days. To determine the independent risk factors for POD, multivariable logistic regression was conducted, including those variables with a p-value < 0.05 at univariate analysis.Results: There were 263 patients included in the study. Seventy-three (27.8%) patients were diagnosed to be POD. Median duration of delirium was 2 days. Forty (15.2%) patients were assessed to experience preoperative anxiety. The occurrence of preoperative anxiety in total hip arthropla

BACKGROUND:One of the potentially important applications of three-dimensional (3D) intracranial vessel wall (IVW) cardiovascular magnetic resonance (CMR) is to monitor disease progression and regression via quantitative measurement of IVW morphology during medical management or drug development. However, a prerequisite for this application is to validate that IVW morphologic measurements based on the modality are reliable. In this study we performed comprehensive reliability analysis for the recently proposed whole-brain IVW CMR technique. METHODS:Thirty-four healthy subjects and 10 patients with known intracranial atherosclerotic disease underwent repeat whole-brain IVW CMR scans. In 19 of the 34 subjects, two-dimensional (2D) turbo spin-echo (TSE) scan was performed to serve as a reference for the assessment of vessel dimensions. Lumen and wall volume, normalized wall index, mean and maximum wall thickness were measured in both 3D and 2D IVW CMR images. Scan-rescan, intra-observer, and inter-observer reproducibility of 3D IVW CMR in the quantification of IVW or plaque dimensions were respectively assessed in volunteers and patients as well as for different healthy subjectsub-groups (i.e. < 50 and ≥ 50 years). The agreement in vessel wall and lumen measurements between the 3D technique and the 2D TSE method was also investigated. In addition, the sample size required for future longitudinal clinical studies was calculated. RESULTS:The intra-class correlation coefficient (ICC) and Bland-Altman plots indicated excellent reproducibility and inter-method agreement for all morphologic measurements (All ICCs > 0.75). In addition, all ICCs of patients were equal to or higher than that of healthy subjects except maximum wall thickness. In volunteers, all ICCs of the age group of ≥50 years were equal to or higher than that of the age group of < 50 years. Normalized wall index and mean and maximum wall thickness were significantly larger in the age group of ≥50 year

Natural products serve as chemical blueprints for most antibiotics in clinical use. The evolutionary process by which these molecules arise is inherently accompanied by the co-evolution of resistance mechanisms that shorten the clinical lifetime of any given class of antibiotics1. Virginiamycin acetyltransferase (Vat) enzymes are resistance proteins that provide protection against streptogramins2, potent antibiotics against Gram-positive bacteria that inhibit the bacterial ribosome3. Owing to the challenge of selectively modifying the chemically complex, 23-membered macrocyclic scaffold of group A streptogramins, analogues that overcome the resistance conferred by Vat enzymes have not been previously developed2. Here we report the design, synthesis, and antibacterial evaluation of group A streptogramin antibiotics with extensive structural variability. Using cryo-electron microscopy and forcefield-based refinement, we characterize the binding of eight analogues to the bacterial ribosome at high resolution, revealing binding interactions that extend into the peptidyl tRNA-binding site and towards synergistic binders that occupy the nascent peptide exit tunnel. One of these analogues has excellent activity against several streptogramin-resistant strains of Staphylococcus aureus, exhibits decreased rates of acetylation in vitro, and is effective at lowering bacterial load in a mouse model of infection. Our results demonstrate that the combination of rational design and modular chemical synthesis can revitalize classes of antibiotics that are limited by naturally arising resistance mechanisms.

Xiuping Pang,1,* Shuang Liang,1,* Tianqi Wang,1 Shuangjiang Yu,2 Rui Yang,1 Teng Hou,1 Yongjun Liu,1 Chaoliang He,2 Na Zhang1 1Department of Pharmaceutics, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Shandong University, Jinan, Shandong Province 250012, People’s Republic of China; 2Key Laboratory of Polymer Ecomaterials, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chaoliang He; Na Zhang Email clhe@ciac.ac.cn; zhangnancy9@sdu.edu.cnPurpose: Combined chemotherapeutic drug and protein drug has been a widely employed strategy for tumor treatment. To realize both tumor accumulation and deep tumor penetration for drugs with different pharmacokinetics, we propose a structure-transformable, thermo-pH dual responsive co-delivery system to co-load granzyme B/docetaxel (GrB/DTX).Methods: Thermo-sensitive hydrogels based on diblock copolymers (mPEG-b-PELG) were synthesized through ring opening polymerization. GrB/DTX mini micelles (GDM) was developed by co-loading these two drugs in pH-sensitive mini micelles, and the GDM-incorporated thermo-sensitive hydrogel (GDMH) was constructed. The thermo-induced gelation behavior of diblock copolymers and the physiochemical properties of GDMH were characterized. GDMH degradation and deep tumor penetration of released mini micelles were confirmed. The pH-sensitive disassembly and lysosomal escape abilities of released mini micelles were evaluated. In vitro cytotoxicity was studied using MTT assays and the in vivo antitumor efficacy study was evaluated in B16-bearing C57BL/6 mice.Results: GDMH was gelatinized at body temperature and can be degraded by proteinase to release mini micelles. The mini micelles incorporated in GDMH can achieve deep tumor penetration and escape from lysosomes to release GrB and DTX. MTT results showed that maxim

Obtaining accurate information about future traffic flows of all links in a traffic network is of great importance for traffic management and control applications. This research studies two particular problems in traffic forecasting: (1) capture the dynamic and non-local spatial correlation between traffic links and (2) model the dynamics of temporal dependency for accurate multiple steps ahead predictions. To address these issues, we propose a deep learning framework named Spatial-Temporal Sequence to Sequence model (STSeq2Seq). This model builds on sequence to sequence (seq2seq) architecture to capture temporal feature and relies on graph convolution for aggregating spatial information. Moreover, STSeq2Seq defines and constructs pattern-aware adjacency matrices (PAMs) based on pair-wise similarity of the recent traffic patterns on traffic links and integrate it into graph convolution operation. It also deploys a novel seq2sesq architecture which couples a convolutional encoder and a recurrent decoder with attention mechanism for dynamic modeling of long-range dependence between different time steps. We conduct extensive experiments using two publicly-available large-scale traffic datasets and compare STSeq2Seq with other baseline models. The numerical results demonstrate that the proposed model achieves state-of-the-art forecasting performance in terms of various error measures. The ablation study verifies the effectiveness of PAMs in capturing dynamic non-local spatial correlation and the superiority of proposed seq2seq architecture in modeling non-stationary temporal dependency for multiple steps ahead prediction. Furthermore, qualitative analysis is conducted on PAMs as well as the attention weights for model interpretation., Comment: 29 pages, 16 figures, 3 tables

Learning monotonic models with respect to a subset of the inputs is a desirable feature to effectively address the fairness, interpretability, and generalization issues in practice. Existing methods for learning monotonic neural networks either require specifically designed model structures to ensure monotonicity, which can be too restrictive/complicated, or enforce monotonicity by adjusting the learning process, which cannot provably guarantee the learned model is monotonic on selected features. In this work, we propose to certify the monotonicity of the general piece-wise linear neural networks by solving a mixed integer linear programming problem.This provides a new general approach for learning monotonic neural networks with arbitrary model structures. Our method allows us to train neural networks with heuristic monotonicity regularizations, and we can gradually increase the regularization magnitude until the learned network is certified monotonic. Compared to prior works, our approach does not require human-designed constraints on the weight space and also yields more accurate approximation. Empirical studies on various datasets demonstrate the efficiency of our approach over the state-of-the-art methods, such as Deep Lattice Networks.

Off-policy evaluation provides an essential tool for evaluating the effects of different policies or treatments using only observed data. When applied to high-stakes scenarios such as medical diagnosis or financial decision-making, it is crucial to provide provably correct upper and lower bounds of the expected reward, not just a classical single point estimate, to the end-users, as executing a poor policy can be very costly. In this work, we propose a provably correct method for obtaining interval bounds for off-policy evaluation in a general continuous setting. The idea is to search for the maximum and minimum values of the expected reward among all the Lipschitz Q-functions that are consistent with the observations, which amounts to solving a constrained optimization problem on a Lipschitz function space. We go on to introduce a Lipschitz value iteration method to monotonically tighten the interval, which is simple yet efficient and provably convergent. We demonstrate the practical efficiency of our method on a range of benchmarks., Comment: To appear at NeurIPS 2020

Dongyue Wang,1,* Min Wang,1,* Hui Zhang,1 He Zhu,1 Na Zhang,1 Jindong Liu2 1Jiangsu Province Key Laboratory of Anesthesiology, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China; 2Department of Anesthesiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jindong LiuDepartment of Anesthesiology, The Affiliated Hospital of XuZhou Medical University, Xuzhou, Jiangsu, People’s Republic of ChinaEmail liujindong1818@163.comPurpose: In this study, the effect of intravenous vitamin C during surgery on the incidence of postoperative pulmonary complications (PPCs) in patients undergoing cardiopulmonary bypass and cardiac surgery was observed, and its protective effect on the lungs was evaluated to provide a reference for clinical medication.Patients and Methods: Patients undergoing cardiac surgery under cardiopulmonary bypass (CPB) were selected. The patients were divided into group A and group C by random sequence. Patients in group A received intravenous vitamin C 1 g 10 minutes after induction of anesthesia, 10 minutes before cardiac reanimation and at the moment of sternal closure. Patients in group C were intravenously injected with the same volume of saline at the same time. The primary outcome was the postoperative pulmonary complication severity score. Other outcomes were the incidence of PPCs, awakening time, extubation time, length of ICU stay, length of hospital stay, adverse events, oxygenation index (PaO2/FiO2), alveolar arterial oxygen partial pressure difference (A-aDO2), dynamic lung compliance (Cd) and static lung compliance (Cs).Results: Seventy patients completed the study. Compared to group C, the postoperative pulmonary complication score [2(2– 3) vs 2(1– 2); P=0.009] and the incidence of postoperative pulmonary complications (32.43% vs 12.12%; P =0.043) were lower in group

Han Dong,1 Bin Dong,1 Na Zhang,2 Songyan Liu,3 Huiying Zhao1 1Department of Geriatric Medicine, The First Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of China; 2Department of Electrical Diagnosis, Jilin Province FAW General Hospital, Changchun, Jilin Province 130021, People’s Republic of China; 3Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of ChinaCorrespondence: Huiying ZhaoDepartment of Geriatric Medicine, The First Hospital of Jilin University, Changchun 130021, People’s Republic of ChinaTel +86-431-88783239Fax +86-431-88786439Email zhaohuiyingjdyy@126.comSongyan LiuDepartment of Neurology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province 130021, People’s Republic of ChinaTel +86-431-84595348Fax +86-431-84596133Email songyanliujilin@163.comPurpose: To explore the neuroprotective effects and mechanisms of Apelin (APLN), and to study the regulation of APLN expression by microRNA (miRNA) in epilepsy.Materials and Methods: In vitro and in vivo epileptic models were established with hippocampal neurons and Wistar rats. Apoptosis of neurons was identified by flow cytometry. Western blotting was used to detect the expression of proteins, and quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was used to analyze the expression of miRNA and messenger RNA (mRNA). Bioinformatics software was used to predict target genes of miRNA, which were confirmed by dual-luciferase reporter gene system and functional experiments.Results: Our study demonstrated protective effects of APLN against neuronal death in epilepsy both in vitro and in vivo. The underlying mechanisms involved are inhibiting the expression of metabotropic glutamate receptor 1 (mGluR1), Bax, and caspase-3; promoting the expression of Bcl-2; and increasing phosphorylated-AKT (p-AKT) levels in neurons. For th

Jin-Ling Li,1,2 Chao-Qun Yan,1 Xu Wang,3 Shuai Zhang,4 Na Zhang,5 Shang-Qing Hu,1 Li-Qiong Wang,1 Cun-Zhi Liu1 1School of Acupuncture and Moxibustion, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 2Department of Acupuncture and Moxibustion, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 3School of Life Sciences, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 4Department of Acupuncture and Moxibustion, Wangjing Hospital, Beijing, People’s Republic of China; 5School of Acupuncture and Moxibustion, Shandong University of Chinese Medicine, Shandong, People’s Republic of ChinaCorrespondence: Cun-Zhi LiuSchool of Acupuncture and Moxibustion, Beijing University of Chinese Medicine, 11 Bei San Huan Dong Lu, Chaoyang District, Beijing 100029, People’s Republic of ChinaTel +86 15901261692Email lcz_tg@126.comObjective: Chronic shoulder pain (CSP) is a common health problem associated with shoulder dysfunction and persistent pain for many different reasons. However, the studies of pain-related functional brain regions in CSP have been poorly investigated. The main purpose of our study was to observe whether there are abnormal functional changes in brain regions in patients with CSP by using functional magnetic resonance imaging (fMRI).Patients and Methods: We compared the differences of brain regions between 37 patients with CSP and 24 healthy controls (HC) using regional homogeneity (ReHo) method. The patients with chronic shoulder pain and healthy controls were matched for age and gender. Brain regions which had abnormal ReHo values were defined as seed region of interests. The approach of seed-based functional connectivity (FC) was further performed to analyze the connectivity between the seeds and whole brain regions. The relationship between abnormal regions and current clinical pain was also evaluated.Res

Alkali metal-sulfur/selenium batteries have attracted much attention because they offer promising high energy density. However, the shuttle effect of the polysulfide dissolutions, poor electrical conductivity, and relatively large volume variations greatly hinder their potential applications. Herein, a novel organic carbon/selenium sulfide (OC/SeS2) composite has been prepared by a one-step in situ method by heating the mixture of commercial polyacrylonitrile (PAN) with selenium sulfide powder in vacuum. The carbonized PAN matrix with an N-doped carbon ring structure could effectively confine SeS2 in the form of small molecules and regulate its electronic structure. The superior sodium/potassium storage performance of the OC/SeS2 composite electrodes stems from their rational chemical structure design, including high electrical conductivity of the N-doped organic carbon network and chemical binding with SeS2 molecules. As a result, the OC/SeS2 cathode delivers a reversible capacity of 416 mAh g-1 after 700 cycles for sodium-ion batteries and 216 mAh g-1 after 500 cycles for potassium-ion batteries at 0.5 A g-1, respectively. These findings could open a new window to develop selenium sulfide cathode for metal-sulfur/selenium batteries.

Xiuping Pang, Tianqi Wang, Dandan Jiang, Weiwei Mu, Bo Zhang, Na ZhangSchool of Pharmaceutical Sciences, Key Laboratory of Chemical Biology (Ministry of Education), Shandong University, Jinan, Shandong Province 250012, Peoples’ Republic of ChinaPurpose: To further enhance the antitumor efficacy through targeted delivery, DTX loaded lipid-based-nanosuspensions (DTX-LNS) were prepared and functionalized by PEGylation or NGR modification to develop DSPE-PEG2000 modified DTX-LNS (P-DTX-LNS) or DSPE-PEG2000-NGR modified DTX-LNS (N-DTX-LNS), respectively.Methods: Based on our previous work, functionalized DTX-LNS including P-DTX-LNS and N-DTX-LNS were prepared using thin-film hydration, and then characterized. Release behavior, stability in vitro, cytotoxicity and cellular uptake of functionalized LNS were observed. To demonstrate tumor targeting efficiency of functionalized DTX-LNS, in vivo real-time and ex vivo imaging study were conducted. Furthermore, therapeutic efficacy in vivo was evaluated in an H22-bearing mice model.Results: Functionalized DTX-LNS 100–110 nm in diameter were successfully prepared and exhibited good stability under various conditions. In vitro release studies demonstrated that DTX was released from functionalized DTX-LNS steadily and reached approximately 95% at 48 hrs. Functionalized DTX-LNS showed dose-dependent cytotoxicity and time-dependent internalization in human hepatocellular liver carcinoma cells (HepG2) cells. In vivo real-time and ex vivo imaging results indicated that tumor targeting efficiencies of P-DiR-LNS and N-DiR-LNS were 29.9% and 34.3%, respectively. Moreover, evaluations of in vivo antitumor efficacy indicated that functionalized DTX-LNS effectively inhibited tumor growth with low toxicity.Conclusion: The functionalized LNS exhibited suitable particle size, nearly spherical structure, enough drug loading and great potentials for large-scale production. The results in vitro and in vivo demonstrated that fu

Although commercial sugarcane (Saccharum spp. hybrid) produces large biomass yields, its lack of cold tolerance limits its cultivation to the tropics and subtropics. In contrast, sugarcane's close relative, Miscanthus, tolerates low temperatures. We studied 18 miscane genotypes, derived from hybridizations between two genotypes of sugarcane and two genotypes of Miscanthus (one each of M. sinensis and M. sacchariflorus). In an initial greenhouse experiment on long-duration chilling stress (12-13 degrees C day/7-9 degrees C night), photosynthetic rates of the Miscanthus parents were significantly higher than the sugarcane parents after 7 days of chilling and were more than double by 14 days. The Miscanthus also retained more of their prechilling (22-25 degrees C day/13-15 degrees C night) photosynthetic rates (68%-72% 7 days, 64%-66% 14 days) than the sugarcanes (27% 7 days, 19%-20% 14 days). Seven of 18 miscanes exhibited higher photosynthetic rates than their sugarcane parents after 7 days of chilling, whereas after 14 days only four miscane genotypes had significantly higher photosynthetic rates than their sugarcane parents, but notably two of these did not differ from their highly tolerant Miscanthus parents. In a subsequent growth chamber experiment to evaluate short-duration chilling stress and postchilling recovery, three miscanes representing the range of responses observed in the greenhouse experiment were compared with their parents. After 4 days of chilling (12/7 degrees C day/night), the miscanes retained between 45% and 60% of their prechilling photosynthetic rate, with the best entry not significantly different from its Miscanthus parent (66%), and all three miscanes performed significantly better than the sugarcane parents (32%-33% for sugarcanes). After 7 days of postchilling recovery (26/18 degrees C day/night), the Miscanthus parents and two of the miscanes fully recovered their prechilling photosynthetic rates but the sugarcane parents only recovere

When photons from distant galaxies and stars pass through our neighboring environment, the wavelengths of the photons would be shifted by our local gravitational potential. This local gravitational redshift effect can potentially have an impact on the measurement of cosmological distance-redshift relation. Using available supernovae data, Wojtak et al [1] found seemingly large biases of cosmological parameters for some extended models (non-flat $\Lambda$CDM, $w$CDM, etc.). Huang [2] pointed out that, however, the biases can be reduced to a negligible level if cosmic microwave background (CMB) data are added to break the strong degeneracy between parameters in the extended models. In this article we forecast the cosmological bias due to local gravitational redshifts for a future WFIRST-like supernovae survey. We find that the local gravitational redshift effect remains negligible, provided that CMB data or some future redshift survey data are added to break the degeneracy between parameters., Comment: 6 pages; 2 figures