Azvudine and nirmatrelvir-ritonavir in hospitalized patients with moderate-to-severe COVID-19: Emulation of a randomized target trial.

To examine the effectiveness of azvudine and nirmatrelvir-ritonavir in treating hospitalized patients with moderate-to-severe COVID-19. We emulated a target trial with a multicenter retrospective cohort of hospitalized adults with moderate-to-severe COVID-19 without contraindications for azvudine or nirmatrelvir-ritonavir between December 01, 2022 and January 19, 2023 (during the Omicron BA.5.2 variant wave). Exposures included treatment with azvudine or nirmatrelvir-ritonavir for 5 days versus no antiviral treatment during hospitalization. Primary composite outcome (all-cause death and initiation of invasive mechanical ventilation), and their separate events were evaluated. Of the 1154 patients, 27.2% were severe cases. In the intent-to-treat analyses, azvudine reduced all-cause death (Hazard ratio [HR]: 0.31; 95% CI: 0.12-0.78), and its composite with invasive mechanical ventilation (HR: 0.47; 95% CI: 0.24-0.92). Nirmatrelvir-ritonavir reduced invasive mechanical ventilation (HR: 0.42; 95% CI: 0.17-1.05), and its composite with all-cause death (HR: 0.38; 95% CI: 0.18-0.81). The study did not identify credible subgroup effects. The per-protocol analyses and all sensitivity analyses confirmed the robustness of the findings. Both azvudine and nirmatrelvir-ritonavir improved the prognosis of hospitalized adults with moderate-to-severe COVID-19.

Recovery experiences mediate the effect of burnout on life satisfaction among Chinese physicians: a structural equation modeling analysis.

PURPOSE: Recovery experiences not only make it possible for individuals to restore their energy resources and return to pre-stressor levels but also contribute to the formation of their subjective well-being. This paper investigates the effect of burnout on life satisfaction among Chinese physicians who are frequently confronted with a considerable number of work-related stressors and examines the mediating role of recovery experiences in the relationship between burnout and life satisfaction. METHODS: A total of 642 physicians working in five public tertiary hospitals in China responded to a self-administered questionnaire including demographic information, the Satisfaction with Life Scale, the Maslach Burnout Inventory-General Scale, and the Recovery Experience Questionnaire. Hierarchical multiple regression analysis was conducted to test the incremental variance of any given set of independent variables. Structural equation modeling was employed to test the presumed relationships between variables involved. Asymptotic and resampling strategies were used to examine the mediating effects of recovery experiences in the relationship between burnout and life satisfaction. RESULTS: Burnout and recovery experiences were important predictors of life satisfaction and the direct effect of burnout on life satisfaction was statistically significant and negative and the path coefficients of burnout with life satisfaction were significantly decreased when recovery experiences were modeled as mediators. CONCLUSION: Findings of the study highlight the importance of promoting recovery experiences to reduce burnout and improve life satisfaction among physicians rather than focusing on the less easily modifiable work-related stressors.

Optimizing quality of life among Chinese physicians: the positive effects of resilience and recovery experience.

BACKGROUND: The physicians in Chinese public tertiary hospitals are exposed to considerable work-related stress because of the imperfections in hierarchical diagnosis and treatment systems, such as the imperfections in referral system and low quality in diagnosis and treatment outcomes in community hospitals, for which most patients visit tertiary hospitals firstly in order to access a higher quality health care service. As a consequence, the health-related quality of life (HRQOL) for Chinese physicians is compromised. However, there is a paucity of research exploring physicians' physical and mental health and positive psychological resource factors such as resilience and recovery experience (RE) which can help maintain well-being. Thus, this study aims to assess HRQOL of Chinese physicians and explore the relationship between HRQOL, resilience, and RE. METHODS: A cross-sectional study with proportional sampling was conducted in Shenyang, China from February to October 2018. A total of 642 physicians in five public tertiary hospitals were enrolled in this study. They completed the smartphone questionnaire including the 36-item Short-Form Health Survey (SF-36), the EGO Resilience Scale, and Recovery Experience Questionnaire (REQ). Linear regression analysis was conducted to explore the factors associated with HRQOL. Structural equation modeling (SEM) was used to evaluate the mediating effect of RE on the relationship between resilience and HRQOL. RESULTS: Regression analysis indicated that resilience and RE were the most important contributors to both physical and mental component summary scores. SEM showed that RE partially mediated the relationship between resilience and HRQOL in these physicians. CONCLUSION: Chinese physicians exhibited good physical health, but poor mental health. Resilience could help maintain and improve HRQOL through the partial mediating effect of RE. Resilience and RE enhancement should be provided to effectively manage work-related stress and improve both physical and mental health for the long-term well-being of physicians.

OsNAC2 positively affects salt-induced cell death and binds to the OsAP37 and OsCOX11 promoters.

Plant development and adaptation to environmental stresses are intimately associated with programmed cell death (PCD). Although some of the mechanisms regulating PCD [e.g., accumulation of reactive oxygen species (ROS)] are common among responses to different abiotic stresses, the pathways mediating salt-induced PCD remain largely uncharacterized. Here we report that overexpression of OsNAC2, which encodes a plant-specific transcription factor, promotes salt-induced cell death accompanied by the loss of plasma membrane integrity, nuclear DNA fragmentation, and changes to caspase-like activity. In OsNAC2-knockdown lines, cell death was markedly decreased in response to severe salt stress. Additionally, OsNAC2 expression was enhanced in rice seedlings exposed to a high NaCl concentration. Moreover, the results of quantitative real-time PCR, chromatin immunoprecipitation, dual-luciferase, and yeast one-hybrid assays indicated that OsNAC2 targeted genes that encoded an ROS scavenger (OsCOX11) and a caspase-like protease (OsAP37). Furthermore, K+ -efflux channels (OsGORK and OsSKOR) were clearly activated by OsNAC2. Overall, our results suggested that OsNAC2 accelerates NaCl-induced PCD and provide new insights into the mechanisms that affect ROS accumulation, plant caspase-like activity, and K+ efflux.

Simplification of genotyping techniques of the ABO blood type experiment and exploration of population genetics.

The ABO blood type is one of the most common and widely used genetic traits in humans. Three glycosyltransferase-encoding gene alleles, IA, IB and i, produce three red blood cell surface antigens, by which the ABO blood type is classified. By using the ABO blood type experiment as an ideal case for genetics teaching, we can easily introduce to the students several genetic concepts, including multiple alleles, gene interaction, single nucleotide polymorphism (SNP) and gene evolution. Herein we have innovated and integrated our ABO blood type genetics experiments. First, in the section of Molecular Genetics, a new method of ABO blood genotyping was established: specific primers based on SNP sites were designed to distinguish three alleles through quantitative real-time PCR. Next, the experimental teaching method of Gene Evolution was innovated in the Population Genetics section: a gene-evolution software was developed to simulate the evolutionary tendency of the ABO genotype encoding alleles under diverse conditions. Our reform aims to extend the contents of genetics experiments, to provide additional teaching approaches, and to improve the learning efficiency of our students eventually.

Developing and validating a deep learning and radiomic model for glioma grading using multiplanar reconstructed magnetic resonance contrast-enhanced T1-weighted imaging: a robust, multi-institutional study.

BACKGROUND: Although surgical pathology or biopsy are considered the gold standard for glioma grading, these procedures have limitations. This study set out to evaluate and validate the predictive performance of a deep learning radiomics model based on contrast-enhanced T1-weighted multiplanar reconstruction images for grading gliomas. METHODS: Patients from three institutions who diagnosed with gliomas by surgical specimen and multiplanar reconstructed (MPR) images were enrolled in this study. The training cohort included 101 patients from institution 1, including 43 high-grade glioma (HGG) patients and 58 low-grade glioma (LGG) patients, while the test cohorts consisted of 50 patients from institutions 2 and 3 (25 HGG patients, 25 LGG patients). We then extracted radiomics features and deep learning features using six pretrained models from the MPR images. The Spearman correlation test and the recursive elimination feature selection method were used to reduce the redundancy and select most predictive features. Subsequently, three classifiers were used to construct classification models. The performance of the grading models was evaluated using the area under the receiver operating curve, sensitivity, specificity, accuracy, precision, and negative predictive value. Finally, the prediction performances of the test cohort were compared to determine the optimal classification model. RESULTS: For the training cohort, 62% (13 out of 21) of the classification models constructed with MPR images from multiple planes outperformed those constructed with single-plane MPR images, and 61% (11 out of 18) of classification models constructed with both radiomics features and deep learning features had higher area under the curve (AUC) values than those constructed with only radiomics or deep learning features. The optimal model was a random forest model that combined radiomic features and VGG16 deep learning features derived from MPR images, which achieved AUC of 0.847 in the training cohort and 0.898 in the test cohort. In the test cohort, the sensitivity, specificity, and accuracy of the optimal model were 0.840, 0.760, and 0.800, respectively. CONCLUSIONS: Multiplanar CE-T1W MPR imaging features are more effective than features from single planes when differentiating HGG and LGG. The combination of deep learning features and radiomics features can effectively grade glioma and assist clinical decision-making.

Development and validation of a prognostic nomogram for malignant esophageal fistula based on radiomics and clinical factors.

BACKGROUND: The current study aimed to comprehensively analyze the clinical prognostic factors of malignant esophageal fistula (MEF). Furthermore, this study sought to establish and validate prognostic nomograms incorporating radiomics and clinical factors to predict overall survival and median survival after fistula for patients with MEF. METHODS: The records of 76 patients with MEF were retrospectively analyzed. A stepwise Cox proportional hazards regression model was employed to screen independent prognostic factors and develop clinical nomograms. Radiomic features were extracted from prefistula CT images and post fistula CT images. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression algorithm was used to filter radiomic features and avoid overfitting. Radiomic signature was a linear combination of optimal features and corresponding coefficients. The joint prognostic nomograms was constructed by radiomic signatures and clinical features. All models were validated by Harrell's concordance index (C-index), caliberation and bootstrap validation. RESULTS: For overall survival, age, prealbumin, KPS and interval between diagnosis of esophageal cancer and fistula were identified as independent prognostic factors and incorporated into the clinical nomogram. Age, prealbumin, serum albumin, KPS and neutrophil proportion were selected for the clinical nomogram of post fistula survival. The C-index of overall survival nomogram was 0.719 (95% CI: 0.645-0.793) and that was 0.722 (95% CI: 0.653-0.791) in the post fistula survival nomogram. The radiomic signature developed by radiomic features of prefistula CT showed a significant correlation with both overall survival and post fistula survival. The C-index of joint nomogarm for overall survival and post fistula survival was 0.831 (95% CI: 0.757-0.905) and 0.77 (95% CI: 0.686-0.854), respectively. The calibration curve showed the joint nomograms outperformed the clinical ones. CONCLUSIONS: The study presents nomograms incorporating independent clinical risk factors and radiomic signature to predict the prognosis of MEF. This prognostic classification system has the potential to guide therapeutic decisions for patients with malignant esophageal fistulas.

Recovery Experience: A Concept for Maintaining Quality of Life and Its Mediating Effect Among Female Nurses in China.

PURPOSE: Nurses are high-risk groups for job burnout, which affect their quality of life (QOL). Recovery experience, a conceptualization of positive psychological resources, can combat the negative impacts of job burnout on health and QOL. The aim of this study was to examine the mediating effect of recovery experience on the relationship between job burnout and QOL among female nurses in China. PARTICIPANTS AND METHODS: QOL information was captured from 1068 female nurses from December 2017 to February 2018 in tertiary hospitals in Shenyang, Liaoning Province of China. A structural equation model was employed to examine the mediating effect of recovery experience on the relationship between job burnout and QOL. RESULTS: Job burnout had a significant impact on both the mental component summary and the physical component summary of a 36-item Short-Form Health Survey. However, mental component summary scores were significantly lower than physical component summary scores in female nurses. Recovery experience played a mediating role in the relationship between job burnout and QOL. CONCLUSION: Job burnout could result in a reduction in QOL among Chinese female nurses. Recovery experience, as a mediating factor, could alleviate the impact of job burnout on QOL. Recovery experience should be strengthened to attenuate job burnout and enhance QOL.

Development and validation of radiomics model built by incorporating machine learning for identifying liver fibrosis and early-stage cirrhosis.

BACKGROUND: Liver fibrosis (LF) continues to develop and eventually progresses to cirrhosis. However, LF and early-stage cirrhosis (ESC) can be reversed in some cases, while advanced cirrhosis is almost impossible to cure. Advances in quantitative imaging techniques have made it possible to replace the gold standard biopsy method with non-invasive imaging, such as radiomics. Therefore, the purpose of this study is to develop a radiomics model to identify LF and ESC. METHODS: Patients with LF (n = 108) and ESC (n = 116) were enrolled in this study. As a control, patients with healthy livers were involved in the study (n = 145). Diffusion-weighted imaging (DWI) data sets with three b-values (0, 400, and 800 s/mm) of enrolled cases were collected in this study. Then, radiomics features were extracted from manually delineated volumes of interest. Two modeling strategies were performed after univariate analysis and feature selection. Finally, an optimal model was determined by the receiver operating characteristic area under the curve (AUC). RESULTS: The optimal models were built in plan 1. For model 1 in plan 1, the AUCs of the training and validation cohorts were 0.973 (95% confidence interval [CI] 0.946-1.000) and 0.948 (95% CI 0.903-0.993), respectively. For model 2 in plan 1, the AUCs of the training and validation cohorts were 0.944, 95% CI 0.905 to 0.983, and 0.968, 95% CI 0.940 to 0.996, respectively. CONCLUSIONS: Radiomics analysis of DWI images allows for accurate identification of LF and ESC, and the non-invasive biomarkers extracted from the functional DWI images can serve as a better alternative to biopsy.

Recovery Experience as the Mediating Factor in the Relationship Between Sleep Disturbance and Depressive Symptoms Among Female Nurses in Chinese Public Hospitals: A Structural Equation Modeling Analysis.

PURPOSE: Nurses are suffering from considerable work-related stress, which can result in disturbed sleep and depressive symptoms. Whereas, recovery experience can alleviate sleep disturbance and help maintain well-being in the working environment. The aim of this study was to examine whether recovery experiences play a mediating role in the relationship between sleep disturbance and depressive symptoms of female nurses in Chinese public hospitals. METHODS: From December 2017 to May 2018, the study with proportional sampling of cross-sectional design was carried out in the public tertiary hospitals from Shenyang of Liaoning Province in China. A total of 1500 female nurses who had been working for one or more years participated in this study. A structural equation model (SEM) was applied to test the assumption that recovery experiences might function as a mediator in the relationship between sleep disturbance and symptoms of depression. RESULTS: Sleep disturbance contributed most to the variance (32.9%) of depressive symptoms and had a significantly positive correlation with depressive symptoms (P<0.01) among nurses. Psychological detachment in recovery experience had a significantly positive correlation with sleep disturbance (P<0.01) and depressive symptoms (P<0.01). Whereas, relaxation, mastery experience, and control in recovery experience were significantly and negatively correlated with sleep disturbance (P<0.01) and depressive symptoms (P<0.01). Recovery experience served as a mediator between sleep disturbance and depressive symptoms (a * b = 0.066, BCa 95% CI: 0.045, 0.095). CONCLUSION: Sleep disturbance was the predictor of depressive symptoms for female nurses. Moreover, recovery experience could combat the detrimental impacts of sleep disturbances on symptoms of depression. This study suggested that nurses might benefit from interventions on improving sleep quality to relieve depressive symptoms through mediating path of recovery experience.

A machine-compiled database of genome-wide association studies.

Tens of thousands of genotype-phenotype associations have been discovered to date, yet not all of them are easily accessible to scientists. Here, we describe GWASkb, a machine-compiled knowledge base of genetic associations collected from the scientific literature using automated information extraction algorithms. Our information extraction system helps curators by automatically collecting over 6,000 associations from open-access publications with an estimated recall of 60-80% and with an estimated precision of 78-94% (measured relative to existing manually curated knowledge bases). This system represents a fully automated GWAS curation effort and is made possible by a paradigm for constructing machine learning systems called data programming. Our work represents a step towards making the curation of scientific literature more efficient using automated systems.