Abnormal glucose metabolism in virus associated sepsis.

Sepsis is identified as a potentially lethal organ impairment triggered by an inadequate host reaction to infection (Sepsis-3). Viral sepsis is a potentially deadly organ impairment state caused by the host's inappropriate reaction to a viral infection. However, when a viral infection occurs, the metabolism of the infected cell undergoes a variety of changes that cause the host to respond to the infection. But, until now, little has been known about the challenges faced by cellular metabolic alterations that occur during viral infection and how these changes modulate infection. This study concentrates on the alterations in glucose metabolism during viral sepsis and their impact on viral infection, with a view to exploring new potential therapeutic targets for viral sepsis.

Impact of free hypertension pharmacy program and social distancing policy on stroke: A longitudinal study.

Background: The estimated lifetime risk of stroke was the highest in East Asia worldwide, especially in China. Antihypertensive therapy can significantly reduce stroke mortality. However, blood pressure control is poor. Medication adherence is a barrier as patients' out-of-pocket costs have risen. We aimed to take advantage of a free hypertension pharmacy intervention and quantified the impact on stroke mortality. Methods: A free pharmaceutical intervention program was implemented in Deqing, Zhejiang province in April 2018. Another non-pharmaceutical intervention, social distancing due to the pandemic of Coronavirus disease 2019 (COVID-19), was also key to affecting stroke mortality. We retrospectively collected the routine surveillance data of stroke deaths from Huzhou Municipal Center for Disease Prevention and Control in 2013-2020 and obtained within-city mobility data from Baidu Migration in 2019-2020, then we quantified the effects of both pharmaceutical intervention and social distancing using Serfling regression model. Results: Compared to the predicted number, the actual number of stroke deaths was significantly lower by 10% (95% CI, 6-15%; p < 0.001) from April 2018 to December 2020 in Deqing. Specifically, there was a reduction of 19% (95% CI, 10-28%; p < 0.001) in 2018. Moreover, we observed a 5% (95% CI, -4 - 14%; p = 0.28) increase in stroke mortality due to the adverse effect of COVID-19 but it wasn't statistically significant. Conclusion: Free hypertension pharmacy program has great potential to prevent considerable stroke deaths. In the future, the free supply of low-cost, essential medications that target patients with hypertension at increased risk of stroke could be taken into account in formulating public health policies and guiding allocations of health care resources.

Sacral neuromodulation remote programming in patients with refractory lower urinary tract dysfunction: China's experience during the COVID-19 pandemic.

Objectives: Sacral neuromodulation is an effective, minimally invasive treatment for refractory lower urinary tract dysfunction. However, regular postoperative programming is crucial for the maintenance of the curative effects of electronic sacral stimulator devices. The outbreak of coronavirus disease 2019 (COVID-19) limited the ability of practitioners to perform traditional face-to-face programming of these stimulators. Therefore, this study aimed to evaluate the application of remote programming technology for sacral neuromodulation during the COVID-19 pandemic in China. Materials and methods: We retrospectively collected data including baseline and programming information of all patients with lower urinary tract dysfunction who underwent sacral neuromodulation remote programming in China after the outbreak of COVID-19 (i.e., December 2019). The patients also completed a self-designed telephone questionnaire on the subject. Results: A total of 51 patients from 16 centers were included. They underwent 180 total remote programming visits, and 118, 2, 25, and 54 voltage, current, pulse width, and frequency adjustments, respectively, were performed. Additionally, remote switching on and off was performed 8 times; impedance test, 54 times; and stimulation contact replacement, 25 times. The demand for remote programming was the highest during the first 6 months of sacral neuromodulation (average, 2.39 times per person). In total, 36 out of the 51 patients completed the questionnaire survey. Of these, all indicated that they chose remote programming to minimize unnecessary travel because they had been affected by COVID-19. The questionnaire also showed that remote programming could reduce the number of patient visits to the hospital, save time, reduce financial costs, and would be easy for patients to master. All surveyed patients indicated that they were satisfied with remote programming and were willing to recommend it to other patients. Conclusion: Remote programming for sacral neuromodulation is feasible, effective, safe, and highly recommended by patients with refractory lower urinary tract dysfunction. Remote programming technology has great development and application potential in the post-pandemic era.

Coarse-Grained Modeling of the SARS-CoV-2 Spike Glycoprotein by Physics-Informed Machine Learning

Coarse-grained (CG) modeling has defined a well-established approach to accessing greater space and time scales inaccessible to the computationally expensive all-atomic (AA) molecular dynamics (MD) simulations. Popular methods of CG follow a bottom-up architecture to match properties of fine-grained or experimental data whose development is a daunting challenge for requiring the derivation of a new set of parameters in potential calculation. We proposed a novel physics-informed machine learning (PIML) framework for a CG model and applied it, as a verification, for modeling the SARS-CoV-2 spike glycoprotein. The PIML in the proposed framework employs a force-matching scheme with which we determined the force-field parameters. Our PIML framework defines its trainable parameters as the CG force-field parameters and predicts the instantaneous forces on each CG bead, learning the force field parameters to best match the predicted forces with the reference forces. Using the learned interaction parameters, CGMD validation simulations reach the microsecond time scale with stability, at a simulation speed 40,000 times faster than the conventional AAMD. Compared with the traditional iterative approach, our framework matches the AA reference structure with better accuracy. The improved efficiency enhances the timeliness of research and development in producing long-term simulations of SARS-CoV-2 and opens avenues to help illuminate protein mechanisms and predict its environmental changes.

System dynamics modeling and robustness analysis for capital-constrained supply chain under disruption

PurposeThe purpose of this study is to explore mitigation measures for cash flow interruption during the epidemic and provide decision support to ensure the regular operation and robustness of the supply chain (SC).Design/methodology/approachConsidering the scenarios of production capacity and demand disruption during the epidemic, the authors adopt system dynamics (SD) to construct a three-echelon SC financial system consisting of a core manufacturer, a capital-constrained retailer and the customer. In different interruption scenarios, through the decision adjustments of stakeholders, the differences in performance are compared to explore solutions for SC robust optimization.FindingsThe results show that partial credit guarantee (PCG) could solve cash flow interruption and maintain the regular operation of the SC. During epidemic, with the product price increases, the revenue of stakeholders and the robustness are generally negatively correlated. But when the manufacturer's production capacity is fully interrupted, increasing product price is the right decision for the retailer and could simultaneously promote performance and robustness.Originality/valueThis paper primarily focuses on the PCG under the cash flow interruption caused by epidemics. The authors adopt the supply chain finance (SCF) theory and SD method to supplement and expand existing research on interruption management of SC. It is a pioneering study to explore the robustness of the SC financial system under disruptions.

Ectopic expression of SARS-CoV-2 S and ORF-9B proteins alters metabolic profiles and impairs contractile function in cardiomyocytes

Coronavirus disease 2019 (COVID-19) is associated with adverse impacts in the cardiovascular system, but the mechanisms driving this response remain unclear. In this study, we conducted "pseudoviral infection” of SARS-CoV-2 subunits to evaluate their toxic effects in cardiomyocytes (CMs), that were derived from human induced pluripotent stem cells (hiPSCs). We found that the ectopic expression of S and ORF-9B subunits significantly impaired the contractile function and altered the metabolic profiles in human cardiomyocytes. Further mechanistic study has shown that the mitochondrial oxidative phosphorylation (OXPHOS), membrane potential, and ATP production were significantly decreased two days after the overexpression of S and ORF-9B subunits, while S subunits induced higher level of reactive oxygen species (ROS). Two weeks after overexpression, glycolysis was elevated in the ORF-9B group. Based on the transcriptomic analysis, both S and ORF-9B subunits dysregulated signaling pathways associated with metabolism and cardiomyopathy, including upregulated genes involved in HIF-signaling and downregulated genes involved in cholesterol biosynthetic processes. The ORF-9B subunit also enhanced glycolysis in the CMs. Our results collectively provide an insight into the molecular mechanisms underlying SARS-CoV-2 subunits-induced metabolic alterations and cardiac dysfunctions in the hearts of COVID-19 patients.

Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases.

Background and Objective: Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor of the digestive system worldwide. Chronic hepatitis B virus (HBV) infection and aflatoxin exposure are predominant causes of HCC in China, whereas hepatitis C virus (HCV) infection and alcohol intake are likely the main risk factors in other countries. It is an unmet need to recognize the underlying molecular mechanisms of HCC in China. Methods: In this study, microarray datasets (GSE84005, GSE84402, GSE101685, and GSE115018) derived from Gene Expression Omnibus (GEO) database were analyzed to obtain the common differentially expressed genes (DEGs) by R software. Moreover, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID). Furthermore, the protein-protein interaction (PPI) network was constructed, and hub genes were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape, respectively. The hub genes were verified using Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Kaplan-Meier Plotter online databases were performed on the TCGA HCC dataset. Moreover, the Human Protein Atlas (HPA) database was used to verify candidate genes' protein expression levels. Results: A total of 293 common DEGs were screened, including 103 up-regulated genes and 190 down-regulated genes. Moreover, GO analysis implied that common DEGs were mainly involved in the oxidation-reduction process, cytosol, and protein binding. KEGG pathway enrichment analysis presented that common DEGs were mainly enriched in metabolic pathways, complement and coagulation cascades, cell cycle, p53 signaling pathway, and tryptophan metabolism. In the PPI network, three subnetworks with high scores were detected using the Molecular Complex Detection (MCODE) plugin. The top 10 hub genes identified were CDK1, CCNB1, AURKA, CCNA2, KIF11, BUB1B, TOP2A, TPX2, HMMR and CDC45. The other public databases confirmed that high expression of the aforementioned genes related to poor overall survival among patients with HCC. Conclusion: This study primarily identified candidate genes and pathways involved in the underlying mechanisms of Chinese HCC, which is supposed to provide new targets for the diagnosis and treatment of HCC in China.

Computational study of novel inhibitory molecule, 1-(4-((2S,3S)-3-amino-2-hydroxy-4-phenylbutyl)piperazin-1-yl)-3-phenylurea, with high potential to competitively block ATP binding to the RNA dependent RNA polymerase of SARS-CoV-2 virus.

For coronaviruses, RNA-dependent RNA polymerase (RdRp) is an essential enzyme that catalyses the replication from RNA template and therefore remains an attractive therapeutic target for anti-COVID drug discovery. In the present study, we performed a comprehensive in silico screening for 16,776 potential molecules from recently established drug libraries based on two important pharmacophores (3-amino-4-phenylbutan-2-ol and piperazine). Based on initial assessment, 4042 molecules were obtained suitable as drug candidates, which were following Lipinski's rule. Molecular docking implemented for the analysis of molecular interactions narrowed this number of compounds down to 19. Subsequent to screening filtering criteria and considering the critical parameters viz. docking score and MM-GBSA binding free energy, 1-(4-((2S,3S)-3-amino-2-hydroxy-4-phenylbutyl)piperazin-1-yl)-3-phenylurea (compound 1) was accomplished to score highest in comparison to the remaining 18 shortlisted drug candidates. Notably, compound 1 displayed higher docking score (-8.069 kcal/mol) and MM-GBSA binding free energy (-49.56 kcal/mol) than the control drug, remdesivir triphosphate, the active form of remdesivir as well as adenosine triphosphate. Furthermore, a molecular dynamics simulation was carried out (100 ns), which substantiated the candidacy of compound 1 as better inhibitor. Overall, our systematic in silico study predicts the potential of compound 1 to exhibit a more favourable specific activity than remdesivir triphosphate. Hence, we suggest compound 1 as a novel potential drug candidate, which should be considered for further exploration and validation of its potential against SARS-CoV-2 in wet lab experimental studies.Communicated by Ramasawamy H. Sarma.

Ionizable drug delivery systems for efficient and selective gene therapy.

Gene therapy has shown great potential to treat various diseases by repairing the abnormal gene function. However, a great challenge in bringing the nucleic acid formulations to the market is the safe and effective delivery to the specific tissues and cells. To be excited, the development of ionizable drug delivery systems (IDDSs) has promoted a great breakthrough as evidenced by the approval of the BNT162b2 vaccine for prevention of coronavirus disease 2019 (COVID-19) in 2021. Compared with conventional cationic gene vectors, IDDSs can decrease the toxicity of carriers to cell membranes, and increase cellular uptake and endosomal escape of nucleic acids by their unique pH-responsive structures. Despite the progress, there remain necessary requirements for designing more efficient IDDSs for precise gene therapy. Herein, we systematically classify the IDDSs and summarize the characteristics and advantages of IDDSs in order to explore the underlying design mechanisms. The delivery mechanisms and therapeutic applications of IDDSs are comprehensively reviewed for the delivery of pDNA and four kinds of RNA. In particular, organ selecting considerations and high-throughput screening are highlighted to explore efficiently multifunctional ionizable nanomaterials with superior gene delivery capacity. We anticipate providing references for researchers to rationally design more efficient and accurate targeted gene delivery systems in the future, and indicate ideas for developing next generation gene vectors.

Lymphocytes regulate expression of the SARS-CoV-2 cell entry factor ACE2 in the pancreas of T2DM patients.

AIMS: COVID-19 patients with type 2 diabetes mellitus (T2DM) show both poorer clinical outcomes and have an increased risk of death. SARS-CoV-2 virus infection requires simultaneous expression of the SARS-CoV-2 cell entry factors angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine type 2 (TMPRSS2) in the same cell. The aim of the study was to explore the underlying mechanisms of a COVID-19 infection in patients with T2DM. METHODS: The distribution and expression of AEC2 and TMPRSS2 in different pancreatic cell types in clinical samples of T2DM patients and diabetic mouse models were analysed by single-cell sequencing, bioinformatics analysis and basic experiments. RESULTS: The results showed that ACE2 and TMPRSS2 are expressed in the ducts of the human pancreas. These findings suggest that SARS-CoV-2 can infect ductal cells in vivo through ACE2 and TMPRSS2. T2DM can promote the co-expression of ACE2 and TMPRSS2 in exocrine ducts, including in the human pancreas. We hypothesize that ACE2 expression levels are associated with increased numbers of lymphocytes in vivo. CONCLUSIONS: Increased blood glucose levels are associated with increased ACE2 expression and an increased number of lymphocytes. At the same time, lymphocytes can promote ACE2 expression.

Real-time detection of SARS-CoV-2 in clinical samples via ultrafast ligation-dependent RNA transcription amplification.

RNA has been recognized as an important biomarker of many infectious pathogens; thus, sensitive, simple and rapid detection of RNA is urgently required for the control of epidemics. Herein, we report an ultrafast ligation-dependent RNA transcription amplification assay with high sensitivity and specificity for real-time detection of SARS-CoV-2 in real clinical samples, termed splint-based cascade transcription amplification (SCAN). Target RNA is first recognized by two DNA probes, which are then ligated together by SplintR, followed by the binding of the T7 promotor and T7 RNA polymerase to the ligated probe and the start of the transcription process. By introducing a vesicular stomatitis virus (VSV) terminator in the ligated probe, large amounts of RNA transcripts are rapidly produced within 10 min, which then directly hybridize with molecular beacons (MBs) and trigger the conformational switch of the MBs to generate a fluorescence signal that can be monitored in real time. The SCAN assay, which can be completed within 30-50 min, has a limit of detection of 104 copies per mL, while exhibiting high specificity to distinguish the target pathogen from those causing similar syndromes. More importantly, the results of SCAN for SARS-CoV-2 detection in clinical samples display great agreement with the most used qRT-PCR and qRT-LAMP, indicating great potential in the diagnosis of pathogens in clinical practice.

Ectopic expression of SARS-CoV-2 S and ORF-9B proteins alters metabolic profiles and impairs contractile function in cardiomyocytes.

Coronavirus disease 2019 (COVID-19) is associated with adverse impacts in the cardiovascular system, but the mechanisms driving this response remain unclear. In this study, we conducted "pseudoviral infection" of SARS-CoV-2 subunits to evaluate their toxic effects in cardiomyocytes (CMs), that were derived from human induced pluripotent stem cells (hiPSCs). We found that the ectopic expression of S and ORF-9B subunits significantly impaired the contractile function and altered the metabolic profiles in human cardiomyocytes. Further mechanistic study has shown that the mitochondrial oxidative phosphorylation (OXPHOS), membrane potential, and ATP production were significantly decreased two days after the overexpression of S and ORF-9B subunits, while S subunits induced higher level of reactive oxygen species (ROS). Two weeks after overexpression, glycolysis was elevated in the ORF-9B group. Based on the transcriptomic analysis, both S and ORF-9B subunits dysregulated signaling pathways associated with metabolism and cardiomyopathy, including upregulated genes involved in HIF-signaling and downregulated genes involved in cholesterol biosynthetic processes. The ORF-9B subunit also enhanced glycolysis in the CMs. Our results collectively provide an insight into the molecular mechanisms underlying SARS-CoV-2 subunits-induced metabolic alterations and cardiac dysfunctions in the hearts of COVID-19 patients.

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19.

BACKGROUND: We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15-20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. METHODS: We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. RESULTS: No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5-528.7, P = 1.1 × 10-4) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3-8.2], P = 2.1 × 10-4). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1-2635.4], P = 3.4 × 10-3), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3-8.4], P = 7.7 × 10-8). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10-5). CONCLUSIONS: Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.

Prior Attention Network for Multi-Lesion Segmentation in Medical Images.

The accurate segmentation of multiple types of lesions from adjacent tissues in medical images is significant in clinical practice. Convolutional neural networks (CNNs) based on the coarse-to-fine strategy have been widely used in this field. However, multi-lesion segmentation remains to be challenging due to the uncertainty in size, contrast, and high interclass similarity of tissues. In addition, the commonly adopted cascaded strategy is rather demanding in terms of hardware, which limits the potential of clinical deployment. To address the problems above, we propose a novel Prior Attention Network (PANet) that follows the coarse-to-fine strategy to perform multi-lesion segmentation in medical images. The proposed network achieves the two steps of segmentation in a single network by inserting a lesion-related spatial attention mechanism in the network. Further, we also propose the intermediate supervision strategy for generating lesion-related attention to acquire the regions of interest (ROIs), which accelerates the convergence and obviously improves the segmentation performance. We have investigated the proposed segmentation framework in two applications: 2D segmentation of multiple lung infections in lung CT slices and 3D segmentation of multiple lesions in brain MRIs. Experimental results show that in both 2D and 3D segmentation tasks our proposed network achieves better performance with less computational cost compared with cascaded networks. The proposed network can be regarded as a universal solution to multi-lesion segmentation in both 2D and 3D tasks. The source code is available at https://github.com/hsiangyuzhao/PANet.

Genome-wide detection of human variants that disrupt intronic branchpoints.

Pre-messenger RNA splicing is initiated with the recognition of a single-nucleotide intronic branchpoint (BP) within a BP motif by spliceosome elements. Forty-eight rare variants in 43 human genes have been reported to alter splicing and cause disease by disrupting BP. However, until now, no computational approach was available to efficiently detect such variants in massively parallel sequencing data. We established a comprehensive human genome-wide BP database by integrating existing BP data and generating new BP data from RNA sequencing of lariat debranching enzyme DBR1-mutated patients and from machine-learning predictions. We characterized multiple features of BP in major and minor introns and found that BP and BP-2 (two nucleotides upstream of BP) positions exhibit a lower rate of variation in human populations and higher evolutionary conservation than the intronic background, while being comparable to the exonic background. We developed BPHunter as a genome-wide computational approach to systematically and efficiently detect intronic variants that may disrupt BP recognition. BPHunter retrospectively identified 40 of the 48 known pathogenic BP variants, in which we summarized a strategy for prioritizing BP variant candidates. The remaining eight variants all create AG-dinucleotides between the BP and acceptor site, which is the likely reason for missplicing. We demonstrated the practical utility of BPHunter prospectively by using it to identify a novel germline heterozygous BP variant of STAT2 in a patient with critical COVID-19 pneumonia and a novel somatic intronic 59-nucleotide deletion of ITPKB in a lymphoma patient, both of which were validated experimentally. BPHunter is publicly available from https://hgidsoft.rockefeller.edu/BPHunter and https://github.com/casanova-lab/BPHunter.

Anti-PF4 antibodies associated with disease severity in COVID-19.

Severe COVID-19 is characterized by a prothrombotic state associated with thrombocytopenia, with microvascular thrombosis being almost invariably present in the lung and other organs at postmortem examination. We evaluated the presence of antibodies to platelet factor 4 (PF4)-polyanion complexes using a clinically validated immunoassay in 100 hospitalized patients with COVID-19 with moderate or severe disease (World Health Organization score, 4 to 10), 25 patients with acute COVID-19 visiting the emergency department, and 65 convalescent individuals. Anti-PF4 antibodies were detected in 95 of 100 hospitalized patients with COVID-19 (95.0%) irrespective of prior heparin treatment, with a mean optical density value of 0.871 ± 0.405 SD (range, 0.177 to 2.706). In contrast, patients hospitalized for severe acute respiratory disease unrelated to COVID-19 had markedly lower levels of the antibodies. In a high proportion of patients with COVID-19, levels of all three immunoglobulin (Ig) isotypes tested (IgG, IgM, and IgA) were simultaneously elevated. Antibody levels were higher in male than in female patients and higher in African Americans and Hispanics than in White patients. Anti-PF4 antibody levels were correlated with the maximum disease severity score and with significant reductions in circulating platelet counts during hospitalization. In individuals convalescent from COVID-19, the antibody levels returned to near-normal values. Sera from patients with COVID-19 induced higher levels of platelet activation than did sera from healthy blood donors, but the results were not correlated with the levels of anti-PF4 antibodies. These results demonstrate that the vast majority of patients with severe COVID-19 develop anti-PF4 antibodies, which may play a role in the clinical complications of COVID-19.

Effectiveness of inactivated COVID-19 vaccines against mild disease, pneumonia, and severe disease among persons infected with SARS-CoV-2 Omicron variant: Real-world study in Jilin Province, China.

BACKGROUND: : It is critical to determine the real-world performance of vaccines against coronavirus disease 2019 (COVID-19) so that appropriate treatments and policies can be implemented. There was a rapid wave of infections by the Omicron variant in Jilin Province (China) during spring 2022. We examined the effectiveness of inactivated vaccines against Omicron using real-world data from this epidemic. METHODS: . This retrospective case-case study of vaccine effectiveness (VE) examined infected patients who were quarantined and treated from April 16 to June 8, 2022 and responded to an electronic questionnaire. Data were analyzed by univariable and multivariable analyses. RESULTS: . A total of 2968 cases with SARS-CoV-2 infections (asymptomatic: 1029, mild disease: 1858, pneumonia: 108, severe disease: 21) were enrolled in the study. Multivariable regression indicated that the risk for pneumonia or severe disease was greater in those who were older or had underlying diseases, but was less in those who received COVID-19 vaccines. Relative to no vaccination, VE against the composite of pneumonia and severe disease was significant for those who received 2 doses (60.1%, 95%CI: 40.0%, 73.5%) or 3 doses (68.1%, 95%CI: 44.6%, 81.7%), and VE was similar in the subgroups of males and females. However, VE against the composite of all three classes of symptomatic diseases was not significant overall, nor after stratification by sex. There was no statistical difference in the VE of vaccines from different manufacturers. CONCLUSION: . The inactivated COVID-19 vaccines protected patients against pneumonia and severe disease from Omicron infection, and booster vaccination enhanced this effect.

Job burnout and its influencing factors in Chinese medical staffs under China's prevention and control strategy for the COVID-19 pandemic.

OBJECTIVE: This study aimed to investigate the influencing factors of burnout among grassroots medical staff in China so as to provide a reference for improving their physical, psychological, and social statuses under China's prevention and control strategy for the COVID-19 pandemic and ensuring the sustainable supply of high-quality medical resources. METHODS: This study was performed on medical staff in five primary hospitals in Jiangsu Province, China, from May 1, 2022, to June 1, 2022, using a general information questionnaire and Maslach Burnout Inventory Scale. SPSS 25.0 and Stata 15.0 were used for two-track data entry and analysis. The OLS regression model was established to analyze the influencing factors for the job burnout of health care personnel. RESULTS: Two hundred seventy valid questionnaires were analyzed. The total score of job burnout was (30.16 ± 10.99). The scores of emotional exhaustion, depersonalization, and self-achievement were (9.88 ± 3.839), (11.99 ± 5.68), and (8.29 ± 5.18), respectively. Feeling depressed and stressed after the pandemic, days working over the past week, and work hours per shift had a positive impact on the Maslach Burnout total score. Increased income and hours working every week had a negative impact on the Maslach Burnout total score. However, sex, age in years, degree, professional title, job category, workplace, marital status, years in practice, health status, active management of health, idea of resignation, and promotion after the pandemic did not affect the Maslach Burnout total score. CONCLUSION: The job burnout of medical staff is affected by health conditions, working conditions, the psychological consequences of a pandemic, wages and marital status. Hospital managers should formulate incentive measures according to different psychological changes in medical staff to create a good medical working environment under the normalization of COVID-19 pandemic prevention and control.

NPInter v5.0: ncRNA interaction database in a new era.

Noncoding RNAs (ncRNAs) play key regulatory roles in biological processes by interacting with other biomolecules. With the development of high-throughput sequencing and experimental technologies, extensive ncRNA interactions have been accumulated. Therefore, we updated the NPInter database to a fifth version to document these interactions. ncRNA interaction entries were doubled from 1 100 618 to 2 596 695 by manual literature mining and high-throughput data processing. We integrated global RNA-DNA interactions from iMARGI, ChAR-seq and GRID-seq, greatly expanding the number of RNA-DNA interactions (from 888 915 to 8 329 382). In addition, we collected different types of RNA interaction between SARS-CoV-2 virus and its host from recently published studies. Long noncoding RNA (lncRNA) expression specificity in different cell types from tumor single cell RNA-seq (scRNA-seq) data were also integrated to provide a cell-type level view of interactions. A new module named RBP was built to display the interactions of RNA-binding proteins with annotations of localization, binding domains and functions. In conclusion, NPInter v5.0 (http://bigdata.ibp.ac.cn/npinter5/) provides informative and valuable ncRNA interactions for biological researchers.

Association of nirmatrelvir/ritonavir treatment on upper respiratory SARS-CoV-2 RT-PCR negative conversion rates among high-risk patients with COVID-19.

BACKGROUND: Acceleration of negative respiratory conversion of SARS-CoV-2 in patients with coronavirus disease 2019 (COVID-19) might reduce viral transmission. Nirmatrelvir/ritonavir is a new antiviral agent recently approved for treatment of COVID-19 that has the potential to facilitate negative conversion. METHODS: A cohort of hospitalized adult patients with mild-to-moderate COVID-19 who had a high-risk for progression to severe disease were studied. These patients presented with COVID-19 symptoms between March 5 and April 5, 2022. The time from positive to negative upper respiratory RT-PCR conversion was assessed by Kaplan-Meier plots and Cox proportional hazards regression with the adjustment for patients baseline demographic and clinical characteristics. RESULTS: There were 258 patients treated with nirmatrelvir/ritonavir and 224 non-treated patients who had mild-to-moderate COVID-19. The median (interquartile range) time for patients who converted from positive to negative RT-PCR was 10 days (7-12 days) in patients treated ≤5 days after symptom onset and 17 days (12-21 days) in non-treated patients, respectively. The proportions of patients with a negative conversion at day 15 were 89.7% and 42.0% in treated patients and non-treated patients, corresponding to a hazard ratio of 4.33 (95% CI, 3.31-5.65). Adjustment for baseline differences between the groups had little effect on the association. Subgroup analysis on treated patients suggests that time to negative conversion did not vary with the patients' baseline characteristics. CONCLUSION: This cohort study of high-risk patients with mild-to-moderate COVID-19 found an association between nirmatrelvir/ritonavir treatment and accelerated negative RT-PCR respiratory SARS-CoV-2 conversion that might reduce the risk of viral shedding and disease transmission.