The Impact of Post Embryo Transfer SARS-CoV-2 Infection on Pregnancy in In Vitro Fertilization: A Prospective Cohort Study (preprint)

ImportanceLimited knowledge exists on the effects of SARS-CoV-2 infection after embryo transfer, despite an increasing number of studies exploring the impact of previous SARS-CoV-2 infection on IVF outcomes. ObjectiveThis prospective cohort study aimed to assess the influence of SARS-CoV-2 infection at various time stages after embryo transfer on pregnancy outcomes in patients undergoing conventional in vitro fertilization/intracytoplasmic sperm injection-embryo transfer (IVF/ICSI) treatment. DesignThe study was conducted at a single public IVF center in China. SettingThis was a population-based prospective cohort study. ParticipantsFemale patients aged 20 to 39 years, with a body mass index (BMI) between 18 and 30 kg/m2, undergoing IVF/ICSI treatment, were enrolled from September 2022 to December 2022, with follow-up until March 2023. ExposureThe pregnancy outcome of patients was compared between those SARS-CoV-2-infected after embryo transfer and those noninfected during the follow-up period. Main Outcomes and MeasuresThe pregnancy outcomes included biochemical pregnancy rate, implantation rate, clinical pregnancy rate, and early miscarriage rate. ResultsA total of 857 female patients undergoing IVF/ICSI treatment were included in the analysis. We observed the incidence of SARS-CoV-2 infection within 10 weeks after embryo transfer. The biochemical pregnancy rate and implantation rate were lower in the infected group than the uninfected group (58.1% vs 65.9%; 36.6% vs 44.0%, respectively), but no statistically significant. Although, the clinical pregnancy rate was significant lower in the infection group when compared with the uninfected group (49.1%vs 58.2%, p < 0.05), after adjustment for confounders, this increased risk was no longer significant between the two groups (adjusted OR, 0.736, 95% CI, 0.518-1.046). With continued follow-up, a slightly higher risk of early miscarriage in the infected group compared to the uninfected group (9.3% vs 8.8%), but it was not significant (adjusted OR, 0.907, 95% CI, 0.414-1.986). Conclusions and RelevanceThe studys findings suggested that SARS-CoV-2 infection within 10 weeks after embryo transfer may have not significantly affect pregnancy outcomes. This evidence allays concerns and provides valuable insights for assisted reproduction practices. Key pointsO_ST_ABSQuestionC_ST_ABSDid the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after embryo transfer affect pregnancy outcomes? FindingsIn this prospective cohort study involving 857 patients, we made a pioneering discovery that SARS-CoV-2 infection following embryo transfer did not exhibit adverse impact on the biochemical pregnancy rate, embryo implantation rate, clinical pregnancy rate, and early miscarriage rate. MeaningThe evidence from this study alleviates existing concerns and offers new insights into the actual risk of SARS-CoV-2 infection after embryo transfer in assisted reproduction.

Increasing trans-cleavage catalytic efficiency of Cas12a and Cas13a with chemical enhancers: Application to amplified nucleic acid detection

The exceptional programable trans-cleavage ability of type V and VI CRISPR/Cas nucleases paved the way for ultrasensitive CRISPR/Cas based sensing of nucleic acid and alternative targets. However, the enhancement of the trans-cleavage activity of Cas effector with organic chemical agents has not been explored thus far. We report here chemically enhanced trans-cleavage activity of Cas12a and Cas13a nucleases which improves sensor performance in CRISPR/Cas biosensing. Improved trans-ssDNA cleavage of Cas12a and trans-ssRNA cleavage of Cas13a were demonstrated by using sulfhydryl reductants and non-ionic surfactants. DTT and PVA were demonstrated to be the most effective chemical enhancers in both cases. By using a fluorescence resonance energy transfer (FRET)-based intramolecular distance measurements, we identified the mechanism of this enhancement to be the conformation change of the ribonucleoprotein and quantified it to be major (about 50% increase of a relevant intramolecular distance). These chemical enhancers have been integrated into the established CRISPR/Cas biosensing protocols without additional modifications. For the detection of Helicobacter Pylori DNA and SARS-CoV-2 RNA, we found a decreased reaction time by 75–83% and 4–6-fold increased sensitivity. These results indicate that chemical enhancers provide a versatile and broadly applicable approach to break through the barriers of long reaction time and sensitivity in CRISPR/Cas sensors.

Warfarin anticoagulation management during the COVID-19 pandemic: The role of internet clinic and machine learning

Background: Patients who received warfarin require constant monitoring by hospital staff. However, social distancing and stay-at-home orders, which were universally adopted strategies to avoid the spread of COVID-19, led to unprecedented challenges. This study aimed to optimize warfarin treatment during the COVID-19 pandemic by determining the role of the Internet clinic and developing a machine learning (ML) model to predict anticoagulation quality. Methods: This retrospective study enrolled patients who received warfarin treatment in the hospital anticoagulation clinic (HAC) and “Internet + Anticoagulation clinic” (IAC) of the Nanjing Drum Tower Hospital between January 2020 and September 2021. The primary outcome was the anticoagulation quality of patients, which was evaluated by both the time in therapeutic range (TTR) and international normalized ratio (INR) variability. Anticoagulation quality and incidence of adverse events were compared between HAC and IAC. Furthermore, five ML algorithms were used to develop the anticoagulation quality prediction model, and the SHAP method was introduced to rank the feature importance. Results: Totally, 241 patients were included, comprising 145 patients in the HAC group and 96 patients in the IAC group. In the HAC group and IAC group, 73.1 and 69.8% (p = 0.576) of patients achieved good anticoagulation quality, with the average TTR being 79.9 ± 20.0% and 80.6 ± 21.1%, respectively. There was no significant difference in the incidence of adverse events between the two groups. Evaluating the five ML models using the test set, the accuracy of the XGBoost model was 0.767, and the area under the receiver operating characteristic curve was 0.808, which showed the best performance. The results of the SHAP method revealed that age, education, hypertension, aspirin, and amiodarone were the top five important features associated with poor anticoagulation quality. Conclusion: The IAC contributed to a novel management method for patients who received warfarin during the COVID-19 pandemic, as effective as HAC and with a low risk of virus transmission. The XGBoost model could accurately select patients at a high risk of poor anticoagulation quality, who could benefit from active intervention.

Research trends and hotspots of breast cancer management during the COVID-19 pandemic: A bibliometric analysis

Background The coronavirus disease 2019 (COVID-19) pandemic is disrupting routine medical care of cancer patients, including those who have cancer or are undergoing cancer screening. In this study, breast cancer management during the COVID-19 pandemic (BCMP) is reviewed, and the research trends of BCMP are evaluated by quantitative and qualitative evaluation. Methods In this study, published studies relating to BCMP from 1 January 2020 to 1 April 2022 were searched from the Web of Science database (WoS). Bibliometric indicators consisted of publications, research hotspots, keywords, authors, journals, institutions, nations, and h-index. Results A total of 182 articles investigating BCMP were searched. The United States of America and the University of Rome Tor Vergata were the nation and the institution with the most publications on BCMP. The first three periodicals with leading published BCMP studies were Breast Cancer Research and Treatment, Breast, and In Vivo. Buonomo OC was the most prolific author in this field, publishing nine articles (9/182, 4.94%). The co-keywords analysis of BCMP suggests that the top hotspots and trends in research are screening, surgery, rehabilitation, emotion, diagnosis, treatment, and vaccine management of breast cancer during the pandemic. The hotspot words were divided into six clusters, namely, screening for breast cancer patients in the pandemic, breast cancer surgery in the pandemic, recovery of breast cancer patients in the pandemic, motion effect of the outbreak on breast cancer patients, diagnosis and treatment of breast cancer patients in the pandemic, and vaccination management for breast cancer patients during a pandemic. Conclusion BCMP has received attention from scholars in many nations over the last 3 years. This study revealed significant contributions to BCMP research by nations, institutions, scholars, and journals. The stratified clustering study provided the current status and future trends of BCMP to help physicians with the diagnosis and treatment of breast cancer through the pandemic, and provide a reference for in-depth clinical studies on BCMP.

A Vicious Cycle: In Severe and Critically Ill COVID-19 Patients

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, is one of the fastest-evolving viral diseases that has instigated a worldwide pandemic. Severe inflammatory syndrome and venous thrombosis are commonly noted in COVID-19 patients with severe and critical illness, contributing to the poor prognosis. Interleukin (IL)-6, a major complex inflammatory cytokine, is an independent factor in predicting the severity of COVID-19 disease in patients. IL-6 and tumor necrosis factor (TNF)-α participate in COVID-19-induced cytokine storm, causing endothelial cell damage and upregulation of plasminogen activator inhibitor-1 (PAI-1) levels. In addition, IL-6 and PAI-1 form a vicious cycle of inflammation and thrombosis, which may contribute to the poor prognosis of patients with severe COVID-19. Targeted inhibition of IL-6 and PAI-1 signal transduction appears to improve treatment outcomes in severely and critically ill COVID-19 patients suffering from cytokine storms and venous thrombosis. Motivated by studies highlighting the relationship between inflammatory cytokines and thrombosis in viral immunology, we provide an overview of the immunothrombosis and immunoinflammation vicious loop between IL-6 and PAI-1. Our goal is that understanding this ferocious circle will benefit critically ill patients with COVID-19 worldwide.

CONFIDENCE LEVEL OF A MOTION FEEDBACK SYSTEM FOR ANALYZING EXERCISE TRAINING EFFICACY: APPLICATIONS, BASIS, AND COMMUNICATIONS

The increase in aged population is a global trend. Inculcating healthy behaviors such as regular exercises in the elderly has a significant impact on the financial and medical burden globally. Moreover, air pollution and the outbreak of the coronavirus disease 19 (COVID-19) pose a serious threat to public health. In order to improve the health conditions of the population, this study developed a motion feedback system named MoveV that can be used for several indoor training exercises. This system provides instant motion feedback by synchronizing exercise training videos on the website using a motion analysis algorithm that is applicable on smartphones, and a cloud database platform is used to record health behaviors. Feature extraction is performed based on force intensity, motion velocity, and exercise direction. The resultant accuracy of the motion feedback system was tested by a motion science expert and presented as the confidence level. For perfect movement, a confidence level of up to 90.5% was achieved, indicating that the MoveV system was able to record users’ exercise frequency and distinguish whether the user was performing well in the exercise movements. The proposed system is convenient and does not incur additional expenditure by purchasing any new device. Furthermore, it provides visual and voice feedback, companionship, and exercise motivation to the users, all of which are important factors when using online exercise platforms.

Distance education quality evaluation based on multigranularity probabilistic linguistic term sets and disappointment theory

Distance education quality evaluation is extremely important in improving the quality of education under COVID-19. As traditional teaching-quality evaluation methods are no longer applicable, it is crucial to construct effective evaluation methods. In the evaluation of distance education quality, decision-makers have different linguistic expression preferences, and the evaluation information may be biased due to an improper grasp of the problem. In addition, the correlation between the criteria of distance education quality evaluation is common, and the results of existing evaluation methods are quite different. In this paper, to compensate for these deficiencies, we utilize the multi-granularity probabilistic linguistic term set (MGPLTS), which can reflect the linguistic expression preference of decision-makers and the importance of linguistic terms, and propose a multi-criteria group decision-making (MCGDM) method. First, the dispersion and concentration degrees are proposed as the theoretical basis for judging the hesitancy of decision-makers’ evaluation information, and the decision-maker weight adjustment model is constructed. To reflect the importance and correlation of criteria, the SWARA method and the CRITIC method are constructed as criteria weight methods. To obtain reliable decision results, decision-makers’ psychological expectations are taken into account, the MULTIMOORA method is improved upon, and a new integration theory is proposed to improve its robustness. Finally, through an example case of distance education quality evaluation and comparison with other methods, the effectiveness, practicability and superiority of this method are verified.

COVID-19 vaccine-related presumed allergic reactions and second dose administration by using a two-step graded protocol.

Background: Acute allergic reactions to messenger RNA (mRNA) vaccines are rare but may limit public health immunization efforts. Objectives: To characterize suspected allergic reactions to the first dose of coronavirus disease 2019 (COVID-19) mRNA vaccine and to assess the safety and utility of a two-step graded-dose protocol for the second dose of the Pfizer-BioNTech vaccine in patients with a history of low suspicion of anaphylaxis to their first dose. Methods: This was a retrospective evaluation of referrals to the allergy and immunology clinic for a presumed allergic reaction to the first dose of the COVID-19 mRNA vaccine (Pfizer-BioNTech or Moderna) between December 17, 2020, and February 28, 2021. Recommendations for the second dose and outcomes were evaluated by trained board-certified allergists. Results: Seventy-seven patients presented with a Pfizer-BioNTech reaction (56 [72.7%]) or with a Moderna reaction (21 [27.3%]). Most patients (69.7%) had symptom onset within 4 hours. Most commonly reported symptoms were cutaneous (51.9%), cardiovascular (48.1%), and respiratory (33.8%) symptoms. Recommendations included to proceed with the single dose (70.1%), two-step graded dose (19.5%), or deferral (10.4%). Twelve of 15 patients completed the second dose with a graded-dose protocol. Of these patients, five reported at least one or more similar symptoms as experienced with their first dose. Conclusion: Of the patients with presumed allergic reactions to their first dose of COVID-19 mRNA vaccine, most were able to safely receive the second dose. For those with a low suspicion of anaphylaxis, the two-step graded protocol with the Pfizer-BioNTech vaccine was well tolerated. A graded-dose protocol could be an effective strategy for second-dose vaccination in those who may otherwise defer the second dose.

Zooming and Re-design the Curriculum Evaluation with Action Learning

The article is addressed while the outbreak of COVID-19 which caused the teachers and the pupils of all educational institutions to stay home for online teaching and learning on May 2021. Therefore, it has forced the policy implementation, routine administration and professional development to re-considerate the coming challenges and the further arrangement. The article aims to the school-based curriculum evaluation of 12year Basic Curriculum Guideline, furthermore it concentrates in the evaluation of single disciplinary. Firstly, it addresses the locality of the curriculum evaluation between two national guidelines. After, the article inquires the possibility of re-locate and re-design of school-based evaluation through the Agile practice with which develops a new guideline. Finally, it presents an agenda of evaluation designed for single disciplinary. The article purposes a school-based curriculum evaluation, which integrates Agile and Action Learning, relates to the nature of pedagogy, for it is embodied in curriculum development. Thus, we are looking forward to the re-designed and re-located curriculum evaluation would support teachers' while they are developing curriculum and are doing instruction. As the curriculum evaluation and curriculum implementation are in sync, it not only aids learning effective of pupils, but also it benefits teachers whose professional development.

Duration of Acute Kidney Injury and in-hospital Mortality in Elder Patients With Severe COVID-19: a Retrospective Cohort Study (preprint)

Background Patients with severe coronavirus disease 2019 (COVID-19) who develop acute kidney injury (AKI) in the intensive care unit (ICU) have extremely high rates of mortality. This study evaluated the prognostic impact of AKI duration on in-hospital mortality in elder patients.Methods We performed a retrospective study of 126 patients with confirmed COVID-19 with severe or critical disease who treated in the ICU from February 4, 2020, to April 16, 2020. AKI was defined according to the Kidney Disease Improving Global Outcomes serum creatinine (Scr) criteria. AKI patients were divided into transient AKI and persistent AKI groups based on whether Scr level returned to baseline within 48 h post-AKI.Results In total, 107 patients were included in the final analysis. The mean age was 70 (64–78) years, and 69 (64.5%) patients were men. AKI occurred in 48 (44.9%) during their ICU stay. Of these, 11 (22.9%) had transient AKI, 37 (77.9%) had persistent AKI. In-hospital mortality was 18.6% (n =11) for patients without AKI, 72.7% (n=8) for patients with transient AKI, and 86.5% (n=32) for patients with persistent AKI (P<0.001). Kaplan–Meier curve analysis revealed that patients with both transient AKI and persistent AKI had significantly higher death rates than those without AKI (log-rank P<0.001). Multivariate Cox regression analysis revealed that transient and persistent AKI were an important risk factor for in-hospital mortality in older patients with severe COVID-19 even after adjustment for variables (hazard ratio [HR]=2.582; 95% CI: 1.025–6.505; P=0.044; and HR=6.974; 95% CI: 3.334–14.588; P<0.001).Conclusions AKI duration is a useful parameter to predict of worse clinical outcomes in elder patients with COVID-19 in the ICU. Among AKI patients, those persistent AKI have a lower in-hospital survival rate than those transient AKI, emphasizing the importance of identifying an appropriate treatment window for early intervention.

Potential mechanism study of herbal pair schizonepetae herba and saposhnikoviae radix against coronavirus pneumonia via network pharmacology and molecular docking

This study aims to predict potential targets and molecular mechanisms of herbal pair Schizonepetae Herba(SH) and Saposhnikoviae Radix(SR) against coronavirus pneumonia based on network pharmacology and molecular docking.At first, the active compounds and potential targets of SH and SR were collected from TCMSP,ETCM,BATMAN-TCM, and the related targets of coronavirus pneumonia were collected from GeneCards,OMIM, NCBI Gene. And then, PPI of common targets was analyzed by STRING,GO and KEGG enrichment analysis was performed by DAVID.At last, Autodock was used for molecular docking of potential pharmacodynamic compounds and key targets.A total of 28 active compounds and 56 key targets were collected from SH and SR.GO enrichment analysis collected 176 biological processes,47 molecular functions and 36 cell compounds (P < 0.05). The results of molecular docking showed that the binding energy of potential pharmacological compounds with key targets, angiotensin converting enzyme II (ACE2) and COVID-19 main protease was lower than -5 kcal/mol. This study demonstrated the potential pharmacodynamic compounds and targets of SH and SR on treatment of coronavirus pneumonia, which laid a foundation for the development and follow-up research of SH and SR.

CryoEM and AI reveal a structure of SARS-CoV-2 Nsp2, a multifunctional protein involved in key host processes. (preprint)

The SARS-CoV-2 protein Nsp2 has been implicated in a wide range of viral processes, but its exact functions, and the structural basis of those functions, remain unknown. Here, we report an atomic model for full-length Nsp2 obtained by combining cryo-electron microscopy with deep learning-based structure prediction from AlphaFold2. The resulting structure reveals a highly-conserved zinc ion-binding site, suggesting a role for Nsp2 in RNA binding. Mapping emerging mutations from variants of SARS-CoV-2 on the resulting structure shows potential host-Nsp2 interaction regions. Using structural analysis together with affinity tagged purification mass spectrometry experiments, we identify Nsp2 mutants that are unable to interact with the actin-nucleation-promoting WASH protein complex or with GIGYF2, an inhibitor of translation initiation and modulator of ribosome-associated quality control. Our work suggests a potential role of Nsp2 in linking viral transcription within the viral replication-transcription complexes (RTC) to the translation initiation of the viral message. Collectively, the structure reported here, combined with mutant interaction mapping, provides a foundation for functional studies of this evolutionary conserved coronavirus protein and may assist future drug design.

CryoEM and AI reveal a structure of SARS-CoV-2 Nsp2, a multifunctional protein involved in key host processes (preprint)

The SARS-CoV-2 protein Nsp2 has been implicated in a wide range of viral processes, but its exact functions, and the structural basis of those functions, remain unknown. Here, we report an atomic model for full-length Nsp2 obtained by combining cryo-electron microscopy with deep learning-based structure prediction from AlphaFold2. The resulting structure reveals a highly-conserved zinc ion-binding site, suggesting a role for Nsp2 in RNA binding. Mapping emerging mutations from variants of SARS-CoV-2 on the resulting structure shows potential host-Nsp2 interaction regions. Using structural analysis together with affinity tagged purification mass spectrometry experiments, we identify Nsp2 mutants that are unable to interact with the actin-nucleation-promoting WASH protein complex or with GIGYF2, an inhibitor of translation initiation and modulator of ribosome-associated quality control. Our work suggests a potential role of Nsp2 in linking viral transcription within the viral replication-transcription complexes (RTC) to the translation initiation of the viral message. Collectively, the structure reported here, combined with mutant interaction mapping, provides a foundation for functional studies of this evolutionary conserved coronavirus protein and may assist future drug design.

Linking social-psychological factors with policy expectation: Using local voices to understand solar PV poverty alleviation in Wuhan, China

The Chinese government has established a photovoltaics poverty alleviation (PVPA) program to help reduce rural poverty and environmental inequality. However, there is a scarcity of detailed investigations into how social-psychological factors influence the rural poor's decision to adopt solar photovoltaics. The present study examines the local voices of low-income villagers in the Wuhan region towards the PVPA projects from a social-psychological perspective. While focusing on local villagers' opinions before the onset of the COVID-19 pandemic, our findings suggest that villagers' neighbors have the greatest influence on those who subequently adopt solar PV. Similarly, village agents play a crucial role in spreading information and creating a sense of trust, which is different than other countries' solar adoption. The common goals of improving the local community aesthetically, environmentally, and economically also increased villagers' adoption likelihood. These improvements boosted villagers' sense of pride, which, in a virtuous cycle, further encouraged participation in improving the community. Residents' fears were reduced through local social interactions which increased knowledge, such as village-wide technology demonstrations, conversations with local adopters, and town hall discussions with village leaders. However, --- the PVPA projects and skepticism about when or if they would receive promised government subsidies prevented many from adopting. These findings provide valuable implications for policymakers in China and other developing countries who wish to encourage renewable energy adoption after the pandemic.

Production of SARS-CoV-2 virus-like particles in insect cells (preprint)

Coronavirus disease (COVID-19) causes a serious threat to human health. To production of SARS-COV-2 virus-like particles (VLPs) in insect cells for vaccine development and scientific research. The E, M and S genes were cloned into multiple cloning sites of the new triple expression plasmid with one p10 promoter, two pPH promoters and three multiple cloning sites. The plasmid was transformed into DH10 BacTM Escherichia coli competent cells to obtain recombinant bacmid. Then the recombinant bacmid was transfected in ExpiSf9 insect cells to generate recombinant baculovirus. After ExpiSf9 infected with the recombinant baculovirus, the E, M, and S protein co-expressed in insect cells. Finally, SARS-CoV-2 VLPs were self-assembled in insect cells after infection. The morphology and the size of SARS-CoV-2 VLPs are similar to the native virions.

Effects of Diabetes and Blood Glucose on COVID-19 Mortality: A Retrospective Observational Study (preprint)

OBJECTIVE To investigate the association of diabetes and blood glucose on mortality of patients with Coronavirus disease 2019 (COVID-19). RESEARCH DESIGN AND METHODS This is a retrospective observational study of all patients with COVID-19 admitted to Huo-Shen-Shan Hospital, Wuhan, China. The hospital was built only for treating COVID-19 and opened on February 5, 2020. The primary endpoint is all-cause mortality during hospitalization. RESULTS Among 2877 hospitalized patients, 15.5% (387/2877) had a history of diabetes and 1.9% (56/2877) died in hospital. After adjustment for confounders, patients with diabetes had a 2-fold increase in the hazard of mortality as compared to patients without diabetes (adjusted HR 2.11, 95%CI: 1.16-3.83, P=0.014). The glucose above 4mmol/L was significantly associated with subsequent mortality on COVID-19(adjusted HR 1.17, 95%CI: 1.10-1.24, per 1mmol/L increase, P<0.001). CONCLUSIONS Diabetes and glucose were associated with increased mortality in patients with COVID-19. These data support that blood glucose should be properly controlled for possibly better survival outcomes in patients with COVID-19.

Network Representation Learning-Based Drug Mechanism Discovery and Anti-Inflammatory Response Against COVID-19 (preprint)

Recent studies have been demonstrated that the excessive inflammatory response is an important factor of death in COVID-19 patients. In this study, we proposed a network representation learning-based methodology, termed AIdrug2cov, to discover drug mechanism and anti-inflammatory response for patients with COVID-19. This work explores the multi-hub characteristic of a heterogeneous drug network integrating 8 unique networks. Inspired by the multi-hub characteristic, we design three billion special meta paths to train a deep representation model for learning low-dimensional vectors that integrate long-range structure dependency and complex semantic relation among network nodes. Using the representation vectors, AIdrug2cov identifies 40 potential targets and 22 high-confidence drugs that bind to tumor necrosis factor(TNF)-α or interleukin(IL)-6 to prevent excessive inflammatory responses in COVID-19 patients. Finally, we analyze mechanisms of action based on PubMed publications and ongoing clinical trials, and explore the possible binding modes between the new predicted drugs and targets via docking program. In addition, the results in 5 pharmacological application suggested that AIdrug2cov significantly outperforms 5 other state-of-the-art network representation approaches, future demonstrating the availability of AIdrug2cov in drug development field. In summary, AIdrug2cov is practically useful for accelerating COVID-19 therapeutic development. The source code and data can be downloaded from https://github.com/pengsl-lab/AIdrug2cov.git.

Vegetable production under COVID-19 pandemic in China: an analysis based on the data of 526 households. (Special Focus: Impacts of COVID-19 on agriculture and rural poverty in China.)

The COVID-19 pandemic had an enormous impact on the vegetable supply chain in China. Effective evaluation of the pandemic's influences on vegetable production is vital for policy settings to enhance the security of vegetable supply. Based on first-hand data from 526 households, we explored regional differences in different types of loss and potential factors affecting the severity farmer households suffered during the pandemic. The results underline that sales contraction and price volatility in the context of interruption of supply chain dominate the total losses during the pandemic. Such losses differ across provinces and are more substantial in provinces with stricter confinement measures. Farmer households' participation in local market and modern marketing methods helps mitigate the negative effects of the COVID-19 shock, while labor hiring and facilities adoption in production widen the losses due to the shortage in the workforce. In the future, the vegetable industry practitioners and relevant government departments should work together to coordinate the development of short and long supply chains and strengthen the stability and security of the vegetable supply chain.