Targeting ARF4-mediated intracellular transport as broad-spectrum antivirals (preprint)

Host factors that regulate cellular vesicular trafficking also contribute to progeny virions’ destination, thus representing as potential antiviral drug targets. Here we demonstrate that genetic deletion of ARF4, a regulator in vesicle transport, repressed multiple pathogenic RNA viral infections including Zika virus (ZIKV), influenza A virus (IAV), SARS-CoV-2 and Vesicular Stomatitis virus (VSV). ARF4 activation was stimulated upon viral infection, and viral production was rescued when reconstituted with the activated ARF4, but not the inactivated mutants. Mechanically, ARF4 deletion obstructed viral normal translocation into Golgi complex, but led to mis-sorting for lysosomal degradation, consequently caused the blockage of final release. More importantly, ARF4 targeting peptides achieved significant therapeutic efficacy against ZIKV and IAV challenge in mice by blocking ARF4 activation. Hence, we clarify the critical role of ARF4 during viral infection, providing a broad-spectrum antiviral target and the basis for further pharmaceutical development.

Machine Learning-Based Prediction Model for Patients with Recurrent Staphylococcus aureus Bacteremia (preprint)

Objectives Staphylococcus aureus bacteremia (SAB) remains a significant contributor to both community-acquired and healthcare-associated bloodstream infections. SAB exhibits a high recurrence rate and mortality rate, leading to numerous clinical treatment challenges. Particularly, since the outbreak of COVID-19, there has been a gradual increase in SAB patients, with a growing proportion of (Methicillin-resistant Staphylococcus aureus)MRSA infections. Therefore, we have constructed and validated a pediction model for recurrent Staphylococcus aureus bacteremia using machine learning. This model aids physicians in promptly assessing the condition and intervening proactively.Methods The patients data is sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database version 2.2. The patients were divided into training and testing datasets using a 7:3 random sampling ratio. The process of feature selection employed two methods: Recursive Feature Elimination (RFE) and Least Absolute Shrinkage and Selection Operator (LASSO). Prediction models were built using Extreme Gradient Boosting (XGBoost),Random Forest (RF),Logistic Regression (LR),Support Vector Machine (SVM),and Artificial Neural Network (ANN). Model validation encompassed Receiver Operating Characteristic (ROC) analysis and Decision Curve Analysis (DCA). We utilized SHAP (SHapley Additive exPlanations) values to demonstrate the significance of each feature.Results After screening, MRSA, PTT, RBC, RDW, Neutrophils_abs, Sodium, Calcium, Vancomycin concentration, MCHC, MCV, and Prognostic Nutritional Index(PNI) were selected as features for constructing the model. Through combined evaluation using ROC and DCA analyses, XGBoost demonstrated the best predictive performance, achieving an AUC value of 0.76 (95% CI: 0.66–0.85). Building a website based on the Xgboost model.The SHAP plot depicted the importance of each feature within the model.Conclusions The adoption of XGBoost for model development holds widespread acceptance in the medical domain. The prediction model for recurrent Staphylococcus aureus bacteremia readmission, developed by our team, aids physicians in timely diagnosis and treatment of patients.

Deep spatial proteomic exploration of severe COVID-19-related pulmonary injury in post-mortem specimens (preprint)

The lung, as a primary target of SARS-CoV-2, exhibits heterogeneous microenvironment accompanied by various histopathological changes following virus infection. However, comprehensive insight into the protein basis of COVID-19-related pulmonary injury with spatial resolution is currently deficient. Here, we generated a region-resolved quantitative proteomic atlas of seven major pathological structures within the lungs of COVID-19 victims by integrating histological examination, laser microdissection, and ultrasensitive proteomic technologies. Over 10,000 proteins were quantified across 71 dissected FFPE post-mortem specimens. By comparison with control samples, we identified a spectrum of COVID-19-induced protein and pathway dysregulations in alveolar epithelium, bronchial epithelium, and pulmonary blood vessels, providing evidence for the proliferation of transitional-state pneumocytes. Additionally, we profiled the region-specific proteomes of hallmark COVID-19 pulmonary injuries, including bronchiole mucus plug, pulmonary fibrosis, airspace inflammation, and hyperplastic alveolar type 2 cells. Bioinformatic analysis revealed the enrichment of cell-type and functional markers in these regions (e.g. enriched TGFBI in fibrotic region). Furthermore, we identified the up-regulation of proteins associated with viral entry, host restriction, and inflammatory response in COVID-19 lungs, such as FURIN and HGF. Collectively, this study provides spatial proteomic insights for understanding COVID-19-caused pulmonary injury, and may serve as a valuable reference for improving therapeutic intervention for severe pneumonia.

Inactivated COVID-19 Vaccination did not affect In vitro fertilization (IVF) / Intra-Cytoplasmic Sperm Injection (ICSI) cycle outcomes (preprint)

Background: The objective of this study is to evaluate the impact of COVID-19 inactivated vaccine administration on the outcomes of in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) cycles in infertile couples in China. Methods: We collected data from the CYART prospective cohort, which included couples undergoing IVF treatment from January 2021 to September 2022 at Sichuan Jinxin Xinan Women & Children's Hospital. Based on whether they received vaccination before ovarian stimulation, the couples were divided into the vaccination group and the non-vaccination group. We compared the laboratory parameters and pregnancy outcomes between the two groups. Findings: After performing propensity score matching (PSM), the analysis demonstrated similar clinical pregnancy rates, biochemical pregnancy and ongoing pregnancy rates between vaccinated and unvaccinated women. No significant disparities were found in terms of embryo development and laboratory parameters among the groups. Moreover, male vaccination had no impact on patient performance or pregnancy outcomes in assisted reproductive technology treatments. Additionally, there were no significant differences observed in the effects of vaccination on embryo development and pregnancy outcomes among couples undergoing ART. Interpretation: The findings suggest that COVID-19 vaccination did not have a significant effect on patients undergoing IVF/ICSI with fresh embryo transfer. Therefore, it is recommended that couples should receive COVID-19 vaccination as scheduled to help mitigate the COVID-19 pandemic.

Fake News Detection and Behavioral Analysis: Case of COVID-19 (preprint)

While the world has been combating COVID-19 for over three years, an ongoing "Infodemic" due to the spread of fake news regarding the pandemic has also been a global issue. The existence of the fake news impact different aspect of our daily lives, including politics, public health, economic activities, etc. Readers could mistake fake news for real news, and consequently have less access to authentic information. This phenomenon will likely cause confusion of citizens and conflicts in society. Currently, there are major challenges in fake news research. It is challenging to accurately identify fake news data in social media posts. In-time human identification is infeasible as the amount of the fake news data is overwhelming. Besides, topics discussed in fake news are hard to identify due to their similarity to real news. The goal of this paper is to identify fake news on social media to help stop the spread. We present Deep Learning approaches and an ensemble approach for fake news detection. Our detection models achieved higher accuracy than previous studies. The ensemble approach further improved the detection performance. We discovered feature differences between fake news and real news items. When we added them into the sentence embeddings, we found that they affected the model performance. We applied a hybrid method and built models for recognizing topics from posts. We found half of the identified topics were overlapping in fake news and real news, which could increase confusion in the population.

Antibiotic resistomes in face-mask biofilm along an urban river: Multiple drivers and co-occurrence with human opportunistic pathogens.

Discarded face masks from the global COVID-19 pandemic have contributed significantly to plastic pollution in surface water, whereas their potential as a reservoir for aquatic pollutants is not well understood. Herein, we conducted a field experiment along a human-impacted urban river, investigating the variations of antibiotic resistance genes (ARGs), pathogens, and water-borne contaminants in commonly-used face masks. Results showed that high-biomass biofilms formed on face masks selectively enriched more ARGs than stone biofilm (0.08-0.22 vs 0.07-0.15 copies/16 S rRNA gene copies) from bulk water, which mainly due to unique microbial communities, enhanced horizontal gene transfer, and selective pressure of accumulated contaminants based on redundancy analysis and variation partitioning analysis. Several human opportunistic pathogens (e.g., Acinetobacter, Escherichia-Shigella, Bacillus, and Klebsiella), which are considered potential ARG carriers, were also greatly concentrated in face-mask biofilms, imposing a potential threat to aquatic ecological environment and human health. Moreover, wastewater treatment plant effluents, as an important source of pollutants to urban rivers, further aggravated the abundances of ARGs and opportunistic pathogens in face-mask biofilms. Our findings demonstrated that discarded face masks provide a hotspot for the proliferation and spread of ARGs and pathogens in urban water, highlighting the urgent requirement for implementing stricter regulations in face mask disposal.

Gammacoronavirus Avian Infectious Bronchitis Virus and Alphacoronavirus Porcine Epidemic Diarrhea Virus Exploit a Cell-Survival Strategy via Upregulation of cFOS to Promote Viral Replication.

Coronaviruses have evolved a variety of strategies to optimize cellular microenvironment for efficient replication. In this study, we report the induction of AP-1 transcription factors by coronavirus infection based on genome-wide analyses of differentially expressed genes in cells infected with avian coronavirus infectious bronchitis virus (IBV). Most members of the AP-1 transcription factors were subsequently found to be upregulated during the course of IBV and porcine epidemic diarrhea virus (PEDV) infection of cultured cells as well as in IBV-infected chicken embryos. Further characterization of the induction kinetics and functional roles of cFOS in IBV replication demonstrated that upregulation of cFOS at early to intermediate phases of IBV replication cycles suppresses IBV-induced apoptosis and promotes viral replication. Blockage of nuclear translocation of cFOS by peptide inhibitor NLSP suppressed IBV replication and apoptosis, ruling out the involvement of the cytoplasmic functions of cFOS in the replication of IBV. Furthermore, knockdown of ERK1/2 and inhibition of JNK and p38 kinase activities reduced cFOS upregulation and IBV replication. This study reveals an important function of cFOS in the regulation of coronavirus-induced apoptosis, facilitating viral replication.IMPORTANCE The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by a newly emerged zoonotic coronavirus (SARS-CoV-2), highlights the importance of coronaviruses as human and animal pathogens and our knowledge gaps in understanding the cellular mechanisms, especially mechanisms shared among human and animal coronaviruses, exploited by coronaviruses for optimal replication and enhanced pathogenicity. This study reveals that upregulation of cFOS, along with other AP-1 transcription factors, as a cell-survival strategy is such a mechanism utilized by coronaviruses during their replication cycles. Through induction and regulation of apoptosis of the infected cells at early to intermediate phases of the replication cycles, subtle but appreciable differences in coronavirus replication efficiency were observed when the expression levels of cFOS were manipulated in the infected cells. As the AP-1 transcription factors are multi-functional, further studies of their regulatory roles in proinflammatory responses may provide new insights into the pathogenesis and virus-host interactions during coronavirus infection.

The origin and evolution of emerged swine acute diarrhea syndrome coronavirus with zoonotic potential.

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly discovered alphacoronavirus with zoonotic potential that causes diarrhea and vomiting mainly in piglets. Having emerged suddenly in 2017, the prevailing opinion is that the virus originated from HKU2, an alphacoronavirus whose primary host is bats, and at some unknown point achieved interspecies transmission via some intermediate. Here, we further explore the evolutionary history and possible cross-species transmission event for SADS-CoV. Coevolutionary analysis demonstrated that HKU2 may have achieved host switch via SADS-related (SADSr)-CoV, which was isolated from the genus Rhinolophus in 2017. SADS-CoV, HKU2, and SADSr-CoV share similar codon usage patterns and showed a lower tendency to use CpG, which may reflect a method of immune escape. The analyses of virus-host coevolution and recombination support SADSr-CoV is the direct source of SADS-CoV that may have undergone recombination events during its formation. Structure-based spike glycoprotein variance analysis revealed a more nuanced evolutionary pathway to receptor recognition for host switch. We did not find a possible positive selection site, and the dN/dS of the S gene was only 0.29, which indicates that the current SADS-CoV is slowly evolving. These results provide new insights that may help predict future cross-species transmission, and possibly surveil future zoonotic outbreaks and associated public health emergencies.

Recent developments in the immunopathology of COVID-19.

There has been an important change in the clinical characteristics and immune profile of Coronavirus disease 2019 (COVID-19) patients during the pandemic thanks to the extensive vaccination programs. Here, we highlight recent studies on COVID-19, from the clinical and immunological characteristics to the protective and risk factors for severity and mortality of COVID-19. The efficacy of the COVID-19 vaccines and potential allergic reactions after administration are also discussed. The occurrence of new variants of concerns such as Omicron BA.2, BA.4, and BA.5 and the global administration of COVID-19 vaccines have changed the clinical scenario of COVID-19. Multisystem inflammatory syndrome in children (MIS-C) may cause severe and heterogeneous disease but with a lower mortality rate. Perturbations in immunity of T cells, B cells, and mast cells, as well as autoantibodies and metabolic reprogramming may contribute to the long-term symptoms of COVID-19. There is conflicting evidence about whether atopic diseases, such as allergic asthma and rhinitis, are associated with a lower susceptibility and better outcomes of COVID-19. At the beginning of pandemic, the European Academy of Allergy and Clinical Immunology (EAACI) developed guidelines that provided timely information for the management of allergic diseases and preventive measures to reduce transmission in the allergic clinics. The global distribution of COVID-19 vaccines and emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with reduced pathogenic potential dramatically decreased the morbidity, severity, and mortality of COVID-19. Nevertheless, breakthrough infection remains a challenge for disease control. Hypersensitivity reactions (HSR) to COVID-19 vaccines are low compared to other vaccines, and these were addressed in EAACI statements that provided indications for the management of allergic reactions, including anaphylaxis to COVID-19 vaccines. We have gained a depth knowledge and experience in the over 2 years since the start of the pandemic, and yet a full eradication of SARS-CoV-2 is not on the horizon. Novel strategies are warranted to prevent severe disease in high-risk groups, the development of MIS-C and long COVID-19.

Genetic characterization of SARS-CoV-2 from cross-border trucks and containers in Kashgar Prefecture, Xinjiang Uygur Autonomous Region, China

Kashgar is a prefecture in Xinjiang Uygur Autonomous Region. China. Kashgar Prefecture (KP) is a land-cargo port connecting China with central Asian countries and Europe. Frequent transportation of cargo has increased the risk of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) introduction into China, which has increased the pressure on coronavirus disease-2019 (COVID-19) prevention and control. In November 2020, an imported virus-induced COVID-19 outbreak occurred in KP. To investigate the genetic characterization of SARS-CoV-2 that contaminated the trucks and containers, and the potential of border rapid logistics system to serve as carriers for SARS-CoV-2 transmission, thirty-five SARS-CoV-2-positive nucleic-acid samples collected from KP cross-border trucks and containers from 6-10 November 2020 were subjected into SARS-CoV-2 genomic sequencing and comparative analyses. The results showed that the median (minimum to maximum) Ct value of ORF1ab was 37.64 (28.91-39.81) . and that of the N gene was 36.50 (26.35-39.30), and the median (minimum to maximum) of the reads mapping ratio to SARS-CoV-2 was 51.95% (0.86%-99.31%), which indicated low viral loads in these environmental samples. Eighteen of 35 samples had genomic coverage >70%. According to the Pango nomenclature, 18 SARS-CoV-2 sequences belonged to six lineages (B.1, B.I.1, B.1.9. B.1.1.220, B.1.153 and B.1.465), three of which (B.I. B.1.1 and 8.1.153) were found in case samples from the same period of four China-neighboring countries. Analyses of nucleotide mutations and phylogenetic trees showed that the genome sequences of SARS-CoV-2 collected from the same location were similar. Four of 18 sequences were in a sub-lineage with the representative strain of COVID-19 outbreak in KP, one of which had 1 or 2 differences in nucleotide mutation sites with the strain that caused the COVID-19 outbreak in KP, which indicated high homology in the viral genome. We showed that cross-border trucks and containers were contaminated by various genotypes of SARS-CoV-2 from other countries during the outbreak in KP. and in which contained the parental virus of the KP cases. These trucks and containers served as carriers for SARS-CoV-2 introduction from other countries to cause local transmission. Our results provide important references for COVID-19 prevention-and-control strategies in border ports and tracing of outbreak sources in China.

Transcriptomic analysis reveals crucial regulatory roles of immediate-early response genes and related signaling pathways in coronavirus infectious bronchitis virus infection.

Coronavirus infection of cells differentially regulates the expression of host genes and their related pathways. In this study, we present the transcriptomic profile of cells infected with gammacoronavirus infectious bronchitis virus (IBV). In IBV-infected human non-small cell lung carcinoma cells (H1299 cells), a total of 1162 differentially expressed genes (DEGs), including 984 upregulated and 178 downregulated genes, was identified. These DEGs were mainly enriched in MAPK and Wnt signaling pathways, and 5 out of the 10 top upregulated genes in all transcripts were immediate-early response genes (IEGs). In addition, the induction of 11 transcripts was validated in IBV-infected H1299 and Vero cells by RT-qPCR. The accuracy, reliability and genericity of the transcriptomic data were demonstrated by functional characterization of these IEGs in cells infected with different coronaviruses in our previous publications. This study provides a reliable transcriptomic profile of host genes and pathways regulated by coronavirus infection.

Recent developments in the immunopathology of COVID-19 (preprint)

There has been an important change in the clinical characteristics and immune profile of COVID-19 patients during the pandemic thanks to the extensive vaccination programs. Here, we highlight recent studies on COVID-19, from the clinical and immunological characteristics to the protective and risk factors for severity and mortality of COVID-19. The efficacy COVID-19 vaccines and potential allergic reactions after administration are also discussed. The occurrence of new variants of concerns such as Omicron BA.2, BA.4 and BA.5 and the global administration of COVID-19 vaccines have changed the clinical scenario of COVID-19. Multisystem inflammatory syndrome in children (MIS-C) has been identified as an important cause of death of children with COVID-19. Perturbations in immunity of T cells, B cells, and mast cells, as well as autoantibodies and metabolic reprogramming may contribute to the long-term symptoms of COVID-19. Atopic diseases, such as allergic asthma and rhinitis, have been shown to be associated with a lower susceptibility and better outcomes of COVID-19. At the beginning of pandemic, EAACI developed guidelines that provided timely information for the management of allergic diseases and preventive measures to reduce transmission in the allergic clinics. The global distribution of COVID-19 vaccines and emerging SARS-CoV-2 variants with reduced pathogenic potential dramatically decreased the morbidity, severity, and mortality of COVID-19. Nevertheless, breakthrough infection remains a challenge for disease control. Hypersensitivity reactions (HSR) to COVID-19 vaccines are low compared to other vaccines, and these were addressed in EAACI statements that provided indications for the management of allergic reactions, including anaphylaxis to COVID-19 vaccines. We have gained a depth knowledge and experience in the over 2 years since the start of the pandemic, and yet a full eradication of SARS-CoV-2 is not on the horizon. Novel strategies are warranted to prevent severe disease in high-risk groups, the development of MIS-C and long COVID.

Construction of SEIQCR epidemic model and its application in the evaluation of public health interventions on COVID-19 in Guangzhou. (Special Issue: Spatio-temporal dynamics analysis, risk assessment and emergency management for COVID-19 epidemic.) [Chinese]

Objective To develop a dynamic model of susceptible(S), exposed people in the latent period(E), infective(I), quarantined(Q), confirmed(C), and recovered(R)(SEIQCR)to evaluate the role of interventions and control the coronavirus disease 2019(COVID-19)epidemic in Guangzhou. Methods Based on the SEIR propagation dynamics model, the modules of "quarantined" and "confirmed" cases were added to establish a new SEIQCR model. The epidemic data in Guangzhou from Jan. 13 to Mar. 17, 2020 were fitted to obtain the parameters of SEIQCR model. Results The number of predicted cases based on these parameters was highly consistent with the actual incidence(R2=0.93). Time-dependent reproduction number declined rapidly with the implementation of first level response to COVID-19, indicating that local transmission was effectively controlled. Conclusion The preventative and control measures were effective. Local government should continue strictly implementing the isolation system and cut off the transmission channels to curb the transmission of COVID-19. The SEIQCR model can provide methodological reference for intervention assessment in other regions.

Unintended Consequences of COVID-19 Public Policy Responses on Renewable Energy Power: Evidence from OECD Countries in the EU (preprint)

Starting from 2020, governments around the world have continued to implement many types of public polices in response to the COVID-19 outbreaks. The dramatic public policies have substantially changed production and consumption activities, thereby temporarily lowing electricity use and greenhouse gas emissions. This study argues that the pandemic-induced public policies unintendedly slow down the transformation of renewable energy use in the EU, since the decline of greenhouse gas emissions led by the lockdowns helps the countries reduce the total emission temporarily. We employ a fixed-effect model to investigate the effects of different types of COVID-19 public policy responses on electricity production, consumption, and net import in 12 OECD countries in the EU, and mainly focus on the electricity production share from renewable energy source. Among several public policy responses, the stringent lockdown policies such as workplace closing, stay at home requirements, and restrictions on gathering size have negative and statistically significant impacts on electricity generation and consumption. Further, the countries with stringent lockdown policies are more likely to import electricity from other countries to mitigate the electricity shortage in their domestic markets. Importantly, we find the lockdown events have negative and statistically significant effects on the share of renewable energy use for the electricity production, while increase the share of fossil fuel use for the electricity production. In opposite, economic support policies such as income support, debt relief and economic stimulus programs can help reduce the share of fossil use for the electricity production and decrease the net import of electricity from other countries. Our results indicate that the public polices in response to the COVID-19 outbreaks have mixed effects on the transition to renewable energy power in the EU, suggesting that the current decline of greenhouse gas emissions comes from the reduction of electricity use led by the lockdown events instead of the adoption of renewable energy use and discourage the transformation of renewable energy source.

Multiple effects of “distance” on domestic tourism demand: A comparison before and after the emergence of COVID-19

This study investigated whether regional differences in economic, socio-psychological, and environmental distance affect tourists' destination choices. Taking Hangzhou, China, as a case, macro- and micro-level data were integrated to examine the effects of multi-dimensional distance on the city's tourism demand via a panel gravity model. All six distance variables were identified as influencing factors, but their effects varied in size and direction. Tourists' behavior has changed since COVID-19;as such, distance effects before and after its emergence were identified. Tourists were less sensitive to economic distance and price differences following the pandemic and tended to favor more culturally and climatically different destinations. The terror management theory was introduced to explain the shift in tourists' choices. Findings provide implications for destination management and marketing amid the pandemic.

Dual-Channel Effect of Job Insecurity on Knowledge Workers’ Innovative Behavior

Job insecurity reflects the desire and expectation of organizational managers for employees’ exhibition of innovative behavior. Ubiquitous and inevitable, it has gradually become a concern psychological problem for job survival and stability. As a key driver of innovation, employee innovation depends heavily on knowledge workers, who are best able to spot problems and identify and capture opportunities. Based upon the transactional theory of stress and coping (TTSC), this paper discusses the influencing mechanism of knowledge workers’ job insecurity and innovative behavior in enterprises, emphatically analyzes the mediating effects of two coping strategies, i.e., proactive work behavior and working withdrawal behavior, and verifies the moderating effect of organizational climate for innovation. With the data from 665 questionnaires of enterprise knowledge workers, this paper shows that job insecurity can influence knowledge workers’ innovative behavior either positively through proactive work behavior or negatively through working withdrawal behavior, thus forming a dual-channel effect model of influencing their innovative behavior, and that organizational climate for innovation has a moderating effect on the relationship between job insecurity and proactive work behavior/working withdrawal behavior. The organizational innovation climate played a moderating role between job insecurity and proactive work behavior and work withdrawal behavior and detected the value of the boundary where the organizational innovation climate played a mediating role.

Incidence and Severity of Aphid-transmitted Viruses and Horticultural Performance of Habanero Pepper (Capsicum chinense Jacq.) Breeding Lines in Benin

Habanero (Capsicum chinense Jacq.) is widely grown and consumed in West and Central African countries, and viral diseases represent an important production challenge. Diagnosis of the viral species affecting habanero productivity in Benin is limited, and understanding this will enable more efficient host resistance breeding. During 2019 and 2020, we characterized the incidence and severity of the viral diseases infecting nine promising habanero breeding lines and one commercial hybrid check under open field conditions in Benin. The horticultural performance, including yield and yield component traits of the entries, was determined during the 2 years of the experiment. A randomized complete block design was used with three replications, each with 24 plants. Data were recorded on days to 50% flowering and 50% fruit maturity, yield and on the yield components of fruit weight (g), fruit length (cm), and fruit width (mm), as well as disease incidence and severity. In total, 35 leaf samples were collected for viral diagnosis among habanero breeding lines. We found that Pepper veinal mottle virus (PVMV;Potyvirus) was the overwhelmingly predominant virus in our trials, with an 80% incidence;however, we found frequent coinfection of PVMV with Cucumber mosaic virus (CMV, Cucumovirus), Polerovirus, and, to a lesser extent, Chili veinal mottle virus (ChiVMV;Potyvirus). The mean disease incidence across all entries was 60%. AVPP1932 and PBC 2010 had the lowest disease incidence (35% and 43%, respectively), whereas AVPP1929 had the highest (86%) disease incidence. The F1 hybrid check Afadja had the overall highest yield, with 30 t·ha-1, followed by AVPP1932, with 19 t·ha-1, both in 2019. There was a negative correlation between disease incidence and total yield (r 5 20.44;P < 0.001), supporting previous studies indicating that viral diseases are major production constraints for habanero in West Africa. This study provides insight regarding the need to improve habanero for resistance to aphid-transmitted viruses and develop integrated pest management strategies to limit losses in Benin. [ FROM AUTHOR] Copyright of HortScience is the property of American Society for Horticultural Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Early Renal-Replacement Therapy May Reduce the All-Cause Mortality of Severe COVID-19: An Observational Cohort Study.

INTRODUCTION: The efficacy of renal-replacement treatment (RRT) remains to be validated in COVID-19. In this retrospective cohort study, we aimed to assess the efficacy of early initiation of RRT in intensive care unit (ICU) adults with severe COVID-19. METHODS: Fifty-eight adult patients in ICU with critically ill or severe COVID-19 with a tendency of critical illness were recruited from February 9, 2020, to March 30, 2020. Early RRT were determined by the ICU medical team based on boom in cytokines levels, increased organs injury/failure, and rapid aggravation of condition. All participants were followed up from the first day of ICU admission to March 30, 2020. The primary outcome was all-cause mortality in ICU. RESULTS: The mean age of the cohort was 68.4 ± 14.6 years, with 81.0% having at least one comorbidity before hospitalization. Twenty patients (34.5%) initiated early RRT after 24.1 ± 10.4 days from the onset and 6.4 ± 3.6 days from ICU admission. Thirty-four of 58 participants (58.6%) died during ICU follow-up. Univariate and multivariate Cox proportional-hazards model showed that early RRT was associated with a lower risk of all-cause mortality in ICU with an adjusted HR of 0.280 (95% CI: 0.106-0.738, p = 0.010). Sudden unexpected death (SUD) was remarkably reduced in the early RRT group, compared with the control group (0.2 vs. 2.9 per 100 person-day, p = 0.02). CONCLUSION: Early RRT can reduce the all-cause in-hospital mortality, especially SUD in patients with severe COVID-19, but not improve multi-organ impairment or increase the risk of AKI. Early initiation of RRT merits an optional strategy in critically ill patients with COVID-19 (ChiCTR2000030773).