Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19 in China (preprint)

The rapid development of new retail and the impact of COVID-19 have catalyzed the blowout growth of community group purchasing. The emergence of community group purchasing collection and delivery points (CGPCDPs) has become a new way to solve the "last mile" problem of new retail delivery. Based on the point of interest (POI) data of CGPCDPs of Nansha District, Guangzhou City, this study uses text analysis, spatial analysis, model analysis, and other methods to analyze the operation mode, spatial distribution, and influencing factors of CGPCDPs. The conclusions are as follows: CGPCDPs initiators are mainly shopkeepers. They depend mainly on wholesale and retail shops. Service targets are mainly urban and rural communities, followed by industrial areas. The distribution of CGPCDPs has apparent spatial differentiation. At the macro scale, it shows the characteristics of "central agglomeration and peripheral dispersion". It is distributed along the "northwest-southeast" direction and presents a "dual-core multi-center" pattern. At meso-micro scale, different built environments in developed areas of cities, villages in the city (ChengZhongCun) and rural areas show distinct distribution patterns. The MGWR regression model has a better fitting effect than OLS and GWR. The main influencing factors are population density, construction land, house price, supporting place, residence density, urban community, and road proximity.

Sustained mTOR inhibition with sirolimus improves respiratory outcomes in LAM patients with COVID-19 (preprint)

Background Lymphangioleiomyomatosis (LAM) is a rare lung disease that predominantly affects women and can lead to severe respiratory complications. The impact of COVID-19 on LAM patients, particularly regarding the use of mammalian target of rapamycin (mTOR) inhibitors, remains poorly understood. This study investigates the clinical outcomes of LAM patients with COVID-19 and evaluates the role of sustained mTOR inhibition in respiratory outcomes.Results Our cohort included 186 LAM patients with COVID-19. Prior to infection, 72.6% were on mTOR inhibitors, with 29.6% discontinuing therapy due to infection. The hospitalization rate was 1.1%, with no reported need for invasive ventilation or fatalities. Patients with FEV1 less than 70% predicted had a higher risk of dyspnea exacerbation and supplemental oxygen requirement. Continuation of mTOR inhibitor therapy was associated with a lower risk of SpO2 decline, especially among patients with impaired lung function. Vaccination status did not significantly affect the prognosis.Conclusions LAM patients with COVID-19 showed a low rate of severe illness and mortality, with impaired lung function correlating with worse respiratory outcomes. Continued mTOR inhibitor therapy during COVID-19 infection may improve respiratory outcomes, suggesting the importance of maintaining treatment during viral pandemics.

Effects of COVID-19 infection in patients with autoimmune pulmonary alveolar proteinosis: a single-center study (preprint)

Background:Autoimmune pulmonary alveolar proteinosis (aPAP) is a rare interstitial lung disease. COVID-19 is associated with worse prognosis in previous lung diseases patients. But the prognosis of aPAP patients after infection with COVID-19 is unclear. In December 2022, China experienced a large-scale outbreak of Omicron variant of the SARS-CoV-2. In this study, we aim to explore the clinical outcomes of aPAP patients infected with COVID-19. Results: A total of 39 aPAP patients were included in this study. 30.77% patients had a decrease in oxygen saturation after COVID-19 infection. We compared the two groups of patients with or without decreased oxygen saturation after COVID-19 infection and found that patients who had previous oxygen therapy (decreased oxygen saturation vs. non decreased oxygen saturation: 6/12 vs. 4/27, P = 0.043), with lower baseline arterial oxygen partial pressure (74.50 ± 13.61 mmHg vs. 86.49 ± 11.92 mmHg, P = 0.009), lower baseline DLCO/VA% [77.0 (74.3, 93.6) % vs. 89.5 (78.2, 97.4) %, P = 0.036], shorter baseline 6MWD [464 (406, 538) m vs. 532 (470, 575) m, P = 0.028], higher disease severity score (P = 0.017), were more likely to have decreased oxygen saturation after COVID-19 infection. Conclusion: aPAP patients with poor baseline respiration have a higher probability of hypoxia after COVID-19 infection, but fatal events were rare.

Does ambient air quality standard contribute to green innovation of enterprises in China? Implications for environmental protection and public health

In the post-COVID-19 era, environmental pollution has been a serious threat to public health. Enterprises are in urgent need of enhancing green technology innovation as the main source of pollutant emissions, and it is necessary for governments to support green innovation of enterprises to reduce pollutant emissions and promote public health. In this context, this paper investigates whether the Ambient Air Quality Standard (AAQS) implemented in 2012 in China contributes to green innovation of enterprises, to provide implications for environmental protection and public health. By using panel data of Chinese A-share listed companies from 2008 to 2020, this study adopts the difference-in-difference model to analyze the policy impact of environmental regulation on green innovation of enterprises and its internal mechanism. The results show that AAQS has significantly improved the green innovation of enterprises. Furthermore, AAQS affects the green innovation of enterprises by virtue of two mechanism paths: compliance cost effect and innovation offset effect. On the one hand, AAQS leads to an increase in production costs of enterprises, thus inhibiting green innovation activities of enterprises. On the other hand, AAQS encourages enterprises to increase R&D investment in green technology, thus enhancing their green innovation. In addition, the impact of AAQS on firms' green innovation has heterogeneous characteristics. Our findings not only enrich the studies of environmental regulation and green innovation of enterprises but also provide policymakers in China and other developing countries with implications for environmental protection and public health improvement.

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.

Gut microbial GABAergic signaling imprints alveolar macrophages and pulmonary response to viral infection associated with psychological stress (preprint)

Background: Epidemiological evidences reveal that populations with psychological stress have an increased likelihood of respiratory viral infection involving influenza A virus (IAV) and SARS-CoV-2, but the mechanism remains elusive. Results By exploiting a chronic restraint stress (CRS) mouse model, we demonstrated that psychiatric stress substantially increased hosts’ vulnerability to viral pneumonia, concurrent with deregulated alveolar macrophages (AMs) and disturbed gut microbiome. The central importance of gut microbiome in stress-exacerbated viral pneumonia was confirmed by microbiome depletion and gut microbiome transplantation. In particular, stress exposure induced a decline in Lactobacillaceae abundance and hence γ-aminobutyric acid (GABA) level in mice. Microbial-derived GABA proved to be released in the peripheral and sensed by AMs via GABA A R, leading to enhanced mitochondrial metabolism and α-ketoglutarate (αKG) generation. The metabolic intermediator in turn served as the cofactor for the epigenetic regulator Tet2 to catalyze DNA hydroxymethylation, and promoted PPARγ-centered gene program underpinning survival, self-renewing, and immunoregulation of AMs. We thus uncover an unappreciated GABA/Tet2/PPARγ regulatory circuitry that was initiated by gut microbiome to instruct distant immune cells through a metabolic-epigenetic program. Accordingly, reconstitution with GABA-producing probiotics, or adoptive transferring of GABA-conditioned AMs, or resumption of pulmonary αKG level remarkably improved AMs homeostasis and alleviated severe pneumonia in stressed mice. Conclusions Together, our study identifies a microbiome-derived tonic signaling that is tuned by mental health status to imprint resident immune cells and defensive response in lungs. The findings are particularly significant for the subpopulation with psychiatric stress to combat critical respiratory viral infection.

Fertility Intention Among Chinese Reproductive Couples During the COVID-19 Outbreak: A Cross-Sectional Study.

A decline in the fertility rate has been observed worldwide, which hampers social development severely. Given the impacts of COVID-19 on individuals and society, it is of great significance to investigate the fertility intention of reproductive couples under COVID-19. The convenience sampling method was used to obtain our study sample. The self-administered questionnaire included the following components: sociodemographic characteristics (age, residence, education, occupation, characteristics of the couples, and annual household income), reproductive history (parity, number of children, child gender, and duration of preparing pregnancy), and attitudes toward COVID-19, was distributed online via an applet of WeChat. The results showed that among 4,133 valid questionnaires, 1,091 had fertility intention before COVID-19, whereas 3,042 did not, indicating a fertility intention rate of 26.4% among participating couples. Of the 1,091 couples who had fertility intention before COVID-19, 520 (47.7%) were affected by the outbreak, whereas 571 (52.3%) were not. By multivariable logistic regression analysis, we further found that couples living in Hubei Province, the epicenter in China (OR 2.20, 95% CI 1.35-3.60), and couples who prepared for pregnancy longer before COVID-19 (OR 1.19, 95% CI 1.06-1.33) were more likely to change their fertility intention under the pandemic. In addition, most of the participants reported their fertility intention was affected by the inconvenience of seeking medical service under COVID-19. Therefore, more forms of medical services to provide convenience for patients might be effective ways to reverse the declined fertility intention rate in facing COVID-19.

Behavioral Intention and Its Predictors toward COVID-19 Booster Vaccination among Chinese Parents: Applying Two Behavioral Theories

The booster vaccination of COVID-19 is being implemented in most parts of the world. This study used behavioral psychology to investigate the predictors of parents' intentions regarding the COVID-19 booster vaccination for their children. This is a cross-sectional study with a self-designed questionnaire based on two behavioral theories-protective motivation theory (PMT) and theory of planned behavior (TPB). A stratified multi-stage sampling procedure was conducted in Nanjing, China, and multivariable regression analyses were applied to examine the parents' intentions. The intention rate was 87.3%. The response efficacy (ORa = 2.238, 95% CI: 1.360–3.682) and response cost (ORa = 0.484, 95% CI: 0.319–0.732) in the PMT, were significant psychological predictors of parents' intentions, and so were the attitude (ORa = 2.619, 95% CI: 1.480–4.636) and behavioral control (ORa = 3.743, 95% CI: 2.165–6.471) in the TPB. The findings of crucial independent predictors in the PMT and TPB constructs inform the evidence-based formulation and implementation of strategies for booster vaccination in children.

Emergency Department Crowding is Harder to Solve: The Impact of COVID-19 of Longer Length of Stay (preprint)

Objectives: To determine the impact of the Coronavirus disease-2019 (COVID-19) pandemic on the length of stay (LOS) and prognosis of patients in the emergency department (ED). Methods A retrospective review of case data of patients in the ED during the early stages of the COVID-19 pandemic in the First Affiliated Hospital of Soochow University (January 15, 2020– January 14, 2021) was performed and compared with that during the pre-COVID-19 period (January 15, 2019 – January 14, 2020). Patient information including age, sex, length of stay, and death was collected. Wilcoxon Rank sum test was utilized to compare the difference in LOS between the two cohorts. Chi-Squared test was utilized to analyze the prognosis of patients. The LOS and prognosis in different departments (emergency internal medicine, emergency surgery, emergency neurology, and other departments) were further analyzed. Results Of the total 8278 patients, 4159 (50.24%) were ordered in the COVID-19 pandemic group and 4119 (49.76%) were ordered in the pre-COVID-19 group. The length of stay prolongs significantly in the COVID-19 group compared with that in the pre-COVID-19 group(13h vs 9.8h; p < 0.001). There was no significant difference in mortality between the two cohorts (4.8% VS 5.3%; p=0.341). Conclusion The COVID-19 pandemic was associated with a significant increase in the length of stay, which may lead to emergency department crowding. And the influence of the COVID-19 pandemic on patients in different emergency departments is different. There is no significant impact on the LOS of emergency neuropathy. Across departments, COVID-19 didn’t have a significant impact on the prognosis of ED patients.

IFP35 as a promising biomarker and therapeutic target for the syndromes induced by SARS-CoV-2 or influenza virus.

Previous studies have shown that the high mortality caused by viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus primarily results from complications of a cytokine storm. Therefore, it is critical to identify the key factors participating in the cytokine storm. Here we demonstrate that interferon-induced protein 35 (IFP35) plays an important role in the cytokine storm induced by SARS-CoV-2 and influenza virus infection. We find that the levels of serum IFP35 in individuals with SARS-CoV-2 correlates with severity of the syndrome. Using mouse model and cell assays, we show that IFP35 is released by lung epithelial cells and macrophages after SARS-CoV-2 or influenza virus infection. In addition, we show that administration of neutralizing antibodies against IFP35 considerably reduces lung injury and, thus, the mortality rate of mice exposed to viral infection. Our findings suggest that IFP35 serves as a biomarker and as a therapeutic target in virus-induced syndromes.

Highly lethal Vibrio parahaemolyticus strains cause acute mortality in Penaeus vannamei post-larvae

A new lethal disease, commonly known as the "glass post-larval disease", occurs in many shrimp hatcheries in China since late 2019. This disease affects 6– 12-day-old post-larvae of Penaeus vannamei and leads to over 90% mortality within 24– 48 h after the first sign of abnormal individuals. The typical gross clinical signs include an empty digestive tract and pale or colorless hepatopancreas, which result in a translucent look of diseased animals. Here, by applying per os infection study, we show that the "glass post-larval disease" is caused by an infectious agent. Three highly lethal Vibrio parahaemolyticus strains, vp-HL-201910, vp-HL-202005, and vp-HL-202006 are isolated from naturally infected post-larvae collected from different farms. They are very closely related to each other since their 16S rRNA and thermolabile hemolysin genes are identical. These strains reproduce the same pathology in experimental animals and can be successfully re-isolated. The normal structure of hepatopancreas tubule and midgut epithelium is seriously damaged by the representative strain vp-HL-202005. A comparison study suggests that vp-HL-202005 is ~1000 times more virulent than the strain causing acute hepatopancreatic necrosis disease. Moreover, the bacteria-free sonicate supernatant of vp-HL-202005 induces the same symptom in post-larvae shrimp, which strongly suggests that the pathology is caused by a bacterial toxin(s). These findings demonstrate that the "glass post-larvae disease" is caused by a specific type of highly lethal V. parahaemolyticus. Thus, we rename it "highly lethal Vibrio disease" (HLVD). HLVD is a serious threat to shrimp aquaculture. • The "glass post-larvae disease" is caused by a highly lethal Vibrio parahaemolyticus. • The HLVD strain causes severe lesions in the hepatopancreas and midgut. • The pathology of HLVD is very likely caused by a bacteria toxin(s). • The HLVD strain is much more virulent than the AHPND strain. • HLVD is a serious threat to shrimp aquaculture. [ FROM AUTHOR] Copyright of Aquaculture is the property of Elsevier B.V. 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.)

Bioinformatic Identification of Hub Genes and Biological Pathways for Sepsis-Associated Acute Lung Injury (preprint)

Background: Sepsis-associated acute lung injury (ALI) is a potentially lethal complication associated with a poor prognosis and high mortality worldwide, especially in the outbreak of COVID-19. However, the fundamental mechanisms of this complication were still not fully elucidated. Thus, we conducted this study to identify hub genes and biological pathways of sepsis-associated ALI, mainly focus on two pathways of LPS and HMGB1. Methods: : Gene expression profile GSE3037 were downloaded from Gene Expression Omnibus (GEO) database, including 8 patients with sepsis-induced acute lung injury, with 8 unstimulated blood neutrophils, 8 LPS- induced neutrophils and 8 HMGB1-induced neutrophils. Differentially expressed genes (DEGs) identifications, Gene Ontology (GO) function analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis, Gene Set Enrichment Analysis (GSEA) and protein-protein interaction (PPI) network constructions were performed to obtain hub genes and relevant biological pathways. Results: : We identified 534 and 317 DEGs for LPS- and HMGB1-induced ALI, respectively. The biological pathways involved in LPS- and HMGB1-induced ALI were also identified accordingly. By PPI network analysis, we found that ten hub genes for LPS-induced ALI (CXCL8, TNF, IL6, IL1B, ICAM1, CXCL1, CXCL2, IL1A, IL1RN and CXCL3) and another ten hub genes for HMGB1-induced ALI (CCL20, CXCL2, CXCL1, CCL4, CXCL3, CXCL9, CCL21, CXCR6, KNG1 and SST). Furthermore, by combining analysis, the results revealed that genes of TNF, CCL20, IL1B, NFKBIA, CCL4, PTGS2, TNFAIP3, CXCL2, CXCL1 and CXCL3 were potential biomarkers for sepsis-associated ALI. Conclusions: : Our study revealed that ten hub genes associated with sepsis-induced ALI were TNF, CCL20, IL1B, NFKBIA, CCL4, PTGS2, TNFAIP3, CXCL2, CXCL1 and CXCL3, which may serve as genetic biomarkers and be further verified in prospective experimental trials.

Interactomes of SARS-CoV-2 and human coronaviruses reveal host factors potentially affecting pathogenesis.

Host-virus protein-protein interactions play key roles in the life cycle of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We conducted a comprehensive interactome study between the virus and host cells using tandem affinity purification and proximity-labeling strategies and identified 437 human proteins as the high-confidence interacting proteins. Further characterization of these interactions and comparison to other large-scale study of cellular responses to SARS-CoV-2 infection elucidated how distinct SARS-CoV-2 viral proteins participate in its life cycle. With these data mining, we discovered potential drug targets for the treatment of COVID-19. The interactomes of two key SARS-CoV-2-encoded viral proteins, NSP1 and N, were compared with the interactomes of their counterparts in other human coronaviruses. These comparisons not only revealed common host pathways these viruses manipulate for their survival, but also showed divergent protein-protein interactions that may explain differences in disease pathology. This comprehensive interactome of SARS-CoV-2 provides valuable resources for the understanding and treating of this disease.

Cell-Free Synthetic Biosensors Based on CRISPR/Cas Mediated Cascade Signal Amplification for Precise RNA Detection (preprint)

Synthetic biology has been harnessed to create new diagnostic technologies. However, most synthetic biosensors involve error-prone amplification steps and limitations of accuracy in RNA detection. Here, we report a cell-free synthetic biosensing platform, termed as SHARK ( S ynthetic Enzyme S h ift RNA Signal A mplifier R elated Cas13a K nockdown Reaction), to efficiently and accurately amplify RNA signal by leveraging the collateral cleavage of activated Cas13a to regulate cell-free enzyme synthesis. Based on cascade amplification and customized enzyme output, SHARK behaves a broad compatibility in different scenarios. Using a personal glucose meter, we detected 50 copies/μl SARS-CoV-2 on a SHARK-loaded paper. In addition, when combined with machine learning, SHARK can perform bio-computations and thus provide miRNA patterns for cancer diagnosis and staging. SHARK shows characteristics of precise recognition, cascade amplification and customizable signal outputting in one pot comparisons with established assays based on 64 clinical samples, presenting great potential in developing next-generation RNA detection technology.

HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study.

Protein-nucleic acid interactions play essential roles in many biological processes, such as transcription, replication and translation. In protein-nucleic acid interfaces, hotspot residues contribute the majority of binding affinity toward molecular recognition. Hotspot residues are commonly regarded as potential binding sites for compound molecules in drug design projects. The dynamic property is a considerable factor that affects the binding of ligands. Computational approaches have been developed to expedite the prediction of hotspot residues on protein-nucleic acid interfaces. However, existing approaches overlook hotspot dynamics, despite their essential role in protein function. Here, we report a web server named Hotspots In silico Scanning on Nucleic Acid and Protein Interface (HISNAPI) to analyze hotspot residue dynamics by integrating molecular dynamics simulation and one-step free energy perturbation. HISNAPI is capable of not only predicting the hotspot residues in protein-nucleic acid interfaces but also providing insights into their intensity and correlation of dynamic motion. Protein dynamics have been recognized as a vital factor that has an effect on the interaction specificity and affinity of the binding partners. We applied HISNAPI to the case of SARS-CoV-2 RNA-dependent RNA polymerase, a vital target of the antiviral drug for the treatment of coronavirus disease 2019. We identified the hotspot residues and characterized their dynamic behaviors, which might provide insight into the target site for antiviral drug design. The web server is freely available via a user-friendly web interface at http://chemyang.ccnu.edu.cn/ccb/server/HISNAPI/ and http://agroda.gzu.edu.cn:9999/ccb/server/HISNAPI/.

Effect of COVID-19 on Epidemiological Characteristics of Road Traffic Injuries in Suzhou:A Retrospective Study (preprint)

Background: To present the new trends in epidemiology of road traffic injuries (RTIs) in Suzhou under the impact of Coronavirus disease 2019 (COVID-19) and control measures.Methods: Pre-hospital care records of RTIs in January-May 2020 and January-May 2019 were collected from the database of Suzhou emergency center, Jiangsu, China， and relevant clinical data were extracted for a retrospective study. RTIs in 2020 and 2019 were defined as observation group and control group respectively.Results: There were 7288 RTIs in the observation group, accounting for 82.17% of the control group. The number of RTIs per month from January to May in the observation group were 79.72%, 47.69%, 79.30%, 85.72% and 99.39% of the control group, respectively. Subgroup analysis showed that the number and composition ratio of electric bicycle related RTIs in the observation group were significantly higher than those in the control group (2641, 36.24% vs 2380, 26.84%, P<0.001). We observed a statistically significant increase in proportion of RTIs with consciousness disorder in the observation group compared to the control group (7.22% vs 6.13%, P = 0.006).Conclusions: Under the impact of COVID-19, the total number of RTIs in Suzhou from January to May 2020 decreased obviously. Nevertheless, there was an obvious rise in electric bicycle related RTIs, and the proportion of RTIs with consciousness disorder also increased. It is necessary for electric bicycle riders to wear helmets.

Clinical medication response under new major infectious disease: off-label use and compassionate use / 药学实践杂志

At present, there are no specific targeted drugs for the treatment of pneumonia (COVID-19) caused by the novel coronavirus (SARS-CoV-2). Interferon, lopinavir/ritonavir, ribavirin, chloroquine phosphate were chosen as off-label use, and remdesivir was chosen as compassionate use. This paper reviewed the behavior of the two medication response to the new major infectious disease.

A 3D Structural Interactome to Explore the Impact of Evolutionary Divergence, Population Variation, and Small-molecule Drugs on SARS-CoV-2-Human Protein-Protein Interactions (preprint)

The recent COVID-19 pandemic has sparked a global public health crisis. Vital to the development of informed treatments for this disease is a comprehensive understanding of the molecular interactions involved in disease pathology. One lens through which we can better understand this pathology is through the network of protein-protein interactions between its viral agent, SARS-CoV-2, and its human host. For instance, increased infectivity of SARS-CoV-2 compared to SARS-CoV can be explained by rapid evolution along the interface between the Spike protein and its human receptor (ACE2) leading to increased binding affinity. Sequence divergences that modulate other protein-protein interactions may further explain differences in transmission and virulence in this novel coronavirus. To facilitate these comparisons, we combined homology-based structural modeling with the ECLAIR pipeline for interface prediction at residue resolution, and molecular docking with PyRosetta. This enabled us to compile a novel 3D structural interactome meta-analysis for the published interactome network between SARS-CoV-2 and human. This resource includes docked structures for all interactions with protein structures, enrichment analysis of variation along interfaces, predicted {Delta}{Delta}G between SARS-CoV and SARS-CoV-2 variants for each interaction, predicted impact of natural human population variation on binding affinity, and a further prioritized set of drug repurposing candidates predicted to overlap with protein interfaces. All predictions are available online for easy access and are continually updated when new interactions are published. NOTE: Some sections of this pre-print have been redacted to comply with current bioRxiv policy restricting the dissemination of purely in silico results predicting potential therapies for SARS-CoV-2 that have not undergone thorough peer-review. The results section titled 'Prioritization of Candidate Inhibitors of SARS-CoV-2-Human Interactions Through Binding Site Comparison,' Figure 4, Supplemental Table 9, and all links to our web resource have been removed. Blank headers left in place to preserve structure and item numbering. Our full manuscript will be published in an appropriate journal following peer-review.