Accelerating drug repurposing for COVID-19 treatment by modeling mechanisms of action using cell image features and machine learning.

The novel coronavirus disease, COVID-19, has rapidly spread worldwide. Developing methods to identify the therapeutic activity of drugs based on phenotypic data can improve the efficiency of drug development. Here, a state-of-the-art machine-learning method was used to identify drug mechanism of actions (MoAs) based on the cell image features of 1105 drugs in the  LINCS database. As the multi-dimensional features of cell images are affected by non-experimental factors, the characteristics of similar drugs vary considerably, and it is difficult to effectively identify the MoA of drugs as there is substantial noise. By applying the supervised information theoretic metric-learning (ITML) algorithm, a linear transformation made drugs with the same MoA aggregate. By clustering drugs to communities and performing enrichment analysis, we found that transferred image features were more conducive to the recognition of drug MoAs. Image features analysis showed that different features play important roles in identifying different drug functions. Drugs that significantly affect cell survival or proliferation, such as cyclin-dependent kinase inhibitors, were more likely to be enriched in communities, whereas other drugs might be decentralized. Chloroquine and clomiphene, which block the entry of virus, were clustered into the same community, indicating that similar MoA could be reflected by the cell image. Overall, the findings of the present study laid the foundation for the discovery of MoAs of new drugs, based on image data. In addition, it provided a new method of drug repurposing for COVID-19. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11571-021-09727-5.

Scalable Randomized Kernel Methods for Multiview Data Integration and Prediction (preprint)

We develop scalable randomized kernel methods for jointly associating data from multiple sources and simultaneously predicting an outcome or classifying a unit into one of two or more classes. The proposed methods model nonlinear relationships in multiview data together with predicting a clinical outcome and are capable of identifying variables or groups of variables that best contribute to the relationships among the views. We use the idea that random Fourier bases can approximate shift-invariant kernel functions to construct nonlinear mappings of each view and we use these mappings and the outcome variable to learn view-independent low-dimensional representations. Through simulation studies, we show that the proposed methods outperform several other linear and nonlinear methods for multiview data integration. When the proposed methods were applied to gene expression, metabolomics, proteomics, and lipidomics data pertaining to COVID-19, we identified several molecular signatures forCOVID-19 status and severity. Results from our real data application and simulations with small sample sizes suggest that the proposed methods may be useful for small sample size problems. Availability: Our algorithms are implemented in Pytorch and interfaced in R and would be made available at: https://github.com/lasandrall/RandMVLearn.

Development of an ELISA Assay for the Determination of SARS-CoV-2 Protein Subunit Vaccine Antigen Content.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protein subunit vaccine is one of the mainstream technology platforms for the development of COVID-19 vaccines, and most R&D units use the receptor-binding domain (RBD) or spike (S) protein as the main target antigen. The complexity of vaccine design, sequence, and expression systems makes it urgent to establish common antigen assays to facilitate vaccine development. In this study, we report the development of a double-antibody sandwich enzyme-linked immunosorbent assay (ELISA) to determine the antigen content of SARS-CoV-2 protein subunit vaccines based on the United States Pharmacopeia <1220> and ICH (international conference on harmonization) Q14 and Q2 (R2) requirements. A monoclonal antibody (mAb), 20D8, was identified as the detection antibody based on its high RBD binding activity (EC50 = 8.4 ng/mL), broad-spectrum anti-variant neutralizing activity (EC50: 2.7−9.8 ng/mL for pseudovirus and EC50: 9.6−127 ng/mL for authentic virus), good in vivo protection, and a recognized linear RBD epitope (369−379 aa). A porcine anti-RBD polyclonal antibody was selected as the coating antibody. Assay performance met the requirements of the analytical target profile with an accuracy and precision of ≥90% and adequate specificity. Within the specification range of 70−143%, the method capability index was >0.96; the misjudgment probability was <0.39%. The method successfully detected SARS-CoV-2 protein subunit vaccine antigens (RBD or S protein sequences in Alpha, Beta, Gamma, or Delta variants) obtained from five different manufacturers. Thus, we present a new robust, reliable, and general method for measuring the antigenic content of SARS-CoV-2 protein subunit vaccines. In addition to currently marketed and emergency vaccines, it is suitable for vaccines in development containing antigens derived from pre-Omicron mutant strains.

Case report: Vaccine-induced immune thrombotic thrombocytopenia complicated by acute cerebral venous thrombosis and hemorrhage after AstraZeneca vaccines followed by Moderna COVID-19 vaccine booster and surgery

Vaccine-induced thrombotic thrombocytopenia (VITT) is a well-known complication of adenoviral vector COVID-19 vaccines including ChAdOx1 nCoV-19 (AstraZeneca) and Ad26. COV2.S (Janssen, Johnson & Johnson). To date, only a few cases of mRNA COVID-19 vaccine such as mRNA-1273 (Moderna) or BNT162b2 (Pfizer-BioNTech)-induced VITT have been reported. We report a case of VITT with acute cerebral venous thrombosis and hemorrhage after a booster of mRNA-1273 (Moderna) vaccine in a patient previously vaccinated with two doses of the AstraZeneca vaccine. A 42-year-old woman presented with sudden onset of weakness of the right upper limb with focal seizure. She had received two doses of AstraZeneca vaccines and a booster with Moderna vaccine 32 days before presentation. She had also undergone a laparoscopic myomectomy 12 days previously. Laboratory examinations revealed anemia (9.5 g/dl), thrombocytopenia (31 × 103/μl), and markedly elevated d-dimer (>20.0 mg/L;reference value < 0.5 mg/L). The initial brain computed tomography (CT) was normal, but a repeated scan 10 h later revealed hemorrhage at the left cerebrum. Before the results of the blood smear were received, on suspicion of thrombotic microangiopathy with thrombocytopenia and thrombosis, plasmapheresis and pulse steroid therapy were initiated, followed by intravenous immunoglobulin (1 g/kg/day for two consecutive days) due to refractory thrombocytopenia. VITT was confirmed by positive anti-PF4 antibody and both heparin-induced and PF4-induced platelet activation testing. Clinicians should be aware that mRNA-1273 Moderna, an mRNA-based vaccine, may be associated with VITT with catastrophic complications. Additionally, prior exposure to the AstraZeneca vaccine and surgical procedure could also have precipitated or aggravated autoimmune heparin-induced thrombocytopenia/VITT-like presentation.

Systematic optimization of host-directed therapeutic targets and preclinical validation of repositioned antiviral drugs.

Inhibition of host protein functions using established drugs produces a promising antiviral effect with excellent safety profiles, decreased incidence of resistant variants and favorable balance of costs and risks. Genomic methods have produced a large number of robust host factors, providing candidates for identification of antiviral drug targets. However, there is a lack of global perspectives and systematic prioritization of known virus-targeted host proteins (VTHPs) and drug targets. There is also a need for host-directed repositioned antivirals. Here, we integrated 6140 VTHPs and grouped viral infection modes from a new perspective of enriched pathways of VTHPs. Clarifying the superiority of nonessential membrane and hub VTHPs as potential ideal targets for repositioned antivirals, we proposed 543 candidate VTHPs. We then presented a large-scale drug-virus network (DVN) based on matching these VTHPs and drug targets. We predicted possible indications for 703 approved drugs against 35 viruses and explored their potential as broad-spectrum antivirals. In vitro and in vivo tests validated the efficacy of bosutinib, maraviroc and dextromethorphan against human herpesvirus 1 (HHV-1), hepatitis B virus (HBV) and influenza A virus (IAV). Their drug synergy with clinically used antivirals was evaluated and confirmed. The results proved that low-dose dextromethorphan is better than high-dose in both single and combined treatments. This study provides a comprehensive landscape and optimization strategy for druggable VTHPs, constructing an innovative and potent pipeline to discover novel antiviral host proteins and repositioned drugs, which may facilitate their delivery to clinical application in translational medicine to combat fatal and spreading viral infections.

Emergency Response, Influence and Lessons in the 2021 Compound Disaster in Henan Province of China.

Henan province, located in central China, suffered a heavy rainstorm and an outbreak of COVID-19 from the middle of July to the middle of August. We review and investigate the emergency response to these two events. The influence of the compound disaster on provincial economic operations, fixed assets, consumer goods, the logistics industry, high-tech manufacturing, and strategic emerging industries is analyzed in detail. Since the province's economic situation has been positive for a long time, the influence of the compound disaster was short-term. The countermeasures to the pandemic were efficient since they had previously been in practice at various times in 2020. However, in the face of unusual disasters such as the rainstorm, the gap between early warning and emergency response needs to be bridged, and the sources of relief funds should be diversified.

Rh-CXCL-12 Attenuates Neuronal Pyroptosis after Subarachnoid Hemorrhage in Rats via Regulating the CXCR4/NLRP1 Pathway.

Subarachnoid hemorrhage (SAH) is a cerebrovascular disease associated with high morbidity and mortality. CXCR4 provides neuroprotective effects, which can alleviate brain injury and inflammation induced by stroke. Previous studies have suggested that CXCR4 reduces the pyroptosis of LPS-stimulated BV2 cells. The purpose of this study was to evaluate the antipyroptosis effects and mechanisms of CXCR4 after SAH. SAH animal model was induced via endovascular perforation. A total of 136 male Sprague-Dawley rats were used. Recombinant human cysteine-X-cysteine chemokine ligand 12 (rh-CXCL-12) was administered intranasally at 1 h after SAH induction. To investigate the underlying mechanism, the inhibitor of CXCR4, AMD3100, was administered intraperitoneally at 1 h before SAH. The neurobehavior tests were assessed, followed by performing Western blot and immunofluorescence staining. The Western blot results suggested that the expressions of endogenous CXCL-12, CXCR4, and NLRP1 were increased and peaked at 24 h following SAH. Immunofluorescence staining showed that CXCR4 was expressed on neurons, microglia, and astrocytes. Rh-CXCL-12 treatment improved the neurological deficits and reduced the number of FJC-positive cells, IL-18-positive neurons, and cleaved caspase-1(CC-1)-positive neurons after SAH. Meanwhile, rh-CXCL-12 treatment increased the levels of CXCL-12 and CXCR4, and reduced the levels of NLRP1, IL-18, IL-1ß, and CC-1. Moreover, the administration of AMD3100 abolished antipyroptosis effects of CXCL-12 and its regulation of CXCR4 post-SAH. The CXCR4/NLRP1 signaling pathway may be involved in CXCL-12-mediated neuronal pyroptosis after SAH. Early administration of CXCL-12 may be a preventive and therapeutic strategy against brain injury after SAH.

The impact of national non-pharmaceutical interventions ('lockdowns') on the presentation of cancer patients.

One of the most ignored aspects of the COVID-19 pandemic has been the impact of public health measures by governments on wider health and welfare. From March 2020, hospitals in the UK saw a dramatic reduction in patients with cancer presenting due to multifactorial reasons. The impact of the pandemic on patients with cancer in the South East London Cancer Alliance was studied. The specific aims were (1) to examine the reduction in cancer diagnoses during the first wave of the pandemic and (2) to examine the stage of diagnosis of patients with cancer presenting during the pandemic compared with that of patients presenting before the pandemic. There was an 18.2% reduction in new cancer diagnoses (an estimate of 987 cancers), when compared with 2019. This fall in cancer diagnoses was most marked in patients with prostate (51.4%), gynaecological (29.7%), breast (29.5%) and lung (23.4%) cancers. There was an overall 3.9% increase in advanced stage presentation (Stages 3 and 4), with an overall 6.8% increase in Stage 4 cancers during this period. The greatest shifts were seen in lung (increase of 6.3%, with an 11.2% increase in Stage 4 cancer alone) and colorectal (5.4%) cancers. For prostate cancer, there was an increase in 3.8% in those presenting with Stage 4 disease. For breast cancer, there was an 8% reduction in patients diagnosed with Stage 1 cancer with commensurate increases in the proportion of those with Stage 2 disease. The experiences in cancer are a salient warning that pandemic control measures and policy need to balance all health and welfare. Alternative strategies need to be adopted during further waves of the current and any future pandemic to ensure that patients with cancer are prioritised for diagnosis and treatment to prevent late-stage presentation and an increase in avoidable deaths.

Global health governance for travel health: lessons learned from the coronavirus disease 2019 (COVID-19) outbreaks in large cruise ships.

BACKGROUND: The outbreak and global pandemic of coronavirus disease 2019 (COVID-19) attracts a great deal of attentions to the problem of travel health. Cruise tourism is increasingly popular, with an estimated 30 million passengers transported on cruise ships worldwide each year. Safeguarding the health of cruise travelers during the entire travel is of ultimate importance for both the industry and global public health. OBJECTIVE: This study aimed to explore the challenges and opportunities in travel health from the perspective of global health governance. METHODS: The global governance framework including problems, values, tools or regulations, and actors related to travel health were used to analyze the issues involved. RESULTS: Up to April 2020, nearly thirty cruise ship voyages reported COVID-19 cases. The Diamond Princess, Grand Princess and Ruby Princess cruise ship had over 1,400 total reported COVID-19 cases, and more than 30 deaths. A community with a common future in travel health is the core value of global health governance for travel health. The travel-related international regulations, including the International Health Regulation (IHR [2005]), United Nations Convention on the Law of the Sea (UNCLOS) and the International Maritime Organization (IMO) conventions should be further updated to deal with the travel health problems. The roles and responsibilities and the cooperation mechanisms of different actors are not clear in relation to the public health emergencies during the travel. CONCLUSION: Travel health transcends national borders and involves multilevel actors, thus needs global cooperation and governance. Regulations and legislation at global and country level are required to prevent large-scale humanitarian crisis on travel health. Multilateral coordination, cooperation and collaboration mechanisms between governments, intergovernmental organizations, non-governmental organizations and industry are needed to build a better community of common destiny for travel health.

Corticosteroids treatment in severe patients with COVID-19: a propensity score matching study.

OBJECTIVES: To explore the efficacy of corticosteroid treatment in patients with severe COVID-19 pneumonia and the association between corticosteroid use and patient mortality. METHODS: A retrospective investigation was made on the medical records of the patients with severe and critical patients with COVID-19 pneumonia from January to February 2020. First, the patients who received corticosteroid treatment were compared with patients without given corticosteroid treatment. Then, a propensity score matching method was used to control confounding factors. Cox survival regression analysis was used to evaluate the effect of corticosteroid therapy on the mortality of severe and critical patients with COVID-19. RESULTS: A total of 371 severe and critical patients were included in our analyses. Two hundred and enine patients were treated with corticosteroid therapy. Most of them were treated with methylprednisolone (197[94.3%]). The median corticosteroid therapy was applied 3 (IQR 2-6) days after admission, 13 (IQR 10-17) days after symptoms appeared. Temperature on admission (OR = 1.255, [95%CI 1.021-1.547], p = 0.032), ventilation (OR = 1.926, [95%CI 1.148-3.269], p = 0.014) and ICU admission (OR = 3.713, [95%CI 1.776-8.277], p < 0.001) were significantly associated with corticosteroids use. After PS matching, the cox regression survival analysis showed that corticosteroid use was significantly associated with a lower mortality rate (HR = 0.592, [95%CI 0.406-0.862], p = 0.006). CONCLUSION: Corticosteroid therapy use in severe and critical patients with COVID-19 pneumonia leads to lower mortality but may cause other side effects. Corticosteroid therapy should be used carefully.

Preliminary analysis on the incidence trend of novel coronavirus pneumonia in Shanghai / 上海预防医学

Objective To investigate the epidemical characteristics and analyze the incidence trend of novel coronavirus pneumonia (NCP) in Shanghai. Methods The epidemical data on NCP in Shanghai from January 20 to February 3, 2020 were collected for epidemiological descriptive analysis. Results The number of cumulative confirmed and suspected cases increased first and then decreased from January 20 to February 3, with the peak date being January 30 and January 29 respectively. The day-on-day growth rate of the suspected cases and the cumulative confirmed cases declined after January 27. Among the confirmed cases, the proportion of the exposure history of relevant confirmed cases was on the rise. The total number of confirmed cases of the resident population exceeded that of the population from other places to Shanghai, and Pudong new area had the largest number of confirmed cases. Conclusion The incidence of NCP showed a slowdown trend in shanghai, but it also faces the pressure of the peak of population returning to city, which should be paid enough attention to.