Background: Critically ill patients diagnosed with COVID-19 may develop a pro-thrombotic state that places them at a dramatically increased lethal risk. Although platelet activation is critical for thrombosis and is responsible for the thrombotic events and cardiovascular complications, the role of platelets in the pathogenesis of COVID-19 remains unclear. Methods: Using platelets from healthy volunteers, non-COVID-19 and COVID-19 patients, as well as wild-type and hACE2 transgenic mice, we evaluated the changes in platelet and coagulation parameters in COVID-19 patients. We investigated ACE2 expression and direct effect of SARS-CoV-2 virus on platelets by RT-PCR, flow cytometry, Western blot, immunofluorescence, and platelet functional studies in vitro, FeCl 3-induced thrombus formation in vivo, and thrombus formation under flow conditions ex vivo.

Circulating tumor cells (CTCs) enter peripheral blood from primary tumors and seed metastases. The genome sequencing of CTCs could offer noninvasive prognosis or even diagnosis, but has been hampered by low single-cell genome coverage of scarce CTCs. Here, we report the use of the recently developed multiple annealing and looping-based amplification cycles for whole-genome amplification of single CTCs from lung cancer patients. We observed characteristic cancer-associated single-nucleotide variations and insertions/deletions in exomes of CTCs. These mutations provided information needed for individualized therapy, such as drug resistance and phenotypic transition, but were heterogeneous from cell to cell. In contrast, every CTC from an individual patient, regardless of the cancer subtypes, exhibited reproducible copy number variation (CNV) patterns, similar to those of the metastatic tumor of the same patient. Interestingly, different patients with the same lung cancer adenocarcinoma (ADC) shared similar CNV patterns in their CTCs. Even more interestingly, patients of smallcell lung cancer have CNV patterns distinctly different from those of ADC patients. Our finding suggests that CNVs at certain genomic loci are selected for the metastasis of cancer. The reproducibility of cancer-specific CNVs offers potential for CTC-based cancer diagnostics.cancer diagnostics | personalized therapy A s a genomic disease, cancer involves a series of changes in the genome, starting from primary tumors, via circulating tumor cells (CTCs), to metastases that cause the majority of mortalities (1-3). These genomic alterations include copy number variations (CNVs), single-nucleotide variations (SNVs), and insertions/deletions (INDELs). Regardless of the concentrated efforts in the past decades, the key driving genomic alterations responsible for metastases are still elusive (1).For noninvasive prognosis and diagnosis of cancer, it is desirable to monitor genomic alterations through the circulatory system. Genetic analyses of cell-free DNA fragments in peripheral blood have been reported (4-6) and recently extended to the whole-genome scale (7-9). However, it may be advantageous to analyze CTCs, as they represent intact functional cancer cells circulating in peripheral blood (10). Although previous studies have shown that CTC counting was able to predict progression and overall survival of cancer patients (11,12), genomic analyses of CTCs could provide more pertinent information for personalized therapy (13). However, it is difficult to probe the genomic changes in DNA obtainable from the small number of captured CTCs. To meet this challenge, a single-cell whole-genome amplification (WGA) method, multiple annealing and loopingbased amplification cycles (MALBAC) (14), has been developed to improve the amplification uniformity across the entire genome over previous methods (15,16), allowing precise determination of CNVs and detection of SNVs with a low false-positive rate in a single cell. Here, we present genomic analyses of CTCs from...

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Background The COVID‐19 pandemic outbreak might induce acute stress disorder (ASD) to people living in the epidemic regions. The current study aims to investigate the association of COVID‐19‐related stressful experiences with ASD and possible psychological mechanisms of the association among college students. Methods Data were collected from 7,800 college students via an online survey during the initial stage of the COVID‐19 outbreak in China (from 31 January to 11 February 2020). Existing scales were adapted to measure stressful experiences, resilience, coping, social support, and ASD symptoms. Path analysis was employed to examine the research hypotheses. Results Among the 7,800 college students, 61.53% were women and their mean age was 20.54 years. Both direct and indirect effects from COVID‐19‐related stressful experiences to ASD symptoms were significant. The relationship between COVID‐19‐related stressful experiences and ASD could be mediated by resilience ( β = 0.01, p < .001), adaptive coping strategies ( β = 0.02, p < .001), and social support ( β = 0.01, p < .001); while not being significantly mediated by maladaptive coping strategies. Conclusion The findings presented the ASD symptoms related to the COVID‐19 outbreak and the mediating role of interpersonal and intrapersonal factors in the association. Identifying the risk and protective factors is important to reduce acute psychological responses.

The global spread of SARS-CoV-2 is posing major public health challenges. One feature of SARS-CoV-2 spike protein is the insertion of multi-basic residues at the S1/S2 subunit cleavage site. Here, we find that the virus with intact spike (Sfull) preferentially enters cells via fusion at the plasma membrane, whereas a clone (Sdel) with deletion disrupting the multi-basic S1/S2 site utilizes an endosomal entry pathway. Using Sdel as model, we perform a genome-wide CRISPR screen and identify several endosomal entry-specific regulators. Experimental validation of hits from the CRISPR screen shows that host factors regulating the surface expression of angiotensin-converting enzyme 2 (ACE2) affect entry of Sfull virus. Animal-to-animal transmission with the Sdel virus is reduced compared to Sfull in the hamster model. These findings highlight the critical role of the S1/S2 boundary of SARS-CoV-2 spike protein in modulating virus entry and transmission and provide insights into entry of coronaviruses.

The 2′,5′-oligoadenylate (2-5A) synthetase (OAS)-RNase L system is an IFN-induced antiviral pathway. RNase L activity depends on 2-5A, synthesized by OAS. Although all three enzymatically active OAS proteins in humans-OAS1, OAS2, and OAS3-synthesize 2-5A upon binding dsRNA, it is unclear which are responsible for RNase L activation during viral infection. We used clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein-9 nuclease (Cas9) technology to engineer human A549-derived cell lines in which each of the OAS genes or RNase L is knocked out. Upon transfection with poly(rI):poly(rC), a synthetic surrogate for viral dsRNA, or infection with each of four viruses from different groups (West Nile virus, Sindbis virus, influenza virus, or vaccinia virus), OAS1-KO and OAS2-KO cells synthesized amounts of 2-5A similar to those synthesized in parental wild-type cells, causing RNase L activation as assessed by rRNA degradation. In contrast, OAS3-KO cells synthesized minimal 2-5A, and rRNA remained intact, similar to infected RNase L-KO cells. All four viruses replicated to higher titers in OAS3-KO or RNase L-KO A549 cells than in parental, OAS1-KO, or OAS2-KO cells, demonstrating the antiviral effects of OAS3. OAS3 displayed a higher affinity for dsRNA in intact cells than either OAS1 or OAS2, consistent with its dominant role in RNase L activation. Finally, the requirement for OAS3 as the major OAS isoform responsible for RNase L activation was not restricted to A549 cells, because OAS3-KO cells derived from two other human cell lines also were deficient in RNase L activation.C ritically important to understanding antiviral innate immunity is determining which host proteins are responsible for inhibiting different types of viruses. However, there are significant gaps in our knowledge about the specificity of many host antiviral proteins. The 2′,5′-oligoadenylate (2-5A) synthetase (OAS)-RNase L system (reviewed in ref. 1) is a case in point. OASs are pattern-recognition receptors for viral dsRNA, a common pathogen-associated molecular pattern for many types of RNA and DNA viruses. In humans, there are four OAS genes, all stimulated by IFN, but only three of these encode catalytically active proteins. OAS1, OAS2, and OAS3 contain one, two, and three core OAS units, respectively, but all three enzymes synthesize 2-5A from ATP upon binding dsRNA (2). OASL, containing one basic unit plus two ubiquitin-like domains, does not synthesize 2-5A but instead activates RIG-I signaling in response to dsRNA (3). In addition, OASs are structurally homologous to cGAS, a sensor of cytoplasmic DNA, often of microbial origin, that produces 2′,5′-cGMP-AMP activators of STING leading to type I IFN production (4).The only well-established function of 2-5A is to activate RNase L, causing endonucleolytic cleavage of viral and cellular ssRNAs, thereby blocking viral replication. Many viruses encode antagonists of the OAS-RNase L pathway, providing evidence that RNase L is a potent antiviral protein (1, 5, 6...

The pandemic of COVID-19, caused by SARS-CoV-2, is a major global health threat. Epidemiological studies suggest that bats (Rhinolophus affinis) are the natural zoonotic reservoir for SARS-CoV-2. However, the host range of SARS-CoV-2 and intermediate hosts that facilitate its transmission to humans remain unknown. The interaction of coronavirus with its host receptor is a key genetic determinant of host range and cross-species transmission. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) as the receptor to enter host cells in a species-dependent manner. In this study, we characterized the ability of ACE2 from diverse species to support viral entry. By analyzing the conservation of five residues in two virus-binding hotspots of ACE2 (hotspot 31Lys and hotspot 353Lys), we predicted 80 ACE2 proteins from mammals that could potentially mediate SARS-CoV-2 entry. We chose 48 ACE2 orthologs among them for functional analysis, and showed that 44 of these orthologs—including domestic animals, pets, livestock, and animals commonly found in zoos and aquaria—could bind the SARS-CoV-2 spike protein and support viral entry. In contrast, New World monkey ACE2 orthologs could not bind the SARS-CoV-2 spike protein and support viral entry. We further identified the genetic determinant of New World monkey ACE2 that restricts viral entry using genetic and functional analyses. These findings highlight a potentially broad host tropism of SARS-CoV-2 and suggest that SARS-CoV-2 might be distributed much more widely than previously recognized, underscoring the necessity to monitor susceptible hosts to prevent future outbreaks.

Data subject to heavy-tailed errors are commonly encountered in various scientific fields. To address this problem, procedures based on quantile regression and Least Absolute Deviation (LAD) regression have been developed in recent years. These methods essentially estimate the conditional median (or quantile) function. They can be very different from the conditional mean functions, especially when distributions are asymmetric and heteroscedastic. How can we efficiently estimate the mean regression functions in ultra-high dimensional setting with existence of only the second moment? To solve this problem, we propose a penalized Huber loss with diverging parameter to reduce biases created by the traditional Huber loss. Such a penalized robust approximate quadratic (RA-quadratic) loss will be called RA-Lasso. In the ultra-high dimensional setting, where the dimensionality can grow exponentially with the sample size, our results reveal that the RA-lasso estimator produces a consistent estimator at the same rate as the optimal rate under the light-tail situation. We further study the computational convergence of RA-Lasso and show that the composite gradient descent algorithm indeed produces a solution that admits the same optimal rate after sufficient iterations. As a byproduct, we also establish the concentration inequality for estimating population mean when there exists only the second moment. We compare RA-Lasso with other regularized robust estimators based on quantile regression and LAD regression. Extensive simulation studies demonstrate the satisfactory finite-sample performance of RA-Lasso.