Reduction in Risk of Death Among Patients Admitted With COVID-19 Between the First and Second Epidemic Waves in New York City.

Background: Many regions have experienced successive epidemic waves of coronavirus disease 2019 (COVID-19) since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with heterogeneous differences in mortality. Elucidating factors differentially associated with mortality between epidemic waves may inform clinical and public health strategies. Methods: We examined clinical and demographic data among patients admitted with COVID-19 during the first (March-August 2020) and second (August 2020-March 2021) epidemic waves at an academic medical center in New York City. Results: Hospitalized patients (n = 4631) had lower overall and 30-day in-hospital mortality, defined as death or discharge to hospice, during the second wave (14% and 11%) than the first (22% and 21%). The wave 2 in-hospital mortality decrease persisted after adjusting for several potential confounders. Adjusting for the volume of COVID-19 admissions, a measure of health system strain, accounted for the mortality difference between waves. Several demographic and clinical patient factors were associated with an increased risk of mortality independent of wave: SARS-CoV-2 cycle threshold, do-not-intubate status, oxygen requirement, and intensive care unit admission. Conclusions: This work suggests that the increased in-hospital mortality rates observed during the first epidemic wave were partly due to strain on hospital resources. Preparations for future epidemics should prioritize evidence-based patient risks, treatment paradigms, and approaches to augment hospital capacity.

Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments.

The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life and devastated the worldwide economy. Numerous efforts have been made to mitigate COVID-19 symptoms and reduce the death rate. We conducted literature mining of more than 250 thousand published works and curated the 174 most widely used COVID-19 medications. Overlaid with the human protein-protein interaction (PPI) network, we used Steiner tree analysis to extract a core subnetwork that grew from the pharmacological targets of ten credible drugs ascertained by the CTD database. The resultant core subnetwork consisted of 34 interconnected genes, which were associated with 36 drugs. Immune cell membrane receptors, the downstream cellular signaling cascade, and severe COVID-19 symptom risk were significantly enriched for the core subnetwork genes. The lung mast cell was most enriched for the target genes among 1355 human tissue-cell types. Human bronchoalveolar lavage fluid COVID-19 single-cell RNA-Seq data highlighted the fact that T cells and macrophages have the most overlapping genes from the core subnetwork. Overall, we constructed an actionable human target-protein module that mainly involved anti-inflammatory/antiviral entry functions and highly overlapped with COVID-19-severity-related genes. Our findings could serve as a knowledge base for guiding drug discovery or drug repurposing to confront the fast-evolving SARS-CoV-2 virus and other severe infectious diseases.

Delineating COVID-19 immunological features using single-cell RNA sequencing.

Understanding the molecular mechanisms of coronavirus disease 2019 (COVID-19) pathogenesis and immune response is vital for developing therapies. Single-cell RNA sequencing has been applied to delineate the cellular heterogeneity of the host response toward COVID-19 in multiple tissues and organs. Here, we review the applications and findings from over 80 original COVID-19 single-cell RNA sequencing studies as well as many secondary analysis studies. We describe that single-cell RNA sequencing reveals multiple features of COVID-19 patients with different severity, including cell populations with proportional alteration, COVID-19-induced genes and pathways, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in single cells, and adaptation of immune repertoire. We also collect published single-cell RNA sequencing datasets from original studies. Finally, we discuss the limitations in current studies and perspectives for future advance.

Reduction in risk of death among patients admitted with COVID-19 between first and second epidemic waves in New York City.

Many regions have experienced successive epidemic waves of COVID-19 since the emergence of SARS-CoV-2 with heterogeneous differences in mortality. Elucidating factors differentially associated with mortality between epidemic waves may inform clinical and public health strategies. We examined clinical and demographic data among patients admitted with COVID-19 during the first (March-June 2020) and second (December 2020-March 2021) epidemic waves at an academic medical center in New York City. Hospitalized patients (N=4631) had lower mortality during the second wave (14%) than the first (23%). Patients in the second wave had a lower 30-day mortality (Hazard Ratio (HR) 0.52, 95% CI 0.44, 0.61) than those in the first wave. The mortality decrease persisted after adjusting for confounders except for the volume of COVID-19 admissions (HR 0.88, 95% CI 0.70, 1.11), a measure of health system strain. Several demographic and clinical patient factors were associated with an increased risk of mortality independent of wave. Article summary: Using clinical and demographic data from COVID-19 hospitalizations at a tertiary New York City medical center, we show that a reduction in mortality during the second epidemic wave was associated with decreased strain on healthcare resources.

Characterization of the chloroplast genome of a rare species in China, Lilium martagon var. pilosiusculum.

Lilium martagon var. pilosiusculum is an endangered species with high ornamental value in Xinjiang province (China). In this study, we reported a complete chloroplast genome of L. martagon var. pilosiusculum, which was de novo assembled using the next-generation sequencing data. The complete chloroplast genome is 152,816 in length, including a large single copy region of 82,265 bp and a small single copy region of 17,541 bp and two inverted repeat regions of 26,505 bp. A total of 110 functional genes were encoded, consisting of 76 protein-coding genes, 30 transfer RNA genes, and four ribosomal RNA genes. The overall AT content of the chloroplast genome is 63.00%. In addition, 68 SSRs and 31 large repeat sequences were found. In the maximum likelihood tree, a strong phylogenetic signal showed that L. martagon var. pilosiusculum is a species of lilium.