Quantifying the importance of the key sites on haemagglutinin in determining the selection advantage of influenza virus: Using A/H3N2 as an example Dear Editor , Authors' contributionsSZ and MHW conceived the study. SZ carried out the analysis, and drafted the first manuscript. SZ and MHW discussed the results. All authors read, revised the manuscript, and gave final approval for publication. Declaration of Competing InterestMHW is a shareholder of Beth Bioinformatics Co., Ltd, and BCYZ is a shareholder of Beth Bioinformatics Co., Ltd and Health View Bioanalytics Ltd. Declarations Ethics approval and consent to participateThe ethical approval or individual consent was not applicable. Availability of data and materialsAll influenza viruses sequence data were collected via the influenza virus database (IVD) of the National center for Biotechnology Information (NCBI). Please see the online supporting information for details. Consent for publicationNot applicable.

Background Tocilizumab blocks pro-inflammatory activity of interleukin-6 (IL-6), involved in pathogenesis of pneumonia the most frequent cause of death in COVID-19 patients. Methods A multicenter, single-arm, hypothesis-driven trial was planned, according to a phase 2 design, to study the effect of tocilizumab on lethality rates at 14 and 30 days (co-primary endpoints, a priori expected rates being 20 and 35%, respectively). A further prospective cohort of patients, consecutively enrolled after the first cohort was accomplished, was used as a secondary validation dataset. The two cohorts were evaluated jointly in an exploratory multivariable logistic regression model to assess prognostic variables on survival. Results In the primary intention-to-treat (ITT) phase 2 population, 180/301 (59.8%) subjects received tocilizumab, and 67 deaths were observed overall. Lethality rates were equal to 18.4% (97.5% CI: 13.6–24.0, P = 0.52) and 22.4% (97.5% CI: 17.2–28.3, P < 0.001) at 14 and 30 days, respectively. Lethality rates were lower in the validation dataset, that included 920 patients. No signal of specific drug toxicity was reported. In the exploratory multivariable logistic regression analysis, older age and lower PaO2/FiO2 ratio negatively affected survival, while the concurrent use of steroids was associated with greater survival. A statistically significant interaction was found between tocilizumab and respiratory support, suggesting that tocilizumab might be more effective in patients not requiring mechanical respiratory support at baseline. Conclusions Tocilizumab reduced lethality rate at 30 days compared with null hypothesis, without significant toxicity. Possibly, this effect could be limited to patients not requiring mechanical respiratory support at baseline. Registration EudraCT (2020-001110-38); clinicaltrials.gov (NCT04317092).

Metabolomics and lipidomics have been used in several studies to define the biochemical alterations induced by COVID-19 in comparison with healthy controls. Those studies highlighted the presence of a strong signature, attributable to both metabolites and lipoproteins/lipids. Here, 1H NMR spectra were acquired on EDTA-plasma from three groups of subjects: i) hospitalized COVID-19 positive patients (≤21 days from the first positive nasopharyngeal swab); ii) hospitalized COVID-19 positive patients (>21 days from the first positive nasopharyngeal swab); iii) subjects after 2–6 months from SARS-CoV-2 eradication. A Random Forest model built using the EDTA-plasma spectra of COVID-19 patients ≤21 days and Post COVID-19 subjects, provided a high discrimination accuracy (93.6%), indicating both the presence of a strong fingerprint of the acute infection and the substantial metabolic healing of Post COVID-19 subjects. The differences originate from significant alterations in the concentrations of 16 metabolites and 74 lipoprotein components. The model was then used to predict the spectra of COVID-19>21 days subjects. In this group, the metabolite levels are closer to those of the Post COVID-19 subjects than to those of the COVID-19≤21 days; the opposite occurs for the lipoproteins. Within the acute phase patients, characteristic trends in metabolite levels are observed as a function of the disease severity. The metabolites found altered in COVID-19≤21 days patients with respect to Post COVID-19 individuals overlap with acute infection biomarkers identified previously in comparison with healthy subjects. Along the trajectory towards healing, the metabolome reverts back to the “healthy” state faster than the lipoproteome.

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In December 2019, the severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) spread worldwide, challenging emergency departments (EDs) with the need of rapid diagnosis for appropriate allocation in dedicated setting. Many authors highlighted the role of lung ultrasound (LUS) in management of the novel coronavirus disease 2019 . The study aims to analyze the performance of LUS in the early identification of COVID-19 patients in ED during a SARS-CoV-2 outbreak. We prospectively collected consecutive adult patients admitted to a first-level ED in Powered by Editorial Manager ® and ProduXion Manager ® from Aries Systems Corporation Florence with history or symptoms suggestive for COVID-19 that underwent LUS during the ED management. LUS findings were categorized in 6 discrete main etiological patterns. "A", "Cardiogenic B" and "Typical C" patterns were referred as non-COVID-19-suggestive, while "Atypical" B or C patterns, "Multiple Consolidations" pattern and "ARDS" pattern were referred as COVID-19-suggestive. The primary outcome was the diagnosis of SARS-CoV-2 infection. From 12 March to 12 May 2020, 360 patients were enrolled. COVID-19 suggestive LUS findings were significantly associated with final COVID-19 diagnosis (86% in COVID-19 vs 29% in non-COVID-19, p < 0.001). The presence in ED of at least one in positive swab OR a COVID-19-suggestive LUS showed a sensitivity of 97% and a negative predictive value (NPV) of 98%. In patients with known SARS-CoV-2 exposition in the last 14 days, a COVID-19-suggestive pattern at LUS had a positive predictive value (PPV) of 97% for COVID-19 diagnosis. Point-of-care ultrasound (PoCUS) is a valuable tool for diagnostic stratification during COVID-19 outbreaks. LUS can help physicians in identifying false-negative RT-PCR, improving its diagnostic sensitivity in ED.