Long non-coding RNAs in virus-related cancers.

Some viral infections lead to tumourigenesis explained by a variety of underlying molecular mechanisms. Long non-coding RNAs (lncRNAs) have the potential to be added to this list due to their diverse mechanisms in biological functions and disease processes via gene alternation, transcriptional regulation, protein modification, microRNA sponging and interaction with RNA/DNA/proteins. In this review, we summarise the dysregulation and mechanism of lncRNAs in virus-related cancers focussing on Hepatitis B virus, Epstein-Barr virus, Human Papillomavirus. We will also discuss the potential implications of lncRNAs in COVID-19.

How has academia responded to the urgent needs created by COVID-19? A multi-level global, regional and national analysis

In the context of the COVID-19 pandemic, gaining insights into how academia has responded to this urgent challenge is of great significance. This article presents academic response patterns at a global, regional and national level from an analysis of publication volume versus reported cases of COVID-19, scientific collaboration and research focus. We also compare academic activity associated with this newly emerging infection to that related to long-standing infections. Our results show that the research community has responded quickly to COVID-19. The highly developed countries, which have the highest number of confirmed cases, are also the major academic contributors. National-level analysis reveals diverse response patterns from different countries. Specifically, academic research in the United Kingdom remained at a relatively constant level throughout the whole year (2020), while the global share of China?s research output was prone to shift as its domestic pandemic status changed. Strong alliances have formed among countries with academic capabilities in response to the COVID-19 pandemic. The distribution of disciplines is relatively decentralised, indicating that a diverse and broad knowledge base contributes to the COVID-19 literature. Most of the analysed countries show dynamic patterns of research focus that vary over time as the pandemic evolves, except India. As one of the world?s biggest suppliers of vaccines, India makes consistent efforts on vaccine research, especially those related to pharmaceutical preparations. Our findings may serve as resources for fostering strategies to respond to future threats of pandemics.

Viral loads, lymphocyte subsets and cytokines in asymptomatic, mildly and critical symptomatic patients with SARS-CoV-2 infection: a retrospective study.

BACKGROUND: Tens of million cases of coronavirus disease-2019 (COVID-19) have occurred globally. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) attacks the respiratory system, causing pneumonia and lymphopenia in infected individuals. The aim of the present study is to investigate the laboratory characteristics of the viral load, lymphocyte subset and cytokines in asymptomatic individuals with SARS-CoV-2 infection in comparison with those in symptomatic patients with COVID-19. METHODS: From January 24, 2020, to April 11, 2020, 48 consecutive subjects were enrolled in this study. Viral loads were detected by RT-PCR from throat-swab, sputum and feces samples. Lymphocyte subset levels of CD3 + , CD4 + , and CD8 + T lymphocytes, B cells and NK cells were determined with biological microscope and flow cytometric analysis. Plasma cytokines (IL2, IL4, IL5, IL6, IL8, IL10, TNF-α, IFN-α and IFN-γ) were detected using flow cytometer. Analysis of variance (ANOVA), Chi-square or Fisher's exact test and Pearson's Correlation assay was used for all data. RESULTS: Asymptomatic (AS), mild symptoms (MS) and severe or critical cases (SCS) with COVID-19 were 11 (11/48, 22.9%), 26 (54.2%, 26/48) and 11 cases (11/48, 22.9%), respectively. The mean age of AS group (47.3 years) was lower than SCS group (63.5 years) (P < 0.05). Diabetes mellitus in AS, MS and SCS patients with COVID-19 were 0, 6 and 5 cases, respectively, and there was a significant difference between AS and SCS (P < 0.05). No statistical differences were found in the viral loads of SARS-CoV-2 between AS, MS and SCS groups on admission to hospital and during hospitalization. The concentration of CD 3 + T cells (P < 0.05), CD3 + CD4 + T cells (P < 0.05), CD3 + CD8 + T cells (P < 0.01), and B cells (P < 0.05) in SCS patients was lower than in AS and MS patients, while the level of IL-5 (P < 0.05), IL-6 (P < 0.05), IL-8 (P < 0.01) and IL-10 (P < 0.01), and TNF-α (P < 0.05) was higher. The age was negatively correlated with CD3 + T cells (P < 0.05), CD3 + CD4 + T cells (P < 0.05), and positively correlated with IL-2 (P < 0.001), IL-5 (P < 0.05), IL-6 (P < 0.05) IL-8 (P < 0.05), and IL-10 (P < 0.05). The viral loads were positively correlated with IL-2 (P < 0.001), IL-5 (P < 0.05), IL-6 (P < 0.05) IL-8 (P < 0.05) and IL-10 (P < 0.05), while negatively correlated with CD 3 + T cells (P < 0.05) and CD3 + CD4 + T cells (P < 0.05). CONCLUSIONS: The viral loads are similar between asymptomatic, mild and severe or critical patients with COVID-19. The severity of COVID-19 may be related to underlying diseases such as diabetes mellitus. Lymphocyte subset and plasma cytokine levels may be as the markers to distinguish severely degrees of disease, and asymptomatic patients may be as an important source of infection for the COVID-19.