The outbreak of the coronavirus disease 2019 (Covid‐19) has become an evolving worldwide health crisis. With the rising prevalence of obesity and diabetes has come an increasing awareness of their impacts on infectious diseases, including increased risk for various infections, post‐infection complications and mortality from critical infections. Although epidemiological and clinical characteristics of Covid‐19 have been constantly reported, no article has systematically illustrated the role of obesity and diabetes in Covid‐19, or how Covid‐19 affects obesity and diabetes, or special treatment in these at‐risk populations. Here, we present a synthesis of the recent advances in our understanding of the relationships between obesity, diabetes and Covid‐19 along with the underlying mechanisms, and provide special treatment guidance for these at‐risk populations.

Highlights Among patients with severe or fatal coronavirus disease 2019 (COVID-19), the most prevalent comorbidities were obesity and hypertension, followed by diabetes, cardiovascular disease, respiratory disease, cerebrovascular disease, malignancy, chronic kidney disease, and liver disease. Comorbid respiratory disease was identified as the strongest risk factor for COVID-19 severity, followed by hypertension, cardiovascular disease, chronic kidney disease, cerebrovascular disease, malignancy, diabetes, and obesity. Subgroup analyses were conducted according to severe clinical outcomes and country of residence in the study population. Knowledge of these risk factors could help clinicians better identify and manage the high-risk populations.

In this large cohort, we found TERT promoter mutations to be common, particularly in FTC and BRAF mutation-positive PTC, and associated with aggressive clinicopathological characteristics.

We present a new algorithm for realtime face tracking on commodity RGB-D sensing devices. Our method requires no user-specific training or calibration, or any other form of manual assistance, thus enabling a range of new applications in performance-based facial animation and virtual interaction at the consumer level. The key novelty of our approach is an optimization algorithm that jointly solves for a detailed 3D expression model of the user and the corresponding dynamic tracking parameters. Realtime performance and robust computations are facilitated by a novel subspace parameterization of the dynamic facial expression space. We provide a detailed evaluation that shows that our approach significantly simplifies the performance capture workflow, while achieving accurate facial tracking for realtime applications.

Type 1 diabetes mellitus (T1DM) is an autoimmune disorder resulted from T cell-mediated destruction of pancreatic β-cells, how to regenerate β-cells and prevent the autoimmune destruction of remnant and neogenetic β-cells is a tough problem. Immunomodulatory propertity of mesenchymal stem cell make it illuminated to overcome it. We assessed the long-term effects of the implantation of Wharton's jelly-derived mesenchymal stem cells (WJ-MSCs) from the umbilical cord for Newly-onset T1DM. Twenty-nine patients with newly onset T1DM were randomly divided into two groups, patients in group I were treated with WJ-MSCs and patients in group II were treated with normal saline based on insulin intensive therapy. Patients were followed-up after the operation at monthly intervals for the first 3 months and thereafter every 3 months for the next 21 months, the occurrence of any side effects and results of laboratory examinations were evaluated. There were no reported acute or chronic side effects in group I compared with group II, both the HbA1c and C peptide in group I patients were significantly better than either pretherapy values or group II patients during the follow-up period. These data suggested that the implantation of WJ-MSCs for the treatment of newly-onset T1DM is safe and effective. This therapy can restore the function of islet β cells in a longer time, although precise mechanisms are unknown, the implantation of WJ-MSCs is expected to be an effective strategy for treatment of type1 diabetes.