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OBJECTIVEDiabetes is one of the most distinct comorbidities of COVID-19. Here, we describe the clinical characteristics of and outcomes in patients with diabetes in whom COVID-19 has been confirmed or clinically diagnosed (with typical features on lung imaging and symptoms), and their association with glucose-lowering or blood pressure-lowering medications. RESEARCH DESIGN AND METHODSIn this retrospective study involving 904 patients with COVID-19 (136 with diabetes, mostly type 2 diabetes), clinical and laboratory characteristics were collected and compared between the group with diabetes and the group without diabetes, and between groups taking different medications. Logistic regression was used in order to explore risk factors associated with mortality or poor prognosis. RESULTSThe proportion of comorbid diabetes is similar between cases of confirmed and of clinically diagnosed COVID-19. Risk factors for higher mortality of patients with diabetes and COVID-19 were older age (adjusted odds ratio [aOR] 1.09 [95% CI 1.04, 1.15] per year increase; P 5 0.001) and elevated C-reactive protein (aOR 1.12 [95% CI 1.00, 1.24]; P 5 0.043). Insulin usage (aOR 3.58 [95% CI 1.37, 9.35]; P 5 0.009) was associated with poor prognosis. Clinical outcomes of those who use an ACE inhibitor (ACEI) or angiotensin II type-I receptor blocker (ARB) were comparable with those of patients who do not use ACEI/ARB among patients with diabetes and hypertension who have COVID-19. CONCLUSIONSC-reactive protein may help to identify patients with diabetes who are at greater risk of dying during hospitalization. Older patients with diabetes were prone to death

Mounting evidence indicates that microbiome plays an important role in the development and progression of cancer. The dogma that urine in healthy individuals must be sterile has been overturned. Dysbiosis of the urinary microbiome has been revealed responsible for various urological disorders, including prostate cancer. The link between chronic inflammation, microbiome and solid tumors has been established for various neoplastic diseases. However, a detailed and comprehensive analysis of urinary microenvironment of bladder cancer has not been yet reported. We performed this study to characterize the potential urinary microbial community possibly associated with bladder cancer. Mid-stream urine was collected from 31 male patients with bladder cancer and 18 non-neoplastic controls. DNA was extracted from urine pellet samples and processed for high throughput 16S rRNA amplicon sequencing of the V4 region using Illumina MiSeq. Sequencing reads were filtered using QIIME and clustered using UPARSE. We observed increased bacterial richness (Observed Species, Chao 1 and Ace indexes; cancer vs. control; 120.0 vs. 56.0; 134.5 vs. 68.3; and 139.6 vs. 72.9, respectively), enrichment of some bacterial genera (e.g., Acinetobacter, Anaerococcus, and Sphingobacterium) and decrease of some bacterial genera (e.g., Serratia, Proteus, and Roseomonas) in cancer group when compared to non-cancer group. Significant difference in beta diversity was found between cancer and non-cancer group, among different risk level, but not among different tumor grade. Enrichment of Herbaspirillum, Porphyrobacter, and Bacteroides was observed in cancer patients with high risk of recurrence and progression, which means these genera maybe potential biomarkers for risk stratification. The PICRUSt showed that various functional pathways were enriched in cancer group, including Staphylococcus aureus infection, glycerolipid metabolism and retinol metabolism. To our knowledge, we performed the most comprehensive study to date to characterize the urinary microbiome associated with bladder cancer. A better understanding of the role of microbiome in the development and progression of bladder cancer could pave a new way for exploring new therapeutic options and biomarkers.

The outbreak of COVID-19 has become a worldwide pandemic. The pathogenesis of this infectious disease and how it differs from other drivers of pneumonia is unclear. Here we analyze urine samples from COVID-19 infection cases, healthy donors and non-COVID-19 pneumonia cases using quantitative proteomics. The molecular changes suggest that immunosuppression and tight junction impairment occur in the early stage of COVID-19 infection. Further subgrouping of COVID-19 patients into moderate and severe types shows that an activated immune response emerges in severely affected patients. We propose a two-stage mechanism of pathogenesis for this unusual viral infection. Our data advance our understanding of the clinical features of COVID-19 infections and provide a resource for future mechanistic and therapeutics studies.