Background: Adenoid cystic carcinoma (ACC) is a relatively uncommon tumor. The existing prediction model is limited to the head and neck. We aim to construct a prognostic nomogram combined with the clinical features and treatment options of ACC to predict the disease-specific survival (DSS) of patients diagnosed with ACC in different anatomic sites. Methods: A novel predictive model was constructed using 1285 patients with ACC from the Surveillance, Epidemiology, and End Results (SEER) registry between 2010 and 2015. The performance of this model was externally validated using 118 patients with ACC in the West China Hospital, Sichuan University between 2010 and 2017. Results: The prognostic model demonstrated that age, primary site, lymph node metastasis, distant metastasis, radiotherapy and surgery were independent factors for DSS. The validation of the model using an external cohort proved its reliability. Conclusion: The developed novel predictive model is shown to provide accurate and efficient predictive information for patients with ACC for different anatomic sites.

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The application of next-generation sequencing (NGS) in routine clinical analysis is still limited. The significance of NGS in the identification of pathogens of lower respiratory tract infection should be assessed as part of routine clinical bacterial examinations and chest imaging results. In the present study, the alveolar lavage fluid samples of 30 patients (25 males and 5 females, aged 19-92 years old, with a median age of 62) were examined by routine bacterial culture and NGS, and the results of pathogen detection and identification were compared. Chest imaging showed consolidation in all 30 patients (100%), and pleural effusion in 13 of the 30 patients (43.33%). The routine bacterial culture of the lavage solution was only positive in 14 of the 30 patients (46.6%), and negative in 16 patients (53.33%). However, the positive rate of NGS test results of the lavage fluid was 100%. A total of 12 cases (40%) were completely consistent with the routine bacterial culture test, with 56 other pathogens of mixed infection detected, accounting for the short comings of the routine bacterial examination. Although NGS cannot distinguish between live and dead bacteria, it is still a useful detection technology for accurate diagnosis of clinical infectious diseases. It is worthy of adaptation in the clinic for more effective clinical management and treatment of the lower respiratory airway infection in addition to the routine bacterial culture testing.

Study Objectives Sleep and circadian phenotypes are associated with several diseases. The present study aimed to investigate whether sleep and circadian phenotypes were causally linked with coronavirus disease 2019 (COVID-19)-related outcomes. Methods Habitual sleep duration, insomnia, excessive daytime sleepiness, daytime napping, and chronotype were selected as exposures. Key outcomes included positivity and hospitalization for COVID-19. In the observation cohort study, multivariable risk ratios (RRs) and their 95% confidence intervals (CIs) were calculated. Two-sample Mendelian randomization (MR) analyses were conducted to estimate the causal effects of the significant findings in the observation analyses. Beta values and the corresponding 95% CIs were calculated and compared using the inverse variance weighting, weighted median, and MR-Egger methods. Results In the UK Biobank cohort study, both often excessive daytime sleepiness and sometimes daytime napping were associated with hospitalized COVID-19 (excessive daytime sleepiness [often vs. never]: RR=1.24, 95% CI=1.02-1.5; daytime napping [sometimes vs. never]: RR=1.12, 95% CI=1.02-1.22). In addition, sometimes daytime napping was also associated with an increased risk of COVID-19 susceptibility (sometimes vs. never: RR= 1.04, 95% CI=1.01-1.28). In the MR analyses, excessive daytime sleepiness was found to increase the risk of hospitalized COVID-19 (MR IVW method: OR = 4.53, 95% CI = 1.04-19.82), whereas little evidence supported a causal link between daytime napping and COVID-19 outcomes. Conclusions Observational and genetic evidence supports a potential causal link between excessive daytime sleepiness and an increased risk of COVID-19 hospitalization, suggesting that interventions targeting excessive daytime sleepiness symptoms might decrease severe COVID-19 rate.

The evidence for chronic hepatitis B virus (HBV) infection and hepatocellular carcinoma (HCC) occurrence is well established. The hepatocyte epithelium carcinogenesis caused by HBV has been investigated and reviewed in depth. Nevertheless, recent findings from preclinical and observational studies suggested that chronic HBV infection is equally important in extrahepatic cancer occurrence and survival, specifically gastrointestinal system-derived cancers. Immune microenvironment changes (immune-suppressive cytokine infiltration), epigenetic modification (N6-methyladenosine), molecular signaling pathways (PI3K–Akt and Wnt), and serum biomarkers such as hepatitis B virus X (HBx) protein are potential underlying mechanisms in chronic HBV infection-induced extrahepatic cancers. This narrative review aimed to comprehensively summarize the most recent advances in evaluating the association between chronic HBV infection and extrahepatic cancer risk and explore the potential underlying molecular mechanisms in the carcinogenesis induction of extrahepatic cancers in chronic HBV conditions.