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Drugs that target immune checkpoints (ICPs) have become the most popular weapons in cancer immunotherapy; however, they are only beneficial for a small fraction of patients. Accumulating evidence suggests that the tumor immune microenvironment (TIME) plays a critical role in anti-cancer immunity. This study aimed to assess the potential merits and feasibility of combinational targeting ICPs and TIME in cancer immunotherapy. A total of 31 cancer type-specific datasets in TCGA were individually collected by the publicly available web servers for multiple bioinformatic analyses of ICPs and TIME factors. GEPIA was used to calculate the prognostic indexes, STRING was used to construct protein-protein interactions, cBioPortal was used for visualization and comparison of genetic alterations, and TISIDB was used to explore the correlation to tumor-infiltrating lymphocytes (TILs). Intriguingly, TIME factors were identified to have more global coverage and prognostic significance across multiple cancer types compared with ICPs, thus offering more general targetability in clinical therapy. Moreover, TIME factors showed interactive potential with ICPs, and genomic alteration of TIME factors coupled with that of ICPs, at least in pancreatic cancer. Furthermore, TIME factors were found to be significantly associated with TILs, including but not limited to pancreatic cancer. Finally, the clinical significance and translational potential of further combination therapies that incorporate both ICP inhibitors and TIME factor-targeted treatments were discussed. Together, TIME factors are promising immunotherapeutic targets, and a combination strategy of TIME factors-targeted therapies with ICP inhibitors may benefit more cancer patients in the future.The emergence of immune checkpoint inhibitors (ICIs) has revolutionized the treatment of recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC). Biomarkers of the therapeutic efficacy of ICIs have been extensively investigated. In this study, we aimed to analyze whether molecular phenotypes of circulating tumor cells (CTCs) are associated with treatment responses and clinical outcomes in patients with R/M HNSCC treated with nivolumab. Peripheral blood samples were collected before treatment initiation and after four infusions of nivolumab. CTCs isolated by depletion of CD45-positive cells were analyzed to determine the expression of EPCAM, MET, KRT19, and EGFR using real-time quantitative polymerase chain reaction. CTC-positive samples were analyzed to determine the expression of PIK3CA, CCND1, SNAI1, VIM, ZEB2, CD44, NANOG, ALDH1A1, CD47, CD274, and PDCD1LG2. Of 30 patients treated with nivolumab, 28 (93.3%) were positive for CTCs. In 20 CTC-positive patients, molecular alterations in CTCs before and after nivolumab treatment were investigated. Patients with MET-positive CTCs had significantly shorter overall survival than those with MET-negative CTCs (p = 0.027). The expression level of CCND1 in CTCs of disease-controlled patients was significantly higher than that of disease-progressed patients (p = 0.034). In disease-controlled patients, the expression level of CCND1 in CTCs significantly decreased after nivolumab treatment (p = 0.043). The NANOG expression in CTCs was significantly increased in disease-controlled patients after nivolumab treatment (p = 0.036). Our findings suggest that the molecular profiling of CTCs is a promising tool to predict the treatment efficacy of nivolumab.Impaired sleep for hospital patients is an all too common reality. selleck products Sleep disruptions due to unnecessary overnight vital sign monitoring are associated with delirium, cognitive impairment, weakened immunity, hypertension, increased stress, and mortality. It is also one of the most common complaints of hospital patients while imposing additional burdens on healthcare providers. Previous efforts to forgo overnight vital sign measurements and improve patient sleep used providers' subjective stability assessment or utilized an expanded, thus harder to retrieve, set of vitals and laboratory results to predict overnight clinical risk. Here, we present a model that incorporates past values of a small set of vital signs and predicts overnight stability for any given patient-night. Using data obtained from a multi-hospital health system between 2012 and 2019, a recurrent deep neural network was trained and evaluated using ~2.3 million admissions and 26 million vital sign assessments. The algorithm is agnostic to patient location, condition, and demographics, and relies only on sequences of five vital sign measurements, a calculated Modified Early Warning Score, and patient age. We achieved an area under the receiver operating characteristic curve of 0.966 (95% confidence interval [CI] 0.956-0.967) on the retrospective testing set, and 0.971 (95% CI 0.965-0.974) on the prospective set to predict overnight patient stability. The model enables safe avoidance of overnight monitoring for ~50% of patient-nights, while only misclassifying 2 out of 10,000 patient-nights as stable. Our approach is straightforward to deploy, only requires regularly obtained vital signs, and delivers easily actionable clinical predictions for a peaceful sleep in hospitals.Patients with primary aldosteronism (PA) have a high prevalence of microalbuminuria (MAU), which leads to more severe systemic vascular damage. However, the primary recommended drug treatment for PA, spironolactone (SPL), has had poor patient compliance owing to its adverse effects, and the effect of SPL compliance on MAU has not been fully evaluated in patients with PA. We analyzed the effect of SPL compliance on endothelial dysfunction by assessing MAU in patients with PA. The study included 145 confirmed PA patients who received long-term medical treatment (mean, 5 years). As expected, compliance with SPL treatment improved patients' blood pressure and serum potassium levels. Patients with PA who complied fully with SPL treatment had a lower rate of MAU than noncompliant patients (13.73% versus 34.88%, respectively; P = 0.004). Multivariate logistic regression analyses adjusted for age and sex showed that continuous SPL treatment was associated with a lower presence of MAU (odds ratio, 0.319; 95% confidence interval, 0.