The cellular-centered view of hypoxia tumor microenvironment: Molecular mechanisms and therapeutic interventions.

Cancer is a profoundly dynamic, heterogeneous and aggressive systemic ailment, with a coordinated evolution of various types of tumor niches. Hypoxia plays an indispensable role in the tumor micro-ecosystem, drastically enhancing the plasticity of cancer cells, fibroblasts and immune cells and orchestrating intercellular communication. Hypoxia-induced signals, particularly hypoxia-inducible factor-1α (HIF-1α), drive the reprogramming of genetic, transcriptional, and proteomic profiles. This leads to a spectrum of interconnected processes, including augmented survival of cancer cells, evasion of immune surveillance, metabolic reprogramming, remodeling of the extracellular matrix, and the development of resistance to conventional therapeutic modalities like radiotherapy and chemotherapy. Here, we summarize the latest research on the multifaceted effects of hypoxia, where a multitude of cellular and non-cellular elements crosstalk with each other and co-evolve in a synergistic manner. Additionally, we investigate therapeutic approaches targeting hypoxic niche, encompassing hypoxia-activated prodrugs, HIF inhibitors, nanomedicines, and combination therapies. Finally, we discuss some of the issues to be addressed and highlight the potential of emerging technologies in the treatment of cancer.

U-shaped association between serum calcium and in-hospital mortality in diabetes patients with congestive heart failure: a cohort study.

Previous studies have reported that the significant association between serum calcium and mortality substantially in patients, especially among those with intensive care unit (ICU). And In diabetes mellitus, congestive heart failure (CHF) is a significant comorbidity. We aim to evaluate the association between serum calcium levels and in-hospital mortality among patients with diabetes and congestive heart failure. The participants in this study were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. To scrutinize potential associations between serum calcium levels and in-hospital mortality, a comprehensive analysis encompassing multivariate logistic regression, cubic spline function model, threshold effect analysis, and subgroup analysis was performed. This retrospective cohort study encompassed 7063 patients, among whom the in-hospital mortality stood at 12.2%. In the multivariate logistic regression, adjusted odds ratios (ORs) were contrasted with the reference category Q6 (8.8-9.1 mg/dL) for serum calcium levels and in-hospital mortality. The adjusted ORs for Q1 (≤ 7.7 mg/dL), Q2 (7.7-8 mg/dL), and Q7 (≥ 9.1 mg/dL) were 1.69 (95% CI 1.17-2.44, p = 0.005), 1.62 (95% CI 1.11-2.36, p = 0.013), and 1.57 (95% CI 1.1-2.24, p = 0.012) respectively. The dose-response analysis uncovered a U-shaped relationship between serum calcium levels and in-hospital mortality in diabetic patients with heart failure. Subgroup analyses confirmed result stability notwithstanding the influence of diverse factors. Our investigation revealed a U-shaped correlation between serum calcium levels and in-hospital mortality in diabetes patients with congestive heart failure, pinpointing a significant inflection point at 9.05 mg/dL.

Association between different insulin resistance surrogates and all-cause mortality in patients with coronary heart disease and hypertension: NHANES longitudinal cohort study.

BACKGROUND: Studies on the relationship between insulin resistance (IR) surrogates and long-term all-cause mortality in patients with coronary heart disease (CHD) and hypertension are lacking. This study aimed to explore the relationship between different IR surrogates and all-cause mortality and identify valuable predictors of survival status in this population. METHODS: The data came from the National Health and Nutrition Examination Survey (NHANES 2001-2018) and National Death Index (NDI). Multivariate Cox regression and restricted cubic splines (RCS) were performed to evaluate the relationship between homeostatic model assessment of IR (HOMA-IR), triglyceride glucose index (TyG index), triglyceride glucose-body mass index (TyG-BMI index) and all-cause mortality. The recursive algorithm was conducted to calculate inflection points when segmenting effects were found. Then, segmented Kaplan-Meier analysis, LogRank tests, and multivariable Cox regression were carried out. Receiver operating characteristic (ROC) and calibration curves were drawn to evaluate the differentiation and accuracy of IR surrogates in predicting the all-cause mortality. Stratified analysis and interaction tests were conducted according to age, gender, diabetes, cancer, hypoglycemic and lipid-lowering drug use. RESULTS: 1126 participants were included in the study. During the median follow-up of 76 months, 455 participants died. RCS showed that HOMA-IR had a segmented effect on all-cause mortality. 3.59 was a statistically significant inflection point. When the HOMA-IR was less than 3.59, it was negatively associated with all-cause mortality [HR = 0.87,95%CI (0.78, 0.97)]. Conversely, when the HOMA-IR was greater than 3.59, it was positively associated with all-cause mortality [HR = 1.03,95%CI (1.00, 1.05)]. ROC and calibration curves indicated that HOMA-IR was a reliable predictor of survival status (area under curve = 0,812). No interactions between HOMA-IR and stratified variables were found. CONCLUSION: The relationship between HOMA-IR and all-cause mortality was U-shaped in patients with CHD and hypertension. HOMA-IR was a reliable predictor of all-cause mortality in this population.

Association of sleep characteristics with cardiovascular disease risk in adults over 40 years of age: a cross-sectional survey.

Background: The relationship between sleep characteristics and cardiovascular disease (CVD) risk has yet to reach a consistent conclusion, and more research needs to be carried out. This study aimed to explore the relationship between snoring, daytime sleepiness, bedtime, sleep duration, and high-risk sleep patterns with CVD risk. Methods: Data from the National Health and Nutrition Examination Survey (NHANES) 2015-2018 were collected and analyzed. Multivariable logistic regression was used to evaluate the relationship between snoring, daytime sleepiness, bedtime, sleep duration, high-risk sleep patterns, and CVD risk. Stratified analysis and interaction tests were carried out according to hypertension, diabetes and age. Results: The final analysis contained 6,830 participants, including 1,001 with CVD. Multivariable logistic regression suggested that the relationship between snoring [OR = 7.37,95%CI = (6.06,8.96)], daytime sleepiness [OR = 11.21,95%CI = (9.60,13.08)], sleep duration shorter than 7 h [OR = 9.50,95%CI = (7.65,11.79)] or longer than 8 h [OR = 6.61,95%CI = (5.33,8.19)], bedtime after 0:00 [OR = 13.20,95%CI = (9.78,17.80)] compared to 22:00-22:59, high-risk sleep patterns [OR = 47.73,95%CI = (36.73,62.04)] and CVD risk were statistically significant. Hypertension and diabetes interacted with high-risk sleep patterns, but age did not. Conclusions: Snoring, daytime sleepiness, excessive or short sleep duration, inappropriate bedtime, and high-risk sleep patterns composed of these factors are associated with the CVD risk. High-risk sleep patterns have a more significant impact on patients with hypertension and diabetes.