Association of red cell distribution width/albumin ratio and in hospital mortality in patients with atrial fibrillation base on medical information mart for intensive care IV database.

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia. The ratio of red cell distribution width (RDW) to albumin has been recognized as a reliable prognostic marker for poor outcomes in a variety of diseases. However, the evidence regarding the association between RDW to albumin ratio (RAR) and in hospital mortality in patients with AF admitted to the Intensive Care Unit (ICU) currently was unclear. The purpose of this study was to explore the association between RAR and in hospital mortality in patients with AF in the ICU. METHODS: This retrospective cohort study used data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database for the identification of patients with atrial fibrillation (AF). The primary endpoint investigated was in-hospital mortality. Multivariable-adjusted Cox regression analysis and forest plots were utilized to evaluate the correlation between the RAR and in-hospital mortality among patients with AF admitted to ICU. Additionally, receiver operating characteristic (ROC) curves were conducted to assess and compare the predictive efficacy of RDW and the RAR. RESULTS: Our study included 4,584 patients with AF with a mean age of 75.1 ± 12.3 years, 57% of whom were male. The in-hospital mortality was 20.3%. The relationship between RAR and in-hospital mortality was linear. The Cox proportional hazard model, adjusted for potential confounders, found a high RAR independently associated with in hospital mortality. For each increase of 1 unit in RAR, there is a 12% rise in the in-hospital mortality rate (95% CI 1.06-1.19). The ROC curves revealed that the discriminatory ability of the RAR was better than that of RDW. The area under the ROC curves (AUCs) for RAR and RDW were 0.651 (95%CI: 0.631-0.671) and 0.599 (95% CI: 0.579-0.620). CONCLUSIONS: RAR is independently correlated with in hospital mortality and in AF. High level of RAR is associated with increased in-hospital mortality rates.

Association between oxidative balance scores and severe abdominal aortic calcification in American adults: National health and nutrition examination survey.

BACKGROUND AND AIM: Abdominal aortic calcification (AAC) is a key predictor of cardiovascular diseases (CVDs). The Oxidative Balance Score (OBS) served as a tool to evaluate the systemic status of oxidative stress. However, evidence on the link between OBS and severe abdominal aortic calcification (SAAC) is currently inadequate. This study aims to establish this correlation in the US adult population, contributing valuable insights to the understanding of cardiovascular health. METHODS AND RESULTS: In our study with 2745 participants from the 2013-2014 National Health and Nutrition Examination Survey (NHANES), we analyzed both OBS and AAC score data. Logistic regression and smooth curve fitting were used to investigate the relationship between OBS and SAAC. The overall prevalence of severe abdominal aortic calcification disease was 9.1%. Multivariable logistic regression revealed that higher oxidative balance scores were associated with a lower risk of SAAC. After adjusting for potential confounders (model III), for every 1-point increase in oxidative balance scores, the odds of SAAC decreased by 3% [OR = 0.97, 95% CI= (0.95,0.99), P = 0.03]. The dose-response relationship demonstrated a negative correlation between oxidative balance scores and SAAC (p for nonlinear = 0.368). CONCLUSIONS: This study reveals a negative association between oxidative balance scores and severe abdominal aortic calcification in US adults. The implications of these findings merit careful consideration and should be taken into account in the formulation of clinical guidelines and updates.

Emerging function of main RNA methylation modifications in the immune microenvironment of digestive system tumors.

Digestive system tumors have been reported in more than 25% of all cancer cases worldwide, bringing a huge burden on the healthcare system. RNA methylation modification-an important post-transcriptional modification-has become an active research area in gene regulation. It is a dynamic and reversible process involving several enzymes, such as methyltransferases, demethylases, and methylation reader proteins. This review provides insights into the role of three major methylation modifications, namely m6A, m5C, and m1A, in the development of digestive system tumors, specifically in the development of tumor immune microenvironment (TIME) of these malignancies. Abnormal methylation modification affects immunosuppression and antitumor immune response by regulating the recruitment of immune cells and the release of immune factors. Understanding the mechanisms by which RNA methylation regulates digestive system tumors will be helpful in exploring new therapeutic targets.

Connectome-based prediction of cognitive performance in patients with temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) patients often exhibit varying degrees of cognitive impairments. This study aims to predict cognitive performance in TLE patients by applying a connectome-based predictive model (CPM) to whole-brain resting-state functional connectivity (RSFC) data. METHODS: A CPM was established and leave-one-out cross-validation was employed to decode the cognitive performance of patients with TLE based on the whole-brain RSFC. RESULTS: Our findings indicate that cognitive performance in TLE can be predicted through the internal and network connections of the parietal lobe, limbic lobe, and cerebellum systems. These systems play crucial roles in cognitive control, emotion processing, and social perception and communication, respectively. In the subgroup analysis, CPM successfully predicted TLE patients with and without focal to bilateral tonic-clonic seizures (FBCTS). Additionally, significant differences were noted between the two TLE patient groups and the normal control group. CONCLUSION: This data-driven approach provides evidence for the potential of predicting brain features based on the inherent resting-state brain network organization. Our study offers an initial step towards an individualized prediction of cognitive performance in TLE patients, which may be beneficial for diagnosis, prognosis, and treatment planning.

Clinical Significance of a Novel Vasculogenic Mimicry-Based Prognostic Model in Hepatocellular Carcinoma.

BACKGROUND: Vasculogenic mimicry, a novel neovascularization pattern of aggressive tumors, is associated with poor clinical outcomes. OBJECTIVE: The aim of this research was to establish a new model, termed VC score, to predict the prognosis, Tumor Microenvironment (TME) components, and immunotherapeutic response in Hepatocellular Carcinoma (HCC). METHODS: The expression data of the public databases were used to develop the prognostic model. Consensus clustering was performed to confirm the molecular subtypes with ideal clustering efficacy. The high- and low-risk groups were stratified utilizing the VC score. Various methodologies, including survival analysis, single-sample Gene Set Enrichment Analysis (ssGSEA), Tumor Immune Dysfunction and Exclusion scores (TIDE), Immunophenoscore (IPS), and nomogram, were utilized for verification of the model performance and to characterize the immune status of HCC tissues. GSEA was performed to mine functional pathway information. RESULTS: The survival and immune characteristics varied between the three molecular subtypes. A five-gene signature (TPX2, CDC20, CFHR4, SPP1, and NQO1) was verified to function as an independent predictive factor for the prognosis of patients with HCC. The high-risk group exhibited lower Overall Survival (OS) rates and higher mortality rates in comparison to the low-risk group. Patients in the low-risk group were predicted to benefit from immune checkpoint inhibitor therapy and exhibit increased sensitivity to immunotherapy. Enrichment analysis revealed that signaling pathways linked to the cell cycle and DNA replication processes exhibited enrichment in the high-risk group. CONCLUSIONS: The VC score holds the potential to establish individualized treatment plans and clinical management strategies for patients with HCC.

Cost-effectiveness of different intervention strategies of human immunodeficiency virus in Zhejiang, China: a Model Study From 2023 to 2052.

OBJECTIVE: :Mass screening for human immunodeficiency virus (HIV) and preexposure prophylaxis (PrEP) may be effective measures for reducing the probability of HIV transmission. Our study aimed to determine the cost-effectiveness of preliminary screening in the general population, PrEP for HIV-negative spouses in serodiscordant couples, or both approaches in Zhejiang Province. DESIGN: :From a policy-maker's perspective, a Markov model was constructed to compare 4 strategies over a 30-year horizon. METHODS: :In the Markov model, the implementation intensities of the strategies varied from 50% to 100%. Different strategies were evaluated by the reduction of unfavorable clinical outcomes, saved life-years (LYs), quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), and net monetary benefits (NMBs). RESULTS: :The PrEP-Screening strategy reduced the most unfavorable clinical outcomes and saved the most LYs and QALYs from 2023 to 2052. It always gained the maximum QALYs and NMB, while its ICER was always lower than the willingness-to-pay (WTP). The NMB of the PrEP-Screening strategy gradually increased as the implementation intensity increased. CONCLUSIONS: :With adequate manpower and policies, we suggest implementing the PrEP-Screening strategy in Zhejiang Province, suggesting that the broader the population coverage of the strategy, the better. In addition, the PrEP strategy is an alternative.

Prognostic and immune predictive roles of a novel tricarboxylic acid cycle-based model in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer. Since the tricarboxylic acid cycle is widely involved in tumor metabolic reprogramming and cuproptosis, investigating related genes may help to identify prognostic signature of patients with HCC. Data on patients with HCC were sourced from public datasets, and were divided into train, test, and single-cell cohorts. A variety of machine learning algorithms were used to identify different molecular subtypes and determine the prognostic risk model. Our findings revealed that the risk score (TRscore), based on the genes OGDHL, CFHR4, and SPP1, showed excellent predictive performance in different datasets. Pathways related to cell cycle and immune inflammation were enriched in the high-risk group, whereas metabolism-related pathways were significantly enriched in the low-risk group. The high-risk group was associated with a greater number of mutations of detrimental biological behavior and higher levels of immune infiltration, immune checkpoint expression, and anti-cancer immunotherapy response. Low-risk patients demonstrated greater sensitivity to erlotinib and phenformin. SPP1 was mainly involved in the interaction among tumor-associated macrophages, T cells, and malignant cells via SPP1-CD44 and SPP1-(ITGA5 + ITGB1) ligand-receptor pairs. In summary, our study established a prognostic model, which may contribute to individualized treatment and clinical management of patients with HCC.

Unraveling the mechanisms of NK cell dysfunction in aging and Alzheimer's disease: insights from GWAS and single-cell transcriptomics.

Background: Aging is an important factor in the development of Alzheimer's disease (AD). The senescent cells can be recognized and removed by NK cells. However, NK cell function is gradually inactivated with age. Therefore, this study used senescence as an entry point to investigate how NK cells affect AD. Methods: The study validated the correlation between cognition and aging through a prospective cohort of the National Health and Nutrition Examination Survey database. A cellular trajectory analysis of the aging population was performed using single-cell nuclear transcriptome sequencing data from patients with AD and different ages. The genome-wide association study (GWAS) cohort of AD patients was used as the outcome event, and the expression quantitative trait locus was used as an instrumental variable. Causal associations between genes and AD were analyzed by bidirectional Mendelian randomization (MR) and co-localization. Finally, clinical cohorts were constructed to validate the expression of key genes. Results: A correlation between cognition and aging was demonstrated using 2,171 older adults over 60 years of age. Gene regulation analysis revealed that most of the highly active transcription factors were concentrated in the NK cell subpopulation of AD. NK cell trajectories were constructed for different age populations. MR and co-localization analyses revealed that CHD6 may be one of the factors influencing AD. Conclusion: We explored different levels of AD and aging from population cohorts, single-cell data, and GWAS cohorts and found that there may be some correlations of NK cells between aging and AD. It also provides some basis for potential causation.