Unveiling Cuproptosis-Driven Molecular Clusters and Immune Dysregulation in Ankylosing Spondylitis.

Background: Ankylosing spondylitis (AS) is a chronic autoimmune disease characterized by inflammation of the sacroiliac joints and spine. Cuproptosis is a newly recognized copper-induced cell death mechanism. Our study explored the novel role of cuproptosis-related genes (CRGs) in AS, focusing on immune cell infiltration and molecular clustering.

Comprehensive Sepsis Risk Prediction in Leukemia Using a Random Forest Model and Restricted Cubic Spline Analysis.

Background: Sepsis is a severe complication in leukemia patients, contributing to high mortality rates. Identifying early predictors of sepsis is crucial for timely intervention. This study aimed to develop and validate a predictive model for sepsis risk in leukemia patients using machine learning techniques.

Identification of Anoikis-Related Genes in Chronic Kidney Disease Based on Bioinformatics Analysis Combined with Experimental Validation.

Background: Chronic kidney disease (CKD) is a progressive condition that arises from diverse etiological factors, resulting in structural alterations and functional impairment of the kidneys. We aimed to establish the Anoikis-related gene signature in CKD by bioinformatics analysis.

Methods: We retrieved 3 datasets from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) of them, which were intersected with Anoikis-related genes (ARGs) to derive Anoikis-related differentially expressed genes (ARDEGs).

Launching a child and adolescent psychiatry training program in Mongolia inspired by Japanese models.

This manuscript details the development and implementation of Mongolia's first official training program for child and adolescent psychiatry (CAP) specialists. This initiative, inspired by and developed in collaboration with Japanese CAP training models, addresses the substantial gap in specialized mental health services for children and adolescents in Mongolia. Our discussion elaborates on the collaborative efforts between the Mongolian National University of Medical Sciences, Nagoya University, and other partnering institutions, reflecting on the initial outcomes and the strategic importance of this program.

Predictive model for assessing the prognosis of rhabdomyolysis patients in the intensive care unit.

Background: Rhabdomyolysis (RM) frequently gives rise to diverse complications, ultimately leading to an unfavorable prognosis for patients. Consequently, there is a pressing need for early prediction of survival rates among RM patients, yet reliable and effective predictive models are currently scarce.

Methods: All data utilized in this study were sourced from the MIMIC-IV database.

Chromosome Numbers and Reproductive Life Cycles in Green Plants: A Phylotranscriptomic Perspective.

The strong correlation between reproductive life cycle type and chromosome numbers in green plants has been a long-standing mystery in evolutionary biology. Within green plants, the derived condition of heterosporous reproduction has emerged from the ancestral condition of homospory in disparate locations on the phylogenetic tree at least 11 times, of which three lineages are extant. In all green plant lineages where heterospory has emerged, there has been a significant downsizing in chromosome numbers.

Exploring using HBsAg to predict interferon treatment course to achieve clinical cure in chronic hepatitis B patients: a clinical study.

Objective: Although pegylated interferon α-2b (PEG-IFN α-2b) therapy for chronic hepatitis B has received increasing attention, determining the optimal treatment course remains challenging. This research aimed to develop an efficient model for predicting interferon (IFN) treatment course.

Methods: Patients with chronic hepatitis B, undergoing PEG-IFN α-2b monotherapy or combined with NAs (Nucleoside Analogs), were recruited from January 2018 to December 2023 at Tianjin Third Central Hospital.

ScRNA-seq unveils the functional characteristics of glioma-associated macrophages and the regulatory effects of chlorogenic acid on the immune microenvironment-a study based on mouse models and clinical practice.

Introduction: Glioma is the most common primary malignant brain tumor. Despite advances in surgical techniques and treatment regimens, the therapeutic effects of glioma remain unsatisfactory. Immunotherapy has brought new hope to glioma patients, but its therapeutic outcomes are limited by the immunosuppressive nature of the tumor microenvironment (TME).

Single-cell transcriptome analysis of medaka lymphocytes reveals absence of fully mature T cells in the thymus and the T-lineage commitment in the kidney.

The cellular and molecular mechanisms underlying lymphocyte development are diverse among teleost species. Although recent scRNA-seq analyses of zebrafish hematopoietic cells have advanced our understanding of teleost hematopoiesis, comparative studies using another genetic model, medaka, which is evolutionarily distant among teleosts, is useful for understanding commonality and species-specificity in teleosts. In order to gain insight into how different molecular and cellular mechanisms of lymphocyte development in medaka and zebrafish, we established a () mutant medaka, which exhibited defects in V(D)J rearrangement of lymphocyte antigen receptor genes, accordingly lacking mature B and T cells.

Glycosylation profiling of triple-negative breast cancer: clinical and immune correlations and identification of LMAN1L as a biomarker and therapeutic target.

Introduction: Breast cancer (BC) is the most prevalent malignant tumor in women, with triple-negative breast cancer (TNBC) showing the poorest prognosis among all subtypes. Glycosylation is increasingly recognized as a critical biomarker in the tumor microenvironment, particularly in BC. However, the glycosylation-related genes associated with TNBC have not yet been defined.

Development and external validation of a model to predict recurrence in patients with non-muscle invasive bladder cancer.

Background: Most patients initially diagnosed with non-muscle invasive bladder cancer (NMIBC) still have frequent recurrence after urethral bladder tumor electrodesiccation supplemented with intravesical instillation therapy, and their risk of recurrence is difficult to predict. Risk prediction models used to predict postoperative recurrence in patients with NMIBC have limitations, such as a limited number of included cases and a lack of validation. Therefore, there is an urgent need to develop new models to compensate for the shortcomings and potentially provide evidence for predicting postoperative recurrence in NMIBC patients.

Developing and validating a machine learning model to predict multidrug-resistant -related septic shock.

Background: Multidrug-resistant Klebsiella pneumoniae (MDR-KP) infections pose a significant global healthcare challenge, particularly due to the high mortality risk associated with septic shock. This study aimed to develop and validate a machine learning-based model to predict the risk of MDR-KP-associated septic shock, enabling early risk stratification and targeted interventions.

Methods: A retrospective analysis was conducted on 1,385 patients with MDR-KP infections admitted between January 2019 and June 2024.

Loss of increases type I interferon signalling and reduces pancreatic tumour growth by enhancing immune cell infiltration.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal forms of cancer, and despite low incidence rates, it remains the sixth leading cause of cancer related deaths worldwide. Immunotherapy, which aims to enhance the immune system's ability to recognize and eliminate cancer cells, has emerged as a promising approach in the battle against PDAC. PARP7, a mono-ADP-ribosyltransferase, is a negative regulator of the type I interferon (IFN-I) pathway and has been reported to reduce anti-tumour immunity.

Comparative efficacy and safety of different recommended doses of telitacicept in patients with systemic lupus erythematosus in China: a systematic review and meta-analysis.

Background: Telitacicept, a new biological agent, was approved in China for treating systemic lupus erythematosus (SLE) in 2021. Its optimal dosing for treating SLE remains unclear. Therefore, the aim of this meta-analysis is to evaluate the efficacy and safety of various telitacicept doses in SLE treatment.

A peptide mimic of SOCS1 modulates equine peripheral immune cells and ocular effector functions : implications for recurrent uveitis.

Introduction: Recurrent uveitis (RU), an autoimmune disease, is a leading cause of ocular detriment in humans and horses. Equine and human RU share many similarities including spontaneous disease and aberrant cytokine signaling. Reduced levels of SOCS1, a critical regulator of cytokine signaling, is associated with several autoimmune diseases.

Interaction with IGF1 overrides ANXA2-mediated anti-inflammatory functions of IGFBP5 .

Background: is a differentially expressed gene (DEG) between M1 and M2 macrophages. This study explained why it causes opposite effects in different circumstances.

Methods: Gene expression profiles of various cell subsets were compared by mining a public database.

Association between complete blood cell count-derived inflammatory biomarkers and gallstones prevalence in American adults under 60 years of age.

Background: The trend of gallstones occurring in younger populations has become a noteworthy public health issue. This study aims to investigate the association between complete blood cell count (CBC)-derived inflammatory indicators and gallstones in adults under 60 years of age in the United States.

Methods: This cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) from 2017 to 2020.

Development and validation of a glycolysis-associated gene signature for predicting the prognosis, immune landscape, and drug sensitivity in bladder cancer.

Background: Bladder cancer (BCa) is one of the most common malignancies worldwide, and its prognostication and treatment remains challenging. The fast growth of various cancer cells requires reprogramming of its energy metabolism using aerobic glycolysis as a major energy source. However, the prognostic and therapeutic value of glycolysis-related genes in BCa remains to be determined.

Integrated Microbiome and Metabolome Analysis Reveals Correlations Between Gut Microbiota Components and Metabolic Profiles in Mice With Mitoxantrone-Induced Cardiotoxicity.

Purpose: Mitoxantrone (MTX) is largely restricted in clinical usage due to its significant cardiotoxicity. Multiple studies have shown that an imbalance in the gut-heart axis plays an important role in the development of cardiovascular disease (CVD). We aim to explore the possible correlations between gut microbiota (GM) compositions and cardiometabolic (CM) disorder in MTX-triggered cardiotoxicity mice.

Comprehensive Analysis of Metabolic Changes in Mice Exposed to Corilagin Based on GC-MS Analysis.

Background: Corilagin is widely distributed in various medicinal plants. In recent years, numerous pharmacological activities of Corilagin have been reported, including anti-inflammatory, antiviral, hepatoprotective, anti-tumor, and anti-fibrosis effects. However, there is still a need for systematic metabolomics analysis to further elucidate its mechanisms of action.

Prognostic value of TIMI risk score combined with systemic immune-inflammation index and lipoprotein(a) in patients with ST-Segment elevation myocardial infarction after percutaneous coronary intervention.

Background: Thrombolysis in Myocardial Infarction (TIMI) risk score in patients with ST-segment elevation myocardial infarction (STEMI) is associated with major adverse cardiovascular events (MACE). This study aimed to develop a prediction model based on the TIMI risk score for MACE in STEMI patients after percutaneous coronary intervention (PCI).

Methods: We conducted a retrospective data analysis on 290 acute STEMI patients admitted to the Affiliated Hospital of Yangzhou University from January 2022 to June 2023 and met the inclusion criteria.

Lyme disease associated neurological and musculoskeletal symptoms: A systematic review and meta-analysis.

Background And Objective: Lyme disease, caused by , presents major health challenges worldwide, leading to serious neurological and musculoskeletal issues that impact patients' lives and healthcare systems. This systematic review and meta-analysis aim to determine the prevalence and link between Lyme disease and these complications, aiming to enhance clinical and public health approaches.

Methods: We systematically searched PubMed, EMBASE, and Web of Science up until April 01, 2024, to find studies reporting the prevalence and severity of neurological and musculoskeletal complications associated with Lyme disease.

Association of a multiplex immune marker panel with incident cognitive impairment and dementia: The Northern Manhattan Study.

Objective: To determine whether a panel of immune markers adds significant information to known correlates of risk of dementia and cognitive impairment.

Background: The impact of immune mechanisms on dementia risk is incompletely characterized.

Design/methods: A subsample of the Northern Manhattan Study, a prospective cohort study in the racially/ethnically diverse population of New York City, underwent comprehensive neuropsychological testing up to three times, at approximately 5-year intervals.

Methodological Approaches to Comparative Trend Analyses: The Case of Adolescent Toothbrushing.

Objectives: Research questions about how and why health trends differ between populations require decisions about data analytic procedure. The objective was to document and compare the information returned from stratified, fixed effect and random effect approaches to data modelling for two prototypical descriptive research questions about comparative trends in toothbrushing.

Methods: Data included five cycles of the Health Behaviour in School-aged Children 2006 to 2022, which provided a sample of 980192 11- to 15- year olds from 35 countries.

Associations between degree of food processing and all-cause and cause-specific mortality: a multicentre prospective cohort analysis in 9 European countries.

Background: Ultra-processed food (UPF) consumption has been linked with higher risk of mortality. This multi-centre study investigated associations between food intake by degree of processing, using the Nova classification, and all-cause and cause-specific mortality.

Methods: This study analyzed data from the European Prospective Investigation into Cancer and Nutrition.