DNA damage response-related signatures characterize the immune landscape and predict the prognosis of HCC via integrating single-cell and bulk RNA-sequencing.

Background: The occurrence and progression of hepatocellular carcinoma (HCC) are significantly affected by DNA damage response (DDR). Exploring DDR-related biomarkers can help predict the prognosis and immune characteristics of HCC.

Methods: First, the single-cell RNA sequencing (scRNA-seq) dataset GSE242889 was processed and performed manual annotation.

Age-specific differences in association of glycosylated hemoglobin levels with the prevalence of cardiovascular diseases among nondiabetics: the National Health and Nutrition Examination Survey 2005-2018.

Background: Previous research has supported the presence of an association between high glycated hemoglobin (HbA1c) levels and cardiovascular disease (CVD). The objective of the present study was to determine whether increased HbA1c levels are associated with high CVD prevalence among nondiabetics. Furthermore, we aimed to explore the possible interaction of HbA1c levels and age in regard to CVD.

Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma.

Background: Psoriasis extends beyond its dermatological inflammatory manifestations, encompassing systemic inflammation. Existing studies have indicated a potential risk of cervical cancer among patients with psoriasis, suggesting a potential mechanism of co-morbidity. This study aims to explore the key genes, pathways, and immune cells that may link psoriasis and cervical squamous cell carcinoma (CESC).

Machine Learning-based Development and Validation of a Cell Senescence Predictive and Prognostic Signature in Intrahepatic Cholangiocarcinoma.

Previous studies have shown that cellular senescence is strongly associated with tumorigenesis and the tumor microenvironment. Accordingly, we developed a novel prognostic signature for intrahepatic cholangiocarcinoma (ICCA) based on senescence-associated long non-coding RNAs (SR-lncRNAs) and identified a lncRNA-miRNA-mRNA axis involving in ICCA. Based on the 197 senescence-associated genes (SRGs) from Genacards and their expression in Fu-ICCA cohort, we identified 20 lncRNAs as senescence-associated lncRNAs (SR-lncRNAs) through co-expression and cox-regression analysis.

Association between visceral adipose tissue and asthma based on the NHANES and Mendelian randomization study.

Background: Obesity is a crucial risk factor for asthma. Observational studies have examined the association between abdominal obesity and asthma symptoms. This study aimed to investigate the causal relationship between visceral adipose tissue (VAT) and asthma and its potential as an independent indicator.

PCDH8 is a novel prognostic biomarker in thyroid cancer and promotes cell proliferation and viability.

Protocadherin 8 (PCDH8), a calcium-dependent transmembrane protein in the protocadherin family, regulates cell adhesion and signal transduction. While some studies have provided indirect evidence that PCDH8 has cancer-promoting properties, this association is controversial. In particular, its involvement in thyroid cancer (THCA) remains unclear.

FOXC2-AS1/FOXC2 axis mediates matrix stiffness-induced trans-differentiation of hepatic stellate cells into fibrosis-promoting myofibroblasts.

Matrix stiffness is a central modulator of hepatic stellate cells (HSCs) activation and hepatic fibrogenesis. However, the long non-coding RNAs (lncRNAs)-regulated transcriptional factors linking matrix stiffness to alterations in HSCs phenotype are not completely understood. In this study, we investigated the effects of matrix stiffness on HSCs activation and its potential mechanism.