Allergy & Immunology

DCAF13 Regulates Cell Proliferation and Immune Escape of Hepatocellular Carcinoma Through Activating the NF-κB Pathway.

Hepatocellular carcinoma (HCC), the third leading cause of global cancer deaths, has a high unmet clinical need due to limited therapeutic efficacy. Immune escape mechanisms in the tumor microenvironment further complicate treatment. Advances in bioinformatics and machine learning offer potential for identifying novel biomarkers and therapeutic targets. This study aimed to identify immune-related ...

Development of an electronic health record-based Human Immunodeficiency Virus (HIV) risk prediction model for women, incorporating social determinants of health.

BACKGROUND: Human Immunodeficiency Virus (HIV) pre-exposure prophylaxis (PrEP) prevents HIV transmission but has low uptake among women. Identifying women who could benefit from PrEP remains a challenge. This study developed a women-specific model to predict HIV risk within a year using electronic health record (EHR) data and social determinants of health (SDoH).

Comprehensive machine learning analysis of PANoptosis signatures in multiple myeloma identifies prognostic and immunotherapy biomarkers.

PANoptosis is closely associated with tumorigenesis and therapeutic response, yet its role in multiple myeloma (MM) remains unclear. This study analyz...

Machine learning reveals genes impacting oxidative stress resistance across yeasts.

Reactive oxygen species (ROS) are highly reactive molecules encountered by yeasts during routine metabolism and during interactions with other organis...

Impact of tertiary lymphoid structure-associated biomarkers on pancreatic cancer via a dual-disease analysis of psoriasis and pancreatic cancer.

Pancreatic cancer (PC), often referred to as the "king of cancers", has demonstrated limited success with immunotherapies, many of which are still und...

Identification of aging-related biomarkers and immune infiltration analysis in renal stones by integrated bioinformatics analysis.

Renal stones (RS) are common urologic condition with unclear pathogenesis. Role of aging-related differentially expressed genes (ARDEGs) in RS remains...

Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, posing a significant threat to the life and health of people globally. LKB1...

Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer.

Emerging evidence suggests a bidirectional relationship between colorectal cancer (CRC) and type 2 diabetes mellitus (T2DM), yet the shared molecular ...

Consensus artificial intelligence-driven prognostic signature for predicting the prognosis of hepatocellular carcinoma: a multi-center and large-scale study.

Hepatocellular carcinoma (HCC), a leading cause of global cancer mortality, requires molecular stratification to advance precision oncology. This stud...

Regulatory T cells and matrix-producing cancer associated fibroblasts contribute on the immune resistance and progression of prognosis related tumor subtypes in ccRCC.

Clear cell renal cell carcinoma (ccRCC) is a prevalent malignant tumor in the field of urology. The effect of cell heterogeneity on the prognosis and ...

Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis.

Here we propose CovSF, a deep learning model designed to track and forecast short-term severity progression of COVID-19 patients using longitudinal cl...

A real-world data analysis of montelukast in FDA Adverse Event Reporting System (FAERS) database.

BACKGROUND: Montelukast(MTK) is a leukotriene receptor antagonist widely used clinically for treating asthma and rhinitis. However, many adverse event...

Boosting Checkpoint Blockade Immunotherapy with T Cell Membrane Redox Homeostasis Regulation and Deep Learning Enhanced NIR-II Imaging.

Immune checkpoint blockade therapy has revolutionized clinical oncotherapy by intercepting immunosuppressive pathways in tumor tissues. Nevertheless, ...

Biologics for severe asthma: deciphering what is best for the patient.

INTRODUCTION: Choosing the right biologic for the right patient is challenging. It requires evaluating patient characteristics and disease manifestati...

Avatar: Personalized Precision Radio-Genomic Theranostic Oncology.

Creation of a virtual avatar of a patient with cancer has the potential to transform theranostics into a truly individualized precision treatment of s...

Breath profiles in paediatric allergic asthma by proton transfer reaction mass spectrometry.

INTRODUCTION: Enhancing paediatric asthma diagnosis is crucial. Molecular analysis of exhaled breath is a rapidly evolving field aimed at harnessing e...

Multivariate Screening and Automated Clustering of Macrophage Immunoreactome to Nanoparticles and Photothermal Therapy.

Immunotherapy aims to control the immune system against diseases such as cancer or infections. Nanotechnology is part of the armamentarium to reprogra...

Non-invasive prediction of NSCLC immunotherapy efficacy and tumor microenvironment through unsupervised machine learning-driven CT Radiomic subtypes: a multi-cohort study.

BACKGROUND: Radiomics analyzes quantitative features from medical images to reveal tumor heterogeneity, offering new insights for diagnosis, prognosis...

A Machine Learning Analysis of Physiological Monitoring Signals to Detect Small Airway Narrowing Due to Cold Air Exposure in Asthma.

Asthma is a chronic inflammatory disease of the small airways, affecting over 200 million people globally. Cold air exposure is a potential risk facto...

Radiomic Model Associated with Tumor Microenvironment Predicts Immunotherapy Response and Prognosis in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma.

No robust biomarkers have been identified to predict the efficacy of programmed cell death protein 1 (PD-1) inhibitors in patients with locoregionall...