Allergy

Chaperonin containing TCP1 subunit 5 as a novel pan-cancer prognostic biomarker for tumor stemness and immunotherapy response: insights from multi-omics data, integrated machine learning, and experimental validation.

BACKGROUND: Chaperonin containing TCP1 subunit 5 (CCT5), a vital component of the molecular chaperonin complex, has been implicated in tumorigenesis, cancer stemness maintenance, and therapeutic resistance. Nevertheless, its comprehensive roles in pan-cancer progression, underlying biological functions, and potential as a predictor of immunotherapy response remains poorly understood.

Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC), a cancer characterized by substantial immune infiltration, exhibits limited sensitivity to conventional radiochemotherapy. Although immunotherapy has shown efficacy in some patients, its applicability is not universally effective. Studies have indicated that programmed cell death (PCD) can modulate the activity of immune cells and participate in the regula...

VLM Models and Automated Grading of Atopic Dermatitis

The task of grading atopic dermatitis (or AD, a form of eczema) from patient images is difficult even for trained dermatologists. Research on automa...

Identification of molecular subtypes and a prognostic signature based on machine learning and purine metabolism-related genes in breast cancer.

Breast cancer (BC), one of the most prevalent malignant tumors worldwide, lacks efficacious diagnostic biomarkers and therapeutic targets. This study ...

AI-Driven Multiscale Study on the Mechanism of Polygonati Rhizoma in Regulating Immune Function in STAD.

Polygonati Rhizoma, a traditional Chinese medicine, has demonstrated immunomodulatory and anticancer properties, yet its precise mechanisms in stomach...

MMRNet: Ensemble deep learning models for predicting mismatch repair deficiency in endometrial cancer from histopathological images.

Combining molecular classification with clinicopathologic methods improves risk assessment and chooses therapies for endometrial cancer (EC). Detectin...

Feasibility of machine learning-based modeling and prediction to assess osteosarcoma outcomes.

Osteosarcoma, an aggressive bone malignancy predominantly affecting children and adolescents, is characterized by a poor prognosis and high mortality ...

Machine learning and single-cell analysis uncover distinctive characteristics of CD300LG within the TNBC immune microenvironment: experimental validation.

Investigating the essential function of CD300LG within the tumor microenvironment in triple-negative breast cancer (TNBC). Transcriptomic and single-c...

A machine learning-based glycolysis and fatty acid metabolism-related prognostic signature is constructed and identified ACSL5 as a novel marker inhibiting the proliferation of breast cancer.

INTRODUCTION: A new perspective on cancer metabolism suggests that it varies by context and is diverse. Cancer metabolism reprogramming can create a h...

Boosting Immunity Through Nutrition and Gut Health: A Narrative Review on Managing Allergies and Multimorbidity.

The increasing global burden of allergic diseases and multimorbidity underscores the urgent need for innovative strategies to strengthen immune health...

Integrating ultrasound and serum indicators for evaluating outcomes of targeted immunotherapy in advanced liver cancer.

BACKGROUND: Hepatocellular carcinoma (HCC) is a major global contributor to cancer-related mortality, with advanced stages presenting substantial ther...

Artificial intelligence-enabled precision medicine for inflammatory skin diseases

Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing dermatology. Generative AI and machine learning a...

Single-cell RNA sequencing reveals immunological link between house dust mite allergy and childhood asthma.

Allergic asthma in children is typically associated with house dust mites (HDM) as the key allergen. Nevertheless, the diagnostic rate remains below 6...

Development and validation of a deep learning model for diagnosing neuropathic corneal pain via in vivo confocal microscopy.

Neuropathic corneal pain (NCP) is an underdiagnosed ocular disorder caused by aberrant nociception and hypersensitivity of corneal nerves, often resul...

Artificial intelligence-enabled precision medicine for inflammatory skin diseases.

Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing dermatology. Generative AI and machine learning app...

IntrinsicEdit: Precise generative image manipulation in intrinsic space

Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. How...

Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer.

Prostate cancer (PCa) remains a leading cause of cancer-related mortality, necessitating robust prognostic models and personalized therapeutic strateg...

Targeting high-risk multiple myeloma genotypes with optimized anti-CD70 CAR-T cells.

Despite the success of BCMA-targeting CAR-Ts in multiple myeloma, patients with high-risk cytogenetic features still relapse most quickly and are in u...

Identifying Mild-to-Moderate Atopic Dermatitis Using a Generic Machine Learning Approach: A Danish National Health Register Study.

Atopic dermatitis is a chronic skin disease, causing itching and recurrent eczematous lesions. In Danish national register data, adults with atopic de...

Construction of a novel CD8T cell-related index for predicting clinical outcomes and immune landscape in ovarian cancer by combined single-cell and RNA-sequencing analysis.

BACKGROUND: CD8T cells, also known as cytotoxic T lymphocytes, play a key role in the tumor immune microenvironment (TME) and immune response. The aim...