Skin Cancer

Animal Models of Allergen Immunotherapy for Allergic Airway Inflammation.

Allergen immunotherapy (AIT) is currently the only disease-modifying therapy for allergic airway inflammation. However, its underlying mechanisms remain incompletely understood, which in turn impede the development of more effective and durable treatment strategies. Although animal models are indispensable for mechanistic dissection and therapeutic innovation, they are limited by significant trans...

Neoantigen Targeting as a Novel Approach for Therapy-Resistant Tumors.

Neoantigens have emerged as central targets in the development of individualized cancer vaccines, as they are recognized by the immune system as foreign and can elicit potent anti-tumor responses. Advances in computational algorithms and machine learning have improved the accuracy of neoantigen prediction, and clinical trials have reported promising results of vaccines incorporating validated neoa...

Nanoparticle-based immunotherapeutic strategies to overcome cancer drug resistance: From biological barriers to artificial intelligence-driven design.

Although cancer immunotherapy has revolutionized oncology, its clinical efficacy remains substantially limited by both primary and acquired resistance...

KM-DBSCAN: an enhanced density and centroid based border detection framework for data reduction towards green AI.

Green AI aims to design and train machine learning models while taking into consideration sustainable resource usage without sacrificing model efficie...

Potential of SERS and proteomics for biomarker detection in cancer cells.

This study investigates the use of quantitative LC-MS/MS-based proteomics and surface-enhanced Raman spectroscopy (SERS) for biomarker detection in cl...

AI-driven body composition atlas reveals its association with NSCLC immunotherapy outcome and molecular background: a multicenter study.

Although previous studies have linked body composition to immunotherapy efficacy, comprehensive multidimensional analyses with biological explanations...

A novel cuproptosis-related prognostic gene signature is identified by machine learning and integrative analyses in gliomas.

Recent studies have highlighted the impact of copper-induced cell death (cuproptosis) on cancer progression, prognosis, and treatment, but it remains ...

IGH::FENDRR and specific KRAS mutations define a novel B-ALL molecular subtype with poor chemotherapy response.

Large scale sequencing efforts have defined up to 27 diagnostic entities in B-ALL, leaving few samples without subtype assignment. Extended genomic an...

Identification of MHC ligands through allele-guided isolation combined with machine learning for improved MHC assignment using ARDisplay-I.

The isolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for T cell-based immuno...

Etiologic diagnosis of seasonal allergic rhinitis supported by artificial intelligence: the @IT-2020 project.

BACKGROUND: A precise etiological diagnosis of seasonal allergic rhinitis (SAR) is essential for a tailored prescription of its only curative treatmen...

Quality, Empathy, and Readability of AI Chatbot Responses to the Survivorship Needs of Adolescents and Young Adults With Melanoma: Evaluation Study.

BACKGROUND: Melanoma, a highly aggressive form of skin cancer, is the second most common type of cancer for adolescent and young adult (AYA, ages 15-3...

In-silico study of machine learning discovers de novo lipogenesis for predicting prognosis and immunotherapy responses in kidney renal clear cell carcinoma.

Prospective Evidence on Artificial Intelligence-Assisted Melanoma Diagnostics: A Systematic Review and Meta-Analysis.

IMPORTANCE: Dermoscopy is a standard of care for melanoma diagnostics, and artificial intelligence (AI) systems are increasingly investigated as decis...

Framing bias in a large language model: Prompt framing influences ChatGPT's accuracy in melanoma classification. A diagnostic accuracy study.

Harnessing the gut microbiota in extra-intestinal cancers: from causal evidence to immunotherapy strategies.

The gut microbiota (GM) has emerged as a key modulator of cancer development and therapeutic response beyond the gastrointestinal tract. In extra-inte...

Microneedle-based theranostics for melanoma: Advances and outlook.

Melanoma represents a highly aggressive malignancy that poses persistent challenges for clinical diagnosis and treatment. Although surgical interventi...

Multidimensional data analysis and classification using SMIAL.

Label-free imaging enables multidimensional data acquisition across spectral and temporal domains and is increasingly used in life sciences. However, ...

Precision oncology meets nanotechnology: AI-driven liposomal nanocarriers for enhanced cancer immunotherapy.

The integration of artificial intelligence (AI) with nanotechnology is redefining therapeutic strategies in cancer immunotherapy and chemotherapy. The...

Unveiling the prognostic and therapeutic landscape of the zinc transporter protein SLC39A family in colorectal cancer through multi-omics and machine learning approaches.

Colorectal cancer (CRC) remains a significant global health challenge due to its high prevalence and mortality rates. Zinc transporter proteins of the...

Deciphering lung adenocarcinoma heterogeneity: a multi-omics approach reveals nuclear division fibroblasts as prognosticators and therapeutic targets.

BACKGROUND: Lung adenocarcinoma (LUAD) is a predominant contributor to cancer‑related mortality globally. Lung‑associated fibroblasts (LAFs) are intri...