AIMC Topic: Mice

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Integrating necroptosis into pan-cancer immunotherapy: a new era of personalized treatment.

Frontiers in immunology
INTRODUCTION: Necroptosis has emerged as a promising biomarker for predicting immunotherapy responses across various cancer types. Its role in modulating immune activation and therapeutic outcomes offers potential for precision oncology.

Unraveling pathogenesis and potential biomarkers for autism spectrum disorder associated with HIF1A pathway based on machine learning and experiment validation.

Neurobiology of disease
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a high social burden and limited treatments. Hypoxic condition of the brain is considered an important pathological mechanism of ASD. HIF1A is a key participant in brain...

Machine learning-aided discovery of T790M-mutant EGFR inhibitor CDDO-Me effectively suppresses non-small cell lung cancer growth.

Cell communication and signaling : CCS
BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long durational erlotinib treatment of non-small cell lung cancer (NSCLC) patients, leading to drug resistance and disease progression. Identification of new selec...

Early colorectal cancer detection: a serum analysis platform combining SERS and machine learning.

Analytical methods : advancing methods and applications
Colorectal cancer (CRC) is one of the deadliest malignancies globally, with high incidence and mortality rates. Early detection is crucial for improving treatment success rates and patient survival. However, due to the difficulty in detecting early s...

Machine learning-based analysis of programmed cell death types and key genes in intervertebral disc degeneration.

Apoptosis : an international journal on programmed cell death
Intervertebral disc degeneration (IVDD) is intricately associated with various forms of programmed cell death (PCD). Identifying key PCD types and associated genes is essential for understanding the molecular mechanisms underlying IVDD and discoverin...

Identification of structural stability and fragility of mouse liver glycogen via label-free Raman spectroscopy coupled with convolutional neural network algorithm.

International journal of biological macromolecules
Glycogen structure is closely associated with its physiological functions. Previous studies confirmed that liver glycogen structure had two dominant states: mainly stable during the day and largely fragile at night. However, the diurnal change of gly...

Exploring an novel diagnostic gene of trastuzumab-induced cardiotoxicity based on bioinformatics and machine learning.

Scientific reports
Trastuzumab (Tra)-induced cardiotoxicity (TIC) is a serious side effect of cancer chemotherapy, which can seriously harm the health of cancer patients. However, there is currently a lack of effective and reliable biomarkers for the early diagnosis of...

High-content imaging and deep learning-driven detection of infectious bacteria in wounds.

Bioprocess and biosystems engineering
Fast and accurate detection of infectious bacteria in wounds is crucial for effective clinical treatment. However, traditional methods take over 24 h to yield results, which is inadequate for urgent clinical needs. Here, we introduce a deep learning-...

Identification of an immune-related gene panel for the diagnosis of pulmonary arterial hypertension using bioinformatics and machine learning.

International immunopharmacology
OBJECTIVE: This study aimed to screen an immune-related gene (IRG) panel and develop a novel approach for diagnosing pulmonary arterial hypertension (PAH) utilizing bioinformatics and machine learning (ML).

Accurate Spatial Heterogeneity Dissection and Gene Regulation Interpretation for Spatial Transcriptomics using Dual Graph Contrastive Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Recent advances in spatial transcriptomics have enabled simultaneous preservation of high-throughput gene expression profiles and the spatial context, enabling high-resolution exploration of distinct regional characterization in tissue. To effectivel...