Atopy

Convergence: Multi-omics and AI are reshaping the landscape biomedical research.

This special volume of Biochimica et Biophysica Acta - Molecular Basis of Disease showcases a transformative era in biomedical research, driven by the convergence of multi-omics technologies, artificial intelligence (AI), and systems biology. The volume is focused across eight thematic sections-spanning cancer, inflammatory and infectious diseases, neurodegeneration, cardiovascular health, autopha...

A machine learning-driven transcriptomic study reveals the key role of Romo1 in reversing central sensitization through stellate ganglion block in migraine: An interventional study based on a recurrent migraine rat model.

OBJECTIVES/BACKGROUND: This study utilized a nitroglycerin (NTG)-induced chronic migraine rat model to explore the therapeutic effects and underlying mechanisms of stellate ganglion block (SGB), aiming to clarify the potential pathogenesis of migraine. Central sensitization is key to chronic migraine development. SGB effectively treats chronic pain by reducing sympathetic tone and inhibiting centr...

A machine learning platform for genotype-specific cardiotoxicity risk prediction using patient-derived iPSC-CMs.

INTRODUCTION: Drug-induced Torsades de Pointes (TdP) has led to withdrawal of several drugs from the market. Individuals with inherited cardiac channe...

Artificial intelligence in smartphone video analysis for equine asthma diagnostic support.

BACKGROUND: Equine asthma is a prevalent respiratory disease that negatively impacts horses' health and athletic performance. Traditional diagnostic m...

Artificial Intelligence Performance in Pediatric Asthma.

OBJECTIVE: Asthma is the most common chronic disease of childhood, characterized by symptoms such as wheezing, shortness of breath, and coughing. With...

Automated detection of air trapping from mechanical ventilation waveform through interpretable dual-channel 1D convolutional neural network.

. Air trapping is a major symptom of respiratory diseases like chronic obstructive pulmonary disease and asthma, and has always been a significant pro...

Anoikis-related biomarkers PARP1 and SDCBP as diagnostic and therapeutic targets for asthma.

This study aims to explore the association between anoikis-related genes (ARGs) and asthma. The dataset GSE143303 for asthma were sourced from the GEO...

Shape matters: inferring the motility of confluent cells from static images.

Cell motility in dense cell collectives is pivotal in various diseases like cancer metastasis and asthma. A central aspect in these phenomena is the h...

Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data.

OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep cluster...

Disease Classification of Pulmonary Xenon Ventilation MRI Using Artificial Intelligence.

RATIONALE AND OBJECTIVES: Hyperpolarized Xenon magnetic resonance imaging (MRI) measures the extent of lung ventilation by ventilation defect percent ...

Identification and single-cell analysis of prognostic genes related to mitochondrial and neutrophil extracellular traps in bladder cancer.

The development of bladder cancer (BLCA) is associated with mitochondrial dysfunction and neutrophil extracellular traps (NETs); however, the relation...

Deep learning deciphers the related role of master regulators and G-quadruplexes in tissue specification.

G-quadruplexes (GQs) are non-canonical DNA structures encoded by G-flipons with potential roles in gene regulation and chromatin structure. Here, we e...

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...

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...

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...

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...

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...

The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolit...

Machine Learning-Based Biomarker Discovery from Serum Trace Elements and Biochemical Parameters in Patients with Nasal Polyps.

Nasal polyps (NP) are benign mucosal outgrowths associated with chronic inflammation that can significantly reduce quality of life. This study aimed t...

Microglial pruning of glycinergic synapses disinhibits spinal PKCγ interneurons to drive pain hypersensitivity in mice.

Microglial activation is linked to neuroinflammation in neuropathic pain. Recently, microglia-mediated synaptic pruning has received mounting attentio...