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Allergens

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Predicting the therapeutic efficacy of AIT for asthma using clinical characteristics, serum allergen detection metrics, and machine learning techniques.

Computers in biology and medicine
Bronchial asthma is a prevalent non-communicable disease among children. The study collected clinical data from 390 children aged 4-17 years with asthma, with or without rhinitis, who received allergen immunotherapy (AIT). Combining these data, this ...

Hot topics in allergen immunotherapy, 2023: Current status and future perspective.

Allergy
The importance of allergen immunotherapy (AIT) is multifaceted, encompassing both clinical and quality-of-life improvements and cost-effectiveness in the long term. Key mechanisms of allergen tolerance induced by AIT include changes in memory type al...

Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds.

PeerJ
BACKGROUND: To enhance the accuracy of allergen detection in cosmetic compounds, we developed a co-culture system that combines HaCaT keratinocytes (transfected with a luciferase plasmid driven by the AKR1C2 promoter) and THP-1 cells for machine lear...

Identifying influence factors and thresholds of the next day's pollen concentration in different seasons using interpretable machine learning.

The Science of the total environment
The prevalence of pollen allergies is a pressing global issue, with projections suggesting that half of the world's population will be affected by 2050 according to the estimation of the World Health Organization (WHO). Accurately forecasting pollen ...

SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features.

International journal of biological macromolecules
Allergy is a hypersensitive condition in which individuals develop objective symptoms when exposed to harmless substances at a dose that would cause no harm to a "normal" person. Most current computational methods for allergen identification rely on ...

Preservative contact allergy in occupational dermatitis: a machine learning analysis.

Archives of dermatological research
Occupational dermatoses impose a significant socioeconomic burden. Allergic contact dermatitis related to occupation is prevalent among healthcare workers, cleaning service personnel, individuals in the beauty industry and industrial workers. Among r...

Alg-MFDL: A multi-feature deep learning framework for allergenic proteins prediction.

Analytical biochemistry
The escalating global incidence of allergy patients illustrates the growing impact of allergic issues on global health. Allergens are small molecule antigens that trigger allergic reactions. A widely recognized strategy for allergy prevention involve...

Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning.

Nature communications
Regional responses to inhaled toxicants are essential to understand the pathogenesis of lung disease under exposure to air pollution. We evaluate the effect of combined allergen sensitization and ozone exposure on eliciting spatial differences in lip...

Machine Learning-Assisted Portable Dual-Readout Biosensor for Visual Detection of Milk Allergen.

Nano letters
Beta-lactoglobulin (β-LG), the primary allergen in cow's milk, makes developing a rapid, sensitive, and convenient detection method essential for individuals with allergies. In this study, a graphdiyne-based self-powered electrochemical biosensor has...