Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Antigens Involved in Adaptive Immunity01:26

Antigens Involved in Adaptive Immunity

An antigen is any substance the immune system identifies as foreign and potentially harmful to the body, prompting an immune response. Antigens have two functional properties: immunogenicity and reactivity. Immunogenicity is the ability of an antigen to stimulate a specific immune response. At the same time, reactivity describes the antigen's ability to react with the cells and antibodies produced in response to it.
Complete Antigens
Complete antigens possess both immunogenicity and reactivity.
Cross-reactivity00:42

Cross-reactivity

Overview
Allergic Reactions02:06

Allergic Reactions

Overview
Allergic Reactions: Anaphylaxis01:30

Allergic Reactions: Anaphylaxis

Anaphylaxis is a severe, life-threatening hypersensitivity reaction mediated by Immunoglobulin E (IgE) antibodies. When IgE binds to allergens, it triggers the release of mediators– histamine, leukotrienes, and prostaglandins from mast cells and basophils. These mediators cause vasodilation, edema, and inflammation, leading to various symptoms.The primary allergens causing anaphylaxis include food items (e.g., peanuts, shellfish), drugs (e.g., penicillin, asparaginase, corticotropin, heparin),...
Antibody Structure01:10

Antibody Structure

Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
Allergic Drug Reactions01:27

Allergic Drug Reactions

Allergic reactions related to drugs are hypersensitivity responses driven by the immune system and bear no connection to the drug's therapeutic action. While drugs in isolation do not trigger an immune response, they can interact with endogenous proteins to form antigens. These antigens stimulate lymphocytes to produce antibodies. IgE-type antibodies attach themselves to mast cells. Upon subsequent exposure to the same stimulus, the antigen-antibody interaction is initiated, unleashing numerous...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The Effect of Cu<sup>2+</sup> and Zn<sup>2+</sup> Ions' Nonbonded Interactions on the Aggregation of β-Amyloid 1-16 and 25-35 Fragments─A Molecular Dynamics Simulation Study.

ACS chemical neuroscience·2026
Same author

Toxic Alerts of Endocrine Disruption Revealed by Explainable Artificial Intelligence.

Environment & health (Washington, D.C.)·2025
Same author

Gotcha GPT: Ensuring the Integrity in Academic Writing.

Journal of chemical information and modeling·2024
Same author

Identifying Substructures That Facilitate Compounds to Penetrate the Blood-Brain Barrier via Passive Transport Using Machine Learning Explainer Models.

ACS chemical neuroscience·2024
Same author

Do Large Language Models Understand Chemistry? A Conversation with ChatGPT.

Journal of chemical information and modeling·2023
Same author

Recent Open Issues in Coarse Grained Force Fields.

Journal of chemical information and modeling·2020

Related Experiment Video

Updated: Jun 26, 2026

Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E (sIgE)
07:10

Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E (sIgE)

Published on: April 21, 2019

Deciphering Allergen Peptides for Dermatological and Cosmetic Applications with Explainable Artificial Intelligence.

Marina Geisiely Damaso1, André Silva Pimentel1

  • 1Departamento de Química, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro,22453-900, Brazil.

Journal of Proteome Research
|June 25, 2026
PubMed
Summary

This study introduces an explainable AI model to identify allergenic peptide motifs for safer cosmetics. The framework enhances understanding of peptide allergens in dermatology and cosmetic science.

Keywords:
allergen peptidesallergycosmeticsdermatologyexplainable machine learning.

Related Experiment Videos

Last Updated: Jun 26, 2026

Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E (sIgE)
07:10

Application of Biochip Microfluidic Technology to Detect Serum Allergen-specific Immunoglobulin E (sIgE)

Published on: April 21, 2019

Area of Science:

  • Dermatology and Cosmetic Science
  • Computational Biology
  • Artificial Intelligence

Background:

  • Allergen peptides pose risks in cosmetic and dermatologic products.
  • Current methods for identifying allergenic peptides are limited.
  • Understanding peptide allergenicity is crucial for product safety.

Purpose of the Study:

  • To develop an explainable AI framework for identifying allergenic peptide motifs.
  • To enhance the understanding of peptide allergenicity in cosmetic and dermatologic applications.
  • To facilitate the design of safer peptide-based formulations.

Main Methods:

  • Hybrid deep learning framework integrating Temporal Convolutional Networks (TCN) and Long Short-Term Memory (LSTM) architectures.
  • Utilized Evolutionary Scale Modeling (ESM) embeddings for capturing evolutionary and structural amino acid nuances.
  • Employed explainability tools (Anchor, LIME, SHAP) for motif identification and importance mapping.

Main Results:

  • Accurate classification of allergenic potential in peptide sequences.
  • Identification of minimal, decisive allergenic motifs and synergistic k-mer contributions.
  • Generated biologically meaningful explanations for model predictions.

Conclusions:

  • The explainable AI framework offers a transparent and scalable method for screening peptide allergens.
  • Enables rational design of safer bioactive peptides for cosmetic and therapeutic use.
  • Supports regulatory compliance and fosters innovation in patient-centered cosmetic products.