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

Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...

You might also read

Related Articles

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

Sort by
Same author

Clinical considerations for immune dysregulation and immunodeficiency in Down syndrome.

Journal of human immunity·2026
Same author

Attenuated estrogen signaling disrupts placentation and drives trophoblast defects in Down syndrome.

bioRxiv : the preprint server for biology·2026
Same author

Immunosuppression in down syndrome regression disorder: a prospective observational cohort study.

Brain communications·2026
Same author

Interferon receptor gene dosage differentially regulates hypoxia-induced platelet activation and pulmonary hypertension in down syndrome.

Frontiers in immunology·2026
Same author

Beyond Identifier Matching: An Empirical Characterization of Failure Modes in Biomedical Knowledge Graph Integration.

medRxiv : the preprint server for health sciences·2026
Same author

Systematic multi-omic deconvolution of the clinical heterogeneity of Down syndrome.

Nature communications·2026

Related Experiment Video

Updated: Jun 23, 2026

Eye Tracking Young Children with Autism
09:03

Eye Tracking Young Children with Autism

Published on: March 27, 2012

An AI-Powered Trisomy 21 Research Assistant.

Sutanu Nandi, Zenitha Sundararajan, Marc Subirana-Granés

    Biorxiv : the Preprint Server for Biology
    |June 22, 2026
    PubMed
    Summary

    A new AI tool, the T21 Research Assistant, helps researchers navigate Down syndrome literature. It prioritizes experimental results for accurate, evidence-based answers, improving information retrieval for this complex genetic condition.

    More Related Videos

    Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats
    10:04

    Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats

    Published on: May 9, 2018

    Related Experiment Videos

    Last Updated: Jun 23, 2026

    Eye Tracking Young Children with Autism
    09:03

    Eye Tracking Young Children with Autism

    Published on: March 27, 2012

    Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats
    10:04

    Construction of an Improved Multi-Tetrode Hyperdrive for Large-Scale Neural Recording in Behaving Rats

    Published on: May 9, 2018

    Area of Science:

    • Genetics and Bioinformatics
    • Artificial Intelligence in Medicine
    • Down Syndrome Research

    Background:

    • Down syndrome (trisomy 21) is linked to numerous health issues, with a rapidly growing body of over 34,000 publications.
    • General AI models struggle with the specificity required for scientific literature retrieval.
    • Retrieval-augmented generation (RAG) enhances AI reliability by linking outputs to source texts, but standard methods don't prioritize experimental data.

    Purpose of the Study:

    • To develop a section-aware RAG system, the T21 Research Assistant, to focus on primary experimental evidence in Down syndrome research.
    • To improve the accuracy and reliability of information retrieval from the extensive Down syndrome literature.
    • To provide researchers with timely and evidence-based answers grounded in experimental results.

    Main Methods:

    • Developed a section-aware RAG system prioritizing "Results" sections of manuscripts.
    • Utilized a curated dataset of 1,789 open-access Down syndrome publications from PubMed Central.
    • Implemented a multistage pipeline: query validation, retrieval, reranking, synthesis, and citation verification using NVIDIA Nemotron models.

    Main Results:

    • The T21 Research Assistant demonstrated strong performance in expert-curated question evaluations.
    • Achieved a BERTScore F1 of 0.712 and recall of 0.758.
    • Outperformed or matched leading proprietary and open-source models in accuracy and reliability.

    Conclusions:

    • The T21 Research Assistant effectively grounds AI responses in primary experimental evidence from Down syndrome research.
    • This section-aware RAG system offers a significant advancement in navigating complex scientific literature.
    • The tool is accessible for researchers at https://bioinformatics.cuanschutz.edu/t21-res-assi/.