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Record W4417427143 · doi:10.1084/jem.20241287

Antibiotic use in early life impairs MAIT cell–mediated immunity in adulthood

2025· article· en· W4417427143 on OpenAlexfundno aff
Gabrielle LeBlanc, Adam L. Sobel, Jonathan Melamed, Dominic A. Haas, Eduard Ansaldo, Aiko M. Cirone, Elizabeth Murguia, Michael G. Constantinides

Bibliographic record

VenueThe Journal of Experimental Medicine · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaScripps Research InstituteNational Institutes of HealthNational Science Foundation
KeywordsAntibioticsCommensalismImmunityImmune systemConcomitantMicrobiome

Abstract

fetched live from OpenAlex

Mucosal-associated invariant T (MAIT) cells are predominantly located in barrier tissues where they rapidly respond to pathogens and commensals by recognizing microbial derivatives of riboflavin synthesis. Early-life exposure to these metabolites imprints the abundance of MAIT cells within tissues, so we hypothesized that antibiotic use during this period may abrogate their development. We identified antibiotics that deplete riboflavin-synthesizing commensals and revealed an early period of susceptibility during which antibiotic administration impaired MAIT cell development. The reduction in MAIT cell abundance rendered mice more susceptible to pneumonia, while MAIT cell-deficient mice were unaffected by early-life antibiotics. Concomitant administration of a riboflavin-synthesizing commensal during antibiotic treatment was sufficient to restore MAIT cell development and immunity. Our work demonstrates that transient depletion of riboflavin-synthesizing commensals in early life can adversely affect responses to subsequent infections.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.266
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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