MétaCan
Menu
← Back to cohort
Record W4210660835 · doi:10.3389/fimmu.2022.823207

Transplacental and Breast Milk Transfer of IgG1 Are Both Required for Prolonged Protection of Offspring Against Influenza A Infection

2022· article· en· W4210660835 on OpenAlexaff
Julia Chronopoulos, James G. Martin, Maziar Divangahi

Bibliographic record

VenueFrontiers in Immunology · 2022
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsChristie (Canada)McGill University Health Centre
Fundersnot available
KeywordsOffspringTransplacentalImmunologyBiologyImmunityPregnancyPassive immunityAntibodyImmune systemLactationInfluenza A virusVirusFetusBreast milkPlacenta

Abstract

fetched live from OpenAlex

The immune system during pregnancy teeters between maintaining fetal tolerance and providing protection against pathogens. Due to this delicate balance, pregnant women and their offspring often have increased susceptibilities to infection. During the first year of life, infant immunity against infection is mainly mediatedviapassively transferred maternal antibodies. However, our understanding of the route of transfer of the maternal antibodies for conferring protection to influenza A virus (IAV) infection in offspring is incomplete. Here we have demonstrated that offspring from IAV-infected mice were significantly protected against IAV infection. This remarkable increase in survival is mediatedviathe elevated maternal serum IgG1. By cross-fostering, we further showed that this enhanced host resistance was only achieved in mice born to and nursed by IAV-infected mothers. Collectively, our data suggest that the prolonged protection of offspring against IAV infection requires maternal IgG1 from both the placenta and breast milk.

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)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.293
Teacher spread0.258 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Immunology→Same topicInfluenza Virus Research Studies→French-language works237,207→