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Record W4403272394 · doi:10.3389/fimmu.2024.1429436

Microbiota activation and regulation of adaptive immunity

2024· review· en· W4403272394 on OpenAlexaff
Mozhdeh Heidari, Saman Maleki Vareki, Ramin Yaghobi, Mohammad Hossein Karimi

Bibliographic record

VenueFrontiers in Immunology · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsLawson Health Research InstituteWestern University
FundersShiraz UniversityShiraz University of Medical Sciences
KeywordsImmune systemImmunityBiologyDysbiosisGut floraAcquired immune systemMicrobiomeImmunologyHomeostasisProinflammatory cytokineInflammationCell biologyBioinformatics

Abstract

fetched live from OpenAlex

In the mucosa, T cells and B cells of the immune system are essential for maintaining immune homeostasis by suppressing reactions to harmless antigens and upholding the integrity of intestinal mucosal barrier functions. Host immunity and homeostasis are regulated by metabolites produced by the gut microbiota, which has developed through the long-term coevolution of the host and the gut biome. This is achieved by the immunological system's tolerance for symbiote microbiota, and its ability to generate a proinflammatory response against invasive organisms. The imbalance of the intestinal immune system with commensal organisms is causing a disturbance in the homeostasis of the gut microbiome. The lack of balance results in microbiota dysbiosis, the weakened integrity of the gut barrier, and the development of inflammatory immune reactions toward symbiotic organisms. Researchers may uncover potential therapeutic targets for preventing or regulating inflammatory diseases by understanding the interactions between adaptive immunity and the microbiota. This discussion will explore the connection between adaptive immunity and microbiota.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.018
GPT teacher head0.285
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations33
Published2024
Admission routes1
Has abstractyes

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