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Record W2579549256 · doi:10.4049/jimmunol.1601247

Microbiome-Modulated Metabolites at the Interface of Host Immunity

2017· review· en· W2579549256 on OpenAlexfundno aff
Eran Blacher, Maayan Levy, Evgeny Tatirovsky, Eran Elinav

Bibliographic record

VenueThe Journal of Immunology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersAbisch-Frenkel-StiftungIsrael Science FoundationGerman-Israeli Foundation for Scientific Research and DevelopmentRising Tide FoundationMinerva FoundationEuropean Foundation for the Study of DiabetesCanadian Institute for Advanced ResearchBenoziyo Endowment Fund for the Advancement of ScienceLeona M. and Harry B. Helmsley Charitable Trust
KeywordsImmunityMicrobiomeHost (biology)BiologyComputational biologyImmune systemImmunologyBioinformaticsEcology

Abstract

fetched live from OpenAlex

The mammalian gastrointestinal tract and associated mucosal immune system harbor a large repertoire of metabolites of prokaryotic and eukaryotic origin that play important roles in eukaryotic development and physiology. These often bioactive small molecules originate from nutrition- and environmental-related sources, or are endogenously produced and modulated by the host and its microbiota. A complex network of interactions exists between the intestinal mucosal immune system and the microbiota. This intimate cross-talk may be driven by metabolite secretion and signaling, and features profound influences on host immunity and physiology, including the endocrine, metabolic, and nervous system function in health and disease. Alterations in microbiome-associated metabolite levels and activity are implicated in the pathogenesis of a growing number of illnesses. In this review we discuss the origin and influence of microbiome-modulated metabolites, with an emphasis on immune cell development and function. We further highlight the emerging data potentially implicating metabolite misbalance with host-microbiome-associated disease.

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)0.001
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.038
GPT teacher head0.373
Teacher spread0.335 · 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

Citations348
Published2017
Admission routes1
Has abstractyes

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