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Record W3102800937 · doi:10.1111/1462-2920.15317

Communal living: glycan utilization by the human gut microbiota

2020· review· en· W3102800937 on OpenAlexafffund
Jonathon A. Briggs, Julie M. Grondin, Harry Brumer

Bibliographic record

VenueEnvironmental Microbiology · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsGlycanBiologyMicrobiomeMetagenomicsHost (biology)Gut floraGeneralist and specialist speciesComputational biologyEvolutionary biologyEcologyBioinformaticsBiochemistryGene

Abstract

fetched live from OpenAlex

Our lower gastrointestinal tract plays host to a vast consortium of microbes, known as the human gut microbiota (HGM). The HGM thrives on a complex and diverse range of glycan structures from both dietary and host sources, the breakdown of which requires the concerted action of cohorts of carbohydrate-active enzymes (CAZymes), carbohydrate-binding proteins, and transporters. The glycan utilization profile of individual taxa, whether 'specialist' or 'generalist', is dictated by the number and functional diversity of these glycan utilization systems. Furthermore, taxa in the HGM may either compete or cooperate in glycan deconstruction, thereby creating a complex ecological web spanning diverse nutrient niches. As a result, our diet plays a central role in shaping the composition of the HGM. This review presents an overview of our current understanding of glycan utilization by the HGM on three levels: (i) molecular mechanisms of individual glycan deconstruction and uptake by key bacteria, (ii) glycan-mediated microbial interactions, and (iii) community-scale effects of dietary changes. Despite significant recent advancements, there remains much to be discovered regarding complex glycan metabolism in the HGM and its potential to affect positive health outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.298
Teacher spread0.268 · 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 teacher head, not a consensus.

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

Citations109
Published2020
Admission routes2
Has abstractyes

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