MétaCan
Menu
Back to cohort
Record W2966720035 · doi:10.1002/bies.201900002

When Cultures Meet: The Landscape of “Social” Interactions between the Host and Its Indigenous Microbes

2019· review· en· W2966720035 on OpenAlexafffund
Naama Geva‐Zatorsky, Eran Elinav, Sven Pettersson

Bibliographic record

VenueBioEssays · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsCanadian Institute for Advanced Research
FundersCanadian Institute for Advanced ResearchHoward Hughes Medical Institute
KeywordsHolobiontBiologyMicrobiomeEcologyHost (biology)InterdependenceGeneticsSymbiosisSociologyBacteria

Abstract

fetched live from OpenAlex

Animals exist as biodiverse composite organisms that include microbial residents, eukaryotic cells, and organs that collectively form a human being. Through an interdependent relationship and an inherent ability to transmit and reciprocate stimuli in a bidirectional way, a human body or the holobiont secures growth, health, and reproduction. As such, the survival of a holobiont is dependent on the maintenance of biological order including metabolic homeostasis by tight regulation of the communication between its eukaryotic and prokaryotic residents. In this review an overview and perspective are provided on the bidirectional communication between microbes and their host in mutually nurturing biochemical, biological, and social interconnected relationships between the components of the holobiont. An emphasis is placed on exemplifying microbiome-mediated effects on host functions-aiming to integrate microbiome functionality to host physiology, be it health or disease. Nutrition, immunology, and sexual dimorphism have been traversed extensively to reflect on health and mind states, social interactions, and urbanization defects/effects. Finally, examples of molecular mechanisms potentially orchestrating these complex transkingdom interactions are provided.

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 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 score0.728
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.037
GPT teacher head0.341
Teacher spread0.304 · 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.

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

Citations3
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueBioEssaysSame topicGut microbiota and healthFrench-language works237,207