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Record W4403104824 · doi:10.1080/19490976.2024.2410476

Relevance of gut microbiome research in food safety assessment

2024· review· en· W4403104824 on OpenAlexaff
Manuel Garrido‐Romero, Florencio Pazos, Elisa Sánchez‐Martínez, Carlos Benito, José Ángel Gómez Ruiz, Gonzalo Borrego‐Yaniz, Cameron Bowes, Hermann Broll, Alberto Caminero, Eleonora Caro, Mónica Chagoyen, Marianne Chemaly, Antonio Fernández‐Dumont, Haris Gisavi, Georgia Gkrintzali, Sangeeta Khare, Abelardo Margollés, Ana Márquez, Javier Martín, Caroline Merten, Antonia Montilla, Ana Muñoz‐Labrador, Jorge Novoa, Konstantinos Paraskevopoulos, Cyrielle Payen, Helen Withers, Patricia Ruas‐Madiedo, Lorena Ruíz, Yolanda Sanz, Rodrigo Jiménez‐Saiz, F. Javier Moreno

Bibliographic record

VenueGut Microbes · 2024
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsMcMaster UniversityPopulation Health Research InstituteHealth Canada
FundersInstituto de Salud Carlos IIIEuropean CommissionEuropean Food Safety Authority
KeywordsBiologyGut microbiomeMicrobiomeRelevance (law)Food safetyEnvironmental healthBiotechnologyBioinformaticsFood scienceMedicine

Abstract

fetched live from OpenAlex

The gut microbiome is indispensable for the host physiological functioning. Yet, the impact of non-nutritious dietary compounds on the human gut microbiota and the role of the gut microbes in their metabolism and potential adverse biological effects have been overlooked. Identifying potential hazards and benefits would contribute to protecting and harnessing the gut microbiome's role in supporting human health. We discuss the evidence on the potential detrimental impact of certain food additives and microplastics on the gut microbiome and human health, with a focus on underlying mechanisms and causality. We provide recommendations for the incorporation of gut microbiome science in food risk assessment and identify the knowledge and tools needed to fill these gaps. The incorporation of gut microbiome endpoints to safety assessments, together with well-established toxicity and mutagenicity studies, might better inform the risk assessment of certain contaminants in food, and/or food additives.

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)0.001
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 score0.984
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.143
GPT teacher head0.404
Teacher spread0.261 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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