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Record W4286698656 · doi:10.3389/fnut.2022.931458

Dietary Component-Induced Inflammation and Its Amelioration by Prebiotics, Probiotics, and Synbiotics

2022· review· en· W4286698656 on OpenAlex
Muhammad Bilal, Shoaib Ashraf, Xin Zhao

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Nutrition · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsSynbioticsImmune systemInflammationGut floraDysbiosisImmunologyInflammatory bowel diseaseMicrobiomeMedicineDiseaseBiologyBioinformaticsProbioticInternal medicine

Abstract

fetched live from OpenAlex

A balanced diet with many dietary components maintains immune homeostasis directly by interacting with innate and adaptive immune components or indirectly through gut microbiota and their metabolites. Dietary components may inhibit pro-inflammatory mediators and promote anti-inflammatory functions or vice versa. Western diets with imbalanced dietary components skew the immune balance toward pro-inflammation and induce intestinal inflammation, consequently leading to many intestinal and systemic inflammatory diseases like ulcerative colitis, Crohn's disease, irritable bowel syndrome, cardiovascular problems, obesity, and diabetes. The dietary component-induced inflammation is usually chronic in nature and frequently caused or accompanied by alterations in gut microbiota. Therefore, microbiome-targeted therapies such as probiotics, prebiotics and synbiotics hold great potentials to amend immune dysregulation and gut dysbiosis, preventing and treating intestinal and systemic inflammatory diseases. Probiotics, prebiotics and synbioitcs are progressively being added to foods and beverages, with claims of health benefits. However, the underlining mechanisms of these interventions for preventing and treating dietary component-induced inflammation are still not very clear. In addition, possibly ineffective or negative consequences of some probiotics, prebiotics and synbiotics call for stringent testing and regulation. Here, we will first briefly review inflammation, in terms of its types and the relationship between different dietary components and immune responses. Then, we focus on current knowledge about the direct and indirect effects of probiotics, prebiotics and synbiotics on intestinal and systemic inflammation. Understanding how probiotics, prebiotics and synbiotics modulate the immune system and gut microbiota will improve our strategies for preventing and treating dietary component-induced intestinal inflammation and inflammatory diseases.

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.

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 score0.943
Threshold uncertainty score1.000

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 head0.026
GPT teacher head0.282
Teacher spread0.255 · 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