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Record W2906626869 · doi:10.1093/nsr/nwy160

Influence of the microbiota on epigenetics in colorectal cancer

2018· article· en· W2906626869 on OpenAlexfundno aff
Danfeng Sun, Yingxuan Chen, Jing‐Yuan Fang

Bibliographic record

VenueNational Science Review · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersSchool of MedicineShanghai Jiao Tong UniversityMinistry of Health, British Columbia
KeywordsEpigeneticsBiologyColorectal cancerCancerGut floraMechanism (biology)GeneGeneticsComputational biologyBioinformaticsImmunology

Abstract

fetched live from OpenAlex

Colorectal cancer is one of the most common malignancies and is the second leading cause of cancer death worldwide. Generally, there are three categories of colorectal cancer development mechanism-genetic, epigenetic and aberrant immunological signaling pathways-all of which may be initiated by an imbalanced gut microbiota. Epigenetic modifications enable host cells to change gene expression without modifying the gene sequence. The microbiota can interact with the host genome dynamically through the interface presented by epigenetic modifications. In particular, bacterially derived short-chain fatty acids have been identified as one clear link in the interaction of the microbiota with host epigenetic pathways. This review discusses recent findings relating to the cross talk between the microbiota and epigenetic modifications in colorectal cancer.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.351
Teacher spread0.337 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations43
Published2018
Admission routes1
Has abstractyes

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