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Record W2136612327 · doi:10.1158/1055-9965.epi-08-0341

Red Meat Intake, Doneness, Polymorphisms in Genes that Encode Carcinogen-Metabolizing Enzymes, and Colorectal Cancer Risk

2008· article· en· W2136612327 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2008
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoLunenfeld-Tanenbaum Research InstituteCancer Care Ontario
FundersNational Cancer Institute
KeywordsColorectal cancerRed meatMedicineOdds ratioPopulationCarcinogenCancerInternal medicineOncologyGenotypePhysiologyGastroenterologyGeneticsBiologyEnvironmental healthGenePathology

Abstract

fetched live from OpenAlex

Colorectal cancer literature regarding the interaction between polymorphisms in carcinogen-metabolizing enzymes and red meat intake/doneness is inconsistent. A case-control study was conducted to evaluate the interaction between red meat consumption, doneness, and polymorphisms in carcinogen-metabolizing enzymes. Colorectal cancer cases diagnosed 1997 to 2000, ages 20 to 74 years, were identified through the population-based Ontario Cancer Registry and recruited by the Ontario Family Colorectal Cancer Registry. Controls were sex-matched and age group-matched random sample of Ontario population. Epidemiologic and food questionnaires were completed by 1,095 cases and 1,890 controls; blood was provided by 842 and 1,251, respectively. Multivariate logistic regression was used to obtain adjusted odds ratio (OR) estimates. Increased red meat intake was associated with increased colorectal cancer risk [OR (> 5 versus < or = 2 servings/wk), 1.67 (1.36-2.05)]. Colorectal cancer risk also increased significantly with well-done meat intake [OR (> 2 servings/wk well-done versus < or = 2 servings/wk rare-regular), 1.57 (1.27-1.93)]. We evaluated interactions between genetic variants in 15 enzymes involved in the metabolism of carcinogens in overcooked meat (cytochrome P450, glutathione S-transferase, UDP-glucuronosyltransferases, SULT, NAT, mEH, and AHR). CYP2C9 and NAT2 variants were associated with colorectal cancer risk. Red meat intake was associated with increased colorectal cancer risk regardless of genotypes; however, CYP1B1 combined variant and SULT1A1-638G>A variant significantly modified the association between red meat doneness intake and colorectal cancer risk. In conclusion, well-done red meat intake was associated with an increased risk of colorectal cancer regardless of carcinogen-metabolizing genotype, although our data suggest that persons with CYP1B1 and SULT1A1 variants had the highest colorectal cancer risk.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.069
GPT teacher head0.329
Teacher spread0.260 · 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