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Record W1951329698 · doi:10.14740/wjon930w

Effect of MTHFR Polymorphisms on Gastrointestinal Cancer Risk in Italy

2015· article· en· W1951329698 on OpenAlexvenueno aff
Federica Mazzuca, Marina Borro, Andrea Botticelli, Laura Aimati, Giovanna Gentile, Carlo Capalbo, Chiara De Maddalena, Eva Mazzotti, Maurizio Simmaco, Paolo Marchetti

Bibliographic record

VenueWorld Journal of Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMethylenetetrahydrofolate reductaseSingle-nucleotide polymorphismInternal medicineLoss of heterozygosityGenotypeEsophageal cancerPancreatic cancerGastroenterologyAlleleColorectal cancerGastrointestinal cancerCancerPopulationCohortLogistic regressionOncologyGeneticsGeneBiology

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of the study was to assess the association of single nucleotide polymorphisms (SNPs) C677T and A1298C in the methylenetetrahydrofolate reductase gene with colorectal, esophageal/gastric and pancreatic cancer in a cohort of Italian patients. METHODS: A total of 790 cancer patients and 202 healthy controls were genotyped and distributions in genotype and allele frequencies were compared by Chi-squared analysis and logistic regression analysis. RESULTS: According to most of previous findings, we found an effect of the C677T variant, but no effect of the A1298C, in colorectal and esophageal/gastric, whereas no association was evidenced with pancreatic cancer. We found that only homozygous TT carriers of the C677T variant had an increased risk for onset of cancer. CONCLUSION: This result could be related to dietary and behavioral habits of the analyzed population, which could mitigate the deleterious effect of the T allele in heterozygosity and it highlights the importance to validate genetic determinant of cancer risk in different population and geographical areas.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.033
GPT teacher head0.385
Teacher spread0.352 · 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 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

Citations13
Published2015
Admission routes1
Has abstractyes

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