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Record W2236938929 · doi:10.1158/1055-9965.epi-15-0798

Serum Endotoxins and Flagellin and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) Cohort

2016· article· en· W2236938929 on OpenAlexaff
So Yeon Kong, Hao Quang Tran, Andrew T. Gewirtz, Gail McKeown‐Eyssen, Veronika Fedirko, Isabelle Romieu, Anne Tjønneland, Anja Olsen, Kim Overvad, Marie‐Christine Boutron‐Ruault, Nadia Bastide, Aurélie Affret, Tilman Kühn, Rudolf Kaaks, Heiner Boeing, Krasimira Aleksandrova, Antonia Trichopoulou, Maria Kritikou, Effie Vasilopoulou, Domenico Palli, Vittorio Krogh, Amalia Mattiello, ­Rosario ­Tumino, Alessio Naccarati, H. Bas Bueno‐de‐Mesquita, Petra H. Peeters, Elisabete Weiderpass, J. Ramón Quirós, Núria Sala, María‐José Sánchez, José María Huerta, Aurelio Barricarte, Miren Dorronsoro, Mårten Werner, Nicholas J. Wareham, Kay‐Tee Khaw, Kathryn E. Bradbury, Heinz Freisling, Faidra Stavropoulou, Pietro Ferrari, Marc J. Gunter, Amanda J. Cross, Elio Ríboli, W. Robert Bruce, Mazda Jenab

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Response and Inflammation
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersWorld Cancer Research FundMedical Research CouncilHellenic Health FoundationInstituto de Salud Carlos IIIWereld Kanker Onderzoek FondsInstitut Gustave-RoussyDeutsche KrebshilfeMutuelle Générale de l'Education NationaleAssociazione Italiana per la Ricerca sul CancroCancerfondenInstitut National de la Santé et de la Recherche MédicaleWorld Health OrganizationEuropean CommissionBundesministerium für Bildung und ForschungLigue Contre le CancerNational Institute for Health and Care ResearchCancer Research UKDeutsches KrebsforschungszentrumCentre International de Recherche sur le Cancer
KeywordsEuropean Prospective Investigation into Cancer and NutritionFlagellinMedicineCancerProspective cohort studyEPICColorectal cancerInternal medicineCohortOncology

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic inflammation and oxidative stress are thought to be involved in colorectal cancer development. These processes may contribute to leakage of bacterial products, such as lipopolysaccharide (LPS) and flagellin, across the gut barrier. The objective of this study, nested within a prospective cohort, was to examine associations between circulating LPS and flagellin serum antibody levels and colorectal cancer risk. METHODS: A total of 1,065 incident colorectal cancer cases (colon, n = 667; rectal, n = 398) were matched (1:1) to control subjects. Serum flagellin- and LPS-specific IgA and IgG levels were quantitated by ELISA. Multivariable conditional logistic regression models were used to calculate ORs and 95% confidence intervals (CI), adjusting for multiple relevant confouding factors. RESULTS: Overall, elevated anti-LPS and anti-flagellin biomarker levels were not associated with colorectal cancer risk. After testing potential interactions by various factors relevant for colorectal cancer risk and anti-LPS and anti-flagellin, sex was identified as a statistically significant interaction factor (Pinteraction < 0.05 for all the biomarkers). Analyses stratified by sex showed a statistically significant positive colorectal cancer risk association for men (fully-adjusted OR for highest vs. lowest quartile for total anti-LPS + flagellin, 1.66; 95% CI, 1.10-2.51; Ptrend, 0.049), whereas a borderline statistically significant inverse association was observed for women (fully-adjusted OR, 0.70; 95% CI, 0.47-1.02; Ptrend, 0.18). CONCLUSION: In this prospective study on European populations, we found bacterial exposure levels to be positively associated to colorectal cancer risk among men, whereas in women, a possible inverse association may exist. IMPACT: Further studies are warranted to better clarify these preliminary observations.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.284
Teacher spread0.269 · 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

Citations35
Published2016
Admission routes1
Has abstractyes

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