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Record W3084219519 · doi:10.1139/bcb-2020-0087

Effects of oral bovine lactoferrin on a mouse model of inflammation associated colon cancer

2020· article· en· W3084219519 on OpenAlexvenueno aff
Hajime Tanaka, Sivagami Gunasekaran, Dina Saleh, David B. Alexander, Hirotaka Ohara, Hiroyuki Tsuda

Bibliographic record

VenueBiochemistry and Cell Biology · 2020
Typearticle
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsnot available
Fundersnot available
KeywordsAzoxymethaneMedicineColorectal cancerGastroenterologyInflammatory bowel diseaseInternal medicineUlcerative colitisLactoferrinColitisPlaceboInflammationIrritable bowel syndromeCrohn's diseaseEnemaIngestionCancerDiseasePathologyBiology

Abstract

fetched live from OpenAlex

Patients with ulcerative colitis or colonic Crohn’s disease have a significantly increased risk of developing colorectal cancer. Bovine lactoferrin (bLF) reportedly inhibited the development of colon cancer in rats and mice, and in a placebo controlled trial, ingestion of bLF inhibited the growth of intestinal polyps. In addition, in a case study, a patient with Crohn’s disease was reported to have remained in remission for over 7 years while ingesting 1 g of bLF daily. Thus, bLF has an inhibitory effect on colon carcinogenesis, and it may also promote remission of Crohn’s disease. The purpose of this study was to investigate the effects of bLF in a mouse model of colorectal cancer related to irritable bowel disease (IBD). The mice were divided into 4 groups: (i) no treatment; (ii) treated with bLF only; (iii) treated with azoxymethane plus dextran sulfate sodium (AOM + DSS); and (iv) treated with AOM + DSS + bLF. AOM was used to initiate intestinal cancer, and DSS was used to induce IBD-like inflammation in the intestine of the C57BL/6 mice. At the end of the study, the mice treated with AOM + DSS + bLF had a better fecal score, fewer lesions in the colon, and less weight loss than the mice treated with AOM + DSS without bLF. However, there were no statistically significant differences between the two groups with respect to tumor burden.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.017
GPT teacher head0.272
Teacher spread0.254 · 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 designBench or experimental
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

Citations24
Published2020
Admission routes1
Has abstractyes

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