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Record W1996410417 · doi:10.1159/000241712

Synergistic Effects of Insulin and Thyroxine on the Differentiation and Proliferation of Epithelial Cells of Suckling Mouse Small Intestine

2009· article· en· W1996410417 on OpenAlexaff
Christiane Malo, Daniel Ménard

Bibliographic record

VenueBiology of the Neonate · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDigestive system and related health
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsInsulinEndocrinologyInternal medicineCortisoneHormoneEnterocyteBiologySmall intestineCellular differentiationChemistryMedicineBiochemistry

Abstract

fetched live from OpenAlex

The interactions between insulin, cortisone and thyroxine on the functional maturation of the small intestine were investigated. 8-day-old suckling mice received one injection/day during 3 days of a single hormone or of the following hormonal combinations: insulin plus cortisone or insulin plus thyroxine. The differentiation of intestinal epithelial cells was evaluated by measuring brush border membrane hydrolytic activities and proliferation by establishing the mitotic index and 3H-thymidine incorporation into DNA. The effects of cortisone and insulin on enterocyte's differentiation are additive. Thyroxine accelerates the differentiation and has a limited action on cell proliferation. Insulin exerts a sustained effect on these two aspects of the intestinal maturation and, furthermore, acts in synergism with thyroxine. It appears that insulin, cortisone and thyroxine have their own specific effect on differentiation and proliferation of the epithelial cells and that these three hormones act in cooperation to induce the maturation of the suckling mouse small intestine during postnatal development.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.216
Teacher spread0.210 · 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 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

Citations49
Published2009
Admission routes1
Has abstractyes

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