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Record W2753755932 · doi:10.1139/cjpp-2017-0371

Female offspring born to obese and insulin-resistant dams are not at increased risk for obesity and metabolic dysfunction during early development

2017· article· en· W2753755932 on OpenAlexafffundvenue
Hanin Aburasayn, Rami Al Batran, Keshav Gopal, Malak Almutairi, Amina Eshreif, Farah Eaton, John R. Ussher

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2017
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
FundersMolly Towell Perinatal Research FoundationWomen and Children's Health Research InstituteChildren's Health Research Institute
KeywordsOffspringObesityEndocrinologyMetabolic syndromeInsulin resistancePregnancyInternal medicineWeaningMedicineBiologyPhysiologyGenetics

Abstract

fetched live from OpenAlex

The percentage of women who are obese at the time of conception or during pregnancy is increasing, with animal and human studies demonstrating that offspring born to obese dams or mothers are at increased risk for obesity and the metabolic syndrome. Our goal was to confirm in an experimental model of metabolic syndrome in the dam, whether the offspring would be at increased risk of obesity. Conversely, we observed that male offspring born to dams with metabolic syndrome had no alterations in their body mass profiles, whereas female offspring born to dams with metabolic syndrome were heavier at weaning, but exhibited no perturbations in energy metabolism. Moreover, they gained weight at a reduced rate versus female offspring born to healthy dams, and thus weighed less at study completion. Hence, our findings suggest that factors other than increased adiposity and insulin resistance during pregnancy are responsible for the increased risk of obesity in children born to obese mothers.

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)0.001
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0050.001

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 head0.027
GPT teacher head0.296
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 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

Citations4
Published2017
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Physiology and PharmacologySame topicBirth, Development, and HealthFrench-language works237,207