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Record W1525476997 · doi:10.1113/jphysiol.2007.147967

Transgenerational effects of prenatal nutrient restriction on cardiovascular and hypothalamic‐pituitary‐adrenal function

2008· article· en· W1525476997 on OpenAlexaff
Caroline Bertram, Omar Khan, Sunil K. Ohri, David Phillips, Stephen G. Matthews, Mark A. Hanson

Bibliographic record

VenueThe Journal of Physiology · 2008
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersBritish Heart Foundation
KeywordsOffspringInternal medicineEndocrinologyBlood pressureMalnutritionMedicinePregnancyIntrauterine growth restrictionFetusBiology

Abstract

fetched live from OpenAlex

The perinatal environment is a powerful determinant of risk for developing disease in later life. Here, we have shown that maternal undernutrition causes dramatic changes in heart structure and hypothalamo-pituitary-adrenal (HPA) function across two generations. Pregnant guinea pigs were fed 70% of normal intake from gestational days 1-35 (early restriction; ER), or 36-70 (late restriction; LR). Female offspring (F(1)) were mated and fed ad libitum to create second generation (F(2)) offspring. Heart morphology, blood pressure, baroreceptor and HPA function were assessed in male F(1) and F(2) offspring. ER(F1) males exhibited elevated blood pressure, increased left ventricular (LV) wall thickness and LV mass. These LV effects were maintained in the ER(F2) offspring. Maternal undernutrition increased basal cortisol and altered HPA responsiveness to challenge in both generations; effects were greatest in LR groups. In conclusion, moderate maternal undernutrition profoundly modifies heart structure and HPA function in adult male offspring for two generations.

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 score0.002
Threshold uncertainty score0.006

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.231
Teacher spread0.214 · 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

Citations136
Published2008
Admission routes1
Has abstractyes

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