The multi‐coloured guinea pig is a novel animal model to study the effects of intrauterine growth restriction on bone and body composition
Bibliographic record
Abstract
Compromised intrauterine nutrition predisposes a fetus to obesity and low bone mass in later life. Design of health interventions to attenuate these sequelea requires the use of animal models of fetal programming. Restricting calorie or protein intake in pregnant rats is most widely used to induce fetal programming. However, the health characteristics of offspring are variable and inconsistently mirror observations in humans. Thus, the objective of this study was to restrict protein intake in pregnant guinea pigs (N=40) to 50% of requirements and observe the effects on body composition and bone, since guinea pigs mineralize bone in utero. Dual energy x‐ray absorptiometry scans were conducted on d 3 and 21 of life and one‐way ANOVA (P<0.05) was used to determine differences between groups. At birth, body weight and length of protein‐restricted (PR) pups in comparison to controls was 30% lower and lean body mass was reduced by 20%. Femoral, tibia, and lumbar spine bone mineral content (BMC) and density (BMD) were 15–30% lower in PR pups than controls. Moreover, whole body BMC and BMD were significantly compromised in PR offspring and this persisted at d 21 of life. Thus, the intrauterine PR guinea pig displays health traits very alike the human small for gestational age neonate. Further investigation is needed to determine whether associated health parameters, such as blood glucose control, are also abnormal. NSERC funded.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".