Early life undernutrition reduces maximum treadmill running capacity in adulthood in mice
Bibliographic record
Abstract
Undernutrition during early life causes chronic disease with specific impairments to the heart and skeletal muscle. The purpose of this study was to determine the effects of early life undernutrition on adult exercise capacity as a result of cardiac and skeletal muscle function. Pups were undernourished during gestation (GUN) or lactation (PUN) using a cross-fostering nutritive mouse model. At postnatal day 21, all mice were weaned and refed a control diet. At postnatal day 67, mice performed a maximal treadmill test. Echocardiography and Doppler blood flow analysis was performed at postnatal day 72, following which skeletal muscle cross-sectional area (CSA) and fiber type were determined. Maximal running capacity was reduced (diet: P = 0.0002) in GUN and PUN mice. Left ventricular mass (diet: P = 0.03) and posterior wall thickness during systole (diet × sex: P = 0.03) of GUN and PUN mice was reduced, causing PUN mice to have reduced (diet: P = 0.04) stroke volume. Heart rate of GUN mice showed a trend (diet: P = 0.07) towards greater resting values than other groups. PUN mice had greater CSA of soleus fibers. PUN had a reduced (diet: P = 0.03) proportion of type-IIX fibers in the extensor digitorum longus (EDL) and a greater (diet: P = 0.008) percentage of type-IIB fibers in the EDL. In conclusion, gestational and postnatal undernourishment impairs exercise capacity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".