The deleterious effects of maternal protein deprivation on the brainstem are minimized with moderate physical activity by offspring during early life
Bibliographic record
Abstract
Maternal protein malnutrition during developmental periods might impair the redox state and the brain's excitatory/inhibitory neural network, increasing central sympathetic tone. Conversely, moderate physical exercise at an early age reduces the risk of chronic diseases. Thus, we hypothesized that a moderate training protocol could reduce the harmful effects of a low-protein maternal diet on the brainstem of young male offspring. We used a rat model of maternal protein restriction during the gestational and lactation period followed by an offspring's continuous treadmill exercise. Pregnant rats were divided into two groups according to the protein content in the diet: normoprotein (NP), receiving 17% of casein, and low protein (LP), receiving 8% of casein until the end of lactation. At 30 days of age, the male offspring were further subdivided into sedentary (NP-Sed and LP-Sed) or exercised (NP-Ex and LP-Ex) groups. Treadmill exercise was performed as follows: 4 weeks, 5 days/week, 60 min/day at 50% of maximal running capacity. The trained animals performed a treadmill exercise at 50% of the maximal running capacity, 60 min/day, 5 days/week, for 4 weeks. Our results indicate that a low-protein diet promotes deficits in the antioxidant system and a likely mitochondrial uncoupling. On the other hand, physical exercise restores the redox balance, which leads to decreased oxidative stress caused by the diet. In addition, it also promotes benefits to GABAergic inhibitory signaling. We conclude that regular moderate physical exercise performed in youthhood protects the brainstem against changes induced by maternal protein restriction.
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 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) | 0.000 | 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".