Early postnatal exposure of rat pups to methylglyoxal induces oxidative stress, inflammation and dysmetabolism at adulthood
Bibliographic record
Abstract
Abstract This work aimed to investigate the effects of early progeny exposure to methylglyoxal (MG), programming for metabolic dysfunction and diabetes-like complications later in life. At delivery (PN1), the animals were separated into two groups: control group (CO), treated with saline, and MG group, treated with MG (20 mg/kg of BW; i.p.) during the first 2 weeks of the lactation period. In vivo experiments and tissue collection were done at PN90. Early MG exposure decreased body weight, adipose tissue, liver and kidney weight at adulthood. On the other hand, MG group showed increased relative food intake, blood fructosamine, blood insulin and HOMA-IR, which is correlated with insulin resistance. Besides, MG-treated animals presented dyslipidaemia, increased oxidative stress and inflammation. Likewise, MG group showed steatosis and perivascular fibrosis in the liver, pancreatic islet hypertrophy, increased glomerular area and pericapsular fibrosis, but reduced capsular space. This study shows that early postnatal exposure to MG induces oxidative stress, inflammation and fibrosis markers in pancreas, liver and kidney, which are related to metabolic dysfunction features. Thus, nutritional disruptors during lactation period may be an important risk factor for metabolic alterations at adulthood.
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".