Higher Hepatic miR-29 Expression in Undernourished Male Rats During the Postnatal Period Targets the Long-Term Repression of IGF-1
Bibliographic record
Abstract
A nutritional mismatch in postnatal life of low birth weight offspring increases the risk of developing the metabolic syndrome. Moreover, this is associated with decreased hepatic Igf1 expression, leading to impaired growth and metabolism. Previously, we have demonstrated that the timing of nutritional restoration in perinatal life can differentially program hepatic gene expression. Although microRNAs also play an important role in silencing gene expression, to date, the impact of a nutritional mismatch in neonatal life on their long-term expression has not been evaluated. Given the complementarity of miR-29 to the 3' untranslated region of Igf1, we examined how protein restoration in maternal protein restriction rat offspring influences hepatic miR-29 and Igf1 expression in adulthood. Pregnant Wistar rats were designated into 1 of 4 dietary regimes: 20% protein (control), 8% protein during lactation only (LP-Lact), 8% protein during gestation only (LP1) or both (LP2). The steady-state expression of hepatic miR-29 mRNA significantly increased in LP2 offspring at postnatal day 21 and 130, and this was inversely related to hepatic Igf1 mRNA and body weight. Interestingly, this reciprocal association was stronger in LP-Lact offspring at postnatal day 21. Functional relevance of this in vivo relationship was evaluated by transfection of miR-29 mimics in neonatal Clone 9 rat hepatoma cells. Transfection with miR-29 suppressed Igf1 expression by 12 hours. Collectively, these findings implicate that nutritional restoration after weaning (post liver differentiation) in maternal protein restriction rat offspring fails to prevent long-term impaired growth, in part, due to miR-29 suppression of hepatic Igf1 expression.
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) | 0.002 | 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".