Influence of aging and maternal protein restriction on PIWI-interacting RNA expression in the offspring rat ventral prostate
Bibliographic record
Abstract
The Developmental Origins of Health and Disease (DOHaD) concept explores the link between exposure to adverse conditions during fetal and early childhood development and the onset of chronic non-communicable diseases, such as prostate cancer (PCa). Changes in epigenetics that control gene expression have been identified as potential contributors to the developmental origin of PCa. Piwi-interacting RNAs (piRNAs), for example, control transposable elements (TEs) and maintain genome integrity in germ cells. However, stress-induced deregulation of TEs warrants investigating the role of piRNAs in the prostate gland from the DOHaD perspective, which remains underexplored. This study aimed to detect and characterize piRNA expression in the ventral prostate (VP) of Sprague Dawley rat offspring at 21 postnatal days (PND21) and PND540. The rats were subjected to maternal protein restriction during pregnancy and lactation to understand its impact on prostate development and aging. Histological analyses showed that the gestational and lactation low-protein diet (GLLP) group experienced a delay in prostate gland development, with increased stromal and epithelial compartments and decreased luminal compartments during early life. Aging in this group resulted in decreased luminal compartments and increased stromal areas. Epithelial atrophy was observed in both groups, with an increased incidence of carcinoma in situ in the GLLP group. Small RNA sequencing from control and restricted groups (at PND21 and PND540) identified piRNA clusters in both young and aged animals. We also detected the expression of PIWI genes (Riwi, Rili, Rili2) in the prostate. Our data highlight the key role of maternal malnutrition in modulating piRNA expression in the offspring's VP, with the potential to influence prostate developmental biology and the risk of prostatic disorders with aging.
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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) | 0.000 | 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".