Low-Protein Diet during Early Life Causes a Reduction in the Frequency of Cells Immunopositive for Nestin and CD34 in Both Pancreatic Ducts and Islets in the Rat
Bibliographic record
Abstract
Feeding a low-protein (LP) diet to pregnant and lactating rats impairs pancreatic islet mass and insulin release in the offspring, leading to glucose intolerance as adults. We hypothesized that an LP diet changes the number of pancreatic endocrine precursor cells or cells supporting endocrine cell neogenesis. Pregnant rats were given LP (8% protein) or a control (20% protein) diet from conception until postnatal d 21. Cells containing nestin, CD34, or c-Kit were quantified in pancreata of the offspring. Stellate cells immunoreactive for nestin were seen to be adjacent to ductal epithelium and were resident within the islets. These were proliferative and immunonegative for cytokeratin 20, fibronectin, tyrosine hydroxylase, pancreatic duodenal homeobox 1, Nk homeodomain transcription factor 6.1, or insulin, but expressed vimentin. Approximately 20% of islet nestin-positive cells also expressed the endothelial cell marker platelet endothelial cell adhesion molecule-1. Both ducts and islets also contained CD34- and c-Kit-positive cells with similar morphology to those expressing nestin. Offspring from rats fed the LP diet had significantly less nestin/CD34-positive cells and reduced expression of nestin mRNA. Within islets, there was an associated decrease in cell proliferation and in cells immunopositive for pancreatic duodenal homeobox 1. Nestin-positive cell number within islets correlated positively with the percent area of beta-cells. Supplementation of pregnant and lactating rats with taurine reversed the deficits in mean islet area and nestin-positive cells caused by the LP diet within the islets of the offspring. Nutritional programming of postnatal beta-cell mass may involve an altered abundance of cells expressing nestin and/or CD34, which may limit endocrine cell development.
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".