Metabolic, stress, and inflammatory biomarker responses to glucose administration in Fischer-344 rats: intraperitoneal vs. oral delivery
Bibliographic record
Abstract
INTRODUCTION: Metabolic effects of anthropogenic chemicals are a focus of environmental health research due to the significant public health implications. Conventional glucose tolerance tests (GTTs) do not generally examine multiple metabolic, inflammatory, and endocrine factors; however, responses to exogenous glucose can provide insight into mode-of-action and disease processes, and warrant consideration in developing models for toxicological assessment. METHODS: GTTs were conducted on male Fischer-344 rats to 1) assess the feasibility of measuring multiple analytes in small sample volumes; 2) monitor analyte response; and 3) determine whether route of glucose delivery (oral, OGTT vs. intraperitoneal, IPGTT, 2g/kg) modified responses. Plasma samples (0, 30, 60, 90, 120min post-glucose administration) were analyzed for triglycerides; hormones involved in glucose regulation (insulin, glucagon, glucagon-like peptide (GLP)-1)), energy homeostasis (ghrelin, leptin), and stress response (corticosterone); cytokines (TNF, IL-6); and markers of endothelial dysfunction (VEGF, PAI-1). RESULTS: Glucose peaked at 30min during the IPGTT but not the OGTT (p<0.001), a trend paralleled by insulin, while triglycerides decreased following the IPGTT (transient) and the OGTT (sustained). GLP-1 was transiently decreased while ghrelin and leptin levels increased progressively during the IPGTT alone. Corticosterone was increased during both the IPGTT (sustained) and OGTT (transient). TNF and VEGF were unchanged, while PAI-1 and IL-6 were not detected. Increasing the oral glucose dose to 3g/kg did not significantly alter profiles. DISCUSSION: Results confirm the feasibility of measuring multiple analytes during a GTT, and indicate that administration of glucose can impact metabolic and endocrine profiles in a route-dependent manner.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".