Diet-induced obesity leads to pro-inflammatory alterations to the vitreous humour of the eye in a rat model
Bibliographic record
Abstract
OBJECTIVE AND DESIGN: The purpose of this study was to investigate if diet-induced obesity (DIO) and subsequent low-level systemic inflammation would result in local increases in pro-inflammatory mediators in the vitreous humour (VH) of the eyes of rats. METHODS: Assay was conducted on VH fluid and serum. RESULTS: Increased protein levels for IL-1β, IL-6, and IL-18 in both serum and VH fluid were observed. VH protein levels for IL-13 and IL-17 were also increased. All mediators significantly increased in VH fluid were also positively correlated with percent body fat. Increased mRNA levels in VH cells for an oxidative stress molecule were accompanied by decreased mRNA levels for an antioxidant scavenger, suggesting an antioxidant/oxidant imbalance in the VH with DIO. In addition, decreased mRNA levels for TRAIL, FAS-L and TGF-β, molecules associated with immune privilege, were also significantly depressed. CONCLUSIONS: DIO-related metabolic disturbances disrupt VH homeostasis in a manner that reflects development of a pro-inflammatory environment. Prolonged exposure to such an environment may lead to overt pathologies with compromised eye function.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".