Bibliographic record
Abstract
Proliferative vitreoretinopathy (PVR) is known to be the most common sight-seeing complication of retinal detachment. The pathogenesis of PVR is characterized by the proliferation and migration of retina pigmented epithelial cells, which leads to formation of contractile cellular membranes and retinal breaks, as well as immune cell infiltration. The Endocannabinoid system modulates immune response; cannabinoid receptor 2 (CB2) is expressed in the cells of the immune system, but also found in the retina. The activation of the CB2 receptor by endogenous or exogenous ligands produces biological activities of immune function; the expression of this receptor is up-regulated by the activation of various inflammatory triggers. The purpose of this study is to further understand what role the CB2 receptor plays during inflammation in the retina and if it is involved in the mediation of immunosuppressive effects. \nAn animal model (mice) was used to induce PVR with an intraocular injection (0.2μl) of 0.1U dispase, a proteolytic enzyme. The severity of PVR in wild type (WT) and CB2-/- saline and dispase groups were evaluated through the observation of cross-sectioned H&E stained ocular tissues. IL-1[beta] cytokine concentrations were captured using an enzyme linked immunosorbent assay with IL-1[beta] sensitive antibodies. \nHistological H&E staining demonstrated pronounced ocular damage in CB2-/- animals compared to WT animals. IL-1[beta] cytokine concentrations showed no significant difference (p>0.05) between WT and CB2-/- animals. \nFrom the results, the ocular damage was more pronounced in CB2-/- mice as compared to WT mice, which suggests an immunodulatory role for CB2 receptors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".