Stage Specificity of Novel Growth Factor Expression During Development of Proliferative Vitreoretinopathy
Bibliographic record
Abstract
To compare the relative levels of connective tissue growth factor (CTGF), platelet-derived growth factor alpha (PDGF-AA), and hepatocyte growth factor (HGF) in glial and retinal pigment epithelial (RPE) cells of epiretinal membranes from proliferative vitreoretinopathy (PVR). A total of 37 PVR membranes, of various stages, underwent fluorescent immunohistochemisty and confocal laser scanning microscopy to localize CTGF, HGF, and PDGF-AA in RPE and glial cells. Numerous RPE, and relatively fewer glial cells, were found in all stages of PVR. CTGF immunoreactivity increased from early to late stage PVR and was principally expressed by RPE cells in early stage, and by glial cells in late stage PVR. HGF, expressed by both RPE and glial cells, was principally expressed in mid-stage PVR. PDGF-AA, expressed by both cell types, demonstrated a uniform level of staining throughout all stages of PVR. RPE and glial cells contribute to the expression of CTGF, HGF, and PDGF-AA during PVR, but with specific developmental patterns. PDGF-AA is expressed uniformly throughout all stages of PVR, while HGF expression peaks during mid stage, and CTGF expression is highest during late stage PVR. These results allow for the development of stage-specific therapeutics for PVR that may allow targeting of the early proliferative and/or the late tractional stages of PVR.
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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 | 0.000 |
| 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".