Comparison of microRNA expression in pseudoexfoliation syndrome with and without glaucoma
Bibliographic record
Abstract
BACKGROUND/AIMS: Pseudoexfoliation syndrome (PXS) is associated with increased risk of glaucoma, but the underlying molecular mechanisms remain unclear. This study aimed to compare microRNA (miRNA) expression profiles between PXS with glaucoma (PXSG) and PXS without glaucoma (PXSWG). METHODS: We enrolled 24 PXS patients undergoing cataract surgery, dividing them into PXSG (n=16) and PXSWG (n=8) groups. miRNA expression in anterior lens capsule tissue was analysed using NanoString nCounter technology. Differentially expressed miRNAs were identified, and functional pathway analysis was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG). The correlations between miRNA expression and clinical variables, including glaucoma severity, endothelial cell counts (ECCs) and systemic factors identified in serum blood tests, were also examined. RESULTS: Using a panel of 827 miRNAs, 23 upregulated miRNAs in PXSG were identified, miRNA-(miR-)887-3 p and miR-933 exhibiting the highest differential expression. The KEGG highlighted enrichment in pathways related to ageing and signal transduction. Elevated levels of several miRNAs, miR-933 and miR-302a-3p, were linked to worse visual field (VF) and thinner peripapillary retinal nerve fibre layer thickness (pRNFLT). Multivariate regression analysis identified associations of miR-302a-3p with lower ECC, miR-302f with thinner pRNFLT and miR-614 with higher triglyceride levels. CONCLUSION: This study indicates potential differences in miRNA expression between PXSG and PXSWG, with several showing suggestive associations with key clinical parameters. These preliminary findings may provide valuable insights into processes relevant to PXS and glaucoma but require validation in larger, independent cohorts to clarify their biomarker potential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".