Highly Expressed Amyloid Beta-42 Of Aqueous Humor In Patients With Neovascular Macular Degeneration
Bibliographic record
Abstract
Background: Age-related macular degeneration (AMD) is a type of macular degeneration disease, and amyloid beta (aβ) is the main component of vitreous warts in AMD patients. Neovascular AMD (nAMD) is the most serious type of AMD, but its pathogenesis remains unclear. The aim of this study was to detect the expression of aβ42 in the aqueous humor of nAMD patients and to evaluate whether aβ42 expression of aqueous humor is correlated with cognitive function in these patients.Methods: A total of 70 patients were enrolled in this study, including 50 nAMD patients (nAMD group) and 20 patients with cataract (control group). The cognitive function of the patients was assessed using the Mini-Mental State Examination and Montreal Cognitive Assessment Scale, and based on their scores, 50 patients with nAMD were divided into two subgroups: the p-nAMD group (18 nAMD patients with normal cognition) and the ci-nAMD group (32 nAMD patients with cognitive impairment). An immunofluorescence microsphere probe technique was used to detect the aβ42 expression of aqueous humor in all patients. Pearson correlation analysis was used.Results: The aβ42 expression of aqueous humor was significantly higher in the nAMD group (124.56 ± 41.93 pg/mL) as compared with the control group (82.94 ± 33.75 pg/mL; P < .01). There was no significant difference in aβ42 expression of aqueous humor between the p-nAMD group (136.42 ± 51.68 pg/mL) and ci-nAMD group (117.90 ± 34.46 pg/mL; P = .14).Conclusion: In nAMD patients, aβ42 was highly expressed in the aqueous humor but was not correlated with cognitive function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".