Local oral and nasal microbiome diversity in age-related macular degeneration
Bibliographic record
Abstract
Age-related macular degeneration (AMD) is a chronic degenerative disease of the retina. Recent reports have highlighted the potential role of mucosal surface microbes in the pathogenesis of AMD. In this case-control study, the composition of the nasal and oral microbiota in newly diagnosed neovascular age-related macular degeneration cases (6 male, 7 female) was compared to controls without retinal diseases (2 male, 3 female). PCR amplification of 16S rRNA genes was performed with universal primers amplifying the V4 variable region (515F-806R). Distinct microbial community characterization was achieved using Principal Coordinates Analysis (PCoA) of the Bray-Curtis index with comparative analysis between cases and controls performed within QIIME 2. Sequencing of all cases and controls revealed clear separation with strong beta diversity between oral and nasal microbial communities (p < 0.001). Microbial composition differed between cases and controls in both oral and nasal samples. The top three oral microbes identified as different compared to controls included Burkholderiales (7.41 log2fold change, p = 3.29E-05), Actinomyceataceae (6.22 log2fold change, p = 3.73E-06) and Gemella (5.28 log2fold change, p = 0.0002). The top three nasal microbes identified as different compared to controls included Rothia (13.6 log2fold change, p = 3.63E-18), Actinobacteria (10.29 log2fold change, p = 9.81E-10) and Propionibacteriales (8.73 log2fold change, p = 6.74E-09). These relative shifts in communities of bacteria detected in newly diagnosed neovascular AMD patients may suggest additional mechanistic links in disease pathogenesis.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".