An Overview of the Dry Eye Disease in Sjögren’s Syndrome Using Our Current Molecular Understanding
Bibliographic record
Abstract
Sjögren's syndrome is a chronic and insidious auto-immune disease characterized by lymphocyte infiltration of exocrine glands. The patients typically present with ocular surface diseases related to dry eye and other systemic manifestations. However, due to the high prevalence of dry eye disease and the lack of objective and clinically reliable diagnostic tools, discriminating Sjögren's syndrome dry eye (SSDE) from non-Sjögren's syndrome dry eye (NSSDE) remains a challenge for clinicians. Diagnosing SS is important to improve the quality of life of patients through timely referral for systemic workups, as SS is associated with serious systemic complications such as lymphoma and other autoimmune diseases. The purpose of this article is to describe the current molecular understanding of Sjögren's syndrome and its implications for novel diagnostic modalities on the horizon. A literature review of the pre-clinical and clinical studies published between 2016 and 2022 was conducted. The SSDE pathophysiology and immunology pathways have become better understood in recent years. Novel diagnostic modalities, such as tear and saliva proteomics as well as exosomal biomarkers, provide hope on the horizon.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".