Lipid Metabolism: An Emerging Player in Sjögren’s Syndrome
Bibliographic record
Abstract
Sjögren's syndrome (SS) is a chronic autoimmune disorder that primarily affects the exocrine glands. Due to the intricate nature of the disease progression, the exact mechanisms underlying SS are not completely understood. Recent research has highlighted the complex interplay between immune dysregulation and metabolic abnormalities in inflammatory diseases. Notably, lipid metabolism has emerged as a crucial factor in the modulation of immune function and the progression of autoimmune diseases, including SS. This review explores the prevalence of dyslipidemia in SS, emphasizing its role in the onset, progression, and prognosis of the disease. We specifically described the impact of altered lipid metabolism in exocrine glands and its association with disease-specific features, including inflammation and glandular dysfunction. Additionally, we discussed the potential clinical implications of lipid metabolism regulation, including the role of polyunsaturated fatty acids (PUFAs) and their deficits in SS pathogenesis. By identifying lipid metabolism as a promising therapeutic target, this review highlights the need for further research into lipid-based interventions for the management of SS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".