Metabolites of prostaglandin synthases as potential biomarkers of Lyme disease severity and symptom resolution
Bibliographic record
Abstract
Lyme disease or Lyme borreliosis (LB) is the commonest vector-borne disease in the North America. It is an inflammatory disease caused by the bacterium Borrelia burgdorferi . The role of the inflammatory processes mediated by prostaglandins (PGs), thromboxanes and leukotrienes (LTs) in LB severity and symptoms resolution is yet to be elucidated. We aim to systematically review and evaluate the role of PGs and related lipid mediators in the induction and resolution of inflammation in LB. We conducted a comprehensive search in PubMed, Ovid MEDLINE(R), Embase and Embase Classic to identify cell-culture, animal and human studies reporting the changes in PGs and related lipid mediators of inflammation during the course of LB. We identified 18 studies to be included into this systematic review. The selected reports consisted of seven cell-culture studies, seven animal studies, and four human studies (from three patient populations). Results from cell-culture and animal studies suggest that PGs and other lipid mediators of inflammation are elevated in LB and may contribute to disease development. The limited number of human studies showed that subjects with Lyme meningitis, Lyme arthritis (LA) and antibiotic-refractory LA had increased levels of an array of PGs and lipid mediators (e.g., LTB 4, 8-isoPGF 2α , and phospholipases A 2 activity). Levels of these markers were significantly reduced following the treatment with antibiotics or non-steroidal anti-inflammatory drugs. Dysregulation of prostaglandins and related lipid mediators may play a role in the etiology of LB and persistence of inflammation that may lead to long-term complications. Further investigation into the precise levels of a wide range of PGs and related factors is critical as it may propose novel markers that can be used for early diagnosis.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".