Resolvin E1 and Cytokines Environment in Skeletally Immature and Adult ACL Tears
Bibliographic record
Abstract
The intra-articular synovial fluid environment in skeletally immature patients following an ACL tear is complex and remains undefined. Levels of inflammatory and anti-inflammatory cytokines change significantly in response to trauma and collectively define the inflammatory environment. Of these factors the resolvins, with their inherent anti-inflammatory, reparative, and analgesic properties, have become prominent. This study examined the levels of resolvins and other cytokines after ACL tears in skeletally immature and adult patients in order to determine if skeletal maturity affects the inflammatory pattern. Skeletally immature and adult patients with an anterior cruciate ligament injury and meniscal tears were prospectively enrolled over a 5-month period. Synovial fluid samples were obtained before surgery quantifying Resolvin E1, IL-1β, TNF-α, and IL-10 by ELISA. Comparisons between skeletally immature patients and adults, the influence of meniscal tear, growth plate maturity and time from trauma were analyzed. Skeletally immature patients had significantly greater levels of Resolvin E1 and IL-10 compared with adults with an isolated anterior cruciate ligament lesion. Among the injured skeletally immature patients Resolvin E1 levels were greater in the open growth plate group compared with those with closing growth plates. Moreover, levels of Resolvin E1 and IL-10 appeared to decrease with time. Our results suggest that skeletally immature patients have a stronger activation of the Resolvin pattern compared to adult patients and that synovial fluid Resolvins could play an antinflammatory role in the knee after anterior cruciate ligament lesion and that its activity may be synergistic with that of IL-10.
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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 | 0.000 | 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".