Characterization of synovial fluid cytokine profiles in chronic meniscal tear of the knee
Bibliographic record
Abstract
Concentrations of pro- and anti-inflammatory cytokines in synovial fluid samples collected from patients with chronic meniscal tears were investigated. An acute inflammatory response is generally reported 24-48 h after knee injury, but the largest body of data available in literature concerns anterior cruciate ligament injury and very little information is available about the balance of soluble factors in the synovial fluid of knees with chronic meniscal tears. Sixty-nine patients (46 males and 23 females) with meniscal tear that occurred more than 3 months earlier were enrolled. According to cartilage integrity assessment by arthroscopic examination, patients were assigned to one of the following groups: (i) no chondral damage (n = 18); (ii) chondral damage graded from I to II (n = 15); and (iii) chondral damage graded from III to IV (n = 37). In all groups, levels of IL-10 and inflammatory cytokines IL-6, TNF-α, and IL-8 where greater compared with those reported in the intact population; by contrast, levels of IL-1ra and IL-1β were significantly lower. Interestingly, IL-6 levels were higher in female than male patients. Cytokine levels did not correlate with degree of chondral damage. IL-6 and IL-1ra levels positively correlated with IL-1β, and negatively correlated with TNF-α. Interestingly, levels of IL-1β and TNF-α were inversely correlated. Our data demonstrate increased levels of pro-inflammatory cytokines (IL-6, IL-8, and TNF-α) in the chronic phase of meniscal trauma. This pro-inflammatory state is maintained in the joint from the time of initial injury to several months later and could be a key factor in hampering cartilage regeneration. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:340-346, 2017.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".