Soluble low affinity nerve growth factor receptor (sLNGFR) may regulate pain in knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: Nerve growth factor β (β-NGF) is a protein which is important to the development of neurons particularly those involved in the transmission of pain and is central to the experience of pain in osteoarthritis (OA). Direct NGF antagonism has been shown to reduce OA pain but is associated with rapidly progressive OA. The aim of the study is to investigate the ability of soluble neurotrophin receptors in the NGF pathway to modulate pain in OA. METHODS: Synovial fluid (SF) was obtained from the knee joints of 43 subjects who underwent total knee arthroplasty. Visual analogue scale (VAS) pain scores were obtained prior to surgery. Customised-automated-ELISAs and commercial-ELISAs and LEGENDplex™ were used to measure soluble low-affinity nerve growth factor (LNGFR), soluble tropomyosin receptor kinase (TrkA), proNGF, β-NGF, other neurotrophins (NT) and cytokines including inflammatory marker TNF-α. RESULTS: The VAS score positively correlated with β-NGF (r=0.34) and there was positive association trend with neurotrophin-3 (NT-3), BDNF and negative association trend with ProNGF. sLNGFR positively correlated with VAS (r=0.33). The β-NGF/soluble TrkA ratio showed a strong positive correlation with VAS (r=0.80). In contrast, there was no correlation between pain and the β-NGF/sLNGFR ratio (r=-0.08). TNF-α positively correlated with β-NGF (r=0.83), NT-3 (r=0.66), and brain-derived neurotrophic factor (BDNF) (r=0.50) and negatively with ProNGF (r= -0.74) and positively correlated with both soluble TrkA (r=0.62), sLNGFR (r=0.26). CONCLUSIONS: This study suggests that endogenous or cleaved sLNGFR, but not soluble TrkA may participate in OA pain modulation thus supporting further research into soluble LNGFR as a therapeutic target in OA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".