PXL01 in sodium hyaluronate results in increased PRG4 expression: a potential mechanism for anti-adhesion
Bibliographic record
Abstract
PURPOSE: To investigate the anti-adhesive mechanisms of PXL01 in sodium hyaluronate (HA) by using the rabbit lactoferrin peptide, rabPXL01 in HA, in a rabbit model of healing tendons and tendon sheaths. The mechanism of action for PXL01 in HA is interesting since a recent clinical study of the human lactoferrin peptide PXL01 in HA administered around repaired tendons in the hand showed improved digit mobility. MATERIALS AND METHODS: On days 1, 3, and 6 after tendon injury and surgical repair, reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was used to assess mRNA expression levels for genes encoding the mucinous glycoprotein PRG4 (also called lubricin) and a subset of matrix proteins, cytokines, and growth factors involved in flexor tendon repair. RabPXL01 in HA was administered locally around the repaired tendons, and mRNA expression was compared with untreated repaired tendons and tendon sheaths. RESULTS: We observed, at all time points, increased expression of PRG4 mRNA in tendons treated with rabPXL01 in HA, but not in tendon sheaths. In addition, treatment with rabPXL01 in HA led to repression of the mRNA levels for the pro-inflammatory mediators interleukin (IL)-1β, IL-6, and IL-8 in tendon sheaths. CONCLUSIONS: RabPXL01 in HA increased lubricin mRNA production while diminishing mRNA levels of inflammatory mediators, which in turn reduced the gliding resistance and inhibited the adhesion formation after flexor tendon repair.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".