KETOTIFEN INHIBITS FIBROBLAST CONTRACTILE RESPONSES IN THE PRESENCE OF MAST CELLS
Bibliographic record
Abstract
Summary Previous work in a rabbit model of post-traumatic joint contractures shows that the mast cell stabilizer ketotifen decreases contracture severity. We show here that ketotifen decreases collagen gel contraction mediated by rabbit joint capsule fibroblasts when mast cells are present. Introduction Ketotifen was shown to decrease contracture severity and associated joint capsule fibrosis in an animal model of post-traumatic joint contractures. Ketotifen prevents the release of profibrotic growth factors from mast cells (MC). An in vitro collagen gel contraction assay is used to examine the effect of ketotifen on joint capsule fibroblasts obtained from this animal model. Methods Six New Zealand White rabbits had a standardised procedure to induce post-traumatic joint contractures and the joint capsule was harvested 4 weeks later. The capsules were minced, placed into T75 culture flasks and incubated at 37 0 C in a humidified atmosphere containing 5% CO 2 . The Joint Capsule fibroblasts (JC, 2.5 × 10 5 cells/mL) were mixed with neutralised collagen solution composed of 59% neutralised PureCol collagen I, serum free DMEM/F12 with 1x serum replacement and 1x antibiotic-antimycotic. Aliquots of solution were then cast into wells of a tissue culture plate. Gelation occurred over 3h at 37°C in a humidified incubator. The collagen gel/cells were maintained with DMEM/F-12 plus 1% serum replacement and 1% antibiotic-antimycotic and incubated at 37°C for 12 h. The gels were released and gel area was calculated up to 72h post-release. Different experiments were conducted with various combinations of a human mast cell line (HMC-1, 7.5 × 10 5 cells/mL), the neuropeptide Substance P (SP, 10 −6 M) and Ketotifen fumurate at 10 −4 , 10 −6 , 10 −8 and 10 −10 M. The various interventions were combined with the JC and collagen gel during the gelation step. Statistical comparisons used a two way ANOVA with a Posthoc Tukey test. Significance was set at p Results The JC contracted the collagen gels in all conditions, with statistically significant differences between time intervals from 6 h to 72 h. When ketotifen alone was added to JC, there was no effect on collagen gel contraction in the range of doses tested. Adding MC to JC led to a significantly increased rate of gel contraction that was inhibited by ketotifen in a dose-dependent manner. The effect was maximal with a concentration of 10 −4 M while the effect was absent by the dose of 10 −10 M. There were statistically significant differences amongst different doses except for comparisons between doses closest to each other (10 −4 vs 10 −6 , 10 −6 vs 10 −8 , 10 −8 vs 10 −10 M). Including SP with MC and JC further increased the rate of gel contraction, which was also significantly inhibited by ketotifen in a similar dose-dependent fashion. Discussion/Conclusion Fibroblasts from rabbit joint capsules contract collagen gels with the effect enhanced by the addition of mast cells. Ketotifen prevents the release of mediators by mast cells, and ketotifen modified the collagen gel assay. It appears that the inhibition of the gel contraction by the fibroblasts is via mast cell stabilization since ketotifen had no direct affect on the fibroblasts in the concentrations evaluated. Ketotifen is a medication used in the chronic treatment of asthma. It has a wide safety profile, it is already approved for human use and it is available in oral preparations.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".