Gaseous nitric oxide exhibits minimal effect on skin fibroblast extracellular matrix gene expression and immune cell viability
Why this work is in the frame
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Bibliographic record
Abstract
NO (nitric oxide) molecule is produced by various mammalian cell types and plays a significant role in inflammation, infection and wound healing processes. Recently, gNO (gaseous nitric oxide) therapy has been utilized for its potential clinical application as an antimicrobial agent, with special focus on skin infection. In a previous study, we demonstrated that 200 ppm gNO, 8 h/day for three consecutive days significantly reduced the number of bacteria in dermal wounds without compromising the viability and function of skin cells. To increase the feasibility and ease of its clinical use, we propose that different doses of gNO (5 to 10 K ppm) for 8 h and as short as 10 min be used, respectively. To achieve this, we set up in vitro experiments and asked whether (i) different doses of gNO have any toxic effect on immune cells and (ii) gNO has any modulating effect on key ECM (extracellular matrix) components in fibroblasts. To further investigate the effect of gNO, expression of more than 100 key ECM genes have been examined using gene array in human fibroblasts. As immune cells play an important role in wound healing, the effect of gNO on proliferation and viability of human and mouse lymphocytes was also examined. The findings showed that, the 5, 25, 75 and 200 ppm of gNO for 8 h slightly increased the expression of Col 5A3 (collagen type V alpha 3), and gNO at 5 ppm decreased the expression of MMP-1 (matrix metalloproteinase 1), while exposure of fibroblast to 10 K ppm of gNO for 10 min does not show any significant changes in ECM genes. Exposure to gNO resulted in inhibition of lymphocyte proliferation without affecting the cell viability. Taken together, our findings show that skin could be treated with gNO without compromising the role of ECM and immune cells in low concentrations with long time exposure or high concentrations for a shorter exposure time.
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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 | 0.000 | 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 | 0.001 |
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 it