The effect of flashlamp pulsed dye laser on the expression of connective tissue growth factor in keloids
Bibliographic record
Abstract
OBJECTIVE: To investigate connective tissue growth factor (CTGF) expression before and after pulsed dye laser (PDL, 595 nm) treatment, and to better understand the mechanism of PDL treatment of keloids. METHOD: Twenty-six patients with keloids were recruited for this study. For each patient, two keloids of similar anatomic location, duration, texture, and appearance were chosen for study; one of these keloids was treated and the other served as a control. Three sessions of PDL treatment, with pulse duration of 1.5 milliseconds, spot size 7 mm, DCD duration 20 milliseconds/delay 10 milliseconds and fluence of 10 J/cm(2), were performed on the keloids at 3- to 4-week intervals. Punch biopsies were performed both on the treated and untreated keloids prior to the first treatment and after the final treatment. The specimens underwent realtime polymerase chain reaction (PCR) and immunohistochemistry (IHC) to investigate the CTGF mRNA and protein expression after PDL treatment. RESULTS: According to realtime PCR, the CTGF mRNA was significantly down-regulated after PDL treatment in 80.77% of patients as compared to the control group. IHC investigation showed that after treatment the CTGF positive cells also significantly decreased in number as compared to the control group in 80.77% of patients. Using the Vancouver scar scale (VSS), there was an average decrease of 20.85 ± 12.33% after PDL treatment. CONCLUSIONS: Pulsed dye laser treatment of keloids significantly down-regulates the expression of CTGF in most cases. This may partially explain the mechanism of action of PDL treatment of keloids.
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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) | 0.001 | 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".