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OBJECTIVE
To identify the risk factors of hypertrophic scarring (HS) after thyroidectomy and construct a risk prediction model.
METHODS
From November 2018 to March 2019, the clinical data of patients undergoing thyroidectomy were collected for retrospective analysis. According to the occurrence of HS, the patients were divided into an HS group and a non-HS group. Univariate analysis and binary logistic regression analysis were conducted to explore the independent risk factors for HS. Receiver operating characteristic analysis was also carried out.
RESULTS
In this sample, 121 of 385 patients developed HS, an incidence of 31.4%. Univariate analysis showed significant differences in sex, age, postoperative infection, history of abnormal wound healing, history of pathologic scar, family history of pathologic scar, and scar prevention measures between the two groups (P < .05). Binary logistic regression analysis indicated that age 45 years or younger (odds ratio [OR], 1.815), history of abnormal wound healing (OR, 4.247), history of pathologic scarring (OR, 9.840), family history of pathologic scarring (OR, 5.708), and absence of preventive scar measures (OR, 5.566) were independent factors for HS after thyroidectomy. The area under the receiver operating characteristic curve was 0.837. When the optimal diagnostic cutoff value was 0.206, the sensitivity was 0.661, and the specificity was 0.932.
CONCLUSIONS
The development of HS after thyroidectomy is related to many factors, and the proposed risk prediction model based on the combined risk factors shows a good predictive value for postoperative HS. When researchers consider the prevention and treatment of scarring in patients at risk, the incidence of HS in different populations can provide theoretical support for clinical decision-making.
Objective
To investigate the relationship among natural aging of epidermal cells, epigenetics, and SPRY1 methylation mechanism.
Methods
Immunohistochemistry, reverse transcription‐PCR (RT‐PCR), and Western blot were used to detect the expression of DNA methyltransferase 1 (DNMT1) and Sprouty1 (SPRY1) in skin epithelial cells from different age groups. An aging model of HaCaT cells was constructed. In HaCaT cells and their aging groups, DNMT1 and SPRY1 expression were detected by RT‐PCR and WB. SPRY1 methylation status in epidermal cells from different age groups and HaCaT cells were detected by Methylation‐Specific PCR (MS‐PCR).
Results
The expression of DNMT1 and SPRY1 in skin epithelial cells from natural aging groups decreased with age; there was no significant difference in the expression of DNMT1 in HaCaT cells and the different age groups. The expression of SPRY1 in HaCaT cells was lower than it was in the aging groups. The methylation status of SPRY1 gradually decreased as the age of skin epidermal cells increased, while the methylation status of SPRY1 was not different between HaCaT cells and the aging group.
Conclusion
DNMT1 is involved in the regulation of natural aging of skin epidermal cells but has a nominal role in our induced aging model. SPRY1 is involved in natural aging and induced aging of skin epidermal cells. The regulation of SPRY1 methylation is involved in the natural senescence of skin epidermal cells, while the induced aging of epidermal cells is nominally involved in the mechanism of SPRY1 methylation.
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