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- Li, Wei, et al.
(författare)
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Non-lab and semi-lab algorithms for screening undiagnosed diabetes : A cross-sectional study
- 2018
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Ingår i: EBioMedicine. - : ELSEVIER SCIENCE BV. - 2352-3964. ; 35, s. 307-316
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Tidskriftsartikel (refereegranskat)abstract
- Background: The terrifying undiagnosed rate and high prevalence of diabetes have become a public emergency. A high efficiency and cost-effective early recognition method is urgently needed. We aimed to generate innovative, user-friendly nomograms that can be applied for diabetes screening in different ethnic groups in China using the non-lab or noninvasive semi-lab data. Methods: This multicenter, multi-ethnic, population-based, cross-sectional study was conducted in eight sites in China by enrolling subjects aged 20-70. Sociodemographic and anthropometric characteristics were collected. Blood and urine samples were obtained 2 h following a standard 75 g glucose solution. In the final analysis, 10,794 participants were included and randomized into model development (n - 8096) and model validation (n = 2698) group with a ratio of 3:1. Nomograms were developed by the stepwise binary logistic regression. The nomograms were validated internally by a bootstrap sampling method in the model development set and externally in the model validation set. The area under the receiver operating characteristic curve (AUC) was used to assess the screening performance of the nomograms. Decision curve analysis was applied to calculate the net benefit of the screening model. Results: The overall prevalence of undiagnosed diabetes was 9.8% (1059/10794) according to ADA criteria. The non-lab model revealed that gender, age, body mass index, waist circumference, hypertension, ethnicities, vegetable daily consumption and family history of diabetes were independent risk factors for diabetes. By adding 2 h post meal glycosuria qualitative to the non-lab model, the semi-lab model showed an improved Akaike information criterion (AIC: 4506 to 3580). The AUC of the semi-lab model was statistically larger than the non-lab model (0.868 vs 0.763, P < 0.001). The optimal cutoff probability in semi-lab and non-lab nomograms were 0.088 and 0.098, respectively. The sensitivity and specificity were 76.3% and 81.6%, respectively in semi-lab nomogram, and 72.1% and 673% in non-lab nomogram at the optimal cut off point. The decision curve analysis also revealed a bigger decrease of avoidable OGTT test (52 per 100 subjects) in the semi-lab model compared to the non-lab model (36 per 100 subjects) and the existed New Chinese Diabetes Risk Score (NCDRS, 35 per 100 subjects). Conclusion: The non-lab and semi-lab nomograms appear to be reliable tools for diabetes screening, especially in developing countries. However, the semi-lab model outperformed the non-lab model and NCDRS prediction systems and might be worth being adopted as decision support in diabetes screening in China.
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| 2. |
- Li, Dongqing, et al.
(författare)
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miR-19a/b and miR-20a promote wound healing by regulating the inflammatory response of keratinocytes
- 2021
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Ingår i: Journal of Investigative Dermatology. - : Elsevier. - 0022-202X .- 1523-1747. ; 141:3, s. 659-671
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Tidskriftsartikel (refereegranskat)abstract
- Persistent and impaired inflammation impedes tissue healing and is characteristic of chronic wounds. A better understanding of the mechanisms controlling wound inflammation is needed. Here we show that in human wound-edge keratinocytes, the expression of miR-17, miR-18a, miR-19a, miR-19b, and miR-20a, which all belong to the miR-17∼92 cluster, is upregulated during wound repair. However, their levels are lower in chronic ulcers than acute wounds at the proliferative phase. Conditional knockout of miR-17∼92 in keratinocytes as well as injection of miR-19a/b and miR-20a antisense inhibitors into wound-edges enhanced inflammation and delayed wound closure in mice. In contrast, conditional overexpression of the miR-17∼92 cluster or miR-19b alone in mice keratinocytes accelerated wound closure in vivo. Mechanistically, miR-19a/b and miR-20a decreased TLR3-mediated NF-κB activation by targeting SHCBP1 and SEMA7A, respectively, reducing the production of inflammatory chemokines/cytokines by keratinocytes. Thus, as crucial regulators of wound inflammation, lack of miR-19a/b and miR-20a may contribute to sustained inflammation and impaired healing in chronic wounds. In line with this, we show that a combinatory treatment with miR-19b and miR-20a improved wound healing in a mouse model of type 2 diabetes.
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