Background: Acne vulgaris (AV) is a chronic inflammatory disease of the pilosebaceous unit. Many factors are involved in the occurrence of acne. It has been confirmed that some adipokines play an important role in the development of AV. Irisin is a novel adipokine, which is highly expressed in skeletal muscle, liver, and fat. It improves insulin resistance (IR) by inducing the browning of white adipose tissue, increasing heat production and energy expenditure. Objective: The purpose of this study was to investigate the role of serum irisin as an adipokine to explore its function in the pathogenesis of AV and its correlation with IR, and whether it can be used as a potential biomarker of insulin sensitivity. Although the hyperinsulinemic-euglycemic clamp remains the gold standard for accurate determination of IR, it cannot be performed routinely. Various alternative simpler measures have been used, the most common being homeostasis model assessment. However, these metrics are limited by their accuracy, cost, and blood collection requirements.[1] Therefore, an effective and feasible serum biomarker is an attractive and relatively straightforward method, which may provide clinicians with a more accurate and simple method for the prediction and diagnosis of IR. IR can often be detected before other symptoms appear, so establishing an early diagnosis method will allow for the appropriate treatment of patients before the disease develops. Patients and Methods: The study included 171 subjects; 115 patients with newly diagnosed AV and 56 apparently healthy subjects. The contents of irisin and interleukin-1 alpha in serum were determined by enzyme-linked immunosorbent assay. The IR index was calculated by the homeostasis model. Results: Serum irisin levels in AV patients and control group were (24.0 ± 11.3) and (104.3 ± 27.0) ng/dl, respectively, which were significantly lower than those in control group (P < 0.001). Serum irisin was negatively correlated with IR (r = −0.711, P 0.001). The sensitivity of irisin was 100.0%, the specificity was 92.8%, and the cutoff point was 53.32. The decrease of serum irisin level could predict the patients with IR in acne. Conclusion: Serum irisin levels in AV patients were significantly decreased. Serum irisin showed acceptable performance criteria in the diagnosis of AV with IR. Serum irisin seems to be a good diagnostic and prognostic marker for IR. Further multi-center studies are needed to confirm this link, which could pave the way for new treatment options.

Background: To explore the role and clinical significance of serum adiponectin and leptin levels in patients with psoriasis accompanied by atherosclerosis. Methods: Eighty patients diagnosed with psoriasis in our dermatology department and 40 healthy people in our physical examination centre were included as the study group and control group, respectively. All the included patients underwent fasting blood and serum tests. Levels of adiponectin, leptin, and the blood lipid content; colour Doppler ultrasonography of both common carotid arteries, internal carotid and external carotid arteries; and intimal-medial thickness (IMT) and carotid plaque were evaluated. Results: In the study group, the leptin level increased, and the serum adiponectin level decreased; these levels were statistically significantly different compared with those in the control group (t = 6.774, P < 0.001 and t = –3.511, P < 0.05, respectively). IMT was negatively correlated with adiponectin levels (r = –0.378, P < 0.001) and positively correlated with leptin levels (r = 0.581, P < 0.001). Conclusions: The imbalanced expression of serum and adiponectin levels will aggravate psoriasis and promote the occurrence of atherosclerosis. Serum levels can be used to assess the disease severity, detect vascular lesions early, and prevent the development of psoriasis to cardiovascular disease.

Background For clinical workers, disease-specific death is a better indicator of tumor severity. Breast cancer is the most prevalent malignancy in women. Luminol type B breast cancer is one of the biggest threats to women's health, and few studies have paid attention to its specific death. Early recognition of luminol type B breast cancer allows clinicians to assess the prognosis and develop more optimal treatment plans. Methods In this study, the basic information of luminal B population, clinical and pathological characteristics, treatment regimen and survival data were collected from the SEER database. The patients were randomly divided into a training group and a validation group. The single-factor and multi-factor competitive risk models were used to analyze the independent influencing factors of tumor-specific death, and the predictive nomogram based on the competitive risk model was constructed. The consistency index (C-index) and calibration curves over time were used to evaluate the accuracy of the predicted nomograms. Results This study included a total of 30,419 luminal B patient. The median follow-up period was 60 (IQR: 44–81) months. Among the 4,705 deaths during the follow-up period, 2,863 patients died specifically, accounting for 60.85% of the deaths. The independent predictive factors of cancer-specific mortality were: married, primary site, grade, stage, the primary site of operation, radiotherapy, chemotherapy, metastasis (lymph node, bone, brain, liver, lung), and Estrogen Receptor and Progesterone Receptor status. In the training cohort, the C-index of the predictive nomogram was 0.858, and the area under the receiver operating characteristic curve (AUC) for the first, third, and fifth years was 0.891, 0.864, and 0.845. The C-index of the validation cohort was 0.862, and the AUC for the first, third, and fifth years was 0.888, 0.872, and 0.849. The calibration curves of the training and validation cohorts showed that the predicted probability of the model was very consistent with the actual probability. And the 5-year survival rate according to the traditional survival analysis was 9.49%, while the 5-year specific mortality rate was only 8.88%. Conclusions The luminal B competing risk model we established has ideal accuracy and calibration.