Abstract Background The development of rosacea is suggested to be closely associated with lipid metabolism, inflammation, and anxiety/depression. Gamma linolenic acid (GLA) is a key factor participating in lipid metabolism, which is also confirmed to regulate the inflammatory response. However, the associations of serum GLA levels with rosacea severity and psychological status still remain unclear. Objective and limitations of the study The present study aimed to investigate the associations of gamma linolenic acid (GLA), a key factor participating in lipid metabolism and the inflammatory response, with rosacea severity and psychological status. The present study still had some limitations. First, this study is a cross-sectional study and does not provide longitudinal evidence about the relationship between GLA and rosacea; Second, the cohort in this study is also relatively small, and a larger cohort is needed in further investigation to reveal the potential role of lipid metabolism in the pathogenesis of rosacea. Methods A total of 62 rosacea patients were consecutively recruited. Patient’s Self-Assessment (PSA) scale and Clinician Erythema Assessment (CEA) as well as 7-item Generalized Anxiety Disorder (GAD-7) and 9-item Patient Health Questionnaire (PHQ-9) were conducted to evaluate the degree of erythema severity and anxiety/depression, respectively. Serum GLA levels were determined by gas chromatography mass. Results Lower levels of serum GLA in rosacea patients were observed (p < 0.001), and subgroup analysis revealed that patients with higher-level GLA had lower scores of PSA, CEA, GAD-7 and PHQ-9. Moreover, Spearman correlation analysis uncovered that serum GLA levels were negatively associated with PSA, CEA, GAD-7 as well and PHQ-9 scores, respectively. Linear regression model found that serum GLA levels at baseline were a predictive factor for prognosis of clinical outcomes after 1-month conventional treatment. Conclusion The present study indicates that lower levels of serum GLA in rosacea patients are negatively associated with the degree of erythema and anxiety/depression status. inflammation anxietydepression anxiety depression (GLA response However unclear GLA, , First crosssectional cross sectional Second small 6 recruited Patients s SelfAssessment Self PSA (PSA CEA (CEA 7item item 7 GAD7 GAD (GAD-7 9item 9 PHQ9 PHQ (PHQ-9 respectively mass p 0.001, 0001 0.001 0 001 0.001) higherlevel higher level GAD- PHQ9. 9. Moreover PHQ- 1month month 1 treatment (GAD- (PHQ- 000 0.00 00 (GAD (PHQ 0.0 0.

ABSTRACT The mechanical properties of magnesium alloy in different molding stages are very important factors to determine its application approaches in engineering. In order to ensure the prediction accuracy of mechanical properties, a TCMSSA-ELM model, which is a hybrid of the sparrow search algorithm (SSA) optimized by the tent chaotic mapping (TCM) algorithm and the extreme learning machine (ELM), is proposed in this study, and the stresses of AZ80 magnesium alloy are predicted by the model through a 812-record dataset. The predicting results indicate that TCMSSA improves the accuracy of ELM model. Compared with ELM model, the data points formed by experimental values of stress and the predicted ones by TCMSSA-ELM model are closer to the ideal 45° line, the average determination coefficient rises by 1.43%, and the average root mean squared error (RMSE) decreases by nearly 61.96%, implying that TCMSSA-ELM model accurately reflects the influence rule of thermodynamic parameters on stress. The novelty of this study is that TCM is used to optimize the population initialization of SSA, which enables SSA to have a higher global search ability, and thus optimizes the weight and threshold selection of ELM, then making TCMSSA-ELM have higher prediction accuracy than other improved ELM models. engineering TCMSSAELM (SSA (TCM , (ELM) AZ AZ8 812record record 812 dataset 45 line 143 1 43 1.43% RMSE (RMSE 6196 61 96 61.96% ability models (ELM 81 4 14 1.43 619 6 9 61.96 8 1.4 61.9 1. 61.

Abstract Objectives The pathological mechanisms of patients with Renal Cell Carcinoma (RCC) remain defined. This study aimed to evaluate relationships between the landscape of gene mutations and their clinical significance in RCC patients. Methods Tissue and peripheral blood samples of 42 patients with RCC were collected and performed for the Next Generation Sequencing (NGS) with Geneseeq PrimeTM 425-gene panel probes. Their landscapes of gene mutation were analyzed. We also carried out an evaluation of Tumor-Node-Metastasis (TNM) staging, RENAL nephelometry score, surgery, and targeted drug treatment of patients. Then we compared the correlations of landscape in gene mutations and the prognosis. Results The most common gene alternations, including BAP1, PBRM1, SETD2, CSF1R, NPM1, EGFR, POLE, RB1, and VHL genes, were identified in tissue and blood samples of 75% of patients. EGFR, POLE, and RB1 gene mutations frequently occurred in relapsed and metastatic patients. BAP1, CCND2, KRAS, PTPN11, ERBB2/3, JAK2, and POLE were presented in the patients with > 9 RENAL nephelometry score. Univariable analysis indicated that SETD2, BAP1, and PBRM1 genes were key factors for Disease-Free Survival (DFS). Multivariable analysis confirmed that mutated SETD1, NPM1, and CSF1R were critical factors for the Progression Free Survival (PFS) of RCC patients with target therapy. Conclusions Wild-type PBRM1 and mutated BAP1 in patients with RCC were strongly associated with the outcomes of the patient. The PFS of the patients with SETD2, NPM1, and CSF1R mutations were significantly shorter than those patients without variants. (RCC defined 4 NGS (NGS 425gene 425 probes analyzed TumorNodeMetastasis Tumor Node Metastasis TNM (TNM staging score surgery prognosis alternations BAP PBRM SETD2 SETD CSFR CSF R NPM1 NPM EGFR RB 75 CCND2 CCND KRAS PTPN11 PTPN ERBB23 ERBB ERBB2 3 ERBB2/3 JAK2 JAK DiseaseFree Disease DFS. DFS . (DFS) SETD1 (PFS therapy Wildtype Wild type patient variants 7 PTPN1 ERBB2/ (DFS

Abstract Purpose: To evaluate the changes of caveolin-1 in lung fibroblasts in newborn Wistar rats when exposed to hyperoxic conditions, as well as lung fibroblasts cell cycle. Methods: One hundred newborn Wistar rats were randomly divided (50 rats/group) into experimental and control groups, exposed to hyperoxic conditions or normal air, respectively. The fraction of inspired oxygen (FiO2) in the experimental group was 90%, whereas this value was 21% in the control group. Lung fibroblasts were collected on days 3, 7, and 14 of the experiment. Caveolin-1 expression dynamics in lung fibroblasts was assayed in each group by immunofluorescence and Western blot analyses. Flow cytometry (FCM) was used to assess the proportions of lung fibroblasts at different stages of the cell cycle. Results: On day 3, no significant difference in caveolin-1 expression was observed between the hyperoxic and control groups; however, on days 7 and 14, caveolin-1 expression was significantly lower in the hyperoxic group than in the control (P<0.05). No apparent differences were observed in caveolin-1 expression in the control group at the different time points. Using FCM analysis, we showed that the proportion of lung fibroblasts in G0/G1 phase in the hyperoxic group decreased compared to that of the control group on day 7, while the proportion of S-phase cells increased (P<0.05). These differences were more significant when the groups were compared on day 14 (P<0.01). Conclusion: After seven days the exposure to hyperoxic conditions, lung fibroblasts proliferated and caveolin-1 expression decreased.