Background: Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based assays are employed in more and more clinical laboratories to quantify steroids. The steroid quantification by LC-MS/MS shows great value in screening or diagnosing endocrine disorders; however, the number of functional steroids included in the LC-MS/MS methods is still limited. Methods: Here, we describe the performance and validation of a 20-steroid plasma panel by LC-MS/MS. The panel included progestogens (including mineralocorticoids and glucocorticoids), androgens and estrogens biosynthesized in steroid metabolic pathways. The LC-MS/MS method was validated according to guidance documents, and subsequently employed to profile steroid changes in endocrine disorders. Results: Using LC-MS/MS, 20 steroids were separated and quantified in 8 min. Coefficients of variation (CVs) of the 20 analytes at the lower limit of quantification (LLoQ) were all less than 15% (ranging from 1.84% to 14.96%). The linearity of the assay was demonstrated by all the R² values greater than 0.995. Individual plasma steroids changed significantly in patients with subclinical Cushing’s syndrome (SCS) and polycystic ovary syndrome (PCOS) – 17-hydroxypregnenolone (17-OH-PR), testosterone (T) and dihydrotestosterone (DHT) were significantly decreased in SCS patients, while in PCOS patients, pregnenolone, corticosterone (CORT), androstenedione (A4) and T were significantly increased and DHT was decreased. Conclusions: The LC-MS/MS method we developed for the quantification of 20 plasma steroids is clinical practicable. The steroid profiling data using this assay indicate its screening value for endocrine disorders. To further explore the value of the assay, more investigations are however needed.

Filamentous actin (F-actin) cytoskeletal remodeling is critical for glucose-stimulated insulin secretion (GSIS) in pancreatic β-cells, and its dysregulation causes type 2 diabetes. The adaptor protein APPL1 promotes first-phase GSIS by up-regulating soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein expression. However, whether APPL2 (a close homology of APPL1 with the same domain organization) plays a role in β-cell functions is unknown. Here, we show that APPL2 enhances GSIS by promoting F-actin remodeling via the small GTPase Rac1 in pancreatic β-cells. β-cell specific abrogation of APPL2 impaired GSIS, leading to glucose intolerance in mice. APPL2 deficiency largely abolished glucose-induced first- and second-phase insulin secretion in pancreatic islets. Real-time live-cell imaging and phalloidin staining revealed that APPL2 deficiency abolished glucose-induced F-actin depolymerization in pancreatic islets. Likewise, knockdown of APPL2 expression impaired glucose-stimulated F-actin depolymerization and subsequent insulin secretion in INS-1E cells, which were attributable to the impairment of Ras-related C3 botulinum toxin substrate 1 (Rac1) activation. Treatment with the F-actin depolymerization chemical compounds or overexpression of gelsolin (a F-actin remodeling protein) rescued APPL2 deficiency-induced defective GSIS. In addition, APPL2 interacted with Rac GTPase activating protein 1 (RacGAP1) in a glucose-dependent manner via the bin/amphiphysin/rvs-pleckstrin homology (BAR-PH) domain of APPL2 in INS-1E cells and HEK293 cells. Concomitant knockdown of RacGAP1 expression reverted APPL2 deficiency-induced defective GSIS, F-actin remodeling, and Rac1 activation in INS-1E cells. Our data indicate that APPL2 interacts with RacGAP1 and suppresses its negative action on Rac1 activity and F-actin depolymerization thereby enhancing GSIS in pancreatic β-cells. Significance Dysregulation of cytoskeletal remodeling could result in defective GSIS and cause type 2 diabetes. Previous studies have reported the role of small GTPases including Rac1 and Cdc42 in the regulation of F-actin remodeling, whereas the upstream regulatory pathway remains poorly understood. Here, we identify the adaptor protein APPL2 as an upstream regulator of Rac1 activation. APPL2 promotes F-actin remodeling by antagonizing the inhibitory effect of RacGAP1 on Rac1 activation, which eventually enhances GSIS. Our findings fill the overall puzzle of F-actin remodeling with a crucial piece and provide insights into type 2 diabetes with disrupted actin dynamics.

Aims/Introduction: Hypertension is one of the most significant risk factors for diabetes. The present study aimed to investigate the associations of lipid profiles, including the ratio of low‐density lipoprotein cholesterol (LDL‐C)‐to‐high‐density lipoprotein cholesterol (HDL‐C) and triglyceride (TG) levels, as well as their interactions, with type 2 diabetes in hypertensive patients.Materials and Methods: Hypertensive patients without a history of diabetes and hypolipidemic agents were enrolled continuously at the Hypertension Clinic, Zhongshan Hospital, Fudan University (Shanghai, China) from 2014 to 2016. General clinical data, including body mass index, blood pressure, fasting glucose and 2‐h post‐load glucose levels, and lipid profiles, were collected. The LDL‐C/HDL‐C ratio, TG/HDL‐C ratio and TC/HDL‐C ratio were separately calculated. Statistical analyses were carried out by using SPSS software (version 13.0).Results: In total, 935 hypertensive patients were included, of which 114 patients (12.2%) were diagnosed with diabetes. After multivariate adjustments, the LDL‐C/HDL‐C ratio and TG levels had the most significant and independent associations with diabetes. In the multivariate logistic regression, the LDL‐C/HDL‐C ratio and TG were independently associated with diabetes. After the interaction variable was included, the LDL‐C/HDL‐C ratio remained independently associated with diabetes, but TG was replaced by TG*LDL‐C/HDL‐C.Conclusions: In conclusion, elevated LDL‐C/HDL‐C ratios and TG levels were associated with diabetes in patients with hypertension, with an interactive effect of the LDL‐C/HDL‐C ratio and TG on diabetes in the hypertensive population.

Objective. Insulin resistance (IR) is closely associated with metabolic profiles, including obesity and dyslipidemia. The aim of the present study was to examine how lipid profiles were associated with IR in nonobese middle-aged and elderly Chinese population. Methods. This cross-sectional study included 1608 subjects. IR was defined by homeostasis model assessment of insulin resistance (HOMA-IR) of at least 2.5. Results. In nonobese subjects (body mass index (BMI) < 25 kg/m², n = 996), triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio (odds ratio (OR) = 1.43, 95% confidence interval (CI) 1.13–1.81, ) was an independent risk factor for IR. The best marker for predicting IR in nonobese subjects was TG/HDL-C ratio with the areas under the receiver operating characteristic curves (AUC) of 0.73 ( ). The optimal cut-off point to identifying IR for TG/HDL-C ratio was ≥1.50 in the nonobese population. Other markers like BMI, TG, and total cholesterol (TC)/HDL-C also had acceptable discriminatory power for predicting IR in nonobese population (AUC ≥ 0.7 and ). BMI had the highest AUC of 0.647 ( ) after being adjusted, but it was not effective enough to predict IR in obese subjects (BMI ≥ 25.0, n = 612). Conclusions. The TG/HDL-C ratio may be the best reliable marker for predicting IR in the nonobese middle-aged and elderly Chinese population.

Several studies have shown that variants in the glucokinase regulatory protein gene (GCKR) were associated with type 2 diabetes and dyslipidemia. The purpose of this study was to examine whether tag single nucleotide polymorphisms (SNPs) in the GCKR region were associated with type 2 diabetes and related traits in a Han Chinese population and to identify the potential mechanisms underlying these associations.

Spinal cord injury (SCI) is a crushing disease without a effective and specific therapeutic strategy. Therefore, it is crucial to uncover underlying mechanism in order to identify potential treatments for SCI. Current studies show ferroptosis might pay important role in SCI. In this study, we aimed to identify the key ferroptosis-related genes providing therapeutic targets for SCI. GSE45006, GSE19890 and GSE156999 from Gene Expression Omnibus (GEO) database were analyzed. A total of 61 ferroptosis-related DEGs were identified, followed by bioinformatics enrichment analyses and PPI network construction. Ten key ferroptosis-related genes were identified by Cytoscape (Cytohubba), most of which were enriched in the HIF-1 signaling pathway. Then we constructed a clip SCI rat model and qPCR was performed to assess the expressions of five genes enriched in HIF-1 signaling pathway (Stat3, Tlr4, Hmox1, Hif1a and Cybb). Finally, a ceRNA network, Stat3, Tlr4, Hmox1/miR127, miR383, miR485/rno-Mut_0003, rno-Pwwp2a_0002 was constructed and expression of mentioned molecules were validated by chip data. Five hub genes from HIF-1 signaling pathway were identified and might play a central role in SCI, which indicated that ferroptosis was correlated with HIF-1 signaling pathway. These results can provide a new insight into molecular mechanisms and identify potential therapeutic targets for SCI.