Polycystic ovary syndrome (PCOS) is a common endocrine disease in females that is characterized by hyperandrogenemia, chronic anovulation, and polycystic ovaries. However, the exact etiology and pathogenesis of PCOS are still unknown. The aim of this study was to clarify the bacterial, stress status, and metabolic differences in the gut microbiomes of healthy individuals and patients with high body mass index (BMI) PCOS (PCOS-HB) and normal BMI PCOS (PCOS-LB), respectively. Here, we compared the gut microbiota characteristics of PCOS-HB, PCOS-LB, and healthy controls by 16S rRNA gene sequencing, FK506-binding protein 5 (FKBP5) DNA methylation and plasma metabolite determination. Clinical parameter comparisons indicated that PCOS patients had higher concentrations of total testosterone, androstenedione, dehydroepiandrosterone sulfate, luteinizing hormone, and HOMA-IR while lower FKBP5 DNA methylation. Significant differences in bacterial diversity and community were observed between the PCOS and healthy groups but not between the PCOS-HB and PCOS-LB groups. Bacterial species number was negatively correlated with insulin concentrations (both under fasting status and 120 min after glucose load) and HOMA-IR but positively related to FKBP5 DNA methylation. Compared to the healthy group, both PCOS groups had significant changes in bacterial genera, including Prevotella_9, Dorea, Maihella, and Slackia, and plasma metabolites, including estrone sulfate, lysophosphatidyl choline 18:2, and phosphatidylcholine (22:6e/19:1). The correlation network revealed the complicated interaction of the clinical index, bacterial genus, stress indices, and metabolites. Our work links the stress responses and gut microbiota characteristics of PCOS disease, which might afford perspectives to understand the progression of PCOS.

Lower limb peripheral artery disease is a prevalent chronic non-communicable disease without obvious symptoms. However, the effect of ischemic lower limb peripheral arteries on hemodynamics remains unclear. In this study, we investigated the variation of the hemodynamics caused by patient-specific structural artery characteristics. Computational fluid dynamic simulations were performed on seven lower limb (including superficial femoral, deep femoral and popliteal) artery models that were reconstructed from magnetic resonance imaging. We found that increased wall shear stress (WSS) was mainly caused by the increasing severity of stenosis, bending, and branching. Our results showed that the increase in the WSS value at a stenosis at the bifurcation was 2.7 Pa. In contrast, the isolated stenosis and branch caused a WSS increase of 0.7 Pa and 0.5 Pa, respectively. The WSS in the narrow popliteal artery was more sensitive to a reduction in radius. Our results also demonstrate that the distribution of the velocity and pressure gradient are highly structurally related. At last, Ultrasound Doppler velocimeter measured result was presented as a validation. In conclusion, the distribution of hemodynamics may serve as a supplement for clinical decision-making to prevent the occurrence of a morbid or mortal ischemic event.

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To characterize the gut bacteriome, mycobiome and serum metabolome profiles in polycystic ovary syndrome (PCOS) patients with normal/overweight individuals and evaluate a potential microbiota-related diagnostic method development for PCOS, 16S rRNA and ITS2 gene sequencing using 88 fecal samples and 87 metabolome analysis from serum samples are conducted and PCOS classifiers based on multiomics markers are constructed. There are significant bacterial, fungal community and metabolite differences among PCOS patients and healthy volunteers with normal/overweight individuals. Healthy individuals with overweight/obesity display less abnormal metabolism than PCOS patients and uniquely higher abundance of the fungal genus Mortierella. Nine bacterial genera, 4 predicted pathways, 11 fungal genera and top 30 metabolites are screened out which distinguish PCOS from healthy controls, with AUCs of 0.84, 0.64, 0.85 and 1, respectively. The metabolite-derived model is more accurate than the microbe-based model in discriminating normal BMI PCOS (PCOS-LB) from normal BMI healthy (Healthy-LB), PCOS-HB from Healthy-HB. Featured bacteria, fungi, predicted pathways and serum metabolites display higher associations with free androgen index (FAI) in the cooccurrence network. In conclusion, our data reveal that hyperandrogenemia plays a central role in the dysbiosis of intestinal microecology and the change in metabolic status in patients with PCOS and that its effect exceeds the role of BMI. Healthy women with high BMI showed unique microbiota and metabolic features.The priority of predictive models in discriminating PCOS from healthy status in this study were serum metabolites, fungal taxa and bacterial taxa.

Background The aims of this study were to compare the efficacy of different androgens measured by liquid chromatography-mass spectrometry (LC-MS/MS) in representing hyperandrogenemia and to evaluate adrenal-origin androgens with a dexamethasone suppression test in patients with polycystic ovary syndrome (PCOS). Methods One hundred and two patients with PCOS and 41 healthy volunteers were recruited and total serum testosterone (TT), androstenedione (AD), dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulfate (DHEA-S) were measured by LC-MS/MS. ROC analysis was performed to compare the efficacy of different androgens in representing hyperandrogenemia. Dexamethasone suppression test was performed in 51 patients with PCOS and above indicators were measured after dexamethasone administration. The prediction efficacy of DHEA and DHEA-S at baseline in the dexamethasone suppression test was evaluated with ROC analysis. Results The AUCs of TT, AD, free androgen index (FAI) and DHEA-S in ROC analysis for representing hyperandrogenemia were 0.816, 0.842, 0.937 and 0.678, respectively. The optimal cutoff value of TT was 0.337 ng/ml, with a sensitivity of 72.0% and specificity of 82.93%. The optimal cutoff value for AD was 1.309 ng/ml, with a sensitivity of 81.0% and specificity of 73.17%. The optimal cutoff value of the FAI was 2.50, with a sensitivity of 87.0% and specificity of 92.68%. Alternatively, AD or FAI more than the optimal cutoff values as evidence of hyperandrogenemia had the highest sensitivity of 91.18%. The levels of cortisol, DHEA and DHEA-S were all suppressed to narrow ranges after dexamethasone administration. Nine and 8 of 51 patients with PCOS had significant decreases in TT and AD, respectively. DHEA can be used as a indicator for predicting significant decrease of TT in dexamethasone suppression test with cutoff value of 13.28 ng/ml. A total of 27.5% (14/51) of patients had DHEA-S excess, but only 1 of 9 patients who had a significant decrease in TT had elevated level of DHEA-S at baseline. Conclusions AD measured by LC-MS/MS can represent hyperandrogenemia in PCOS patients and, combined with TT or FAI, can improve the screening efficiency of hyperandrogenemia. Seventeen percent of PCOS patients had adrenal-origin androgen dominance, with TT significantly decreasing after 2 days of dexamethasone administration. Adrenal-origin androgen dominance was not parallel with DHEA-S excess in patients with PCOS.