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Resting‐state functional connectivity in the human brain is heritable, and previous studies have investigated the genetic basis underlying functional connectivity. However, at present, the molecular mechanisms associated with functional network centrality are still largely unknown. In this study, functional networks were constructed, and the graph‐theory method was employed to calculate network centrality in 100 healthy young adults from the Human Connectome Project. Specifically, functional connectivity strength (FCS), also known as the “degree centrality” of weighted networks, is calculated to measure functional network centrality. A multivariate technique of partial least squares regression (PLSR) was then conducted to identify genes whose spatial expression profiles best predicted the FCS distribution. We found that FCS spatial distribution was significantly positively correlated with the expression of genes defined by the first PLSR component. The FCS‐related genes we identified were significantly enriched for ion channels, axon guidance, and synaptic transmission. Moreover, FCS‐related genes were preferentially expressed in cortical neurons and young adulthood and were enriched in numerous neurodegenerative and neuropsychiatric disorders. Furthermore, a series of validation and robustness analyses demonstrated the reliability of the results. Overall, our results suggest that the spatial distribution of FCS is modulated by the expression of a set of genes associated with ion channels, axon guidance, and synaptic transmission.

Analyzing global steroid metabolism in humans can shed light on the etiologies of steroid-related diseases. However, existing methods require large amounts of serum and lack the evaluation of accuracy. Here, we developed an LC/MS/MS method for the simultaneous quantification of 12 steroid hormones: testosterone, pregnenolone, progesterone, androstenedione, corticosterone, 11-deoxycortisol, cortisol, 17-hydroxypregnenolone, 17-hydroxyprogesterone, dehydroepiandrosterone, estriol, and estradiol. Steroids and spiked internal standards in 100 μl serum were extracted by protein precipitation and liquid-liquid extraction. The organic phase was dried by evaporation, and isonicotinoyl chloride was added for steroid derivatization, followed by evaporation under nitrogen and redissolution in 50% methanol. Chromatographic separation was performed on a reverse-phase PFP column, and analytes were detected on a triple quadrupole mass spectrometer with ESI. The lower limits of quantification ranged from 0.005 ng/ml for estradiol to 1 ng/ml for cortisol. Apparent recoveries of steroids at high, medium, and low concentrations in quality control samples were between 86.4% and 115.0%. There were limited biases (−10.7% to 10.5%) between the measured values and the authentic values, indicating that the method has excellent reliability. An analysis of the steroid metabolome in pregnant women highlighted the applicability of the method in clinical serum samples. We conclude that the LC/MS/MS method reported here enables steroid metabolome analysis with high accuracy and reduced serum consumption, indicating that it may be a useful tool in both clinical and scientific laboratory research.

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HE4 can serve as a potential biomarker for prediction of CKD and has important reference value for CKD staging.

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BackgroundDespite several treatment options that are available for meningiomas, surgery is the only method currently practiced. Peritumoral brain edema (PTBE) in meningiomas causes difficulty marginalizing the dissection in an intraoperative setting.PurposeTo evaluate whether the epidemiological variables, imaging characteristics, and pathologic parameters are correlated with the presence of PTBE in meningiomas.Study TypeRetrospective study from 2015 to 2018.SubjectsIn all, 550 patients with histopathologically confirmed meningioma were included. After exclusion of patients with extradural, spinal, and intraventricular meningiomas and those with image artifacts, a total of 441 patients were included in the final analysis.Field Strength/SequenceImages were performed with 3T MR scanners and axial/sagittal T1WI, axial/coronal T2WI and axial/sagittal/coronal contrast‐enhanced T1WI after administration of 0.1 mmol/kg of body weight of Gd‐DTPA.AssessmentFourteen variables were patients' age, sex, skull changes, calcification, density, location, margin, volume, cerebrospinal fluid (CSF) cleft, signal intensity (SI) on T2WI, degree and pattern of contrast enhancement, WHO histological classification, and Ki‐67 labeling index.Statistical TestsThe relationship between each factor and the formation of PTBE was examined by multivariate logistic regression analysis.ResultsAfter multivariate logistic regression, the absence of CSF cleft (odds ratio [OR]: 63.43, 95% confidence interval [CI]: 27.24–121.42, P = 1.2 × 10−8), non‐skull base location (OR: 15.32, 95% CI: 5.81–28.23, P = 0.0008), high SI on T2WI (OR: 5.05, 95% CI: 2.27–14.88, P = 0.01), and G I uncommon subtypes (OR: 4.75, 95% CI: 1.42–15.94, P = 0.01) were found to be significant independent factors associated with the occurrence of PTBE in meningiomas. In patients with PTBE‐positive meningiomas, there was no significant correlation between the volume of PTBE and the volume of the tumor (r = 0.17, P = 0.60).Data ConclusionThese factors may be suggestive of anticipating the formation of PTBE.Level of Evidence: 3Technical Efficacy Stage: 3J. Magn. Reson. Imaging 2020;52:174–182.