Objective To evaluate the relationship between the changes in gray matter volume ( GMV) in different brain regions in the early postoperative period and the development of chronic pain after radical mastectomy. Methods Forty-four American Society of Anesthesiologists physical status Ⅰ or Ⅱpatients, aged 25-64 yr, scheduled for elective radical mastectomy, were divided into 3 groups according to the numeric rating scale ( NRS) score within 3 months after surgery: severe chronic pain group ( NRS score≥3, group SEP), slight chronic pain group (NRS score=1 or 2, group SLP) and no chronic pain group ( NRS score=0, group NP ) . All the patients underwent whole brain MRI scan within 7 days after surgery. MRI data processing and analysis were carried out using SPM8-based VBM software package and REST 1. 8 software. Results There were 17 cases in group SEP, 10 cases in group SLP and 17 cases in group NP. Compared with group NP, GMV in the right postcentral gyrus was significantly decreased, and GMV in the right superior frontal gyrus was increased in group SEP ( P＜0. 01) . Conclusion The changes in GMV in the right postcentral and superior frontal gyrus in the early postoperative period may be related to the development of chronic pain after radical mastectomy.

Glutathione (GSH) is a major antioxidant in cells, and plays vital roles in the cellular defense against oxidants and in the regulation of redox signals. In a previous report, we demonstrated that stem cell function is critically affected by heterogeneity and dynamic changes in cellular GSH concentration. Here, we present a detailed protocol for the monitoring of GSH concentration in living stem cells using FreSHtracer, a real-time GSH probe. We describe the steps involved in monitoring GSH concentration in single living stem cells using confocal microscopy and flow cytometry. These methods are simple, rapid, and quantitative, and able to demonstrate intracellular GSH concentration changes in real time. We also describe the application of FreSHtracer to the sorting of stem cells according to their GSH content using flow cytometry. Typically, microscopic or flow cytometric analyses of FreSHtracer and MitoFreSHtracer signals in living stem cells take ~2~3 h, and the fractionation of stem cells into subpopulations on the basis of cellular GSH levels takes 3~4.5 h. This method could be applied to almost every kind of mammalian cell with minor modifications to the protocol described here.
Flow Cytometry ; Fluorescent Dyes ; Glutathione ; Methods ; Microscopy, Confocal ; Oxidants ; Oxidation-Reduction ; Population Characteristics ; Stem Cells

Objective:To explore the risk factors for mortality in pediatric acute respiratory distress syndrome (PARDS) requiring extracorporeal membrane oxygenation (ECMO) support.Methods:Clinical data of 109 patients with severe PARDS supported by ECMO, who were hospitalized in 6 ECMO centers in China from September 2012 to February 2020, were retrospectively analyzed. They were divided into survival group and death group according to the prognosis. Chi-square test and rank sum test were used to compare the variables between the two groups, including the demographic data, laboratory examination results, clinical data before and after ECMO, and other supportive treatment. Univariate and multivariate Logistic regression models were used to analyze the prognostic risk factors.Results:In these 109 cases, 54 died and 55 survived. Compared with the survival group, the death group had higher incidences of acute kidney injury (AKI) (48.1% (26/54) vs. 21.8% (12/55) , χ2=8.318, P=0.004) and coagulation dysfunction (22.2% (12/54) vs. 7.3% (4/55) , χ2=4.862, P=0.027), and higher rate of renal replacement therapy (48.1% (26/54) vs. 21.8% (12/55) , χ2=9.694, P=0.008) during ECMO support. Logistic regression analysis showed that continuous renal replacement therapy (CRRT) and AKI were independent risk factors for death in patients with severe PARDS requiring ECMO support ( HR=3.88,95% CI 1.04-14.52, HR=4.84,95% CI 1.21-19.46, both P<0.05). Conclusion:AKI and CRRT are independent risk factors for predicting mortality in patients with severe PARDS requiring ECMO support.