Correlation of large conductance Ca2+ activated K+ channelα andβ subunit expression in uterine smooth muscle with the postpartum hemorrhage induced by uterine inertia

Objective:To study the correlation of large conductance Ca2+ activated K+ channel (BKCa)α andβ subunit expression in uterine smooth muscle with the postpartum hemorrhage induced by uterine inertia.Methods: The puerperae who underwent cesarean section and had postpartum hemorrhage induced by uterine inertia in Panzhihua Women and Children Health Hospital between March 2015 and May 2017 were selected as the hemorrhage group of the study, and the puerperae who underwent cesarean section and were without postpartum hemorrhage in Panzhihua Women and Children Health Hospital during the same period were selected as the control group. Proper amount of uterine muscle tissue was collected during the cesarean section to measure the expression of BKCaα andβ subunits and the levels of contraction-related proteins in uterine muscle as well as the contraction characteristic parameters of the uterine muscle.Results: The mRNA expression and protein expression of BKCaα andβ subunits in uterine muscle tissue of hemorrhage group were significantly higher than those of control group;the contraction amplitude, contraction frequency and contraction activity of uterine muscle tissue as well as the OTR, COX2, CX43 and HSP27 levels in uterine muscle tissue of hemorrhage group were significantly lower than those of control group;the BKCaα andβ subunit expression in uterine muscle tissue of hemorrhage group were negatively correlated with the contraction amplitude, contraction frequency and contraction activity as well as the OTR, COX2, CX43 and HSP27 levels.Conclusion: The high expression of BKCa in uterine smooth muscle can reduce the uterine muscle contractility and decrease the levels of contraction-related proteins, and it is closely related to the occurrence of postpartum hemorrhage induced by uterine inertia.

Construction of electron rich Fe active sites by FeCu alloy anchoring on carbon nitride for photocatalytic nitrogen reduction

Given the clean and inexhaustible solar energy from solar light,photocatalytic ammonia synthesis is extremely appealing.However,high electron-hole recombination rates and insufficient active sites severely limited N2 photoreaction reduction.Herein,we designed and fabricated FeCu alloy nanoparticles anchored on carbon nitride nanosheets with excellent photocatalyt ic ammonia synthesis performance.As a coupler between Fe and carbon nitride,Cu promotes the separation of photogenerated charge carriers in carbon nitride under solar light irradiation,and renters the semiconductor a forceful electron donor for the Fe active sites.The accumulated electrons at Fe sites furtherly facilitated the adsorption and activation of the molecular nitrogen.Besides,the uniform dispersed FeCu alloy nanoparticles were on carbon nitride nanosheets enhanced the stability of photocataly tic nitrogen reduction reaction,making the artificial photocataly tic ammonia synthesis more sustainable for application.This work highlights that a direct electron transfer channel can be used to regulate the photochemical nitrogen fixation network.

A predictive model of response to metoprolol in children and adolescents with postural tachycardia syndrome

Background The present work was designed to explore whether electrocardiogram(ECG)index-based models could predict the effectiveness of metoprolol therapy in pediatric patients with postural tachycardia syndrome(POTS).Methods This study consisted of a training set and an external validation set.Children and adolescents with POTS who were given metoprolol treatment were enrolled,and after follow-up,they were grouped into non-responders and responders depending on the efficacy of metoprolol.The difference in pre-treatment baseline ECG indicators was analyzed between the two groups in the training set.Binary logistic regression analysis was further conducted on the association between significantly different baseline variables and therapeutic efficacy.Nomogram models were established to predict therapeutic response to metoprolol.The receiver-operating characteristic curve(ROC),calibration,and internal validation were used to evaluate the prediction model.The predictive ability of the model was validated in the external validation set.Results Of the 95 enrolled patients,65 responded to metoprolol treatment,and 30 failed to respond.In the responders,the maximum value of the P wave after correction(Pcmax),P wave dispersion(Pd),Pd after correction(Pcd),QT interval dis-persion(QTd),QTd after correction(QTcd),maximum T-peak-to-T-end interval(Tpemax),and T-peak-to-T-end interval dispersion(Tped)were prolonged(all P<0.01),and the P wave amplitude was increased(P<0.05)compared with those of the non-responders.In contrast,the minimum value of the P wave duration after correction(Pcmin),the minimum value of the QT interval after correction(QTcmin),and the minimum T-peak-to-T-end interval(Tpemin)in the responders were shorter(P<0.01,<0.01 and<0.01,respectively)than those in the non-responders.The above indicators were screened based on the clinical significance and multicollinearity analysis to construct a binary logistic regression.As a result,pre-treatment Pcmax,QTcmin,and Tped were identified as significantly associated factors that could be combined to provide an accurate prediction of the therapeutic response to metoprolol among the study subjects,yielding good discrimination[area under curve(AUC)=0.970,95%confidence interval(CI)0.942-0.998]with a predictive sensitivity of 93.8%,specificity of 90.0%,good calibration,and corrected C-index of 0.961.In addition,the calibration curve and standard curve had a good fit.The accuracy of internal validation with bootstrap repeated sampling was 0.902.In contrast,the kappa value was 0.769,indicating satisfactory agreement between the predictive model and the results from the actual observations.In the external validation set,the AUC for the prediction model was 0.895,and the sensitivity and specificity were 90.9%and 95.0%,respectively.Conclusions A high-precision predictive model was successfully developed and externally validated.It had an excellent predictive value of the therapeutic effect of metoprolol on POTS among children and adolescents.

Full waveform inversion based on hybrid gradient

The low-wavenumber components in the gradient of full waveform inversion(FWI)play a vital role in the stability of the inversion.However,when FWI is implemented in some high frequencies and current models are not far away from the real velocity model,an excessive number of low-wavenumber components in the gradient will also reduce the convergence rate and inversion accuracy.To solve this problem,this paper firstly derives a formula of scattering angle weighted gradient in FWI,then proposes a hybrid gradient.The hybrid gradient combines the conventional gradient of FWI with the scattering angle weighted gradient in each inversion frequency band based on an empirical formula derived herein.Using weighted hybrid mode,we can retain some low-wavenumber components in the initial lowfrequency inversion to ensure the stability of the inversion,and use more high-wavenumber components in the high-frequency inversion to improve the convergence rate.The results of synthetic data experiment demonstrate that compared to the conventional FWI,the FWI based on the proposed hybrid gradient can effectively reduce the low-wavenumber components in the gradient under the premise of ensuring inversion stability.It also greatly enhances the convergence rate and inversion accuracy,especially in the deep part of the model.And the field marine seismic data experiment also illustrates that the FWI based on hybrid gradient(HGFWI)has good stability and adaptability.

Prediction of intravenous immunoglobulin resistance in Kawasaki disease in children

Background We aimed to explore predictive measures for intravenous immunoglobulin(IVIG)resistance in children with Kawasaki disease(KD).Methods Patients diagnosed with KD were enrolled in this study.Univariate analysis and multiple logistic regression were utilized to analyze the clinical features and laboratory results prior to IVIG-treatment of the two groups.Independent predictors of IVIG resistance were analyzed,and a predictive model for KD children with IVIG resistance was constructed.Results A total of 277 children with KD,180 boys and 97 girls,aged 2-128(median 23)months,were enrolled in the study.Compared with the IVIG-responsive group,the IVIG-resistant group had higher levels of the peripheral neutrophil count,mean platelet volume,mean platelet volume-to-lymphocyte ratio and C-reactive protein,and total serum bilirubin,but lower levels of peripheral lymphocyte count,serum albumin and serum prealbumin.Age(in months),peripheral neutrophil count,lymphocyte count and mean platelet volume and serum albumin were independent indicators for IVIG resistance by multivariate logistic regression analysis.A logistic regression model and a scoring system were set up,where cut-off values of—0.46 and 6.5 points yielded sensitivities of 83.9%and 77.4%,and specificities of 74.8%and 61.0%,respectively.The areas under the curve(AUC)were 0.808 in the logistic regression model,and 0.750 in the scoring system.Conclusion Our model for predicting IVIG-resistant children with KD,involving age(months),peripheral neutrophil count,lymphocyte count and mean platelet volume and serum albumin prior to IVIG-treatment,is helpful for clinical prediction of children with IVIG-resistant KD.