Exploring Impaired SERCA Pump-Caused Alternation Occurrence in Ischemia

Impaired sarcoplasmic reticulum (SR) calcium transport ATPase (SERCA) gives rise to Ca(2+) alternans and changes of the Ca2+release amount. These changes in Ca(2+) release amount can reveal the mechanism underlying how the interaction between Ca(2+) release and Ca(2+) uptake induces Ca(2+) alternans. This study of alternans by calculating the values of Ca(2+) release properties with impaired SERCA has not been explored before. Here, we induced Ca(2+) alternans by using an impaired SERCA pump under ischemic conditions. The results showed that the recruitment and refractoriness of the Ca(2+) release increased as Ca(2+) alternans occurred. This indicates triggering Ca waves. As the propagation of Ca waves is linked to the occurrence of Ca(2+) alternans, the "threshold" for Ca waves reflects the key factor in Ca(2+) alternans development, and it is still controversial nowadays. We proposed the ratio between the diastolic network SR (NSR) Ca content (Cansr) and the cytoplasmic Ca content (Ca i ) (Cansr/Ca i ) as the "threshold" of Ca waves and Ca(2+) alternans. Diastolic Cansr, Ca i , and their ratio were recorded at the onset of Ca(2+) alternans. Compared with certain Cansr and Ca i , the "threshold" of the ratio can better explain the comprehensive effects of the Ca(2+) release and the Ca(2+) uptake on Ca(2+) alternans onset. In addition, these ratios are related with the function of SERCA pumps, which vary with different ischemic conditions. Thus, values of these ratios could be used to differentiate Ca(2+) alternans from different ischemic cases. This agrees with some experimental results. Therefore, the certain value of diastolic Cansr/Ca i can be the better "threshold" for Ca waves and Ca(2+) alternans

Reliable Detection of Myocardial Ischemia Using Machine Learning Based on Temporal-Spatial Characteristics of Electrocardiogram and Vectorcardiogram

Background: Myocardial ischemia is a common early symptom of cardiovascular disease (CVD). Reliable detection of myocardial ischemia using computer-aided analysis of electrocardiograms (ECG) provides an important reference for early diagnosis of CVD. The vectorcardiogram (VCG) could improve the performance of ECG-based myocardial ischemia detection by affording temporal-spatial characteristics related to myocardial ischemia and capturing subtle changes in ST-T segment in continuous cardiac cycles. We aim to investigate if the combination of ECG and VCG could improve the performance of machine learning algorithms in automatic myocardial ischemia detection. Methods: The ST-T segments of 20-second, 12-lead ECGs, and VCGs were extracted from 377 patients with myocardial ischemia and 52 healthy controls. Then, sample entropy (SampEn, of 12 ECG leads and of three VCG leads), spatial heterogeneity index (SHI, of VCG) and temporal heterogeneity index (THI, of VCG) are calculated. Using a grid search, four SampEn and two features are selected as input signal features for ECG-only and VCG-only models based on support vector machine (SVM), respectively. Similarly, three features (S ( I ), THI, and SHI, where S ( I ) is the SampEn of lead I) are further selected for the ECG + VCG model. 5-fold cross validation was used to assess the performance of ECG-only, VCG-only, and ECG + VCG models. To fully evaluate the algorithmic generalization ability, the model with the best performance was selected and tested on a third independent dataset of 148 patients with myocardial ischemia and 52 healthy controls. Results: The ECG + VCG model with three features (S ( I ),THI, and SHI) yields better classifying results than ECG-only and VCG-only models with the average accuracy of 0.903, sensitivity of 0.903, specificity of 0.905, F1 score of 0.942, and AUC of 0.904, which shows better performance with fewer features compared with existing works. On the third independent dataset, the testing showed an AUC of 0.814. Conclusion: The SVM algorithm based on the ECG + VCG model could reliably detect myocardial ischemia, providing a potential tool to assist cardiologists in the early diagnosis of CVD in routine screening during primary care services

Chronic Alcohol Causes Alteration of Lipidome Profiling in Brain

Much efforts have been tried to clarify the molecular mechanism of alcohol-induced brain damage from the perspective of genome and protein; however, the effect of chronic alcohol exposure on global lipid profiling of brain is unclear. In the present study, by using Q-TOF/MS-based lipidomics approach, we investigated the comprehensive lipidome profiling of brain from the rats orally administrated with alcohol daily, continuously for one year. Through systematically analysis of all lipids in prefrontal cortex (PFC) and striatum region, we found that long-term alcohol exposure profoundly modified brain lipidome profiling. Notably, three kinds of lipid classes, glycerophospholipid (GP), glycerolipid (GL) and fatty acyls (FA), were significantly increased in these two brain regions. Interestingly, most of the modified lipids were involved in synthetic pathways of endoplasmic reticulum (ER), which may result in ER stress-related metabolic disruption. Moreover, alcohol-modified lipid species displayed long length of carbon chain with high degree of unsaturation. Taken together, our results firstly present that chronic alcohol exposure markedly modifies brain lipidomic profiling, which may activate ER stress and eventually result in neurotoxicity. These findings provide a new insight into the mechanism of alcohol-related brain damage.Peer reviewe

Methamphetamine exposure drives cell cycle exit and aberrant differentiation in rat hippocampal-derived neurospheres

Introduction: Methamphetamine (METH) abuse by pregnant drug addicts causes toxic effects on fetal neurodevelopment; however, the mechanism underlying such effect of METH is poorly understood.Methods: In the present study, we applied three-dimensional (3D) neurospheres derived from the embryonic rat hippocampal tissue to investigate the effect of METH on neurodevelopment. Through the combination of whole genome transcriptional analyses, the involved cell signalings were identified and investigated.Results: We found that METH treatment for 24 h significantly and concentration-dependently reduced the size of neurospheres. Analyses of genome-wide transcriptomic profiles found that those down-regulated differentially expressed genes (DEGs) upon METH exposure were remarkably enriched in the cell cycle progression. By measuring the cell cycle and the expression of cell cycle-related checkpoint proteins, we found that METH exposure significantly elevated the percentage of G0/G1 phase and decreased the levels of the proteins involved in the G1/S transition, indicating G0/G1 cell cycle arrest. Furthermore, during the early neurodevelopment stage of neurospheres, METH caused aberrant cell differentiation both in the neurons and astrocytes, and attenuated migration ability of neurospheres accompanied by increased oxidative stress and apoptosis.Conclusion: Our findings reveal that METH induces an aberrant cell cycle arrest and neuronal differentiation, impairing the coordination of migration and differentiation of neurospheres

China’s labor-capital ratio human capital accumulation, and labor wage: an empirical analysis using a VAR model

China’s labor-capital ratio (L-C ratio) has fallen sharply over the past two decades, indicating that labor is increasingly being replaced by capital. However, research on the L-C ratio trend is inadequate, especially regarding the driving force and its impact. This study focuses on the relationship between China’s L-C ratio and human capital accumulation by applying the panel vector auto-regression (PVAR) approach. Using a panel data of 30 Chinese provinces for 1997–2014, the analysis yields the following findings: First, the L-C ratio has a negative impact on human capital accumulation, suggesting that the major driving force of the L-C ratio’s sharp decline is the demand-side driving force, rather than the supply-side. Second, the decline of the L-C ratio is majorly driven by the demand-side factors after the Labor Contract Law, but by the supply-side factors before the law, suggesting that the Labor Contract Law has greatly changed the demand-supply balance of China’s labor market. Third, the L-C ratio has a negative effect on labor wages by increasing regional human capital accumulation, suggesting that employees can increase their wages through human capital investment in reaction to the decline in the L-C ratio