Association of Polymorphisms of the Matrix Metalloproteinase 9 Gene with Ischaemic Stroke in a Southern Chinese Population

Background/Aims: Matrix metalloproteinase 9 (MMP9), a potent endopeptidase degrading extracellular matrix, plays a pivotal role in the pathogenesis of ischaemic stroke (IS). The present study was undertaken to determine the association of MMP9 gene polymorphisms and the risk of IS in a southern Chinese population. Methods: A cohort of 1274 patients and 1258 age-matched healthy controls were genotyped to detect the four MMP9 polymorphisms (rs17156, rs3787268, rs3918241 and rs3918242) using SNaPshot. Results: Our study demonstrated a significant difference in the genotype and allele frequencies of the MMP9 rs3918242 polymorphism between the IS patients and the controls (P = 0.012 for the genotype and P = 0.0092 for the allele). Stratification by smoking status showed statistically significant differences in the frequency and allele of the rs3918242 polymorphism between IS patients and the controls (P = 0.0052 for the genotype and P = 0.0019 for the allele). Further stratification by IS subtypes revealed that the presence of the T allele of the MMP9 rs3918242 polymorphism confers a higher risk of the large artery atherosclerosis subtype of IS (P = 0.017). Moreover, IS patients with the rs3918242 T allele of MMP9 presented with increased serum MMP9 production, and this increase was more significant in smokers with IS (P = 0.022). Patients carrying the variant T allele of the MMP9 rs3918242 polymorphism exhibited significantly higher infarct volumes than those with the major CC genotype (P = 0.036). Conclusion: Our study provides preliminary evidence that the MMP9 rs3918242 polymorphism is linked to a higher risk of IS, confirming the role of MMP9 in the pathophysiology of IS, with potentially important therapeutic implications

Research on System Economic Operation and Management Based on Deep Learning

It is of great significance to accurately predict the operation of the system economy, analyze the gains and losses of macrocontrol policies, evaluate the operation quality of the economic system, and correctly formulate the future development plan and strategy. This paper introduces the deep belief network, which has attracted much attention in the field of deep learning in recent years, into the research of system economic operation and management. This method solves the problems of slow training and learning speed, easy to fall into local minima and insufficient generalization of BP artificial neural network in the research of system economic operation and management. Taking the consumer price index and total import and export volume of F Province as the research object, the experiment proves that DBN has better application in system economic operation and management than BP neural network and vector autoregressive analysis. This paper analyzes and compares the modeling performance of DBN, BP neural network, and VaR method from many aspects, such as prediction accuracy, training convergence speed, and pretraining with or without samples. Relevant empirical results show that DBN has better economic prediction performance than BP neural network and ver. On the other hand, DBN can effectively use nonstandard samples to pretrain network weight parameters. Therefore, DBN is a better operation and management modeling means of economic system, with excellent practicability and application, and is expected to be popularized and applied in the field of economic forecasting

On a combined measurement technique of PIV and shadowgraph in environmental fluid dynamics

In this paper, a combined measurement technique of Particle Image Velocimetry (PIV) and shadowgraph is proposed to investigate the environmental fluid dynamics. This measurement system is based on a PIV system, with a backlight added to produce the shadow of dyed water. The images recorded by a CCD camera are then processed for the PIV and shadowgraph data, separately. The experimental results show that this technique is well suitable for the investigation of time-dependent flow field with temperature variation. Fairly good agreements with the experimental and CFD results are achieved. © 2009 SPIE

Explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping

Radionuclide identification is an important part of the nuclear material identification system. The development of artificial intelligence and machine learning has made nuclide identification rapid and automatic. However, many methods directly use existing deep learning models to analyze the gamma-ray spectrum, which lacks interpretability for researchers. This study proposes an explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping. This method shows the area of interest of the neural network on the gamma-ray spectrum by generating a class activation map. We analyzed the class activation map of the gamma-ray spectrum of different types, different gross counts, and different signal-to-noise ratios. The results show that the convolutional neural network attempted to learn the relationship between the input gamma-ray spectrum and the nuclide type, and could identify the nuclide based on the photoelectric peak and Compton edge. Furthermore, the results explain why the neural network could identify gamma-ray spectra with low counts and low signal-to-noise ratios. Thus, the findings improve researchers’ confidence in the ability of neural networks to identify nuclides and promote the application of artificial intelligence methods in the field of nuclide identification

Exosomal miR-132-3p from mesenchymal stromal cells improves synaptic dysfunction and cognitive decline in vascular dementia

Abstract Background/aims Vascular dementia (VD) results in cognition and memory deficit. Exosomes and their carried microRNAs (miRs) contribute to the neuroprotective effects of mesenchymal stromal cells, and miR-132-3p plays a key role in neuron plasticity. Here, we investigated the role and underlying mechanism of MSC EX and their miR-132-3p cargo in rescuing cognition and memory deficit in VD mice. Methods Bilateral carotid artery occlusion was used to generate a VD mouse model. MiR-132-3p and MSC EX levels in the hippocampus and cortex were measured. At 24-h post-VD induction, mice were administered with MSC EX infected with control lentivirus (EXCon), pre-miR-132-3p-expressing lentivirus (EXmiR-132-3p), or miR-132-3p antago lentivirus (EXantagomiR-132-3p) intravenously. Behavioral and cognitive tests were performed, and the mice were killed in 21 days after VD. The effects of MSC EX on neuron number, synaptic plasticity, dendritic spine density, and Aβ and p-Tau levels in the hippocampus and cortex were determined. The effects of MSC EX on oxygen–glucose deprivation (OGD)-injured neurons with respect to apoptosis, and neurite elongation and branching were determined. Finally, the expression levels of Ras, phosphorylation of Akt, GSK-3β, and Tau were also measured. Results Compared with normal mice, VD mice exhibited significantly decreased miR-132-3p and MSC EX levels in the cortex and hippocampus. Compared with EXCon treatment, the infusion of EXmiR-132-3p was more effective at improving cognitive function and increasing miR-132-3p level, neuron number, synaptic plasticity, and dendritic spine density, while decreasing Aβ and p-Tau levels in the cortex and hippocampus of VD mice. Conversely, EXantagomiR-132-3p treatment significantly decreased miR-132-3p expression in cortex and hippocampus, as well as attenuated EXmiR-132-3p treatment-induced functional improvement. In vitro, EXmiR-132-3p treatment inhibited RASA1 protein expression, but increased Ras and the phosphorylation of Akt and GSK-3β, and decreased p-Tau levels in primary neurons by delivering miR-132-3p, which resulted in reduced apoptosis, and increased neurite elongation and branching in OGD-injured neurons. Conclusions Our studies suggest that miR-132-3p cluster-enriched MSC EX promotes the recovery of cognitive function by improving neuronal and synaptic dysfunction through activation of the Ras/Akt/GSK-3β pathway induced by downregulation of RASA1

Implication of MicroRNA503 in Brain Endothelial Cell Function and Ischemic Stroke

The role of miR-503 in brain endothelium and ischemic stroke (IS) remains unclear. We aimed to study the relationship between plasma miR-503 and the onset time, severity, subtypes, and von Willebrand Factor (vWF) level in IS patients and to investigate the roles and underlying mechanisms of miR-503 in middle cerebral artery occlusion (MCAO) mice and cultured cerebral vascular endothelial cells (ECs). In MCAO mice, the effects of plasma from acute severe IS patients (ASS) with or without miR-503 antagomir on brain and ECs damage were determined. In cultured human ECs, the effects of miR-503 overexpression or knockdown on the monolayer permeability, apoptosis, ROS, and NO generation were investigated. For mechanism study, the PI3K/Akt/eNOS pathway, cleaved caspase-3, and bcl-2 were analyzed. Results showed that plasma miR-503 was significantly increased in IS patients, especially in acute period and severe cases and subtypes of LAA and TACI, and was positively correlated with vWF. Logistic analysis indicated that miR-503 was an independent risk factor for IS, with the area under curve of 0.796 in ROC analysis. In MCAO mice, ASS pretreatment aggravated neurological injury, BBB damage, brain edema, CBF reduction, and decreased NO production while increased apoptosis and ROS generation in brain ECs, which were partly abolished by miR-503 antagomir. In cultured ECs, miR-503 overexpression and knockdown confirmed its effects on regulating monolayer permeability, cell apoptosis, NO, and ROS generation via PI3K/Akt/eNOS pathway or bcl-2 and cleaved caspase-3 proteins. These together indicate that miR-503 is a promising biomarker and novel therapeutic target for IS

Genetic Variants of lncRNA GAS5 Contribute to Susceptibility of Ischemic Stroke among Southern Chinese Population

Emerging evidence suggests that the long noncoding RNA (lncRNA) growth arrest special 5 (GAS5) plays crucial roles in the pathogenesis of ischemic stroke (IS). The current research is aimed at assessing the correlation between two functional GAS5 variants (rs145204276 and rs55829688) and susceptibility to IS in a Han Chinese population. This study genotyped the two GAS5 variants in 1086 IS patients as well as 1045 age-matched healthy controls by using an improved multitemperature ligase detection reaction (iMLDR-TM) genotyping technology. We observed a considerable change in the frequencies of the rs145204276 allele and genotype among the IS patients and healthy control group. The del-T haplotype was substantially more prevalent in the IS cases compared to the control individuals. When study participants were stratified according to environmental factors, we found that the rs145204276 del allele was correlated with a higher risk of IS in male, smokers, hypertensive, and those ≥65 years old. Additional stratification conforming to IS subtypes exhibited that individuals carrying the rs145204276 del allele conferred a higher risk of expanding a larger artery atherosclerosis stroke subset. Moreover, there was a significant association between the rs145204276 del allele and elevated expression of GAS5 in IS patients. In contrast, the frequency of the allele related to rs55829688 was not statistically correlated with IS in all analysis. Our study supports a model wherein the rs145204276 variant in the GAS5 lncRNA is associated with IS risk, thus representing a potentially viable biomarker for IS prevention and treatment