Relationship between Carotid Artery Sclerosis and Blood Pressure Variability in Essential Hypertension Patients

Objectives: This study aimed to investigate the relationship between the presence of carotid arteriosclerosis (CAS) and blood pressure variability (BPV) in patients with essential hypertension. Methods: One hundred and forty four essential hypertension patients underwent ambulatory BP monitoring for 24 hours after hospitalization. Common BPV metrics were calculated. General clinical parameters, including age, gender, height, weight, history of coronary heart disease, stroke, diabetes, hypertension, smoking and drink, were recorded. Biochemical indices were obtained from a blood test. Carotid intima-media thickness (IMT) and carotid plaques were assessed to separate patients into a non-CAS group (IMT≤0.9 mm; n=82) and a CAS group (IMT>0.9 mm; n=62). BPV metrics and clinical parameters were analyzed and compared between the two groups. Multivariate logistic regression analysis was performed to determine the associated risk factors of CAS. Results: Multivariate logistic regression analysis revealed that two BPV metrics, the standard deviation of daytime systolic blood pressure (SSD) (OR: 1.587, 95%CI: 1.242–2.028), the difference between average daytime SBP and nighttime SBP (OR: 0.914, 95%CI: 0.855-0.977), as well as three clinical parameters (age, OR: 1.098, 95%CI: 1.034-1.167; smoking, OR: 4.072, 95%CI: 1.466–11.310, and fasting blood glucose, OR: 2.029, 95%CI: 1.407–2.928), were significant factors of CAS in essential hypertension patients. Conclusion: SSD, in combination with the ageing, smoking and FBG, has been identified as risk factors for CAS in patients with essential hypertension

When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We?

With the development of blockchain technology, smart contracts have become an important component of blockchain applications. Despite their crucial role, the development of smart contracts may introduce vulnerabilities and potentially lead to severe consequences, such as financial losses. Meanwhile, large language models, represented by ChatGPT, have gained great attentions, showcasing great capabilities in code analysis tasks. In this paper, we presented an empirical study to investigate the performance of ChatGPT in identifying smart contract vulnerabilities. Initially, we evaluated ChatGPT's effectiveness using a publicly available smart contract dataset. Our findings discover that while ChatGPT achieves a high recall rate, its precision in pinpointing smart contract vulnerabilities is limited. Furthermore, ChatGPT's performance varies when detecting different vulnerability types. We delved into the root causes for the false positives generated by ChatGPT, and categorized them into four groups. Second, by comparing ChatGPT with other state-of-the-art smart contract vulnerability detection tools, we found that ChatGPT's F-score is lower than others for 3 out of the 7 vulnerabilities. In the case of the remaining 4 vulnerabilities, ChatGPT exhibits a slight advantage over these tools. Finally, we analyzed the limitation of ChatGPT in smart contract vulnerability detection, revealing that the robustness of ChatGPT in this field needs to be improved from two aspects: its uncertainty in answering questions; and the limited length of the detected code. In general, our research provides insights into the strengths and weaknesses of employing large language models, specifically ChatGPT, for the detection of smart contract vulnerabilities

Medical image registration based on PCA and M_PSNR

Medical image registration is not only the premise of medical image fusion, but also the focus of medical image processing. It plays an important role in clinical diagnosis and treatment planning. Aiming at the problem of mutual information value in image registration, a PCA neural network and M_PSNR based method for rigid registration of reference and floating images was proposed. In this method, the centroid of the image needs to be figured out through the image matrix, and the rotation Angle and translation of the image registration can be calculated by PCA method to obtain the optimal rotation transformation and the initial registration value. Finally, M_PSNR method improved by PSNR was used for similarity test to increase the speed and efficiency of registration and simplify the calculation process

Treadmill Exercise Decreases Aβ Deposition and Counteracts Cognitive Decline in APP/PS1 Mice, Possibly via Hippocampal Microglia Modifications

Recent studies have suggested that exercise may be beneficial for delaying or attenuating Alzheimer’s disease (AD). However, the underlying mechanisms were not clear. Microglia-mediated neuroinflammation is suggested to play an important role in the pathology of AD. The present study investigated the beneficial effects of treadmill exercise on amyloid-β (Aβ) deposition and cognitive function in amyloid precursor protein (APP)/PS1 mice in the early stage of AD progression and microglia-mediated neuroinflammation was mainly analyzed. The results demonstrated that 12 weeks of treadmill exercise preserved hippocampal cognitive function in APP/PS1 mice and substantially suppressed Aβ accumulation in the hippocampus. Treadmill exercise significantly inhibited neuroinflammation, which was characterized by a remarkably reduced expression of pro-inflammatory factors and increased expression of anti-inflammatory mediators in the hippocampus, resulting from a shift in activated microglia from the M1 to M2 phenotype. Treadmill exercise also attenuated oxidative stress presented by a marked reduction in methane dicarboxylic aldehyde (MDA) level and dramatically elevated SOD and Mn-SOD activities in the hippocampus. These findings suggest that treadmill exercise can effectively prevent the decrease in hippocampal-dependent cognitive function and Aβ deposits in early AD progression possibly via modulating microglia-mediated neuroinflammation and oxidative stress

Circadian Rhythm-Dependent Alterations of Gene Expression in Drosophila Brain Lacking Fragile X Mental Retardation Protein

Fragile X syndrome is caused by the loss of the FMR1 gene product, fragile X mental retardation protein (FMRP). The loss of FMRP leads to altered circadian rhythm behaviors in both mouse and Drosophila; however, the molecular mechanism behind this phenomenon remains elusive. Here we performed a series of gene expression analyses, including of both mRNAs and microRNAs (miRNAs), and identified a number of mRNAs and miRNAs (miRNA-1 and miRNA-281) with circadian rhythm-dependent altered expression in dfmr1 mutant flies. Identification of these RNAs lays the foundation for future investigations of the molecular pathway(s) underlying the altered circadian rhythms associated with loss of dFmr1

A Finite Volume Method for Modeling Shallow Flows with Wet-Dry Fronts on Adaptive Cartesian Grids

A second-order accurate, Godunov-type upwind finite volume method on dynamic refinement grids is developed in this paper for solving shallow-water equations. The advantage of this grid system is that no data structure is needed to store the neighbor information, since neighbors are directly specified by simple algebraic relationships. The key ingredient of the scheme is the use of the prebalanced shallow-water equations together with a simple but effective method to track the wet/dry fronts. In addition, a second-order spatial accuracy in space and time is achieved using a two-step unsplit MUSCL-Hancock method and a weighted surface-depth gradient method (WSDM) which considers the local Froude number is proposed for water depths reconstruction. The friction terms are solved by a semi-implicit scheme that can effectively prevent computational instability from small depths and does not invert the direction of velocity components. Several benchmark tests and a dam-break flooding simulation over real topography cases are used for model testing and validation. Results show that the proposed model is accurate and robust and has advantages when it is applied to simulate flow with local complex topographic features or flow conditions and thus has bright prospects of field-scale application

Deadline Aware Retransmission Threshold Setting Protocol in Cyber-Physical Systems

Many time-sensitive applications impose high requirement on real-time response. There exist many algorithms and routing protocols for efficient data packet delivery. However, previous works set the same retransmission threshold for all the relay nodes along a delivery path. The method decreases the probability of a packet being transmitted through the delivery path within given deadline. In this paper, we focus on finding the optimal retransmission thresholds for the relay nodes, such that the summation of the probability of a packet being transmitted to the next relay node or destination node within the specified deadline is maximized. A distributed greedy algorithm that can be run on sensor node is proposed, which enables the sensor node to adaptively set the optimal retransmission threshold. To avoid dropping the packet forwarded to the destination within given deadline with high probability, we develop a packet dropped protocol based on probabilistic delay bound. Experimental results show that the proposed protocols have better performance

Systemic transplantation of human umbilical cord derived mesenchymal stem cells-educated T regulatory cells improved the impaired cognition in AβPPswe/PS1dE9 transgenic mice.

Alzheimer's disease (AD) is one of most prevalent dementias, which is characterized by the deposition of extracellular amyloid-beta protein (Aβ) and the formation of neurofibrillary tangles within neurons. Although stereotaxic transplantation of mesenchymal stem cells (MSCs) into the hippocampus of AD animal model as immunomodulatory cells has been suggested as a potential therapeutic approach to prevent the progress of AD, it is invasive and difficult for clinical perform. Systemic and central nervous system inflammation play an important role in pathogenesis of AD. T regulatory cells (Tregs) play a crucial role in maintaining systemic immune homeostasis, indicating that transplantation of Tregs could prevent the progress of the inflammation. In this study, we aimed to evaluate whether systemic transplantation of purified autologous Tregs from spleens of AβPPswe/PS1dE9 double-transgenic mice after MSCs from human umbilical cords (UC-MSCs) education in vitro for 3 days could improve the neuropathology and cognition deficits in AβPPswe/PS1dE9 double-transgenic mice. We observed that systemic transplantation of autologous Tregs significantly ameliorate the impaired cognition and reduced the Aβ plaque deposition and the levels of soluble Aβ, accompanied with significantly decreased levels of activated microglia and systemic inflammatory factors. In conclusion, systemic transplantation of autologous Tregs may be an effective and safe intervention to prevent the progress of AD

Development and Performance Evaluation of Cold-Patching Materials Using Waterborne Epoxy-Emulsified Asphalt Mixtures

Patching is one of the most common maintenance methods for potholes in roads. In order to improve the performance of cold-patching asphalt mixtures, an emulsified asphalt modified with waterborne epoxy resin was developed. Two waterborne epoxy resins and two curing agents were selected. The optimal experimental contents of the curing agents were obtained by measuring the compressive strength of the waterborne epoxy mortar (WEM) under different curing agent contents and curing period. The difference between the two waterborne epoxy resins was obtained by the flexural strength and stress–strain curves, which were measured by the modified bending test on the WEM. The evaluation method of the initial strength and forming strength of the waterborne epoxy emulsified asphalt mixture (WEEAM) was proposed by the experimental study of the compaction molding method and curing conditions. The high temperature performance, low temperature performance, and moisture susceptibility of the mixture were verified by comparing various kinds of WEEAM. The results show that using WEEAM as a road repair material has great advantages in improving pavement performance and road service levels