Fasudil in Combination With Bone Marrow Stromal Cells (BMSCs) Attenuates Alzheimer\u27s Disease-Related Changes Through the Regulation of the Peripheral Immune System.

Alzheimer\u27s disease (AD) is a chronic progressive neurodegenerative disease. Its mechanism is still not clear. Majority of research focused on the central nervous system (CNS) changes, while few studies emphasize on peripheral immune system modulation. Our study aimed to investigate the regulation of the peripheral immune system and its relationship to the severity of the disease after treatment in an AD model of APPswe/PSEN1dE9 transgenic (APP/PS1 Tg) mice. APP/PS1 Tg mice (8 months old) were treated with the ROCK-II inhibitor 1-(5-isoquinolinesulfonyl)-homo-piperazine (Fasudil) (intraperitoneal (i.p.) injections, 25 mg/kg/day), bone marrow stromal cells (BMSCs; caudal vein injections, 1 × 1

Study of LDS at Public Mathematics in Local Universities

Analysis of the current situation and background of learning disabilities students at public mathematics in local universities of engineering is provided. We also discuss why these appear . Keywords: Local Universities, Learning Disabilities Students(LDS), Statu

Stress relaxation analysis facilitates a quantitative approach towards antimicrobial penetration into biofilms

Biofilm-related infections can develop everywhere in the human body and are rarely cleared by the host immune system. Moreover, biofilms are often tolerant to antimicrobials, due to a combination of inherent properties of bacteria in their adhering, biofilm mode of growth and poor physical penetration of antimicrobials through biofilms. Current understanding of biofilm recalcitrance toward antimicrobial penetration is based on qualitative descriptions of biofilms. Here we hypothesize that stress relaxation of biofilms will relate with antimicrobial penetration. Stress relaxation analysis of single-species oral biofilms grown in vitro identified a fast, intermediate and slow response to an induced deformation, corresponding with outflow of water and extracellular polymeric substances, and bacterial re-arrangement, respectively. Penetration of chlorhexidine into these biofilms increased with increasing relative importance of the slow and decreasing importance of the fast relaxation element. Involvement of slow relaxation elements suggests that biofilm structures allowing extensive bacterial re-arrangement after deformation are more open, allowing better antimicrobial penetration. Involvement of fast relaxation elements suggests that water dilutes the antimicrobial upon penetration to an ineffective concentration in deeper layers of the biofilm. Next, we collected biofilms formed in intra-oral collection devices bonded to the buccal surfaces of the maxillary first molars of human volunteers. Ex situ chlorhexidine penetration into two weeks old in vivo formed biofilms followed a similar dependence on the importance of the fast and slow relaxation elements as observed for in vitro formed biofilms. This study demonstrates that biofilm properties can be derived that quantitatively explain antimicrobial penetration into a biofilm

Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning

Proactive edge association is capable of improving wireless connectivity at the cost of increased handover (HO) frequency and energy consumption, while relying on a large amount of private information sharing required for decision making. In order to improve the connectivity-cost trade-off without privacy leakage, we investigate the privacy-preserving joint edge association and power allocation (JEAPA) problem in the face of the environmental uncertainty and the infeasibility of individual learning. Upon modelling the problem by a decentralized partially observable Markov Decision Process (Dec-POMDP), it is solved by federated multi-agent reinforcement learning (FMARL) through only sharing encrypted training data for federatively learning the policy sought. Our simulation results show that the proposed solution strikes a compelling trade-off, while preserving a higher privacy level than the state-of-the-art solutions.Comment: 6 pages, 4 figures, IEEE Trans. on Veh. Techno

Age-Gain-Dependent Random Access for Event-Driven Periodic Updating

This paper considers utilizing the knowledge of age gains to reduce the network average age of information (AoI) in random access with event-driven periodic updating for the first time. Built on the form of slotted ALOHA, we require each device to determine its age gain threshold and transmission probability in an easily implementable decentralized manner, so that the unavoided contention can be limited to devices with age gains as high as possible. For the basic case that each device utilizes its knowledge of age gain of only itself, we provide an analytical modeling approach by a multi-layer discrete-time Markov chains (DTMCs), where an external infinite-horizon DTMC manages the jumps between the beginnings of frames and an internal finite-horizon DTMC manages the evolution during an arbitrary frame. Such modelling enables that optimal access parameters can be obtained offline. For the enhanced case that each device utilizes its knowledge of age gains of all the devices, we require each device to adjust its access parameters for maximizing the estimated network \textit{expected AoI reduction} (EAR) per slot, which captures the essential for improving the contribution of the throughput to the AoI performance. To estimate the network EAR, we require each device to use Bayes' rule to keep a posteriori joint probability distribution of local age and age gain of an arbitrary device based on the channel observations. Numerical results validate our theoretical analysis and demonstrate the advantage of the proposed schemes over the existing schemes in a wide range of network configurations

Flow-of-traffic prediction program based mobile edge computing for Internet of vehicles using double auction

With an aim of maximizing the efficiency of edge offloading and the resource utilization of edge computing server simultaneously, a new flow-of-traffic prediction based edge computing offloading solution was proposed for Internet of vehicles (IoV).Firstly, both the efficiency utility function of vehicle and the resource utilization of mobile edge computing (MEC) server were established by considering task priority.Next, the formulated dual-objective optimization problem was transformed into a double auction problem between vehicles and MEC servers.Finally, based on the designed flow-of-traffic based pricing function of vehicle and MEC server, a McAfee auction algorithm was adopted to complete the edge computing process.Simulation results show that benefiting from the flow-of-traffic prediction information, the proposed solution can significantly improve both the efficiency of computation offloading and the utilization of computation resource

Risk factors for extraurothelial recurrence in upper tract urothelial carcinoma after radical nephroureterectomy: a retrospective study based on a Chinese population

ObjectivesThe risk factors for extraurothelial recurrence (EUR) after radical nephroureterectomy (RNU) in patients with upper urinary tract urothelial carcinoma (UTUC) are currently inconsistent and unclear. In this study, we aimed to identify these risk factors and develop a grading system for EUR.MethodsWe retrospectively analyzed 220 patients who underwent RNU for UTUC in our center from January 2009 to December 2020. Overall survival (OS) and extraurothelial recurrence-free survival (EURFS) were compared using the Kaplan–Meier curve with a log-rank test. Univariate and multivariate Cox regression models were applied to identify the independent risk factors related to EUR.ResultsThe median follow-up period was 42 (range: 2–143) months. Of the 220 patients, 61 patients developed EUR in our cohort, which had worse survival outcome. Multivariate Cox regression analysis showed pathologic stage, lymph node (LN) status, lymphovascular invasion (LVI), Ki-67, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were independent risk factors for EUR. The Kaplan–Meier curves revealed a significant difference in EUR among the three risk groups.ConclusionOur study suggests that pathologic stage, LN status, LVI, Ki-67, NLR, and PLR are independent risk factors for EUR in UTUC patients after RNU. The development of a grading system for EUR risk stratification may assist urologists in making clinical decisions regarding the management of UTUC

Non-invasive magnetocardiography of living rat based on diamond quantum sensor

Magnetocardiography (MCG) has emerged as a sensitive and precise method to diagnose cardiovascular diseases, providing more diagnostic information than traditional technology. However, the sensor limitations of conventional MCG systems, such as large size and cryogenic requirement, have hindered the widespread application and in-depth understanding of this technology. In this study, we present a high-sensitivity, room-temperature MCG system based on the negatively charged Nitrogen-Vacancy (NV) centers in diamond. The magnetic cardiac signal of a living rat, characterized by an approximately 20 pT amplitude in the R-wave, is successfully captured through non-invasive measurement using this innovative solid-state spin sensor. To detect these extremely weak biomagnetic signals, we utilize sensitivity-enhancing techniques such as magnetic flux concentration. These approaches have enabled us to simultaneously achieve a magnetometry sensitivity of 9 $\text{pT}\cdot \text{Hz}^{-1/2}$ and a sensor scale of 5 $\text{mm}$. By extending the sensing scale of the NV centers from cellular and molecular level to macroscopic level of living creatures, we have opened the future of solid-state quantum sensing technologies in clinical environments