Chlorpromazine Protects Against Apoptosis Induced by Exogenous Stimuli in the Developing Rat Brain

Background: Chlorpromazine (CPZ), a commonly used antipsychotic drug, was found to play a neuroprotective role in various models of toxicity. However, whether CPZ has the potential to affect brain apoptosis in vivo is still unknown. The purpose of this study was to investigate the potential effect of CPZ on the apoptosis induced by exogenous stimuli. Methodology: The ethanol treated infant rat was utilized as a valid apoptotic model, which is commonly used and could trigger robust apoptosis in brain tissue. Prior to the induction of apoptosis by subcutaneous injection of ethanol, 7-day-old rats were treated with CPZ at several doses (5 mg/kg, 10 mg/kg and 20 mg/kg) by intraperitoneal injection. Apoptotic cells in the brain were measured using TUNEL analysis, and the levels of cleaved caspase-3, cytochrome c, the pro-apoptotic factor Bax and the anti-apoptotic factor Bcl-2 were assessed by immunostaining or western blot. Findings: Compared to the group injected with ethanol only, the brains of the CPZ-pretreated rats had fewer apoptotic cells, lower expression of cleaved caspase-3, cytochrome c and Bax, and higher expression of Bcl-2. These results demonstrate that CPZ could prevent apoptosis in the brain by regulating the mitochondrial pathway. Conclusions: CPZ exerts an inhibitory effect on apoptosis induced by ethanol in the rat brain, intimating that it may offer

An Integrated Observer Framework Based Mechanical Parameters Identification for Adaptive Control of Permanent Magnet Synchronous Motor

An integrated observer framework based mechanical parameters identification approach for adaptive control of permanent magnet synchronous motors is proposed in this paper. Firstly, an integrated observer framework is established for mechanical parameters’ estimation, which consists of an extended sliding mode observer (ESMO) and a Luenberger observer. Aiming at minimizing the influence of parameters coupling, the viscous friction and the moment of inertia are obtained by ESMO and the load torque is identified by Luenberger observer separately. After obtaining estimates of the mechanical parameters, the optimal proportional integral (PI) parameters of the speed-loop are determined according to third-order best design method. As a result, the controller can adjust the PI parameters in real time according to the parameter changes to realize the adaptive control of the system. Meanwhile, the disturbance is compensated according to the estimates. Finally, the experiments were carried out on simulation platform, and the experimental results validated the reliability of parameter identification and the efficiency of the adaptive control strategy presented in this paper

All around suboptimal health — a joint position paper of the suboptimal health study consortium and European association for predictive, preventive and personalised medicine

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person. This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions:Stress overload associated pathologiesMale and female healthPlanned pregnanciesPeriodontal healthEye disordersInflammatory disorders, wound healing and pain management with associated complicationsMetabolic disorders and suboptimal body weightCardiovascular pathologiesCancersStroke, particularly of unknown aetiology and in young individualsSleep medicineSports medicineImproved individual outcomes under pandemic conditions such as COVID-19

Global Analysis of UDP Glucose Pyrophosphorylase (UDPGP) Gene Family in Plants: Conserved Evolution Involved in Cell Death

UDP glucose pyrophosphorylase (UDPGP) family genes have been reported to play essential roles in cell death or individual survival. However, a systematic analysis on UDPGP gene family has not been performed yet. In this study, a total of 454 UDPGP proteins from 76 different species were analyzed. The analyses of the phylogenetic tree and orthogroups divided UDPGPs into three clades, including UDP-N-acetylglucosamine pyrophosphorylase (UAP), UDP-glucose pyrophosphorylase (UGP, containing UGP-A and UGP-B), and UDP-sugar pyrophosphorylase (USP). The evolutionary history of the UDPGPs indicated that the members of UAP, USP, and UGP-B were relatively conserved while varied in UGP-A. Homologous sequences of UGP-B and USP were found only in plants. The expression profile of UDPGP genes in Oryza sativa was mainly motivated under jasmonic acid (JA), abscisic acid (ABA), cadmium, and cold treatments, indicating that UDPGPs may play an important role in plant development and environment endurance. The key amino acids regulating the activity of UDPGPs were analyzed, and almost all of them were located in the NB-loop, SB-loop, or conserved motifs. Analysis of the natural variants of UDPGPs in rice revealed that only a few missense mutants existed in coding sequences (CDSs), and most of the resulting variations were located in the non-motif sites, indicating the conserved structure and function of UDPGPs in the evolution. Furthermore, alternative splicing may play a key role in regulating the activity of UDPGPs. The spatial structure prediction, enzymatic analysis, and transgenic verification of UAP isoforms illustrated that the loss of N- and C-terminal sequences did not affect the overall 3D structures, but the N- and C-terminal sequences are important for UAP genes to maintain their enzymatic activity. These results revealed a conserved UDPGP gene family and provided valuable information for further deep functional investigation of the UDPGP gene family in plants

Transcriptional dynamics during cell wall removal and regeneration reveals key genes involved in cell wall development in rice

Efficient and cost-effective conversion of plant biomass to usable forms of energy requires a thorough understanding of cell wall biosynthesis, modification and degradation. To elucidate these processes, we assessed the expression dynamics during enzymatic removal and regeneration of rice cell walls in suspension cells over time. In total, 928 genes exhibited significant up-regulation during cell wall removal, whereas, 79 genes were up-regulated during cell wall regeneration. Both gene sets are enriched for kinases, transcription factors and genes predicted to be involved in cell wall-related functions. Integration of the gene expression datasets with a catalog of known and/or predicted biochemical pathways from rice, revealed metabolic and hormonal pathways involved in cell wall degradation and regeneration. Rice lines carrying Tos17 mutations in genes up-regulated during cell wall removal exhibit dwarf phenotypes. Many of the genes up-regulated during cell wall development are also up-regulated in response to infection and environmental perturbations indicating a coordinated response to diverse types of stress

A Privacy-Preserving Caching Scheme for Device-to-Device Communications

With device-to-device (D2D) communication, user equipment can share data with each other without the involvement of network infrastructures. In order to maintain the Quality of Service (QoS) and Quality of Experience (QoE) for user applications in D2D communications, most existing schemes use proactive content caching that needs to predict content popularity before making caching decisions which may result in privacy leakage, since the information of users is collected to train a deep learning-based model to predict content popularity. Therefore, it is crucial to guarantee secure data collection in machine learning-based framework. In this paper, we propose a privacy-preserving D2D caching scheme with a passive content caching strategy based on node importance, which can deliver more efficient caching and prevent the potential leakage of user privacy. The scheme is based on softwaredefined networking (SDN), in which the controller is responsible for calculating node importance of devices according to the information of requests and encounters collected by SDN switches. Base station will decide which device can establish reliable and secure communication with content requester based on historical information. The simulation results show that the proposed strategy can outperform other D2D caching strategies in terms of cache hit rate and data rate

COVID-19 and preparing planetary health for future ecological crises: Hopes from glycomics for vaccine innovation

A key lesson emerging from COVID-19 is that pandemic proofing planetary health against future ecological crises calls for systems science and preventive medicine innovations. With greater proximity of the human and animal natural habitats in the 21st century, it is also noteworthy that zoonotic infections such as COVID-19 that jump from animals to humans are increasingly plausible in the coming decades. In this context, glycomics technologies and the third alphabet of life, the sugar code, offer veritable prospects to move omics systems science from discovery to diverse applications of relevance to global public health and preventive medicine. In this expert review, we discuss the science of glycomics, its importance in vaccine development, and the recent progress toward discoveries on the sugar code that can help prevent future infectious outbreaks that are looming on the horizon in the 21st century. Glycomics offers veritable prospects to boost planetary health, not to mention the global scientific capacity for vaccine innovation against novel and existing infectious agents

An Efficient Trajectory Negotiation and Verification Method Based on Spatiotemporal Pattern Mining

In trajectory-based operations, trajectory negotiation and verification are conducive to using airspace resources fairly, reducing flight delay, and ensuring flight safety. However, most of the current methods are based on route negotiation, making it difficult to accommodate airspace user-initiated trajectory requests and dynamic flight environments. Therefore, this paper develops a framework for trajectory negotiation and verification and describes the trajectory prediction, negotiation, and verification processes based on a four-dimensional trajectory. Secondly, users predict flight trajectories based on aircraft performance and flight plans and submit them as requested flight trajectories to the air traffic management (ATM) system for negotiation in the airspace. Then, a spatiotemporal weighted pattern mining algorithm is proposed, which accurately identifies flight combinations that violate the minimum flight separation constraint from four-dimensional flight trajectories proposed by users, as well as flight combinations with close flight intervals and long flight delays in the airspace. Finally, the experimental results demonstrate that the algorithm efficiently verifies the user-proposed flight trajectory and promptly identifies flight conflicts during the trajectory negotiation and verification processes. The algorithm then analyzes the flight trajectories of aircrafts by applying various constraints based on the specific traffic environment; the flight combinations which satisfy constraints can be identified. Then, based on the results identified by the algorithm, the air traffic management system can negotiate with users to adjust the flight trajectory, so as to reduce flight delay and ensure flight safety

Building a Third-Party Recycling Platform for E-Waste Recycling through an Extended Producer Responsibility Framework

The Extended Producer Responsibility (EPR) system has recently been implemented within E-waste recycling as a key environmental measure. The current insufficient measures and lack of standards in China limit the adoption of EPR. This paper proposes a third-party E-waste recyling system (EWRS) models through EPR. The hope is to simplify the process of returning E-waste from consumers to producers and to help developing a scientific recycling and standard management system. The proposed framework uses the e-commerce information platform to collect and analyze recycling data in real time, therefore optimizing the design of the supply chain