The aging trajectories of brain functional hierarchy and its impact on cognition across the adult lifespan

IntroductionThe hierarchical network architecture of the human brain, pivotal to cognition and behavior, can be explored via gradient analysis using restingstate functional MRI data. Although it has been employed to understand brain development and disorders, the impact of aging on this hierarchical architecture and its link to cognitive decline remains elusive.MethodsThis study utilized resting-state functional MRI data from 350 healthy adults (aged 20–85) to investigate the functional hierarchical network using connectome gradient analysis with a cross-age sliding window approach. Gradient-related metrics were estimated and correlated with age to evaluate trajectory of gradient changes across lifespan.ResultsThe principal gradient (unimodal-to-transmodal) demonstrated a significant non-linear relationship with age, whereas the secondary gradient (visual-to-somatomotor) showed a simple linear decreasing pattern. Among the principal gradient, significant age-related changes were observed in the somatomotor, dorsal attention, limbic and default mode networks. The changes in the gradient scores of both the somatomotor and frontal–parietal networks were associated with greater working memory and visuospatial ability. Gender differences were found in global gradient metrics and gradient scores of somatomotor and default mode networks in the principal gradient, with no interaction with age effect.DiscussionOur study delves into the aging trajectories of functional connectome gradient and its cognitive impact across the adult lifespan, providing insights for future research into the biological underpinnings of brain function and pathological models of atypical aging processes

Square Key Matrix Management Scheme in Wireless Sensor Networks

In this paper we propose a symmetric cryptographic approach named Square Key Matrix Management Scheme (SKMaS) in which a sensor node named Key Distribution Server (KDS) is responsible for the security of key management. When the system starts up, the KDS sends its individual key and two sets of keys to sensor nodes. With the IDs, any two valid sensor nodes, e.g. i and j, can individually identify the corresponding communication keys (CKs) to derive a dynamic shared key (DSK) for encrypting/decrypting messages transmitted between them. When i leaves the underlying network, the CKs and the individually keys currently utilized by i can be reused by a newly joining sensor, e.g. h. However, when h joins the network, if no such previously-used IDs are available, h will be given a new ID, CKs and the individually key by the KDS. The KDS encrypts the CKs, with which an existing node q can communicate with h, with individual key so that only q rather than h can correctly decrypt the CKs. The lemmas and security analyses provided in this paper prove that the proposed system can protect at least three common attacks

Mesh Network for RFID and Electric Vehicle Monitoring in Smart Charging Infrastructure

With an increased number of plug-in electric vehicles (PEVs) on the roads, PEV charging infrastructure is gaining an ever-more important role in simultaneously meeting the needs of drivers and those of the local distribution grid. However, the current approach to charging is not well suited to scaling with the PEV market. If PEV adoption continues, charging infrastructure will have to overcome its current shortcomings such as unresponsiveness to grid constraints, low degree of autonomy, and high cost, in order to provide a seamless and configurable interface from the vehicle to the power grid. Among the tasks a charging station will have to accomplish will be PEV identification, charging authorization, dynamic monitoring, and charge control. These will have to be done with a minimum of involvement at a maximum of convenience for a user. The system proposed in this work allows charging stations to become more responsive to grid constraints and gain a degree of networked autonomy by automatically identifying and authorizing vehicles, along with monitoring and controlling all charging activities via an RFID mesh network consisting of charging stations and in-vehicle devices. The proposed system uses a ZigBee mesh network of in-vehicle monitoring devices which simultaneously serve as active RFID tags and remote sensors. The system outlined lays the groundwork for intelligent charge-scheduling by providing access to vehicle’s State of Charge (SOC) data as well as vehicle/driver IDs, allowing a custom charging schedule to be generated for a particular driver and PEV. The approach presented would allow PEV charging to be conducted effectively while observing grid constraints and meeting the needs of PEV drivers

The growing needs of genetic counselling—Feasibility in utilization of tele-genetic counselling in Asia and Hong Kong

The need for the expansion of genomic services has been at a record time high in the past decade. As technological advancement continues to strengthen the entire genetic and genomic pipeline and clinical operational workflow, the major challenge remains to be the speed of workforce development to meet service growth. In particular, the international expansion of genetic counselling (GC) services has been a topic of interest for the past few years. GC is an emerging profession in most of Asia, and in many countries the profession of GC often refers to physicians or front-line health workers with expertise in genetics to provide GC services rather than being a specific independent profession. As genetic and genomic services, especially pre-test and post-test GC, expand globally, the need to tackle the longstanding obstacles of GC personnel shortage and funding issues must not be overlooked. There is an urgent need internationally, and especially in Asia, where GC profession is comparatively less well-established, to seek alternative approaches to meet service demand. The present review examines the global development and feasibility of tele-genetics and tele-genetic counselling (TGC), and serves as the foundation to explore a possible roadmap in Hong Kong via the Hong Kong Genome Project

Src-family kinase-Cbl axis negatively regulates NLRP3 inflammasome activation.

Activation of the NLRP3 inflammasome is crucial for immune defense, but improper and excessive activation causes inflammatory diseases. We previously reported that Pyk2 is essential for NLRP3 inflammasome activation. Here we show that the Src-family kinases (SFKs)-Cbl axis plays a pivotal role in suppressing NLRP3 inflammasome activation in response to stimulation by nigericin or ATP, as assessed using gene knockout and gene knockdown cells, dominant active/negative mutants, and pharmacological inhibition. We reveal that the phosphorylation of Cbl is regulated by SFKs, and that phosphorylation of Cbl at Tyr371 suppresses NLRP3 inflammasome activation. Mechanistically, Cbl decreases the level of phosphorylated Pyk2 (p-Pyk2) through ubiquitination-mediated proteasomal degradation and reduces mitochondrial ROS (mtROS) production by contributing to the maintenance of mitochondrial size. The lower levels of p-Pyk2 and mtROS dampen NLRP3 inflammasome activation. In vivo, inhibition of Cbl with an analgesic drug, hydrocotarnine, increases inflammasome-mediated IL-18 secretion in the colon, and protects mice from dextran sulphate sodium-induced colitis. Together, our novel findings provide new insights into the role of the SFK-Cbl axis in suppressing NLRP3 inflammasome activation and identify a novel clinical utility of hydrocortanine for disease treatment