Regulatory T cells (Tregs) maintain immune equilibrium by suppressing immune responses through various multistep contact dependent and independent mechanisms. Cellular therapy using polyclonal Tregs in transplantation and autoimmune diseases has shown promise in preclinical models and clinical trials. Although novel approaches have been developed to improve specificity and efficacy of antigen specific Treg based therapies, widespread application is currently restricted. To date, design-based approaches to improve the potency and persistence of engineered chimeric antigen receptor (CAR) Tregs are limited. Here, we describe currently available Treg based therapies, their advantages and limitations for implementation in clinical studies. We also examine various strategies for improving CAR T cell design that can potentially be applied to CAR Tregs, such as identifying co-stimulatory signalling domains that enhance suppressive ability, determining optimal scFv affinity/avidity, and co-expression of accessory molecules. Finally, we discuss the importance of tailoring CAR Treg design to suit the individual disease.Transient vestibular organ deafferentation, such that is caused by traumatic tissue injury, is presently addressed by corticosteroid therapy. However, restoration of neurophysiological properties is rarely achieved. Here, it was hypothesized that the tissue-protective attributes of α1-antityrpsin (AAT) may promote restoration of neuronal function. Inner ear injury was inflicted by unilateral labyrinthotomy in wild-type mice and in mice overexpressing human AAT. A 2-week-long assessment of vestibular signs followed. All animals responded with peak vestibular dysfunction scores within 4 h after local trauma. While wild-type animals displayed partial or no recovery across 7 days post-injury, AAT-rich group exhibited early recovery from behavioral score 9-out-of-9 at peak to 4.8 ± 0.44 (mean ± SD) within 8 h from injury, a time when wild-type mice scored 8.6 ± 0.54 (p  less then  0.0001), and from vestibular score 15-out-of-15 to 7.8 ± 2.2 within 24 h, when wild-type mice scored 13.0 ± 2.0 (p  less then  0.01). Thus, recovery and functional normalisation of an injured vestibular compartment is achievable without corticosteroid therapy; expedited tissue repair processes appear to result from elevated circulating AAT levels. This study lays the foundation for exploring the molecular and cellular mediators of AAT within the repair processes of the delicate microscopic structures of the vestibular end organ.Adaptive traffic signal control (ATSC) is a promising technique to improve the efficiency of signalized intersections, especially in the era of connected vehicles (CVs) when real-time information on vehicle positions and trajectories is available. Numerous ATSC algorithms have been proposed to accommodate real-time traffic conditions and optimize traffic efficiency. The common objective of these algorithms is to minimize total delay, decrease queue length, or maximize vehicle throughput. Despite their positive impacts on traffic mobility, the existing ATSC algorithms do not consider optimizing traffic safety. This is most likely due to the lack of tools to evaluate safety in real time. However, recent research has developed various real-time safety models for signalized intersections. These models can be used to evaluate safety in real time using dynamic traffic parameters, such as traffic volume, shock wave characteristics, and platoon ratio. Evaluating safety in real time can enable developing ATSC strategies for real-time safety optimization. In this paper, we present a novel self-learning ATSC algorithm to optimize the safety of signalized intersections. The algorithm was developed using the Reinforcement Learning (RL) approach and was trained using the simulation platform VISSIM. The trained algorithm was then validated using real-world traffic data obtained from two signalized intersections in the city of Surrey, British Columbia. Compared to the traditional actuated signal control system, the proposed algorithm reduces traffic conflicts by approximately 40 %. Moreover, the proposed ATSC algorithm was tested under various market penetration rates (MPRs) of CVs. The results showed that 90 % and 50 % of the algorithm's safety benefits can be achieved at MPR values of 50 % and 30 %, respectively. To the best of the authors' knowledge, this is the first self-learning ATSC algorithm that optimizes traffic safety in real time.The motivation of this research is to understand tourists' aberrant driving behaviors while traveling by car and explore the factors related to these behaviors. A questionnaire that measures driving behaviors, driving attitudes, driving skills, and personal attributes was implemented via the Internet. Through factor analysis, a four-factor structure of tourists' aberrant driving behaviors was obtained. The result indicates that tourists' unsafe driving behaviors have different characteristics from unsafe driving behaviors in daily travel, with a higher frequency of behaviors related to environment, carelessness and fatigue driving. The main cause of these behaviors is drivers' attitude rather than skill and personal attribute. buy Gandotinib When drivers reported themselves good at staying focused, behaviors subject to "Carelessness" were found to increase as there is a more approving attitude towards careless driving among those drivers.Rear-end crashes are closely related to car-following situation of vehicles. Speeding and insufficient headway are the major reasons as the drivers have not enough time to react to a sudden brake from the leading vehicle. Perceptual countermeasures, like speed reduction markings, are widely used in practice for accident prevention, and are verified with substantial effectiveness. However, compared with its practical application, the perceptual countermeasures are rarely analyzed in depth from the perspective of drivers' visual perception where the meaning of "perceptual" actually dwells. In addition, its effect on drivers' headway (distance) choice is almost ignored in previous research. Given this, the present study explored the effects of a certain type of perceptual treatment, i.e., the peripheral transverse line markings (PTLMs), on drivers' choice of speed and headway (distance) in car-following by a series of on-road experiments. In the on-road experiments, temporary line markings were installed on a real-world freeway in China to shape the PTLMs.