Vehicle Control Research Articles

Quaternion-based fixed-time tracking control for an autonomous underwater vehicle with consideration of measurement bias

This article investigates trajectory and attitude tracking control problem of a 6-degree of freedom (DOF) autonomous underwater vehicle (AUV) subject to measurement bias and external disturbance. First, the model dynamics of rotational channels are established by unit-quaternion, which possesses simplicity and broader applicability compared to the Euler angle such that the maneuver signal could be uniquely determined. Meanwhile, by introducing constraint of the logarithm function and initial value, the unwinding phenomenon existing in rotation motion can be avoided tactfully. Considering the high requirement for sensor accuracy, the resulting measurement bias in position and velocity channels, making AUV into a mismatched system and bring the uncertain term in the process of controller design. Therefore, the echo state network (ESN) with online updates performance is applicable to approximate uncertain term simultaneously generated by measurement bias and unknown external disturbance. Then, by incorporating composite hyperbolic tangent function, the quasi-fast terminal sliding mode (QTSM) surface is constructed to realize the fixed-time convergence peculiarity of the AUV tracking system. Compared with the existing methods, the proposed algorithm can regulate artificially the stable schedule of the AUV tracking system and possess the capacity of bias tolerance and anti-disturbance. Finally, simulation results verify the validity and feasibility of the developed control algorithm.

A comprehensive review on safe reinforcement learning for autonomous vehicle control in dynamic environments

To operate safely in a dynamic environment, autonomous vehicles must possess the same level of predictive driving abilities as human drivers and must be capable of anticipating the future actions of other dynamic objects in the environment, especially those of neighboring vehicles. The development of safe autonomous vehicles (AVs) poses a challenging task as it requires algorithms that can make real-time decisions in unpredictable circumstances. Reinforcement learning (RL) presents a promising approach for AV control, as it utilizes trial and error to enable optimal decision-making. However, traditional RL algorithms are unsuitable for safety-critical applications, as they may explore unsafe actions, potentially resulting in accidents. Safe reinforcement learning (SRL) algorithms have been developed to address this issue, prioritizing safe and reliable decisions. These algorithms incorporate constraints to prevent unsafe actions or utilize techniques to estimate action risk and avoid actions deemed excessively risky. Despite computational challenges, SRL holds significant promise for AV control, and is likely to play a crucial role in developing safe and reliable systems. SRL methods are critical for the general adoption of autonomous vehicles by guaranteeing their safety and reliability. These algorithms utilize methods like uncertainty and risk estimation along with penalty functions, to avoid excessively risky actions and have the potential to significantly reduce accidents and build public trust in autonomous driving. However, there are challenges that need to be addressed, such as the dynamic nature of real-world traffic, high computational costs, and the diversity of road design; and these varying conditions make the designing, testing, and validating of SRL algorithms difficult. Despite these challenges, SRL presents a promising solution, through integrating new sensing technologies and machine learning techniques, to develop safe, efficient, and environmentally friendly transportation systems.

Empagliflozin ameliorates olfactory bulbectomy-induced depression by mitigating oxidative stress and possible involvement of brain derived neurotrophic factor in diabetic rats

Empagliflozin, a sodium-glucose co-transporter 2 (SGLT2) inhibitor, has recently reported to prevent the depression as chronic animal model. However, its impact on neuroinflammation-mediated depression were remains unexplored. The present study aimed to explore the antidepressant potential of empagliflozin using a neuroinflammation-mediated depression involving the olfactory bulbectomy (OBX) model in rats. To establish this model, initially a low dose of streptozotocin was injected to induce diabetes in all group of animals. Following the confirmation of hyperglycemia, OBX surgery was performed. Post-surgery, the drug treatments were administered orally for 14 consecutive days. The study evaluated the effects of daily oral administration of empagliflozin at doses of 5 and 10 mg/kg, alongside metformin (200 mg/kg) and clomipramine (50 mg/kg), on OBX-induced behavioral depression in rats. Separate sham and vehicle control groups were also maintained. Behavioral parameters in open field, forced swim test, elevated plus maze and splash test were recorded on 28th day. Results showed that empagliflozin, particularly at the higher at the higher dose, significantly enhanced behavioral outcomes, evidenced by increased distance traveled, greater open arm entries, and reduced immobility, alongside a notable reduction in grooming time. Moreover, empagliflozin significantly restored the antioxidants level specifically Glutathione (GSH) and Catalase (CAT) in OBX insulted rat brain and reversed Lipid peroxidase (LPO). Notably, molecular docking study demonstrated a good binding affinity of empagliflozin for Brain-Derived Neurotrophic Factor (BDNF), suggesting that its antidepressant effects may be mediated through the modulation of the BDNF pathway. These findings support the potential therapeutic application of empagliflozin for depression, particularly in cases associated with neuroinflammation and oxidative stress.

Proposal of an Optimal Control of an Electric Vehicle by Combined FOC and DTC Techniques

Proposal of an Optimal Control of an Electric Vehicle by Combined FOC and DTC Techniques

Comparison of Dietary Supplementation with Krill Oil, Fish Oil, and Astaxanthin on an Experimental Ethanol-Induced Gastric Ulcer Model: A Biochemical and Histological Study

Background/Objectives: Despite advances in ulcer treatment research, the search for new, safe, and effective strategies for preventing and treating ulcer diseases persists. Methods: In this study, the protective effects of dietary supplementation with krill oil (KO), fish oil (FO), and astaxanthin (ASX) on an ethanol-induced gastric ulcer model were compared during biochemical and histological observations. Sprague–Dawley (n = 64) rats randomly divided into four groups—normal control (vehicle), KO, FO, and ASX groups—received the supplements via the orogastric route at a rate of 2.5% (v/w) of their daily feed consumption for 4 weeks. Then, ulcer induction was performed with ethanol. Results: The ulcer group showed increased levels of malondialdehyde (MDA), chemiluminescence (CL), and myeloperoxidase (MPO) activity and decreased levels of glutathione in the gastric tissues. While KO, FO, and ASX supplementation decreased chemiluminescence levels in the ulcer group, only ASX supplementation decreased MDA levels and MPO activity. Conclusions: In conclusion, supplementation with KO or FO has a similar protective effect against ethanol-induced ulcer damage, as it inhibits ROS formation and reduces lipid peroxidation. However, ASX supplementation has a higher protective effect than KO or FO supplementations against experimental ethanol-induced gastric lesions in rats, as it inhibits ROS formation and reduces neutrophil infiltration and lipid peroxidation.

Design and Implementation of Unity-based Special Unmanned Vehicle Operating Simulator

Special unmanned vehicles can replace personnel to perform military tasks with high risk coefficients, such as long-distance reconnaissance, guided irradiation, and weapons strikes. In order to ensure that the special unmanned vehicle can quickly and accurately complete the established task action, the operator should carry out a large number of trainings in advance for the task content, if the training is directly used in the early stage of the training to manipulate the training, which has the security risks, it’s easy to increase the operator's psychological pressure, and the actual training site can't realistically restore the task scene, the training effect is also single. In view of the above problems, this paper designs a special unmanned vehicle control simulator, which enables the trainers to intuitively understand the task content and key points, and at the same time can control the unmanned vehicle in the virtual task environment to carry out the established task training and result review and analysis, so as to rapidly improve the control level of the trainers and ensure the successful completion of the established task.

Toxicology profile of a novel GLP-1 receptor biased agonist-SAL0112 in nonhuman primates

Oral small-molecule GLP-1 receptor biased agonists exhibit promising treatment efficacy of type 2 diabetes and obesity. SAL0112 is a novel compound that has demonstrated remarkable efficacy in preclinical animal models. Herein, both in vitro and in vivo preclinical toxicity investigations were conducted to explore the safety profile of SAL0112. The HTRF assay and TR-FRET assay were utilized for cAMP detection. Patch clamp assay was employed for hERG potassium ion channel determination. Cynomolgus monkeys were used in a cardiovascular safety pharmacology study and a 13-week repeated dose toxicity study. The telemetry system was employed to detect cardiovascular indicators such as ECG, HR, and BP. During the repeated dose toxicity study, body weight, food intake, hematology, coagulation function test, serum biochemistry tests, and urine analysis were measured. Macroscopic and microscopic observations were conducted at the end of the study. TK studies were conducted on Day 1 and Day 91. SAL0112 exhibited a high degree of potency in activating the monkey GLP-1 receptor whereas had no effect on the rodent GLP-1 receptor. In contrast to Danuglipron, which demonstrated high potency on hERG with an IC50 value of 6.9 μM, the IC50 of SAL0112 on hERG was greater than 100 μM. Compared to the Vehicle Control group, no significant changes in cardiovascular indicators were observed in the cardiovascular safety pharmacology study after a single dose of SAL0112 up to 250 mg/kg (P > 0.05). A repeated dose toxicity study revealed moderate anorexigenic effects and a reduction in body weight, effects that were found to be reversible and not associated with any pathological changes. The NOAEL of SAL0112 is 150 mg/kg, providing an approximate safety margin of threefold. SAL0112 demonstrated a favorable safety profile in cynomolgus monkeys, with a substantial therapeutic window that supports the progression of this compound into clinical studies.

Chronic late gestation fetal hyperglucagonaemia results in lower insulin secretion, pancreatic mass, islet area and beta- and α-cell proliferation.

Fetal glucagon concentrations are elevated in the presence of a compromised intrauterine environment, as in cases of placental insufficiency and perinatal acidaemia. Our objective was to investigate the impact of late gestation fetal hyperglucagonaemia on in vivo insulin secretion and pancreatic islet structure. Chronically catheterized late gestation fetal sheep received an intravenous infusion of glucagon at low (5ng/kg/min; GCG-5) or high (50ng/kg/min; GCG-50) concentrations or a vehicle control (CON) for 8-10days.Glucose-stimulated fetal insulin secretion (GSIS) was measured following 3h (acute response) and 8-10days (chronic response) of experimental infusions. Insulin, glucose and amino acid concentrations were measured longitudinally. The pancreas was collected at the study end for histology and gene expression analysis. Acute exposure (3h) to GCG-50 induced a 3-fold increase in basal insulin concentrations with greater GSIS. Meanwhile, chronic exposure to both GCG-5 and GCG-50 decreased basal insulin concentrations 2-fold by day 8-10. Chronic GCG-50 also blunted GSIS at the study end. Fetal amino acid concentrations were decreased within 24h of GCG-5 and GCG-50, while there were no differences in fetal glucose. Histologically, GCG-5 and GCG-50 had lower β- and α-cell proliferation, as well as lower α-cell mass and pancreas weight, while GCG-50 had lower islet area. This study demonstrates that chronic glucagon elevation in late gestation fetuses impairs β-cell proliferation and insulin secretion, which has the potential to contribute to later-life diabetes risk. We speculate that the action of glucagon in lower circulating fetal amino acid concentrations may have a suppressive effect on insulin secretion. KEY POINTS: We have previously demonstrated in a chronically catheterized fetal sheep model that experimentally elevated glucagon in the fetus impairs placental function, reduces fetal protein accretion and lowers fetal weight. In the present study, we further characterized the effects of elevated fetal glucagon on fetal physiology with a focus on pancreatic development and β-cell function. We show that experimentally elevated fetal glucagon results in lower β- and α-cell proliferation, as well as decreased insulin secretion after 8-10days of glucagon infusion. These results have important implications for β-cell reserve and later-life predisposition to diabetes.

Macrophage-derived amphiregulin promoted the osteogenic differentiation of chondrocytes through EGFR/Yap axis and TGF-β activation

Endochondral ossification represents a crucial biological process in skeletal development and bone defect repair. Macrophages, recognized as key players in the immune system, are now acknowledged for their substantial role in promoting endochondral ossification within cartilage. Concurrently, the epidermal growth factor receptor (EGFR) ligand amphiregulin (Areg) has been documented for its contributory role in restoring bone tissue homeostasis post-injury. However, the mechanism by which macrophage-secreted Areg facilitates bone repair remains elusive. In this study, the induction of macrophage depletion through in vivo administration of clodronate liposomes was employed in a standard open tibial fracture mouse model to assess bone healing using micro-computed tomography (micro-CT) analysis, histomorphology, and ELISA serum evaluations. The investigation revealed sustained expression of Areg during the fracture healing period in wild-type mice. Macrophage depletion significantly reduced the number of macrophages on the local bone surface and vital organs. This reduction led to diminished Areg secretion, decreased collagen production, and delayed fracture healing. However, histological and micro-CT assessments at 7 and 21 days post-local Areg treatment exhibited a marked improvement of bone healing compared to the vehicle control. In vitro studies demonstrated an increase of Areg secretion by the Raw264.7 cells upon ATP stimulation. Indirect co-culture of Raw264.7 and ATDC5 cells indicated that Areg overexpression enhanced the osteogenic potential of chondrocytes, and vice versa. This osteogenic promotion was attributed to Areg's activation of the membrane receptor EGFR in the ATDC5 cell line, the enhanced phosphorylation of transcription factor Yap, and the facilitation of the expression of bioactive TGF-β by chondrocytes. Collectively, this research elucidates the direct mechanistic effects of macrophage-secreted Areg in promoting bone homeostasis following bone injury.

Research on the potential of integrated vehicle control with closed-loop phase portrait analysis

The phase portrait is an important tool for analyzing vehicle stable region widely utilized in vehicle dynamic control systems. At handling limits, traditional open-loop vehicle stable region constraints will restrict the vehicle control ability, while the closed-loop actuator interventions can help states outside the open-loop stable region converge back to stable origin, which is more suitable for constraining vehicle states under extreme working conditions. This article systematically analyzes the potential of integrated vehicle control with closed-loop phase portrait. Firstly, a vehicle dynamic model considering actuator dynamics and tire transient characteristics is established. Then, a numerical optimal control method for calculating closed-loop controllability region is introduced. The controllability region under different friction coefficients, vehicle speeds, convergence time, vehicle steering response characteristics, actuator time constants, and tire transient characteristics are discussed and analyzed. In terms of different control inputs combinations, this article displays the controllability regions under different front steering angles, rear steering angles, direct yaw moments, and their synergistic performances. Control input laws derived from numerical optimization are summarized in two specific directions. Finally, a comparative analysis of open-loop stable regions and closed-loop controllability regions confirms the superiority of the proposed method. Potential applications of the systematic analysis are also discussed.

Trajectory optimization and stability control for a novel unmanned intelligent wheel-legged vehicles on unstructured terrains

The trend of intelligent vehicles is currently expanding, and a new class of unmanned intelligent vehicles known as wheel-legged vehicles (WLVs) is emerging. WLVs excel in transportation on unstructured terrain by offering a unique combination of the efficiency of wheels on flat ground and the versatility of legs to tackle obstacles. To enhance the locomotion performance of WLVs on unstructured terrains, this paper presents a novel framework for improving their locomotion through nonlinear programming-based (NLP) trajectory optimization and stability control. The framework optimizes the vehicle’s body and wheel positioning while incorporating terrain information and employs a linear rigid body dynamic model for efficient motion planning. The stability control framework combines feedforward control using ground reaction forces with feedback control through joint PD control and utilizes model predictive control (MPC) to adjust the wheel slip ratio to prevent slip on steep slopes. Experimental validation on the real vehicle with torque-controlled wheels demonstrated the capability of driving over a 1 m height with a 30°slope at an average speed of 0.7 m/s and a maximum speed of 1.03 m/s. Our approach also enables the WLV to overcome obstacles, such as inclines, while dynamically negotiating these challenging terrains.

Silmitasertib in Combination With Cabozantinib Impairs Liver Cancer Cell Cycle Progression, Induces Apoptosis, and Delays Tumor Growth in a Preclinical Model.

The rising incidence of hepatocellular carcinoma (HCC) is a global problem. Several approved treatments, including immune therapy and multi-tyrosine kinase inhibitors, are used for treatment, although the results are not optimum. There is an unmet need to develop highly effective chemotherapies for HCC. Targeting multiple pathways to attack cancer cells is beneficial. Cabozantinib is an orally available bioactive multikinase inhibitor and has a modest effect on HCC treatment. Silmitasertib is an orally bioavailable, potent CK2 inhibitor with a direct role in DNA damage repair and is in clinical trials for other cancers. In this study, we planned to repurpose these existing drugs on HCC treatment. We observed a stronger antiproliferative effect of these two combined drugs on HCC cells generated from different etiologies as compared to the single treatment. Global RNA-seq analyses revealed a decrease in the expression of G2/M cell cycle transition genes in HCC cells following combination treatment, suggesting G2 phase cell arrest. We observed G2/M cell cycle phase arrest in HCC cells upon combination treatment compared to the single-treated or vehicle-treated control cells. The downregulation of CCNA2 and CDC25C following combination therapy further supported the observation. Subsequent analyses demonstrated that combination treatment inhibited 70 kDa ribosomal protein S6 kinase (p70S6K) phosphorylation, and increased Bim expression. Apoptosis of HCC cells were accompanied by increased poly (ADP-ribose) polymerase cleavage and caspase-9 activation. Next, we observed that a combination therapy significantly delayed the progression of HCC xenograft growth as compared to vehicle control. Together, our results suggested combining cabozantinib and silmitasertib would be a promising treatment option for HCC.

An Investigation of Classical Model Predictive Controller Path Tracking Performance of a Two-Wheel and Four-Wheel Steering Vehicle

Studies on self-driving vehicles have become a trend in recent years, and many systems have been developed to enable autonomous manoeuvre. Various methods have been used to improve path-tracking algorithms which increase vehicle performance, including tracking accuracy and stability. Path tracking is one of the primary problems for autonomous vehicles where the vehicle deviates from target paths, which leads to unnecessary counter-correction. Conventional front wheel steering is unable to satisfy the manoeuvre with a high lateral acceleration since the front steering angle is limited in accurately responding to vehicle dynamics. Moreover, the characteristics of front wheel steering vehicles affect handling stability due to the fact that the turning radius is larger than the vehicle itself. This disadvantageous can compromise safety during under-steer and over-steer situations. The main objective of this preliminary study is to investigate the performance of a four-wheel steering system (4WS) in path tracking for autonomous vehicles using a classical model predictive controller (MPC). Conventional two-wheel steering (2WS) tracking performance following the desired driving system with the same MPC controller is compared with 4WS vehicles. The driving system is developed using Driving Scenario Designer to extract the desired yaw angle and lateral position for controller references constructed in Matlab Simulink. Fixed MPC constraint, prediction, control horizon, yaw angle and lateral position weights were used to compare the performance between 2WS and 4WS vehicles. The simulation results show that 4WS is three times better than 2WS vehicles in tracking predetermined paths. 4WS vehicle show 74.55% better performance in lateral position tracking and 68.75% better performance in trailing predetermined yaw angle value. The simulation data from the preliminary study will be used as a guideline to develop an advanced controller of 4WS vehicles.

Motion control of autonomous underwater vehicle based on physics-informed offline reinforcement learning

Online reinforcement learning (RL) methods for autonomous underwater vehicles (AUV) are time-consuming and unsafe due to the need for real-world interaction. Offline RL methods can improve efficiency and safety by training with dynamic models, but an accurate model for AUV is difficult to obtain due to its highly nonlinear dynamics. These limit the application of RL methods in AUV control. To solve this issue, we propose physics-informed model-based conservative offline policy optimization (PICOPO). It offers the advantages of small dataset, strong generalizability and high safety by combining the physics-informed dynamic modelling method and the offline RL technique. First, the PICOPO constructs a physics-informed model based on a small offline dataset to serve as the digital twins (DT) of the actual AUV. This DT can forecast the long-term motion states of AUV with high-precision. The RL-based controller is then trained offline within this DT, eliminating the need for real-world interaction and allowing direct deployment to the AUV without fine-tuning. In this paper, simulations and field tests are carried out to evaluate the proposed method. Our results demonstrate that PICOPO achieves accurate motion control with just 2000 samples and enables zero-shot sim-to-real transfer, showcasing strong generalizability across various motion control tasks.

Electronic brake system-based hierarchical motion control of commercial vehicle for autonomous obstacle avoidance

As a high-level autonomous driving technology, efficient and safe automatic obstacle avoidance on highway is one of the critical and ongoing topics that requires in-depth research for commercial vehicles. Electronic control air pressure brake system, owing to its fast response and active braking ability, is an effective active-chassis technology to function path tracking and stability control in such condition. Yaw motion stability control problem of autonomous driving commercial vehicle based on active braking control with electronic air brake system for automatic obstacle avoidance is investigated. First, a hierarchical yaw motion dynamics control architecture is introduced after vehicle and brake system modeling. The quintic polynomial curve-based trajectory planning method and a Model Predictive Control based trajectory tracking control strategy are formulated. Second, to evade the possible stability losing issue in this circumstance, Cubature Kalman Filter (CKF) is utilized to estimate the vehicle motion states, and a fuzzy PID control-based differential brake stability control strategy is designed for the electronic brake system composed of front-and-rear two sets of dual-channel pressure regulator and ABS solenoid valve. Finally, the proposed hierarchical yaw stability control strategy for a commercial vehicle in typical obstacle avoidance conditions is comparatively verified based on the joint simulation tools. After the yaw stability control, the peak value of the lateral displacement error of trajectory tracking can be reduced by 44.7%. The yaw stability control strategy based on fuzzy PID control can reduce the yaw rate by 46%–57% and the sideslip angle by 60%–73% under different conditions. The results show that the proposed control strategy can effectively improve the yaw stability of the vehicle while avoiding obstacles at high speed.

3′,4′-Dihydroxyflavonol Inhibits Fibrotic Response in a Rabbit Model of Glaucoma Filtration Surgery

Post-operative fibrosis of the filtering bleb limits the success of glaucoma filtration surgery (GFS). To minimise subconjunctival scarring following GFS, treatment with antimetabolites such as Mitomycin C (MMC) has become standard practice; however, their use is associated with considerable side effects. This study aimed to investigate the anti-scarring properties of 3′,4′-dihydroxyflavonol (DiOHF). GFS was performed in New Zealand white rabbits who received eye drops of DiOHF three times daily and vehicle eye drops after surgery (n = 5) or a single intraoperative treatment of MMC (n = 5). Blebs were imaged immediately following surgery and on days 7, 15, 21, and 28 for clinical examination. On day 28, eyes were harvested to assess collagen deposition, expression of α-SMA, oxidative stress, angiogenesis, fibroblast activity, and inflammation in the conjunctiva/Tenon’s layer. At 7 and 28 days post-GFS, MMC-treated blebs were more ischaemic than DiOHF- or vehicle-treated blebs. On day 28, DiOHF treatment significantly suppressed collagen accumulation, CD31 expression, Vimentin expression, and CD45 expression compared to the vehicle control. No difference was observed in 3-Nitrotyrosine or αSMA expression between treatment groups. Treatment with DiOHF reduced conjunctival scarring and angiogenesis in rabbits with GFS, which was comparable to MMC. DiOHF may be a safer and more effective wound-modulating agent than conventional antifibrotic therapy in GFS.

Optical flow-based control for micro air vehicles: an efficient data-driven incremental nonlinear dynamic inversion approach

Optical flow-based control for micro air vehicles: an efficient data-driven incremental nonlinear dynamic inversion approach

Drone motion prediction from flight data: a nonlinear time series approach

In this paper, we explore the application of data-driven predictive systems in enhancing unmanned aerial vehicle (UAV) control capabilities. We introduce a new model for predicting the motion of individual drones by utilizing fundamental flight control data. The model aims to improve the autonomy of individual drones and circumvent the complexity of traditional flight control systems, thus eliminating intricate nested controls. The proposed model lays the foundation for studying collective behaviours within a cluster of drones, thereby advancing the research into swarm behaviour exhibited by drones. The research findings demonstrate the potential of data-driven methods in the construction of UAV control systems. In particular, we here show a comparison of the prediction performances between two neural network architectures using real drone flight data involved in various kinds of motions. We explore the utility of using long short term memory (LSTM) and nonlinear autoregressive with exogenous inputs (NARX) family of nonlinear time series models in developing a virtual drone model using real experimental data.

Safeguarding Personal Identifiable Information (PII) after Smartphone Pairing with a Connected Vehicle

The integration of connected autonomous vehicles (CAVs) has significantly enhanced driving convenience, but it has also raised serious privacy concerns, particularly regarding the personal identifiable information (PII) stored on infotainment systems. Recent advances in connected and autonomous vehicle control, such as multi-agent system (MAS)-based hierarchical architectures and privacy-preserving strategies for mixed-autonomy platoon control, underscore the increasing complexity of privacy management within these environments. Rental cars with infotainment systems pose substantial challenges, as renters often fail to delete their data, leaving it accessible to subsequent renters. This study investigates the risks associated with PII in connected vehicles and emphasizes the necessity of automated solutions to ensure data privacy. We introduce the Vehicle Inactive Profile Remover (VIPR), an innovative automated solution designed to identify and delete PII left on infotainment systems. The efficacy of VIPR is evaluated through surveys, hands-on experiments with rental vehicles, and a controlled laboratory environment. VIPR achieved a 99.5% success rate in removing user profiles, with an average deletion time of 4.8 s or less, demonstrating its effectiveness in mitigating privacy risks. This solution highlights VIPR as a critical tool for enhancing privacy in connected vehicle environments, promoting a safer, more responsible use of connected vehicle technology in society.

7936 Type 1 Diabetes Therapeutic Compound MSB-61: Using RNA Sequencing To Identify The Mechanism

Abstract Disclosure: P. Khan: None. K. Corbin: None. N. Ajmal: None. S. Bergmeir: None. G. Gu: None. X. Tong: None. C.S. Nunemaker: None. Abstract Type 1 diabetes (T1D) is a chronic autoimmune disease in which loss of insulin-producing beta-cells leads to hyperglycemia due to which patients eventually require lifelong insulin therapy to maintain normal glycemic control. Insulin remains the gold standard and the only effective treatment for T1D since its discovery 100 years ago. Protecting the pancreatic beta cells from cytokine-induced cell death and restoring insulin secretion are important to treat T1D, two properties that are currently lacking in present therapies. Our lab identified a chemical compound MSB-61 that increases insulin release and protects pancreatic islets against T1D-associated cytokines and endoplasmic reticulum (ER) stress. This study aims to identify the mechanism of action of MSB-61 in protecting pancreatic islets from ER stress-induced cell death. To achieve this aim pancreatic islets obtained from CD-1 strain mice were exposed for one hour to 50uM MSB-61 or vehicle control. After treatment, RNA was collected for RNA sequencing. In addition to RNA extraction for sequencing, MSB-61's ability to secrete insulin was verified by performing ELISA on control,10 and 50uM MSB-61-treated islets, and the activity of protection from cell death was assessed by performing cell death assay on islets treated with ER stressors in the presence and absence of 10 and 50uM MSB-61. Using Genialis, a bioinformatics service, we evaluated 57,010 genes (including non-coding transcripts) in our RNA sequencing data set. The DESeq2 technique of data analysis allowed us to identify 350 differentially expressed genes (DEGs), of which 251 were upregulated and 74 were downregulated. After removing non-coding/undefined transcripts and genes with <5 counts per million, a total of 117 genes remained; 108 up and 9 down. According to the String database (string-db.org), many of the top DEGs formed a common network of genes associated with cell death protection and insulin secretion. A key component of that gene network is a stress-responsive orphan nuclear receptor with known protective effects in beta cells. Testing this orphan nuclear receptor as a possible direct or indirect target of MSB-61 for cell death prevention can aid in identifying the genes and pathways targeted by MSB-61, allowing us to improve our approaches to T1D treatment and develop better medications. Presentation: 6/3/2024