Inhibitors of Phosphatidylinositol 3′-Kinases Promote Mitotic Cell Death in HeLa Cells

The phosphatidylinositol 3-kinase (PI3K) pathway plays an important role in many biological processes, including cell cycle progression, cell growth, survival, actin rearrangement and migration, and intracellular vesicular transport. However, the involvement of the PI3K pathway in the regulation of mitotic cell death remains unclear. In this study, we treated HeLa cells with the PI3K inhibitors, 3-methyladenine (3-MA, as well as a widely used autophagy inhibitor) and wortmannin to examine their effects on cell fates using live cell imaging. Treatment with 3-MA decreased cell viability in a time- and dose-dependent manner and was associated with caspase-3 activation. Interestingly, 3-MA-induced cell death was not affected by RNA interference-mediated knockdown (KD) of beclin1 (an essential protein for autophagy) in HeLa cells, or by deletion of atg5 (an essential autophagy gene) in mouse embryonic fibroblasts (MEFs). These data indicate that cell death induced by 3-MA occurs independently of its ability to inhibit autophagy. The results from live cell imaging studies showed that the inhibition of PI3Ks increased the occurrence of lagging chromosomes and cell cycle arrest and cell death in prometaphase. Furthermore, PI3K inhibitors promoted nocodazole-induced mitotic cell death and reduced mitotic slippage. Overexpression of Akt (the downstream target of PI3K) antagonized PI3K inhibitor-induced mitotic cell death and promoted nocodazole-induced mitotic slippage. These results suggest a novel role for the PI3K pathway in regulating mitotic progression and preventing mitotic cell death and provide justification for the use of PI3K inhibitors in combination with anti-mitotic drugs to combat cancer

Energy Efficiency Optimization for RIS-Assisted UAV-Enabled MEC Systems

The reconfigurable intelligent surface (RIS) can proactively modify the wireless communication environment and further improve the service quality of the wireless networks. Motivated by this vision, in this paper, we propose to introduce the RIS into the unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) systems. Considering both the amount of completed task bits and the energy consumption, the energy efficiency of the RIS-assisted UAV-enabled MEC systems is maximized by jointly optimizing the bit allocation, phase shift, and UAV trajectory via an iterative algorithm with a double-loop structure. Simulation results show that: 1) the UAV tends to fly closer to the RIS rather than the IoT devices; 2) the energy efficiency first increases and then decreases with the increase of the total amount of task-input bits of IoT devices; 3) higher energy efficiency can be achieved by our proposed algorithm

EXTRACTING RURAL CRASH INJURY AND FATALITY PATTERNS DUE TO CHANGING CLIMATES IN RITI COMMUNITIES BASED ON ENHANCED DATA ANALYSIS AND VISUALIZATION TOOLS (PHASE II)

This report documents the research activities to investigate the traffic crashes in Rural, Isolated, Tribal, or Indigenous (RITI) communities involving considerable incapacitating injuries and fatalities. The traffic crashes occurring in RITI communities, are different from urban traffic crashes, and are related more to the features like speeding, low application of safety devices (for instance, seatbelt), adverse weather conditions and lacking maintenance and repairs for road conditions, and inferior lighting conditions. Thus, it is necessary to study the properties and attributes of traffic crashes at the RITI area using data analysis methods, such as statistical methods, and data-driven methods. This project is trying to analyze the rural crash injury and fatality patterns caused by changing climates in RITI communities based on enhanced data analysis using latest mathematical method. The mixed logit model to examine the risk factors in determining driver injury severity in four crash configurations in two-vehicle rear-end crashes on state roads based on seven-years of data from the Washington State Department of Transportation. The differences between the MLM and the LCM are investigated for exploring the relationships between driver injury severity in the rain-related rural single-vehicle crash and its corresponding risk factors. Moreover, this project develops a latent class mixed logit model with temporal indicators to investigate highway single-vehicle crashes and the effects of significant contributing factors to driver injury severity. The results of this research will be beneficial to transportation agencies to propose effective methods to improve rural crash severities under special climate and weather conditions and minimize the rural crash risks and severities

Unbalanced Circuit-PSI from Oblivious Key-Value Retrieval

Circuit-based Private Set Intersection (circuit-PSI) enables two parties, a client and a server, with their input sets $X$ and $Y$ respectively, to securely compute a function $f$ on the intersection $X \cap Y$, while keeping $X \cap Y$ secret from both parties. Although several computationally efficient circuit-PSI protocols have been proposed recently, they most focus on the balanced scenario where $|X|$ is similar to $|Y|$. However, in many realistic scenarios, a circuit-PSI protocol may be performed in the unbalanced case where $|X|$ is remarkably smaller than $|Y|$ (e.g., the client is a constrained device holding a small set, while the server is a service provider holding a large set). Directly applying existing protocols to this scenario will lead to significant efficiency issues because the communication complexity of the protocols scales at least linearly with the size of the larger set, i.e., $\max(|X|, |Y|)$. In this work, we put forth efficient constructions for unbalanced circuit-PSI with sublinear communication complexity in the size of the larger set. The main insight is that we formalize unbalanced circuit-PSI as obliviously retrieving values corresponding to keys from a set of key-value pairs. To this end, we present a new functionality called Oblivious Key-Value Retrieval (OKVR) and design the OKVR protocol from a new notion called sparse Oblivious Key-Value Stores (sparse OKVS). We conduct extensive experiments and the results show that our constructions remarkably outperform the state-of-the-art circuit-PSI schemes (EUROCRYPT\u2719, PETs\u2722, CCS\u2722), i.e., $1.84 \sim 48.86 \times$ communication improvement and $1.50 \sim39.81 \times$ faster computation. Very recently, Son and Jeong (AsiaCCS\u2723) also present unbalanced circuit-PSI protocols, and our constructions outperform them by $1.18 \sim 15.99 \times$ and $1.22 \sim 10.44 \times$ in communication and computation overhead, respectively, depending on set sizes and network environments

A Quantum Mechanism Study of the C-C Bond Cleavage to Predict the Bio-Catalytic Polyethylene Degradation

The growing amount of plastic solid waste (PSW) is a global concern. Despite increasing efforts to reduce the residual amounts of PSW to be disposed off through segregated collection and recycling, a considerable amount of PSW is still landfilled and the extent of PSW ocean pollution has become a worldwide issue. Particularly, polyethylene (PE) and polystyrene (PS) are considered as notably recalcitrant to biodegradation due to the carbon-carbon backbone that is highly resistant to enzymatic degradation via oxidative reactions. The present research investigated the catalytic mechanism of P450 monooxygenases by quantum mechanics to determine the bio-catalytic degradation of PE or PS. The findings indicated that the oxygenase-induced free radical transition caused the carbon-carbon backbone cleavage of aliphatic compounds. This work provides a fundamental knowledge of the biodegradation process of PE or PS at the atomic level and facilitates predicting the pathway of plastics’ biodegradation by microbial enzymes

Tetraploid cells from cytokinesis failure induce aneuploidy and spontaneous transformation of mouse ovarian surface epithelial cells

Most ovarian cancers originate from the ovarian surface epithelium and are characterized by aneuploid karyotypes. Aneuploidy, a consequence of chromosome instability, is an early event during the development of ovarian cancers. However, how aneuploid cells are evolved from normal diploid cells in ovarian cancers remains unknown. In the present study, cytogenetic analyses of a mouse syngeneic ovarian cancer model revealed that diploid mouse ovarian surface epithelial cells (MOSECs) experienced an intermediate tetraploid cell stage, before evolving to aneuploid (mainly near-tetraploid) cells. Using long-term live-cell imaging followed by fluorescence in situ hybridization (FISH), we demonstrated that tetraploid cells originally arose from cytokinesis failure of bipolar mitosis in diploid cells, and gave rise to aneuploid cells through chromosome mis-segregation during both bipolar and multipolar mitoses. Injection of the late passage aneuploid MOSECs resulted in tumor formation in C57BL/6 mice. Therefore, we reveal a pathway for the evolution of diploid to aneuploid MOSECs and elucidate a mechanism for the development of near-tetraploid ovarian cancer cells

Flux regulation through glycolysis and respiration is balanced by inositol pyrophosphates in yeast

Although many prokaryotes have glycolysis alternatives, it\u27s considered as the only energy-generating glucose catabolic pathway in eukaryotes. Here, we managed to create a hybrid-glycolysis yeast. Subsequently, we identified an inositol pyrophosphatase encoded by OCA5 that could regulate glycolysis and respiration by adjusting 5-diphosphoinositol 1,2,3,4,6-pentakisphosphate (5-InsP7) levels. 5-InsP7 levels could regulate the expression of genes involved in glycolysis and respiration, representing a global mechanism that could sense ATP levels and regulate central carbon metabolism. The hybrid-glycolysis yeast did not produce ethanol during growth under excess glucose and could produce 2.68 g/L free fatty acids, which is the highest reported production in shake flask of Saccharomyces cerevisiae. This study demonstrated the significance of hybrid-glycolysis yeast and determined Oca5 as an inositol pyrophosphatase controlling the balance between glycolysis and respiration, which may shed light on the role of inositol pyrophosphates in regulating eukaryotic metabolism

Drone-Based Computer Vision-Enabled Vehicle Dynamic Mobility and Safety Performance Monitoring

This report documents the research activities to develop a drone-based computer vision-enabled vehicle dynamic safety performance monitoring in Rural, Isolated, Tribal, or Indigenous (RITI) communities. The acquisition of traffic system information, especially the vehicle speed and trajectory information, is of great significance to the study of the characteristics and management of the traffic system in RITI communities. The traditional method of relying on video analysis to obtain vehicle number and trajectory information has its application scenarios, but the common video source is often a camera fixed on a roadside device. In the videos obtained in this way, vehicles are likely to occlude each other, which seriously affects the accuracy of vehicle detection and the estimation of speed. Although there are methods to obtain high-view road video by means of aircraft and satellites, the corresponding cost will be high. Therefore, considering that drones can obtain high-definition video at a higher viewing angle, and the cost is relatively low, we decided to use drones to obtain road videos to complete vehicle detection. In order to overcome the shortcomings of traditional object detection methods when facing a large number of targets and complex scenes of RITI communities, our proposed method uses convolutional neural network (CNN) technology. We modified the YOLO v3 network structure and used a vehicle data set captured by drones for transfer learning, and finally trained a network that can detect and classify vehicles in videos captured by drones. A self-calibrated road boundary extraction method based on image sequences was used to extract road boundaries and filter vehicles to improve the detection accuracy of cars on the road. Using the results of neural network detection as input, we use video-based object tracking to complete the extraction of vehicle trajectory information for traffic safety improvements. Finally, the number of vehicles, speed and trajectory information of vehicles were calculated, and the average speed and density of the traffic flow were estimated on this basis. By analyzing the acquiesced data, we can estimate the traffic condition of the monitored area to predict possible crashes on the highways

Research on technical support SaaS platform of soil pollution control based on the whole process management

In order to improve the effect of soil pollution prevention and control, a technical-support cloud platform is designed to establish a high-level technologies, uniform standards, and regulatory tool for soil environmental investigation, risk assessment and repair work. Firstly, according to the process of soil remediation, combined with the source and pollution characteristics of soil pollutants, the main pollution components in the soil environment were classified and distributed, and then the platform was designed and developed. The system has the functions of project management, query, risk analysis and prediction, drawing, tabulation and so on. Finally, combining with the soil environmental quality standards, the effectiveness and cost indicators of the treatment methods were classified and digitized, which would greatly improve the implementation efficiency and reduce the cost of the project management