Kaposi's Sarcoma Herpesvirus Upregulates Aurora A Expression to Promote p53 Phosphorylation and Ubiquitylation

Aberrant expression of Aurora A kinase has been frequently implicated in many cancers and contributes to chromosome instability and phosphorylation-mediated ubiquitylation and degradation of p53 for tumorigenesis. Previous studies showed that p53 is degraded by Kaposi's sarcoma herpesvirus (KSHV) encoded latency-associated nuclear antigen (LANA) through its SOCS-box (suppressor of cytokine signaling, LANASOCS) motif-mediated recruitment of the EC5S ubiquitin complex. Here we demonstrate that Aurora A transcriptional expression is upregulated by LANA and markedly elevated in both Kaposi's sarcoma tissue and human primary cells infected with KSHV. Moreover, reintroduction of Aurora A dramatically enhances the binding affinity of p53 with LANA and LANASOCS-mediated ubiquitylation of p53 which requires phosphorylation on Ser215 and Ser315. Small hairpin RNA or a dominant negative mutant of Aurora A kinase efficiently disrupts LANA-induced p53 ubiquitylation and degradation, and leads to induction of p53 transcriptional and apoptotic activities. These studies provide new insights into the mechanisms by which LANA can upregulate expression of a cellular oncogene and simultaneously destabilize the activities of the p53 tumor suppressor in KSHV-associated human cancers

Triboelectric Nanogenerators in Sustainable Chemical Sensors

The rapid development of sensing technology has created an urgent need for chemical sensor systems that can be rationally integrated into efficient, sustainable, and wearable electronic systems. In this case, the triboelectric nanogenerator (TENG) is expected to be a major impetus to such innovation because it can not only power the sensor by scavenging mechanical energies and transforming them into electricity but also act as the chemical sensor itself due to its intrinsic sensitivity towards the chemical reaction that occurs at the triboelectric interface. In this review, recent research achievements of chemical sensors that are based on TENGs are comprehensively reviewed according to the role of TENGs in the system, that is, pure power supplies or self-powered active chemical sensors. Focus is put on discussing the design criteria and practical applications of the TENG-based active sensors in different fields, which is unfolded with a classification that includes biosensors, gas sensors, and ion sensors. The materials selection, working mechanism, and design strategies of TENG-based active chemical sensor systems (CSSs) are also discussed, ending with a concise illustration of the key challenges and possible corresponding solutions. We hope this review will bring inspiration for the creation and development of TENG-based chemical sensors with higher sensitivity, simpler structure, and enhanced reliability

A New Disturbance Feedforward Control Method for Electro-Optical Tracking System Line-Of-Sight Stabilization on Moving Platform

A feedforward control was proposed based on the decoupling of target movement and disturbance from gyro signals to improve the stabilization precision of line-of-sight (LOS) for an electro-optical tracking system (EOTS) on a moving platform. Signals measured by gyros mounted on gimbal consist of target movement and disturbance. To remove target movement and obtain middle and high frequency disturbance velocity, the gyro signals were filtered by a high pass filter. The disturbance velocity was integrated into the position signal and fed forward to the inner position loop of the fast steering mirror. A detailed analysis was provided to show the proposed approach, to improve disturbance suppression performance with only slight weakening of target tracking ability. The proposed feedforward control was effectively verified through a series of comparative simulations and experiments. Besides, the method was applied in a real ship-based project

Triboelectric Nanogenerators in Sustainable Chemical Sensors

The rapid development of sensing technology has created an urgent need for chemical sensor systems that can be rationally integrated into efficient, sustainable, and wearable electronic systems. In this case, the triboelectric nanogenerator (TENG) is expected to be a major impetus to such innovation because it can not only power the sensor by scavenging mechanical energies and transforming them into electricity but also act as the chemical sensor itself due to its intrinsic sensitivity towards the chemical reaction that occurs at the triboelectric interface. In this review, recent research achievements of chemical sensors that are based on TENGs are comprehensively reviewed according to the role of TENGs in the system, that is, pure power supplies or self-powered active chemical sensors. Focus is put on discussing the design criteria and practical applications of the TENG-based active sensors in different fields, which is unfolded with a classification that includes biosensors, gas sensors, and ion sensors. The materials selection, working mechanism, and design strategies of TENG-based active chemical sensor systems (CSSs) are also discussed, ending with a concise illustration of the key challenges and possible corresponding solutions. We hope this review will bring inspiration for the creation and development of TENG-based chemical sensors with higher sensitivity, simpler structure, and enhanced reliability

Characterization of Two New Apodemus Mitogenomes (Rodentia: Muridae) and Mitochondrial Phylogeny of Muridae

Apodemus is the most common small rodent species in the Palearctic realm and an ideal species for biogeographical research and understanding environmental changes. Elucidating phylogenetic relationships will help us better understand species adaptation and genetic evolution. Due to its stable structure, maternal inheritance, and rapid evolution, the mitogenome has become a hot spot for taxonomic and evolutionary studies. In this research, we determined the mitochondrial genome of Apodemus agrarius ningpoensis and Apodemus draco draco and studied the phylogeny of Muridae using ML and BI trees based on all known complete mitogenomes. The mitochondrial genome of Apodemus agrarius ningpoensis was 16,262 bp, whereas that of Apodemus draco draco was 16,222 bp, and both encoded 13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA genes. Analysis of base composition showed a clear A-T preference. All tRNAs except tRNASer and tRNALys formed a typical trilobal structure. All protein-coding genes contained T- and TAA as stop codons. Phylogeny analysis revealed two main branches in the Muridae family. Apodemus agrarius ningpoensis formed sister species with Apodemus chevrieri, whereas Apodemus draco draco with Apodemus latronum. Our findings provide theoretical basis for future studies focusing on the mitogenome evolution of Apodemus

Multiple adaptive factors based interacting multiple model estimator

Abstract In the field of optoelectronic tracking, precisely modeling the motion equations of the tracked target is often challenging, and in some cases, they may even be entirely unknown. This necessitates the use of a robust state estimator for accurate state estimation. Additionally, atmospheric turbulence, variations in illumination, and intricate observation backgrounds may introduce a significant increase in observation noise for the tracked target. To address these challenges, one approach is to introduce adaptive factors, such as the Mahalanobis method, into the robust state estimator to enhance estimation accuracy. However, further exploration has revealed that adaptive factors designed using different methods offer unique advantages in scenarios with varying levels of noise amplification. In this paper, different adaptive factors are further combined using an interacting multiple model approach, allowing the designed state estimator to exhibit stronger adaptability to noise amplification. The stability and effectiveness of this algorithm are validated through program simulations, double reflection mirror experiment, and drone trace prediction, demonstrating its applicability and reliability in diverse scenarios

Characterization of Two New <i>Apodemus</i> Mitogenomes (Rodentia: Muridae) and Mitochondrial Phylogeny of Muridae

Apodemus is the most common small rodent species in the Palearctic realm and an ideal species for biogeographical research and understanding environmental changes. Elucidating phylogenetic relationships will help us better understand species adaptation and genetic evolution. Due to its stable structure, maternal inheritance, and rapid evolution, the mitogenome has become a hot spot for taxonomic and evolutionary studies. In this research, we determined the mitochondrial genome of Apodemus agrarius ningpoensis and Apodemus draco draco and studied the phylogeny of Muridae using ML and BI trees based on all known complete mitogenomes. The mitochondrial genome of Apodemus agrarius ningpoensis was 16,262 bp, whereas that of Apodemus draco draco was 16,222 bp, and both encoded 13 protein-coding genes, 2 ribosomal RNA genes, and 22 transfer RNA genes. Analysis of base composition showed a clear A-T preference. All tRNAs except tRNASer and tRNALys formed a typical trilobal structure. All protein-coding genes contained T- and TAA as stop codons. Phylogeny analysis revealed two main branches in the Muridae family. Apodemus agrarius ningpoensis formed sister species with Apodemus chevrieri, whereas Apodemus draco draco with Apodemus latronum. Our findings provide theoretical basis for future studies focusing on the mitogenome evolution of Apodemus

Extended State Kalman Filter-Based Model Predictive Control for Electro-Optical Tracking Systems with Disturbances: Design and Experimental Verification

A modified Extended State Kalman Filter (ESKF)-based Model Predictive Control (MPC) algorithm is introduced to tailor the enhanced disturbance suppression in electro-optical tracking systems. Traditional control techniques, although robust, often struggle in scenarios with concurrent internal, external disturbances, and sensor noise. The proposed algorithm effectively overcomes these limitations by precisely estimating system states and actively mitigating disturbances, thus significantly boosting noise and perturbation control resilience. The primary contributions of this study include the integration of ESKF for accurate system state and disturbance estimation in noisy environments, the embedding of an ESKF estimation-compensation loop to simulate an improved disturbance-free system, and a simplified modeling approach for the controlled device. This designed structure minimizes the reliance on extensive system identification, easing the predictive control model-based constraints. Moreover, the approach incorporates total disturbance estimation into the optimization problem, safeguarding against actuator damage and ensuring high tracking accuracy. Through rigorous simulations and experiments, the ESKF-based MPC has demonstrated enhanced model error tolerance and superior disturbance suppression capabilities. Comparative analyses under varying model parameters and external disturbances highlight its exceptional trajectory tracking performance, even in the presence of model uncertainties and external noise

A Non-Interactive Attribute-Based Access Control Scheme by Blockchain for IoT

As an important method of protecting data confidentiality in the Internet of Things (IoT), access control has been widely concerned. Because attribute-based access control mechanisms are dynamic, it is not only suitable to solve the dynamic access problem in IoT, but also to deal with the dynamic caused by node movement and access data change. The traditional centralized attribute-based access control mechanism has some problems: due to the large number of devices in IoT, the central trusted entity may become the bottleneck of the whole system. Moreover, when a central trusted entity is under distributed denial-of-service (DDoS) attack, the entire system may crash. Blockchain is a good way to solve the above problems. Therefore, we developed a non-interactive, attribute-based access control scheme that applies blockchain technology in IoT scenarios by using PSI technology. In addition, the attributes of data user and data holder are hidden, which protects the privacy of both parties’ attributes and access policy. Furthermore, the experimental results indicate that our scheme has high efficiency

Modular Design in Triboelectric Sensors: A Review on the Clinical Applications for Real-Time Diagnosis

Triboelectric nanogenerators (TENGs) have garnered considerable interest as a promising technology for energy harvesting and stimulus sensing. While TENGs facilitate the generation of electricity from micro-motions, the modular design of TENG-based modular sensing systems (TMSs) also offers significant potential for powering biosensors and other medical devices, thus reducing dependence on external power sources and enabling biological processes to be monitored in real time. Moreover, TENGs can be customised and personalized to address individual patient needs while ensuring biocompatibility and safety, ultimately enhancing the efficiency and security of diagnosis and treatment. In this review, we concentrate on recent advancements in the modular design of TMSs for clinical applications with an emphasis on their potential for personalised real-time diagnosis. We also examine the design and fabrication of TMSs, their sensitivity and specificity, and their capabilities of detecting biomarkers for disease diagnosis and monitoring. Furthermore, we investigate the application of TENGs to energy harvesting and real-time monitoring in wearable and implantable medical devices, underscore the promising prospects of personalised and modular TMSs in advancing real-time diagnosis for clinical applications, and offer insights into the future direction of this burgeoning field