Search Results (41,517)

Breast cancer (BC) is a widespread malignancy that affects the lives of millions of women each year, and its resulting financial and healthcare hardships cannot be overstated. These issues, in combination with side effects and obstacles associated with the current standard of care, generate considerable interest in new potential targets for treatment as well as means for BC prevention. One potential preventive compound is Withaferin A (WFA), a traditional medicinal compound found in winter cherries. WFA has shown promise as an anticancer agent and is thought to act primarily through its effects on the epigenome, including, in particular, the methylome. However, the relative importance of specific genes’ methylation states to WFA function remains unclear. To address this, we utilized human BC cell lines in combination with CRISPR-dCas9 fused to DNA methylation modifiers (i.e., epigenetic editors) to elucidate the importance of specific genes’ promoter methylation states to WFA function and cancer cell viability. We found that targeted demethylation of promoters of the tumor suppressors p21 and p53 within MDA-MB-231/MCF7 cells resulted in around 1.7×/1.5× and 1.2×/1.3× increases in expression, respectively. Targeted methylation of the promoter of the oncogene CCND1 within MDA-MB-231/MCF7 cells resulted in 0.5×/0.8× decreases in gene expression. These changes to p21, p53, and CCND1 were also associated with decreases in cell viability of around 25%/50%, 5%/35%, and 12%/16%, respectively, for MDA-MB-231/MCF7 cells. When given in combination with WFA in both p53 mutant and wild type cells, we discovered that targeted methylation of the p21 promoter was able to modulate the anticancer effects of WFA, while targeted methylation or demethylation of the promoters of p53 and CCND1 had no significant effect on viability decreases from WFA treatment. Taken together, these results indicate that p21, p53, and CCND1 may be important targets for future in vivo studies that may lead to epigenetic editing therapies and that WFA may have utility in the prevention of BC through its effect on p21 promoter methylation independent of p53 function. Full article

Collision avoidance and path planning are critical topics in autonomous vehicle development. This paper presents the progressive development of an optimization-based controller for autonomous vehicles using the Control Lyapunov Function–Control Barrier Function–Quadratic Programming (CLF-CBF-QP) approach. This framework enables a vehicle to navigate to its destination while avoiding obstacles. A unicycle model is utilized to incorporate vehicle dynamics. A series of simulations were conducted, starting with basic model-in-the-loop (MIL) non-real-time simulations, followed by real-time simulations. Multiple scenarios with different controller configurations and obstacle setups were tested, demonstrating the effectiveness of the proposed controllers in avoiding collisions. Real-time simulations in Simulink were used to demonstrate that the proposed controller could compute control actions for each state within a very short timestep, highlighting its computational efficiency. This efficiency underscores the potential for deploying the controller in real-world vehicle autonomous driving systems. Furthermore, we explored the feasibility of a hierarchical control framework comprising deep reinforcement learning (DRL), specifically a Deep Q-Network (DQN)-based high-level controller and a CLF-CBF-QP-based low-level controller. Simulation results show that the vehicle could effectively respond to obstacles and generate a successful trajectory towards its goal. Full article

Airborne magnetic anomaly detection is an important passive remote sensing technique. However, since the magnetic field caused by the aircraft interferes with the detection accuracy, this part of interference should be eliminated by an aeromagnetic compensation method. Most existing compensation methods assume that the ambient magnetic field is uniform when calculating the compensation model parameters. However, as the ambient magnetic field is actually not uniform and varies with the aircraft location, the solved parameters ignore the part of aircraft interference related to the varied ambient magnetic field. Although some of the latest deep learning-based aeromagnetic compensation methods avoid the assumption of uniformity of the ambient magnetic field, the insufficient supervision leads to a poor model generalization. To address these limitations, we propose a self-supervised compensation method. The proposed method utilizes a network to separate the total measured magnetic field into the ambient magnetic field part and the aircraft magnetic field part. By doing so, the method avoids the influence of the uniform ambient magnetic field assumption and enhances the model generalization. In addition, we introduce an improvement ratio loss function to distinguish the aircraft magnetic field from the ambient magnetic field when updating the model parameters. The proposed method is verified using measurement data from real flights. The experimental results indicate that the proposed method significantly outperforms state-of-the-art methods in real flights compensation. Full article

The structural and functional integrity of the retinal pigment epithelium (RPE) plays a key role in the normal functioning of the visual system. RPE cells are characterized by an efficient system of photoreceptor outer segment phagocytosis, high metabolic activity, and risk of oxidative damage. RPE dysfunction is a common pathological feature in various retinal diseases. Dysregulation of RPE cell proteostasis and redox homeostasis is accompanied by increased reactive oxygen species generation during the impairment of phagocytosis, lysosomal and mitochondrial failure, and an accumulation of waste lipidic and protein aggregates. They are the inducers of RPE dysfunction and can trigger specific pathways of cell death. Autophagy serves as important mechanism in the endogenous defense system, controlling RPE homeostasis and survival under normal conditions and cellular responses under stress conditions through the degradation of intracellular components. Impairment of the autophagy process itself can result in cell death. In this review, we summarize the classical types of oxidative stress-induced autophagy in the RPE with an emphasis on autophagy mediated by molecular chaperones. Heat shock proteins, which represent hubs connecting the life supporting pathways of RPE cells, play a special role in these mechanisms. Regulation of oxidative stress-counteracting autophagy is an essential strategy for protecting the RPE against pathological damage when preventing retinal degenerative disease progression. Full article

This study proposes a design procedure for the multi-objective aeroelastic optimization of a tow-steered composite wing structure that operates at transonic speed. The aerodynamic influence coefficient matrix is generated using the doublet lattice method, with the steady-state component further refined through high-fidelity computational fluid dynamics (CFD) analysis to enhance accuracy in transonic conditions. Finite element analysis (FEA) is used to perform structural analysis. A multi-objective transonic aeroelastic optimization problem is formulated for the tow-steered composite wing structure, where the objective functions are designed for mass and critical speed, and the design constraints include structural and aeroelastic limits. A comparative analysis of eight state-of-the-art algorithms is conducted to evaluate their performance in solving this problem. Among them, the Multi-Objective Multi-Verse Optimization (MOMVO) algorithm stands out, demonstrating superior performance and achieving the best results in the aeroelastic optimization task. Full article

The optimization of pumping station inlet channels is a key research area for improving the operation efficiency, reducing the energy consumption, and enhancing the operation reliability of pumping stations. For the elbow inlet channel of the Majinggang Pumping Station project, based on the Stress-Blended Eddy Simulation (SBES) turbulence model and entropy generation theory, an optimization design plan is proposed by altering the inclination angle of the flow channel base plate, the length of the transitional arc segment, and the length of the curved segment. Various schemes were analyzed and comprehensively compared in terms of the hydraulic loss, the velocity-weighted average angle, and the axial-velocity distribution uniformity of the channel. The results indicate that optimal hydraulic performance is achieved when the inclination angle of the base plate is between 8° and 10°. In a reasonable range of values, appropriately increasing the length of the transitional arc and reducing the section width (throat width) can improve the hydraulic performance of the inlet channel. The optimal model obtained achieved an impressive velocity-weighted average angle of 89.25°, along with an axial-velocity distribution uniformity of 97.5%. Its excellent hydraulic performance not only meets the design requirements of the pumping station in terms of functionality but also takes into account economic efficiency, and it serves as a valuable reference for similar projects, contributing to the more refined and intelligent development of the optimization of pumping station inlet flow channels. Full article

Mapping agricultural fields using high-resolution satellite imagery and deep learning (DL) models has advanced significantly, even in regions with small, irregularly shaped fields. However, effective DL models often require large, expensive labeled datasets, which are typically limited to specific years or regions. This restricts the ability to create annual maps needed for agricultural monitoring, as changes in farming practices and environmental conditions cause domain shifts between years and locations. To address this, we focused on improving model generalization without relying on yearly labels through a holistic approach that integrates several techniques, including an area-based loss function, Tversky-focal loss (TFL), data augmentation, and the use of regularization techniques like dropout. Photometric augmentations helped encode invariance to brightness changes but also increased the incidence of false positives. The best results were achieved by combining photometric augmentation, TFL, and Monte Carlo dropout, although dropout alone led to more false negatives. Input normalization also played a key role, with the best results obtained when normalization statistics were calculated locally (per chip) across all bands. Our U-Net-based workflow successfully generated multi-year crop maps over large areas, outperforming the base model without photometric augmentation or MC-dropout by 17 IoU points. Full article

Medical Internet of Things (IoT) systems can be used to monitor and treat patient health conditions. Security and privacy issues in medical IoT services are more important than those in any other IoT-enabled service. Therefore, various mutual authentication and key-distribution schemes have been proposed for secure communication in medical IoT services. We analyzed Hu et al.’s scheme and found that an attacker can impersonate legitimate sensor nodes and generate illegitimate session keys using the information stored in the sensor node and the information transmitted over the public channel. To overcome these vulnerabilities, we propose a scheme that utilizes physically unclonable functions to ensure a secure session key distribution and increase the computational efficiency of resource-limited sensor nodes. In addition, the proposed scheme enhances privacy protection using pseudonyms, which we prove using a formal security analysis tool, ProVerif 2.05. Full article

Utilizing LiDAR sensors mounted on unmanned aerial vehicles (UAVs) to acquire three-dimensional data of fruit orchards and extract precise information about individual trees can greatly facilitate unmanned management. To address the issue of low accuracy in traditional watershed segmentation methods based on canopy height models, this paper proposes an enhanced method to extract individual tree crowns in fruit orchards, enabling the improved detection of overlapping crown features. Firstly, a distribution curve of single-row or single-column treetops is fitted based on the detected treetops using variable window size. Subsequently, a cubic spatial region extending infinitely along the Z-axis is generated with equal width around this curve, and all crown points falling within this region are extracted and then projected onto the central plane. The projecting contour of the crowns on the plane is then fitted using Gaussian functions. Treetops are detected by identifying peak points on the curve fitted by Gaussian functions. Finally, the watershed algorithm is applied to segment fruit tree crowns. The results demonstrate that in citrus orchards with pronounced crown overlap, this novel method significantly reduces the number of undetected trees with a precision of 97.04%, and the F1 score representing the detection accuracy for fruit trees reaches 98.01%. Comparisons between the traditional method and the Gaussian fitting–watershed fusion algorithm across orchards exhibiting varying degrees of crown overlap reveal that the fusion algorithm achieves high segmentation accuracy when dealing with overlapping crowns characterized by significant height variations. Full article

Four classes of multiple symmetric sums over cyclic products of binomial coefficients are examined. By incorporating the generating function approach and recursive construction method, they are expressed analytically as coefficients of rational functions. Several recurrence relations and generating functions are explicitly determined when the dimension of the multiple sums does not exceed five. Full article

Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting women of reproductive age characterized by a spectrum of clinical, metabolic, reproductive, and psychological abnormalities. This syndrome is associated with significant long-term health risks, necessitating elucidation of its pathophysiology, early diagnosis, and comprehensive management strategies. Several contributory factors in PCOS, including androgen excess and insulin resistance, collectively enhance oxidative stress, which subsequently leads to mitochondrial dysfunction. However, the precise mechanisms through which oxidative stress induces mitochondrial dysfunction remain incompletely understood. Comprehensive searches of electronic databases were conducted to identify relevant studies published up to 30 September 2024. Mitochondria, the primary sites of reactive oxygen species (ROS) generation, play critical roles in energy metabolism and cellular homeostasis. Oxidative stress can inflict damage on components, including lipids, proteins, and DNA. Damage to mitochondrial DNA (mtDNA), which lacks efficient repair mechanisms, may result in mutations that impair mitochondrial function. Dysfunctional mitochondrial activity further amplifies ROS production, thereby perpetuating oxidative stress. These disruptions are implicated in the complications associated with the syndrome. Advances in genetic analysis technologies, including next-generation sequencing, have identified point mutations and deletions in mtDNA, drawing significant attention to their association with oxidative stress. Emerging data from mtDNA mutation analyses challenge conventional paradigms and provide new insights into the role of oxidative stress in mitochondrial dysfunction. We are rethinking the pathogenesis of PCOS based on these database analyses. In conclusion, this review explores the intricate relationship between oxidative stress, mtDNA mutations, and mitochondrial dysfunction, offers an updated perspective on the pathophysiology of PCOS, and outlines directions for future research. Full article

Technology has increasingly influenced the provision of healthcare services by enhancing patient safety, optimising workflows, and improving efficiency. Large healthcare facilities have adopted automated dispensing cabinets (ADCs) as an advanced technological solution. A key gap exists in understanding the ADC implementation experience in different contexts. Therefore, this study seeks to fill this literature gap by exploring key stakeholders’ perspectives on the benefits, barriers, and improvement opportunities related to ADCs, offering valuable insights to support their effective integration across various healthcare settings. This qualitative study was conducted in Saudi Arabia. The implementation of ADCs generally has positive outcomes for all staff. The system has brought about enhanced medication tracking, greater time efficiency, along with reduced workload and medication errors. However, there are barriers to their implementation, including changes in workflow and workload distribution, cabinet design, technical medication management challenges, and the need for staff training. To maximise the effectiveness of ADCs, healthcare organisations should focus on improving operational workflows, providing ongoing staff training, and maintaining robust system monitoring. Additionally, manufacturers should focus on advancing technology to further enhance the efficiency and functionality of ADCs. Full article

Upper Kuskokwim (Athabaskan, Alaska) is a polysynthetic language with morphologically complex verbs involving pronominal affixes denoting clause arguments. One goal of this paper is to see how clauses in this kind of language are organized and operate in conversational discourse. This study is based on a dataset of transcribed conversations, arranged as sequences of elementary discourse units. The issues explored in this article include the structure of clauses, their functioning in discourse, the composition and expression of clause arguments and other participants, as well as an assessment of more and less typical clauses. I find that clauses are strongly aligned with elementary discourse units; that there is a preference for verb-centered, independent, and one-place clauses; and that lexically expressed arguments are rare. Overall, the clause is a viable notion for the description of Upper Kuskokwim conversational discourse. The specifics of clause structure and clause functioning in Upper Kuskokwim can be explained by a combination of general principles of discourse production and the typological features of the language. Full article

With the increase of extreme weather events caused by global climate change, the issue of power system resilience has become more and more important. Traditional power system management methods cannot cope with dynamic real-time changes, and it is difficult to effectively predict and respond to potential failures caused by extreme weather. To this end, this paper proposes a real-time power system optimization method based on the Smart “Predict, then Optimize” (SPO) framework. The SPO method first uses the Transformer model to predict, in real time, the future line damage states and then dynamically adjusts the optimization strategy based on the prediction results. This method can efficaciously enhance the prediction accuracy of faulty lines under extreme weather conditions and optimize generation scheduling, load management, as well as EV battery scheduling to minimize the system cost. This study proposes a solution based on the SPO loss function, artificial intelligence prediction model, and bi-level optimization model to address the dynamic optimization of power systems under extreme conditions, significantly enhancing the system’s response to extreme weather events. The experimental results demonstrate that the SPO method can optimize system operation in real time, significantly reducing load shedding and total system cost during typhoon weather, which not only improves the system’s economic efficiency but also effectively enhances power system resilience. Full article

OFD1 is a protein involved in many cellular processes, including cilia biogenesis, mitotic spindle assembly, translation, autophagy and the repair of double-strand DNA breaks. Despite many potential interactors identified in high-throughput studies, only a few have been directly confirmed with their binding sites identified. We performed an analysis of the evolutionary conservation of the OFD1 sequence in three clades: 80 Tetrapoda, 144 Vertebrata or 26 Animalia species, and identified 59 protein-binding motifs localized in the OFD1 regions conserved in various clades. Our results indicate that OFD1 contains 14 potential post-translational modification (PTM) sites targeted by at least eight protein kinases, seven motifs bound by proteins recognizing phosphorylated aa residues and a binding site for phosphatase 2A. Moreover, OFD1 harbors both a motif that enables its phosphorylation by mitogen-activated protein kinases (MAPKs) and a specific docking site for these proteins. Generally, our results suggest that OFD1 forms a scaffold for interaction with many proteins and is tightly regulated by PTMs and ligands. Future research on OFD1 should focus on the regulation of OFD1 function and localization. Full article