Abstract Background Breast cancer (BRCA) remains one of the most frequently diagnosed malignancies and a leading cause of cancer-related mortality among women worldwide. Its molecular heterogeneity and limited therapeutic options for aggressive subtypes highlight the need for novel treatment strategies. Drug repositioning offers a promising approach by identifying new therapeutic uses for existing drugs with established safety profiles. Methods We applied an integrative transcriptomic and bioinformatics framework to identify candidate drug targets and repurposed drugs for BRCA. Differentially expressed genes (DEGs) were identified from four Gene Expression Omnibus (GEO) microarray datasets using the limma package with thresholds of |log2 fold change| > 1 and false discovery rate (FDR) < 0.05. Overlapping DEGs were expanded through protein–protein interaction analysis using the STRING database. Functional annotation across ten biological evidence categories was performed using WebGestalt to prioritize BRCA risk genes through a multi-criteria scoring approach. Drug–gene interactions were then analyzed using the Drug–Gene Interaction Database (DGIdb), and tissue-specific gene expression was evaluated using the GTEx database. Results Twenty-eight consistently dysregulated genes were identified and expanded into a 77-gene interaction network. Functional prioritization yielded 18 BRCA risk genes, including five druggable targets associated with 11 candidate drugs. ITGB7 emerged as a promising biomarker and therapeutic target, with vedolizumab identified as the top candidate drug. Conclusions This study highlights the potential of integrative transcriptomic analysis to identify biomarkers and drug repositioning candidates in BRCA, providing a foundation for further experimental validation.
This work of literature critically reflects on what appeared to be rude yet tactical communication styles by Islamic preachers on online platforms. This article, on the one hand, employs an integrated theoretical approach that integrates the Quranic communication ethics with pragmatics, critical discourse analysis (CDA) and politeness theory to understand how deviant practices of the classical Islamic communication norms are pragmatically used to forge solidarity, emotional closeness and authenticity of da’wah within a modern digital setting. This article, after studying the speech of well-known digital preachers in detail, demonstrates that strategic impropriety is not merely an ethical offense but a rhetorical maneuver for renegotiating religious authority in the online community. Based on the concept of qaulan in the Quran, this research provides a normative Islamic approach to the development of da’wah communication styles and to the relationships among politeness, pragmatic effectiveness and social relevance in the development of authority and audience interest in the digital world.
Frequency control in isolated hybrid microgrids is an emerging field. The present work investigates the theoretical background and practical applications of adaptive controllers. These controllers are optimized using the Harris Hawks optimization algorithm modified with the balloon effect (HHO + BE), ensuring high precision and adaptability. The hybrid microgrid configuration includes photovoltaic (PV) systems, electric vehicles (EVs), and heat pumps (HPs), all coordinated with the diesel generator to act as flexible resources during disturbances. Full-scale simulations were performed in MATLAB/Simulink to assess the system response under different disturbance scenarios. The findings confirm that the proposed optimized controller outperforms traditional controller and existing metaheuristic-based techniques, providing significantly less frequency deviation and faster recovery times. In addition to the technical performance analysis, an economic and environmental analysis was conducted based on 1000 h of annual corrective operation. The results are striking: the proposed system reduces diesel consumption by approximately 95%, resulting in an estimated annual savings of $4.86 million with a significant reduction in emissions. This highlights the controller's dual advantage of stabilizing the grid and promoting sustainability.
High-performance computing (HPC) systems consume enormous amounts of energy, with idle nodes as a major source of energy waste. Powering down idle nodes can mitigate this problem, but long boot/shutdown delays can introduce significant queueing penalties if transitions are poorly timed. To address this trade-off, we present SPARS, a reinforcement learning-enabled simulator for power management in HPC job scheduling. SPARS integrates job scheduling and node power-state management within a discrete-event simulation framework. It supports traditional scheduling policies such as First Come First Serve and EASY Backfilling, along with enhanced variants that employ reinforcement learning agents to dynamically decide when nodes should be powered on or off. Users can configure workloads and platforms in JSON format, specifying job arrivals, execution times, node power models, and transition delays. The simulator records comprehensive metrics—including energy usage, wasted power, job waiting times, and node utilization—and provides Gantt chart visualizations to analyze scheduling dynamics and power transitions. Unlike widely used Batsim-based frameworks that rely on heavy inter-process communication, SPARS provides lightweight event handling and consistent simulation results, making experiments easier to reproduce and extend. Its modular design allows new scheduling heuristics or learning algorithms to be integrated with minimal effort. By providing a flexible, reproducible, and extensible platform, SPARS enables researchers and practitioners to systematically evaluate power-aware scheduling strategies, explore the trade-offs between energy efficiency and performance, and accelerate the development of sustainable HPC operations.
This study presents a comprehensive evaluation of bi-refiorming of methane (BRM), combining bibliometric analysis (2019-mid-2024) with a technical review of thermodynamics, mechanisms, and catalyst design. Bibliometric mapping revealed a significant research gap regarding the dual role of bimetallic species in active sites and supports. Specifically, there is a lack of systematic reviews addressing the dual role of bimetallic species and supports. Technical review confirms BRM feasibility at high temperatures, identifying CH4 activation and oxygen dynamics as the rate-controlling step. The catalytic review demonstrates that bimetallic catalysts and doped supports enhance active-site dispersion, oxygen storage and mobility, and coke resistance compared with monometallic systems, yielding improved activity and stability. This work advocates for consistent reporting of performance metrics (conversion, H2/CO, carbon deposition rate, time-on-stream). By bridging bibliometric trends with technical insights, this work provide roadmap in the development of a more stable, sustainable catalyst system for efficient syngas production.
