Plants encounter various stresses in their natural environments and can effectively respond to only one stress at a time. Through a complex gene network, transcription factors (TFs) such as WRKY TFs regulate a diverse array of stress responses. The clarification of the structural characteristics of WRKY proteins, along with recent advancements in molecular dynamics simulations, has shed light on the formation, stability, and interactions of DNA–protein complexes. This has provided a novel viewpoint regarding the control of WRKY TFs. The investigation of superfamilies, encompassing their historical development, diversity, and evolutionary patterns, has become feasible due to the transcriptome approach’s capacity to provide extensive and comprehensive transcripts. The significance of WRKY TFs lies in their pivotal role within several signaling cascades and regulatory networks that influence plant defense responses. The present review summarizes the functional aspects of the high-volume sequence data of WRKY TFs from different species studied to date. Moreover, a comparative analysis approach was utilized to determine the functions of the identified WRKY TFs in response to both abiotic and biotic stresses, as revealed through numerous studies on different plant species. The results of this review will be pivotal in understanding evolutionary events and the significance of WRKY TFs in the context of climate change, incorporating new scientific evidence to propose an innovative viewpoint.

Background/Objectives: Artificial intelligence is rapidly permeating the field of psychiatry. It offers novel avenues for the diagnosis, treatment, and prediction of mental health disorders. This structured review aims to consolidate current approaches to the application of AI in telepsychiatry. In addition, it evaluates their technological maturity, clinical utility, and ethical–legal robustness. Methods: A systematic search was conducted across the PubMed, Scopus, and Google Scholar databases for the period spanning 2015 to 2025. The selection and analysis processes adhered to the PRISMA 2020 guidelines. The final synthesis included 44 publications, among which 14 were empirical studies encompassing a broad spectrum of algorithmic approaches—ranging from neural networks and natural language processing (NLP) to multimodal architectures. Results: The review revealed a wide array of AI applications in telepsychiatry, encompassing automated diagnostics, therapeutic support, predictive modeling, and risk stratification. The most actively employed techniques include natural language and speech processing, multimodal analysis, and advanced forecasting models. However, significant barriers to implementation persist—ethical (threats to autonomy and risks of algorithmic bias), technological (limited generalizability and a lack of explainability), and legal (ambiguous accountability and weak regulatory frameworks). Conclusions: This review underscores a growing disconnect between the rapid evolution of AI technologies and the institutional maturity of tools suitable for scalable clinical integration. Despite notable technological advances, the clinical adoption of AI in telepsychiatry remains limited. The analysis identifies persistent methodological gaps and systemic barriers that demand coordinated efforts across research, technical, and regulatory communities. It also outlines key directions for future empirical studies and interdisciplinary development of implementation standards.

The growing demand for sustainable and high-performance materials has positioned cellulose as a key biopolymer for next-generation functional systems. Beyond its traditional use, cellulose undergoes a qualitative transformation at the nanoscale, where increased surface area, interfacial dominance, and tunable chemistry enable functions unattainable in bulk form. This review provides a critical and integrative analysis of functionalization strategies governing the transition from structural modification to application-specific performance in cellulose and nanocellulose-based materials. A unified structure–property–function–process (SPFP) framework is introduced to systematically connect modification approaches with resulting structural features, physicochemical properties, and functional outcomes. Chemical, physical, and surface/interface modification strategies are comparatively evaluated with respect to their efficiency, scalability, and environmental trade-offs. Rather than cataloguing methods, the review emphasizes cross-domain synthesis and identifies key limitations, including high energy demand, reagent consumption, structural instability, and challenges in large-scale implementation. Particular attention is given to applications in biomedicine, environmental remediation, and energy technologies, where performance is governed by surface reactivity, accessibility, and hierarchical organization. The analysis highlights that no single modification strategy is universally optimal, and that effective material design requires balancing performance, sustainability, and process feasibility. By integrating conceptual frameworks, comparative analysis, and emerging design principles, this review provides a forward-looking perspective on the development of cellulose-based functional materials, supporting their transition from laboratory-scale demonstrations to application-ready technologies.

The problems associated with the advancement of technology and the environment are growing more complicated in recent years. Wildfires are one of the most important environmental challenges since they seriously endanger the world's ecosystems. There are many different types of damage done to forests, which result in both climate change and the devastation of terrestrial ecosystems. Consequently, the implementation of efficient strategies for early warning, prevention, the efficacy of ecological methods like fuel management strategies and green fire barriers in preventing wildfires and well-coordinated treatments is necessary to lessen their impact on both people and the environment. This overview examines the development of several technologies from previous years to the present with the purpose of detecting, tracking, and preventing forest fires. It draws attention to the advantages, restrictions, and potential advancements in this field of research. Because of their catastrophic effects on ecosystems and potential consequences on the climate, forest fires have become a major environmental concern. To create more potent plans for preventing and controlling wildfires, our research demonstrated the necessity for significant advancements in ecological methods, technological breakthroughs, and community involvement to strengthen wildfire preservation efforts.