Potential Therapeutic Implications of Caffeic Acid in Cancer Signaling: Past, Present, and Future

Caffeic acid (CA) has been present in many herbs, vegetables, and fruits. CA is a bioactive compound and exhibits various health advantages that are linked with its anti-oxidant functions and implicated in the therapy and prevention of disease progression of inflammatory diseases and cancer. The anti-tumor action of CA is attributed to its prooxidant and anti-oxidant properties. CA’s mechanism of action involves preventing reactive oxygen species formation, diminishing the angiogenesis of cancer cells, enhancing the tumor cells’ DNA oxidation, and repressing MMP-2 and MMP-9. CA and its derivatives have been reported to exhibit anti-carcinogenic properties against many cancer types. CA has indicated low intestinal absorption, low oral bioavailability in rats, and pitiable permeability across Caco-2 cells. In the present review, we have illustrated CA’s therapeutic potential, pharmacokinetics, and characteristics. The pharmacological effects of CA, the emphasis on in vitro and in vivo studies, and the existing challenges and prospects of CA for cancer treatment and prevention are discussed in this review

Nanocellulose derived from agricultural biowaste by-products–Sustainable synthesis, biocompatibility, biomedical applications, and future perspectives: A review

Cellulose, a natural linear biopolymer composed of hierarchically arranged cellulose nanofibrils, presents a compelling avenue for sustainable nanocellulose synthesis from agricultural by-products. This innovative approach both mitigates organic waste and landfill disposal and unlocks the latent potential of nanocellulose, transforming agricultural residue into valuable resources. This paradigm shift towards sustainability resonates across diverse industrial sectors, particularly in biomedical research and development. In recent years, the remarkable attributes of nanocellulose, including its biocompatibility, low cytotoxicity, and exceptional water-holding capacity for cell immobilization, have propelled its adoption in various medical applications. From drug delivery systems to wound healing, tissue engineering, and antimicrobial treatments, nanocellulose has emerged as a versatile biomaterial. Moreover, the strategic integration of nanocellulose into composites and its structural functionalization enable customizing its properties for specific functions, further expanding its utility. This comprehensive review explores prominent types of nanocellulose—including cellulose nanocrystals, cellulose nanofibrils, and microbial or bacterial cellulose—elucidating their biomedical applications. This review underscores the sustainability principles underpinning its utilization by exploring the cellulose sources derived from biowaste and industrial processes for nanocellulose production. As a crucial component in a wide array of biomedical materials, nanocellulose both drives innovation and propels the advancement of biomedicine toward sustainability

Intelligent SOX Estimation for Automotive Battery Management Systems: State-of-the-Art Deep Learning Approaches, Open Issues, and Future Research Opportunities

Real-time battery SOX estimation including the state of charge (SOC), state of energy (SOE), and state of health (SOH) is the crucial evaluation indicator to assess the performance of automotive battery management systems (BMSs). Recently, intelligent models in terms of deep learning (DL) have received massive attention in electric vehicle (EV) BMS applications due to their improved generalization performance and strong computation capability to work under different conditions. However, estimation of accurate and robust SOC, SOH, and SOE in real-time is challenging since they are internal battery parameters and depend on the battery’s materials, chemical reactions, and aging as well as environmental temperature settings. Therefore, the goal of this review is to present a comprehensive explanation of various DL approaches for battery SOX estimation, highlighting features, configurations, datasets, battery chemistries, targets, results, and contributions. Various DL methods are critically discussed, outlining advantages, disadvantages, and research gaps. In addition, various open challenges, issues, and concerns are investigated to identify existing concerns, limitations, and challenges. Finally, future suggestions and guidelines are delivered toward accurate and robust SOX estimation for sustainable operation and management in EV operation.</jats:p