Search Results (6,641)

Although medicinal plants possess vast biological properties, crude medicinal plant extracts often show limited therapeutic efficacy due to poor aqueous solubility, instability, and inadequate bioavailability, which restricts efficient intracellular delivery. As cancer is a genetic disease requiring intracellular and nuclear targeting, improved delivery systems are essential. Warburgia salutaris is traditionally used in Southern Africa and possesses reported anticancer and anti-inflammatory properties; however, its crude extracts exhibit suboptimal delivery characteristics. This study comparatively evaluated the anticancer effects of unencapsulated (WSN) and liposomal-encapsulated (WSE) crude leaf extracts, with emphasis on apoptotic mechanisms. Liposomal formulation was confirmed by FTIR, PXRD, and DLS, yielding stable nanoparticles (159.4 nm; PDI 0.114; +79.3 mV). Both WSN and WSE demonstrated efficacy and concentration-dependent cytotoxicity against MCF-7 breast cancer cells (IC₅₀ < 0.0195 mg/mL) with minimal toxicity toward Vero kidney cells and RAW 264.7 macrophages. Mechanistically, WSN induced rapid cytotoxicity with necrotic features, whereas WSE promoted regulated apoptosis. Apoptosis was validated by DAPI/PI staining, Annexin V/PI flow cytometry, mRNA expression levels of Bax, Bcl-2, and caspase-3 measured with RT-PCR and proteome profiling array, confirming activation of intrinsic and extrinsic pathways. Both extracts also reduced LPS-induced ROS production. LC-MS identified multiple bioactive phytochemicals. Overall, liposomal encapsulation enhanced therapeutic precision, stability, and selectivity cytotoxicity, supporting its development as a nanomedicine-based anticancer strategy. Full article

Carbon quantum dots (CQDs) and stimuli-responsive hydrogels are advanced functional materials whose hybridization yields CQD-enhanced stimuli-sensitive hydrogels, opening new interdisciplinary avenues for smart material applications. This review systematically summarizes the latest advances in these composites, focusing on synthetic strategies, structure–property modulation mechanisms, and practical applications. Distinct from existing reviews that either investigate CQDs or hydrogels independently or discuss their composites in a single research field, this work features core novelties in integration strategy, application scope and critical analysis: it systematically compares the advantages, limitations and applicable scenarios of three typical CQD–hydrogel integration approaches (physical entrapment, in situ synthesis, covalent conjugation), comprehensively covers the multi-field application progress of the composites and conducts in-depth cross-field analysis of their common scientific issues and technical bottlenecks. By incorporating CQDs, the composites achieve remarkable performance optimizations: 40% improved mechanical toughness, sub-ppm-level heavy metal-sensing sensitivity, and over 80% organic dye photocatalytic degradation efficiency, addressing pure hydrogels’ inherent limitations of insufficient strength and single functionality. These enhancements enable sophisticated applications in biomedical field (real-time biosensing, controlled drug delivery), environmental remediation (pollutant detection/degradation), energy storage, and flexible electronics. The synergistic interplay between CQDs and hydrogels facilitates precise single/multi-stimulus responsiveness (pH, temperature, light), a pivotal advance for precision medicine and intelligent environmental monitoring. Despite promising progress, the large-scale practical application of CQD–hydrogel composites still faces prominent challenges: the difficulty in scalable fabrication with the uniform dispersion of CQDs in hydrogel matrices, poor long-term stability of most composites under physiological cyclic stress (service life < 6 months in practical tests), and low accuracy in discriminating multi-stimuli in complex real-world matrices. Future research should prioritize biomass-based eco-friendly CQD synthesis, machine learning-aided multimodal responsive systems, and 3D bioprinting for scalable manufacturing. Full article

CRISPR interference (CRISPRi), a programmable transcriptional repression technology derived from nuclease-deficient CRISPR-Cas systems, has emerged as a powerful method for selectively inhibiting oncogene expression without altering the genomic DNA. This feature offers a major advantage over other oncogene targeting technologies such as CRISPR-mediated gene knockout, mRNA inhibition by siRNA or miRNA, or small-molecule inhibitors of the proteins encoded by the oncogenes, especially in cancers driven by transcriptional dysregulation or otherwise undruggable oncogenes. Here, I present a comprehensive review of CRISPRi mechanisms, delivery strategies, and preclinical applications in oncology (including advances in targeting core oncogenic drivers like MYC and KRAS). The advantages of CRISPRi as well as in vivo validation of CRISPRi-mediated tumor suppression are discussed. Finally, I outline translational challenges and future directions for incorporating CRISPRi into precision cancer therapies. The accumulated evidence suggests that CRISPRi could become a cornerstone for next-generation gene-regulatory therapeutics. Full article

We utilized molecular dynamics (MD) simulations to explore the interaction of the RGD peptide with the αvβ3 integrin receptor, a key process for targeted drug delivery to tumors. The goal of these simulations was to model the transport of boron atoms by the RGD peptide and to characterize the binding event between this vector and its receptor. The study focused on the interaction processes and spatial arrangements of the solvated RGD–integrin system. Simulations were run for 100 ns to achieve relaxed-state configurations. Our model featured two RGD peptides: one pre-localized within the integrin’s binding site and another initially positioned externally. The external peptide was observed to diffuse freely and subsequently bind to the αvβ3 integrin. This spontaneous binding event provides valuable insights into the pharmacological specificity and mechanisms of the RGD–integrin interaction, informing the design of effective drug delivery systems. Full article

Background: The care and management of a pregnant woman suffering from end-stage brain cancer is surrounded by medical, legal, and ethical controversies. When this brain pathology leads to brain death (BD), continuation of life-sustaining treatments has been considered futile and unethical. An exception could be the case of pregnancy, in order to deliver a healthy neonate. Aim: The presentation of a pregnant woman with a terminal stage brain astrocytoma, admitted in the intensive care unit (ICU) to support the pregnancy, until optimal fetal viability, after she had neurological deterioration and confirmed BD, and a brief literature review of previously relevant published cases. Case Presentation: A 36-year-old woman with a medical history of brain astrocytoma in the last 2 years was admitted in ICU for the first time due to status epilepticus, six months after she stopped anticonvulsant therapy. Her epilepsy was controlled, and a pregnancy of 14 weeks was confirmed. Two weeks later, she deteriorated. After a multidisciplinary approach, it was decided to mechanically ventilate the patient and support the pregnancy. Brain death was determined after a couple of days. Results: A cesarean section was performed 11 weeks after BD diagnosis (at 27 weeks of gestational age) resulting in the delivery of a live, premature infant, weighing 549 gr. Conclusions: Maternal corporeal support can maximize the chances for survival in the neonate by prolonging the pregnancy of a brain-dead woman. Full article

This study examines the spatio-temporal evolution and restricting mechanisms of agricultural supply chain resilience in the Yangtze River Basin from a gradient perspective. An evaluation index system encompassing the dimensions of the supply side, demand side, circulation side, and support side was developed. The Entropy-Weighted TOPSIS method, kernel density estimation, and obstacle degree model were comprehensively applied to measure and dynamically analyze supply chain resilience across 11 provinces from 2013 to 2023. The findings reveal distinct spatio-temporal evolution patterns: while the overall resilience shows an upward trend, significant gradient disparities exist, with downstream areas exhibiting markedly higher resilience than the mid- and upstream regions. Regarding the restricting mechanisms, the circulation and support sides exhibit higher levels of obstacles, representing key constraints to resilience enhancement. Among these, express delivery volume, freight turnover, and local R&D personnel full-time equivalents are the core obstacle factors affecting resilience. Based on these findings, this study proposes targeted recommendations, including optimizing rural last-mile logistics, upgrading inter-provincial freight hubs, improving rail–water intermodal transport, and strengthening cold-chain infrastructure, as well as implementing differentiated regional strategies and establishing cross-regional coordination mechanisms. These recommendations aim to provide decision-making guidance for enhancing the risk-response capabilities of agricultural supply chains in the Yangtze River Basin and to promote balanced regional development. Full article

Periodontitis is a highly prevalent chronic inflammatory disease with significant oral and systemic consequences, including associations with cardiovascular disease, diabetes, and adverse pregnancy outcomes. Although mechanical debridement remains the cornerstone of therapy, adjunctive antibiotic use is increasingly limited by antimicrobial resistance, biofilm-associated tolerance, pharmacokinetic constraints, and disruption of the commensal microbiome, leading to inconsistent outcomes and disease recurrence. This review highlights the mechanistic limitations of conventional antibiotic therapies in periodontitis and critically examines emerging next-generation therapeutic strategies aimed at overcoming these challenges. Specifically, it explores antimicrobial peptides, quorum sensing inhibitors, nanotechnology-based drug delivery systems, host modulation approaches, and microbiome-targeted therapies, with emphasis on their molecular mechanisms, clinical relevance, and translational potential. By integrating microbial, host, and pharmacological perspectives, this review provides a comprehensive framework for advancing precision-guided periodontal therapy and supports the shift toward targeted, sustainable, and personalized treatment strategies. Full article

This study proposes a heterogeneous fusion path planning framework for unmanned aerial vehicles (UAVs) operating in complex emergency rescue and civil environments. Existing single-mechanism metaheuristics—including Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Genetic Algorithms (GAs)—suffer from fundamental limitations in three-dimensional kinematic path planning: PSO converges rapidly but stagnates at local optima due to population variance collapse; ACO offers robust local exploitation but incurs prohibitive cold-start overhead; GAs maintain diversity at the cost of expensive crossover operations. To address these complementary deficiencies simultaneously, the proposed framework introduces a spherical coordinate representation that reduces computational complexity and naturally enforces UAV kinematic constraints, combined with adaptive weight factors and a serial PSO-ACO fusion strategy, and subsequently incorporates adaptive weight factors. A serial fusion strategy is then introduced, wherein the sub-optimal trajectory generated by the Spherical PSO phase is mapped into the ACO pheromone field via a Gaussian Kernel Density Mapping (GKDM) mechanism, enabling the ACO phase to perform fine-grained local exploitation within a kinematically feasible corridor. Various constraints along the flight path are formulated into distinct cost functions, which cover aircraft track length, pitch angle variation, altitude difference variation, obstacle avoidance, and smoothness; the core task of the algorithm is to find the flight path with the minimum total cost. The proposed algorithm is dedicated to UAV path planning in complex emergency rescue environments (disaster-stricken areas, hazardous zones) and is further applicable to civil low-altitude logistics delivery, industrial facility inspection, ecological environment monitoring and urban air mobility (UAM) scenarios with complex obstacle constraints. It can effectively improve the safety and efficiency of UAVs in reaching rescue points, delivering emergency supplies, conducting disaster surveys, and completing various civil low-altitude operation tasks. Full article

Food delivery logistics sustainability includes environmental impact, economic efficiency, and service quality. Traditional logistics models mainly rely on fixed ''pickup buffer'' policies (such as a set 10 min wait). These systems do not account for the changing nature of restaurant operations and delivery conditions, leading to higher operating costs, driver idle time, and poorer food quality. To move delivery systems from reactive decision-making to proactive, dynamically forecasted operations, an adaptive control mechanism is needed. In on-demand food delivery, this offers a clear path to sustainability through better dispatch accuracy, order prep, and pickup coordination. To resolve these bottlenecks, this study examines how a smart logistics framework based on a dynamic Gradient Boosting Regressor (GBR) and policy-sensitive GBR can provide more accurate estimates of drivers' waiting times in light of contextual factors such as rush hour, time of day, and operational constraints. In last-mile food delivery, the proposed method aims to reduce operational costs, improve scheduling effectiveness, and maximize resource utilization by moving beyond static, predefined waiting periods to adaptive, context-aware decisions. The developed framework analyzes a proprietary dataset of 368,250 instant orders from a major Saudi Arabian logistics provider to evaluate the efficacy of static thresholds versus a proposed predictive, dynamic machine-learning-based approach. After rigorous data cleaning and temporal-logic adjustments, a ''High-Fidelity Ground-Truth'' subset of 1842 verified orders is used to simulate policy performance. This 99.5% reduction is necessitated by the widespread absence of the ''Order Ready'' timestamp in operational logs, which is the critical target variable for supervised learning; comparative analysis confirms the subset remains representative of the parent population’s spatiotemporal dynamics. The baseline analysis reveals severe inefficiencies in the static model, with a 61.67% violation rate for driver wait times, particularly in Riyadh (p < 0.001) and during late-night operations. The simulation results demonstrate that the dynamic policy reduces the ''Buffer Miss Rate'' (premature driver arrivals) from 59.08% to 7.32%, resulting in a 68.5% reduction in total operational waste costs. Full article

Myocardial infarction (MI) is one of the prevalent cardiovascular diseases, which is caused by obstruction of one or more coronary arteries, leading to cardiac tissue ischemia and death. One of the main consequences of MI is heart failure, which is defined as dysfunction of the heart muscle to pump blood into peripheral organs. Cardiac patches have drawn a lot of interest as a potentially effective way to restore damaged cardiac tissue and enhance its functionality. They are polymer-based scaffolds designed to be implanted on the heart surface, and they have shown a significant therapeutic effect in the treatment of MI by improving cardiac function and providing mechanical support for the infarction site by the delivery of various bioactive substances or cells. Several biomaterials with specific mechanical and chemical characteristics have been widely used as a scaffold in the process of fabricating cardiac patches. In this study, we focus on the latest developments in the manufacturing of synthetic-polymer-based cardiac patches used to treat heart failure induced by myocardial infarction. We describe the mechanical and chemical characteristics of several synthetic polymers and highlight the main benefits and drawbacks of each type. An overview of the major challenges and the future development directions in the field of cardiac patches is also highlighted. Full article

This study examines the effect of microfluidization on the physicochemical properties, stability, release behavior, and cytocompatibility of cannabidiol (CBD) nanoemulsions intended for topical application. CBD is a non-psychoactive cannabinoid characterized by anti-inflammatory and analgesic activity; however, its therapeutic use is limited by low solubility and poor bioavailability. To address these limitations, nanoemulsions were formulated using avocado oil and Tween 80 and optimized through a Box–Behnken experimental design evaluating microfluidization pressure (5000–20,000 PSI), CBD concentration (0–2%), and oil content (8–10%). Nanoemulsions were characterized over a 60-day period in terms of droplet size, dispersity index (D), and zeta potential. An increase in processing pressure led to a reduction in both droplet size and dispersity, with optimal conditions identified between 11,000 and 15,000 PSI. Higher oil and CBD concentrations were associated with an increase in the magnitude of the zeta potential, contributing to electrostatic stabilization of the system. Encapsulation efficiency reached approximately 81.4%. Cell viability assays in HaCaT keratinocytes indicated no significant cytotoxic effects. The optimized formulation exhibited a sigmoidal CBD release profile best described by Weibull and Gompertz models (R² ≈ 0.99), suggesting combined diffusion and interfacial mechanisms that support efficient topical delivery. Full article

Cysteine is a sulfur-containing amino acid that plays a central role in skin physiology through thiol-mediated redox regulation and glutathione (GSH) synthesis. It critically influences melanogenesis, collagen homeostasis, and wound healing. However, its clinical application is limited by poor stability and bioavailability. In this review, we provide a mechanistic and comparative analysis of cysteine and its derivatives, including N-acetylcysteine (NAC), cysteinamide (C-NH₂), GSH, and related compounds. These derivatives regulate melanogenesis by modulating dopaquinone pathways and tyrosinase activity, maintain collagen balance by preserving redox-sensitive enzymatic processes, and enhance wound healing through antioxidant and anti-inflammatory mechanisms. Importantly, chemical modifications such as acetylation, amidation, and esterification improve pharmacokinetic properties, enabling more effective intracellular delivery. Furthermore, different derivatives exhibit distinct advantages depending on biological context, highlighting the importance of compound selection. Overall, cysteine derivatives emerge as promising therapeutic candidates for dermatological applications, particularly in pigmentation disorders and impaired wound healing. Future studies should focus on in vivo validation and clinical translation. Full article

Background/Objectives: Primary acquired lacrimal drainage obstruction (PALDO) is a common cause of epiphora. Although dacryoendoscopic recanalization (DER) is widely performed, its long-term success is limited by restenosis related to fibro-inflammatory processes. This study aimed to evaluate the efficacy of a novel Q-needle for targeted intraductal delivery of antifibrotic and anti-inflammatory agents during DER. Methods: A retrospective review was performed on 190 eyes treated with DER, silicone tube intubation (SI), and retrograde intraductal injection via the inferior meatus using a Q-needle. A mixture of dexamethasone (1 mL), 5-fluorouracil (1 mL), and triamcinolone acetonide (1 mL) was administered directly into the obstruction site under endoscopic visualization. Obstruction type was classified intraoperatively as secretory or structural based on dacryoendoscopic findings. Results: The overall surgical success rate was 92.1%, with significantly greater success in secretory-type PALDO compared to the structural type (96.8% vs. 87.4%, p = 0.031). These outcomes contrast with previous reports in which secretory-type PALDO was associated with poorer prognosis after DER. Conclusions: The improved outcomes in the secretory group suggest a potential role of combined antiproliferative and multi-phase anti-inflammatory therapy in effectively addressing the key mechanisms of restenosis. Q-needle–assisted intraductal injection during DER may represent a simple and safe adjunctive approach to improve surgical consistency and long-term patency in patients with PALDO. Full article

Traumatic brain injury (TBI) represents a significant global health challenge with limited effective treatments. The secondary injury phase, characterized by persistent neuroinflammation, is a major contributor to long-term neurological deficits. Conventional therapies face substantial hurdles, including the blood–brain barrier (BBB), short therapeutic windows, and poor neuroregenerative capacity. Innovative biomaterials offer a promising platform to overcome these limitations by providing localized Drug Deliv., immunomodulation, and structural support for neural regeneration. This review outlines the pathological mechanisms of neuroinflammation and repair obstacles following TBI. It then systematically categorizes and discusses the mechanisms of various biomaterials—including natural, synthetic, nano-scale, composite, and intelligent materials—in modulating neuroinflammation. Furthermore, we elaborate on strategies for promoting neural repair, such as constructing regenerative scaffolds, delivering therapeutic agents (e.g., neurotrophic factors, stem cells, and exosomes), and remodeling the regenerative microenvironment. Special emphasis is placed on the emerging application of exosome delivery systems. Finally, we address the challenges in clinical translation and present future perspectives on smart materials, multi-modal systems, and personalized therapies, highlighting the transformative potential of biomaterials in TBI management. Full article

Unmanned Aerial Vehicles (UAVs) have become widely used tools for different applications including surveillance, search and rescue, and package delivery. However, autonomous path planning in dynamic environments with moving obstacles, wind disturbances, and energy constraints remains a significant challenge. This paper proposes a novel Multi-Head Attention Deep Q-Network with Prioritized Experience Replay (MA-DQN + PER) that integrates bio-inspired attention mechanisms with deep reinforcement learning for efficient UAV path planning. Our approach features a 46-dimensional state space that captures all environmental information, including static obstacles, wind conditions, and energy status. The proposed Attention-QNetwork architecture uses four specialized attention heads to selectively focus on different aspects of the environment, including obstacle avoidance, target tracking and energy management, and wind compensation. To improve sample efficiency and convergence speed, we incorporate Prioritized Experience Replay (PER) as well as Prioritized Experience Replay (PER) with a sum-tree data structure to improve sample efficiency and convergence speed. A curriculum learning strategy that includes 10 difficulty levels is designed to progressively enhance the agent’s capabilities. Extensive simulations demonstrate that our MA-DQN + PER approach reaches a 96% task success rate (defined as the percentage of episodes where the UAV successfully reaches the target without collision or battery depletion), while the convergence speed was 68% quicker than that of the baseline DQN. Our method demonstrates superior performance in path efficiency (+17%), energy consumption reduction (−26%), and collision avoidance compared to state-of-the-art algorithms. Full article