Search Results (142)

Phytochemicals from medicinal plants offer significant therapeutic benefits, yet their clinical utility is often limited by poor solubility, instability, and low bioavailability. Nanotechnology presents a transformative approach to overcome these challenges by encapsulating phytochemicals in nanocarriers that enhance stability, targeted delivery, and controlled release. This review highlights major classes of phytochemicals such as polyphenols, flavonoids, and alkaloids and explores various nanocarrier systems including liposomes, polymeric nanoparticles, and hybrid platforms. It also discusses their mechanisms of action, improved pharmacokinetics, and disease-specific targeting. Further, the review examines clinical advancements, regulatory considerations, and emerging innovations such as smart nanocarriers, AI-driven formulation, and sustainable manufacturing. Nano-phytomedicine offers a promising path toward safer, more effective, and personalized therapies, bridging traditional herbal knowledge with modern biomedical technology. Full article

Carbon nanotubes (CNTs) have emerged as pivotal nanomaterials in sensing technologies owing to their unique structural, electrical, and mechanical properties. Their high aspect ratio, exceptional surface area, excellent electrical conductivity, and chemical tunability enable superior sensitivity and rapid response in various sensor platforms. This review presents a comprehensive overview of recent advancements in CNT-based sensors, encompassing both single-walled (SWCNTs) and multi-walled carbon nanotubes (MWCNTs). We discuss their functional roles in diverse sensing applications, including gas sensing, chemical detection, biosensing, and pressure/strain monitoring. Particular emphasis is placed on the mechanisms of sensing, such as changes in electrical conductivity, surface adsorption phenomena, molecular recognition, and piezoresistive effects. Furthermore, we explore strategies for enhancing sensitivity and selectivity through surface functionalization, hybrid material integration, and nanostructuring. The manuscript also covers the challenges of reproducibility, selectivity, and scalability that hinder commercial deployment. In addition, emerging directions such as flexible and wearable CNT-based sensors, and their role in real-time environmental, biomedical, and structural health monitoring systems, are critically analyzed. By outlining both current progress and existing limitations, this review underscores the transformative potential of CNTs in the design of next-generation sensing technologies across interdisciplinary domains. Full article

Barium stannate (BaSnO₃) has emerged as a promising alternative electron transport material owing to its superior electron mobility, resistance to UV degradation, and energy bandgap tunability, yet BaSnO₃-based perovskite solar cells have not reached the efficiency levels of TiO₂-based designs. This theoretical study presents a design-driven evaluation of BaSnO₃-based perovskite solar cell architectures, incorporating MAPbI₃ or FAMAPbI₃ perovskite materials, Spiro-OMeTAD, or Cu₂O hole transport materials as well as hole-free configurations, under varying light intensity. Using a systematic device modelling approach, we explore the influence of key design variables—such as layer thickness, donor density, and interface defect concentration—of BaSnO₃ and operating temperature on the power conversion efficiency (PCE). Among the proposed designs, the FTO/BaSnO₃/FAMAPbI₃/Cu₂O/Au heterostructure exhibits an exceptionally effective arrangement with PCE of 38.2% under concentrated light (10,000 W/m², or 10 Sun). The structure also demonstrates strong thermal robustness up to 400 K, with a low temperature coefficient of −0.078% K⁻¹. These results underscore the importance of material and structural optimisation in PSC design and highlight the role of high-mobility, thermally stable inorganic transport layers—BaSnO₃ as the electron transport material (ETM) and Cu₂O as the hole transport material (HTM)—in enabling efficient and stable photovoltaic performance under high irradiance. The study contributes valuable insights into the rational design of high-performance PSCs for emerging solar technologies. Full article

Multimodal artificial intelligence (AI) is driving a paradigm shift in modern biomedicine by seamlessly integrating heterogeneous data sources such as medical imaging, genomic information, and electronic health records. This review explores the transformative impact of multimodal AI across three pivotal areas: biomaterials science, medical diagnostics, and personalized medicine. In the realm of biomaterials, AI facilitates the design of patient-specific solutions tailored for tissue engineering, drug delivery, and regenerative therapies. Advanced tools like AlphaFold have significantly improved protein structure prediction, enabling the creation of biomaterials with enhanced biological compatibility. In diagnostics, AI systems synthesize multimodal inputs combining imaging, molecular markers, and clinical data—to improve diagnostic precision and support early disease detection. For precision medicine, AI integrates data from wearable technologies, continuous monitoring systems, and individualized health profiles to inform targeted therapeutic strategies. Despite its promise, the integration of AI into clinical practice presents challenges such as ensuring data security, meeting regulatory standards, and promoting algorithmic transparency. Addressing ethical issues including bias and equitable access remains critical. Nonetheless, the convergence of AI and biotechnology continues to shape a future where healthcare is more predictive, personalized, and responsive. Full article

The progression of research in concentration photovoltaic systems parallels the advancement of high-efficiency multi-junction solar cells. To translate the theoretical optical framework into practical experimentation, a modular and structurally validated mechanical configuration for a high-concentration photovoltaic (HCPV) system was developed, incorporating boundary conditions and ensuring full system integration. The system incorporates a modular mechanical architecture, allowing flexible integration and interchangeability of optical components for experimental configurations. The architecture offers a high degree of mechanical flexibility, providing each optical stage with multiple linear and angular adjustment capabilities to support precision alignment. To ensure tracking precision, the system was coupled with a three-dimensional sun tracker capable of withstanding torques up to 60 Nm and supporting a combined payload of 80 kg, including counterbalance. The integration necessitated implementation of a counterbalance mechanism along with comprehensive static load analysis to ensure alignment stability and mechanical resilience. A reinforced triangular support structure, fabricated from stainless steel, was validated through simulation to maintain deformation below 0.1 mm under stress levels reaching 5 MN/m², confirming its mechanical robustness and reliability. Windage analysis confirmed that the tracker could safely operate at 15 m/s wind speed for tilt angles of 35° (counter-clockwise) and −5° (clockwise), while operation at a 80° (counter-clockwise) tilt is safe up to 12 m/s, ensuring compliance with local environmental conditions. Overall, the validated system demonstrates structural resilience and modularity, supporting experimental deployment and future scalability. Full article

Injectable biopolymer-based hydrogels have emerged as a powerful class of biomaterials designed for minimally invasive therapeutic strategies in modern medicine. These smart hydrogels, derived from natural biopolymers, such as alginate, chitosan, gelatin, hyaluronic acid, and collagen, offer unique advantages, including biocompatibility, biodegradability, and the ability to mimic the extracellular matrix. This review provides a comprehensive overview of recent advancements in the design, crosslinking mechanisms, and biofunctionality of injectable hydrogels tailored for targeted drug delivery and tissue regeneration. Special attention is given to their role in in situ gelling systems, cancer therapy, musculoskeletal repair, and neural regeneration. Challenges related to mechanical strength, degradation control, and clinical translation are also discussed, along with future perspectives for scalable manufacturing and regulatory approval. Full article

Electroactive polymers (EAPs) have emerged as versatile materials for self-powered actuators and biosensors, revolutionizing biomedical diagnostics and healthcare technologies. These materials harness various energy harvesting mechanisms, including piezoelectricity, triboelectricity, and ionic conductivity, to enable real-time, energy-efficient, and autonomous sensing and actuation without external power sources. This review explores recent advancements in EAP-based self-powered systems, focusing on their applications in biosensing, soft robotics, and biomedical actuation. The integration of nanomaterials, flexible electronics, and wireless communication technologies has significantly enhanced their sensitivity, durability, and multifunctionality, making them ideal for next-generation wearable and implantable medical devices. Additionally, this review discusses key challenges, including material stability, biocompatibility, and optimization strategies for enhanced performance. Future perspectives on the clinical translation of EAP-based actuators and biosensors are also highlighted, emphasizing their potential to transform smart healthcare and bioelectronic applications. Full article

Zinc oxide nanoparticles (ZnO NPs) have garnered significant attention across various scientific and technological domains due to their unique physicochemical properties, including high surface area, photostability, biocompatibility, and potent antimicrobial activity. These attributes make ZnO NPs highly versatile, enabling their application in biomedicine, environmental science, industry, and agriculture. They serve as effective antimicrobial agents in medical treatments and as catalysts in environmental purification processes, owing to their ability to generate reactive oxygen species (ROS) and exhibit photocatalytic activity under UV light. Moreover, ZnO NPs are being increasingly employed in advanced drug delivery systems and cancer therapies, highlighting their potential in modern medicine. Their growing popularity is further supported by their ease of synthesis, cost-effectiveness, and capacity for diverse functionalization, which expand their utility across multiple sectors. This review focuses on research from the past five years (2020–2025) on the practical uses of ZnO nanoparticles in the biomedical, environmental, industrial, and agricultural fields. It also highlights current trends, existing challenges, and future perspectives. By examining these aspects, the article provides a comprehensive understanding of the versatile roles of ZnO NPs and their emerging significance in science and technology. Full article

Reliable forecasts of large-scale chlorophyll-a (Chl-a) levels one week ahead in the Murray–Darling Basin are essential for water resources management, as increasing Chl-a levels in water bodies indicate possible harmful algal blooms, a serious threat for freshwater security. A lack of high-resolution data in space and time is a major constraint for delivering early warnings. To address data scarcity, we developed a forecasting model integrating remote sensing data and time-series modelling. Using in situ Chl-a measurements from Murray–Darling Basin water bodies, we locally recalibrated a two-band ratio algorithm, namely the Normalized Difference Chlorophyll Index (NDCI), from Sentinel-2 data to derive Chl-a levels. The recalibrated model significantly improved the accuracy of high Chl-a estimates in our dataset after mitigating data heteroscedasticity. Building on these improved satellite-derived Chl-a estimates, we developed a time-series model for forecasting weekly Chl-a levels including quantification of forecast uncertainty through prediction intervals. The developed model, validated at eight sites for 2021–2022 data, performed well at shorter lead times, showing R² = 0.41 and RMSE = 8.1 μg/L for overall performance at a one-week lead time. The prediction intervals generally aligned well with nominal levels, demonstrating their reliability. This study provides a valuable tool for the water managers/decision-makers to issue early warnings of algal blooms in the Murray–Darling Basin. Full article

Background: Modified thoracoabdominal nerve block through a perichondrial approach (M-TAPA) and external oblique intercostal plane block (EOIB) provide abdominal analgesia by blocking thoracoabdominal nerves. Our aim was to compare the analgesic efficacy of M-TAPA vs. EOIB on the quality of recovery and pain scores in patients who underwent laparoscopic cholecystectomy surgery (LC). Methods: Patients with American Society of Anesthesiologists status I-II, aged between 18 and 65 years, and scheduled for elective LC under general anesthesia were enrolled in the study. The patients were randomized into two groups: Group M-TAPA (n = 30) and Group EOIB (n = 30). The blocks were performed with 40 mL 0.25% bupivacaine in total. The primary outcome of the study was the global quality of recovery score, and the secondary outcomes were the pain scores, rescue analgesic requirement, and adverse effects during the 24-h postoperative period. Results: The global quality of recovery scores at 24 h were similar in both groups. There was a reduction in the median static and dynamic numerical rating scale (NRS) in the first 2 h postoperatively for M-TAPA compared to the EOIB (p < 0.001). The need for rescue analgesia was significantly lower in the M-TAPA group compared to the EOIB group (p < 0.005). Conclusions: Opioid consumption was lower in the M-TAPA group, and the pain scores of the two groups were similar, with the exception of the first 2 h postoperatively. Both the M-TAPA block and EOIB are effective for analgesia following laparoscopic abdominal surgeries. Full article

Background/Objectives: The guideline on allergen-specific immunotherapy of the European Academy of Allergy and Clinical Immunology recommends subcutaneous allergen-specific immunotherapy for the treatment of allergic rhinitis in children and adults with moderate to severe symptoms. The five years cohort study described below was designed in 2020 to demonstrate non-inferiority in terms of safety, tolerability and efficacy in a paediatric population compared with adult patients treated with microcrystalline tyrosine-adsorbed allergoids for their tree and grass pollen allergy in a perennial setting. Here, we present the preliminary findings from the first year. Methods: The Combined Symptom and Medication Score was chosen as the primary endpoint of this therapy. Secondary endpoints include the Rhinoconjunctivitis Quality of Life Questionnaire, the retrospective Rhinoconjunctivitis score, the Asthma Control Test and the Rhinitis Control Test, as well as an analysis of adverse drug reactions. Results: A total number of 320 patients were enrolled into this study, with 129 of these patients in the age group between 5 and 17 years and 191 patients in the adult age group. Mean Combined Symptom and Medication Score values did not differ significantly between minors and adults in the first pollen season after treatment induction. The retrospective score showed a strong and significant reduction in rhinoconjunctivitis and asthma symptoms. Treatment was well tolerated, with more than 80% of patients reporting no adverse drug reactions. Conclusions: The validity of this study approach of a cohort study has been confirmed by this first interim analysis for the initial course of therapy in the first year. Full article

The rapid evolution of micro- and nano-architectures is revolutionizing biomedical engineering, particularly in the fields of therapeutic and diagnostic micromechanics. This review explores the recent innovations in micro- and nanostructured materials and their transformative impact on healthcare applications, ranging from drug delivery and tissue engineering to biosensing and diagnostics. Key advances in fabrication techniques, such as lithography, 3D printing, and self-assembly, have enabled unprecedented control over material properties and functionalities at microscopic scales. These engineered architectures offer enhanced precision in targeting and controlled release in drug delivery, foster cellular interactions in tissue engineering, and improve sensitivity and specificity in diagnostic devices. We examine critical design parameters, including biocompatibility, mechanical resilience, and scalability, which influence their clinical efficacy and long-term stability. This review also highlights the translational potential and current limitations in bringing these materials from the laboratory research to practical applications. By providing a comprehensive overview of the current trends, challenges, and future perspectives, this article aims to inform and inspire further development in micro- and nano-architectures that hold promise for advancing personalized and precision medicine. Full article

The main objective of this study was to analyze the physical fitness parameters of young competitive padel players, compare potential differences between male and female players, and examine the relationships among various physical fitness variables in this population. The sample consisted of 18 players (10 boys and 8 girls) aged between 12 and 16 years old belonging to the Technification program for minors of the Valencian Padel Federation. The players completed a test battery that consisted of different tests: CMJ jump, internal and external shoulder rotator strength, manual dynamometry, functional upper body strength (forehand throw, backhand throw, bilateral overhead throw, and serve throw), smash speed, 5 × 10 m agility test, and tapas test. Data analysis was carried out with SPSS software for Windows (Version 25.0, IBM Corp., Armonk, NY, USA). The results showed that the boys obtained significantly higher values in the tests of dynamometry, speed, agility (tapas test), and throws (forehand, backhand, serve, and over the head), and the girls obtained significantly higher values in the test of shoulder external rotation (non-dominant). At the same time, the force variables were significantly and positively related to each other. The CMJ values are also significantly and positively correlated with the variables of shoulder rotation, sprint speed, and medicine ball throws. Regarding agility, significant and positive correlations were found in the tapas test. However, the 5 × 10 m test showed negative and significant correlations with some variables. It has been observed that the results obtained coincide with the results found in other studies carried out with players of the same age in other sports, such as tennis and soccer. Full article

Lake Hume, a critical reservoir within the Murray River system, Australia, has been identified as a potential source of cyanobacteria in downstream rivers during past mega-blooms. This study aims to evaluate the impact of lake-level fluctuations on cyanobacterial abundance at the dam outlets, with the goal of mitigating the risk of cyanobacteria intake from hydropower and irrigation outlets during periods of low dam levels. Utilising a one-dimensional vertical hydrodynamic model (LAKEoneD), the study simulated time series data on water temperature and stratification within Lake Hume. These outputs were then incorporated into a cyanobacteria growth model driven by water temperature, mixing dynamics and light. Despite inherent uncertainties in the models, the simulated cell counts effectively mirrored bloom occurrences. Consequently, a series of simulations across varying water levels in the lake revealed a consistent risk of significant cyanobacteria intake through both the hydropower and irrigation outlets when water levels dropped below specific thresholds. Notably, water levels below 20 m and 10 m posed heightened risks of releases of seed populations of cyanobacteria from the hydropower and irrigation outlets, respectively. Full article

The changes in frequency and intensity of rainfall, variation in temperature, increasing extreme weather events, and rising greenhouse gas emissions can together have a varying impact on food grain production, which then leads to significant impacts on food security in the future. The purpose of this study is to quantify how maize productivity might be affected due to climate change in Southern India. The present study examines how the projected changes to the northeast monsoon will affect maize yield in Tamil Nadu during the rabi season, which spans from September to December, by using a three-step methodology. Firstly, global climate models that accurately represent the large-scale features of the mean monsoon were chosen. Secondly, baseline and future climate data were extracted from the selected global models and the baseline data were compared with observations. Thirdly, the panel data regression model was fitted with the India Meteorological Department’s (IMD) observed climate data to generate the baseline coefficients and projected the maize production using future climate data generated from the global climate model. The Representative Concentration Pathways (RCPs) of RCP4.5 and RCP8.5 were used from two global climate model outputs, namely GFDL_CM3 and HadGEM2_CC, to predict the climate change variability on maize yields during the middle (2021–2050) and the end (2071–2100) of this century. The maize yield is predicted to increase by 3 to 5.47 per cent during the mid-century period and it varies from 7.25 to 14.53 per cent during the end of the century for the medium- (RCP4.5) and high-emission (RCP8.5) climate change scenarios. The maize grain yield increasing during the future periods indicated that the increase in rainfall and temperature during winter in Southern India reduced the possibility of a negative impact of temperature on the maize yield. Full article