Search Results (254)

Given their role in viral polyprotein processing, viral proteases (PRs) are excellent targets for antiviral therapy. Most assays developed for screening PR inhibitors are in vitro assays, and therefore have several limitations, including the inability to account for cell permeability, toxicity and the need for compounds activation within cells. The development of cellular reporters overcoming these limitations is therefore highly desirable. In this study, we developed two different Bioluminescence Resonance Energy Transfer (BRET)-based reporters for Human Immunodeficiency virus-1 (HIV-1) PR, allowing the simultaneous monitoring of cell viability and HIV-1 PR activity. The reporters employ two different BRET pairs as donor and acceptor moieties: Renilla luciferase (RLuc) with Yellow Fluorescent Protein (YFP), and Nano luciferase (NLuc) with mNeonGreen (mNG), both linked by the HIV-1 p2/p7 cleavage site. While both reporters specifically detected HIV-1 protease activity, mNG-p2/p7-NLuc exhibited higher sensitivity, increased energy transfer and better spectral separation between donor and acceptor emissions, resulting in a significantly higher BRET ratio. mNG-p2/p7-NLuc was used to quantify the effect of a panel of protease inhibitors in living cells, assessing simultaneously cell viability and HIV-1 PR activity. Additionally, it was employed to measure the potency of well-known HIV-1 PR inhibitors. Together, these findings demonstrate the utility of the mNG-p2/p7-NLuc reporter as a cell-based tool for the evaluation of HIV-1 PR activity and inhibitor efficacy. Its dual-readout capability provides a valuable platform for antiviral drug screening in physiologically relevant conditions. Full article

Background: Greenhouses are pivotal to sustainable agriculture as they provide suitable conditions to support the growth of crops in unusable land such as arid areas. However, conventional greenhouse cover materials such as glass, polycarbonate (PC), and polyethylene (PE) sheets are limited in regulating internal conditions in the greenhouses based on environmental changes. Quantum and nonlinear metamaterials are emerging materials with the potential to optimize the covers and ensure appropriate regulation. Objective: This comprehensive review investigated the performance optimization of greenhouse covers through the potential application of nonlinear and quantum metamaterials as nano-additives, examining their effects on electromagnetic radiation management, crop growth enhancement, and temperature regulation within greenhouse systems. Method: The scoping review method was used, where 39 published articles were examined. Results: The review revealed that integrating nano-additives ensured that the greenhouse covers would block harmful near-infrared (NIR) radiation that generated heat while also optimizing for photosynthetically active radiation (PAR) to promote crop yields. Conclusions: The insights also indicated that the high sensitivity of the metamaterials would facilitate the regulation of the internal conditions within the greenhouses. However, challenges such as complex production processes that were not commercially scalable and the recyclability of the metamaterials were identified. Future work should further investigate pathways to produce hybrid greenhouse covers that integrate metamaterials with conventional materials to enhance scalability. Full article

Myopia is a common refractive error with a rising prevalence worldwide, and its early diagnosis is crucial to prevent long-term visual impairment. This study presents an accessible, automated approach for detecting myopia from fundus photographs by analyzing the optic disc, using a deep learning model based on the YOLO (You Only Look Once) architecture, version 8 and 11. The pipeline was designed to be usable by eye care practitioners (ECPs) with no expertise in computer science. Fundus images were processed to extract the optic disc region using a custom-trained YOLOv8 model, and a subsequent classification algorithm determined the presence or absence of myopia based on features from the extracted region. The system was trained on a single-clinic dataset of 730 augmented images, with 98 images reserved for internal validation, and tested on 50 independent optic disc images. It achieved a high diagnostic accuracy, with strong sensitivity and F1 scores. Lightweight models such as YOLOv11-nano performed comparably to larger variants in the testing dataset (AUC 97.5% vs. 97.3%), effectively supporting myopia detection. This work highlights the feasibility of integrating AI-based screening tools into clinical practice without requiring advanced technical skills, offering a scalable and cost-effective solution to support early diagnosis of myopia in diverse healthcare settings. Full article

Chagas disease, caused by Trypanosoma cruzi (T. cruzi), remains a significant public health challenge in Latin America. Traditional diagnostic methods relying on manual microscopy suffer from low sensitivity, subjective interpretation, and poor performance in suboptimal conditions. This study presents a novel computer vision framework integrating motion analysis with deep learning for automated T. cruzi detection in microscopic videos. Our motion-based detection pipeline leverages parasite motility as a key discriminative feature, employing frame differencing, morphological processing, and DBSCAN clustering across 23 microscopic videos. This approach effectively addresses limitations of static image analysis in challenging conditions including noisy backgrounds, uneven illumination, and low contrast. From motion-identified regions, $64\times 64$ patches were extracted for classification. MobileNetV2 achieved superior performance with 99.63% accuracy, 100% precision, 99.12% recall, and an AUC-ROC of 1.0. Additionally, YOLOv5 and YOLOv8 models (Nano, Small, Medium variants) were trained on 43 annotated videos, with YOLOv5-Nano and YOLOv8-Nano demonstrating excellent detection capability on unseen test data. This dual-stage framework offers a practical, computationally efficient solution for automated Chagas diagnosis, particularly valuable for resource-constrained laboratories with poor imaging quality. Full article

The nitrogen-vacancy (NV) center magnetic sensor, leveraging nitrogen-vacancy quantum effects, enables high-sensitivity magnetic field detection via optically detected magnetic resonance (ODMR). However, conventional single-point integrated devices suffer from limitations such as inefficient regional magnetic field detection and challenges in discerning the directional variations of dynamic magnetic fields. To address these issues, this study proposes an array- based architecture that innovatively substitutes the conventional 532 nm laser with quantum-dot light-emitting diodes (QLEDs). Capitalizing on the advantages of QLEDs—including compatibility with micro/nano-fabrication processes, wavelength tunability, and high luminance—a 2 × 2 monolithically integrated magnetometer array was developed. Each sensor unit achieves a magnetic sensitivity of below 26 nT·Hz^−1/2 and a measurable range of ±120 μT within the 1–10 Hz effective bandwidth. Experimental validation confirms the array’s ability to simultaneously resolve multi-regional magnetic fields and track dynamic field orientations while maintaining exceptional device uniformity. This advancement establishes a scalable framework for the design of large-scale magnetic sensing arrays, demonstrating significant potential for applications requiring spatially resolved and directionally sensitive magnetometry. Full article

Microplastics, synthetic polymer particles measuring less than 5 mm, have become a widespread environmental pollutant, raising concerns over their possible effects on human health. Growing evidence links MPs to vascular aging and cardiovascular disease beyond their ecological toxicity. Upon inhalation, ingestion, or skin contact, microplastics can traverse biological barriers, circulate systemically, and accumulate in vascular tissues. Experimental investigations indicate that MPs, especially polystyrene and polyethylene in nano- and micro-sized forms, induce oxidative stress, mitochondrial dysfunction, and chronic inflammation. These disruptions activate redox-sensitive signaling pathways, such as NF-κB and NLRP3 inflammasome, causing endothelial dysfunction, vascular smooth muscle modulation, and foam cell production, indicating early vascular aging. Animal models and in vitro studies have consistently shown endothelial activation, increased cytokine production, and changes in vascular tone after exposure to MPs. Initial human research has detected microplastics in blood, thrombi, and atherosclerotic plaques, which correlate with negative cardiovascular outcomes and systemic inflammation. Notably, recent research suggests that the gut microbiota and antioxidant systems may play a role in adaptive reactions, although these processes are still not fully understood. MP-induced vascular toxicity is covered in this interdisciplinary review, highlighting molecular pathways, experimental data, and translational gaps. Full article

Transitioning to sustainable energy systems demands the creation of innovative methods that deliver dependable and effective renewable energy technologies. CSP systems that integrate parabolic trough designs with thermal energy storage (TES) systems provide essential solutions to overcome energy intermittency challenges. Molten salts serve dual functions as heat transfer fluids (HTFs) and thermal energy storage (TES) media, making them critical to CSP system performance improvements. The study introduces a hybrid MCDM framework that combines the CRITIC method for objective weighting with the SWARA approach for expert-adjusted weighting and utilizes an enhanced Lexicographic Goal Programming to evaluate molten salt options for off-grid parabolic trough systems. The evaluation process considered melting point alongside thermal stability while also assessing cost-effectiveness, recyclability, and safety requirements. The use of Pareto front analysis helped identify non-dominated salts, which then underwent a tiered optimization process emphasizing safety, performance, and sustainability features. Results confirm that the ternary nitrate composition Ca(NO₃)₂:NaNO₃:KNO₃ offers the best overall performance across all tested policy scenarios, driven by its superior thermophysical properties. Solar Salt (NaNO₃-KNO₃) consistently ranks as a robust second choice, excelling in economic and sustainability metrics. The proposed approach provides a flexible, policy-sensitive framework for material selection tailored to enhance the efficiency and sustainability of off-grid CSP systems and support the renewable energy objectives. Full article

Brain ischemia is a severe condition caused by reduced cerebral blood flow, leading to the disruption of ion gradients in brain tissue. This imbalance triggers spreading depolarizations, which are waves of neuronal and glial depolarization propagating through the gray matter. Microelectrode arrays (MEAs) are essential for real-time monitoring of these electrophysiological processes both in vivo and in vitro, but their sensitivity and signal quality are critical for accurate detection of extracellular brain activity. In this study, we evaluate the performance of a flexible microelectrode array based on gold-coated zinc oxide nanorods (ZnO NRs), referred to as nano-fMEA, specifically for high-fidelity electrophysiological recording under pathological conditions. Acute mouse brain slices were tested under two ischemic models: oxygen–glucose deprivation (OGD) and hyperkalemia. The nano-fMEA demonstrated significant improvements in event detection rates and in capturing subtle fluctuations in neural signals compared to flat fMEAs. This enhanced performance is primarily attributed to an optimized electrode–tissue interface that reduces impedance and improves charge transfer. These features enabled the nano-fMEA to detect weak or transient electrophysiological events more effectively, making it a valuable platform for investigating neural dynamics during metabolic stress. Overall, the results underscore the promise of ZnO NRs in advancing electrophysiological tools for neuroscience research. Full article

This work introduces an original approach to the manufacturing of ionizing radiation-sensitive systems for radiotherapy applications—dosimetry. They are based on the Fricke dosimetric solution and the formation of macro-gels and capsules, and nano- and micro-gels. The reaction of ionic polymers, such as sodium alginate, with Fe and Ca metal ions is employed. Critical polymer concentration (c*) is taken as the criterion. Reaction of ionic polymers with metal ions leads to products related to c*. Well below c*, nano- and micro-gels may form. Above c*, macro-gels and capsules can be prepared. Nano- and micro-gels containing Fe in the composition can be used for infusion of a physical gel matrix to prepare 2D or 3D dosimeters. In turn, macro-gels can be formed with Fe ions crosslinking polymer chains to obtain radiation-sensitive hydrogels, so-called from wall-to-wall, serving as 3D dosimeters. The encapsulation process can lead to capsules with Fe ions serving as 1D dosimeters. This work presents the concept of manufacturing various gel structures, their main features and manufacturing challenges. It proposes new directions of research towards novel dosimeters. Full article

Background/Objectives: Carbohydrate antigen 19-9 (CA19-9) is a clinically established biomarker primarily used for monitoring disease progression and recurrence in pancreatic and gastrointestinal cancers. Accurate and continuous quantification of CA19-9 in patient samples is critical for effective clinical management. This study aimed to develop dual-emitting molecularly imprinted nanopolymers (dual@nanoMIPs) for ratiometric and reliable detection of CA19-9 in serum. Methods: Dual-emitting nanoMIPs were synthesized via a one-step molecular imprinting process, incorporating both blue-emitting carbon dots (b-CDs) as internal reference fluorophores and yellow-emitting quantum dots (y-QDs) as responsive probes. The CA19-9 template was embedded into the polymer matrix to create specific recognition sites. Fluorescence measurements were carried out under 365 nm excitation in 1% human serum diluted in phosphate-buffered saline (PBS). Results: The dual@nanoMIPs exhibited a ratiometric fluorescence response upon CA19-9 binding, characterized by the emission quenching of the y-QDs at 575 nm, while the b-CDs emission remained stable at 467 nm. The fluorescence shift observed in the RGB coordinates from yellow to green in the concentration range of CA19-9 tested, improved quantification accuracy by compensating for matrix effects in serum. A linear detection range was achieved from 4.98 × 10⁻³ to 8.39 × 10² U mL⁻¹ in serum samples, with high specificity and reproducibility. Conclusions: The dual@nanoMIPs developed in this work enable a stable, sensitive, and specific detection of CA19-9 in minimally processed serum, offering a promising tool for longitudinal monitoring of cancer patients. Its ratiometric fluorescence design enhances reliability, supporting clinical decision-making in the follow-up of pancreatic cancer. Full article

Chinese lacquer, a historically significant bio-based coating, has garnered increasing attention in sustainable materials research due to its outstanding corrosion resistance, thermal stability, and environmental friendliness. Its curing process relies on the laccase-catalyzed oxidation and polymerization of urushiol to form a dense lacquer film. However, the stringent temperature and humidity requirements (20–30 °C, 70–80% humidity) and a curing period that can extend over several weeks severely constrain its industrial application. Recent studies have significantly enhanced the curing efficiency through strategies such as pre-polymerization control, metal ion catalysis (e.g., Cu²⁺ reducing drying time to just one day), and nanomaterial modification (e.g., nano-Al₂O₃ increasing film hardness to 6H). Nevertheless, challenges remain, including the sensitivity of laccase activity to environmental fluctuations, the trade-off between accelerated curing and film performance, and issues related to toxic pigments and VOC emissions. Future developments should integrate enzyme engineering (e.g., directed evolution to broaden laccase tolerance), intelligent catalytic systems (e.g., photo-enzyme synergy), and green technologies (e.g., UV curing), complemented by multiscale modeling and circular design strategies, to drive the innovative applications of Chinese lacquer in high-end fields such as aerospace sealing and cultural heritage preservation. Full article

Understanding the dynamics of phytoplankton size classes (PSCs), highly sensitive to environmental conditions in marine ecosystems, is crucial for comprehending variations in primary production and biogeochemical processes. Over the past decades, the littoral seas of Korea have undergone significant environmental shifts, yet long-term studies on PSC distribution remain limited. Employing a regionally developed deep neural network model and 20 years (2003–2022) of satellite ocean color data, we assessed spatiotemporal variability in dominant PSCs in the Yellow Sea (YS), South Sea of Korea (SS), and East/Japan Sea (EJS). Micro-size phytoplankton dominated turbid nearshore waters of the YS and western SS year-round, while nano-size phytoplankton were seasonally prevalent in the central YS and EJS. Pico-size phytoplankton exhibited strong summer dominance under warm, stratified, nutrient-depleted conditions, showing a sustained long-term expansion across all regions, particularly in the southwestern EJS. This expansion was closely linked to rising sea surface temperatures and changes in nutrient stoichiometry. The increasing dominance of smaller phytoplankton may reduce primary production, alter food web structure, and ultimately diminish fishery productivity. These findings provide new insight into climate-driven ecological shifts in marginal seas and underscore the need for integrated long-term monitoring to anticipate future ecosystem responses in a rapidly warming ocean. Full article

We present a hermetically sealed capacitive microelectromechanical system (MEMS) strain sensor designed for arterial pulse waveform extraction using the strain plethysmography (SPG) modality. The MEMS strain sensor features a small form factor of 3.3 mm × 3.3 mm × 1 mm, leverages a nano-gap fabrication process to improve the sensitivity, and uses a differential sensing mechanism to improve the linearity and remove the common mode drift. The MEMS strain sensor is interfaced with an application-specific integrated circuit (ASIC) to form a compact strain sensing system. This system exhibits a high strain sensitivity of 316 aF/µε, a gauge factor (GF) of 35, and a strain sensing resolution of 1.26 µε, while maintaining a linear range exceeding 700 µε. SPG signals have been reliably captured at both the fingertip and wrist using the MEMS strain sensor with high signal quality, preserving various photoplethysmography (PPG) features. Experimental results demonstrate that heart rate (HR) and heart rate variability (HRV) can be estimated from the SPG signal collected at the fingertip and wrist using the sensor with an accuracy of over 99%. Pulse arrival time (PAT) and pulse transit time (PTT) have been successfully extracted using the sensor together with a MEMS seismometer, showcasing its potential for ambulatory BP monitoring (ABPM) application. Full article

Constructing the surface structures of hydroxyapatite (HA) materials is a promising strategy for orchestrating the cell behaviors of bone marrow mesenchymal stem cells (BMSCs), beneficial for advancing BMSC-based tissue repair and regenerative therapies. The majority of previous strategies have focused on fabricating artificial micro-/nano-scale geometric topographies or patterns on HA surfaces. Yet, constructing surface crystal defects has received insufficient attention and application, despite their importance as highlighted by theoretical calculations. This is largely due to the instability of crystal defects, which tend to be eliminated during crystallization. Here, given the fact that stepped structures are rich in stable crystal defects along their edges and kinks, we crafted HA dishes featuring stepped surfaces and utilized them to establish cell culture models of BMSCs. The outcomes revealed that the stepped structures markedly altered the physicochemical properties of HA surfaces and affected the cytoskeleton structures, spreading area, cell morphology, and focal adhesions of BMSCs in the cell culture model, resulting in inhibited cell adhesion. Given that YAP is a key mechanical sensitive factor, and its nuclear translocation is closely tied to cytoskeletal reorganization, the nuclear translocation efficiency of YAP has been investigated. The results showed that a changed cell adhesion could affect the nuclear translocation efficiency of YAP, which would be an important reason for the change in proliferation and differentiation ability of BMSCs. This work not only enhances the understanding of the responses of BMSCs to HA surface structures but also facilitates the design and optimization of HA materials. Moreover, our manufacturing method is facile and efficient, positioning it to potentially integrate with other processing techniques for the more effective and precise regulation of BMSCs. Full article

Effective thermal management is essential for the safe and efficient operation of lithium-ion battery packs, particularly in compact, airflow-sensitive applications such as drones. This study presents a comprehensive thermal analysis of a 16-cell lithium-ion battery pack by exploring seven geometric configurations under airflow speeds ranging from 0 to 15 m/s and integrating nano-carbon-based phase change materials (PCMs) to enhance heat dissipation. A Computational Fluid Dynamics (CFD) approach was employed using Ansys Discovery and Workbench 2024 R1 to simulate airflow and heat transfer processes with high spatial resolution. Using high-fidelity 3D simulations, we found that the trapezoidal wide-base configuration, combined with a 5-inlet and 1-outlet airflow design, achieved the most balanced cooling performance across all speed regimes. This configuration maintained battery temperatures within the optimal operating range (∼45 °C) in both low- and high-speed airflow conditions, with a maximum temperature reduction of up to 8.3 °C compared to the standard square configuration. Additionally, PCM integration extended the thermal regulation duration to approximately 12.5 min, effectively buffering thermal spikes during peak loads. These findings underscore the critical role of CFD-driven geometric optimization and advanced material integration in designing high-efficiency, compact cooling systems for energy-dense battery applications in drones and portable electronics. Full article