Search Results (298)

Background: Primary cells derived from connective tissues contain mesenchymal stem/stromal cell (MSC)–like progenitors with chondrogenic potential relevant for cartilage repair. However, donor- and tissue-specific variability and the lack of robust, high-content analytical methods limit their translational use. Objectives: This study aimed to develop and optimize a high-content imaging workflow for quantitative evaluation of chondrogenesis in three-dimensional (3D) pellets derived from primary cells. Methods: Primary human cells isolated from cartilage were chondrogenically differentiated in vitro. A systematic optimization of immunofluorescence staining parameters was performed, including staining platform, enzymatic matrix digestion, non-specific site blocking, membrane permeabilization, and nuclear counterstaining. Type II collagen was detected using an Alexa Fluor 488–conjugated antibody, and pellets were analyzed using high-content non-confocal imaging. Fluorescence intensities were adjusted to the pellet area to account for size-dependent effects. Results: Staining directly in imaging plates enabled streamlined high-content analysis. Controlled pepsin-mediated matrix digestion markedly enhanced antibody penetration, while excessive digestion compromised pellet integrity. Extended bovine serum albumin blocking improved type II collagen signal intensity and homogeneity. Triton X-100 permeabilization increased detection sensitivity but occasionally induced structural disruption in weakly organized control pellets. The optimized protocol enabled clear discrimination between chondrogenic pellets and controls, with approximately threefold higher type II collagen signal in chondrogenic samples. Conclusions: This study establishes a high-content imaging–based workflow for quantitative assessment of 3D chondrogenesis from primary cells. The approach provides a rapid, scalable platform with direct relevance for in vitro screening, potency testing, and quality control in cartilage-oriented advanced therapy development. Full article

The integration of high-penetration renewable energy creates new requirements for cross-timescale peak shaving and for system robustness under extreme meteorological conditions. This study develops a dual-timescale capacity allocation method for pumped hydro storage (PHS), combining 8760 h chronological production simulation with monthly typical-day retrospective analysis. The model represents the operating limits of conventional units, nuclear power, hydropower, wind power, photovoltaic generation, tie-line exchange, and PHS energy shifting. On this basis, a stepwise capacity-sensitivity framework is established to minimize annualized comprehensive system cost while controlling renewable energy curtailment within a predefined planning threshold, rather than treating zero curtailment as an unconditional monthly hard constraint. Using long-term planning data from a coastal provincial power grid in southeastern China, the study compares the 2035 and 2040 planning scenarios. The results show that isolated typical-day models tend to overestimate PHS requirements because they disconnect chronological continuity and cross-day reservoir buffering. In 2035, the system presents a two-level seasonal capacity structure: 15,000 MW can support normalized operation in stable months, whereas the rigid boundary rises to 19,000 MW under extreme autumn high-wind conditions. In 2040, wind and photovoltaic capacity increase by approximately 20.01 GW compared with 2035, deepening low-net-load valleys and compressing seasonal regulation margins. Under the assumed planning boundary, the recommended PHS capacity converges to 23,000 MW. The proposed framework provides a practical reference for flexible resource planning in coastal power grids with deep renewable energy integration. Full article

Self-compacting concrete (SCC) is widely adopted in complex structural engineering due to its excellent flowability and filling capacity. However, in harsh corrosive environments, its complex internal pore structure can easily serve as a preferential pathway for the transport of aggressive media, leading to durability deterioration. This study systematically investigates the effects of chemical attack inhibitor (CAI) on the workability, mechanical properties, sulfate attack resistance, and chloride ion penetration resistance of SCC. The micro-mechanisms governing pore structure evolution are elucidated using low-field nuclear magnetic resonance (LF-NMR) and X-ray computed tomography (X-CT). At a CAI dosage of 2%, the fresh SCC exhibits a slump of 260 mm and slump flow of 720 mm, indicating excellent filling and gap-passing abilities. Meanwhile, the compressive strengths at 3 d, 7 d, and 28 d remain at a high level. After 120 sulfate wet-dry cycles, the strength loss rate is only 8.4%, with an erosion resistance coefficient exceeding 90%. In addition, the resistance to chloride ion penetration is significantly improved, with an electric flux of only 1331 C, which is considerably lower than that of the control group (1637 C). At the optimal dosage of CAI, the concrete exhibits a dense and uniform internal structure devoid of macroscopic defects or cracks, with minimized porosity, thus synergistically enhancing the resistance to sulfate attack and chloride attack. On the contrary, further increasing the CAI dosage markedly intensifies the inhibitory effect of organic components on cement hydration, leading to increased early-age defects and enhanced pore connectivity. Thus, an appropriate amount of CAI can effectively improve the overall performance of SCC, providing a solid experimental basis and theoretical support for its engineering application in harsh corrosive environments. Full article

Quantitative structure–activity relationship (QSAR) modeling has conventionally relied on expert-designed molecular descriptors to encode chemical structures. DeepSnap is a descriptor-free QSAR approach that converts prepared three-dimensional molecular conformers into image representations and feeds them directly into convolutional neural networks for activity prediction. This focused narrative review traces DeepSnap from its introduction in 2018 to its current state and places it within the broader landscape of descriptor-based QSAR, topology-based and 3D-aware graph neural networks, and related image-based or semi-image-based molecular representation approaches. Previous studies applied DeepSnap to Tox21 nuclear receptor and molecular initiating event endpoints, rat hepatic clearance, blood–brain barrier penetration, acute oral toxicity, and cosmetics–pharmaceutical compound classification. Across the DeepSnap series, image-based and descriptor-based predictions have provided complementary information, particularly in ensemble or consensus models. However, high or near-ceiling ROC–AUC values reported for selected endpoints should not be interpreted as indicating deterministic or universally generalizable predictions; rather, they should be considered in the context of endpoint-specific model development, image-rendering parameter optimization, possible class imbalance, split dependence, limited matched external replication, and incomplete benchmarking against modern molecular representation models. Limitations include a dependence on nonphysical rendering parameters, single- or representative-conformer input, incomplete matched benchmarking against 2D and 3D molecular representation models, and an interpretability gap addressed in part by CAM-family visualization in the AI-based Substance Hazard Integrated Prediction System (AI-SHIPS) and S-COPHY (a model developed by Shiseido for cosmetics–pharmaceutical compound classification). Future directions include standardized image-generation protocols, conformer-ensemble extensions, systematic interpretability analysis, matched benchmarking, and potential integration with graph-based and 3D-aware molecular learning approaches. Full article

Being capable of high-resolution imaging and non-contact measurement, Ground Penetrating Radar (GPR) is a promising technology for the detection of unexploded ordnance (UXO). However, UXO detection is severely hindered by clutter, particularly in environments with significant surface roughness where conventional suppression methods prove ineffective. To address this, we propose a polarimetric GPR clutter suppression method based on an improved non-convex Tensor Robust Principal Component Analysis (TRPCA) framework. Specifically, a polarization-aware tensor construction scheme is designed by stacking the HH and VV channel data. This approach exploits the strong inter-channel correlation of clutter to enhance its low-rank property, while highlighting the distinct sparse signatures of targets derived from their polarimetric responses. To further optimize tensor decomposition, we introduce a non-convex Tensor Adjustable Logarithmic Norm (TALN) to overcome the estimation bias inherent in the conventional Tensor Nuclear Norm (TNN). Serving as a tighter surrogate for tensor rank, the proposed TALN regularizer improves the approximation accuracy of the low-rank component, thereby ensuring a clearer separation between clutter and targets. The resulting non-convex optimization problem is efficiently solved using Alternating Direction Method of Multipliers (ADMM). Numerical simulations and laboratory experiments demonstrate that the proposed method suppresses strong clutter stemming from rough-surface reflections more effectively than existing methods, achieving a Signal-to-Clutter Ratio (SCR) improvement of over 20 dB. Full article

Herein, we report a simple procedure regarding the photodynamic therapy (PDT) treatment as a minimally invasive modality for treating superficial bladder cancer that utilizes a photosensitizer, light, and oxygen to generate cytotoxic reactive oxygen species (ROS). This study evaluates the histopathological and morphological changes induced by PDT in an ex vivo model of low-grade (LG) pTa non-muscle-invasive bladder cancer (NMIBC). We investigated the efficacy of exogenous protoporphyrin IX (PpIX) and Rose Bengal (RB) by incubating tissue samples (n = 30) with an oxygen-saturated solution of PpIX (1–3 mM) or RB (0.3–0.5 mM) for one hour. Since the criticism of using frozen tissue in research already exists, this framing explains how to mitigate those limitations. Thus, we use oxygen-saturated solutions PpIX and oxygen-saturated solutions of RB. We discussed a few aspects related to the use of frozen tissue in PDT. Frozen tissue preserves lipids critical for assessing membrane damage and maintains higher levels of metabolic markers like antioxidant molecules like glutathione and more likely lack factors such as metabolic activity, intact cell membranes, and oxygenation. It is critical to differentiate between “artifactual” changes and the “pathological” death of cells. Thus, we used histopathological microscopy observation typically used in daily clinical investigations to characterize cells before and after PDT. Following irradiation with the light dose of 72 J/cm² (410 nm or 532 nm at 300 mW for 15 min), hematoxylin–eosin staining revealed concentration-dependent apoptotic changes, including chromatin condensation, pyknosis, and nuclear fragmentation. While both agents induced cell death, RB demonstrated faster and more intense cytotoxicity than PpIX. These findings provide microscopic evidence of PDT-induced tumor destruction and suggest that RB is a potent candidate for further preclinical evaluation. At 410 nm (deep blue/violet), light penetration in biological tissue is very shallow, typically only around 0.3 to 1 mm; therefore, in a 2 mm thick tissue sample, most of the light would be absorbed within the first millimeter, with minimal light reaching the full depth of tissues. In this protocol, the generated ROS is used to destroy tumor tissue by attacking the cellular microenvironment directly. This led to immediate membrane disruption and lipid peroxidation. The proof-of-concept is an early-stage study designed to verify that a PDT treatment is feasible, safe, and biologically active in an ex vivo model of LG pTa NMIBC. Full article

Histone demethylases regulate epigenetic modifications and DNA damage repair in fungal pathogens, yet their specific functions in Magnaporthe oryzae remain poorly understood. This study identifies MoRph1, a JmjC domain-containing histone demethylase that interacts with the COMPASS complex. Targeted deletion of MoRph1 resulted in significantly reduced vegetative growth, impaired conidiation, and defective appressorium formation. The mutant displayed compromised appressorial turgor pressure due to delayed degradation of glycogen and lipid reserves, leading to inefficient host penetration and attenuated virulence on rice and barley. MoRph1 localized to the nucleus, and its absence caused increased nuclear abnormalities under DNA damage stress, suggesting impaired genome stability maintenance. Biochemical analysis confirmed that MoRph1 specifically demethylates histone H3 lysine 36 trimethylation. Transcriptome analysis revealed altered expression of genes associated with DNA replication, mismatch repair, and oxidative stress response. These results establish MoRph1 as a crucial epigenetic regulator coordinating fungal development, infection structure function, energy mobilization, and DNA damage repair. This study underscores the importance of chromatin-level regulation in fungal pathogenicity and provides a foundation for future evaluation of MoRph1 as a potential antifungal target. Full article

Following the massive power cut in Spain on 28 April 2025, questions have been raised about the reliability of energy generation infrastructure in the face of the variability of renewable energy sources. On the other hand, the market penetration of electric vehicles and their charging requirements implies the need for knowledge about the availability of electric generation technologies. This research work presents a macro-level analysis of the availability factor of electricity generation mix, applied to the case of Spain and based on data collected between 2019 and 2024. Using hourly generation and installed capacity data, a methodology is developed to estimate the seasonal and daily availability of the main generation technologies: photovoltaic, solar thermal, wind, hydroelectric, nuclear, combined cycle, coal and others. The analysis reveals that conventional sources, such as nuclear and combined cycles, exhibit low variability, with daily fluctuation of less than 1%. In contrast, renewable sources show significant variability. Photovoltaic availability increases from 22.6% ± 1.3% in the early morning to 57.8% ± 0.6% during summer afternoons, while solar thermal energy reaches a maximum of 78.5% ± 1.3% under the same conditions. The results highlight the uncertainty generated by the high penetration of renewable energy and the challenges posed by balancing generation with demand, particularly given new consumption patterns influenced, for example, by electric vehicles, battery storage and green hydrogen, among others. The integration of probabilistic planning frameworks into infrastructure development and the extension of this analysis to the provincial level, together with the incorporation of restriction and self-consumption scenarios involving constraints and self-consumption, will help to ensure the robust operation of the grid in the future. Full article

Wood is a sustainable material, but hygroscopicity can affect dimensional stability and mechanical durability. Recent research has increasingly focused on combining citric acid with various polyols as eco-friendly crosslinking systems to improve wood properties. Herein, a solvent-free and catalyst-free method was used to synthesize bio-based polyesters from citric acid and mannitol. In situ curing was carried out after vacuum-pressure impregnation of fast-growing poplar wood (Populus deltoides Marshall). Morphological characterization showed that the polyester filled the cell lumen and penetrated the cell wall structure. It was confirmed by Fourier Transform Infrared (FTIR) and cross-polarization/magic angle spinning (CP/MAS) ¹³C nuclear magnetic resonance (NMR) analysis that the polyester formed covalent ester bonds with wood hydroxyl groups, which indicated successful chemical grafting. The dimensional stability and mechanical properties of the modified wood were greatly improved. The parallel compressive strength of the grain reached 41.5 MPa, which was 41.7% higher than that of the untreated wood. This research adopted a citric acid–mannitol polyester, providing a sustainable, economical, and scalable approach for the development of high-performance, degradable wood composites for construction/furniture applications. Full article

Background/Objectives: Oral diseases remain among the most prevalent noncommunicable conditions worldwide, with biofilm-driven dysbiosis playing a central role in dental caries, gingivitis, periodontitis, and oral candidiasis. Curcumin has attracted considerable interest because of its anti-inflammatory, antioxidant, antimicrobial, and regenerative properties. However, its clinical use remains limited by poor water solubility, chemical instability, rapid metabolism, and low bioavailability. This review aimed to provide a comprehensive analysis of curcumin-based nanoformulations for oral health applications, with emphasis on their mechanistic actions, antibiofilm activity, and translational relevance. Methods: This review examined representative nanocarrier systems developed for curcumin delivery in oral health. These included polymeric nanoparticles, nanomicelles and nanoemulsions, solid lipid nanoparticles and nanostructured lipid carriers, nanogels, hydrogels, mucoadhesive films, and metallic or hybrid nanosystems. The analysis focused on molecular mechanisms of action, antimicrobial and antibiofilm effects against major oral pathogens, and key translational challenges. Results/Findings: Across the reviewed studies, nanoformulations consistently improved curcumin solubility, stability, tissue penetration, mucosal retention, and controlled release. Mechanistically, they enhanced anti-inflammatory activity through inhibition of nuclear factor kappa B (NF-κB), strengthened antioxidant defenses via the nuclear factor erythroid 2-related factor 2/heme oxygenase-1 (Nrf2/HO-1) axis, supported tissue repair and osteogenic responses, disrupted oral biofilms, and modulated local immune responses. Antimicrobial activity was reported against Streptococcus mutans, Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, and Candida albicans, with reduced exopolysaccharide production, impaired adhesion, and improved biofilm penetration. Conclusions: Curcumin-based nanoformulations represent promising adjunctive platforms for oral healthcare. However, their clinical translation still requires improved stability in the oral-environment standardized manufacturing and characterization, rigorous safety evaluation, and well-designed controlled clinical studies. Full article

China’s power sector is undergoing a complicated transformation characterized by intricate dependence on the dominant coal infrastructure and abundant renewable energy resources. This study assesses China’s carbon-neutral transition pathways for the period of 2024–2060 by using the “Establish Before Breaking” principle within a policy-informed, high-resolution energy system modeling framework. To examine the technological, economic, and environmental trade-offs of various carbon-neutral strategies, four scenarios (Reference (REF), Carbon Capture and Storage (CCS), Renewable-Based (REB), and Integrated (ING)) were developed, and their impacts were assessed through the application of the Low Emission Analysis Platform and the Next Energy Modeling (LEAP–NEMO) model. The results reveal that the ING scenario represents the most feasible and policy-consistent pathway, achieving an 88% renewable electricity share and a total installed capacity of approximately 8000 gigawatts (GW) by 2060. This pathway relies on a dual-track strategy that combines accelerated renewable deployment—supported by geographical complementarity and multi-regional Power-to-X (PtX) systems—with the strategic stabilization of conventional generation assets. The findings further demonstrate that retaining a small but critical share of flexible coal-CCS (0.2–0.5%) and nuclear capacity is necessary to address sub-daily variability, mitigate duck-curve effects, and ensure power system reliability under high renewable penetration. This integrated approach offers a systematic pathway for deep decarbonization within China’s unique energy context, ensuring a just, equitable, and sustainable transition. Full article

Radiopharmaceutical therapy (RPT) has emerged as a transformative modality in oncology, particularly for patients with metastatic or inoperable tumors. By leveraging molecularly targeted carriers conjugated to cytotoxic radionuclides, RPT enables precise delivery of ionizing radiation to tumor sites while minimizing off-target effects. Central to this approach are alpha (α) and beta (β) particle-emitting radionuclides. This review aims to provide a comprehensive overview of all clinically relevant alpha and beta emitters and incorporates the most recent advances from 2017–2025, offering a comprehensive and up-to-date perspective. Alpha and beta emitters hold significant promises for the future, especially in nuclear medicine, energy, and environmental monitoring. Medically, these emitters are at the forefront of targeted radiotherapy, offering new hope for cancer treatment. Alpha emitters such as Actinium-225 and Radium-223 are gaining attention for their high linear energy transfer, which allows them to effectively kill cancer cells while minimizing damage to surrounding healthy tissues. Beta emitters, including Lutetium-177 and Iodine-131, are already widely used for treating thyroid cancer, neuroendocrine tumors, and prostate cancer. They offer a longer range in tissue penetration than alpha particles, making them suitable for larger or more diffuse tumors. Alpha and beta emitters hold tremendous promise in targeted radiotherapy. However, current research is limited by an incomplete understanding of resistance pathways, insufficient long-term safety and efficacy data, and underdeveloped personalized treatment frameworks. As production technologies improve and safety protocols advance, these emitters will likely play an even more prominent role in both health care and scientific innovation. Full article

Under high renewable energy penetration, nuclear power units face significant challenges in peak regulation and market clearing due to constraints on minimum technical output and ramping capability. To address this issue, a long-term power system of Guangdong Province in 2035 is taken as the study case, and an energy–reserve co-clearing simulation framework based on Security-Constrained Unit Commitment (SCUC) and Security-Constrained Economic Dispatch (SCED) is established to systematically evaluate the clearing performance of nuclear power and the formation mechanism of residual electricity under multiple market scenarios. On this basis, a nuclear power-coupled Alkaline Electrolysis (AEL) hydrogen production pathway is proposed as a peak-shaving utilization option, and an economic assessment model for nuclear-based hydrogen production is developed to quantify the investment performance under different hydrogen production capacities and operating modes. The results indicate that the integration of an AEL hydrogen production system can effectively alleviate the rigidity of nuclear power output. Under the “12-3-48-3” flexible peak-shaving mode, the residual electricity available for hydrogen production increases by approximately 30% compared with a typical peak-shaving strategy. Under scenarios with low electricity prices and green hydrogen prices, when the hydrogen production capacity is configured at 50–100 MW, the investment payback period is approximately six years, and the project exhibits strong economic robustness against variations in the discount rate. These findings demonstrate that nuclear-based hydrogen production is economically feasible in future power systems with high renewable penetration, providing quantitative support for nuclear flexibility enhancement and the coordinated development of low-carbon energy systems. Full article

Integrating enhanced oil recovery (EOR) with geological carbon storage presents a dual-strategy solution for sustainable hydrocarbon production and greenhouse gas emission mitigation. CO₂ flooding, particularly under miscible conditions, is a pivotal technology in this endeavor. This study employs advanced in situ nuclear magnetic resonance (NMR) imaging to visually and quantitatively investigate the pore-scale mechanisms of CO₂ flooding in fractured carbonate rocks from a Kazakhstan oilfield. By establishing a novel correlation between NMR data and pore throat size distribution, we quantify the lower limit of pore throat mobilization—a key parameter for evaluating storage and displacement efficiency. Results show that miscible CO₂ flooding significantly reduces this limit to the submicron scale (0.1 μm) in matrix rocks, dramatically improving oil recovery from small pores. However, fracture networks dominate fluid flow, leading to early gas breakthrough and severely limiting CO₂ penetration and miscible displacement in the matrix. The study provides pore-scale insights for optimizing CO₂ injection strategies to maximize both hydrocarbon recovery and CO₂ storage potential in complex carbonate formations. The study elucidates the microscopic mobilization mechanisms and remaining oil distribution patterns during CO₂ flooding in volatile reservoirs. Moreover, it represents an environmentally friendly methodology for mitigating greenhouse gas emissions. Full article

To address the problems existing in nuclear reactor accident emergency training, a design scheme and system prototype of radiation detection training equipment for penetrating radiation fields in enclosed spaces, based on inertial sensors and wireless Bluetooth communication is proposed. First, the penetrating radiation field is modeled. On this basis, a calculation model of the neutron/γ dose equivalent rate is established. This model is based on the motion path of simulated radiation detection equipment. Second, the MPU6050 inertial sensor is designed and developed. It monitors the three-axis acceleration and three-axis angular acceleration values in real time. This enables the indoor positioning function of the simulated detection training equipment. The Digital Motion Processor (DMP) filtering algorithm is used to process the measured data. This improves the detection accuracy. Finally, a Bluetooth communication module is designed and developed. It transmits the detected position data to the main control computer in real time. The main control computer performs calculation and analysis to obtain the radiation intensity value. This value is sent to the Arduino controller. The Arduino controller controls the display of the value on the liquid crystal screen. Experimental verification is carried out. Experimental verification indicates that the maximum error of the system’s three-dimensional spatial positioning is 0.08 m, the mean relative error of the radiation dose rate simulation is 4.81%, and the maximum relative error is 7.8%. The system relatively accurately achieves radiation dose simulation and radiation source localization according to different working modes, providing a high cost-effectiveness training method for radiation detection training with high safety and good economy. Full article