Search Results (5,432)

Against the backdrop of growing demand for rapid soil testing technologies in precision agriculture, this study proposes a detection method based on pyrolysis-electronic nose and machine olfaction signal analysis to achieve precise measurement of key soil nutrients. An electronic nose system comprising 10 metal oxide semiconductor gas sensors was constructed to collect response signals from 112 black soil samples undergoing pyrolysis at 400 °C. By extracting time-domain and frequency-domain features from sensor responses, an initial dataset of 180 features was constructed. A novel feature fusion method combining Pearson correlation coefficients (PCC) with recursive feature elimination cross-validation (RFECV) was proposed to optimize the feature space, enhance representational power, and select key sensitive features. In predicting soil organic matter (SOM), total nitrogen (TN), available potassium (AK), and available phosphorus (AP content, we compared support vector machines (SVM), support vector machine-random forest models (SVM-RF), and particle swarm optimization-enhanced support vector machine-random forest models (PSO-SVM-RF). Results indicate that PSO-SVM-RF demonstrated optimal performance across all nutrient predictions, achieving a coefficient of determination (R²) of 0.94 for SOM and TN, with a performance-to-bias ratio (RPD) exceeding 3.8. For AK and AP, R² improved to 0.78 and 0.74, respectively. Compared to the SVM model, the root mean square error (RMSE) decreased by 25.4% and 21.6% for AK and AP, respectively, with RPD values approaching the practical threshold of 2.0. This study validated the feasibility and application potential of combining electronic nose technology with a time-frequency domain feature fusion strategy for precise quantitative analysis of soil nutrients, providing a new approach for soil fertility assessment in precision agriculture. Full article

Background and Objectives: The aim of this study is to employ quantitative proteomics to elucidate the molecular mechanism and signaling pathways modulated by plasma rich in growth factors (PRGF) in a murine model of geographic atrophy (GA)-like retinal degeneration. Materials and Methods: C57BL/6J mice were used as a model GA-like retinal degeneration by a single systemic NaIO₃ administration. Animals were divided into three groups: Control (PBS), Disease (NaIO₃ + PBS), and PRGF-treated (NaIO₃ + PRGF). After 7 days, retinas and retinal pigment epithelium were collected for proteomic analysis. Proteins were extracted, digested using the FASP method, and analyzed by Data-Independent Acquisition (DIA-PASEF) mass spectrometry; data were processed with DIA-NN and statistically analyzed with Perseus. Functional pathway analysis was performed using Ingenuity Pathway Analysis. Results: A total of 6511 proteins were identified. The Disease model showed the expected deregulation of pathways related to oxidative stress, inflammation, and fibrosis. Comparison between the PRGF and Control groups showed that PRGF significantly reduced oxidative and cellular stress proteins/pathways. In the same way, when PRGF and Disease groups were compared, PRGF treatment showed a significant reduction in pathways associated with inflammation, oxidative stress, and cellular stress. PRGF also activated several homeostatic pathways not only related to neuroprotective pathways but also with the lipid deposition (drusen) reduction. All these results suggest that PRGF treatment exerts a protective effect against NaIO₃-induced retinal damage. Conclusions: These findings suggest that PRGF effectively mitigates the degenerative effects of NaIO₃ by activating specific protective and compensatory signaling pathways in the retina. PRGF is indicated as a promising new therapeutic option for ameliorating age-related macular degeneration progression. Full article

Regarding the deep integration of China’s “dual carbon” strategy with high-quality development, the objectives of practicing ESG principles and fostering new quality productive forces are highly aligned, which constitute an endogenous driving force for corporate sustainability. Government subsidies, by providing directional incentives and guiding resource allocation, further facilitate the integration and agglomeration of factors that underpin new quality productive forces. Yet, existing research offers limited theoretical explanation and empirical evidence regarding the relationship among these three dimensions and the mechanisms through which their effects are transmitted. To fulfill the research, this study uses resources from A-share listed enterprises in China between 2015 and 2023. From the perspective of government subsidies and grounded in signaling theory and resource allocation theory, we construct an index system to measure new quality productive forces and employ a two-way fixed effects model alongside Bootstrap mediation test to investigate the mechanisms and transmission pathways linking ESG performance, government subsidies, and new quality productive forces. The results reveal that strong ESG performance substantially enhances the new quality productive forces, and the assertion stays steadfast after addressing endogeneity concerns and conducting multiple robustness checks. Moreover, ESG performance enhances firms’ access to government subsidies, which subsequently has a partial mediation effect. The analysis also uncovers heterogeneity: the beneficial impact of ESG performance is more salient among small and medium-sized firms as well as firms in eastern regions. This study contributes to the literature by extending the theoretical framework on the correlation between ESG performance and new quality productive forces, while also offering practical insights for advancing corporate ESG practices and refining government subsidy policies. Full article

Ratoon rice cultivation is an efficient production system that achieves a second harvest from the stubble of the main crop, but its yield potential is largely constrained by variation in axillary bud regeneration capacity. Here, we identify OsPM19L, a plasma membrane–localized AWPM-19 domain protein, as a key regulator of rice ratooning ability. Transcriptome analysis revealed higher OsPM19L expression in strong-regeneration cultivars, followed by a sharp decline after harvest. Promoter assays and hormonal treatments demonstrated that OsPM19L is strongly induced by ABA and functions as a positive regulator in ABA signaling. Under field conditions, ospm19l mutants exhibited increased tiller number but reduced ratooning index, whereas OsPM19L-OE plants showed the opposite pattern, indicating stage-specific regulation of tillering and regeneration. Hormone profiling and gene expression analyses showed that OsPM19L is associated with altered levels of multiple phytohormones in regenerating axillary buds, showing higher CK and GA levels and lower IAA and ABA levels in OsPM19L-OE compared with the wild type. Consequently, OsPM19L appears to facilitate dormancy release and enhance early axillary bud growth during the ratoon season. These findings indicate OsPM19L may act as a central regulator linking ABA signaling with hormonal cross-talk, providing new insights into the molecular control of regeneration and potential targets for improving ratoon rice productivity. Full article

Background/Objectives: Difficult-to-treat epileptic syndromes include conditions typically emerging in the first years of life and are characterized by a high rate of drug refractoriness. This study aimed to better define the safety profile of drugs used as adjunctive therapies for seizures associated with these syndromes using real-world pharmacovigilance data. Methods: We retrospectively analyzed the publicly available data regarding Individual Case Safety Reports (ICSRs), presenting stiripentol, cannabidiol, or fenfluramine as suspected drugs, reported on the Eudravigilance database until the third quarter of 2024. Data were evaluated with descriptive analyses and then with disproportionality measures, including the reporting odds ratio. Results: A total of 5986 ICSRs met the inclusion criteria (71.6% from cannabidiol, 14.5% fenfluramine, and 13.9% stiripentol). Significantly higher probabilities of reporting Cardiac disorders, Vascular disorders, and Respiratory, thoracic, and mediastinal disorders were observed with fenfluramine. Cannabidiol was associated with Product issues, whereas stiripentol was associated with injury, poisoning, procedural complications, Metabolism and nutrition disorders, and Blood and lymphatic system disorders. Conclusions: Our analysis did not highlight new and unexpected serious safety signals but confirmed the need to strictly monitor patients for the risk of adverse events. However, further prospective studies are required to better clarify the safety profile of these drugs in order to optimize their use. Full article

Thanks to both endogenous and exogenous antioxidants (AOs), the antioxidant defense system ensures redox homeostasis, which is crucial for protecting the body from oxidative stress and maintaining overall health. The food industry also exploits the antioxidant properties to prevent or delay the oxidation of other molecules during processing and storage. There are many classical methods for assessing antioxidant capacity/activity, which are based on mechanisms such as hydrogen atom transfer (HAT), single electron transfer (SET), electron transfer with proton conjugation (HAT/SET mixed mode assays) or the chelation of selected transition metal ions (e.g., Fe²⁺ or Cu¹⁺). The antioxidant capacity (AOxC) index value can be expressed in terms of standard AOs (e.g., Trolox or ascorbic acid) equivalents, enabling different products to be compared. However, there is currently no standardized method for measuring AOxC. Nanoparticle sensors offer a new approach to assessing antioxidant status and can be used to analyze environmental samples, plant extracts, foodstuffs, dietary supplements and clinical samples. This review summarizes the available information on nanoparticle sensors as tools for assessing antioxidant status. Particular attention has been paid to nanoparticles (with a size of less than 100 nm), including silver (AgNPs), gold (AuNPs), cerium oxide (CeONPs) and other metal oxide nanoparticles, as well as nanozymes. Nanozymes belong to an advanced class of nanomaterials that mimic natural enzymes due to their catalytic properties and constitute a novel signal transduction strategy in colorimetric and absorption sensors based on the localized surface plasmon resonance (LSPR) band. Other potential AOxC sensors include quantum dots (QDs, <10 nm), which are particularly useful for the sensitive detection of specific antioxidants (e.g., GSH, AA and baicalein) and can achieve very good limits of detection (LOD). QDs and metallic nanoparticles (MNPs) operate on different principles to evaluate AOxC. MNPs rely on optical changes resulting from LSPR, which are monitored as changes in color or absorbance during synthesis, growth or aggregation. QDs, on the other hand, primarily utilize changes in fluorescence. This review aims to demonstrate that, thanks to its simplicity, speed, small sample volumes and relatively inexpensive instrumentation, nanoparticle-based AOxC assessment is a useful alternative to classical approaches and can be tailored to the desired aim and analytes. Full article

In this work, a stable silver nanoparticle (AgNPs) with strong surface plasmon resonance absorption (Abs) signals was synthesized using light-wave technology. In the absence of aptamers, AgNPs can aggregate in a given concentration of salt solution, resulting in significant changes in color. After adding the aptamer (Apt), it was observed that the aptamer can coordinate with AgNPs and adsorb on the surface of AgNPs, thereby maintaining the stability of the nanosol. In the presence of mercury ions (Hg²⁺), their high-affinity reaction with the aptamer compromised the latter’s protective effect on AgNPs, causing the color of the system to change again. Based on this, a simple and rapid new Abs method for detecting Hg²⁺ can be constructed. The linear range was 2.5 × 10⁻³–10.00 μmol/L, and the detection limit (DL) of the system was 2.03 nmol/L. Full article

Temperature offers a simple yet powerful signal to program cellular behavior. Here, we engineered and characterized a set of temperature-dependent genetic circuits that integrate RNA thermometers with site-specific DNA recombinases to achieve precise, irreversible control of gene expression. Using the serine recombinase Bxb1 placed under the control of the Salmonella FourU RNA thermometer, we demonstrate how promoter strength critically defines thermal sensitivity: weak promoters’ activity clears ON/OFF transitions, while strong promoters lead to continuous, quasi-temperature-independent recombination. Furthermore, temperature pulse duration and growth phase of cell culture were found to modulate recombination efficiency, providing additional layers of control. We illustrate the potential of this framework through proof-of-concept applications, including (i) the generation of spatial expression patterns on 2D surfaces via localized heating, (ii) a paper-based device capable of recording temperature gradients as stable genetic outputs, and (iii) a temperature-triggered lysis system for controlled cellular release. Together, these results establish temperature-regulated recombinase circuits as versatile and robust tools for programmable, spatially resolved, and irreversible control of gene expression, paving the way for new applications in synthetic biology, biosensing, and bioproduction. Full article

Organ fibrosis is a progressive and often irreversible pathological process characterized by excessive deposition of extracellular matrix, leading to tissue dysfunction and failure. Despite its significant impact on various organ systems, available antifibrotic therapies remain limited. This review focuses on novel therapeutic approaches to inhibit fibrosis and improve clinical outcomes. Current strategies include small molecule inhibitors, monoclonal antibodies targeting fibrosis mediators, gene therapies, and cell-based approaches, including mesenchymal stem cells and induced pluripotent stem cells. In addition, the development of innovative drug delivery systems and combination therapies involving pulsed magnetic fields (PMFs) opens new possibilities for increasing the precision and efficacy of treatment. In recent years, multiomic approaches have enabled a better understanding of fibrosis mechanisms, facilitating the personalization of therapy. The role of artificial intelligence in drug discovery has also increased, as exemplified by models that support the design of small-molecule inhibitors currently undergoing clinical evaluation. This review discusses key signaling pathways involved in fibrosis progression, such as TGF-β, p38 MAPK, and fibroblast activation, as well as novel therapeutic targets. Although clinical trial results indicate promising potential for new therapies, challenges remain in optimizing drug delivery, considering patient heterogeneity, and ensuring long-term safety. The future of fibrosis therapy relies on integrating precision medicine, combination therapies, and molecularly targeted strategies to inhibit or even reverse the fibrosis process. Further intensive interdisciplinary collaboration is required to successfully implement these innovative solutions in clinical practice. Full article

Quorum sensing (QS) is a unique form of communication that exists among microbial communities. This system enables microbial cells to achieve behavioral coordination by generating and perceiving specific QS signaling molecules. This “chemical dialogue” allows microorganisms to synchronously express specific genes, thereby regulating group-level functions such as biofilm formation, virulence factor production, antibiotic biosynthesis, and metabolic coordination. Recently, the livestock industry has faced a multitude of challenges, including antibiotic resistance, environmental impact, and production efficiency. QS-based technologies have emerged as novel strategies to address these challenges simultaneously. It is important to note that a key principle of this strategy is that treatments should focus on regulating and modulating microbial QS systems rather than broadly inhibiting them. Therefore, the application of QS-based technologies provides new technical approaches to address core challenges in sustainable livestock production, including alternatives to antibiotics, improved farming efficiency, and environmentally friendly management. Moreover, it contributes to the achievement of carbon neutrality objectives by reducing methane emissions in ruminants through targeted inhibition of methanogen QS. This review systematically examines the biosynthesis mechanisms and regulatory features of the three core QS signaling molecules, with a focus on their practical applications in monogastric animal production, ruminant production, and aquatic animal production. It also explores the interdisciplinary innovative applications of QS-based technologies across multiple fields. By analyzing current research limitations and industrialization bottlenecks, this review outlines key future research directions and development challenges, aiming to provide a reference for the widespread application of QS-based technologies in animal production. Full article

Elevation Digital Beamforming (DBF) technology is key to achieving high-resolution wide-swath (HRWS) imaging in spaceborne Synthetic Aperture Radar (SAR) systems. However, multi-channel DBF-SAR systems face a prominent conflict between the need for real-time channel error calibration and the constraints of limited on-board hardware resources. To address this bottleneck, this paper proposes a real-time channel error calibration method based on Fast Fourier Transform (FFT) pulse compression and introduces a “calibration-operation” dual-mode control with a parameter-persistence architecture. This scheme decouples high-complexity computations by confining them to the system initialization phase, enabling on-board, real-time, closed-loop compensation for multi-channel signals with low resource overhead. Test results from a high-performance Field-Programmable Gate Array (FPGA) platform demonstrate that the system achieves high-precision compensation for inter-channel amplitude, phase, and time-delay errors. In the 4-channel system validation, the DBF synthesized signal-to-noise ratio (SNR) improved by 5.93 dB, reaching a final SNR of 44.26 dB. This performance approaches the theoretical ideal gain and significantly enhances the coherent integration gain of multi-channel signals. This research fully validates the feasibility of on-board, real-time calibration with low resource consumption, providing key technical support for the engineering robustness and efficient data processing of new-generation SAR systems. Full article

Ovarian aging (OA) results from the senescence of different cell types present in the ovary, decreasing female fertility and quality of life and augmenting the risk of a variety of fertility-unrelated pathological conditions. The changes observed in the ovarian cells are accompanied by changes occurring in various elements of the hypothalamic–pituitary–ovarian (HPO) axis, the complex endocrine system that regulates the female reproductive cycle. Issues pertaining to the HPO axis have been addressed in animal models via hormonal treatments with preparations inhibiting ovarian follicular recruitment at the level of the receptors of gonadotropin-releasing hormone (GnRH)-secreting neurons, mainly acting on glutamate- and gamma-aminobutyric acid (GABA)-driven signaling. GnRH agonists and antagonists have also been used in women exposed to chemotherapeutics. HPO-independent OA can be delayed through the administration of different antioxidants and mitochondria-protecting agents, among which melatonin has been shown to be particularly useful. Other therapeutic approaches used with success in women include hormonal and growth factor (GF) modulators, such as growth hormone (GH), insulin-like growth factor 1 (IGF-1), vascular endothelial growth factors (VEGF), and dehydroepiandrosterone (DHEA), and the development of patient-tailored combination-based therapies (IGF-1 + VEGF + DHEA) has also been suggested. Intraovarian injection of autologous platelet-rich plasma (PRP), mitochondrial donation through pronuclear transfer, and ovarian tissue cryopreservation and autotransplantation have also yielded promising results in women, and their use can preserve not only fertility but also the ovarian endocrine function. Personalized mixtures of specific agents (desatinib, quercetin, rapamycin, metformin, resveratrol, melatonin, and coenzyme Q10) targeting different cell types in the ovary are currently under investigation. Overall, this review aims to present a global view of the subject, uniting the physiological and molecular background of this pathology with the history and development of potential treatment strategies and new perspectives in this domain. As such, this study may be helpful both to clinicians facing problems resulting from OA and to researchers pursuing further developments in this field. Full article

Industrial electric motors powered by variable frequency drives (VFDs) offer better controllability as compared to the conventional sinusoid-fed motors. However, the switching transients of VFDs induce shaft voltage in electric motors, which can lead to bearing failure. This may cause the machine to shut down and pose a serious threat to the system’s reliability. Several shaft voltage mitigation strategies are suggested in the literature, including insulated bearings, grounding brushes, copper shields, and filters. Although mitigation strategies have been extensively studied, shaft voltage signal processing remains relatively underexplored. This review introduces diffusion models (DMs), a new generative learning technique, as an effective solution for processing shaft voltage signals. These models are good at reducing noise, handling uncertainty, and capturing complex patterns over time. DMs offer robust performance under dynamic conditions as compared to traditional machine learning (ML) and deep learning (DL) techniques. In summary, the review outlines the sources and causes of shaft voltage, its existing mitigation strategies, and the theory behind DMs for shaft voltage analysis. Thus, by combining insights from electrical engineering and artificial intelligence (AI), this work addresses an important gap in the existing literature and provides a strong path forward for improving the reliability of industrial motor systems. Full article

Multimodal perception for student-state monitoring is difficult to deploy in rural classrooms because sensors are noisy and computing resources are highly constrained. This work targets these challenges by enabling noise-resilient, multimodal, real-time student-state recognition on low-cost edge devices. We propose LightEdu-Net, a sensor-noise-adaptive Transformer-based multimodal network that integrates visual, physiological, and environmental signals in a unified lightweight architecture. The model incorporates three key components: a sensor noise adaptive module (SNAM) to suppress degraded sensor inputs, a cross-modal attention fusion module (CMAF) to capture complementary temporal dependencies across modalities, and an edge-aware knowledge distillation module (EAKD) to transfer knowledge from high-capacity teachers to an embedded-friendly student network. We construct a multimodal behavioral dataset from several rural schools and formulate student-state recognition as a multimodal classification task with explicit evaluation of noise robustness and edge deployability. Experiments show that LightEdu-Net achieves 92.4% accuracy with an F1-score of 91.4%, outperforming representative lightweight CNN and Transformer baselines. Under a noise level of 0.3, accuracy drops by only 1.1%, indicating strong robustness to sensor degradation. Deployment experiments further show that the model operates in real time on Jetson Nano with a latency of 42.8 ms (23.4 FPS) and maintains stable high accuracy on Raspberry Pi 4B and Intel NUC platforms. Beyond technical performance, the proposed system provides a low-cost and quantifiable mechanism for capturing fine-grained learning process indicators, offering new data support for educational economics studies on instructional efficiency and resource allocation in underdeveloped regions. Full article

In recent years, polymer-mediated signal amplification has drawn wide attention in bioelectronic sensing. With the rapid progress of biosensing and flexible electronics, polymers with excellent electron–ion transport properties, tunable molecular structures, and good biocompatibility have become essential materials for enhancing detection sensitivity and interfacial stability. However, current sensing systems still face challenges such as signal attenuation, surface fouling, and multi-component interference in complex biological environments, limiting their use in medical diagnosis and environmental monitoring. This review summarizes the progress of conductive polymers, molecularly imprinted polymers, hydrogels, and composite polymers in medical diagnosis, food safety, and environmental monitoring, focusing on their signal amplification mechanisms and structural optimization strategies in electronic transport regulation, molecular recognition enhancement, and antifouling interface design. Overall, polymers improve detection performance through interfacial electronic reconstruction and multidimensional synergistic amplification, offering new ideas for developing highly sensitive, stable, and intelligent biosensors. In the future, polymer-based amplification systems are expected to expand in multi-parameter integrated detection, long-term wearable monitoring, and in situ analysis of complex samples, providing new approaches to precision medicine and sustainable environmental health monitoring. Full article