Search Results (159,807)

This article presents a systematic review of the ecophysiological mechanisms underpinning the essential role of plant-growth-promoting microorganisms (PGPMs) in improving rice yield and quality. The scientific literature is thoroughly reviewed, highlighting how PGPMs positively influence the growth, development, and health of rice plants. Key aspects, such as nitrogen fixation, nutrient solubilization, hormone production, and disease resistance induction, are emphasized. Additionally, technological advancements related to PGPM use are analyzed, including the identification of effective strains, the formulation of enhanced biofertilizers, and genetic engineering. The article concludes that PGPMs represent a promising tool with which to boost the sustainability and productivity of rice cultivation, providing a robust foundation for future research and practical applications in a field crucial to global food security. Full article

Drug abuse is a major public problem in the workplace, traffic, and forensic issues, which requires a standardized test device to monitor on-site drug use. For field testing, the most important requirements are portability, sensitivity, non-invasiveness, and quick results. Motivated by this problem, a point of care (POC) test based on lateral flow assay (LFA) was developed for the detection of cocaine (COC) and methamphetamine (MET) in saliva which has been selected as the matrix for this study due to its rapid and non-invasive collection process. In the design strategy of an LFA test, the use of gold nanoparticles (AuNPs) with strong optical properties has been combined with the advantages of selecting aptamers under in vitro conditions, making it a highly specific and stable recognition probe for the detection of small molecules in saliva. The developed aptamer-based LFA in a competitive format, was able to detect COC and MET in synthetic saliva at concentrations as low as 5.0 ng/mL. After analytical performance studies, the test system also detected COC and MET in real patient samples, which was verified by chromatographic methods. Full article

The aim of this research was to obtain two-layer polymer composites with favorable mechanical and functional properties. The composites consisted of one lower layer of polymer with less elastic properties, containing no admixtures, and one upper layer of polymer with more elastic properties, containing plant admixtures, in the amount of 10% by weight of either goldenrod (Solidago virgaurea L.), or of turmeric (Curcuma longa L.). The admixtures S. virgaurea and C. longa were intended to introduce new biodegradable and medicinal properties without causing too much deterioration of physical or mechanical properties. Some polymer composites additionally contained magnetic particles in the form of carbonyl iron (Fe) in the amount of 20% by weight. The tests of mechanical tensile strength of the composites, water absorption, frost resistance, and surface contact angle were performed. Microscopic examinations determined the roughness of the cross-sectional surfaces. A constant magnetic field with magnetic induction B, which was an additional external factor changing the properties and structure of two-layer polymer composites, was also used in the research. Full article

The neuropathological diagnosis of Alzheimer’s disease (AD) relies on amyloid beta (Aβ) deposition in brain tissues. To study the relationship between Aβ deposition and brain structure, as determined using ¹¹C-Pittsburgh compound B (PiB) and magnetic resonance imaging (MRI), respectively, we developed a regression model with PiB and MRI data as the predictor and response variables, respectively, and proposed a regression method for studying the association between them based on a supervised sparse multivariate analysis with dimension reduction based on a composite paired basis function. By applying this method to imaging data of 61 patients with AD (age: 55–85), the first component showed the strongest correlation with the composite score, owing to the supervised feature. The spatial pattern included the hippocampal and parahippocampal regions for MRI. The peak value was observed in the posterior cingulate and precuneus for PiB. The differences in PiB scores among the diagnosis groups 12 months after PiB imaging were significant between the normal and AD groups (p = 0.0284), but not between the normal and mild cognitive impairment (MCI) groups or the MCI and AD groups (p = 0.3508). Our method may facilitate the development of a dementia biomarker from brain imaging data. Scoring imaging data allows for visualization and the application of traditional analysis, facilitating clinical analysis for better interpretation of results. Full article

Introduction and objective: Rapid and efficient interpretation of echocardiographic findings is critical in clinical decision-making. This study aimed to design and validate a new graphical method, called CARDIOBOX, to represent echocardiographic findings in dogs. Methods: A prospective, observational, exploratory cohort study was conducted over three years. The design of CARDIOBOX was based on baseline values obtained from 802 healthy dogs and 2165 ill dogs. Using these data, a graph consisting of nine boxes was built to show the intervals of the different echocardiographic measurements. Validation of the method was performed by a survey of 55 veterinarians, who compared the use of CARDIOBOX with the use of numerical tables. Results: CARDIOBOX demonstrated significantly faster interpretability (p < 0.05) without reducing its effectiveness. In addition, the staff surveyed considered it easy to use and interpret. Conclusions: The introduction of CARDIOBOX emerges as a resource that facilitates rapid and efficient interpretation of echocardiographic findings in dogs. This new graphical method is presented as a valuable tool for veterinary professionals in clinical decision-making in the field of veterinary cardiology. Full article

China, the world’s largest egg producer, faces challenges of protein feed shortages and nitrogen pollution from manure. Low-protein diets (LPDs) offer potential solutions, but their adoption by small-scale farmers is uncertain. This study used surveys, meta-analysis, life-cycle assessment, and life-cost analysis to address these gaps. A field survey in Quzhou County (a typical representative of small- and medium-scale farmers in China’s egg farming industry) found that 84% of egg farmers were unfamiliar with LPDs and believed higher protein levels were better. On average, pre-laying and late-laying diets exceeded national LPD recommendations by 0.3% and 0.5% crude protein (CP), respectively. The main barriers to LPD adoption were perceived low quality, lack of veterinary recommendations, and limited technical support. A meta-analysis of 30 studies (published before July 2024) showed that reducing CP by less than 1% did not compromise productivity. Local LPD demonstrations and training improved farmer confidence. Results indicated a 10% reduction in the nitrogen footprint and a 115% increase in earnings for LPD-demonstration farmers. The study suggests a coupled pathway integrating research and technology diffusion, highlighting the need for collaboration among scientists, feed companies, and technical experts to overcome misconceptions and promote LPD adoption. This integrated framework offers valuable insights for sustainable agricultural development in China and other resource-limited countries. Full article

This study evaluates the feasibility of using Haralick texture analysis on low-field, T2-weighted MRI images for detecting prostate cancer, extending current research from high-field MRI to the more accessible and cost-effective low-field MRI. A total of twenty-one patients with biopsy-proven prostate cancer (Gleason score 4+3 or higher) were included. Before transperineal biopsy guided by low-field (58–74mT) MRI, a radiologist annotated suspicious regions of interest (ROIs) on high-field (3T) MRI. Rigid image registration was performed to align corresponding regions on both high- and low-field images, ensuring an accurate propagation of annotations to the co-registered low-field images for texture feature calculations. For each cancerous ROI, a matching ROI of identical size was drawn in a non-suspicious region presumed to be normal tissue. Four Haralick texture features (Energy, Correlation, Contrast, and Homogeneity) were extracted and compared between cancerous and non-suspicious ROIs. Two extraction methods were used: the direct computation of texture measures within the ROIs and a sliding window technique generating texture maps across the prostate from which average values were derived. The results demonstrated statistically significant differences in texture features between cancerous and non-suspicious regions. Specifically, Energy and Homogeneity were elevated (p-values: <0.00001–0.004), while Contrast and Correlation were reduced (p-values: <0.00001–0.03) in cancerous ROIs. These findings suggest that Haralick texture features are both feasible and informative for differentiating abnormalities, offering promise in assisting prostate cancer detection on low-field MRI. Full article

After wheat harvesting in coastal saline–alkali land, when the straw is returned to the field and the soil is rotary tilled, the lack of reliable discrete element simulation parameter models restricts the optimization and improvement of special tillage and land preparation equipment for saline–alkali land to some extent. In this study, the Hertz–Mindlin with JKR model was used to calibrate the discrete element simulation parameters. Taking the soil-wheat crop residue mixture’s angle of repose as the test index, four groups of parameters that significantly affect the angle of repose and their optimal value ranges were screened out through the Plackett–Burman test and the steepest ascent test. Then, the Box–Behnken test was conducted to obtain the quadratic regression model of the significant parameters and the angle of repose, and the optimal values of the significant parameters were obtained. The optimal parameter combination was used for simulation tests, and the relative errors between the measured values and the simulation test values of the angle of repose and the wheat residue coverage rate were 0.74% and 1.34%. The reliable parameters provide a theoretical basis for the optimization and improvement of the equipment for soil preparation in saline–alkali land. Full article

The soluble interleukin-2 receptor (sIL-2R) is a novel biomarker associated with a variety of immune-mediated diseases. It is produced through the proteolytic cleavage of the membrane-bound interleukin-2 receptor α-chain on activated T lymphocytes; hence, its increase reflects T-cell activation and immune dysregulation. Elevated sIL-2R levels are frequently documented in conditions such as rheumatoid arthritis, systemic lupus erythematosus, sarcoidosis, relapsing polychondritis, histiocytosis, hemophagocytic lymphohistiocytosis, lymphomas, and graft-versus-host disease, suggesting a potential role in monitoring disease activity and progression. However, sIL-2R levels may increase in the context of immune response to infections and malignancies, requiring careful interpretation. It is essential to determine whether elevated levels of this marker within specific ranges could suggest a specific entity, due to the implications this may have for the management of patients. This case-based review presents five patients with different immune-mediated diseases, highlighting how these different conditions can present with characteristic ranges of sIL-2R elevation. By integrating clinical findings with sIL-2R measurements, we emphasize the biomarker’s utility in guiding diagnosis, as well as monitoring disease activity and determining prognosis, which can enhance clinical decision-making and patient management in rheumatology and related fields. Full article

Terahertz radiation patterns can be registered using various detectors; however, in most cases, the scanning resolution is limited. Thus, we propose an alternative method for the detailed scanning of terahertz light field distributions after passing simple and complex structures. Our method relies on using a dielectric waveguide to achieve better sampling resolution. The optical properties of many materials were analyzed using time-domain spectroscopy. A cyclic olefin copolymer (COC) was chosen as one of the most transparent. This study contains a characterization of the losses introduced by the waveguide and a discussion of the setup’s geometry. As a structure introducing the radiation pattern, a 2D quasi-periodic amplitude grating was chosen to observe the Talbot effect (self-imaging). Moreover, some interesting physical phenomena were observed and discussed due to the possibility of detailed scanning, with subwavelength resolution, registering the terahertz wavefront changes behind the structure. Full article

The Panjin Wetland is a complex ecosystem comprising coastal and inland wetland. It has an important function in wetland conservation and ecological. For this research, we quantified the landscape type changes in Panjin Wetland from 1992–2022, and analyzed the interaction between the combined PLUS and InVEST models to predict the future evolution of spatial and temporal patterns of habitat quality (HQ) and landscape patterns in Panjin Wetland. The results showed the following: (1) The change in natural wetland area from 1992 to 2022 generally showed a decreasing trend, the landscape patterns showed a trend of fragmentation. In 2032, the ecological protection scenarios showed an increase of 79.51 km² of natural wetland, while the other scenarios showed a decrease. (2) In 2022, the average habitat quality score is 0.441, and in 2032, the average habitat quality scores in the natural development scenarios, farmland protection scenarios, ecological protection scenarios, and economic development scenarios are 0.427, 0.448, 0.438, and 0.416, respectively. (3) The outcomes of this study offer insights into the sustainable management and rational development of coastal wetland, thereby contributing to the existing body of knowledge in the field of coastal wetland research, particularly in the areas of land planning and forecasting. Full article

This study aims to explore the application of artificial intelligence (AI) technology in the preservation and exhibition of artworks, with the “Exhibition Environment Status Detection Device and System” and the “Automatic Exhibition Guide System”, developed by Cheng Shiu University, as case studies. In recent years, AI technology has made significant advancements in image recognition, machine learning, and data analysis, which provide new opportunities for art management. However, due to high costs and implementation challenges, as well as a lack of qualified personnel to use these tools and systems, small art galleries and museums have not yet had the opportunity to acquire such systems. Therefore, this study observes the practical application of the “Exhibition Environment Status Detection Device and System” and the “Automatic Exhibition Guide System” in the fields of art preservation and exhibition. The study employs case study and observation methods, with participatory observation as the primary data collection approach. The results indicate that AI technology significantly enhances the preservation conditions of artworks and the interactivity of exhibitions. The paper suggests that future efforts should focus on long-term planning relating to technology costs and professional talent development to fully realize the potential of AI in art management and exhibition. Additionally, the application of these technologies can be extended to other fields. Full article

Groundwater level (GWL) in dry areas is an important parameter for understanding groundwater resources and environmental sustainability. Remote sensing data combined with machine learning algorithms have become one of the important tools for groundwater level modeling. However, the effectiveness of the above-based model in the plains of the arid zone remains underexplored. Fortunately, soil salinity and soil moisture may provide an optimized solution for GWL prediction based on the application of apparent conductivity (ECa, mS/m) using electromagnetic induction (EMI). This has not been attempted in previous studies in oases in arid regions. The study proposed two strategies to predict GWL, included an ECa-based GWL model and a remote sensing-based GWL model (RS_GWL), and then compared and explored their performances and cooperation possibilities. To this end, this study first constructed the ECa prediction model and the RS_GWL with ensemble machine learning algorithms using environmental variables and field observations (474 ECa reads and 436 groundwater level observations from a mountain–oasis–desert system, respectively). Subsequently, a strategy to improve the prediction accuracy of GWL was proposed by comparing the correlation between GWL observations and the two models. The results showed that the RS_GWL prediction model explains 30% and 90% of the spatial variability in the two value domain intervals, GWL < 10 m and GWL > 10 m, respectively. The R² of the modeling and the validation of the ECa was 79% and 73%, respectively. Careful analysis of the scatter plots between predicted ECa and GWL revealed that when ECa varies between 0–600 mS/m, 600–800 mS/m, 800–1100 mS/m, and >1100 mS/m, the fluctuation ranges of the corresponding GWL correspond to 0–31 m, 0–15 m, 0–10 m, and 0–5 m. Finally, combining the spatial variability of ECa and RS_GWL spatial distribution map, the following optimization strategies were finally established: GWL < 5 m (in natural land with ECa > 1100 mS/m), GWL < 5 m (occupied by farmland from RS_GWL) and GWL > 10 m (from RS_GWL), and 3 < GWL < 10 m (speculated). In conclusion, this study has demonstrated that the integration of EMI technology has significantly improved the precision of forecasting shallow GWL in oasis plain regions, outperforming the outcomes achieved by the use of remote sensing data alone. Full article

In agricultural production, the underside of crop leaves and the middle-lower canopy are key areas where pests and diseases typically develop at early stages. Increasing droplet deposition in these critical regions is essential for improving pesticide efficacy and crop yield. This study aims to optimize airflow-assisted parameters to enhance spray operation quality. By extracting the physical characteristics of soybean leaves at the V7 growth stage and conducting theoretical analysis, the study explored the factors influencing leaf orientation and droplet deposition, as well as the coupling relationship between these two aspects. A one-way fluid–structure coupling model was established using COMSOL software 6.1 to simulate the interaction between airflow and soybean leaves. The simulation results showed that airflow caused 71.1% of upper leaves, 66.7% of middle leaves, and 43.3% of lower leaves to have a flipping angle greater than 10°, with most flipped leaves (61.9%) concentrated on the windward side. Using droplet deposition on the middle-lower canopy and the underside of leaves as evaluation indices, a numerical simulation orthogonal experiment was conducted. The results indicated that the optimal operational parameters were an initial airflow speed of 20 m/s, an outlet-to-canopy distance of 0.45 m, and a forward airflow deflection angle of 32°. This optimal parameter combination improved droplet deposition. Field experiments confirmed these results, showing that compared to the spraying without optimization, droplet deposition on the lower and middle canopy and the underside of the leaves increased by 2.1 times and 2.3 times, respectively. Full article

RNA-seq technology has been widely used for the characterization of the transcriptome profile induced by several diseases in both humans and animals. In the present study, RNA-seq was used to identify the differential expression of genes associated with the immune response in cattle infected with two different strains of Babesia bigemina, both derived from the same Mexican field isolate, which exhibit distinct phenotypic characteristics: the virulent strain, capable of producing acute clinical signs, and the attenuated strain, capable of stimulating a protective immune response when used as an immunogen with an efficacy greater than 80%. The differential gene expression analysis performed revealed a total of 620 differentially expressed genes (DEGs). However, the intersection of the edgeR and DESeq2 programs used in the bioinformatics analysis only identified 247 DEGs, of which 108 genes were enriched to be closely correlated with the bovine immune response based on gene ontology terms; most of the DEGs obtained encode proteins associated with the major histocompatibility complex, immunoglobulins, and T-cell surface receptors. The infection caused by the attenuated strain induced higher transcription of immune response genes compared to the infection caused by the virulent strain; nonetheless, in both infections, a greater down-regulation than up-regulation was observed. Different immunoglobulin-associated genes were found to be up-regulated in the group inoculated with the attenuated strain, whereas these were down-regulated in the virulent strain-inoculated group. In addition, an up-regulation of the HSPA6, CD163, and SLC11a1 genes was observed in the group inoculated with the virulent strain, previously reported in other Apicomplexan infections. The findings provide relevant information that could contribute to clarifying the immune response associated with an acute bovine babesiosis infection by B. bigemina. Full article