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Alternative audio-graphic method for presenting structural information in mathematical graphs designed for low-vision users
Mapping mangrove multi-trait functional diversity from satellite observations across dense and fragmented stands using spectral-biophysical derivatives
Metabolomic analysis of rumen fluid in Tan sheep reveals sex-specific key metabolites and pathways associated with residual feed intake
Evaluation of the diagnostic concordance of FDA-approved PD-L1 assays in clear cell renal cell carcinoma
Artificial intelligence derived grading of mustard gas induced corneal injury and opacity
Abstract Artificial intelligence (AI) has emerged as a transformative tool in ophthalmology for disease diagnosis and prognosis. However, use of AI for assessing corneal damage due to chemical injury in live rabbits remains lacking. This study aimed to develop an AI-derived clinical classification model for an objective grading of corneal injury and opacity levels in live rabbits following ocular exposure of sulfur mustard (SM). An automated method to grade corneal injury minimizes diagnostic errors and enhances translational application of preclinical research in better human eyecare. SM induced corneal injury and opacity from 401 in-house rabbit corneal images captured with a clinical stereomicroscope were used. Three independent subject matter specialists classified corneal images into four health grades: healthy, mild, moderate, and severe. Mask-RCNN was employed for precise corneal segmentation and extraction, followed by classification using baseline convolutional neural network and transfer learning algorithms, including VGG16, ResNet101, DenseNet121, InceptionV3, and ResNet50. The ResNet50-based model demonstrated the best performance, achieving 87% training accuracy, and 85% and 83% prediction accuracies on two independent test sets. This deep learning framework, combining Mask-RCNN with ResNet50 allows reliable and uniform grading of SM-induced corneal injury and opacity levels in affected eyes.
Global overlooked multidimensional water scarcity
Freshwater resources are fundamental to supporting humanity, and measures of water scarcity have been critical for identifying where water requirements and water availability are imbalanced. Existing water scarcity metrics typically account for blue water withdrawals (i.e., from surface-/groundwater), while the contribution of green water (i.e., soil moisture) and water quality—dimensions with important implications for multiple societal sectors—to water scarcity remains unclear. Here, we introduce the concept of multidimensional water scarcity that explicitly assesses all three of these dimensions of water scarcity and evaluates their individual and combined effects. We find that 22 to 26% of the global land area and 58 to 64% of the global population are exposed to some form of water scarcity annually, with multidimensional (i.e., blue, green, and quality) water scarcity particularly high in India, China, and Pakistan. Examining seasonal water scarcity, we estimate that 5.9 billion people (or 80% of the world’s population in 2015) were exposed to at least one dimension of water scarcity for at least 1 mo per year and that 1-in-10 people (10%) were exposed to multidimensional water scarcity at least 1 mo per year. Our findings demonstrate that the challenges of water scarcity are far more widespread than previously understood. As such, our assessment provides a more holistic view of global water scarcity issues and points to overlooked scarcity where action needs to bring human pressure on freshwater resources into balance with water quantity and quality.
Severity and factors associated with pain in patients on mechanical ventilators in Amhara region, North-West Ethiopia: a multi-center prospective observational study
Unveiling diversity and adaptations of the wild tomato Microbiome in their center of origin in the Ecuadorian Andes
Abstract Microbiome assembly has been studied for many plant species and is recognized as a key driver of plant growth and plant tolerance to (a)biotic stresses. To date, assembly of the tomato rhizosphere microbiome has been investigated primarily for commercial varieties and field soils subjected to agricultural management practices, whereas the microbiome of wild tomato genotypes in their native habitats remains largely unexplored. This research focused on distinct populations of Solanum pimpinellifolium in three natural habitats in the Ecuadorian Andes to identify the taxonomic and functional diversity of their rhizosphere microbiome. The results showed that, despite genotypic differences among the wild tomato populations, different soil types and soil microbiome compositions, the rhizosphere microbiome showed strikingly compositional similarity across the three habitats. Proteobacteria, in particular taxa classified as Enterobacteriaceae, and specific unclassified fungal taxa were highly represented in the rhizosphere of S. pimpinellifolum. Metagenomic analyses suggested that the prevalence of Enterobacteriaceae on wild tomato roots may be explained by several traits, in particular nutrient competition, motility, iron acquisition, membrane transport, stress response, and plant hormone biosynthesis. These results reveal a conserved microbiome signature associated with wild tomato rhizosphere in their center of origin. Just as the genomes of wild crop ancestors provide a valuable source of beneficial traits for breeding cultivated varieties, exploring their microbiome in native environments could uncover microbial taxa and traits that similarly contribute to crop growth and health.
Anisotropic bounding surface plasticity model for soils
Nano ordered polyacrylonitrile-grafted chitosan as a robust biopolymeric catalyst for efficient synthesis of highly substituted pyrrole derivatives
Novel machine learning approach for enhanced smart grid power use and price prediction using advanced shark Smell-Tuned flexible support vector machine
Glycine betaine treatment extends the shelf life and retards cap browning of button mushrooms
Benthic communities on restored coral reefs confer equivalent aesthetic value to healthy reefs
Abstract Coral reefs are valuable ecosystems that provide diverse ecosystem services to people. For example, many reefs have exceptionally high tourism value, attracting visitors to experience their ecologically and visually rich reef habitat. However, human-induced degradation can alter ecosystem services, such as when damaged reefs lose their visual appeal. Coral restoration has become a common response to reef degradation, but restoration success is usually evaluated based on coral cover increases rather than ecosystem service recovery. Here, we quantify the aesthetic value of restored reefs at one of the world’s largest coral restoration projects, compared to nearby healthy and degraded reefs. Using deep learning models trained on people’s visual preferences, we estimated the aesthetic value of coral reef benthic photographs with high prediction accuracy (R2 = 0.95). Restored reefs exhibited aesthetic value that was statistically equivalent to healthy reefs and significantly higher than degraded reefs. High aesthetic value was primarily driven by colour diversity and live coral cover, which were both higher in healthy and restored reefs than degraded reefs. Taken together, these results demonstrate the recovery of aesthetic value towards a healthy state after large-scale restoration, indicating that coral restoration can support vital tourism services and well-being contributions to people.
Lower cholesterol level on admission predicts poor outcome after prolonged cardiac arrest
Calcineurin targets that mediate <i>Cryptococcus</i> thermotolerance
The identification Mycobacterium tuberculosis genes that modulate long term survival in the presence of rifampicin and streptomycin
Abstract In 2023, Mycobacterium tuberculosis (Mtb) caused 10.6 million new tuberculosis cases and 1.3 million deaths. The WHO proscribed treatment is not always successful, even when strains were sensitive to the antibiotics.as clinical Mtb populations contain phenotypically tolerant subpopulations, termed persisters. Here a Mtb transposon library was challenged with rifampicin (RIF) and streptomycin (STM) under conditions designed to identify genes that modulate persister frequency. Mutants with reduced survival in RIF were predominantly in genes associated with membrane integrity e.g. arabinogalactan assembly genes cpsA/lytR/Psr, whilst for STM, reduced survival was associated with toxin/antitoxin genes. Some mutations enhanced survival. For RIF these included the methyl citrate cycle genes prpC, prpD and prpR, and the trkA-C K+ uptake system genes ceoB and Rv2690, and for STM, the resistance associated gene, gidB, and anion-transport genes Rv3679c and Rv3680c. Few genes overlapped the RIF and STM selections, demonstrating that survival mechanisms were antibiotic-specific. Directed deletions of ΔprpD and ΔfadE5 confirmed their predicted enhanced and reduced RIF fitness respectively. The study identified genes that modulate not only persister frequency but also resistance and tolerance, and demonstrates that the mechanisms that produce these phenotypes are diverse and antibiotic-specific.