Quantitative ultrasound radiofrequency analysis for monitoring Parkinson's disease.

Cell segmentation-the process of defining cell outlines in microscopy images-is essential for quantitative image analysis. Segmentation of budding yeast is challenging due to its asymmetric cell division and mother-bud morphology. Consequently, dividing cells are frequently misidentified as two separate cells, causing errors in downstream analysis. Here, we addressed this challenge by adapting the Segment Anything Model (SAM) to construct YeastSAM, a deep learning-based segmentation framework optimized for budding yeast. YeastSAM achieved more than three-fold higher accuracy in segmenting dividing cells compared with existing methods. When combined with single-molecule RNA imaging and organelle imaging, YeastSAM can be incorporated into a computational pipeline to build cellular maps. This enables quantitative analysis of the spatial regulation of gene expression. This study offers an accessible model for yeast cell segmentation, empowering researchers with minimal programming experience to perform quantitative image analysis.

This study explores the association between district vitality and industrial structure in historic districts through a quantitative analysis of the Xuanen Xinglong Historic District. In this study, on the basis of multisource data, we constructed the framework of a quantitative analysis system for the association between historic district vitality and industrial structure to explore the reasons for the decline in historic district vitality and propose strategies and recommendations for creating vitality in historic districts. The findings reveal that (1) the vitality of the Xuanen Xinglong Historic District showed a higher middle area than the surrounding area and more rest days than working days; (2) in terms of functionality, the degree of aggregation of POIs in catering, shopping and consumption, living services, and recreation and sports in the Xuanen Xinglong Historic District is high; and (3) the impact of POI data on district vitality is more significant for shopping and consumption and catering, followed by company and enterprise, hotel and accommodation, and recreation and sports, with other types of POIs having a weaker impact. The results can guide strategies for industrial upgrading and cultural tourism development for Xuanen Xinglong and other historic districts facing similar challenges.

Comparative evaluation of beetroot and Mangosteen Peel extracts as natural alternatives to malachite green in the Kato-Katz method.

• Industrialization in Ennore is unauthorized, unsustainable, infringed and unjust • Industrialization and urbanization have decreased the area of wetlands by 89.34% • Subnational government had manipulated 1996-CZMP Map to favour political elites • Manipulation had served political elites’ interests, to favor that of global elites • Peri-urban environmental injustice is caused by regulatory capture by the elites Industrialization, urbanization and population growth are the major drivers behind abominable ‘Land-Use Land-Cover Change (LULCC)’, and the loss of local ecosystem services and environmental quality, at peri-urban interfaces. Such dynamics indicate the need to analyse the LULCC pattern, and explore the political drivers behind unsustainable LULCC. This paper, taking ‘Ennore Peri-Urban Region’ as the study area, has adopted a ‘Geospatial Mixed-Methods Case-Study Approach’ that synergises ‘Quantitative LULCC Analysis’ and ‘Qualitative Political Discourse Analysis’. The quantitative LULCC analysis was performed by utilizing ‘Supervised Image Classification’ and ‘Change Detection Analysis’. Quantitative results have revealed that total area of wetland, waterbody and cropland/shrubland has decreased by 89.34%, 14.43% and 10.61% respectively, in the period 1988-2023. Especially, cropland/shrubland has been severely affected in the core industrial region. Such unsustainable LULCC has occurred due to an intensive peri-urban industrialization, and a gradual peri-urbanization. The area under settlement and dense-vegetation have increased by 507.84% and 3.42%, respectively. Qualitative-political discourse analysis has revealed that such an unsustainable peri-urban LULCC has occurred due to the five-year delay in preparing the ‘Coastal Zone Management Plan (CZMP)’ and its map, and the unauthorized manipulation of 1996-CZMP Map by the subnational ‘Government of Tamil Nadu’, without the approval of the national ‘Government of India’. Such delay and manipulation had initially favoured the vested interests of political elites, and eventually that of global urban business elites, through regulatory capture by the latter. These indicate an inefficient, unfair, unequitable, unjust, incoherent and non-transparent intergovernmental environmental governance, and a weak public participation in decision-making.

Interpretation of the IARC quantitative bias analysis of talc and ovarian cancer.

The oleoresin defense system of loblolly pine (Pinus taeda) protects trees from insects and pathogens and is an important source of renewable biofuels and chemicals, but the genetic basis of oleoresin production is poorly understood. We characterized the genetic architecture of oleoresin flow, resin canal number, stem wood terpene content, and monoterpene composition in two clonal populations of P. taeda. We used quantitative genetic analyses, genome-wide association studies (GWASs), multiplex network learning, and gene expression profiling to elucidate shared gene networks underlying defense traits and to identify high-quality candidates for breeding and engineering loblolly pine. Genetic analyses revealed polygenic inheritance and trait-to-trait correlations provide strong evidence for shared genes regulating constitutive and induced oleoresin flow. We identified 236 single nucleotide polymorphisms associated with oleoresin flow, resin canal number, and terpene composition and highlight candidate genes likely involved in terpene biosynthesis, cambial meristem reprogramming, and pathogen perception and immune signaling. Fourteen GWAS candidates were methyl jasmonate-responsive in tissues where resin canals initiate and terpene production occurs. Integrating quantitative genetics, GWAS, gene expression, and multiplex network analyses enabled the prioritization of high-quality candidate genes. This work advances the development of more resilient loblolly pine optimized for ecological performance, renewable chemical, and biofuel production.

The city of innovation, tech, and business: How fifty U.S. capital cities use strategic tech rhetoric in their branding

The role of curing conditions in the wear behavior of hybrid epoxy-polyester powder coatings

Understanding processes in geoscience porous media is fundamental to a broad spectrum of environmental and energy-related applications. These processes include multiphase fluid transport, interfacial dynamics, reactive transformations, and interactions with solids or microbial components in geological materials, all governed by wettability, capillarity, and reactive transport at fluid-fluid and fluid-solid interfaces. Laboratory-based multiscale imaging provides critical insights into these phenomena, enabling direct visualization and quantitative characterization from the nanometer to meter scale. It is essential for advancing predictive models and optimizing the design of subsurface and engineered porous systems. This review presents an integrated overview of planar imaging, surface topography and volumetric imaging techniques relevant to porous media research, emphasizing the type of information each method can provide, their applicability to porous media systems, and their inherent limitations. We highlight how imaging data are combined with quantitative analyses and modeling to bridge pore-scale mechanisms with continuum-scale behavior, and we critically discuss current challenges such as limited spatio-temporal resolution, sample representativity, and restricted data accessibility. We conduct an in-depth analysis on open-science trends in experimental and computational porous media research and find that, while open-access publishing has become widespread, the availability of imaging data and analysis code remains limited, often restricted to 'upon request'. Finally, we underscore the importance of open sharing of imaging datasets to enable reproducibility, foster cross-disciplinary integration, and support the development of robust predictive frameworks for porous media systems.

The demand for rapid and reliable analytical methods in the pharmaceutical industry continues to grow, with Ultra-/High-Performance Liquid Chromatography (U/HPLC) remaining the gold standard for impurity profiling, quantification of active pharmaceutical ingredients, and degradation product analysis. However, traditional HPLC methods are often constrained by pressure limitations at higher flow rates, which can hinder analytical throughput. While recent advancements in column technology have improved performance, they typically exacerbate pressure-related challenges. In this study, we evaluate a novel column technology designed to address these limitations by enabling high-resolution separations at reduced pressures and increased flow rates. Our findings demonstrate that the column, when operated in Radial Flow Stream Splitting (RFS) mode, maintains quantitative accuracy and repeatability while achieving up to a 120 % improvement in separation efficiency and a 30 % reduction in backpressure compared to conventional operation. By way of assaying over-the-counter medication, we have found no difference in the quantitative reliability of the assay when in RFS vs stock mode, despite reducing the analysis time by up to 40 %.

NeuroGT: Biophysically grounded graph transformers for self-supervised representation learning of neuronal morphology.

Towards quantitative CEUS assessments of ex-vivo feto-placental (micro)vasculature: A feasibility study

Establishment of standardized intraoral implant model in the rabbit edentulous diastema

Comparative study of four matrix effect correction strategies for bile acid quantification in mouse serum.

Comparison of three kinds of models for detecting tartrazine in tea powder by synchronous fluorescence spectroscopy combined with chemometrics.

Chilean Azorella monantha: A Green approach for the extraction of secondary metabolites by using microwave-assisted green solvents extraction

Application of qualitative and quantitative techniques to estimate the sex of Brazilian skulls and mandibles

While cone beam CT (CBCT) is commonly used in musculoskeletal imaging of the extremities, its application in spinal imaging has been restricted by small field-of-view (FOV) coverage. Recent advancements in gantry-based CBCT systems promise to enable comprehensive imaging of the spinal column. This study aimed to evaluate the performance of a novel gantry-based, multi-scan CBCT system for spinal imaging with complete anatomic coverage and compare it to energy integrating (EI)CT and photon counting (PC)CT using dose-matched protocols. An anthropomorphic torso phantom was used to simulate human anatomy. Gantry-based CBCT scans of the thoracolumbar spine were performed using different presets (low-dose, enhanced, best quality), while EICT and PCCT scans followed dose-matched clinical protocols. Qualitative image analysis was assessed by three blinded readers using a 4-point Likert scale, and quantitative analysis was conducted using global noise level (GNL) measurements. CBCT achieved diagnostic-quality imaging for the thoracic and lumbar spine, particularly with "best" and "enhanced" presets. Subjective image quality was highest for PCCT, followed by EICT and CBCT. CBCT demonstrated lower GNL than EICT, nearing PCCT levels. However, high radiation doses (5mGy) were required for CBCT imaging of the upper thoracic spine (Th1-Th6) due to anatomical complexity, while low doses (0,5 mGy) sufficed for the lower thoracolumbar spine (Th7-S1). Gantry-based CBCT was able to generate diagnostic-quality images of large spinal regions at relatively low radiation doses in a phantom setting, although the upper thoracic spine (above Th6) required higher doses. The overall subjective image quality remained below EICT and PCCT.

A combined approach of fingerprint, chemometric analysis, and network pharmacology based on available studies was employed to identify quality markers (Q-markers) in Moringa oleifera leaves (MOLs) for hyperglycemia. Subsequently, we conducted a quantitative analysis of these Q-markers to provide a scientific basis for quality control and clinical application of MOLs. High-performance liquid chromatography (HPLC) was used to establish the fingerprint of MOLs, and similarity evaluation and common peak identification were conducted. Chemometric methods were applied to screen differential biomarkers of MOLs from different batches. Based on the findings from network pharmacology, a "component-target-pathway" network was constructed using the identified key targets and pathways to predict the potential hypoglycemic Q-markers of MOLs. Moreover, 12 batches of MOLs were used as research objects to determine the content of Q-markers. Four compounds associated with therapeutic efficacy were identified as Q-markers through fingerprint analysis and a series of chemometric methods. Network pharmacology analysis was performed based on the chosen Q-markers to elaborate the potential pharmacodynamic mechanisms. More importantly, it will provide a reference for further research on the quality control and pharmacological substance basis of MOLs, as well as data support for the rational utilization of MOLs medicinal materials.