Search Results (19,224)

Coronary artery disease (CAD) remains the leading cause of cardiovascular morbidity and mortality worldwide, with plaque composition and morphology being as key determinants of disease progression and clinical outcomes. Accurate plaque characterization is essential for risk stratification and therapeutic decision-making, yet conventional image interpretation is limited by inter-observer variability and time-intensive workflows. Artificial intelligence (AI) models have emerged as a transformative tool for automated coronary plaque analysis across multiple imaging modalities. AI-driven models demonstrate high diagnostic accuracy for plaque detection, segmentation, quantification, and vulnerability assessment. Integration of AI-derived imaging biomarkers with clinical risk scores can further enhance prediction of major adverse cardiovascular events and supports personalized management. These advances position AI-enhanced imaging as a powerful adjunct for both invasive and non-invasive evaluation of CAD. Despite its promise, important barriers to widespread clinical adoption remain, including data heterogeneity, algorithmic bias, limited model transparency, insufficient prospective validation, regulatory challenges, and incomplete integration into clinical workflows. Addressing these challenges will be essential to ensure safe, generalizable, and cost-effective implementation of AI in routine cardiovascular care. Full article

This paper addresses a critical inconsistency in models of the term structure of interest rates (TSIR), where zero-coupon bonds are priced under risk-neutral measures distinct from those used in equity markets. We consider a unified TSIR framework that treats zero-coupon bonds as European options with deterministic payoffs, ensuring that they are priced under the same risk-neutral measure that governs equity derivatives. Using put–call parity, we extract zero-coupon bond implied yield curves from S&P 500 index options and compare them with the US daily treasury par yield curves. As the implied yield curves contain maturity time T and strike price K as independent variables, we investigate the $K$—dependence of the implied yield curve. Our findings, that at-the-money option-implied yield curves provide the closest match to treasury par yield curves, support the view that the equity options market contains information that is highly relevant for the TSIR. By insisting that the risk-neutral measure used for bond valuation is the same as that revealed by equity derivatives, we offer a new organizing principle for future TSIR research. Full article

Accurate prediction of the effective thermal conductivity (ETC) of nuclear fuels is essential for optimizing fuel performance and ensuring reactor safety. However, the experimental determination of ETC is often limited by cost and complexity, while high-fidelity simulations are computationally intensive. This study presents a novel hybrid framework that integrates experimental data, validated mesoscale finite element simulations, and machine-learning (ML) models to efficiently and accurately estimate ETC for advanced uranium-based nuclear fuels. The framework was demonstrated on three fuel systems: UO₂-BeO composites, UO₂-Mo composites, and U-10Zr metallic alloys. Mesoscale simulations incorporating microstructural features and interfacial thermal resistance were validated against experimental data, producing synthetic datasets for training and testing ML algorithms. Among the three regression methods evaluated, namely Bayesian Ridge, Random Forest, and Multi-Polynomial Regression, the latter showed the highest accuracy, with prediction errors below 10% across all fuel types. The selected multi-polynomial model was subsequently used to predict ETC over extended temperature and composition ranges, offering high computational efficiency and analytical convenience. The results closely matched those from the validated simulations, confirming the robustness of the model. This integrated approach not only reduces reliance on costly experiments and long simulation times but also provides an analytical form suitable for embedding in engineering-scale fuel performance codes. The framework represents a scalable and generalizable tool for thermal property prediction in nuclear materials. Full article

Background: The original Closed Kinetic Chain Upper Extremity Stability Test (CKCUEST) is a simple assessment tool but does not account for individual differences in hand starting position and fails to provide information on limb asymmetries. The purpose of the study is to evaluate the test–retest reliability of a new single-arm CKCUEST as well as the reliability of the limb symmetry index (LSI). This version normalizes the test based on the participant’s arm length and allows for the assessment of limb symmetry since it is performed one arm at a time. Methods: Twelve healthy young adults provided both verbal and written consent to participate. Participants were excluded if they had sustained an injury in the past three months requiring medical attention and/or resulting in decreased activity for more than three days. Testing was conducted in the push-up position with participants’ thumbs placed parallel and at a distance equal to the length of their dominant arm (measured from the acromion to the tip of the middle finger), and feet positioned shoulder-width apart. Participants were instructed to keep the testing hand stable on the floor while the opposite hand reached across the body to touch the stationary hand and then return to the starting position marked with athletic tape. The goal was to complete as many touches as possible in 15 s, with each touch counted only if the participant touched the stationary hand, returned to the starting position, and maintained the shoulder-width stance. The average number of touches from the three trials was used for analysis. Intraclass Correlation Coefficients (ICC_(3,1)) were computed to determine test–retest reliability. Results: Test–retest reliability of the single-arm CKCUEST individual tests was good to excellent. The ICC_(3,1) was 0.88 (95% CI: 0.74–0.95) for all tests, 0.89 (95% CI: 0.66–0.96) for the dominant arm, and 0.93 (95% CI: 0.78–0.98) for the non-dominant arm. In contrast, the reliability of the Limb Symmetry Index (LSI) was questionable, showing substantial variability with an ICC_(3,1) of 0.53 (95% CI: −0.03–0.83) between Day 1 and Day 2, despite similar mean values (Day 1: 93.6 ± 8.46; Day 2: 94.8 ± 5.77). The Kappa coefficient suggested a substantial level of agreement for the direction of the asymmetry (preferred limb) (Kappa coefficient = 0.62). Conclusions: The new single-arm CKCUEST, which personalizes the hand starting position and measures limb symmetry, demonstrates high reliability among healthy young adults. Full article

Quiescin sulfhydryl oxidase 1 (QSOX1) is a disulfide bond-forming enzyme with both disulfide isomerase and oxidoreductase activities. It plays an important role in protein folding, stability, and secretion. Growing evidence demonstrates that QSOX1 is upregulated in multiple cancer types and influences key behaviors of cancer cells, including proliferation, migration, invasion, and metastasis. Elevated QSOX1 expression is also associated with tumor malignancy and disease relapse. However, the molecular mechanisms by which QSOX1 drives cancer progression remain incompletely understood. In this review, we summarize current knowledge of QSOX1 expression and regulation in cancer, discuss its functional roles, and highlight key unanswered questions to warrant further investigation. Full article

Background: As the U.S. population ages, the need for gastrointestinal (GI) care and procedures grows. Medicare is a significant payer for these procedures, but declining reimbursements raise concerns about the availability of GIs and thus equitable access to care. This study examines the relationship between Medicare reimbursements for GI procedures and the regional supply and demand of GI physicians. Methods: This study analyzed the Medicare facility and non-facility setting physician reimbursements for the top 10 GI procedures for 2003, 2013, and 2023. Facility reimbursements were compared across four regions (Northeast, Midwest, South, and West) and compared to regional GI physician supply and demand data for 2013 and 2025 projections. Linear regression and mixed-effects models were used to evaluate relationships between reimbursements, physician supply, and demand. Results: The national average adjusted facility setting physician reimbursements for the top 10 GI procedures declined by 45.6% from 2003 to 2023. In 2013 and projected for 2025, the South had the highest GI physician supply and demand, but consistently lower facility setting physician reimbursements compared to the Northeast and West. Associations between supply, demand, and reimbursements were observed, though regional patterns showed paradoxical trends, such as similar low reimbursements in the South and Midwest despite differing supply levels. Conclusions: Regional inconsistencies between physician supply and reimbursements highlight the complexity of economic and healthcare dynamics. Declining Medicare reimbursements for GI procedures are multifactorial and, as the aging population grows, these reductions may widen disparities. Further investigation is needed to address barriers and ensure equitable access to GI care. Full article

Background: Leiomyosarcomas are an aggressive soft-tissue sarcoma that arise from smooth muscle, have a high metastatic potential and account for 10–20% of soft-tissue sarcomas. Despite decades of research, the first-line treatment remains unresolved due to the absence of direct comparative trials, heterogeneous study designs, and trade-offs between efficacy and toxicity. This systematic review evaluates the optimal therapeutic systemic chemotherapy regimens in the first-line setting, specifically gemcitabine- and doxorubicin-based regimens, including associated toxicities. Methods: A systematic search in MEDLINE (Ovid), Embase (Ovid), and Cochrane Library (Wiley) identified studies of first-line gemcitabine- or doxorubicin-based chemotherapy for leiomyosarcoma. The review protocol was registered in PROSPERO (CRD420261280028). Of the 3092 articles screened, 11 articles were eligible for inclusion, comprising results from 1225 patients. Eligible studies were in English and included ≥10 patients with advanced/metastatic leiomyosarcoma reporting on LMS-specific outcomes and no prior systemic therapy. This qualitative systematic review synthesizes prospective and retrospective evidence without quantitative meta-analysis. Results: The review included two phase 3 trials, six phase 2 trials, one phase 1b trial, and two retrospective studies. While there was no direct comparison in this setting, doxorubicin-based combinations consistently reported higher objective response rates, progression-free survival, and overall survival. The most favorable outcomes were observed in the LMS04 trial with doxorubicin plus trabectedin followed by surgery and trabectedin maintenance, yielding a median progression-free survival of 12 months, overall survival of 33 months, and objective response rate of 36%. This regimen also had the highest grade 3–4 toxicity. Conclusions: Doxorubicin-based regimens remain the most active first-line option for leiomyosarcoma, although treatment practices remain heterogeneous. Full article

In this paper, we consider the inevitable large fluctuations of pressure in typical molecular dynamics (MD) simulations of ligand–protein binding problems. In simulations under the constant pressure of one bar, the pressure artifactually fluctuates over the range of $\pm 100$ bars or more. This artifact can cause gross inaccuracy in the apparent binding affinity computed as the ratio of the probability for the ligand to be bound inside the protein and the probability for the ligand to be outside the protein. Based on statistical thermodynamics, we derive a correction factor for the ligand–protein binding affinity to compensate for the artifactual pressure fluctuations. The correction factor depends on the change in the system volume between the bound and the unbound states of the ligand. We conducted four sets of MD simulations for glycerol affinities with four aquaglyceroporins: AQP10, AQP3, AQP7, and GlpF. Without the correction factor, the apparent affinity of glycerol with each of these four aquaglyceroporins is computed directly from the simulations to be very low (~1/M). With the correction factor applied, glycerol’s affinity is computed to be 1/mM to 1/µM. In conclusion, glycerol has high affinity for its native facilitator aquaglyceroporins, which is in contrast to the current literature not correcting the artifactual consequences of the large pressure fluctuations in typical in silico experiments. Full article

Spatial data has distinctive properties that differentiate it from non-spatial data. One prominent characteristic is spatial autocorrelation (SA). When machine learning techniques are applied for spatial data modeling, they require spatially explicit consideration. If these inherent spatial structures are ignored, models may produce biased predictions. However, integrating this property into the model yields additional spatial insight, thereby enhancing learning and improving predictive accuracy. This study examines spatially explicit $K$-nearest neighbors (SE-KNN) by integrating SA as a spatially explicit property, $\lambda$, into the learning algorithm. The innovation of SE-KNN lies in its alignment with the principle of spatial autocorrelation, as KNN’s core learning assumption—that similar observations tend to have similar outcomes—naturally parallels spatial dependence. The proposed SE-KNN is applied to a house price prediction model using house sales data from Franklin County, Ohio to demonstrate a spatially dependent, data-rich, and real-world problem. The results show that SE-KNN achieved the best prediction accuracy compared to mean of absolute error (MAE) of three other machine learning approaches (i.e., standard KNN, linear regression, and artificial neural networks). The proposed method effectively captures the spatial structures in the housing market and leaves only a trace amount of SA in the residuals. Full article

CRISPR-Cas9 systems have enabled unprecedented advances in genome engineering, particularly in developing treatments for human diseases, like cancer. Despite potential applications, limitations of Cas9 include its relatively large size and strict targeting requirements. Cas12j2, a variant ofCasΦ-2, shows promise for overcoming these limitations. However, its effectiveness in mammalian cells remains relatively unexplored. This study sought to develop an optimized CRISPR-Cas12j2 system for targeted knockout of the E6 oncogene in HPV-associated cancers. A combination of computational tools (ColabFold, CCTop, Cas-OFFinder, HADDOCK2.4, and Amber for Molecular Dynamics) was utilized to investigate the impact of engineered modifications on structural integrity and gRNA binding of Cas12j2 fusion constructs, in potential intracellular conditions. Cas12j2_F2, a Cas12j2 variant designed and evaluated in this study, behaves similarly to the wild-type Cas12j2 structure in terms of RMSD/RMSF profiles, compact Rg values, and minimal electrostatic perturbation. The computationally validated Cas12j2 variant was incorporated into a custom expression vector, co-expressing the engineered construct along with a dual gRNA for packaging into a viral vector for targeted knockout of HPV-associated cancers. This study provides a structural and computational foundation for the rational design of Cas12j2 fusion constructs with enhanced stability and functionality, supporting their potential application for precise genome editing in mammalian cells. Full article

The endolysosomal system plays a pivotal role in cellular function. Before reaching lysosomes for degradation, the endocytosed cargoes are sorted at various stages of endosomal trafficking for recycling and/or rerouting. The proper execution of these processes depends on tightly regulated ion fluxes across endolysosomal membranes. Recent studies have demonstrated the importance of two-pore channels (TPCs), including TPC1 and TPC2, in endolysosomal trafficking. These channels are expressed in the membranes of distinct populations of endosomes and lysosomes, where they respond to nicotinic acid adenine dinucleotide phosphate (NAADP) and phosphatidylinositol 3,5-bisphosphate [PI(3,5)P₂] to conduct Ca²⁺ and Na⁺ release from these acidic organelles. Here, we discuss the potential implications of Ca²⁺ and Na⁺ fluxes mediated by TPCs across endolysosomal membranes in the physiological and pathophysiological functions of these organellar channels. Full article

With globalization rising, much scholarship has presented “a race to the bottom” regarding standards posing serious environmental concerns. This paper considers the debate of globalization leading to a “race to the bottom” or, contrastingly, a “race to the top.” With the growth of information technology and communication, the paper explores existing frameworks to advance green computing in the globalized context. Given a notable void in policy-driven frameworks in the current green computing literature, the paper proposes a comprehensive five-component policy framework to advance green computing, relying on norms and mandates for success. The framework includes the following: 1. Public policy involvement to drive private corporate sustainability. 2. Investment in green technology via government intervention. 3. Industrywide organizations promoting sustainable computing. 4. Proper disposal of computing equipment. 5. Comprehensive industry standards. Ultimately, this framework passionately advocates for the advancement of green computing and encourages further empirical research and evaluation of its respective elements. Full article

Background: The increasing prevalence of low-birth-weight (LBW) offspring from obese mothers underscores the need for dietary strategies to mitigate the transgenerational propagation of metabolic diseases. Objectives: We determined whether dietary protein restriction under obesogenic conditions altered maternal energy balance and led to LBW offspring and whether branched-chain amino acid (BCAA) supplementation improved maternal energy balance and mitigated weight and craniofacial skeletal deficits in offspring. Methods: High-fat-fed obese pregnant Sprague Dawley rats (~8–10 weeks of age, n = 8–11/group) were randomized in study 1 to control high-fat diet (20% protein; HFD), low-protein diet (LP; 5% protein), and LP + BCAA diet (100% BCAA requirements) and in study 2 to control HFD (20% protein), LP (10% protein), and LP + 2BCAA diet (200% BCAA requirements). Post-weaning offspring were fed HFD until 8 weeks of age. Results: Protein restriction promoted hyperphagia and energy expenditure, whereas BCAA supplementation attenuated such hyperphagic effects in pregnancy but not in lactation. Protein restriction reduced maternal body weight in lactation, and although BCAA supplementation did not reverse the weight loss, it enhanced insulin sensitivity and paradoxically reduced offspring survival. Maternal protein restriction reduced offspring body weight and craniofacial bone growth that persisted into adulthood, but BCAA supplementation did not rescue such deficits. Conclusions: Maternal protein restriction in obese dams enhanced maternal energy expenditure but impaired offspring growth and development. Although BCAA supplementation improved maternal energy balance, it was insufficient to reverse the adverse effects of maternal protein restriction on offspring growth under obesogenic conditions. Full article

This study presents a validated framework to quantify regional sea-level risk on U.S. coasts by (i) extracting trends and seasonality from satellite altimetry (ADT, GMSL), (ii) learning regional dynamical regimes via PCA-embedded KMeans on gridded ADT time series, and (iii) coupling these regimes with socioeconomic exposure (population, income, ocean-sector employment/GDP) and wetland submersion scoring. Relative to linear and ARIMA/SARIMA baselines, a sinusoid+trend fit and an LSTM forecaster reduce out-of-sample error (MAE/RMSE) across the North Atlantic, North Pacific, and Gulf of Mexico. The clustering separates high-variability coastal segments, and an interpretable submersion score integrates elevation quantiles and land cover to produce ranked adaptation priorities. Overall, the framework converts heterogeneous physical signals into decision-ready coastal risk tiers to support targeted defenses, zoning, and conservation planning. Full article