Search Results (18,388)

Air pollution forecasting is essential for understanding environmental patterns and mitigating health risks, especially in urban areas. This study investigates the forecasting of criterion pollutants—CO,O3,SO2,NO2,PM2.5, and PM10—across multiple temporal frames (hourly, daily, weekly, monthly) in Salamanca, Mexico, utilizing temporal, meteorological, and pollutant data from local monitoring stations. The primary objective is to identify robust models capable of short- and mid-term predictions, despite challenges related to data inconsistencies and missing values. Leveraging the low-code PyCaret framework, a benchmark analysis was conducted to identify the best-performing models for each pollutant. Statistical evaluations, including ANOVA and Tukey HSD tests, were employed to compare model performance across different time frames. The results reveal significant variations in prediction accuracy depending on both the pollutant and temporal windows, with stronger predictive performance observed in the weekly and monthly frames. The research indicates that the incorporation of temporal and environmental variables enhances forecast accuracy and highlights the value of low-code AutoML tools, such as PyCaret, in streamlining model selection and improving overall forecasting efficiency. Full article

This paper proposes a flood risk visualization method that is (1) readily transferable (2) hyperlocal, (3) computationally inexpensive, and (4) geometrically accurate. This proposal is for risk communication, to provide high-resolution, three-dimensional flood visualization at the sub-meter level. The method couples a laser scanning point cloud with algorithms that produce textured floodwaters, achieved through compounding multiple sine functions in a graphics shader. This hyper-local approach to visualization is enhanced by the ability to portray changes in (i) watercolor, (ii) texture, and (iii) motion (including dynamic heights) for various flood prediction scenarios. Through decoupling physics-based predictions from the visualization, a dynamic, flood risk viewer was produced with modest processing resources involving only a single, quad-core processor with a frequency around 4.30 GHz and with no graphics card. The system offers several major advantages. (1) The approach enables its use on a browser or with inexpensive, virtual reality hardware and, thus, promotes local dissemination for flood risk communication, planning, and mitigation. (2) The approach can be used for any scenario where water interfaces with the built environment, including inside of pipes. (3) When tested for a coastal inundation scenario from a hurricane, 92% of the neighborhood participants found it to be more effective in communicating flood risk than traditional 2D mapping flood warnings provided by governmental authorities. Full article

Air pollution in urban street canyons presents a serious health risk, especially in densely populated areas. While previous research has explored airflow characteristics in these canyons, it often lacks detailed data on pollutant dispersion and the effects of wind speed on airflow patterns and vortex formation. This study uses Computational Fluid Dynamics (CFD) to deliver quantitative measurements of pollutant dispersion rates and qualitative insights into airflow patterns across various street canyon morphologies. The analysis examines a range of aspect ratios (ARs), from wide (AR = 0.75) to narrow (AR = 4.5), and different wind speeds to evaluate their effects on pollutant dispersion. Findings indicate that purging flow rates decline as the AR increases, with a more pronounced decrease at lower AR values. In narrower streets, airflow patterns are particularly sensitive to wind velocity, leading to unexpected vortices that hinder effective pollutant dispersion. By incorporating these insights into urban design strategies, cities can enhance street ventilation, thereby reducing pollutant concentrations and improving public health. This study also tests a specific street layout in Seville to predict pollutant accumulation under various conditions, assessing health risks based on World Health Organization guidelines. Ultimately, this research aids in developing healthier, more sustainable urban environments. Full article

Background: The fatality rate of hemorrhagic fever with renal syndrome (HFRS), due to hantavirus transmitted by rodents, ranges from 1% to 12%. This study aims to delineate the clinical and laboratory characteristics of HFRS, identify factors associated with disease severity, and construct and validate a nomogram for prognosis prediction of HFRS in the central part of China. Methods: Out of 598 HFRS patients diagnosed via serology tests from four hospitals in Hubei Province, 551 were included. Clinical data were gathered and analyzed, followed by logistic univariate and multivariate analyses to identify independent prognostic factors. A nomogram was developed and validated to forecast the patient’s prognosis. Results: Vaccination led to a notable drop in HFRS incidence from 2018 to 2019, and seasonal trends exhibited bimodal changes with peaks from May to July and November to January. The 30-day mortality rate was 4.17% (23/551). Red blood cell count (RBC), age, two-stage overlap, qSOFA ≥ 2, aspartate aminotransferase (AST), and three-stage overlap were identified as independent prognostic factors. A predictive risk classification system using a nomogram chart was developed, and Kaplan–Meier curves indicated that the new system accurately distinguished 30-day mortality among the three risk groups. Conclusions: The risk score (EASTAR) system demonstrated good predictive performance for prognostic prediction, and it can be applied to quickly screen patients who require ICU admission. Full article

Asthma, a chronic respiratory condition characterized by airway inflammation, affects millions of individuals worldwide. Challenges remain in asthma prediction and diagnosis from its complex etiology involving genetic and environmental factors. Here, we investigated the relationship between genome-wide DNA methylation and genetic risk for asthma quantified via polygenic scores in two cohorts from the Netherlands Twin Register; one enriched with asthmatic families measured on the Illumina EPIC array (n = 526) and a general population cohort measured on the Illumina HM450K array (n = 2680). We performed epigenome-wide association studies of asthma polygenic scores in each cohort with results combined through meta-analysis (total samples = 3206). The EWAS meta-analysis identified 63 significantly associated CpGs, (following Bonferroni correction, α = 0.05/358,316). An investigation of previous mQTL associations identified 48 mQTL associations between 24 unique CpGs and 48 SNPs, of which two SNPs have previous associations with asthma. Enrichment analysis using the 63 significant CpGs highlighted previous associations with ancestry, smoking, and air pollution. A dizygotic twin within-pair analysis of the 63 CpGs revealed similar directional effects between the two cohorts in 33 of the 63 CpGs. These findings further characterize the intricate relationship between DNA methylation and genetics relative to asthma. Full article

Background: Non-Hodgkin lymphoma (NHL) is associated with significant cardiovascular risks due to treatment-related toxicities, including cancer therapy-related cardiac dysfunction (CTRCD). While multimodality imaging, particularly echocardiography, is pivotal in monitoring cardiac function, the prognostic role of cardiopulmonary exercise testing (CPET) in predicting CTRCD remains underexplored. Methods: The prospective study enrolled 127 NHL patients, 72 men (56.7%) and 55 women (43.3%), with a median age of 62 years (range 34–83 years). The patients were assessed before initiating antitumor treatment and at six months follow-up using echocardiography and cardiopulmonary exercise testing. Results: Asymptomatic CTRCD occurred in 14.2% of NHL patients at six months of treatment. Patients with CTRCD exhibited significantly lower median work rates, volume of oxygen (VO₂) at the anaerobic threshold, and O₂ consumption efficiency, reflecting compromised metabolic and functional performance. Baseline peak oxygen consumption (VO₂ peak) positively correlated with left ventricle ejection fraction (LVEF) at six months, while VO₂ peak < 14 mL/kg/min was negatively associated with LVEF. Conclusions: Asymptomatic CTRCD was identified in 14.2% of NHL patients at six months, with lower work rates, VO₂ at the anaerobic threshold, and O₂ consumption efficiency, indicating impaired performance. Baseline peak oxygen consumption correlated positively with LVEF, highlighting CPET’s potential for early CTRCD risk assessment. Full article

Surgical guides are integral tools in orthodontics, enhancing the precision and predictability of mini-implant placement. These guides facilitate accurate positioning, reduce risks to surrounding anatomical structures, and ensure proper angulation and depth during procedures. The aim of the present paper is to present a detailed review of the surgical guides used in orthodontics, focusing on their classification, mechanical properties, biocompatibility, and future developments. The advantages, disadvantages, clinical steps, and implications are also described based on the data in recent scientific literature. Future developments may incorporate artificial intelligence and augmented reality, further optimizing treatment planning and patient outcomes, thus solidifying the role of surgical guides in efficient orthodontic care. Full article

Women diagnosed with early-stage breast cancer can develop metastatic disease following successful initial treatment, with bone being the most common site of metastases. The Breast to Bone (B2B) cohort study of early-stage breast cancer patients was established as a research platform to study the basic biology of breast cancer to bone metastasis and to identify the factors that could improve prevention, early detection and treatment for this debilitating and incurable disease. The B2B cohort includes 478 women diagnosed with incident primary breast cancer (stages I to III) who were recruited from Calgary, Alberta and surrounding areas between February 2010 and July 2015. Four projects have been conducted to date, utilizing data and samples from this cohort. These studies have found the following: (a) women with insufficient or deficient levels of vitamin D (25[OH]D) concentrations in pretreatment serum samples had larger tumors and higher breast cancer grades, (b) several metabolomic biomarkers and cytokines were associated with tumor characteristics and time to recurrence, (c) additional biomarkers were found to be predictive for the high risk of bone metastasis and (d) circulating progastrin (hPG80) was associated with multiple survival outcomes. These research studies and future ones will provide new evidence on bone metastasis etiology in women diagnosed with early-stage breast cancer, improve identification of those at high risk and contribute to personalized treatment and prevention options. Full article

Shark bycatch represents a substantial issue in the management of oceanic fisheries. Utilizing data on shark bycatch from the longline fishery, as released by the Western and Central Pacific Fisheries Commission, this study applied the boosted regression tree model to examine the impact of environmental factors on the bycatch per unit effort (BPUE) of key bycatch species, as well as to predict the spatial distribution dynamics of both BPUE and bycatch risk (BR). The findings emphasize that the oxygen concentration, sea surface temperature, and chlorophyll-a concentration are paramount to sharks’ BPUE. Furthermore, the study compared the variations in environmental preferences across diverse shark species, pinpointing key environmental attributes defining the ecological niches of distinct shark populations. The spatial predictions identified the hotspots of BPUE and BR for the bigeye thresher shark (Alopias superciliosus), longfin mako (Isurus paucus), silky shark (Carcharhinus falciformis), and oceanic whitetip shark (Carcharhinus longimanus) in tropical latitudes (10° S to 15° N), and for the blue shark (Prionace glauca) and shortfin mako (Isurus oxyrinchus) in temperate zones (south of 30° S or north of 30° N). The geometric center analysis indicated that all shark species exhibited large annual fluctuations in BPUE and BR, and most populations displayed significant shifting trends. Several grids (5° × 5°) were identified as high-risk areas due to their considerable contribution to bycatch. Furthermore, the geometric centers of BR were observed to shift eastward towards equatorial waters, compared to the geometric centers of BPUE. This underscores the necessity of considering factors beyond BPUE when identifying critical areas for the implementation of area-specific bycatch mitigation measures. The insights derived from this study can enhance and support the development and enforcement of targeted area-based fishery management initiatives. Full article

The multi-model ensemble (MME) approaches are highly regarded in climate prediction and risk assessment for their capacity to integrate multiple global climate models (GCMs) and minimize uncertainties associated with individual models. However, the quantitative impacts of spatial scale, weighted ensemble, and bias correction on the spatiotemporal comprehensive performance of MME remain unknown. In this study, we comprehensively assessed the historical simulation capabilities of 41 CMIP6 GCMs at national, basin, and grid scales. Additionally, we investigated the impact of bias correction and weighted ensemble on enhancing climate simulation performance. The results indicate that CMIP6 models exhibit notable differences in simulating regional climate characteristics of China across different scales. Weighted multi-model ensemble schemes incorporating better-performing models consistently outperform equal-weight approaches, achieving an average 20.67% reduction in the DISO (distance between indices of simulation and observation) index, with temporal performance improvements being particularly pronounced. Bias correction played a critical role in the enhancement of MMEs, reducing DISO values by 41.60% on average, particularly in the spatial dimension. Among all MMEs, the grid-scale optimized ensemble (GBQ), combining bias correction, model selection, and performance-based weighting, demonstrated superior comprehensive performance, achieving the lowest DISO values across spatial and temporal dimensions. These findings provide new insights for enhancing regional climate simulation and evaluation, and they provide more reliable scientific information for investigating climate change and formulating adaptation strategies in China. Full article

Background: New safety concerns about targeted anticancer agents (TAAs) often emerge in the first few years after their initial regulatory approval. Our aim was to determine whether new serious and potentially fatal adverse drug reactions (ADRs) continue to emerge in the updated drug labels of TAAs several years after their initial regulatory approval and whether their emergence can be predicted. Methods: The updated drug labels of TAAs approved by the U.S. Food and Drug Administration before July 2013 were analyzed. Serious and potentially fatal ADRs were identified in the Warnings & Precautions (WPs) and Boxed Warnings (BWs) sections of the updated drug labels. Generalized linear mixed models were used to examine the associations between the number of adverse drug reactions and time, drug type (small molecules vs. monoclonal antibodies), and the availability of companion diagnostics for biomarkers. Results: Among 37 eligible TAAs, 25 (68%) were small molecules and 11 (30%) had available companion diagnostics for the biomarkers. Time was a significant predictor of new WPs (p ˂ 0.001) and BWs (p = 0.008). The updated drug labels of the small molecules received significantly more new WPs (p = 0.042) as compared to monoclonal antibodies. The availability of the companion diagnostics for the biomarkers did not have an impact on the emergence of new ADRs. Conclusions: New serious ADRs of TAAs continue to emerge in updated drug labels several years after their initial regulatory approval. Oncologists, regulators, and payers should be aware of the changing risk–benefit ratios of approved TAAs. Full article

Background/Objectives: Evaluating basic daily activities like sitting, standing, and walking is crucial for predicting preoperative risks and postoperative recovery. These functional abilities can be assessed through patient history or measured using objective tests. For this purpose, the 30-Second Sit-to-Stand (30STS) Test and Timed Up-and-Go (TUG) Test are frequently used in clinical settings. However, few studies have evaluated their effectiveness in anesthesia and orthopedics. In this study, we aimed to assess the applicability of these tests across clinical disciplines. Methods: A total of 43 patients who underwent total knee arthroplasty (TKA) surgery between January and December 2023 with American Society of Anesthesiologists (ASA) scores of 2–3 were retrospectively evaluated. The 30STS, TUG, and VAS scores were recorded preoperatively and on postoperative days 90–180. Results: The preoperative 30STS and TUG scores showed no statistically significant difference between the ASA 2–3 groups, but the ASA 2 group demonstrated a more pronounced performance improvement in both tests during the first 90 days postoperatively. The correlation tests revealed a strong positive relationship with the TUG Test and a moderate positive relationship with the 30STS and VAS scores. Conclusions: The correlation between the preoperative and postoperative results of the 30STS and TUG Tests suggests that preoperative tests can predict post-operative functional performance. However, the lack of a significant statistical relationship between the preoperative tests and ASA scores indicates that these tests may not be sufficiently useful for assessing the functional capacity. The better test outcomes in the ASA 2 patients indicate that combining these assessments with anesthetic evaluations may improve postoperative functional predictions, thereby promoting a multidisciplinary approach. Full article

The presence of moisture in the insulation of power transformers accelerates the degradation of both paper and oil, thereby increasing the risk of unexpected failures. Due to the hygroscopic nature of cellulose, the insulation can retain up to 8% moisture after the transformer manufacturing process. Reducing this moisture content is crucial in extending the operational lifespan of transformers. The drying cycle of paper insulation is a critical step in power transformer manufacturing, directly influencing the insulation’s longevity and overall performance. This paper introduces a nomogram that combines degradation and drying models, enabling the precise optimization of the drying process based on various parameters such as the temperature, paper mass, and extraction rate. The results of this study demonstrate that for a given extraction rate threshold, the required drying time can be determined based on the mass of paper to be dried, the drying temperature, and the degree of paper degradation (degree of polymerization). These predictive tools are essential for engineers and researchers aiming to enhance transformer reliability. Full article

Cronobacter sakazakii is an opportunistic food-borne pathogen that causes severe infections with high morbidity and mortality rates in neonates, the elderly, and immunocompromised individuals. The plant extracts containing natural antibacterial compounds are currently under consideration as alternatives to synthetic artificial preservatives for the control of C. sakazakii. There has been increasing interest in using plant-derived antimicrobials in combination with mild heat to control pathogens in preservative-free foods. In this study, the individual and combined effects of four independent variables, i.e., polyphenol-rich haskap extract (HE) concentration (2–10%), tannic acid (TA) concentration (0.1–0.5), temperature (35–55 °C), and time (1–5 min), on C. sakazakii inactivation were investigated by response surface methodology (RSM) with a five-level four factor central composite design (CCD) and an optimal combination for maximum inhibition was determined. The statistic metrics of R², R²_adjusted, R²_predicted, coefficient of variation (CV), Predicted Residual Error Sum of Squares (PRESSs), adequate precision, and lack-of-fit were used to reveal the prediction performance. The results revealed that all the independent variables, except time, influenced C. sakazakii inactivation. Among the independent variables, the temperature was the most effective variable (p < 0.0001) as regards inactivation. The synergistic effects of HE with TA and temperature were observed. Many possible optimum conditions of mild heat treatment that maximized the inhibition of C. sakazakii were obtained. The findings indicated that two distinct combinations were identified as the most effective inhibition of C. sakazakii: high concentration at low temperature and high temperature at low concentration. It can be concluded that haskap polyphenol extract, alone or in combination with tannic acid, has the potential to be used as a natural preservative to reduce the risk of C. sakazakii. Full article

Background/Objectives: Breast cancer remains a leading cause of cancer-related morbidity worldwide, and refining prognostic tools is essential for individualized patient management. Recent evidence suggests that the systemic immune–inflammation index (SII), derived from routine blood tests, may offer valuable prognostic insights. This study aimed to evaluate whether SII can reliably predict clinical outcomes for patients undergoing curative resection. Methods: We retrospectively analyzed patients with histologically confirmed breast cancer who underwent surgical intervention at a single tertiary center. Preoperative complete blood counts were used to calculate SII. Using receiver operating characteristic (ROC) curve analysis, we identified an optimal SII cutoff. Using statistical tests, including t-tests and ANOVA, we examined differences in clinicopathological factors between low- and high-SII groups. Using univariate and multivariate analyses, we explored associations between SII and variables such as tumor stage and hormone receptor status. Results: Patients with elevated SII levels showed significant associations with more advanced tumor stage and systemic inflammatory profiles. The identified SII cutoff separated patients into distinct risk groups, and high SII values correlated with poorer prognostic features. Multivariate models indicated that SII provided additional predictive value beyond standard markers. Conclusions: Our findings suggest that SII may provide prognostic insights into breast cancer, particularly in stratifying patients based on inflammatory profiles. However, the current study does not support the use of SII as a clinical tool for tailoring treatment strategies. Further preclinical and randomized controlled trials are required to determine its predictive utility and to assess its potential integration into personalized management approaches. Full article