Search Results (5,825)

Background: Epidermal growth factor receptor (EGFR) mutations are presented in approximately 50% of East Asian populations with advanced non-small cell lung cancer (NSCLC). While EGFR-tyrosine kinase inhibitors (TKIs) are the standard treatment, patient outcomes are also influenced by host-related factors. This study aimed to investigate clinical and radiological factors associated with early mortality and develop a prognostic prediction model in advanced EGFR-mutated NSCLC. Methods: A retrospective cohort was conducted in patients with EGFR-mutated NSCLC treated with first line EGFR-TKIs from January 2012 to October 2022 at Chiang Mai University Hospital. Clinical data and radiologic findings at the initiation of treatment were analyzed. A multivariable flexible parametric survival model was used to determine the predictors of death at 18 months. The predicted survival probabilities at 6, 12, and 18 months were estimated, and the model performance was evaluated. Results: Among 189 patients, 84 (44.4%) died within 18 months. Significant predictors of mortality included body mass index <18.5 or ≥23, bone metastasis, neutrophil-to-lymphocyte ratio ≥ 5, albumin-to-globulin ratio < 1, and mean pulmonary artery diameter ≥ 29 mm. The model demonstrated good performance (Harrell’s C-statistic = 0.72; 95% CI: 0.66–0.78). Based on bootstrap internal validation, the optimism-corrected Harrell’s C-statistic was 0.71 (95% CI: 0.71–0.71), derived from an apparent C-statistic of 0.75 (95% CI: 0.74–0.75) and an estimated optimism of 0.04 (95% CI: 0.03–0.04). Estimated 18-month survival ranged from 87.1% in those without risk factors to 2.1% in those with all predictors. A web-based tool was developed for clinical use. Conclusions: The prognostic model developed from fundamental clinical and radiologic parameters demonstrated promising utility in predicting 18-month mortality in patients with advanced EGFR-mutated NSCLC receiving first-line EGFR-TKI therapy. Full article

Objective: This study aims to examine the anterior chamber structure and related factors in 8-year-old children based on data from The Yamanashi Adjunct Study of the Japan Environment and Children’s Study (JECS). Methods: A total of 709 children aged 8 years (350 boys and 359 girls) who participated in the JECS Adjunct Study were included. The right eyes were primarily used for measurements. Optical Coherence Tomography (OCT) was utilized to scan the anterior chambers of the participants’ eyes. The following parameters were measured: Angle Opening Distance (AOD500, 750), Trabecular Iris Space Area (TISA500, 750), Anterior Chamber Angle (ACA500, 750), Peripheral Iris Thickness (IT500, 750), and Peripheral Corneal Thickness (PCT500, 750). The relationships between anterior chamber structure, axial length (AL), spherical equivalent (SE), logMAR (without correction), and body height were analyzed. Results: A significant negative correlation was found between SE and ACA (500: coefficient = −0.19; 750: −0.24), AOD (500: −0.19; 750: −0.24), and TISA (500: −0.17; 750: −0.23) (p < 0.001). Conversely, a significant positive correlation was observed between AL and ACA (500: 0.22; 750: 0.26), AOD (500: 0.25; 750: 0.30), and TISA (500: 0.24; 750: 0.29) (p < 0.001). Boys exhibited a longer AL (boys: girls = 23.30 ± 0.76 mm; girls = 22.79 ± 0.72 mm) and greater CT (500: boys = 812.82 ± 51.94 mm; girls = 784.48 ± 51.81 mm; 750: boys = 776.01 ± 48.64 mm; girls = 751.34 ± 49.63 mm) compared to girls (p < 0.001) despite no significant difference in body height. CT and IT showed no correlation with AL or SE, and visual acuity had minimal correlation with IT and CT. Conclusions: In our cohort of eight-year-old children, the anterior chamber angle structure correlates with ocular structures and refractive error, revealing notable differences between boys and girls. Full article

Microbiome analysis has revolutionized our understanding of various biological processes, spanning human health and epidemiology (including antimicrobial resistance and horizontal gene transfer), as well as environmental and agricultural studies. At the heart of microbiome analysis lies the characterization of microbial communities through the quantification of microbial taxa and their dynamics. In the study of bacterial abundances, it is becoming more relevant to consider their relationship, to embed these data in the framework of network theory, allowing characterization of features like node relevance, pathways, and community structure. In this study, we address the primary biases encountered in reconstructing networks through correlation measures, particularly in light of the compositional nature of the data, within-sample diversity, and the presence of a high number of unobserved species. These factors can lead to inaccurate correlation estimates. To tackle these challenges, we employ simulated data to demonstrate how many of these issues can be mitigated by applying typical transformations designed for compositional data. These transformations enable the use of straightforward measures like Pearson’s correlation to correctly identify positive and negative relationships among relative abundances, especially in high-dimensional data, without having any need for further corrections. However, some challenges persist, such as addressing data sparsity, as neglecting this aspect can result in an underestimation of negative correlations. Full article

In this paper, the accuracy of basic and advanced spiral inductor models for gallium nitride (GaN) integrated inductors is evaluated. Specifically, the experimental measurements of geometrically scaled circular spiral inductors, fabricated in a radio frequency (RF) GaN-on silicon technology, are exploited to estimate the errors of two lumped geometrically scalable models, i.e., a simple π-model with seven components and an advanced model with thirteen components. The comparison is performed by using either the standard performance parameters, such as inductance (L), quality factor (Q-factor), and self-resonance frequency (SRF), or the two-port scattering parameters (S-parameters). The comparison reveals that despite a higher complexity, the developed advanced model achieves a significant reduction in SRF percentage errors in a wide range of geometrical parameters, while enabling an accurate estimation of two-port S-parameters. Indeed, the correct evaluation of both SRF and two-port S-parameters is crucial to exploit the model in an actual circuit design environment by properly setting the inductor geometrical parameters to optimize RF performance. Full article

In this study, we analyzed data from 2992 cows to comprehensively evaluate the adult weight (WEI), a key growth and body-size indicator, in West China cattle, aiming to estimate the related phenotypic and genetic parameters. The analysis focused on four weight traits while considering non-genetic factors such as parity, season, year, and birth weight. Data were processed and corrected using a MIXED procedure and a multi-trait animal model. Results showed that these non-genetic factors significantly affected the weight traits (p < 0.05), which had high heritability (0.25–0.39) (p < 0.01). WEI is crucial for improving the genetic traits of cattle in western China and provides innovative approaches for optimizing herd management, enhancing the efficiency of genetic selection, and boosting beef cattle productivity. Full article

Understanding the differential impacts of emission sources of volatile organic compounds (VOCs) on formaldehyde (HCHO) levels is pivotal to effectively mitigating key photochemical radical precursors, thereby enhancing the regulation of atmospheric oxidation capacity (AOC) and ozone formation. This investigation systematically selected and analyzed year-long VOC measurements across three urban zones in Shenzhen, China. Photochemical age correction methods were implemented to develop the initial concentrations of VOCs before source apportionment; then Positive Matrix Factorization (PMF) modeling resolved six primary sources: solvent usage (28.6–47.9%), vehicle exhaust (24.2–31.2%), biogenic emission (13.8–18.1%), natural gas (8.5–16.3%), gasoline evaporation (3.2–8.9%), and biomass burning (0.3–2.4%). A machine learning (ML) framework incorporating Shapley Additive Explanations (SHAP) was subsequently applied to evaluate the influence of six emission sources on HCHO concentrations while accounting for reaction time adjustments. This machine learning-driven nonlinear analysis demonstrated that vehicle exhaust nearly always emerged as the primary anthropogenic contributor in diverse functional zones and different seasons, with gasoline evaporation as another key contributor, while the traditional reactivity metric method, ozone formation potential (OFP), tended to underestimate the role of the two sources. This study highlights the primacy of strengthening emission reduction of transportation sectors to mitigate HCHO pollution in megacities. Full article

This article presents a probabilistic methodology for assessing corrosion initiation in reinforced concrete structures exposed to chloride ingress. The approach addresses key limitations of conventional analytical models by accounting for non-diffusive barriers and incorporating a rigorous statistical treatment of censored data to mitigate biases introduced by limited simulation durations. A combination of analytical solutions for diffusion from opposite sides with time-dependent boundary conditions is also proposed and validated. The probabilistic study includes the depassivation assessment of a hollow pier section. The blocking effect caused by rebars is statistically characterised through correction factors derived from finite element simulations. These factors are used to adjust analytical solutions, which are computationally inexpensive. Results show that neglecting the rebar blocking effect can overestimate the mean corrosion initiation time by up to 42%, while the use of censored data reduces bias in lifetime estimates. The observed frequency of censored events reached up to 20% when simulations were truncated at 100 years. The corrected analytical models closely match the finite element results, statistically validating their application. The case study indicates premature corrosion initiation (less than 10 years to achieve target reliability), underscoring the need to better reconcile the desired levels of reliability with realistic input parameters for depassivation. Full article

Background: In clinical practice, visual outcomes with anti-VEGF therapy may be worse than those observed in clinical trials. In this study, we aim to investigate the long-term outcomes of neovascularization treated with intravitreal aflibercept injections (IAI) in a teaching hospital setting. Methods: This is a retrospective, single-center study including 81 nAMD patients (116 eyes), those both newly diagnosed and switched from ranibizumab. All patients had a follow-up duration of at least seven years. Treatment involved three monthly injections followed by either a pro re nata (PRN) or treat and extend regimen. Follow-up care was primarily conducted by training physicians. The primary endpoint was the change in best-corrected visual acuity (BCVA) over seven years. Secondary endpoints included central retinal thickness changes, qualitative OCT parameters, macular atrophy progression, injection frequency, and treatment adherence. Results: Among the 116 eyes, 52 (44.8%) completed the seven-year follow-up. Visual acuity improved by +2.1 letters in the overall population (+6.3 letters in treatment-naive eyes) after the loading phase but gradually declined, resulting in a loss of −12.3 letters at seven years. BCVA remained stable (a loss of fewer than 15 letters) in 57.7% of eyes. Central retinal thickness (CRT) decreased significantly during follow-up in both naive and switcher eyes. Macular atrophy occurred in 94.2% of eyes, progressing from 1.42 mm² to 8.55 mm² over seven years (p < 0.001). The mean number of injections was 4.1 ± 1.8 during the first year and 3.7 per year thereafter. Advanced age at diagnosis was a risk factor for loss to follow-up, with bilaterality being a protective factor against loss to follow-up (p < 0.05). Conclusions: This study highlights the challenges faced by a retina clinic in a teaching hospital. Suboptimal functional and anatomical outcomes in real life may derive from insufficient patient information and inconsistent monitoring, which contributes to undertreatment and affects long-term visual outcomes. It also raises concerns about supervision in a teaching hospital which needs to be improved. Full article

Background: This study presents an innovative approach to cardiovascular disease (CVD) risk prediction based on a comprehensive analysis of clinical, immunological and biochemical markers using mathematical modelling and machine learning methods. Baseline data include indices of humoral and cellular immunity (CD59, CD16, IL-10, CD14, CD19, CD8, CD4, etc.), cytokines and markers of cardiovascular disease, inflammatory markers (TNF, GM-CSF, CRP), growth and angiogenesis factors (VEGF, PGF), proteins involved in apoptosis and cytotoxicity (perforin, CD95), as well as indices of liver function, kidney function, oxidative stress and heart failure (albumin, cystatin C, N-terminal pro B-type natriuretic peptide (NT-proBNP), superoxide dismutase (SOD), C-reactive protein (CRP), cholinesterase (ChE), cholesterol, and glomerular filtration rate (GFR)). Clinical and behavioural risk factors were also considered: arterial hypertension (AH), previous myocardial infarction (PICS), aortocoronary bypass surgery (CABG) and/or stenting, coronary heart disease (CHD), atrial fibrillation (AF), atrioventricular block (AB block), and diabetes mellitus (DM), as well as lifestyle (smoking, alcohol consumption, physical activity level), education, and body mass index (BMI). Methods: The study included 52 patients aged 65 years and older. Based on the clinical, biochemical and immunological data obtained, a model for predicting the risk of premature cardiovascular aging was developed using mathematical modelling and machine learning methods. The aim of the study was to develop a predictive model allowing for the early detection of predisposition to the development of CVDs and their complications. Numerical methods of mathematical modelling, including Runge–Kutta, Adams–Bashforth and backward-directed Euler methods, were used to solve the prediction problem, which made it possible to describe the dynamics of changes in biomarkers and patients’ condition over time with high accuracy. Results: HLA-DR (50%), CD14 (41%) and CD16 (38%) showed the highest association with aging processes. BMI was correlated with placental growth factor (37%). The glomerular filtration rate was positively associated with physical activity (47%), whereas SOD activity was negatively correlated with it (48%), reflecting a decline in antioxidant defence. Conclusions: The obtained results allow for improving the accuracy of cardiovascular risk prediction, and form personalised recommendations for the prevention and correction of its development. Full article

Objectives: This study sought to echocardiographic manifestations and the related risk factors affecting the prognosis of isolated congenitally corrected transposition of the great arteries (CCTGA). Methods: A total of 143 patients (≥18 years of age) were diagnosed with isolated CCTGA at Anzhen Hospital. The patients were classified as the operation group and the non-operation group depending on whether they had undergone tricuspid valve surgery. The echocardiographic data and follow-up were compared, and the primary outcomes examined were defined as death or heart transplantation. Results: The average age of 143 patients with isolated CCTGA was 39.93 ± 13.50 years. Tricuspid valve surgery was performed in 31 patients with isolated CCTGA, and 112 patients did not undergo tricuspid valve surgery. The incidence of tricuspid valve structural changes in the operation group was 39.1%, and this group had higher numbers of patients with right ventricular diastolic diameter, right ventricular systolic diameter, left atrial dimensions, and regurgitation before surgery compared with the non-operation group (p < 0.05). Follow-up results showed no significant difference in the number of death/heart transplantations, and the incidence of systemic ventricular ejection fraction (SVEF) < 40% between the two groups. The survival rate of the surgery group was higher than that of the non-surgery group, although not statistically significant (p = 0.123). Age, right ventricular end-diastolic diameter, and decreased SVEF at the first diagnosis are independent predictive risk factors for major adverse outcomes. Conclusions: Adult patients with isolated CCTGA may have structural abnormalities in their tricuspid valves. There were no significant differences in the incidence of adverse outcomes, morphological right ventricular systolic dysfunction, and survival between the surgery group and the non-surgery group. However, this study is a retrospective study, and the sample size of the surgical group is relatively small, which may limit the generalizability of the research conclusions. In the future, a prospective, large-scale study will be conducted to evaluate the therapeutic effect of tricuspid valve surgery on such patients. Full article

To address the issues of large errors, low accuracy, and time-consuming simulations in finite element (FE) models of tapping processes, which hinder the identification of optimal structural parameters, this study integrates FE simulation with experimental testing to optimize the structural parameters of spiral taps specifically designed for stainless steel. Initially, single-factor experiments were conducted to analyze the influence of mesh parameters on experimental outcomes, leading to the identification of optimal mesh coefficients. Subsequently, the accuracy of the FE tapping simulation model was validated by comparing trends in axial force, torque, and chip morphology between simulations and actual tapping experiments. Orthogonal experimental design combined with entropy weight analysis and range analysis was then employed to conduct FE simulations. The results indicated that the optimal structural parameter combination is a helix angle of 43°, cone angle of 19°, and cutting edge relief amount of 0.18 mm. Finally, based on this combination, optimized spiral taps were manufactured and subjected to comparative performance testing. The results demonstrated significant improvements: the average maximum axial force decreased by 33.22%, average maximum torque decreased by 13.41%, average axial force decreased by 38.22%, and average torque decreased by 24.87%. Error analysis comparing corrected simulation results with actual tapping tests revealed axial force and torque error rates of 5.04% and 0.24%, respectively. Full article

Alzheimer’s disease (AD) and ischemic stroke (IS) are prevalent neurological disorders that frequently co-occur in the same individuals. Recent studies have demonstrated that AD and IS share several common risk factors and pathogenic elements, including an overlapping genomic architecture. However, the relationship between IS risk gene polymorphisms and AD has been less extensively studied. We aimed at determining whether IS risk gene polymorphisms were associated with the risk of AD and the severity of AD in AD patients. We utilized data of AD patients and normal controls (NCs) sourced from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. IS risk single nucleotide polymorphisms (SNPs) were identified through the most recent and largest IS genome-wide association study (GWAS) meta-analysis. Subsequently, we conducted SNP-based association analysis of IS-risk SNPs with the risk of AD, along with amyloid, tau, and neuroimaging for AD. The generalized multifactor dimensionality reduction (GMDR) model was used to assess the interactions among IS-risk SNPs and apolipoprotein E (ApoE) ε4. Protein–protein interactions (PPIs) of the IS-risk genes product and APOE were explored using the STRING database. Seven IS-risk SNPs were involved in the study. Five SNPs were found to be associated with at least one measurement of cerebrospinal fluid (CSF) levels of amyloid-beta 1–42 (Aβ₄₂), total tau (t-tau), and phosphorylated tau 181 (p-tau₁₈₁), as well as the volumes of the hippocampus, whole brain, entorhinal cortex, and mid-temporal regions. After multiple testing corrections, we found that T allele of rs1487504 contributed to an increased risk of AD in non-ApoE ε4 carriers. The combination of rs1487504 and ApoE ε4 emerged as the optimal two-factor model, and its interaction was significantly related to the risk of AD. Additionally, C allele of rs880315 was significantly associated with elevated levels of CSF Aβ₄₂ in AD patients, and A allele of rs10774625 was significantly related to a reduction in the volume of the entorhinal cortex in AD patients. This study found that IS risk SNPs were associated with both the risk of AD and AD major indicators in the ADNI cohort. These findings elucidated the role of IS in AD from a genetic perspective and provided an innovative approach to predict AD through IS-risk SNPs. Full article

A critical gap exists between coastal communities’ need for accessible flood risk assessment tools and the availability of sophisticated modeling, which remains limited by technical barriers and computational demands. This study introduces three key innovations through Coastal Defense Pro: (1) the first operational web-based AI ensemble for coastal flood risk assessment integrating real-time multi-agency data, (2) an automated regional calibration system that corrects systematic model biases through machine learning, and (3) browser-accessible implementation of research-grade modeling previously requiring specialized computational resources. The system combines Bayesian neural networks with optional LSTM and attention-based models, implementing automatic regional calibration and multi-source elevation consensus through a modular Python architecture. Real-time API integration achieves >99% system uptime with sub-3-second response times via intelligent caching. Validation against Hurricane Isabel (2003) demonstrates correction from 197% overprediction (6.92 m predicted vs. 2.33 m observed) to accurate prediction through automated identification of a Chesapeake Bay-specific reduction factor of 0.337. Comprehensive validation against 15 major storms (1992–2024) shows substantial improvement over standard methods (RMSE = 0.436 m vs. 2.267 m; R² = 0.934 vs. −0.786). Economic assessment using NACCS fragility curves demonstrates 12.7-year payback periods for flood protection investments. The open-source Streamlit implementation democratizes access to research-grade risk assessment, transforming months-long specialist analyses into immediate browser-based tools without compromising scientific rigor. Full article

Congenital hypothyroidism (CH) is a leading preventable cause of neurocognitive impairment. Its incidence appears to be rising in several countries. We analysed 27 years of newborn-screening data (1997–2023) from the largest Chilean screening centre, covering 3,225,216 newborns (51.1% of national births), to characterise temporal trends and potential drivers of CH incidence. Annual CH incidence was modelled with Prais–Winsten regression to correct for first-order autocorrelation; additional models assessed trends in gestational age, sex, biochemical markers, and aetiological subtypes. We identified 1550 CH cases, giving a mean incidence of 4.9 per 10,000 live births and a significant yearly increase of 0.067 per 10,000 (95 % CI 0.037–0.098; p < 0.001). Mild cases (confirmation TSH < 20 mU/L) rose (+0.89 percentage points per year; p = 0.002). The program’s recall was low (0.05%). Over time, screening and diagnostic TSH values declined, total and free T4 concentrations rose, gestational age at diagnosis fell, and a shift from thyroid ectopy toward hypoplasia emerged; no regional differences were detected. The sustained increase in CH incidence, alongside falling TSH thresholds and growing detection of in situ glands, suggests enhanced recognition of milder disease. Ongoing surveillance should integrate environmental, iodine-nutrition, and genetic factors to clarify the causes of this trend. Full article

Creating a comfortable microclimate in the premises of buildings is currently becoming one of the priorities in the field of architecture, construction and engineering systems. The increased attention from the scientific community to this topic is due not only to the desire to ensure healthy and favorable conditions for human life but also to the need for the rational use of energy resources. This area is becoming particularly relevant in the context of global challenges related to climate change, rising energy costs and increased environmental requirements. Practice shows that any technical solutions to ensure comfortable temperature, humidity and air exchange in rooms should be closely linked to the concept of energy efficiency. This allows one not only to reduce operating costs but also to significantly reduce greenhouse gas emissions, thereby contributing to sustainable development and environmental safety. In this connection, this study presents a parametric assessment of the influence of climatic and geometric factors on the aerodynamic characteristics of the air cavity, which affect the heat exchange process in the ventilated layer of curtain wall systems. The assessment was carried out using a combined analytical calculation method that provides averaged thermophysical parameters, such as mean air velocity ($V_s$), average internal surface temperature ($t_{in.s}^{av}$), and convective heat transfer coefficient (${\alpha }_s$) within the air cavity. This study resulted in empirical average values, demonstrating that the air velocity within the cavity significantly depends on atmospheric pressure and façade height difference. For instance, a 10-fold increase in façade height leads to a 4.4-fold increase in air velocity. Furthermore, a three-fold variation in local resistance coefficients results in up to a two-fold change in airflow velocity. The cavity thickness, depending on atmospheric pressure, was also found to affect airflow velocity by up to 25%. Similar patterns were observed under ambient temperatures of +20 °C, +30 °C, and +40 °C. The analysis confirmed that airflow velocity is directly affected by cavity height, while the impact of solar radiation is negligible. However, based on the outcomes of the analytical model, it was concluded that the method does not adequately account for the effects of solar radiation and vertical temperature gradients on airflow within ventilated façades. This highlights the need for further full-scale experimental investigations under hot climate conditions in South Kazakhstan. The findings are expected to be applicable internationally to regions with comparable climatic characteristics. Ultimately, a correct understanding of thermophysical processes in such structures will support the advancement of trends such as Lightweight Design, Functionally Graded Design, and Value Engineering in the development of curtain wall systems, through the optimized selection of façade configurations, accounting for temperature loads under specific climatic and design conditions. Full article