Search Results (31,967)

Membranous nephropathy (MN) is the most prevalent cause of nephrotic syndrome (NS) in adults, and it can be primary (idiopathic) with an unknown cause or secondary due to a variety of conditions (lupus, infections, malignancies, medications, etc.). It progresses to chronic kidney disease (CKD) in up to 60% of patients, and 10 to 30% develop end-stage kidney disease (ESKD). This retrospective study examines the importance of specific factors, including baseline demographic and clinical data, kidney biopsy PH findings, and selected biochemical parameters, influencing MN outcomes after 10 years of follow-up. The cohort included 94 individuals in whom a diagnosis of MN was established by percutaneous biopsy of the left kidney’s lower pole at the University Clinical Center of Serbia (UCCS) between 2008 and 2013. According to the outcomes, patients were divided into three groups: the recovery (Rec) group, with complete remission, including normal serum creatinine (Scr) and proteinuria (Prt), the group with development of chronic kidney disease (CKD), and the group with development of end-stage kidney disease (ESKD). Nephropathologists graded pathohistological (PH) results from I to III based on the observed PH findings. During the follow-up period, 33 patients were in the Rec group, CKD developed in 53 patients, and ESKD developed in 8 patients. Baseline creatinine clearance levels (Ccr), Scr, and uric acid (urate) were found to be significantly associated with the outcomes (p < 0.001). The lowest values of baseline Scr and urate were observed in the Rec group. The presence of acute kidney injury (AKI) or CKD at the time of kidney biopsy was associated with the more frequent development of ESKD (p = 0.02). Lower Ccr was associated with a higher likelihood of progressing to CKD (B = −0.021, p = 0.014), whereas older age independently predicted progression to ESKD (B = 0.02, p = 0.032). Based on this study, it was concluded that the most important biochemical and clinical factors that are associated with the outcomes of this disease are the values of Scr, Ccr, and urate and the existence of CKD at the time of kidney biopsy. Unlike most previous studies, the presence of HTN had no statistical significance in the outcome of the disease. Full article

Gastric-type cervical adenocarcinoma (GCA) is a rare and aggressive subtype of cervical adenocarcinoma. Despite its clinical significance, its molecular carcinogenesis and therapeutic targets remain poorly understood. This study aimed to compare the clinicopathological, immunohistochemical, and molecular profiles of GCA and usual-type cervical adenocarcinoma (UCA), exploring prognostic and therapeutic biomarkers in a Japanese population. A total of 110 cervical adenocarcinoma cases, including 16 GCA and 94 UCA cases, were retrospectively analyzed for clinicopathological features, and a panel of immunohistochemical markers was assessed. Sanger sequences were performed for the KRAS, PIK3CA, and BRAF genes, and survival and clinicopathological correlations were assessed using Kaplan–Meier and Cox regression analyses. GCA was significantly associated with more aggressive features than UCA, including lymph node involvement, advanced FIGO stages, increasing recurrence rate, and poor survival status. High ARID1B expression was observed in a subset of GCA cases and correlated with worse progression-free and overall survival. Additionally, PD-L1 expression was more frequent in GCA than UCA and was associated with unfavorable prognostic factors. Conversely, UCA cases showed strong p16 expression, supporting their HPV-driven pathogenesis. Molecular profiling revealed KRAS and PIK3CA mutations in both subtypes, while BRAF mutations were identified exclusively in GCA. These findings reveal distinct clinical and molecular profiles for both tumor types and underscore ARID1B and PD-L1 as predictive prognostic and therapeutic biomarkers in GCA, implicating the use of subtype-specific treatment strategies. Full article

In this study, we aimed to address the lack of systematic research on key collision dynamics parameters (elastic restitution coefficient) in the full mechanization of rapeseed operations, which hinders the development of precision agriculture. In this present work, the restitution coefficient of rapeseed was systematically investigated, and a predictive model (R² = 0.959) was also established by using Box–Behnken design response surface methodology (BBD-RSM). The results show that the collision restitution coefficient varies in the range of 0.539–0.649, with the key influencing factors ranked as follows: moisture content (M_c) > material layer thickness (L) > drop height (H). The EDEM simulation methodology was adopted to validate the experimental results, and the results show that there is a minimal relative error (−1% < δ < 1%) between the measured and simulated rebound heights, indicating that the established model shows a reliable prediction performance. Moreover, by comprehensively analyzing stress, strain, and energy during the collision process between rapeseed and Q235 steel, it can be concluded that the process can be divided into five stages—free fall, collision compression, collision recovery, rebound oscillation, and rebound stabilization. The maximum stress (1.19 × 10⁻² MPa) and strain (6.43 × 10⁻⁶ mm) were observed at the beginning of the collision recovery stage, which can provide some theoretical and practical basis for optimizing and designing rapeseed machines, thus achieving the goals of precise control, harvest loss reduction, and increased yields. Full article

Background/Objectives: This study aimed to create a ‘carbapenem resistance score’ with the risk factors of carbapenem-resistant Gram-negative bacterial infections (GNBIs) in patients with hematological malignancies. Methods: Patients with carbapenem-resistant and susceptible GNBIs were included in this study and compared in terms of risk factors. Three models of “carbapenem resistance risk scores” were created with statistically significant variables. Results: The study included 154 patients with hospital-acquired GNBIs, of whom 64 had carbapenem-resistant GNBIs and 90 had carbapenem-susceptible GNBIs. Univariate and multivariate analyses identified several statistically significant risk factors for carbapenem resistance, including transfer from another hospital or clinic (p = 0.038), prior use of antibiotics like fluoroquinolones (p = 0.009) and carbapenems (p = 0.001), a history of carbapenem-resistant infection in the last six months (p < 0.001), rectal Klebsiella pneumoniae colonization (p < 0.001), hospitalization for ≥30 days (p = 0.001), and the presence of a urinary catheter (p = 0.002). Notably, the 14-day mortality rate was significantly higher in the carbapenem-resistant group (p < 0.001). Based on these findings, three risk-scoring models were developed. Common factors in all three models were fluoroquinolone use in the last six months, rectal K. pneumoniae colonization, and the presence of a urinary catheter. The fourth variable was transfer from another hospital (Model 1), a history of carbapenem-resistant infection (Model 2), or hospitalization for ≥30 days (Model 3). All models demonstrated strong discriminative power (AUC for Model 1: 0.830, Model 2: 0.826, Model 3: 0.831). For all three models, a cutoff value of >2.5 was adopted as the threshold to identify patients at high risk for carbapenem resistance, a value which yielded high positive and negative predictive values. Conclusions: This study successfully developed three practical risk-scoring models to predict carbapenem resistance in patients with hematological malignancies using common clinical risk factors. A cutoff score of >2.5 proved to be a reliable threshold for identifying high-risk patients across all models, providing clinicians with a valuable tool to guide appropriate empirical antibiotic therapy. Full article

This study investigates mechanisms that influence how users perceive a technology’s usefulness after adoption as they continue to use the technology. The Expectation Confirmation Model (ECM) has been widely used to examine the key drivers of IT continuance, emphasizing perceived usefulness as a central factor. Although researchers have explored factors, such as ease of use, trust, and site quality, affecting post-adoption perceived usefulness, the mechanisms shaping post-adoption perceived usefulness remain underexplored. This study proposes that post-adoption perceived usefulness is shaped through the actualization of the technology’s affordances. Using a survey focused on fitness app usage (e.g., Fitbit), we examined various affordances users actualize and whether actualization of an affordance shapes their perception of usefulness. Results show that some affordances are actualized widely by most users (e.g., exercise status updating) while others are actualized by fewer users (e.g., reminders to exercise or guiding users how to exercise). Moreover, when an affordance is widely actualized, it significantly influences users’ perceptions of usefulness within the ECM framework. Given that perceived usefulness is a key factor in predicting IT continuance, our findings contribute to the literature by highlighting the influence of actualized affordances on perceptions of usefulness and hence IT continuance. Full article

Chronic kidney disease (CKD) has now reached epidemic proportions in many parts of the world, primarily due to the high incidence of diabetes and hypertension. By 2040, CKD is predicted to be the fifth-leading cause of years of life lost. Developing strategies to prevent CKD and to reduce its progression to kidney failure is thus of great public health significance. Hypertension is known to be both a cause and a consequence of kidney damage and an eminently modifiable risk factor. An increased risk of hypertension, especially among women, has been linked to chronic exposure to the ubiquitous food contaminant cadmium (Cd). The mechanism is unclear but is likely to involve its action on the proximal tubular cells (PTCs) of the kidney, where Cd accumulates. Here, it leads to chronic tubular injury and a sustained drop in the estimated glomerular filtration rate (eGFR), a common sequela of ischemic acute tubular necrosis and acute and chronic tubulointerstitial inflammation, all of which hinder glomerular filtration. The present review discusses exposure levels of Cd that have been associated with an increased risk of hypertension, albuminuria, and eGFR ≤ 60 mL/min/1.73 m² (low eGFR) in environmentally exposed people. It highlights the potential role of 20-hydroxyeicosatetraenoic acid (20-HETE), the second messenger produced in the kidneys, as the contributing factor to gender-differentiated effects of Cd-induced hypertension. Use of GFR loss and albumin excretion in toxicological risk calculation, and derivation of Cd exposure limits, instead of β₂-microglobulin (β₂M) excretion at a rate of 300 µg/g creatinine, are recommended. Full article

Ship structures are subjected to cyclic loading from waves and currents during operation, which can lead to fatigue failure, particularly at locations with structural discontinuities such as welds. Although various fatigue assessment methods have been developed, there is a lack of experimental data and comparative studies for actual ship structure details. This study addresses this limitation by evaluating the fatigue strength of longi-web connections in hull structures using local stress approaches, including hot spot stress, effective notch stress, notch stress intensity factor, and structural stress methods. Finite element analyses were conducted, and the predicted fatigue lives and failure locations were compared with experimental results. Although there are some differences between each method, all methods are valid and reasonable for predicting the primary failure locations and evaluating fatigue life. These findings provide a basis for considering suitable fatigue assessment methods for welded ship structures with respect to joint geometry and failure mechanisms. Full article

Background and Objectives: There is a global rise of public interest in integrative medicine. The principles of integrative medicine combining conventional medicine with evidence-based complementary therapies have been implemented in many medical areas, including plastic surgery, to improve patient’s outcome. The aim of the present study was to systematically analyze the application and use of additional non-pharmacological interventions (NPIs) of patients of a German department of plastic surgery. Materials and Methods: The present real-world data study utilized data from the Network Oncology registry between 2016 and 2021. Patients included in this study were at the age of 18 or above, stayed at the department of plastic surgery and received at least one plastic surgical procedure. Adjusted multivariable logistic regression analyses were performed to detect associations between the acceptance of NPIs and predicting factors such as age, gender, year of admission, or length of hospital stay. Results: In total, 265 patients were enrolled in the study between January 2016 and December 2021 with a median age of 65 years (IQR: 52–80) and a male/female ratio of 0.77. Most of the patients received reconstructive surgery (90.19%), followed by hand surgery (5.68%) and aesthetic surgery (2.64%). In total, 42.5% of the enrolled patients accepted and applied NPIs. Physiotherapy, rhythmical embrocations, and compresses were the most often administered NPIs. Conclusions: This exploratory analysis provides a descriptive overview of the application and acceptance of NPIs in plastic surgery patients within a German integrative care setting. While NPIs appear to be well accepted by a subset of patients, further prospective studies are needed to evaluate their impact on clinical outcomes such as postoperative recovery, pain management, patient-reported quality of life, and overall satisfaction with care. Full article

Coarse-grained soils serve as essential fill materials in earth–rock dam engineering, where their mechanical properties critically influence dam deformation and stability, directly impacting project safety. Artificial intelligence (AI) techniques are emerging as powerful tools for predicting the mechanical properties of coarse-grained soils. However, AI-based prediction models for these properties face persistent challenges, particularly in parameter tuning—a process requiring substantial computational resources, extensive time, and specialized expertise. To address these limitations, this study proposes a novel prediction model that integrates Adaptive Simulated Annealing (ASA) with an improved Particle Swarm Optimization (PSO) algorithm to optimize the Elman Neural Network (ENN). The methodology encompasses three key aspects: First, the standard PSO algorithm is enhanced by dynamically adjusting its inertial weight and learning factors. The ASA algorithm is then employed to optimize the Adaptive PSO (APSO), effectively mitigating premature convergence and local optima entrapment during training, thereby ensuring convergence to the global optimum. Second, the refined PSO algorithm optimizes the ENN, overcoming its inherent limitations of slow convergence and susceptibility to local minima. Finally, validation through real-world engineering case studies demonstrates that the ASA-PSO-optimized ENN model achieves high accuracy in predicting the mechanical properties of coarse-grained soils. This model provides reliable constitutive parameters for stress–strain analysis in earth–rock dam engineering applications. Full article

Background: Despite therapeutic advances, morbidity and mortality remain high in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA), primarily due to increased cardiovascular risk. Objectives: Our study aimed to evaluate the cardiovascular risk profile and biomarker dynamics in patients with RA and PsA treated with Janus kinase inhibitors (JAKis). To our knowledge, this is the first study assessing Lp(a) levels in this context. Methods: This prospective, observational study assessed 48 adult patients. The follow-up period was 12 months. Traditional cardiovascular risk factors and biological markers, including lipid profile, lipoprotein(a) [Lp(a)], and uric acid (UA), were assessed at baseline and follow-up. Correlations between JAKi therapy, lipid profile changes, and cardiovascular risk factors were investigated. Cox regression analysis was used to identify predictors of non-major cardiovascular events. Results: A strong positive correlation was observed between baseline and 12-month Lp(a) levels (r = 0.926), despite minor statistical shifts. No major cardiovascular events occurred during follow-up; however, 47.9% of patients experienced non-major cardiovascular events (e.g., uncontrolled arterial hypertension, exertional angina, and new-onset arrhythmias). Active smoking [hazard ratio (HR) 9.853, p = 0.005], obesity (HR 3.7460, p = 0.050), and arterial hypertension (HR 1.219, p = 0.021) were independent predictors of these events. UA (HR 1.515, p = 0.040) and total cholesterol (TC) (HR 1.019, p = 0.034) were significant biochemical predictors as well. Elevated baseline Lp(a) combined with these factors was associated with an increased event rate, particularly after age 60. Conclusions: Traditional cardiovascular risk factors remain highly prevalent and predictive, underscoring the need for comprehensive cardiovascular risk management. Lp(a) remained stable and may serve as a complementary biomarker for risk stratification in JAKi-treated patients. Full article

Background/Objectives: Myelodysplastic syndrome (MDS) is a heterogeneous clonal hematopoietic disorder characterized by ineffective hematopoiesis and leukemic transformation risk. Current therapies show limited efficacy, with ~50% of patients failing hypomethylating agents. This review aims to synthesize recent discoveries through an integrated network model and examine translation into precision therapeutic approaches. Methods: We reviewed breakthrough discoveries from the past three years, analyzing single-cell multi-omics technologies, epitranscriptomics, stem cell architecture analysis, and precision medicine approaches. We examined cell-type-specific splicing aberrations, distinct stem cell architectures, epitranscriptomic modifications, and microenvironmental alterations in MDS pathogenesis. Results: Four interconnected mechanisms drive MDS: genetic alterations (splicing factor mutations), aberrant stem cell architecture (CMP-pattern vs. GMP-pattern), epitranscriptomic dysregulation involving pseudouridine-modified tRNA-derived fragments, and microenvironmental changes. Splicing aberrations show cell-type specificity, with SF3B1 mutations preferentially affecting erythroid lineages. Stem cell architectures predict therapeutic responses, with CMP-pattern MDS achieving superior venetoclax response rates (>70%) versus GMP-pattern MDS (<30%). Epitranscriptomic alterations provide independent prognostic information, while microenvironmental changes mediate treatment resistance. Conclusions: These advances represent a paradigm shift toward personalized MDS medicine, moving from single-biomarker to comprehensive molecular profiling guiding multi-target strategies. While challenges remain in standardizing molecular profiling and developing clinical decision algorithms, this systems-level understanding provides a foundation for precision oncology implementation and overcoming current therapeutic limitations. Full article

HIV infection and hypertensive disorders of pregnancy (HDP), particularly preeclampsia (PE) with severe features, are leading causes of maternal mortality worldwide. This study investigates the role of asymmetric dimethylarginine (ADMA) and prostacyclin (PGI2) concentrations in endothelial impairment in normotensive pregnant versus PE women within an HIV endemic setting in KwaZulu-Natal Province, South Africa. The study population (n = 84) was grouped according to pregnancy type, i.e., normotensive (n = 42) and PE (n = 42), and further stratified by HIV status. Clinical factors were maternal age, weight, blood pressure (both systolic and diastolic) levels, and gestational age. Plasma concentrations of ADMA and PGI2 were measured using the enzyme-linked immunoassay (ELISA). Differences in outcomes were analyzed using the Mann–Whitney U and Kruskal–Wallis test together with Dunn’s multiple-comparison post hoc test. The non-parametric data were presented as medians and interquartile ranges. Gravidity, gestational age, and systolic and diastolic blood pressures were significantly different across the study groups where p < 0.05 was deemed significant. Furthermore, the concentration of ADMA was significantly elevated in PE HIV-positive vs. PE HIV-negative (p = 0.0174) groups. PGI2 did not show a significant difference in PE compared to normotensive pregnancies (p = 0.8826) but was significantly different across all groups (p = 0.0212). An increase in plasma ADMA levels was observed in the preeclampsia HIV-negative group compared to the normotensive HIV-negative group. This is linked to the role played by ADMA in endothelial impairment, a characteristic of PE development. PGI2 levels were decreased in PE compared to the normotensive group regardless of HIV status. These findings draw attention to the importance of endothelial indicators in pathogenesis and possibly early prediction of PE development. Full article

The introduction of mobile banking is essential in today’s financial sector, where technological innovation plays a critical role. To remain competitive in the current market, businesses must analyze client attitudes and perspectives, as these influence long-term demand and overall profitability. While previous studies have explored general adoption behaviors, limited research has examined how individual factors such as social influence, lifestyle compatibility, financial technology self-efficacy, and perceived usage cost affect mobile banking adoption among specific generational cohorts. This study addresses that gap by offering insights into these variables, contributing to the growing literature on mobile banking adoption, and presenting actionable recommendations for financial institutions targeting younger market segments. Using a structured questionnaire survey, data were collected from both users and non-users of mobile banking among the Gen Z population in the United States. The regression model significantly predicts mobile banking adoption, with an intercept of $-0.548$ ($p < 0.001$). Among the independent variables, perceived cost of usage has the strongest positive effect on adoption ($B=0.857$, $\beta =0.722$, $p < 0.001$), suggesting that adoption increases when mobile banking is perceived as more affordable. Social influence also has a significant positive impact ($B=0.642$, $\beta =0.643$, $p < 0.001$), indicating that peer influence is a central driver of adoption decisions. However, self-efficacy shows a significant negative relationship ($B=-0.343$, $\beta =-0.339$, $p < 0.001$), and lifestyle compatibility was found to be statistically insignificant ($p=0.615$). These findings suggest that reducing perceived costs, through lower fees, data bundling, or clearer communication about affordability, can directly enhance adoption among Gen Z consumers. Furthermore, leveraging peer influence via referral rewards, Partnerships with influencers, and in-app social features can increase user adoption. Since digital self-efficacy presents a barrier for some, banks should prioritize simplifying user interfaces and offering guided assistance, such as tutorials or chat-based support. Future research may employ longitudinal designs or analyze real-life transaction data for a more objective understanding of behavior. Additional variables like trust, perceived risk, and regulatory policies, not included in this study, should be integrated into future models to offer a more comprehensive analysis. Full article

The soil-borne fungal pathogen Verticillium dahliae causes devastating vascular wilt disease in numerous crops, including cotton. In this study, we reveal that VdSOX1, a highly conserved sarcosine oxidase gene, is significantly upregulated during host infection and plays a multifaceted role in fungal physiology and pathogenicity. Functional deletion of VdSOX1 leads to increased fungal virulence, accompanied by enhanced microsclerotia formation, elevated carbon source utilization, and pronounced upregulation of effector genes, including over 50 predicted secreted proteins genes. Moreover, the VdSOX1 knockout strains suppress the expression of key defense-related transcription factors in cotton, such as WRKY, MYB, AP2/ERF, and GRAS families, thereby impairing host immune responses. Transcriptomic analyses confirm that VdSOX1 orchestrates a broad metabolic reprogramming that links nutrient acquisition to immune evasion. Our findings identify VdSOX1 as a central regulator that promotes V. dahliae virulence by upregulating effector gene expression and suppressing host immune responses, offering novel insights into the molecular basis of host–pathogen interactions and highlighting potential targets for disease management. Full article

Background: Neonatal jaundice is common and can cause severe hyperbilirubinemia if untreated. The early identification of at-risk newborns is challenging despite the existing guidelines. Objective: This study aimed to identify the key maternal and neonatal risk factors for jaundice requiring phototherapy using machine learning. Methods: In this study hospital, phototherapy was administered following the American Academy of Pediatrics (AAP) guidelines when a neonate’s transcutaneous bilirubin level was in the high-risk zone. To identify the risk factors for phototherapy, we retrospectively analyzed the electronic medical records of 8242 neonates admitted between 2017 and 2022. Predictive models were trained using maternal and neonatal data. XGBoost showed the best performance (AUROC = 0.911). SHAP values interpreted the model. Results: Mode of delivery, neonatal feeding indicators (including daily formula intake and breastfeeding frequency), maternal BMI, and maternal white blood cell count were strong predictors. Cesarean delivery and lower birth weight were linked to treatment need. Conclusions: Machine learning models using perinatal data accurately predict the risk of neonatal jaundice requiring phototherapy, potentially aiding early clinical decisions and improving outcomes. Full article