Search Results (57,383)

Background: Well-known risk factors for soft tissue heterotopic ossification (HO) include aging and mechanical stress, which may be linked to oxidative stress and downstream nucleotide metabolites. Thus, we investigated the involvement of extracellular ATP (ex-ATP) and its metabolites in the oxidative stress-induced mineralization of TT-D6 cells and primary mouse tendon cells. Methods: An osteogenic culture with the intermittent addition of hydrogen peroxide was monitored for two weeks using metabolomic and gene expression analyses. Results: Calcium deposition was significantly enhanced by 0.3 mM hydrogen peroxide in the osteogenic media after 2 weeks, with minimal calcification in its absence. Similar results were observed in a medium transfer experiment using 3-day-old hydrogen peroxide-treated conditioned medium, which led to an increased expression of osterix and alkaline phosphatase. Metabolomic analysis revealed a gradual increase in ex-ATP and its metabolites, including ADP, AMP, and adenosine, in the medium. The metabolite increase was enhanced by hydrogen peroxide after 12 h. Moreover, exogenous adenosine (100 μM) increased mineralization in osteogenic media. Additionally, 1 μM dipyridamole, an inhibitor of equilibrative nucleoside transporter 1 (Ent1), also increased it in response to low-dose (0.1 mM) hydrogen peroxide. Conclusions: The enhanced osteogenic calcification of the tendon cell culture by hydrogen peroxide was associated with an increase in extracellular nucleotide metabolites, especially adenosine, with some evidence of causality. Full article

Oral squamous cell carcinoma (OSCC) remains a major cause of cancer-related mortality worldwide, with limited biomarker-driven tools for risk stratification. CD147 is a membrane glycoprotein implicated in tumor metabolism, invasion, immune evasion, and therapy resistance. This study aimed to evaluate the prognostic and predictive relevance of CD147 expression in distinct tumor compartments of OSCC. Formalin-fixed tumor samples from 229 OSCC patients were analyzed via tissue microarray and immunohistochemistry to assess CD147 expression in the tumor center, periphery, and adjacent mucosa. Associations with clinicopathological parameters, survival, and therapy response were evaluated using non-parametric statistical tests, Kaplan–Meier, multivariate Cox, and binary logistic regression analyses. Complementary transcriptomic and immunological analyses were performed using The Cancer Genome Atlas (TCGA), the University of Alabama at Birmingham Cancer data analysis (UALCAN), Tumor and Immune System Interaction Database (TISIDB), and the Genotype-Tissue Expression (GTEx) project’s datasets. Low CD147 expression in the tumor invasive front was independently associated with improved overall survival, while expression in the tumor center or mucosa showed no prognostic value. No significant associations between CD147 and adjuvant therapy response were identified. TCGA-based analyses confirmed CD147 overexpression in tumors and its correlation with immunosuppressive signaling and resistance-associated transcriptional networks. Peripheral CD147 expression serves as a compartment-specific, independent prognostic marker in OSCC in this retrospective single-center cohort. Its spatially restricted prognostic relevance and association with immune modulation and therapy resistance highlight CD147 as a promising candidate for future biomarker-driven and therapeutic strategies. Full article

Malignant gliomas are the most common primary tumors of the central nervous system (CNS), originating from glial cells. They account for 30% of all CNS tumors. Among them, glioblastoma (GBM) is the most common, accounting for 45% of all glial tumors, while low-grade gliomas (LGGs) account for 31.8% of all gliomas. The aim of this study was to analyze the protein-expression profile of HTR4 and PDE4D genes in patients with glioma by immunohistochemical (IHC) analysis, to determine whether some interrelationship between them exists, to correlate their expression with clinical and histopathological parameters and therapy, and to determine their impact on patients’ survival. In addition, we analyzed the level of genomic instability (GI) (microsatellite (MIN), chromosomal (CIN) and total GI) by AP-PCR, in order to understand whether it can represent a tool for biological stratification of glioma tumors and risk assessment. Our results revealed that synchronized expression of 5-HTR4 and PDE4D proteins represents a stable modulatory signaling axis of glial-tumor biology, and reflects the activity of cAMP signaling pathway, but cannot independently stratify patients. Moreover, our study confirms that the combination of MIN, CIN and total GI represents a powerful tool for biological tumor stratification, risk assessment and understanding the pathobiological spectrum of the disease. Full article

Lymphovascular invasion is an adverse pathologic feature in prostate cancer, but its independent molecular drivers remain unclear due to strong confounding by tumor grade and stage. We performed a confounder-adjusted transcriptomic analysis of 403 TCGA-PRAD samples. Differential expression was adjusted for Gleason score and pathological T stage. A transcriptional profile associated with LVI was derived and tested in multivariable logistic and Cox proportional hazards models for biochemical recurrence-free survival, with bootstrap internal validation. After multivariable adjustment, 129 genes were independently associated with LVI. This gene set was overwhelmingly enriched for interferon-alpha/beta signaling and antiviral response pathways. A continuous composite score derived from this profile predicted a reduced risk of biochemical recurrence independently of standard clinicopathological factors (adjusted HR per unit = 0.911, 95% CI: 0.835–0.993, p = 0.033). Multi-omics integration revealed subtle promoter hypomethylation and strong correlations between methylation and expression for key interferon genes, supporting transcriptional regulation. We identify a robust, interferon-response transcriptional profile that specifically defines LVI in prostate cancer after accounting for major clinical confounders. This transcriptional signature provides independent prognostic information, refines the biological understanding of LVI, and presents a novel targetable pathway for further investigation. Full article

Customer Segment Classification is a machine learning task in marketing analytics that involves assigning customers to predefined categories using features derived from historical transactional data. However, conventional approaches, such as statistical and clustering-based algorithms, may face challenges in fully capturing the nonlinear relationships in customer data, which can lead to limited insights and suboptimal segmentation outcomes. This paper introduces RFM-Net, an approach that integrates Deep Learning with Recency, Frequency, and Monetary (RFM) analysis for customer segment classification. By leveraging RFM features as input and labeled customer segments as output, we designed a specialized Convolutional Neural Network (CNN) model tailored for classification tasks. In the proposed method, labels are generated by a rule-based logic from RFM scores and then used as supervised ground truth. Accordingly, learning an expert-defined mapping is employed to model customer segmentation, rather than discovering a new segmentation structure. The proposed method enables businesses to classify customers into strategically meaningful segments such as Champions, Loyal Customers, At Risk, and Hibernating, thereby facilitating effective and targeted marketing strategies. Unlike traditional CNN architectures, RFM-Net offers a more compact, lightweight, and computationally efficient model with fewer layers and parameters, supporting improved interpretability and reduced risk of overfitting. Experimental results conducted on a real-world dataset demonstrated the effectiveness of RFM-Net with an accuracy of 94.33%. The results of this study showed a relative average increase of 13.17% compared to the results reported in previous studies on the same dataset. The core contribution of this research lies in combining the powerful generalization capabilities of deep learning with the effectiveness of RFM analysis, offering a robust solution for data-driven customer relationship management. Full article

Cooling curve analysis enables accurate determination of aluminum alloy solidification parameters while capturing important non-equilibrium phenomena that are difficult to resolve using thermodynamic models alone. Modern casting simulation tools such as MAGMASOFT and ProCAST provide advanced capabilities, including user-defined material databases and microstructure models, but their predictive accuracy depends strongly on the quality of alloy-specific input data. In particular, the effects of trace element variations and chemical modification treatments, such as strontium-induced depression of the Al–Si eutectic temperature, are not always quantitatively represented in generic databases. This study demonstrates that thermal analysis provides experimentally based solidification data under controlled cooling conditions representative of foundry practice. Cooling curve analysis directly records undercooling, recalescence, and modification-induced temperature shifts, including eutectic temperature changes of ~10 °C after strontium treatment, which significantly influence solidification kinetics and defect formation. A short industrial thermal analysis test enables the extraction of key parameters, including liquidus, eutectic, coherency, rigidity, and solidus temperatures; fraction-solid evolution; and latent heat release. When integrated into casting simulation databases, these experimentally derived parameters support improved modeling of feeding behavior, shrinkage porosity risk, hot tearing tendency, and microstructure development. The proposed approach positions cooling curve analysis as a practical complementary tool for calibrating and enhancing simulation input data under real alloy and process conditions. Full article

Large organizations face a critical systems integration challenge when executing multiple concurrent security modernization programs. This paper examines the U.S. Department of Defense’s simultaneous implementation of three transformational initiatives—post-quantum cryptography (PQC) migration, Zero Trust Architecture (ZTA) deployment, and AI security assurance—each operating under separate governance structures, timelines, and compliance frameworks. Through systematic evidence synthesis of 59 sources (47 policy/standards documents and 12 performance benchmarks), we identify cross-program dependencies that create integration failures when programs operate in isolation. We propose a shared modernization substrate—a four-layer infrastructure architecture (Cryptographic Services, Identity Management, Analytics Pipeline, Policy Orchestration) that enables coordinated execution while preserving program independence. The framework addresses the fundamental systems challenge of achieving interoperability across programs with misaligned schedules and competing resource demands. We introduce a five-level Triad Convergence Maturity Model (TCMM) with operationalized indicators enabling repeatable organizational assessment. Illustrative application to three DoD modernization contexts demonstrates the framework’s ability to differentiate maturity levels. Performance analysis synthesizes published benchmark data: enterprise PQC latency overhead is modest (measured), while tactical environment estimates of 158–383% overhead are derived from benchmark extrapolation under packet-loss assumptions (modeled). Scenario modeling suggests that coordinated incident response through the substrate architecture could substantially reduce risk exposure windows compared to siloed approaches (modeled). The framework transforms fragmented program execution into synchronized systems modernization, offering practical guidance for chief information officers, program managers, and enterprise architects managing concurrent technology transitions. Full article

Objectives: The general objective of the study was to analyze the influence of sociodemographic factors and care and hygiene practices on the appearance of Incontinence-Associated Dermatitis (IAD). The specific objectives were to identify the relationship between sociodemographic variables (age, sex, comorbidities) and the incidence of IAD, and to evaluate hygiene protocols (cleaning products and absorbent use and practices) and compare time to IAD onset according to the hygiene practices used. Methods: A multicenter, prospective cohort study was conducted across 10 social health centers. The study population consisted of older institutionalized patients with urinary and/or mixed incontinence who used absorbents continuously. The variables included risk assessment using validated scales, such as the Braden scale and the Perianal Assessment Tool (PAT), as well as ad hoc questionnaires. Survival analysis of time-to-event onset was assessed using the Kaplan–Meier curve and the Log-Rank test. Results: A statistically significant association was found between the occurrence of IAD and the Braden scale (p = 0.004) and the PAT scale (p = 0.02). However, no statistically significant association was found with age, sex, or the Barthel Index. Regarding hygiene, soapy wipes were associated with the highest incidence of IAD. In contrast, dry wipes were the most effective, with the lowest cumulative risk and the longest time-to-event (p = 0.001). The brand of the absorbent used had a significant influence (p = 0.024), suggesting that the “B” brand prevented one IAD per six patients compared with the “A” brand. The frequency of absorbent changes did not show a statistically significant association. Conclusions: The risk of developing IAD was strongly linked to the scores of the Braden and PAT scales, the brand of the absorbent (“B” being more effective), and the cleaning product used, with dry wipes being the most protective compared to soapy wipes. On the other hand, factors such as age, sex, degree of dependence (Barthel), or frequency of absorbent change did not show a significant influence on the appearance of IAD. Full article

Background/Objectives: Bacterial meningitis is a severe disease with a fatality rate of 5–50%. It is mainly caused by Streptococcus pneumoniae or Neisseria meningitidis, which can also cause simultaneous infections outside the central nervous system. Toll-like receptors (TLRs) have an important role in the innate immune system. The TLR2 subfamily comprises the four highly homologous members TLR1, TLR2, TLR6, and TLR10, which also have an important immunomodulatory role in infectious diseases. Methods: The study cohort consists of 190 bacterial meningitis patients aged 1 to 147 months from randomized clinical trials and 268 controls from Luanda, Angola. Polymorphisms of TLR2 (rs111200466) and TLR10 (rs10856837 and rs11096956) were determined using PCR-based methods and Sanger sequencing. The genotyping results were analyzed together with clinical data to determine whether gene polymorphisms of TLR2 and TLR10 are associated with susceptibility and outcome of bacterial meningitis in Angolan children. Results: At admission and during hospitalization, patients with pneumococcal meningitis carrying a variant (ins/del or del/del) of TLR2 rs111200466 had a significantly lower risk of coexisting infections (OR 0.27; 95% CI 0.11–0.65; p = 0.004), particularly pneumonia (OR 0.18; 95% CI 0.06–0.49; p = 0.001). In addition, haplotype analysis demonstrated that a variant genotype of TLR2 rs111200466 together with a wildtype of TLR10 SNPs (rs10856837 and rs11096956) may protect against coexisting pneumonia (OR 0.2; 95% CI 0.06–0.6; p = 0.007). Conclusions: This study suggests an association between coexisting infection and genetic variation in TLR2 and TLR10 of bacterial meningitis in Angolan children. Full article

Escalating global climate change has intensified the frequency and scale of wildfires in mountainous regions hosting transmission line infrastructure. These conflagrations act as extreme meteorological events, capable of generating localized heatwaves that compromise the air insulation of power lines and trigger protective relay operations, thereby posing systemic threats to regional grid stability. To enhance wildfire early-warning efficacy for grid security, this study formulates wildfire early warning for power transmission corridors as a regression-based risk prediction problem and proposes a hierarchical “global screening–local refinement” risk assessment framework. The primary contribution of this study lies in the integration of a machine-learning-based global wildfire risk screening model with tower-level spatial refinement using geographically weighted regression (GWR), enabling coordinated global–local wildfire risk characterization along power transmission corridors The framework employs a predictive model built on a Gradient Boosting Decision Tree algorithm, integrating geospatial and statistical analyses. A global risk model, utilizing historical data from the Himawari-8 satellite alongside meteorological, topographic, and anthropogenic variables, produces a composite risk index. This index is spatially interpolated via Kriging to generate stratified wildfire risk maps for broad-area assessment. For precise corridor-level analysis, these Globally Projected Risk Indices, along with localized terrain features, inter-tower clearance distances, and proximity to historical ignition points, are incorporated into a Geographically Weighted Regression model. This yields a spatially calibrated wildfire risk index along critical routes. The results show that the GBDT-based model achieved the best predictive performance among the evaluated regression models, with an R² of 0.626 and a mean squared error of 0.178. This approach offers a scientifically robust and operationally viable reference for wildfire prevention strategies in power line maintenance. Full article

Background and Objectives: Obstetric anal sphincter injuries (OASISs) are severe complications of vaginal delivery that can result in long-term pelvic floor dysfunction and reduced quality of life. Global data indicate a rising incidence of OASISs, including in Lithuania. This study aimed to identify risk factors for OASISs and evaluate their impact on urinary (UI) and fecal incontinence (FI), pelvic organ prolapse (POP), and quality of life in affected women. Materials and Methods: A retrospective case–control study was conducted at the Lithuanian University of Health Sciences Hospital (LUHS) Kauno Klinikos in 2024. Women who gave birth between 2004 and 2023 and experienced OASIS (n = 90) were compared with women matched for birth history but without perineal tears (n = 90). Data were collected from medical records and electronic questionnaires, including the International Consultation on Incontinence Questionnaire—Short Form (ICIQ-SF), Wexner score, Pelvic Organ Prolapse Symptom Score (POP-SS), and Pelvic Floor Impact Questionnaire (PFIQ-7). Participants were grouped by delivery year (2004–2013 or 2014–2023). Statistical analysis was performed using Mann–Whitney U, Chi-square, Fisher’s exact and Student’s t-tests, with p < 0.05 considered significant. Results: Newborn weight and vacuum-assisted delivery were significantly associated with OASIS (p < 0.05 and p = 0.029). In the 2014–2023 cohort, women with OASIS reported significantly higher rates and severity of UI, FI, and POP symptoms compared to controls. Quality of life scores related to UI and FI were significantly worse in the recent OASIS group, whereas no significant differences were observed in the 2004–2013 cohort. Conclusions: Between 2004 and 2023, 0.4% of women who gave birth at LUHS experienced third- or fourth-degree perineal tears, with newborn weight and vacuum extraction identified as risk factors. These women reported higher rates of UI and FI and POP, and those who delivered between 2014 and 2023 rated their related quality of life significantly worse than women without OASIS. Full article

Background: Acute kidney injury (AKI) is a serious complication in vasculitis patients and may adversely affect prognosis. However, the role of blood urea nitrogen (BUN) as a predictor of AKI and mortality in vasculitis has not been fully elucidated. Methods: We retrospectively analyzed 701 patients with large-, medium-, and small-vessel vasculitis from the MIMIC-III/IV databases to evaluate the relationship between BUN, AKI occurrence, and mortality. AKI was defined according to the KDIGO serum creatinine criteria. Logistic and Cox regression models, restricted cubic spline (RCS) analyses, and multiple machine learning models were employed to identify risk factors and assess predictive performance. Results: AKI occurred in 25.1% (176/701) of vasculitis patients and was associated with significantly higher 30- and 365-day mortality rates (p < 0.05). Multivariable logistic regression identified BUN as an independent predictor of AKI (OR: 1.03; 95% CI: 1.02–1.05; p < 0.0001). Patients in the highest BUN tertile had a 5.67-fold greater risk of AKI compared to the lowest tertile (p < 0.0001). The Cox regression confirmed BUN as an independent predictor of 30- and 365-day mortality among patients with AKI (p < 0.05). The RCS analysis identified a critical BUN threshold of 32 mg/dL, above which the mortality risk markedly increased. Machine learning models further validated the prognostic significance of BUN and age, with the logistic regression model achieving the highest predictive accuracy (area under the curve: 0.904). Conclusions: BUN is a practical predictor of AKI and mortality in vasculitis and may assist early risk stratification in this population. Full article

Older patients with unresectable locally advanced non-small-cell lung cancer (NSCLC) frequently receive concurrent chemoradiotherapy (CCRT) with daily low-dose carboplatin; however, real-world data on its efficacy, safety, and prognostic factors remain limited. We aimed to retrospectively evaluate the clinical outcomes of this regimen and examined whether systemic inflammation-based indices predict prognosis in this setting. We reviewed 52 consecutive patients with locally advanced NSCLC treated with first-line CCRT using daily low-dose carboplatin at three Japanese institutions between April 2007 and December 2019. The median progression-free survival (PFS) and overall survival (OS) were 11.5 and 40.1 months, respectively. Twenty patients received durvalumab as consolidation therapy. In the overall cohort, multivariate analysis identified the Glasgow Prognostic Score (GPS) as an independent predictor of PFS. A GPS of 0–1 was also associated with a significantly longer OS in univariate analysis. CCRT with daily low-dose carboplatin provided durable disease control with acceptable toxicity in older patients with unresectable stage II/III NSCLC. The GPS appears to be a simple marker for PFS in this population and may aid in pretreatment risk stratification alongside histology and consolidation strategies. Full article

Objectives: To explore the association between the dietary inflammatory index (DII) and type 2 diabetes mellitus (T2DM) risk and to evaluate potential interactions of obesity and dyslipidemia in the context of this association. Methods: This cohort study included 8055 adults. Dietary data from food frequency questionnaires were used to calculate DII, reflecting dietary inflammatory potential. T2DM was defined as fasting plasma glucose ≥7.0 mmol/L, HbA1c ≥6.5%, a documented T2DM history, or glucose-lowering therapy. Multivariate Cox regression models assessed the DII-T2DM association, with multiplicative interaction analysis via product terms and additive interactions evaluated using relative excess risk due to interaction (RERI) and attributable proportion due to interaction (AP). Results: After a median 5.01-year follow-up, 1034 incident T2DM cases had occurred. The highest versus lowest DII quartile showed an unadjusted HR of 1.20 (95% CI: 1.01–1.42), which attenuated after adjusting for demographic and clinical confounders. In women, the highest DII quartile had a significantly adjusted HR of 1.36 (1.03–1.81), with a 16% increased risk per 1-SD DII increase (adjusted HR:1.16, 95% CI:1.04–1.29); no association was observed in men. Positive multiplicative and additive interactions emerged in total participants between high DII and central obesity (measured by waist circumference/waist-to-hip ratio), accounting for 22% and 31% of excess T2DM risk, respectively. No interactions were found with dyslipidemia and other obesity metrics (BMI, waist-to-height ratio). Conclusions: This study suggests that a highly pro-inflammatory diet may be associated with an increased incident risk of T2DM among women. Waist circumference and waist-to-hip ratio and a high DII are found to act synergistically in elevating T2DM risk. Full article

Background/Objectives: Toothpaste ingredients such as strontium chloride (SrCl₂) and potassium carbonate (K₂CO₃) are recognized for their desensitizing and remineralizing effects but may be absorbed through the oral mucosa. Their potential cytotoxic and cardiotoxic properties, however, remain inadequately characterized. Here, we investigated the effects of SrCl₂ and K₂CO₃ on mouse-induced pluripotent stem cells (iPSCs) and iPSC-derived cardiomyocytes (iPSC-CMs). Methods: Cells were exposed to varying concentrations of each compound for up to 72 h. Real-time cell analysis (xCELLigence RTCA Cardio system) was used to assess proliferation, and flow cytometry was used to evaluate cell viability. Functional properties of iPSC-CMs were examined using multi-electrode array (MEA) recordings and xCELLigence-based impedance measurements. Cardiac marker expression was examined via immunofluorescence and quantitative RT-PCR. Results: Both SrCl₂ and K₂CO₃ affected iPSC proliferation and reduced viability in a dose- and time-dependent manner, accompanied by altered embryoid body (EB) morphology and increased cell death. In iPSC-CMs, both compounds downregulated key cardiac genes and disrupted spontaneous beating activity, with effects intensifying at higher concentrations. Conclusions: These results demonstrate that SrCl₂ and K₂CO₃ induced dose-dependent cytotoxic and arrhythmogenic effects on iPSCs and iPSC-CMs. At elevated concentrations, these compounds impair iPSC-CM function and may pose safety concerns upon chronic exposure. Further mechanistic and long-term in vivo studies are warranted to assess their potential cardiotoxic risk in consumer oral care products. Full article