Search Results (25,042)

Background: Reliable identification remains a cornerstone of forensic investigations, particularly when encountering degraded remains or suboptimal biological evidence. This study evaluates the potential of dentine metabolomics, utilizing proton nuclear magnetic resonance (¹H-NMR) spectroscopy, to detect cancer-associated metabolic signatures in dental tissues for forensic applications. Methods: Forty-four non-carious second molars were analyzed, comprising 22 samples from deceased individuals with a documented history of cancer and 22 age- and sex-matched controls. Metabolomic profiling was conducted using ¹H-NMR spectroscopy to identify and quantify dentine metabolites. Statistical evaluation included unsupervised principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), receiver operating characteristic (ROC) curve analysis, and exploratory binary logistic regression. Results: Among the 209 identified metabolites, inosinic acid and 2-ketobutyric acid were identified as the most robust discriminative biomarkers across both multivariate and univariate frameworks. The exploration within-sample predictive model achieved a Nagelkerke R² of 0.822 and an overall classification accuracy of 90.9%, with a specificity of 95.5% and a sensitivity of 86.4%. These key metabolites are fundamentally associated with purine metabolism and oxidative stress pathways frequently dysregulated in oncogenesis. Conclusions: This pilot study suggests that dentine may retain metabolomic information associated with cancer comorbidity under heterogeneous postmortem conditions. However, the findings remain exploratory and require validation in larger cohorts with standardized postmortem variables before practical forensic implementation. Full article

Physical Unclonable Functions (PUFs) represent a highly promising hardware security primitive, yet they face constraints of insufficient reliability and threats from modeling attacks. This paper designs a novel Feed-Forward Crossbar Matrix Arbiter PUF (FC-MA PUF). It incorporates an inter-stage crossbar structure, a feed-forward control system, and a mechanism for selecting reliable challenge-response pairs. These features significantly enhance the structural non-linearity and stability, substantially improving security and adaptability to a wider range of operating environments. It provides a high-strength authentication solution with low resource overhead for lightweight security-demanding devices such as IoT devices. The proposed FC-MA PUF has been successfully implemented on a Field-Programmable Gate Array (FPGA) platform. Experimental results for the selected 4-stage FC-MA PUF configuration show a bias, inter-chip uniqueness, and bit error rate (BER) of 49.88%, 49.68%, and 0.018%, respectively. Furthermore, the structure allows for flexible configuration of the number of feed-forward modules based on practical application requirements: a greater number of feed-forward modules enhances security but also leads to an increased BER and a decreased proportion of stable challenge-response pairs. Experimental results based on a training set of 1,000,000 challenge-response pairs demonstrate that: with two feed-forward units, the stable (Challenge Response Pair)CRP ratio is 39.72% and the Covariance Matrix Adaptation Evolutionary Strategies (CMA-ES) attack prediction success rate is 58.20%; with three units, the ratio decreases to 29.12% and the prediction rate drops to 54.91%; with four units, these values further decline to 20.18% and 52.33% respectively. These results confirm that the proposed FC-MA PUF effectively resists multiple modeling attacks, including Logistic Regression (LR), Support Vector Machine (SVM), and CMA-ES. Full article

Background/Objectives: Sarcopenia (SP) and osteoporosis (OP) are common yet underrecognized complications of liver cirrhosis, contributing to increased morbidity and mortality. Their coexistence, termed osteosarcopenia (OS), represents a compounded musculoskeletal impairment. Insulin-like growth factor 1 (IGF-1), synthesized in the liver, has been implicated in muscle and bone metabolism. This study aimed to assess the prevalence and association of laboratory and clinical parameters with SP, OP, and OS in cirrhotic patients, with a focus on IGF-1 deficiency and their impact on mortality. Methods: This cross-sectional study included 100 cirrhotic patients at a tertiary center. Sarcopenia was diagnosed using CT-derived L3 skeletal muscle index and osteoporosis via the DEXA scan. IGF-1 levels and metabolic parameters were measured. Multivariate logistic regression identified laboratory and clinical factors associated with musculoskeletal complications. However, due to the cross-sectional design, causal relationships could not be inferred. Results: SP, OP, and OS were present in 41%, 22%, and 11% of patients, respectively. IGF-1 levels were significantly lower in patients with SP, OP, and OS (p < 0.05) and were independently associated with increased risk of SP (OR = 1.797, p = 0.006), OP (OR = 1.873, p = 0.045), and OS (OR = 2.326, p = 0.003). Mortality rates were significantly higher among patients with OS (72.7%), OP (77.3%), and SP (56.1%). OS conferred the highest adjusted mortality risk (OR = 2.739, p = 0.009), followed by SP (OR = 2.278, p = 0.015) and OP (OR = 1.958, p = 0.036). Conclusions: Musculoskeletal complications are highly prevalent and predictive of mortality in cirrhosis. IGF-1 deficiency is a strong independent biomarker for SP, OP, and OS. Routine screening and early intervention targeting IGF-1 pathways and nutrition may improve outcomes in this population. Full article

Background: The aim of this study was to derive and internally validate a prescriptive clinical prediction rule (CPR) for identifying baseline factors associated with short-term clinical improvement in patients with neck pain (NP) undergoing a manual therapy (MT)-based physiotherapy program. Methods: A prospective cohort study was conducted, including 71 patients with NP (18–65 years). Participants received six MT-based sessions over three weeks. Baseline assessments included Pain Intensity Numeric Rating Scale (PI-NRS), Neck Disability Index (NDI), Body Mass (BM), Body Mass Index (BMI), International Physical Activity Questionnaire-Short Form (IPAQ-SF), Hospital Anxiety and Depression Scale (HADS), Minnesota Satisfaction Questionnaire-Short Form (MSQ), and Craniovertebral Angle (CVA). Clinical improvement was defined using the Global Perceived Effect Scale (GPES-7). Univariate analyses, receiver operating characteristic (ROC) curve analysis, and forward stepwise logistic regression were performed to derive the predictive model. Results: Fifty-six participants (78.9%) reported moderate to complete improvement. BM ≥ 76.5 kg and MSQ score ≤ 42.5 were retained in the final regression model. When both predictors were present, the probability of clinical improvement increased to 96.43% (positive likelihood ratio = 7.58). The model demonstrated adequate fit (Nagelkerke R² = 0.247; Hosmer–Lemeshow p = 0.804). Internal validation yielded an optimism-corrected AUC of 0.741, suggesting minimal overfitting. Conclusions: Higher BM and lower MSQ score were associated with greater short-term improvement following MT in patients with NP. These findings highlight the relevance of integrating physical and psychosocial factors in prescriptive rehabilitation approaches. External validation of this CPR is required before clinical implementation. Full article

Background: Depression is a key psychosocial risk factor for cardiovascular disease (CVD); however, the degree to which lack of health insurance amplifies this risk remains unclear. Geographical disparities in mental health, cardiovascular outcomes, and insurance coverage further complicate prevention efforts. Understanding the interplay between these factors is crucial for planning targeted interventions to mitigate population-level cardiovascular risk. Objective: To assess whether health insurance modifies the relationship between depression and CVD among adults and to illustrate geographic disparities in combined mental health, cardiovascular risk, and insurance burden across US states and territories. Methods: We analyzed Behavioral Risk Factor Surveillance System (BRFSS) data from 2019 to 2023, including adults aged ≥18 years with complete data on depression, CVD, and health insurance status (n = 457,670). Logistic regression models were employed to estimate the relationship between depression and CVD, adjusting for demographic and behavioral risk factors. An interaction term between depression and lack of health insurance was included to examine moderation. State-level prevalence estimates were used to construct a four-tier composite burden index incorporating depression, CVD, and rates of lack of health insurance. Choropleth maps were developed to depict geographic patterns. Results: Overall, 21.1% of adults were found to have depression, 12.3% had CVD, and 5.8% had no health insurance. Depression was significantly associated with CVD (adjusted OR = 1.69; 95% CI: 1.65–1.72). Lack of health insurance significantly moderated the relationship between depression and CVD (interaction OR = 1.33; 95% CI: 1.18–1.51, p < 0.001). Geographic mapping analyses demonstrated marked heterogeneity. Tier 4 (highest burden) states included Kentucky, West Virginia, Louisiana, Oklahoma, Texas, New Jersey, Guam, and the U.S. Virgin Islands. Many Tier 3 and Tier 4 regions were clustered in the South and Appalachia. Conclusions: Depression is strongly associated with an increased prevalence of CVD, and this association is further amplified among individuals without health insurance coverage. Geographic disparities demonstrate critical hotspots where simultaneous mental health challenges, elevated risk of CVD, and limited insurance converge, highlighting the need for combined, area-specific public health strategies and approaches addressing both mental and cardiovascular health. Full article

Background: The goal of this study was to evaluate whether medical recommendation of Angocin^® Anti-Infekt N (hereafter referred to as Angocin^®) on the day of diagnosis of an acute upper respiratory tract infection (aURTI) or acute sinusitis (AS) is negatively associated with a recurrence of these diagnoses, incidence of antibiotic prescriptions, incidence of chronic sinusitis, nasal polyps, or sick leave duration. Methods: This retrospective cohort study utilized the IQVIA^TM Disease Analyzer database and included patients by general practitioners with at least one diagnosis of aURTI or AS from 2005 to 2024 and a prescription of Angocin^®, nasal medications (xylometazoline, oxymetazoline) and mucolytics (ambroxol or acetylcysteine), other phytopharmaceutical drugs, or antibiotics on the day of diagnosis. Patients who received Angocin^® were matched separately to each of the three comparison cohorts in a 1:5 ratio using a nearest-neighbor propensity score approach. The relationship between Angocin^® prescription and the risks of a recurrence, subsequent antibiotic use or progression to chronic disease was then estimated with Cox proportional hazard models. To examine whether Angocin^® exposure was associated with the length of sick leave, univariable conditional logistic regression was applied. Results: A total of 3501 Angocin^® patients and 17,505 patients in each further cohort were investigated. Angocin^® prescription was associated with a significantly lower incidence of a newly diagnosed aURTI/AS as compared to other phytopharmaceuticals (Hazard ratio (HR): 0.78; 95% confidence interval (CI): 0.68–0.86), nasal medications and mucolytics (HR: 0.79; 95% CI: 0.71–0.88), or antibiotics (HR: 0.85; 95% CI: 0.77–0.95). In addition, there was a significantly lower incidence of subsequent further prescriptions of antibiotics when compared to other phytopharmaceuticals (HR: 0.92; 95% CI: 0.82–0.99), nasal medications and mucolytics (HR: 0.87 (95%; CI: 0.80–0.95), or antibiotics (HR: 0.62; 95% CI: 0.57–0.67). Furthermore, Angocin^® was associated with the most advantageous pattern of work absence across all time periods examined. Conclusions: Considering the limitations of the study, the results cast a positive light on Angocin^® prescription in the management of aURTI/AS, particularly with regard to recurrence rates, subsequent antibiotic prescriptions, and sick leave duration. Full article

Background: This study examined age-related differences and interrelationships among psychological symptoms, personality traits, and emotional expression styles in a community sample of 151 participants aged 10–77 years, spanning four age groups: adolescents, young adults, middle-aged adults, and older adults. Methods: Psychological symptoms were assessed using the SCL-90, personality traits using the Big Five Inventory-2 (BFI-2), and emotional expression patterns were derived from facial expression recognition via a convolutional neural network (CNN) model. Kruskal–Wallis H tests were used to examine age-related differences. K-means cluster analysis was applied to identify emotional expression patterns, and logistic regression was used to construct a mental health risk screening model. Results: The young adult group (19–35 years) achieved the highest scores on the depression (M = 1.73) and anxiety (M = 1.61) dimensions, indicating a higher level of psychological distress during this life stage. Personality traits showed a significant developmental trajectory: neuroticism decreased with age (H(3) = 17.09, p < 0.001, η² = 0.11), declining from 2.69 in the young adult group to 2.17 in the older adult group; conscientiousness increased with age (H(3) = 37.39, p < 0.001, η² = 0.24), representing the most substantial age-related effect. K-means clustering identified three distinct emotional expression patterns: Cluster 1 was characterised by happiness, Cluster 2 by anger, disgust, and fear, and Cluster 3 by neutrality, sadness, and surprise. Cluster 2 exhibited the highest scores on neuroticism, anxiety, depression, and mood swings, and scored significantly higher than the other two clusters on interpersonal sensitivity, depression, anxiety, and hostility (p < 0.05). Mental health risk screening indicated that 26.5% of participants were classified as high-risk. Logistic regression analysis (AUC = 0.742) showed that neuroticism was the strongest predictor of elevated mental health risk (OR = 4.58), while extraversion (OR = 0.41) and conscientiousness (OR = 0.57) were significant protective factors. Conclusions: These findings provide exploratory evidence regarding age-related patterns of psychological symptoms and personality traits in a convenience sample and offer preliminary support for personality-based mental health risk screening. Notably, the SCL-90 was employed as a screening tool rather than for clinical diagnosis. Given the unequal age group sizes, particularly the small young adult subgroup, generalisability across the lifespan should not be assumed. Full article

Aim: To evaluate the diagnostic value of conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) features in differentiating benign from malignant Bethesda III/IV thyroid nodules, and to identify independent predictors of malignancy. Methods: We retrospectively analyzed 164 surgically confirmed Bethesda III/IV thyroid nodules. CUS and CEUS features were evaluated by two experienced radiologists blinded to pathological outcomes. Univariate analysis compared features between benign and malignant groups. Multivariate logistic regression was used to identify independent predictors. Diagnostic models were constructed based on CUS alone, CEUS alone, and their combination, with performance evaluated using receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each model. Results: The malignancy rate was 48.8% (80/164). Multivariate analysis identified microcalcifications (OR = 4.815, p < 0.001), aspect ratio >1 (OR = 2.499, p = 0.028), and irregular shape (OR = 2.465, p = 0.035) as independent risk factors, while older age (OR = 0.926 per year, p < 0.001) was protective. The CUS model achieved an AUC of 0.815 with high sensitivity (91.3%) and NPV (87.7%). The CEUS model performed poorly (AUC = 0.609). The combined model (AUC = 0.823) showed no significant improvement over CUS alone (p > 0.05). Physician subjective diagnosis based on CEUS TI-RADS yielded an AUC of 0.775. Conclusions: Conventional ultrasound features provide good diagnostic value for Bethesda III/IV nodules, with high sensitivity and NPV suitable for clinical screening. The addition of CEUS offered limited incremental benefit in this specific population, suggesting that the diagnostic value of CEUS for differentiating benign from malignant cytologically indeterminate thyroid nodules (ITNs) may be limited. Full article

Background/Objectives: Type 2 diabetes (T2D) develops gradually over many years through a prolonged preclinical phase, yet traditional static risk scores often fail to capture these dynamic metabolic trajectories. We propose a longitudinal deep learning framework to predict the 10-year risk of Type 2 diabetes onset defined by comprehensive ADA criteria by modeling the physiological acceleration of routine clinical biomarkers. Methods: Utilizing an 18-year longitudinal dataset from the community-based Korean Genome and Epidemiology Study (KoGES) cohort, we selected $N=4354$ participants with complete follow-up records, ensuring high data integrity without requiring synthetic data augmentation. We constructed a 3-dimensional tensor of 21 non-invasive clinical variables spanning a 6-year observation window. To resolve the inherent precision-recall trade-offs of individual models, we developed a stacking ensemble that integrates Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures via a logistic regression meta-learner. To evaluate the added value of longitudinal modeling, we compared this dynamic framework against a static XGBoost baseline that only saw the most recent data. Results: Evaluated on an independent test set ($n=874$), the ensemble significantly outperformed baseline models, achieving an overall accuracy of 0.90 (95% CI: 0.88–0.92) and an AUROC of 0.94 (95% CI: 0.93–0.95). By harmonizing LSTM’s sensitivity and GRU’s precision, the model yielded an exceptional Positive Predictive Value (PPV) of 0.97, a sensitivity of 0.80, and a specificity of 0.98. Conclusions: This framework provides a highly accurate, resource-efficient triage instrument for T2D screening, thereby reducing unnecessary clinical alerts and improving screening efficiency. Full article

Background: The aim of our study was to evaluate the association of angiopoietin 2 (ANGPT2) rs2442598 and vascular endothelial growth factor A (VEGFA) rs2010963 with diabetic nephropathy (DN) in Slovenian subjects with type 2 diabetes mellitus (T2DM). Angiopoietin–endothelial tyrosine kinase receptor (Ang-Tie2) and VEGF-A signaling regulate glomerular endothelial stability and permeability and may contribute to DN susceptibility. Methods: We conducted a case–control study including 897 unrelated Slovenian subjects with T2DM (344 DN cases; 553 long-standing T2DM controls without DN). ANGPT2 rs2442598 and VEGFA rs2010963 were genotyped using TaqMan assays. Genetic associations were analysed using co-dominant, additive, dominant, and recessive genetic models with logistic regression adjusted for waist circumference, systolic blood pressure, fasting glucose, and triglycerides. Results: ANGPT2 rs2442598 was significantly associated with DN, with increased risk in carriers of the C allele, including a significant additive per allele effect (OR 1.39, 95% CI 1.10–1.74) and a dominant model effect (OR 1.47, 95% CI 1.11–1.96). In contrast, VEGFA rs2010963 showed no evidence of association across genetic models. Conclusions: In Slovenian patients with T2DM, ANGPT2 rs2442598 is associated with DN, whereas VEGFA rs2010963 is not. This association suggests that ANGPT2 genetic variation may influence DN risk and supports further functional work to define the biological effects of rs2442598. Full article

Background/Objectives: Schools, as structured social environments, are important settings for shaping lifelong eating habits, and teachers play a mediating role in nutrition education. This study aimed to assess nutrition knowledge among public school teachers, examine their perceptions of the school food environment, and identify factors associated with knowledge scores. Methods: A stratified cross-sectional survey was conducted among 736 teachers from 12 public schools during the fall of 2025. A structured questionnaire based on the Knowledge–Attitudes–Practice model was used to evaluate nutrition knowledge, teaching practices, perceived school food environment, and teachers’ observations of student food-related behaviors. Group differences were examined using t-tests and ANOVA, and multivariable logistic regression was applied to identify factors associated with low nutrition knowledge. Results: The mean knowledge score was 6.26 ± 2.64 out of 12, with 23.6% of teachers classified as having low knowledge, 59.9% satisfactory, and 16.4% good. Primary school teachers scored significantly higher than subject teachers (7.27 vs. 5.64; p < 0.001). Regular conduct of nutrition classes was associated with lower odds of low knowledge (adjusted OR 0.10, 95% CI 0.05–0.23, p < 0.001). A sensitivity analysis using continuous knowledge scores confirmed this pattern, with the absence of nutrition teaching predicting a 1.40-point reduction in scores (95% CI −1.86 to −0.94, p < 0.001). Teachers rated school meal quality moderately high, and frequently observed student refusal of canteen food and purchase of sweets or fast food outside school. Conclusions: This study found that public school teachers in Karaganda, Kazakhstan showed satisfactory overall nutrition knowledge, with gaps in applied understanding and common dietary myths. Primary teachers and those actively teaching nutrition had higher knowledge scores, indicating an association between pedagogical engagement and content knowledge. To help optimize the school food environment, educational policies would benefit from the development of cross-curricular instructional materials fitted specifically for secondary school subject teachers. Full article

Background: Brucella canis is an emerging zoonotic pathogen responsible for canine reproductive disorders and public health concerns. This study assessed the seroprevalence of B. canis in dogs from Campania, Southern Italy (2022–2025). Methods: Serum samples (n = 400) were retrospectively screened using an indirect immunofluorescence assay (IFAT), performed according to the manufacturer’s instructions. Screening was conducted at a 1:40 cut-off, followed by serial dilutions to determine endpoint titres. Statistical analysis included chi-square tests for univariable screening, followed by nominal logistic regression models to evaluate the association between IFAT positivity and predictive factors (year, province, and sex of dogs). Additionally, a general linear model (GLM) was applied to the seropositive subset (n = 69) to analyse the magnitude of the antibody response, expressed as geometric mean titres (GMTs). Results: The overall seroprevalence was 17.3% (95% CI: 13.6–21.0%). Dog’s sex, year of sampling, and province were not significant independent predictors of infection (p > 0.05), but GLM analysis showed that sampling year (p = 0.0024) and province (p = 0.0490) significantly influenced antibody intensity. A significant temporal increase in antibody intensity was observed towards 2025 (p = 0.037), suggesting an intensification of infection pressure. Conclusions: Our results confirm that Brucella canis is an endemic pathogen in the shelter dog population of southern Italy. The high seroprevalence and significant increase in antibody magnitude (GMT) over the study period indicate rising infection pressure, highlighting the urgent need for mandatory screening and a coordinated One Health surveillance strategy to manage zoonotic risk effectively. Full article

Background: Postoperative complications following colorectal surgery remain a persistent clinical challenge. Traditional risk stratification has focused on patient characteristics, while conventional modeling approaches treat procedural factors such as operative duration and surgical approach as independent predictors, potentially obscuring interaction effects. Methods: This study developed a machine learning model stratifying 7908 colorectal surgery patients into four distinct procedural risk categories based on combined surgical approach and operative duration (laparoscopic-short, laparoscopic-long, open-short, open-long), rather than treating these factors as separate variables. A gradient boosting ensemble classifier with RUSBoost resampling was trained on predictor variables including patient demographics, comorbidities, and intraoperative factors. Results: Feature importance analysis revealed that the open-long category emerged as the single most important predictor, substantially exceeding all other variables. Weight loss, body mass index, patient age, and electrolyte abnormalities ranked as the next most important predictors. Stratified complication rates demonstrated a critical interaction: prolonged duration more than doubled complication risk in open procedures (short-duration: 9.99%, long-duration: 20.46%), whereas laparoscopic procedures showed only a modest increase from short-duration (10.45%) to long-duration (14.08%) cases. Logistic regression benchmark analysis confirmed the duration-approach interaction (OR = 1.53, 95% CI: 0.97–2.39), achieving comparable discrimination (c-statistic 0.678 vs. 0.665 for the ensemble model). Decision curve analysis demonstrated logistic regression provided superior clinical utility across most threshold probabilities. Conclusions: The dual analytical framework (i.e., statistical inference for quantifying associations and machine learning for predictive feature ranking) offers complementary insights for clinical application. These findings demonstrate that stratified feature engineering can elucidate complex risk phenotypes that may be obscured when procedural factors are analyzed independently. Full article

Objective: To evaluate the utility of synovial iron quantification using Magnetic resonance imaging (MRI) in assessing structural joint damage in the knee of patients with rheumatoid arthritis (RA). Methods: This cross-sectional study employed a two-stage design. In the initial comparative stage, 6 patients with RA and 5 patients with osteoarthritis (OA) were recruited to compare synovial R2* values, a metric derived from iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation (IDEAL-IQ) MRI sequences representing synovial iron content. Following this, the RA cohort was expanded to a total of 51 patients to investigate the association between R2* values and clinical parameters, including disease activity and bone erosion. Synovial fluid iron levels were measured with an Iron Assay Kit and synovial iron deposits were semi-quantified via Prussian blue staining. Associations between R2* and clinical and laboratory parameters, including inflammatory factors and joint damage indices, were analyzed using Spearman’s rank correlation. Univariate and multivariate ordered logistic regression models were employed to identify factors associated with bone erosion severity. An R2*-based nomogram was developed and validated using receiver operating characteristic (ROC) analysis and calibration curves. Results: Synovial R2* values were significantly higher in RA patients than those with osteoarthritis (53.66 S⁻¹ vs. 31.38 S⁻¹, p < 0.05), consistent with Prussian blue staining results. While synovial R2* values showed no significant correlation with systemic iron metabolic markers, inflammatory indicators, or the Disease Activity Score 28, they were positively correlated with bone erosion severity (ρ = 0.500, p < 0.001) and negatively associated with the joint space width (ρ = −0.307, p < 0.05). Multivariate analysis identified R2* as an independent indicator linked to bone erosion extent (OR = 2358.336, p < 0.001). The R2*-based nomogram demonstrated good discriminative performance. (AUC = 0.83). Conclusions: The R2* value derived from IDEAL-IQ MRI is a reliable tool for quantifying synovial iron and may represent a promising non-invasive imaging biomarker reflecting bone erosion in RA patients. Full article

Background/Objectives: Risk stratification in asymptomatic carotid stenosis has traditionally relied on the degree of luminal narrowing; however, plaque vulnerability may better predict cerebrovascular events. Ipsilateral silent brain lesions (SBLs) are considered surrogate markers of stroke risk. This study aimed to identify carotid plaque features on duplex ultrasound (DUS) and computed tomography angiography (CTA), as well as circulating biomarkers, associated with ipsilateral SBL in patients with clinically asymptomatic ≥70% internal carotid artery stenosis. Methods: This prospective observational study with cross-sectional imaging analysis included 316 clinically asymptomatic patients with ≥70% carotid stenosis treated between January 2022 and October 2024. All patients underwent cranial non-contrast CT for SBL detection, DUS plaque characterization (according to the Gray–Weale classification and plaque surface morphology), and CTA analysis, including plaque surface, composition, length, and attenuation values categorized according to Schroeder’s criteria (<50 HU lipid-rich; 51–120 HU fibrous; >120 HU calcified). Demographic, clinical, and laboratory parameters, including inflammatory biomarkers, were recorded. Multivariate logistic regression was performed to identify independent predictors of SBL. Results: SBL were detected in 72 patients (22.8%). On DUS, SBL were significantly associated with Gray–Weale class II plaques, heterogeneous composition, and irregular or ulcerated surfaces (all p < 0.001). On CTA, lipid-rich plaques (<50 HU), ulcerated surfaces, heterogeneous morphology, and lower median plaque density were significantly more frequent in the SBL group (all p < 0.001). In multivariate analysis, independent predictors of SBL were male sex (OR 2.2; 95% CI 1.2–5.7; p = 0.029), Gray–Weale class II plaques (p = 0.002), lipid-rich plaque morphology (OR 21.39; 95% CI 6.86–66.76; p < 0.001), and ulcerated plaque surface on CTA (OR 20.62; 95% CI 7.37–57.68; p < 0.001). Conclusions: Specific ultrasound and CT plaque characteristics were associated with ipsilateral silent brain lesions in patients with asymptomatic ≥70% carotid stenosis. A multiparametric imaging approach may improve risk stratification beyond stenosis severity alone. Full article