Search Results (13,310)

Background: Behçet’s Disease (BD) was traditionally classified according to the International Study Group (ISG), where oral ulcers were mandatory. The International Team for the Revision of the International Criteria for BD (ICBD) introduced a scoring system instead. Our aim was to assess (a) sensitivity, (b) concordance between ISG and ICDB criteria in global and severe BD cases (ocular, vascular, and neurological), and (c) evaluate their clinical implications. Methods: Retrospective cohort study including 142 BD patients diagnosed in a well-defined population in Northern Spain, between January 1980 and November 2023. Both ISG and ICBD criteria were compared, sensitivity and concordance were assessed using Prevalence-Adjusted and Bias-Adjusted Kappa (PABAK) and the unadjusted Kappa. Results: A total of 142 BD patients diagnosed by expert rheumatologists (73 men; mean age of 36.4) were studied. Among them, 84 met ISG criteria, while 116 fulfilled ICBD criteria. Sensitivity of ISG and ICBD criteria in the overall cohort was (59.1% and 81.6%), respectively. Among patients with severe manifestations (ocular, vascular, or neurological), sensitivity increased to 71.2% for ISG and 92.5% for ICBD. Overall concordance was moderate (Kappa = 0.490), with 70.4% of patients classified identically. When adjusting prevalence and bias, concordance improved slightly (PABAK = 0.549). Of the 32 patients classified as BD exclusively by ICBD, 7 were receiving anti-TNF therapy, and 2 were receiving apremilast. Conclusions: The ICBD criteria demonstrated higher sensitivity than the traditional ISG criteria in classifying BD, particularly in severe cases. Classifying these additional patients under ICBD facilitated the initiation of on-label biologic treatments, potentially enhancing BD management, especially for severe cases. Full article

Using Photoplethysmogram (PPG) signals for identity recognition has been proven effective in biometric authentication. However, in real-world applications, PPG signals are prone to interference from noise, physical activity, diseases, and other factors, making it challenging to ensure accurate user recognition and verification in complex environments. To address these issues, this paper proposes an improved MSF-SE ResNet50 (Multi-Scale Feature Squeeze-and-Excitation ResNet50) model based on 2D PPG signals. Unlike most existing methods that directly process one-dimensional PPG signals, this paper adopts a novel approach based on two-dimensional PPG signal processing. By applying Continuous Wavelet Transform (CWT), the preprocessed one-dimensional PPG signal is transformed into a two-dimensional time-frequency map, which not only preserves the time-frequency characteristics of the signal but also provides richer spatial information. During the feature extraction process, the SENet module is first introduced to enhance the ability to extract distinctive features. Next, a novel Lightweight Multi-Scale Feature Fusion (LMSFF) module is proposed, which addresses the limitation of single-scale feature extraction in existing methods by employing parallel multi-scale convolutional operations. Finally, cross-stage feature fusion is implemented, overcoming the limitations of traditional feature fusion methods. These techniques work synergistically to improve the model’s performance. On the BIDMC dataset, the MSF-SE ResNet50 model achieved accuracy, precision, recall, and F1 scores of 98.41%, 98.19%, 98.27%, and 98.23%, respectively. Compared to existing state-of-the-art methods, the proposed model demonstrates significant improvements across all evaluation metrics, highlighting its significance in terms of network architecture and performance. Full article

Objective: Visceral leishmaniasis (VL), a Neglected Tropical Disease caused by Leishmania donovani, remains insufficiently addressed by current therapies due to high toxicity, poor efficacy, and immunosuppressive complications. This study aimed to identify and characterize repurposed drugs that simultaneously target parasite-encoded and host-associated mechanisms essential for VL pathogenesis. Methods: Two complementary in silico drug repurposing strategies were employed. The first method utilized electron–ion interaction potential (EIIP) screening followed by molecular docking and molecular dynamics (MD) simulations targeting two L. donovani proteins: Rab5a and pteridine reductase 1 (PTR1). The second approach employed network-based drug repurposing using the Drugst.One platform, prioritizing candidates via STAT3-associated gene networks. Predicted drug–target complexes were validated by 100 ns MD simulations, and pharmacokinetic parameters were assessed via ADMET profiling using QikProp v7.0 and SwissADME web server. Results: Entecavir and valganciclovir showed strong binding to Rab5a and PTR1, respectively, with Glide Scores of −9.36 and −9.10 kcal/mol, and corresponding MM-GBSA ΔG_bind values of −14.00 and −13.25 kcal/mol, confirming their stable interactions and repurposing potential. Network-based analysis identified nifuroxazide as the top candidate targeting the host JAK2/TYK2–STAT3 axis, with high stability confirmed in MD simulations. Nifuroxazide also displayed the most favorable ADMET profile, including oral bioavailability, membrane permeability, and absence of PAINS alerts. Conclusions: This study highlights the potential of guanine analogs such as entecavir and valganciclovir, and the nitrofuran derivative nifuroxazide, as promising multi-target drug repurposing candidates for VL. Their mechanisms support a dual strategy targeting both parasite biology and host immunoregulation, warranting further preclinical investigation. Full article

Background: In high-risk and frail patients with multivessel coronary artery disease (MV CAD), guidelines indicated complete revascularization with or without the use of cardiopulmonary bypass (CPB) bears a high morbidity and mortality risk. In cases where catheter interventions were deemed unsuitable and conventional coronary artery bypass grafting (CABG) posed an unacceptable perioperative risk, patients were scheduled for minimally invasive direct coronary artery bypass (MIDCAB) grafting or minimally invasive multivessel coronary artery bypass grafting (MICS-CABG). We called this approach “palliative revascularization.” This study assesses the safety and impact of palliative revascularization on clinical outcomes and overall survival. Methods: A consecutive series of 57 patients undergoing MIDCAB or MICS-CABG as a palliative surgery between 2008 and 2018 was included. The decision for palliative surgery was met in heart team after carefully assessing each case. The patients underwent single or double-vessel revascularization using the left internal thoracic artery and rarely radial artery/saphenous vein segments, both endoscopically harvested. Inpatient data could be completed for all 57 patients. The mean follow-up interval was 4.2 ± 3.7 years, with a follow-up rate of 91.2%. Results: Mean patient age was 79.7 ± 7.4 years. Overall, 46 patients (80.7%) were male, 26 (45.6%) had a history of atrial fibrillation and 25 (43.9%) of chronic kidney disease. In total, 13 patients exhibited a moderate EuroSCORE II, while 27 were classified as high risk, with a EuroSCORE II exceeding 5%. Additionally, 40 patients (70.2%) presented with three-vessel disease, 17 (29.8%) suffered an acute myocardial infarction within three weeks prior to surgery and 50.9% presented an impaired ejection fraction. There were 48 MIDCAB and nine MICS CABG with no conversions either to sternotomy or to CPB. Eight cases were planned as hybrid procedures and only 15 patients (26.3%) were completely revascularized. During the first 30 days, four patients (7%) died. A myocardial infarction occurred in only one case, no patient necessitated immediate reoperation. The one-, three- and five-year survival rates were 83%, 67% and 61%, respectively. Conclusions: MIDCAB and MICS CABG can be successfully conducted as less invasive palliative surgery in high-risk multimorbid patients with MV CAD. The early and mid-term results were better than predicted. A higher rate of hybrid procedures could improve long-term outcome in selected cases. Full article

Background/Objectives: Fat and inflammation confound current magnetic resonance imaging (MRI) methods for assessing fibrosis in liver disease. Sodium or amide proton transfer-weighted MRI methods may be more specific for assessing liver fibrosis. The purpose of this study was to determine the feasibility of sodium and amide proton transfer-weighted MRI in individuals with liver disease and to determine if either method correlated with clinical markers of fibrosis. Methods: T₁ and T₂ relaxation maps, proton density fat fraction maps, liver shear stiffness maps, amide proton transfer-weighted (APTw) images, and sodium images were acquired at 3T. Image data were extracted from regions of interest placed in the liver. ANOVA tests were run with disease status, age, and body mass index as independent factors; significance was set to p < 0.05. Post-hoc t-tests were run when the ANOVA showed significance. Results: A total of 36 participants were enrolled, 34 of whom were included in the final APTw analysis and 24 in the sodium analysis. Estimated liver tissue sodium concentration differentiated participants with liver disease from those without, whereas amide proton transfer-weighted MRI did not. Estimated liver tissue sodium concentration negatively correlated with the Fibrosis-4 score, but amide proton transfer-weighted MRI did not correlate with any clinical marker of disease. Conclusions: Amide proton-weighted imaging was not different between groups. Estimated liver tissue sodium concentrations did differ between groups but did not provide additional information over conventional methods. Full article

Retinal vessel segmentation in fundus images is critical for diagnosing microvascular and ophthalmologic diseases. However, the task remains challenging due to significant vessel width variation and low vessel-to-background contrast. To address these limitations, we propose WDM-UNet, a novel spatial-wavelet dual-domain fusion architecture that integrates spatial and wavelet-domain representations to simultaneously enhance the local detail and global context. The encoder combines a Deformable Convolution Encoder (DCE), which adaptively models complex vascular structures through dynamic receptive fields, and a Wavelet Convolution Encoder (WCE), which captures the semantic and structural contexts through low-frequency components and hierarchical wavelet convolution. These features are further refined by a Gated Fusion Transformer (GFT), which employs gated attention to enhance multi-scale feature integration. In the decoder, depthwise separable convolutions are used to reduce the computational overhead without compromising the representational capacity. To preserve fine structural details and facilitate contextual information flow across layers, the model incorporates skip connections with a hierarchical fusion strategy, enabling the effective integration of shallow and deep features. We evaluated WDM-UNet in three public datasets: DRIVE, STARE, and CHASE_DB1. The quantitative evaluations demonstrate that WDM-UNet consistently outperforms state-of-the-art methods, achieving 96.92% accuracy, 83.61% sensitivity, and an 82.87% F1-score in the DRIVE dataset, with superior performance across all the benchmark datasets in both segmentation accuracy and robustness, particularly in complex vascular scenarios. Full article

Objectives: Diabetes Mellitus involves demanding challenges that interfere with family functioning and routines. In turn, family and social context impacts individual glycemic control. This study aims to identify this recursive interplay, the mutual influences of family systems and diabetes management. Design: Data was collected through a cross-sectional design comparing patients, aged 22–55, with and without metabolic control. Methods: Participants filled out a set of self-report measures of sociodemographic, clinical and family systems assessment. Patients (91) were also invited to describe their perception about disease management interference regarding family functioning. We first examined the extent to which family variables grouped dataset to determine if there were similarities and dissimilarities that fit with our initial diabetic groups’ classification. Results: Cluster analysis results identify a two-cluster solution validating initial classification of two groups of patients: 49 with metabolic control (MC) and 42 without metabolic control (NoMC). Independent sample tests suggested statistically significant differences between groups in family subscales- family difficulties and family communication (p < 0.05). Binary logistic regression shed light on predictors of explained variance to no metabolic control, in four models: Sociodemographic, Clinical data, SCORE-15/Congruence Scale and Eating Behavior. Furthermore, groups differ on family support, level and sources of family conflict caused by diabetes management issues. Considering only patients who co-habit with a partner for more than one year (N = 44), NoMC patients score lower on marital functioning in all categories (p < 0.05). Discussion: Family-Chronic illness interaction plays a significant role in a patient’s adherence to treatment. This study highlights the Standards of Medical Care for Diabetes, considering caregivers and family members on diabetes care. Full article

Background/Objectives: Multifactorial prevention of falls in persons with dementia has minimal or non-significant effects. Personalised prevention is recommended. We have previously shown that gait speed, basic activities of daily living (ADL), and depression (high Cornell scores) were independent predictors of falls in persons with mild and moderate cognitive impairment. This study explored person-specific risks of falls related to physical, mental, and cognitive functions and types of dementia: Alzheimer’s disease (AD), vascular dementia (VD), mixed Alzheimer’s disease/vascular dementia (MixADVD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB). Methods: The study used data from “The Norwegian Registry of Persons Assessed for Cognitive Symptoms” (NorCog). Differences between the dementia groups and predictors of falls, gait speed, ADL, and Cornell scores were analysed. Results: Among study participants, 537/1321 (40.7%) reported a fall in the past year, with significant variations between dementia diagnoses. Fall incidence increased with age, comorbidity/polypharmacy, depression, and MAYO fluctuation score and with reduced physical activity, gait speed, and ADL. Persons with VD and MixADVD had high fall incidences and impaired gait speed and ADL. Training of physical fitness, endurance, muscular strength, coordination, and balance and optimising treatment of comorbidities and medication enhance gait speed. Improving ADL necessitates, in addition, relief of cognitive impairment and fluctuations. Relief of depression and fluctuations by psychological and pharmacological interventions is necessary to reduce the high fall risk in persons with DLB. Conclusions: The fall incidence and fall predictors varied significantly. Personalised interventions presuppose knowledge of each individual’s fall risk factors. Full article

Gastric adenocarcinoma is a malignant tumor that develops from the glandular cells of the inner wall of the stomach. The prevalence of this type of disease varies from 90 to 95% of all types of gastric cancer. The aim of our study was to investigate the differences in the content of cytokines and oxidative stress markers in patients with gastric adenocarcinoma associated with H. pylori infection depending on the stage. The study included 281 patients with gastric cancer. At stage I of the disease—75 people, stage II—70 people, stage III—69 people, and stage IV of the disease—67 people. The levels of TNF-α, IL-2, IL-8, IFNγ, TNF-β, IL-17A, IL-6, IL-10, and IL-4 in the blood serum of patients and healthy individuals were determined by enzyme immunoassay and plasma oxidative stress scores (MDA, SOD, CAT, GST, GPO, CP). The present study revealed that H. pylori-infected gastric adenocarcinoma at different stages is associated with different plasma levels of cytokines, lipid peroxidation products, and antioxidant defense factors. Further studies are needed to evaluate the effectiveness of therapeutic strategies combining cytokine regulation and oxidative stress to improve clinical outcomes in gastric cancer. Full article

Background/Objectives: The TOPAZ-1 phase III trial reported a survival benefit of using durvalumab, an anti-programmed death ligand 1 (anti-PD-L1) antibody, in combination with gemcitabine and cisplatin (GCD) treatment in patients with advanced biliary tract cancer. This retrospective study investigated the efficacy and safety of GCD treatment for advanced biliary tract cancer in real-world conditions. Methods: The study subjects were 52 patients with biliary tract cancer who received GCD therapy between January 2023 and May 2024. The observation parameters included the modified Glasgow Prognostic Score (mGPS), neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), tumor markers (CEA, CA19-9), overall response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and adverse events. Results: The cohort included 36 men and 16 women, with a median age of 73.0 years. There were 36 cases of cholangiocarcinoma (distal: 10, perihilar: 19, intrahepatic: 7), 13 cases of gallbladder cancer, and 3 cases of ampullary carcinoma. The stages were locally advanced in 30 cases and metastatic in 22 cases. Biliary drainage was performed in 30 cases. There were 38 cases receiving first-line therapy and 14 cases receiving second-line or later treatments. The median values at the start of GCD therapy were ALB 3.7 g/dL, CRP 0.39 mg/dL, NLR 2.4, PLR 162.5, CEA 4.8 ng/mL, and CA19-9 255.9 U/mL. The mGPS distribution was 0:23 cases, 1:18 cases, and 2:11 cases. The treatment outcomes were ORR 25.0% (CR 2 cases, PR 11 cases), DCR 78.8% (SD 28 cases, PD 10 cases, NE 1 case), median PFS 8.6 months, and median OS 13.9 months. The PLR was suggested to be useful for predicting PFS. A decrease in CEA at six weeks after the start of treatment was a significant predictor of PFS and OS. Gallbladder cancer had a significantly poorer prognosis compared to other cancers. The immune-related adverse events included hypothyroidism in two cases, cholangitis in one case, and colitis in one case. Conclusions: The ORR, DCR, and PFS were comparable to those in the TOPAZ-1 trial. Although limited by its retrospective design and small sample size, this study suggests that GCD therapy is an effective treatment regimen for unresectable biliary tract cancer in real-world clinical practice. Full article

Background: Meniere’s disease is characterized by a triad of vertigo episodes, fluctuating hearing loss, and tinnitus. The disease is followed by a loss of quality of life in patients, with the severity depending on the individual and the stage of the disease. Since there are no quantitatively validated tests that connect all elements of the disease, the only source of subjective data that can be analyzed is the disease diary and questionnaires, among which the MDPOSI (Meniere’s Disease Patient-Oriented Symptom-Severity Index) stands out as a designated quality-of-life assessment tool. This study aims to evaluate the differences in the questionnaire depending on the clinical characteristics of the disease. Methods: The study recruited 60 patients, with clinical variables including age, gender, disease laterality, caloric testing results, and PTA results, the presence of spontaneous nystagmus, pathological values of calorimetric testing, or rotatory chair testing abnormalities. Results: The appearance of spontaneous nystagmus showed a significant association with worse hearing threshold values at 500 Hz (p = 0.036, OR 4.416) and higher. Worse SRT scores correlated with Q1 (p = 0.011), Q2 (p = 0.028), Q4 (p = 0.045), Q5 (p = 0.013), and the total MDPOSI score (p = 0.008, 0.339). Multivariate analysis showed that a higher total value of the MDPOSI questionnaire was statistically significantly associated with older age (p = 0.042) and spontaneous nystagmus (p = 0.037). Conclusions: There is a correlation between the clinical characteristics of Meniere’s disease and the MDPOSI questionnaire, making it useful for assessing quality of life and disease progression. Full article

Objective: To analyze the composition of the oral microbiome in periodontal pocket lesions and on the tongue dorsum of patients with Helicobacter pylori-associated gastric disease. Materials and Methods: Patients diagnosed with gastric disease and H. pylori (HP+) were evaluated in comparison to a control group of H. pylori-negative patients without gastric disease (HP−). Periodontal and oral health clinical parameters (PPD, BoP, PSE, plaque score and modified DMFT) were assessed for each patient. Microbiological samples were collected from the deepest periodontal pockets and tongue dorsum, followed by DNA extraction, 16S rRNA PCR amplification, and Next-Generation-Sequencing (NGS) analyses. Results: Sixty-seven patients (27F; 40M, aged 35–85 years) were enrolled. Of these, 52 were HP+ and 15 were HP−. HP+ patients exhibited a significantly higher presence of decayed teeth (p < 0.05) and slightly fewer missing teeth (p > 0.05). The plaque score was significantly higher in HP+ patients (p < 0.05), while PPD and BoP showed no significant differences (p > 0.05). NGS analysis revealed no presence of H. pylori in any samples of both periodontal and tongue sites. HP+ patients showed a distinct microbial composition, including higher prevalence of Capnocytophaga, Fusobacterium, and Peptostreptococcus genera in both locations (pockets and tongue dorsum). Conclusions: The study demonstrated that HP+ patients exhibit distinct oral microbial profiles compared to HP− patients, especially in areas with deeper periodontal pockets. H. pylori was not detected in the oral microbiomes of either group. Full article

Systemic sclerosis (SSc) is an autoimmune connective tissue disorder characterized by vascular abnormalities, immune dysfunction, and progressive fibrosis. One of the most common manifestations of SSc is interstitial lung disease (ILD), known by a progressive course leading to significant morbidity and mortality. Aim: to investigate autoantibodies, cytokines, and genetic markers in SSc-ILD through a systematic review and analysis of a Kazakh cohort of SSc-ILD patients. Methods: A PubMed search over the past 10 years was performed with “SSc-ILD”, “autoantibodies”, “cytokines”, and “genes”. Thirty patients with SSc were assessed for lung involvement, EScSG score, and modified Rodnan skin score. IL-6 was measured by ELISA, antinuclear factor on HEp-2 cells by indirect immunofluorescence, and specific autoantibodies by immunoblotting. Genetic analysis was performed using a 120-gene AmpliSeq panel on the Ion Proton platform. Results: The literature review identified 361 articles, 26 addressed autoantibodies, 20 genetic variants, and 12 cytokine profiles. Elevated levels of IL-6, TGF-β, IL-33, and TNF-α were linked to SSc. Based on the results of the systemic review, we created a preliminary immunogenic panel for SSc-ILD with following analysis in Kazakh patients with SSc (n = 30). Fourteen of them (46.7%) demonstrated signs of ILD and/or lung hypertension, with frequent detection of antibodies such as Scl-70, U1-snRNP, SS-A, and genetic variants in SAMD9L, REL, IRAK1, LY96, IL6R, ITGA2B, AIRE, TREX1, and CD40 genes. Conclusions: Current research confirmed the presence of the broad range of autoantibodies and variations in IRAK1, TNFAIP3, SAMD9L, REL, IRAK1, LY96, IL6R, ITGA2B, AIRE, TREX1, CD40 genes in of Kazakhstani cohort of SSc-ILD patients. Full article

If we do not urgently educate current and future medical professionals to critically evaluate and distinguish credible AI-assisted diagnostic tools from those whose performance is artificially inflated by data leakage or improper validation, we risk undermining clinician trust in all AI diagnostics and jeopardizing future advances in patient care. For instance, machine learning models have shown high accuracy in diagnosing Parkinson’s Disease when trained on clinical features that are themselves diagnostic, such as tremor and rigidity. This study systematically investigates the impact of data leakage and feature selection on the true clinical utility of machine learning models for early Parkinson’s Disease detection. We constructed two experimental pipelines: one excluding all overt motor symptoms to simulate a subclinical scenario and a control including these features. Nine machine learning algorithms were evaluated using a robust three-way data split and comprehensive metric analysis. Results reveal that, without overt features, all models exhibited superficially acceptable F1 scores but failed catastrophically in specificity, misclassifying most healthy controls as Parkinson’s Disease. The inclusion of overt features dramatically improved performance, confirming that high accuracy was due to data leakage rather than genuine predictive power. These findings underscore the necessity of rigorous experimental design, transparent reporting, and critical evaluation of machine learning models in clinically realistic settings. Our work highlights the risks of overestimating model utility due to data leakage and provides guidance for developing robust, clinically meaningful machine learning tools for early disease detection. Full article

Non-invasive ultrasound diagnosis, combined with deep learning, is frequently used for detecting thyroid diseases. However, real-time detection on portable devices faces limitations due to constrained computational resources, and existing models often lack sufficient capability for small object detection of thyroid nodules. To address this, this paper proposes an improved lightweight small object detection network framework called LISA-YOLO, which enhances the lightweight multi-scale collaborative fusion algorithm. The proposed framework exploits the inherent symmetrical characteristics of ultrasound images and the symmetrical architecture of the detection network to better capture and represent features of thyroid nodules. Specifically, an improved depthwise separable convolution algorithm replaces traditional convolution to construct a lightweight network (DG-FNet). Through symmetrical cross-scale fusion operations via FPN, detection accuracy is maintained while reducing computational overhead. Additionally, an improved bidirectional feature network (IMS F-NET) fully integrates the semantic and detailed information of high- and low-level features symmetrically, enhancing the representation capability for multi-scale features and improving the accuracy of small object detection. Finally, a collaborative attention mechanism (SAF-NET) uses a dual-channel and spatial attention mechanism to adaptively calibrate channel and spatial weights in a symmetric manner, effectively suppressing background noise and enabling the model to focus on small target areas in thyroid ultrasound images. Extensive experiments on two image datasets demonstrate that the proposed method achieves improvements of 2.3% in F1 score, 4.5% in mAP, and 9.0% in FPS, while maintaining only 2.6 M parameters and reducing GFLOPs from 6.1 to 5.8. The proposed framework provides significant advancements in lightweight real-time detection and demonstrates the important role of symmetry in enhancing the performance of ultrasound-based thyroid diagnosis. Full article