Search Results (601)

Objectives: To evaluate the association between antidepressant use and the risk of venous thromboembolism (VTE), including deep vein thrombosis and pulmonary embolism (PE), through a systematic review and meta-analysis of observational studies. Methods: A comprehensive literature search was conducted in Medline, Embase^®, and Web of Science^® up to December 2024. Eighteen studies (cohort, case-control, and nested case-control designs) meeting inclusion criteria were analyzed. Study quality was assessed using the Newcastle–Ottawa Scale. Pooled relative risks (RR) with 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup analyses were performed based on recency of antidepressant use, VTE onset type (first vs. recurrent), and VTE subtype (PE). Results: Antidepressant use was associated with a significantly increased risk of VTE (RR = 1.22; 95% CI: 1.12–1.32; p < 0.001). Subgroup analyses revealed a stronger association for recent use (within 90 days), first-onset VTE, recurrent VTE, and PE. Heterogeneity was high (I² = 87.92%), but sensitivity analysis confirmed result robustness. No publication bias was detected. Conclusions: This meta-analysis indicates a modest but statistically significant increase in the risk of VTE associated with antidepressant use, particularly among recent users, individuals experiencing either first-time or recurrent VTE, and those with PE-type events. These findings highlight the importance of individualized VTE risk assessment when initiating antidepressant therapy. Full article

Background and Clinical Significance: Hemophagocytic lymphohistiocytosis (HLH) and autoimmune hemolytic anemia (AIHA) are both life-threatening hematologic syndromes that rarely present together outside of malignancy. Advanced acquired immunodeficiency syndrome (AIDS) creates a milieu of profound immune dysregulation and hyperinflammation, predisposing patients to atypical overlaps of these disorders. Case Presentation: A 30-year-old woman with poorly controlled AIDS presented with three weeks of jaundice, fever, and fatigue. Initial labs revealed pancytopenia, hyperbilirubinemia, and elevated ferritin level. Direct anti-globulin testing confirmed warm AIHA (IgG⁺/C3d⁺) with transient cold agglutinins. Despite intravenous immunoglobulin (IVIG), rituximab, and transfusions, she developed hepatosplenomegaly, extreme hyperferritinemia, and sIL-2R > 10,000 pg/mL, meeting HLH-2004 criteria. Bone marrow biopsy excluded malignancy; further work-up revealed Epstein–Barr virus (EBV) viremia and cytomegalovirus (CMV) reactivation. Dexamethasone plus reduced-dose etoposide transiently reduced soluble interleukin-2 receptor (sIL-2R) but precipitated profound pancytopenia, Acute respiratory distress syndrome (ARDS) from CMV/parainfluenza pneumonia, bilateral deep vein thrombosis (DVT), and an ST-elevation myocardial infarction (STEMI). She ultimately died of hemorrhagic shock after anticoagulation despite maximal supportive measures. Conclusions: This case underscores the diagnostic challenges of HLH-AIHA overlap in AIDS, where cytopenias and hyperferritinemia mask the underlying cytokine storm. Pathogenesis likely involved IL-6/IFN-γ overproduction, impaired cytotoxic T-cell function, and molecular mimicry. While etoposide remains a cornerstone of HLH therapy, its myelotoxicity proved catastrophic in this immunocompromised host, highlighting the urgent need for cytokine-targeted agents to mitigate treatment-related mortality. Full article

User authentication is crucial for safeguarding access to digital systems and services. Biometric authentication serves as a strong and user-friendly alternative to conventional security methods such as passwords and PINs, which are often susceptible to breaches. This study proposes a deep learning-based multimodal biometric system that combines fingerprint (FP) and finger vein (FV) modalities to improve accuracy and security. The system explores three fusion strategies: feature-level fusion (combining feature vectors from each modality), score-level fusion (integrating prediction scores from each modality), and a hybrid approach that leverages both feature and score information. The implementation involved five pretrained convolutional neural network (CNN) models: two unimodal (FP-only and FV-only) and three multimodal models corresponding to each fusion strategy. The models were assessed using the NUPT-FPV dataset, which consists of 33,600 images collected from 140 subjects with a dual-mode acquisition device in varied environmental conditions. The results indicate that the hybrid-level fusion with a dominant score weight (0.7 score, 0.3 feature) achieved the highest accuracy (99.79%) and the lowest equal error rate (EER = 0.0018), demonstrating superior robustness. Overall, the results demonstrate that integrating deep learning with multimodal fusion is highly effective for advancing scalable and accurate biometric authentication solutions suitable for real-world deployments. Full article

Background: Retinal diseases are becoming an important public health issue, with early diagnosis and timely intervention playing a key role in preventing vision loss. Optical coherence tomography (OCT) remains the leading non-invasive imaging technique for identifying retinal conditions. However, distinguishing between diabetic macular edema (DME) and macular edema resulting from retinal vein occlusion (RVO) can be particularly challenging, especially for clinicians without specialized training in retinal disorders, as both conditions manifest through increased retinal thickness. Due to the limited research exploring the application of deep learning methods, particularly for RVO detection using OCT scans, this study proposes a novel diagnostic approach based on stacked convolutional neural networks. This architecture aims to enhance classification accuracy by integrating multiple neural network layers, enabling more robust feature extraction and improved differentiation between retinal pathologies. Methods: The VGG-16, VGG-19, and ResNet50 models were fine-tuned using the Kermany dataset to classify the OCT images and afterwards were trained using a private OCT dataset. Four stacked models were then developed using these models: a model using the VGG-16 and VGG-19 networks, a model using the VGG-16 and ResNet50 networks, a model using the VGG-19 and ResNet50 models, and finally a model using all three networks. The performance metrics of the model includes accuracy, precision, recall, $F_2$-score, and area under of the receiver operating characteristic curve (AUROC). Results: The stacked neural network using all three models achieved the best results, having an accuracy of 90.7%, precision of 99.2%, a recall of 90.7%, and an $F_2$-score of 92.3%. Conclusions: This study presents a novel method for distinguishing retinal disease by using stacked neural networks. This research aims to provide a reliable tool for ophthalmologists to improve diagnosis accuracy and speed. Full article

The palm-vein recognition system has garnered attention as a biometric technology due to its resilience to external environmental factors, protection of personal privacy, and low risk of external exposure. However, with recent advancements in deep learning-based generative models for image synthesis, the quality and sophistication of fake images have improved, leading to an increased security threat from counterfeit images. In particular, palm-vein images acquired through near-infrared illumination exhibit low resolution and blurred characteristics, making it even more challenging to detect fake images. Furthermore, spoof detection specifically targeting palm-vein images has not been studied in detail. To address these challenges, this study proposes the Fourier-gated feature-fusion network (FGFNet) as a novel spoof detector for palm-vein recognition systems. The proposed network integrates masked fast Fourier transform, a map-based gated feature fusion block, and a fast Fourier convolution (FFC) attention block with global contrastive loss to effectively detect distortion patterns caused by generative models. These components enable the efficient extraction of critical information required to determine the authenticity of palm-vein images. In addition, fractal dimension estimation (FDE) was employed for two purposes in this study. In the spoof attack procedure, FDE was used to evaluate how closely the generated fake images approximate the structural complexity of real palm-vein images, confirming that the generative model produced highly realistic spoof samples. In the spoof detection procedure, the FDE results further demonstrated that the proposed FGFNet effectively distinguishes between real and fake images, validating its capability to capture subtle structural differences induced by generative manipulation. To evaluate the spoof detection performance of FGFNet, experiments were conducted using real palm-vein images from two publicly available palm-vein datasets—VERA Spoofing PalmVein (VERA dataset) and PLUSVein-contactless (PLUS dataset)—as well as fake palm-vein images generated based on these datasets using a cycle-consistent generative adversarial network. The results showed that, based on the average classification error rate, FGFNet achieved 0.3% and 0.3% on the VERA and PLUS datasets, respectively, demonstrating superior performance compared to existing state-of-the-art spoof detection methods. Full article

Background: The optimal anticoagulation strategy for obese patients with superficial vein thrombosis (SVT) remains unclear. This study evaluates the impact of obesity on anticoagulation patterns and clinical outcomes in patients with lower limb SVT. Methods: We conducted a prospective observational study including consecutive patients with SVT in a tertiary hospital from 2014 to 2024. Patients with SVT ≥ 5 cm in length and ≥3 cm from the saphenofemoral junction were included. Obese (BMI ≥ 30) and non-obese (BMI < 30) patients were compared. Patients were followed for one year. Outcomes were assessed at 90 and 365 days. The primary outcomes were venous thromboembolism (VTE) recurrence (SVT, deep vein thrombosis [DVT], or pulmonary embolism [PE]). The secondary outcomes were major bleeding and all-cause mortality. Results: Of 136 patients, 58 (42.6%) were obese. Both groups had similar baseline characteristics, except for younger age and higher smoking prevalence in obese patients. Most patients received anticoagulation (91.9%), primarily a prophylactic dose of low molecular weight heparin or a prophylactic dose of fondaparinux. No significant differences were found in VTE recurrence at 90 or 365 days (p = 0.505), and no major bleeding events occurred. Female sex was associated with a higher risk of VTE recurrence (OR 4.33, 95% CI 1.17–15.98, p = 0.028), but obesity did not influence outcomes. Conclusions: Obesity was not associated with increased VTE recurrence in patients with lower limb SVT. No major bleeding events were observed. These findings suggest that standard anticoagulation regimens may be appropriate for obese patients with SVT, but further studies are needed to confirm these results. Full article

Background/Objectives: Postoperative deep vein thrombosis (DVT) is a common and serious complication after tibial fracture surgery. This study aimed to develop and evaluate machine learning (ML) models to predict the occurrence of DVT following tibia fracture surgery. Methods: A retrospective analysis was conducted on patients who had undergone surgery for isolated tibial fractures. A total of 42 predictive models were developed using combinations of six ML algorithms—logistic regression, support vector machine, random forest, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), and neural networks—and seven feature selection methods, including SHapley Additive exPlanations (SHAP), Least Absolute Shrinkage and Selection Operator (LASSO), Boruta, recursive feature elimination, univariate filtering, and full-variable inclusion. Model performance was assessed based on discrimination, quantified by the area under the receiver operating characteristic curve (AUC-ROC), and calibration, measured using Brier scores, with internal validation performed via bootstrapping. Results: Of 471 patients, 80 (17.0%) developed postoperative DVT. The ML models achieved high overall accuracy in predicting DVT. Twenty-four models showed similarly excellent discrimination (pairwise AUC comparisons, p > 0.05). The top-performing model (random forest with RFE) attained an AUC of ~0.99, while several others (including LightGBM and SVM-based models) also reached AUC values in the 0.97–0.99 range. Notably, support vector machine models paired with Boruta or LASSO feature selection demonstrated the best calibration (lowest Brier scores), indicating reliable risk estimation. The final selected SVM models achieved high specificity (≥95%) with moderate sensitivity (~75–80%) for DVT detection. Conclusions: ML models demonstrated high accuracy in predicting postoperative DVT following tibial fracture surgery. Support vector machine-based models showed particularly favorable discrimination and calibration. These results suggest the potential utility of ML-based risk stratification to guide individualized prophylaxis, warranting further validation in prospective clinical settings. Full article

Pulmonary embolism (PE) is an under-recognised yet serious complication in patients with acute ischaemic stroke (AIS), contributing significantly to morbidity and mortality. The interplay of traditional risk factors—such as immobility, endothelial dysfunction, and hypercoagulability—with AIS-specific conditions, including atrial fibrillation, malignancy, and reperfusion therapies, complicates both diagnosis and management. Despite available prophylactic strategies, including low-molecular-weight heparin and intermittent pneumatic compression, their use remains limited by bleeding concerns and a lack of tailored guidelines. This review synthesises the current evidence on the incidence, risk factors, pathophysiology, diagnostic approaches, and preventive strategies for PE in AIS, identifying critical gaps in risk stratification and clinical decision-making. We propose a novel mechanistic framework—the Brain–Lung Thromboinflammatory Axis Hypothesis—which posits that stroke-induced systemic inflammation, neutrophil extracellular trap (NET) formation, and pulmonary endothelial activation may drive in situ pulmonary thrombosis independent of deep vein thrombosis. This conceptual model highlights new diagnostic and therapeutic targets and underscores the need for stroke-specific VTE risk calculators, biomarker-guided prophylaxis, and prospective trials to optimise prevention and outcomes in this vulnerable population. Full article

The Sidi Aissa Pb-Zn-(Ag) District, located within the Nappe Zone of northern Tunisia, has been reinterpreted as a typical intermediate-sulfidation (IS) epithermal mineralization system based on field observations and lithogeochemical analyses. Previously described as vein-style Pb-Zn deposits, the local geological framework is dominated by extensional normal faults forming half-grabens. These faults facilitated the exhumation of deep Triassic autochthonous rocks and the extrusion of 8-Ma rhyodacites and Messinian basalts. These structures, functioning as pathways for magmatic-hydrothermal fluids, facilitated the upward migration of acidic fluids, which interacted with the surrounding wall rocks, forming a subsurface alteration zone. The mineralization, shaped by Miocene extensional tectonics and magmatic activity, occurred in three stages: early quartz-dominated veins, an intermediate barite-rich phase, and late-stage supergene oxidation. Hydrothermal alteration, characterized by silicification, argillic, and propylitic zones, is closely associated with the deposition of base metals (Pb, Zn) and silver. The mineral assemblage, including barite, galena, sphalerite, and quartz, reflects dynamic processes such as fluid boiling, mixing, and pressure changes. Full article

Venous thromboembolism (VTE) represents a significant complication of cancer immunotherapy, with emerging evidence suggesting distinct pathophysiological mechanisms compared to traditional chemotherapy-associated thrombosis. This narrative review examines the epidemiology and pathogenesis of VTE in patients receiving immunotherapies for cancer including immune checkpoint inhibitors (ICIs), chimeric antigen receptor (CAR) T-cell therapy, bispecific T-cell engagers (BiTEs), among others. Real-world studies demonstrate a wide range of VTE incidence rates in ICI recipients, with potential mechanisms including exacerbated underlying interleukin-8-mediated inflammatory pathways and consequent neutrophil extracellular trap (NET) formation. CAR T-cell therapy is associated with unique hemostatic challenges, including concurrent thrombotic and bleeding risks related to cytokine release syndrome. Current risk assessment tools show limited predictive utility in patients receiving immunotherapies for cancer, highlighting the need for novel stratification models. Future research priorities include developing immunotherapy-specific risk prediction tools, elucidating mechanistic pathways linking immune activation to thrombosis, and establishing evidence-based and tailored thromboprophylaxis strategies. As cancer immunotherapy continues to evolve, understanding and mitigating thrombotic complications remains crucial for optimizing patient outcomes. Full article

Mulberry (Morus spp.), as an economically significant crop in sericulture and medicinal applications, faces severe threats to leaf yield and quality from pest and disease infestations. Traditional detection methods relying on chemical pesticides and manual observation prove inefficient and unsustainable. Although computer vision and deep learning technologies offer new solutions, existing models exhibit limitations in natural environments, including low recognition rates for small targets, insufficient computational efficiency, poor adaptability to occlusions, and inability to accurately identify structural features such as leaf veins. We propose Mamba-YOLO-ML, an optimized model addressing three key challenges in vision-based detection: Phase-Modular Design (PMSS) with dual blocks enhancing multi-scale feature representation and SSM selective mechanisms and Mamba Block, Haar wavelet downsampling preserving critical texture details, and Normalized Wasserstein Distance loss improving small-target robustness. Visualization analysis of the detection performance on the test set using GradCAM revealed that the enhanced Mamba-YOLO-ML model demonstrates earlier and more effective focus on characteristic regions of different diseases compared with its predecessor. The improved model achieved superior detection accuracy with 78.2% mAP50 and 59.9% mAP50:95, outperforming YOLO variants and comparable Transformer-based models, establishing new state-of-the-art performance. Its lightweight architecture (5.6 million parameters, 13.4 GFLOPS) maintains compatibility with embedded devices, enabling real-time field deployment. This study provides an extensible technical solution for precision agriculture, facilitating sustainable mulberry cultivation through efficient pest and disease management. Full article

Venous thromboembolism (VTE), comprising deep vein thrombosis (DVT) and pulmonary embolism (PE), is a life-threatening vascular disorder associated with significant morbidity and mortality. Prompt diagnosis is crucial for preventing fatal complications. Current clinical VTE diagnosis predominantly relies on imaging modalities such as compression ultrasound, computed tomography angiography (CTA), and magnetic resonance imaging (MRI). However, these techniques are resource-intensive, time-consuming, and may expose patients to radiation risks. Consequently, the development of highly sensitive and specific biomarkers is imperative to enhance early detection and guide therapeutic interventions. This review examines established and emerging biomarkers in venous thrombosis, evaluates current challenges, and outlines promising future directions for biomarker research in VTE. Full article

Background and Objectives: Inherited thrombophilia (IT) increases the risk of adverse pregnancy outcomes, but the benefit of low-molecular-weight heparin (LMWH) prophylaxis remains debated. This study aimed evaluate the effect of LMWH by analyzing outcomes in women with IT who received LMWH versus those who did not and also compare pregnancy complication rates before and after inherited thrombophilia diagnosis. Materials and Methods: We conducted a retrospective case–control study including 276 pregnant women with inherited thrombophilia and prior pregnancy complications and 276 healthy pregnant controls on delivery. The main outcome was the incidence of complications: preterm rupture of membranes, oligohydramnios, fetal growth restriction, preterm delivery, stillbirth, HELLP syndrome, gestational hypertension, deep vein thrombosis, and recurrent pregnancy loss. The effect of LMWH was assessed by comparing complication rates among inherited thrombophilia patients who received therapy versus those who did not. Results: Women with IT were older, had higher BMI, delivered earlier, and had neonates with lower birth weight compared to controls. In current pregnancies, LMWH was associated with reduced rates of preterm delivery, fetal growth restriction, gestational hypertension, and recurrent pregnancy loss, especially in factor V Leiden carriers. LMWH had little effect on low-risk genotypes and was not independently associated with outcome reduction. Conclusions: LMWH prophylaxis should be reserved for high-risk women with IT. Routine use in all IT pregnancies is not justified and may cause unnecessary risks and costs. Early screening, risk stratification, and individualized care are essential to optimize outcomes. Full article

Direct oral anticoagulants (DOACs) have been licensed worldwide for several years for various indications. Each year, 10–15% of patients receiving oral anticoagulants will undergo an interventional procedure, and expert groups have issued several guidelines for perioperative management in such situations. According to the PAUSE study, the proposed randomized strategy of stopping DOACs without bridging therapy in patients with atrial fibrillation was associated with low rates of major bleeding and arterial thromboembolism so that its implementation is increasingly safe. The present study was carried out in order to investigate the efficacy and safety of the standardized perioperative DOAC management strategy by measuring the residual activity of oral anticoagulants when stopping them preoperatively in daily practice in a regional hospital. Thirty-two patients were included in the present study. They were patients who suffered from atrial fibrillation or deep vein thrombosis and were receiving an oral anticoagulant, rivaroxaban or apixaban at the indicated dose. These patients underwent an elective surgery or invasive procedure at the Karditsa General Hospital between May 2022 and April 2023. The results showed that in a percentage of >90% of the patients on the day of surgery they had a residual anti-Xa activity below 0.5 U/mL. This rate is considered high and confirms the safety and efficacy of the guideline-recommended protocol for perioperative discontinuation of DOACs. Full article

Background/Objectives: The endoscopic transsphenoidal approach constitutes an excellent technique for adrenocorticotropin hormone (ACTH)-producing pituitary tumours. It is associated with subnormal postoperative serum cortisol levels, which may guide decisions regarding immediate re-operation. Methods: The authors retrospectively reviewed patients with Cushing’s disease who had undergone endoscopic transsphenoidal surgery between 2013 and 2023. All operations were performed by neurosurgeons and skull-base otolaryngologists. Surgical outcomes were evaluated in combination with prognostic factors such as cortisol and ACTH levels in terms of long-term remission and late recurrence rates of Cushing’s disease. Results: Fifty patients aged between 15 and 69 (average 37.8) years were evaluated, having undergone 50 operations. The median follow-up was 76.5 months (range: 23–122 months). Major complications with a transient CSF leak resulting from the surgical approach occurred in three patients. Two patients in the series experienced minor complications, developing a deep vein thrombosis, and thirteen patients developed transient diabetes insipidus. The initial remission rate was 84% (n = 42/50). Initial non-remission occurred in eight (8) patients (16%), with three macro- and five microadenomas. A total of 3 of the 42 patients with initial remission had a late recurrence after 50 months follow-up and required repeat transsphenoidal surgery. Seven patients (16.6%) who did not exhibit early postoperative cortisol reduction subsequently achieved remission. Male gender was the only factor that was significantly associated with lower remission rates in either short- or long-term follow-up (p = 0.003 and 0.038, respectively). An immediate postoperative ACTH nadir of ≤5 pg/mL was significantly related to long-term remission (p = 0.004). In our study, a significant correlation was confirmed between remission of the disease and 24 h urinary cortisol values, both early and late (p = 0.019), and serum cortisol <138 nmol/L. In this retrospective study from a single institution specialising in pituitary tumour management, the endoscopic transsphenoidal approach was shown to be both safe and effective. Additionally, we found that the risk of relapse in patients with Cushing’s disease persisting for more than 5 years after surgery is real but low. Moreover, failure to achieve an early postoperative cortisol reduction does not preclude a subsequent remission. Conclusions: Our findings demonstrate that ACTH, postoperative serum cortisol, and urinary free cortisol are valuable predictors of relapse over a five-year period and are closely correlated to each other. Full article