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关键词： peripheral arterial disease   coronary artery disease   coronary angiography  

摘要： Peripheral arterial disease (PAD) and coronary artery disease (CAD) are manifestations of atherosclerosis, affecting a substantial proportion of the population. Despite their interrelation, the prevalence of CAD in severe PAD varies, prompting the need to understand their complex relationship. This study retrospectively analyzes prospectively collected data from a high-volume vascular center to assess CAD prevalence, risk factors, and implications for patients undergoing vascular surgery. Among 667 arterial disease patients, 19.5% underwent coronary angiography, with CAD detected in 61.5% of cases. CAD varied across vascular beds. Decision-making around preoperative coronary angiography and revascularization remains complex, with benefits for high-risk patients still being debated. In accordance with current guidelines, the routine practice of coronary revascularization preceding vascular surgery is generally discouraged. This study underscores the need for risk stratification to identify patients who might benefit from coronary revascularization prior to vascular surgery while adhering to cost-effectiveness and avoiding unnecessary and time-consuming diagnostics in the majority of patients. Patient demographics, risk factors, and clinical presentation were analyzed alongside hospital stay, mortality, and complications. The study highlights the challenges in managing patients with concurrent CAD and PAD and calls for improved protocols for treating this high-risk group.

关键词： adversarial attack   AI security   computer vision   explainable AI  

摘要： Through advances in AI-based computer vision technology, the performance of modern image classification models has surpassed human perception, making them valuable in various fields. However, adversarial attacks, which involve small changes to images that are hard for humans to perceive, can cause classification models to misclassify images. Considering the availability of classification models that use neural networks, it is crucial to prevent adversarial attacks. Recent detection methods are only effective for specific attacks or cannot be applied to various models. Therefore, in this paper, we proposed an attention mechanism-based method for detecting adversarial attacks. We utilized a framework using an ensemble model, Grad-CAM and calculated the silhouette coefficient for detection. We applied this method to Resnet18, Mobilenetv2, and VGG16 classification models that were fine-tuned on the CIFAR-10 dataset. The average performance demonstrated that Mobilenetv2 achieved an F1-Score of 0.9022 and an accuracy of 0.9103, Resnet18 achieved an F1-Score of 0.9124 and an accuracy of 0.9302, and VGG16 achieved an F1-Score of 0.9185 and an accuracy of 0.9252. The results demonstrated that our method not only detects but also prevents adversarial attacks by mitigating their effects and effectively restoring labels.

关键词： biomaterials   chairside CAD/CAM materials   prosthetic dentistry   minimally invasive dentistry  

摘要： The present review provides an up-to-date overview of chairside CAD/CAM materials used in restorative dentistry, focusing on their classification, properties, and clinical applications. If CAD/CAM technology was only an aspiration in the past, a higher proportion of clinics are employing it nowadays. The market is overflowing with biomaterials, and these materials are constantly evolving, making it challenging for practitioners to choose the most appropriate one, especially in correlation with patients' medical diseases. The evolution of CAD/CAM technology has revolutionized dental practice, enabling the efficient fabrication of high-quality restorations in a single appointment. The main categories of chairside CAD/CAM materials include feldspathic ceramics, leucite-reinforced ceramics, lithium disilicate, zirconia, hybrid ceramics, and acrylic resins. The mechanical, physical, and aesthetic properties of these materials are discussed, along with their advantages and limitations for different clinical scenarios. Factors influencing material selection, such as strength, aesthetics, and ease of use, are also assessed. Ultimately, the guiding principle of dentistry is minimally invasive treatment following the particularity of the clinical case to obtain the envisioned result. Correlating all these factors, a simple, up-to-date classification is required to begin an individualized treatment. By synthesizing current evidence, this comprehensive review aims to guide clinicians in selecting appropriate chairside CAD/CAM materials to achieve optimal functional and aesthetic outcomes in restorative procedures. The integration of digital workflows and continued development of novel materials promise to further enhance the capabilities of chairside CAD/CAM systems in modern dental practice.

关键词： obstructive sleep apnea   orthognathic surgery   virtual planning   cone beam computed tomography   airway volume  

摘要： Background and Objectives: Obstructive sleep apnea is an extremely diffuse pathology that, if left untreated, can lead to very serious cardiovascular consequences. The primary goal of treatment is to maintain airflow in the upper airway tract, which can be obtained thanks to orthognathic surgery such as maxillo-mandibular advancement (MMA). This procedure increases the volume of the posterior airway space (PAS)-a parameter considered fundamental in OSA physiology. However, the correlation between the degree of advancement, the volume increase, and the clinical improvement in OSA is not yet clear, even in patients who undergo virtual surgical planning. Aiming to test the correlation of these parameters and the role of PAS volume changes, we present our pre- and post-operative volumetric analysis of the PAS using cone beam computed tomography (CBCT) following CAD/CAM-assisted maxillomandibular advancement. Materials and Methods: We collected information from patients who underwent MMA for moderate or severe OSA, planned virtually with custom-made devices, between 2020 and 2022 at the Maxillofacial Surgery and Odontostomatology Unit of the Policlinico Hospital in Milan. The degree of mandibular advancement (pogonion antero-posterior advancement) was noted. All patients underwent pre- and post-operative CBCT and pre- and post-operative polysomnography to measure the Apnea-Hypopnea Index (AHI) parameters. Both exams were performed within six months before and after surgery. The surgeries were planned virtually along with the production of custom-made devices (cutting guides and mandibular osteosynthesis plates). Volumetric analysis of the PAS was performed pre- and post-CBCT images using medical segmentation software (Mimics, Materialise, Mimcs 26.0). Results: Ten patients (nine men and one woman) with a mean age of 51 years were included in this study. The mean pogonion advancement was 14.5 mm, ranging from 13.8 to 15.6. The mean pre-surgical AHI was 52.31 events/h, whi

关键词： CVD   Heart and kidneys   Heart failure   CAD   Arrhythmias   Heart and kidneys   Heart failure   CAD   Arrhythmias  

摘要： Chronic kidney disease (CKD) is one of the major risk factors for cardiovascular diseases (CVD, manifested as coronary artery disease, heart failure, arrhythmia and sudden cardiac death) and the simultaneous presence of both CVD and CKD has a significant impact on the prognosis of patients. The diagnostic and therapeutic options for CVD are often limited in patients with advanced CKD and there is little or no evidence from large clinical studies for many interventional and pharmacological forms of treatment. This consensus paper provides an overview of the particularities of CVD in CKD and summarizes the current evidence and recommendations for the treatment of patients with CVD and CKD.

关键词： biocontrol   hunting camera   predation   sentinel prey   surveillance camera  

摘要： Cameras are increasingly used by ecologists to study species distribution and interactions. They are mainly used to study large animals such as mammals but can also be used to record small invertebrates, including insects.
Camera traps, capturing images within a specified field of view, can be used for biomonitoring and investigating insect-related interactions, such as predation. Understanding predation on insect prey has direct implications for agriculture and conservation biology, enabling predator species identification and quantification of biological control.
This review examines 28 studies published between 1988 and March 2024 focusing on the use of cameras to monitor insect predator-prey interactions, predominantly targeting agricultural pests. Studies varied in recording equipment used and tended to be spatially and temporally limited, making results difficult to generalise at larger scale.
We provide an overview of equipment options, camera settings, the merits of video versus picture recording, night-time imaging strategies, trigger mechanisms, equipment costs, and strategies for managing theft and vandalism. Additionally, we discuss avenues for improving image processing efficiency, including enhancing predator identification through artificial intelligence methods. Challenges related to limitations in the taxonomic levels of predator identification are also addressed.
Finally, we offer guidelines for researchers interested in using camera technology and propose future perspectives on their use in insect conservation and biocontrol efforts.

关键词： surrogate model   parameter tuning   CAM5 precipitation   nonuniform parameter parameterization scheme  

摘要： The uncertainty of physical parameters is a major factor contributing to poor precipitation simulation performance in Earth system models (ESMs particularly in tropical and Pacific regions. To address the high computational cost of repetitive ESM runs, this study proposes a multilevel surrogate model-based parameter optimization framework and applies it to improve the precipitation performance of CAM5. A top-level surrogate model using gradient boosting regression trees (GBRTs) was constructed, leveraging the candidate point (CAND) approach applied to balance exploration and exploitation. A bottom-level surrogate model was then built based on a small, selected dataset;we designed a trust region approach to adjust the sampling region during the bottom-level tuning process. Experimental results demonstrate that the proposed method achieves fast convergence and significantly enhances precipitation simulation accuracy, with an average improvement of 19% in selected regions. In integrating optimization results through a nonuniform parameterization scheme and parameter smoothing, substantial improvements were observed in the South Pacific, Ni & ntilde;o, South America, and East Asia. Comparisons with remote sensing data confirm that the optimized precipitation simulations do not introduce significant biases to other variables, validating the effectiveness and robustness of the proposed method.

关键词： femoroacetabular impingement syndrome   hip shape   magnetic resonance imaging   principal component analysis   correspondence model  

摘要： Background: Radiographic studies have reported a high prevalence of cam morphology in athletes, especially in male athletes, suggesting these individuals are at an elevated risk of developing femoroacetabular impingement syndrome (FAIS). However, recent research has shown that 2-dimensional measurements do not accurately characterize cam deformities, motivating the need for 3-dimensional (3D) analyses. Purpose: To develop a 3D statistical shape model of the proximal femur to evaluate cam morphology in collegiate athletes through (1) quantifying shape variation 2) establishing sex-based shape differences, and (3) comparing shapes between male athletes and male cam FAIS patients. Study Design: Cross-sectional study;Level of evidence, 3. Methods: Double-echo steady-state magnetic resonance images were prospectively acquired of the hips of Division I collegiate athletes (28 male, 23 female). An existing data set of computed tomography scans of cam FAIS patients (26 male) and morphologically screened controls (30 male, 17 female) was also evaluated. The proximal femur was segmented, reconstructed into a 3D surface, and analyzed to generate a correspondence model using ShapeWorks. Principal component analysis, parallel analysis, and linear discriminant analysis quantified variation in proximal femoral shape. Results: Variation in the full cohort primarily occurred in the head-neck junction, femoral offset, and location of the greater trochanter relative to the head/neck (mode VIII, adjusted P = .01;modes I and IV, adjusted P = .002 and adjusted P = .003, respectively;modes IV and VIII, adjusted P = .0003 and adjusted P = .0007, resepctively. P < .001). Modes represented anatomic variation significantly different between pairs within a group. Variation between male and female athletes occurred in the concavity of the head at the head-neck junction, length of the femur, and length of the femoral offset (modes I and II, adjusted P = .006 and adjusted P = .009, respectively).

关键词： Artificial intelligence   Bite-wing   Deep learning   Periodontal bone loss   YOLOv8  

摘要： Periodontal disease is a significant global oral health problem. Radiographic staging is critical in determining periodontitis severity and treatment requirements. This study aims to automatically stage periodontal bone loss using a deep learning approach using bite-wing images. A total of 1752 bite-wing images were used for the study. Radiological examinations were classified into 4 groups. Healthy (normal no bone loss;stage I (mild destruction bone loss in the coronal third (< 15%);stage II (moderate destruction bone loss is in the coronal third and from 15 to 33% (15-33%);stage III-IV (severe destruction bone loss extending from the middle third to the apical third with furcation destruction (> 33%). All images were converted to 512 x 400 dimensions using bilinear interpolation. The data was divided into 80% training validation and 20% testing. The classification module of the YOLOv8 deep learning model was used for the artificial intelligence-based classification of the images. Based on four class results, it was trained using fivefold cross-validation after transfer learning and fine tuning. After the training, 20% of test data, which the system had never seen, were analyzed using the artificial intelligence weights obtained in each cross-validation. Training and test results were calculated with average accuracy, precision, recall, and F1-score performance metrics. Test images were analyzed with Eigen-CAM explainability heat maps. In the classification of bite-wing images as healthy, mild destruction, moderate destruction, and severe destruction, training performance results were 86.100% accuracy, 84.790% precision, 82.350% recall, and 84.411% F1-score, and test performance results were 83.446% accuracy, 81.742% precision, 80.883% recall, and 81.090% F1-score. The deep learning model gave successful results in staging periodontal bone loss in bite-wing images. Classification scores were relatively high for normal (no bone loss) and severe bone loss in bite-win