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关键词： ANOCA   coronary angiography   death   ischemic stroke   myocardial infarction   stable angina pectoris   0VD   zero-vessel disease   ANOCA   angina with no obstructive coronary arteries   CAD   coronary artery disease   CAG   coronary angiography   RD   risk difference  

摘要： According to international guidelines, patients with angina and no obstructive coronary artery disease (ANOCA) are at elevated risk for adverse clinical events.

关键词： Automated breast ultrasound system   Ultrasound   Diagnostic performance   Breast cancer: AI-CAD  

摘要： To assess the diagnostic performance and clinical usefulness of deep learning-based computer-aided detection (AI-CAD) for automated breast ultrasound (ABUS) across radiologists with varying ABUS experience. This retrospective study included 114 women (228 breasts) who underwent ABUS in 2019. Three radiologists interpreted images with and without AI-CAD. We evaluated sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the curve (AUC), reading time and interobserver agreement in Breast Imaging Reporting & Data System (BI-RADS) categorization and biopsy recommendations. Among 114 women (50.9 +/- 10.8 years), 28 were diagnosed with breast cancer. The following performance metrics improved significant with AI-CAD: Reader 1 (least experienced of ABUS;2 years of ABUS experience), AUC, 0.837 to 0.947 (p = 0.009), and NPV, 95.8% to 98.4% (p = 0.022);Reader 2 (7 years of experience), PPV, 50.0% to 59.5% (p = 0.042);Reader 3 (8 years of experience), PPV, 55.6% to 66.7% (p = 0.034). Reader 1 with AI-CAD achieved a performance comparable or higher than those of more experienced readers without AI. Specifically: compared with Reader 2, specificity (93.5% vs. 88.0%), PPV (65.8% vs. 50.0%), and accuracy (93.0% vs. 87.7%) were higher. Although Reader 3 originally demonstrated higher NPV (98.4% vs. 95.8%) and AUC (0.954 vs. 0.837) without CAD, these differences were no longer significant when Reader 1 used AI-CAD. Across all readers, AI-CAD reduced the mean reading time by an average of 25 s (p < 0.001). Inter-observer agreement after AI-CAD use (BI-RADS kappa: 0.279 -> 0.363;biopsy recommendation kappa: 0.666 -> 0.736) showed no statistically significant difference. AI-CAD enhanced diagnostic performance and reading efficiency in ABUS interpretation, demonstrating the most pronounced improvement for the less experienced reader.

关键词： angina with nonobstructive arteries   coronary physiology   coronary vasomotor disorders   endothelial dysfunction   myocardial bridging   Ach   acetylcholine   ANOCA   angina with nonobstructive coronary arteries   CAD   coronary artery disease   CFR   coronary flow reserve   CFT   coronary function testing   CMD   coronary microvascular dysfunction   EAPCI   European Association of Percutaneous Cardiovascular Interventions   FFR   fractional flow reserve   IMR   index of microcirculatory resistance   IVUS   intravascular ultrasound   MB   myocardial bridge   MVN   Microvascular Network   SAQ   Seattle Angina Questionnaire  

摘要： Coronary function testing (CFT) protocols in patients with angina with nonobstructive coronary arteries (ANOCA) differ among expert working groups. The European Association of Percutaneous Cardiovascular Interventions (EAPCI) endorses testing for coronary artery spasm and microvascular dysfunction, while the Microvascular Network (MVN) recommends additional assessment for myocardial bridging and endothelial dysfunction.

关键词： CAM   error tolerance   in-memory computing   logical operation   SRAM  

摘要： With the explosive growth of global data volume, efficient matching and computation have become core requirements for data processing. Reconfigurable SRAM macro for content-addressable memory (CAM) that realize rapid data matching and in-memory computing (IMC) that reduce frequent data exchange between memory and computing unit is a promising new architecture for data efficient matching and calculation. However, during data matching using previous reconfigurable SRAM macro for CAM and IMC, errors in input data or information stored in memory can compromise the success of data matching. And in conventional reconfigurable SRAM macro for CAM and IMC, there is a widespread problem of short-circuit current between the matching cells and the mismatching cells during data match operations, which impairs its energy efficiency. To address above problems, this paper proposes a reconfigurable 11T SRAM macro for error tolerance CAM and IMC. The proposed macro enables both exact matching and error tolerance matching, allows logic operations to be performed, and resolves the problem of short-circuit current between the matching cells and the mismatching cells during data match operations. At a supply voltage of 1 V, our design achieves an energy consumption of 0.231 fJ/bit and a frequency of 515 MHz for exact matching, 1.249 fJ/bit and 462 MHz for error tolerance matching, and 25.47 fJ/bit and 489 MHz for logic computation.

关键词： AlphaFold   AlphaMissense   exome sequencing   hydrocephalus   L1CAM   prenatal diagnosis  

摘要： Background Prenatal diagnosis of X-linked hydrocephalus caused by variants in the L1CAM gene is often complicated by the identification of Variants of Uncertain Significance (VUSs). This study showcases an accelerated diagnostic workflow using artificial intelligence (AI) to rapidly interpret a novel missense variant for a family with a history of the disorder. Methods We performed exome sequencing (ES) on a male fetus with significant sonographic brain anomalies from a 29-year-old pregnant woman. To efficiently analyze the resulting VUSs, we used the AI tool AlphaMissense to predict their pathogenicity and prioritize them for validation. The top candidate variant was then assessed via Sanger sequencing for co-segregation across eight maternal relatives. The structural impact of the mutation was visualized using the AlphaFold 3 model. Results Exome sequencing identified four VUSs. AlphaMissense predicted only one, L1CAM c.1228C>G (***410Asp), as 'likely pathogenic'. Subsequent Sanger sequencing confirmed that this variant co-segregated perfectly with the disease phenotype in the family. Based on this strong genetic evidence, the variant was reclassified from a VUS to 'Likely Pathogenic'. Structural modeling revealed that the ***410Asp substitution disrupts a critical salt bridge, likely compromising protein stability. Conclusion Our two-step approach-using AI for rapid VUS prioritization followed by targeted Sanger validation-proved to be a highly efficient strategy. It provided a definitive and clinically actionable diagnosis that facilitated genetic counseling and enabled the family to pursue Preimplantation Genetic Testing (PGT). This workflow significantly enhances the power of genomic testing in the prenatal setting.

关键词： cardiac CT   non obstructive coronary artery disease   NOCAD   CAD  

摘要： Non-obstructive coronary artery disease (NOCAD) encompasses a heterogeneous group of conditions in which patients present with angina, ischemia or myocardial infarction despite the absence of obstructive epicardial stenoses. This spectrum includes myocardial infarction with non-obstructive coronary arteries (MINOCA) and angina or ischemia with non-obstructive coronary arteries (ANOCA/INOCA), entities increasingly recognized as clinically significant and associated with adverse outcomes. Advances in cardiac computed tomography (CT) have expanded the diagnostic capabilities beyond the exclusion of obstructive coronary artery disease, enabling comprehensive anatomical, functional and tissue-level assessment relevant to NOCAD. CT allows precise identification of non-obstructive atherosclerosis, high-risk plaque features, myocardial bridging and structural vascular remodelling. Quantitative and qualitative characterization of plaque burden correlates with ischemic risk and provides prognostic information that complements traditional stenosis-based evaluation. Emerging CT-derived biomarkers, such as pericoronary fat attenuation index and epicardial adipose tissue metrics, offer insight into vascular inflammation and microvascular dysfunction, key mechanisms in NOCAD. Functional CT techniques, such as CT-derived fractional flow reserve and CT perfusion imaging, enable non-invasive assessment of hemodynamic significance and microvascular impairment, although their routine use is limited by methodological variability and evolving clinical evidence. Beyond coronary evaluation, CT also provides myocardial tissue characterization, detects extracardiac causes of symptoms and contributes to comprehensive differential diagnosis. Despite its strengths, cardiac CT remains limited by spatial resolution, radiation exposure and its inability to directly visualize the microcirculation. Nevertheless, ongoing technological refinement and integration of computational modelling are likely t

关键词： I-CAM-Q   Complementary and alternative medicine   Cross-sectional study   Linguistic and intercultural adaptation   Hungary   Questionnaire validation  

摘要： Background The International Questionnaire to Measure the Use of Complementary and Alternative Medicine (I-CAM-Q) is a standardized tool for assessing CAM use. While it has been adapted into several languages, this study presents the first Hungarian translation and cultural adaptation. Given the growing interest in CAM in Hungary, a validated Hungarian version is essential for accurate data collection and informed healthcare policy. Methods The I-CAM-Q was translated into Hungarian using a rigorous forward-backward translation protocol involving expert translators, proofreaders, and a reconciliation *** final version was pilot-tested among healthy volunteer healthcare workers from ophthalmology departments. The questionnaires were used to assess clarity, cultural relevance, and reliability in this cross-sectional study. Individuals with diagnosed eye diseases were excluded. Results Among ophthalmologically healthy volunteers, 77.8% consulted physicians in the past 12 months, while 8.9% visited chiropractors and spiritual healers, and 2.2% consulted acupuncturists. In the past 3 months, physicians remained the most consulted (73.7%), followed by chiropractors (53.3%). CAM therapies were mainly used for general well-being and acute conditions, with high satisfaction 75-100% of users rated chiropractic, acupuncture, and spiritual healing as "very useful."Phytomedicines were used primarily for acute illness (41.7%) and general wellbeing (27.1%), with 68.1% of users rating them as very useful. Dietary supplements were widely consumed, especially Vitamin D (62.9%) and Vitamin C (57.1%), mainly for prevention (46.2%) and general health (38.5%). Meditation and relaxation techniques were also commonly practiced, with 92.3% and 69.2% of users, respectively, rating them as very useful. Conclusions The Hungarian version of the I-CAM-Q was successfully translated, culturally adapted, and validated. It provides a reliable tool for assessing CAM use in Hungary and supports f

关键词： CAD/CAM composite block   Universal adhesive   Curing mode   Dentin sealing   Microtensile bond strength   Adhesive dentistry  

摘要： The aim of this study was to investigate influence of curing mode of universal adhesives and dentin sealing approach on microtensile bond strength (MTBS) of CAD/CAM composite to dentin. Occlusal surfaces of 36 human molars were ground to expose flat dentin and randomly assigned to 6 groups according to: (1) Adhesive curing mode [light-cured/LC (One coat 7 Universal, COLTENE);dual-cure/DC (One coat 7 Universal/Dual-cure Activator, COLTENE);and self-cure/SC (Palfique Universal Bond, Tokuyama);and (2) Dentin sealing approach (delayed sealing/DDS and immediate sealing/IDS). Following 1-week provisionalization, CAD/CAM composite blocks (Brilliant Crios, COLTENE), 4 mm2, were cemented over conditioned dentin surfaces. After 24 h, bonded assemblies were thermo-cycled for 5000 cycles. Specimens were tested for MTBS. Failure mode was analyzed under stereomicroscope. Data were statistically analyzed using ANOVA. DDS showed significantly higher MTBS values than IDS when using LC and DC adhesives. While, IDS produced significantly higher MTBS values than DDS when using SC adhesive. Predominant failure mode was adhesive in all groups, except for SC adhesive in IDS group, mixed failure was the predominant mode. Light- and dual-cured universal adhesives improved bond strength in delayed dentin sealing approach. Self-cure universal adhesive produced better bond strength when applied to immediately sealed dentin.

关键词： woodland extraction   semantic segmentation   convolutional attention mechanism   change detection   twin networks  

摘要： Highlights What are the main findings? The proposed CAM-HRNet achieves state-of-the-art performance in binary forest land change detection (IoU: 75.24%, F1: 85.88%). The framework effectively performs semantic change detection, identifying both changed areas and their specific land-cover types. What are the implications of the main findings? It provides a powerful, automated tool for accurate and efficient dynamic monitoring of forest land resources. The integrated architecture offers a valuable reference for other precise feature extraction tasks in remote *** What are the main findings? The proposed CAM-HRNet achieves state-of-the-art performance in binary forest land change detection (IoU: 75.24%, F1: 85.88%). The framework effectively performs semantic change detection, identifying both changed areas and their specific land-cover types. What are the implications of the main findings? It provides a powerful, automated tool for accurate and efficient dynamic monitoring of forest land resources. The integrated architecture offers a valuable reference for other precise feature extraction tasks in remote *** As a vital component of Earth's ecosystem, forest land plays an irreplaceable role in maintaining ecological balance. To address the limitations of traditional deep learning methods in remote sensing data generalization, this paper proposes CAM-HRNet, a change detection framework that integrates the High-Resolution Net (HRNet) backbone with a convolutional attention mechanism. The method leverages HRNet's multi-scale parallel structure and incorporates attention mechanisms at different scales, while a step-by-step up-sampling mechanism enables smooth multi-scale feature fusion with reduced information loss. By combining CAM-HRNet's feature extraction capabilities with a twin network structure, we develop both binary and semantic change detection methods. The binary method identifies changed areas through difference feature calculation,