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2025
Granulomatous and amyloidogenic cardiomyopathies are infiltrative conditions that can be fatal if left untreated. Among these, cardiac amyloidosis and cardiac sarcoidosis are significant but often underdiagnosed causes of heart failure, each serving as cardiac manifestations of broader systemic diseases. Advancements in imaging techniques, along with the emergence of novel therapies—particularly for cardiac amyloidosis—have brought these conditions into sharper focus for both clinicians and researchers. The assessment of patients' cardiac and extracardiac symptoms, combined with echocardiography, is crucial in raising initial suspicion for these diseases. Cardiac magnetic resonance imaging is essential for differentiating between the two, as distinct late gadolinium enhancement patterns are observed in each condition. Additional diagnostic value is provided by positron emission tomography and Technetium-labeled nuclear scintigraphy, which can help confirm the diagnosis in the majority of patients. Early diagnosis is key to improving outcomes. Treatment strategies for these conditions differ significantly: cardiac amyloidosis is primarily managed with disease-modifying therapies for the transthyretin subtype and chemotherapy for the AL subtype, while cardiac sarcoidosis is treated with corticosteroids and immunosuppressive drugs aimed at reducing inflammation.- Book : ()
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2025
- Book : 6()
- Pub. Date : 2025
- Page : pp.100104-100104
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2025
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- Pub. Date : 2025
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2025
SUMMARYMolecular targeted drugs are frequently used in precision cancer therapies. However, the prolonged administration of these agents can result in drug resistance. Cancer cells exhibiting defects in homologous recombination are particularly susceptible to genotoxic stress, such as that induced by PARP inhibitors (PARPi), resulting in synthetic lethality. Here, we show that sustained treatment of such cancer cells with PARPi selectively upregulates YAP1-2α, a minor isoform of YAP1. Elevated YAP1-2α heterodimerizes with TAZ to induce liquid-liquid phase separation (LLPS) in the nucleus. This LLPS-driven process generates nuclear condensates that activate a super-enhancer comprising YAP1-2α, TAZ, TEAD, and BRD4. The super-enhancer reconfigures transcriptional networks to enhance cancer stem-like malignant properties, thereby potentiating cell resilience and augmenting cell resistance to adverse conditions, including precision cancer therapies. Our study reveals the presence of a super-enhancer that promotes malignant tumor progression. Targeting the YAP1-2α/TAZ-induced super-enhancer is a promising strategy for overcoming resistance to anticancer modalities.- Book : ()
- Pub. Date : 2025
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2025
- Book : ()
- Pub. Date : 2025
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2025
Most accidents during the construction of nuclear power plants are caused by human unsafe behavior. How to scientifically determine the risk management priority of human unsafe behaviors is the basis for effectively preventing accidents in under-construction nuclear power plants. Although employees are adopted for control in under-construction nuclear power plants, the records of unsafe behaviors are mostly recorded by inspectors, and the records of behaviors may have missing values. To overcome the above problems, this paper applies machine learning algorithms to construct an employee behavioral risk assessment model. Firstly, by analyzing the influencing factors of unsafe behaviors, the assessment indexes are proposed, then the Random Forest algorithm is used to obtain the characteristic importance of the proposed indexes and exclude those with smaller characteristic importance. Finally, the harmony search (HS) algorithm is used to optimize the back propagation (BP) neural network to construct an assessment model and compare with the BP evaluation model. The results show that the HS-BP model is more accurate and efficient. The results show that the method can comprehensively and effectively analyze workers‘ unsafe behaviors, and the BP neural network is optimized to construct the assessment model using the Harmonic Search algorithm, which is more accurate than the original model. The use of the machine learning method to assess workers’ behaviors can objectively output the risk level and overcome the one-sidedness and subjectivity of the traditional expert evaluation method.- Book : 13(2)
- Pub. Date : 2025
- Page : pp.340-340
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2025
The accessory navicular (AN) is an accessory bone located on the posteromedial aspect of the navicular tuberosity that can cause pain following overuse or trauma, particularly during childhood. However, the detailed epidemiological characteristics of AN in children have not been well studied. This study aimed to clarify the prevalence of AN and painful AN among Japanese children by examining the characteristics according to sex and age. This cross-sectional study used data from the Katsuragi Integrated Defense for Locomotive Syndrome in Children Study, focusing on musculoskeletal disorders in 875 children aged 6–15 years, with 1750 feet being assessed. Children were divided into five age groups: 6–7, 8–9, 10–11, 12–13, and 14–15. AN was detected using ultrasound to avoid radiation exposure. The sex- and age-group-dependent prevalence of AN and painful AN were calculated, and statistical analyses examined sex differences in prevalence by age group. The overall prevalence of AN was 15.1%, higher in females (17.9%) than in males (12.3%). The prevalence of AN increased with age in both sexes. Among cases diagnosed with AN, 20.8% were symptomatic, with a unimodal peak observed at ages 12–13 in males and 10–11 in females. No statistically significant differences were observed in the proportion of painful AN between sexes. This is the first large-scale epidemiological study on AN in children. The overall prevalence of AN was 15.1%, higher in females than in males. Additionally, 20.8% of patients with AN experienced pain. The results of this study provide important epidemiological data to support clinical management strategies for pediatric patients with AN.- Book : 20(1)
- Pub. Date : 2025
- Page : pp.e0318014-e0318014
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2025
- Book : online()
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2025
- Book : ()
- Pub. Date : 2025
- Page : pp.111010-111010
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2025
- Book : ()
- Pub. Date : 2025
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