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Proximal humeral fractures (PHF), ranking as the third most common osteoporotic fractures, pose a significant challenge in management. With a rising incidence in an aging population, controversy surrounds surgical versus nonoperative treatments, particularly for displaced 3- and 4-part fractures in older patients. Locking plates (LP) and proximal intramedullary nails (PHN) are primary choices for surgical intervention, but both methods entail complications.

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Adeno-associated viral (AAV) vectors are increasingly used for preclinical and clinical cardiac gene therapy approaches. However, gene transfer to cardiomyocytes poses a challenge due to differences between AAV serotypes in terms of expression efficiency and . For example, AAV9 vectors work well in rodent heart muscle cells but not in cultivated neonatal rat ventricular cardiomyocytes (NRVCMs), necessitating the use of AAV6 vectors for studies.

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Background: Dysbiosis of the lung microbiome can contribute to the initiation and progression of lung cancer. Synchronous multiple primary lung cancer (sMPLC) is an increasingly recognized subtype of lung cancer characterized by high morbidity, difficulties in early detection, poor prognosis, and substantial clinical challenges. However, the relationship between sMPLC pathogenesis and changes in the lung microbiome remains unclear.

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Background: Macrophages play a dual role in the tumor microenvironment(TME), capable of secreting pro-inflammatory factors to combat tumors while also promoting tumor growth through angiogenesis and immune suppression. This study aims to explore the characteristics of macrophages in lung adenocarcinoma (LUAD) and establish a prognostic model based on macrophage-related genes.

Method: We performed scRNA-seq analysis to investigate macrophage heterogeneity and their potential pseudotime evolutionary processes.

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Introduction: Cyber situational awareness is critical for detecting and mitigating cybersecurity threats in real-time. This study introduces a comprehensive methodology that integrates the Isolation Forest and autoencoder algorithms, Structured Threat Information Expression (STIX) implementation, and ontology development to enhance cybersecurity threat detection and intelligence. The Isolation Forest algorithm excels in anomaly detection in high-dimensional datasets, while autoencoders provide nonlinear detection capabilities and adaptive feature learning.

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