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LZZAY01 accelerated autophagy and apoptosis in colon cancer cells and improved gut microbiota in CAC mice.

Microbiol Spectr

January 2025

Laboratory of Microbiology and Immunology, School of Basic Medical Science, Inner Mongolia Medical University, Hohhot, China.

Colorectal cancer (CRC) is one of the malignant tumors globally, with high morbidity and mortality rates. The mainstay treatment of CRC includes surgery, radiotherapy, and chemotherapy. However, these treatments are associated with a high recurrence rate, poor prognosis, and highly toxic side effects.

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Plasticity is needed during development and homeostasis to generate diverse cell types from stem and progenitor cells. Following differentiation, plasticity must be restricted in specialized cells to maintain tissue integrity and function. For this reason, specialized cell identity is stable under homeostatic conditions; however, cells in some tissues regain plasticity during injury-induced regeneration.

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The application of extracellular vesicles (EVs) as therapeutics or nanocarriers in cell-free therapies necessitates meticulous evaluations of different features, including their identity, bioactivity, batch-to-batch reproducibility, and stability. Given the inherent heterogeneity in EV preparations, this assessment demands sensitive functional assays to provide key quality control metrics, complementing established methods to ensure that EV preparations meet the required functionality and quality standards. Here, we introduce the detectEV assay, an enzymatic-based approach for assessing EV luminal cargo bioactivity and membrane integrity.

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Novel GSIP: GAN-based sperm-inspired pixel imputation for robust energy image reconstruction.

Sci Rep

January 2025

Department of Computer Science, Faculty of Computers and Informatics, Kafrelsheikh University, Kafrelsheikh, Egypt.

Missing pixel imputation is a critical task in image processing, where the presence of high percentages of missing pixels can significantly degrade the performance of downstream tasks such as image segmentation and object detection. This paper introduces a novel approach for missing pixel imputation based on Generative Adversarial Networks (GANs). We propose a new GAN architecture incorporating an identity module and a sperm motility-inspired heuristic during filtration to optimize the selection of pixels used in reconstructing missing data.

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Design of an improved graph-based model for real-time anomaly detection in healthcare using hybrid CNN-LSTM and federated learning.

Heliyon

December 2024

Department of Computer Science & Engineering, K L E F Deemed To Be University, Green Fields, Vaddeswaram, Guntur (dt), Andhra Pradesh, 521230, India.

Real-time monitoring and anomaly detection are essential in healthcare to ensure safe conditions for patients and maintain the integrity of medical data samples. The majority of existing systems, despite improvements in healthcare technologies, cannot capture the spatial and temporal patterns of multimodal data simultaneously, process high Volume data in real-time, and ensure the privacy of patients' identity effectively. In this work, we handle these limitations by proposing a complete approach that uses state-of-the-art deep learning and data processing architectures to realize resilient anomaly detection in healthcare systems.

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