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Artificial intelligence (AI) is currently becoming a leading field in data processing [...].
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The complex interplay between cells and materials is a key focus of this research, aiming to develop optimal scaffolds for regenerative medicine. The need for tissue regeneration underscores understanding cellular behavior on scaffolds, especially cell adhesion to polymer fibers forming focal adhesions. Key proteins, paxillin and vinculin, regulate cell signaling, migration, and mechanotransduction in response to the extracellular environment. This study utilizes advanced microscopy, specifically the AiryScan technique, along with advanced image analysis employing the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) cluster algorithm, to investigate protein distribution during osteoblast cell adhesion to polymer fibers and glass substrates. During cell attachment to both glass and polymer fibers, a noticeable shift in the local maxima of paxillin and vinculin signals is observed at the adhesion sites. The focal adhesion sites on polymer fibers are smaller and elliptical but exhibit higher protein density than on the typical glass surface. The characteristics of focal adhesions, influenced by paxillin and vinculin, such as size and density, can potentially reflect the strength and stability of cell adhesion. Efficient adhesion correlates with well-organized, larger focal adhesions characterized by increased accumulation of paxillin and vinculin. These findings offer promising implications for enhancing scaffold design, evaluating adhesion to various substrates, and refining cellular interactions in biomedical applications.
Asunto(s)
Adhesiones Focales , Mecanotransducción Celular , Paxillin/metabolismo , Vinculina/metabolismo , Adhesiones Focales/metabolismo , Adhesión Celular/fisiología , Polímeros/metabolismo , Fosfoproteínas/metabolismo , Proteína-Tirosina Quinasas de Adhesión Focal/metabolismoRESUMEN
Objectives: The purpose of this paper is to assess the determination of male and female sex from trabecular bone structures in the pelvic region. The study involved analyzing digital radiographs for 343 patients and identifying fourteen areas of interest based on their medical significance, with seven regions on each side of the body for symmetry. Methods: Textural parameters for each region were obtained using various methods, and a thorough investigation of data normalization was conducted. Feature selection approaches were then evaluated to determine a small set of the most representative features, which were input into several classification machine learning models. Results: The findings revealed a sex-dependent correlation in the bone structure observed in X-ray images, with the degree of dependency varying based on the anatomical location. Notably, the femoral neck and ischium regions exhibited distinctive characteristics between sexes. Conclusions: This insight is crucial for medical professionals seeking to estimate sex dependencies from such image data. For these four specific areas, the balanced accuracy exceeded 70%. The results demonstrated symmetry, confirming the genuine dependencies in the trabecular bone structures.