PyFMLab: Open-source software for atomic force microscopy microrheology data analysis.

Background: Atomic force microscopy (AFM) is one of the main techniques used to characterize the mechanical properties of soft biological samples and biomaterials at the nanoscale. Despite efforts made by the AFM community to promote open-source data analysis tools, standardization continues to be a significant concern in a field that requires common analysis procedures. AFM-based mechanical measurements involve applying a controlled force to the sample and measure the resulting deformation in the so-called force-distance curves.

Modeling the extracellular matrix in cell migration and morphogenesis: a guide for the curious biologist.

The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted. In processes of cell migration, the ECM also acts as a scaffold, providing structural support to cells as well as points of potential attachment. Although the ECM is a well-studied structure, its role in many biological processes remains difficult to investigate comprehensively due to its complexity and structural variation within an organism.

Prevalence of smoking habits, attitudes and knowledge on counteractive strategies among a sample of healthcare employees: results of the smoking-free health environments project in the province of Palermo, Italy.

Introduction: Tobacco use is responsible for over 7 million deaths annually, making smoking the leading cause of preventable mortality globally. Over the last two decades in Italy, the prevalence of smoking among physicians has consistently decreased, while it remains higher and is gradually decreasing among non-physician healthcare workers. The aim of this study was to investigate the Prevalence of smoking habits, attitudes, and knowledge on counteractive strategies among employees in the Primary Healthcare Facilities in the Province of Palermo, Italy.

Reliable, standardized measurements for cell mechanical properties.

Atomic force microscopy (AFM) has become indispensable for studying biological and medical samples. More than two decades of experiments have revealed that cancer cells are softer than healthy cells (for measured cells cultured on stiff substrates). The softness or, more precisely, the larger deformability of cancer cells, primarily independent of cancer types, could be used as a sensitive marker of pathological changes.

Relative importance of speech and voice features in the classification of schizophrenia and depression.

Speech is a promising biomarker for schizophrenia spectrum disorder (SSD) and major depressive disorder (MDD). This proof of principle study investigates previously studied speech acoustics in combination with a novel application of voice pathology features as objective and reproducible classifiers for depression, schizophrenia, and healthy controls (HC). Speech and voice features for classification were calculated from recordings of picture descriptions from 240 speech samples (20 participants with SSD, 20 with MDD, and 20 HC each with 4 samples).