Less than 7% of the world's population live at an altitude above 1500 m. Yet, as many as 67% of medalists in the 2020 men's and women's Olympic marathon, and 100% of medalists in the 2020 men's and women's Olympic 5000 m track race may have been born or raised above this otherwise rare threshold. As a possible explanation, research spanning nearly a quarter of a century demonstrates that indigenous highlanders exhibit pulmonary adaptations distinct from their lowland counterparts.
View Article and Find Full Text PDFA quantitative description of nuclear mechanics is crucial for understanding its role in force sensing within eukaryotic cells. Recent studies indicate that the chromatin within the nucleus cannot be treated as a homogeneous material. To elucidate its material properties, we combine optical tweezers manipulation of isolated nuclei with multi-color fluorescence imaging of lamin and chromatin to map the response of nuclei to local deformations.
View Article and Find Full Text PDFBiomolecular condensates assemble in living cells through phase separation and related phase transitions. An underappreciated feature of these dynamic molecular assemblies is that they form interfaces with other cellular structures, including membranes, cytoskeleton, DNA and RNA, and other membraneless compartments. These interfaces are expected to give rise to capillary forces, but there are few ways of quantifying and harnessing these forces in living cells.
View Article and Find Full Text PDFBackground: This study investigates the association between the mean arterial blood pressure (MAP), vasopressor requirement, and severity of hypoxic-ischemic encephalopathy (HIE) after cardiac arrest (CA).
Methods: Between 2008 and 2017, we retrospectively analyzed the MAP 200 h after CA and quantified the vasopressor requirements using the cumulative vasopressor index (CVI). Through a postmortem brain autopsy in non-survivors, the severity of the HIE was histopathologically dichotomized into no/mild and severe HIE.
Objective: To establish a deep learning model for the detection of hypoxic-ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format.
Methods: 168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.