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1.
Biophys Rev (Melville) ; 5(3): 031302, 2024 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-39091432

RESUMEN

Living cells can perform incredible tasks that man-made micro/nano-sized robots have not yet been able to accomplish. One example is that white blood cells can sense and move to the site of pathogen attack within minutes. The robustness and precision of cellular functions have been perfected through billions of years of evolution. In this context, we ask the question whether cells follow a set of physical principles to sense, adapt, and migrate. Microfluidics has emerged as an enabling technology for recreating well-defined cellular environment for cell migration studies, and its ability to follow single cell dynamics allows for the results to be amenable for theoretical modeling. In this review, we focus on the development of microfluidic platforms for recreating cellular biophysical (e.g., mechanical stress) and biochemical (e.g., nutrients and cytokines) environments for cell migration studies in 3D. We summarize the basic principles that cells (including bacteria, algal, and mammalian cells) use to respond to chemical gradients learned from microfluidic systems. We also discuss about novel biological insights gained from studies of cell migration under biophysical cues and the need for further quantitative studies of cell function under well-controlled biophysical environments in the future.

2.
Platelets ; 34(1): 2264978, 2023 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-37933490

RESUMEN

Platelets contribute to COVID-19 clinical manifestations, of which microclotting in the pulmonary vasculature has been a prominent symptom. To investigate the potential diagnostic contributions of overall platelet morphology and their α-granules and mitochondria to the understanding of platelet hyperactivation and micro-clotting, we undertook a 3D ultrastructural approach. Because differences might be small, we used the high-contrast, high-resolution technique of focused ion beam scanning EM (FIB-SEM) and employed deep learning computational methods to evaluate nearly 600 individual platelets and 30 000 included organelles within three healthy controls and three severely ill COVID-19 patients. Statistical analysis reveals that the α-granule/mitochondrion-to-plateletvolume ratio is significantly greater in COVID-19 patient platelets indicating a denser packing of organelles, and a more compact platelet. The COVID-19 patient platelets were significantly smaller -by 35% in volume - with most of the difference in organelle packing density being due to decreased platelet size. There was little to no 3D ultrastructural evidence for differential activation of the platelets from COVID-19 patients. Though limited by sample size, our studies suggest that factors outside of the platelets themselves are likely responsible for COVID-19 complications. Our studies show how deep learning 3D methodology can become the gold standard for 3D ultrastructural studies of platelets.


COVID-19 patients exhibit a range of symptoms including microclotting. Clotting is a complex process involving both circulating proteins and platelets, a cell within the blood. Increased clotting is suggestive of an increased level of platelet activation. If this were true, we reasoned that parts of the platelet involved in the release of platelet contents during clotting would have lost their content and appear as expanded, empty "ghosts." To test this, we drew blood from severely ill COVID-19 patients and compared the platelets within the blood draws to those from healthy volunteers. All procedures were done under careful attention to biosafety and approved by health authorities. We looked within the platelets for empty ghosts by the high magnification technique of electron microscopy. To count the ghosts, we developed new computer software. In the end, we found little difference between the COVID patient platelets and the healthy donor platelets. The results suggest that circulating proteins outside of the platelet are more important to the strong clotting response. The software developed will be used to analyze other disease states.


Asunto(s)
COVID-19 , Aprendizaje Profundo , Humanos , ARN Viral , SARS-CoV-2 , Plaquetas/ultraestructura , Orgánulos
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