The American journal of pathology
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Coronavirus disease 2019 has markedly varied clinical presentations, with most patients being asymptomatic or having mild symptoms. However, severe acute respiratory disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is common and associated with mortality in patients who require hospitalization. The etiology of susceptibility to severe lung injury remains unclear. ⋯ The interaction and imbalance between ACE and ACE2 result in an unopposed angiotensin II. Considering that the ACE insertion (I)/deletion (D) gene polymorphism contributes to the ACE level variability in general population, in which mean ACE level in DD carriers is approximately twice that in II carriers, we propose a hypothesis of genetic predisposition to severe lung injury in patients with coronavirus disease 2019. It is plausible that the ACE inhibitors and ACE receptor blockers may have the potential to prevent and to treat the acute lung injury after SARS-CoV-2 infection, especially for those with the ACE genotype associated with high ACE level.
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Hyaluronan (HA) is a ubiquitous glycosaminoglycan of the extracellular matrix. It is present in the endothelial glycocalyx covering the apical surface of endothelial cells. The endothelial glycocalyx regulates blood vessel permeability and homeostasis. ⋯ This review focuses on endothelial glycocalyx HA and highlights its key roles in the functions of the endothelial glycocalyx, its shedding in several pathologic conditions such as sepsis, diabetes, chronic and acute kidney injury, ischemia/reperfusion, atherosclerosis, and inflammation, which are all accompanied by increased circulating HA levels. Plasma/serum HA level is becoming recognized as a biomarker of endothelial glycocalyx damage in select pathologies. Hyaluronidase, the main HA-degrading enzyme, and its involvement in the impairment of endothelial glycocalyx are also addressed.
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Review
Endothelial Glycocalyx Hyaluronan: Regulation and Role in Prevention of Diabetic Complications.
The endothelial glycocalyx is critically involved in vascular integrity and homeostasis, by regulating vascular permeability, regulating mechanotransduction, and reducing inflammation and coagulation. The turnover of the glycocalyx is dynamic to fine-tune these processes. This is in particular true for its main structural component, hyaluronan (HA). ⋯ The (re)synthesis of HA is dependent on the availability of its sugar substrates, thus linking glycocalyx biology directly to cellular glucose metabolism. It is therefore of particular interest to consider the consequences of dysregulated cellular glucose in diabetes for glycocalyx biology and its implications for endothelial function. This review summarizes the metabolic regulation of endothelial glycocalyx HA and its potential as a therapeutic target in diabetic vascular complications.
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The glycocalyx is a layer coating the luminal surface of vascular endothelial cells. It is vital for endothelial function as it participates in microvascular reactivity, endothelium interaction with blood constituents, and vascular permeability. Structural and functional damage to glycocalyx occurs in various disease states. ⋯ By contrast, the concentrations of these compounds in the circulation decrease after successful protective interventions in I/R, suggesting their use as surrogate biomarkers of endothelial integrity. In light of the importance of the glycocalyx in preserving endothelial cell integrity and its involvement in pathologic conditions, several promising therapeutic strategies to restore the damaged glycocalyx and to attenuate its deleterious consequences have been suggested. This review focuses on alterations of glycocalyx during I/R injury in general (to vital organs in particular), and on maneuvers aimed at glycocalyx recovery during I/R injury.
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With the rapid development of image scanning techniques and visualization software, whole slide imaging (WSI) is becoming a routine diagnostic method. Accelerating clinical diagnosis from pathology images and automating image analysis efficiently and accurately remain significant challenges. Recently, deep learning algorithms have shown great promise in pathology image analysis, such as in tumor region identification, metastasis detection, and patient prognosis. ⋯ In this review, the pathology image segmentation process using deep learning algorithms is described in detail. The goals are to provide quick guidance for implementing deep learning into pathology image analysis and to provide some potential ways of further improving segmentation performance. Although there have been previous reviews on using machine learning methods in digital pathology image analysis, this is the first in-depth review of the applications of deep learning algorithms for segmentation in WSI analysis.