It has previously been shown that the large increase in GH-binding capacity of mouse liver microsomes during pregnancy is due largely to an increase in the amount of GH-binding protein (GHBP), with a more modest increase in GH receptor (GHR). Here we show that mouse liver GHBP is predominantly present as a membrane-associated protein structurally distinct from the soluble form of GHBP present in serum. Liver GHBP is associated with both intracellular membranes and the plasma membrane. Membrane-associated GHBP and soluble GHBP appear to be identical polypeptides distinguished by the addition of different N-glycans to asparagine residues. The pattern of release of GHBP from membranes by various treatments indicates that GHBP associates with membranes through noncovalent interactions with one or more membrane protein, but not with GHR. Covalent crosslinking provides evidence for several GHBP-associated membrane polypeptides, with molecular masses ranging from 58 kDa to over 200 kDa.These studies in the mouse and similar studies in the rat suggest that GHBP is an important cell-surface receptor for GH in the liver of these species. We postulate that an arginine-glycine-aspartic acid sequence found on rat and mouse GHBP but absent in other species is responsible for the association of GHBP with the plasma membrane by binding to one or more integrins on the surface of liver cells.
Background: COVID-19 had spread quickly among the population and it has caused considerable morbidity and mortality in more than 200 countries worldwide, which became a public health emergency of international concern. This study was to investigate whether some clinical features, laboratory tests and imaging findings at the initial diagnosis of COVID-19 infection affect the number of days that nucleic acids turned negative (Dnegative) during hospitalization.Methods: The Mann-Whitney U test and one-way analysis of variance (ANOVA) were used to examine the difference in Dnegative between clinical features, laboratory tests and imaging findings. ANOVA was also applied to differentiate between the age, Dnegative, and imaging findings among different clinical types. Multiple linear regression (MLR) analysis was used to quantify the effect of clinical characteristics, imaging findings and Dnegative, and establish regression equation.Results: The Dnegative of COVID-19 patients who had comorbidity was significantly larger than that of those without (33.35 ± 14.63, 27.79 ± 12.89, P = 0.007). Common patients were younger than severe and critically severe patients (P <0.001, P = 0.003). As compared to common patients, severe patients had larger Dnegative (P <0.001), and the ratio of ground-glass opacity (RGGO), consolidation (RC), and the sum of GGO and consolidation (RSUM) of lesions on chest CT increased significantly (all P <0.001). The MLR analysis equation was y (Dnegative)= 22.35 + 0.36 × RSUM.Conclusions: The severe COVID-19 patients were older than common patients, and their Dnegative were larger as well. The chest CT findings at initial diagnosis (including RGGO, RC, and RSUM) could be used to differentially diagnose the common and severe patients, and had certain potential ability in predicting Dnegative.Trial registration: Retrospectively registered.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.