446 research outputs found

    Endocytosis of the ASGP receptor H1 is reduced by mutation of tyrosine-5 but still occurs via coated pits

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    The clustering of plasma membrane receptors in clathrin-coated pits depends on determinants within their cytoplasmic domains. In several cases, individual tyrosine residues were shown to be necessary for rapid internalization. We have mutated the single tyrosine at position 5 in the cytoplasmic domain of the major subunit H1 of the asialoglycoprotein receptor to alanine. Expressed in fibroblasts cells, the mutant protein was accumulated in the plasma membrane, and its rate of internalization was reduced by a factor of four. The residual rate of endocytosis, however, was still significantly higher than that of resident plasma membrane proteins. Upon acidification of the cytoplasm, which specifically inhibits the formation of clathrin-coated vesicles but not uptake of the fluid phase marker Lucifer yellow, residual endocytosis was blocked. By immunoelectron microscopy mutant H1 could be directly demonstrated in coated pits. The fraction of wild-type and mutant H1 present in coated pits as determined by immunogold localization correlated well with the respective rates of internalization. Thus, mutation of tyrosine-5 only partially inactivates recognition of H1 for incorporation into coated pits

    Dynamic interactions of the asialoglycoprotein receptor subunits with coated pits. Enhanced interactions of H2 following association with H1

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    Lateral mobility studies comparing native and mutated membrane proteins, combined with treatments that alter clathrin lattice structure, can measure membrane protein-coated pit interactions in intact cells (Fire, E., Zwart, D., Roth, M. G., and Henis, Y. I. (1991) J. Cell Biol. 115, 1585-1594). We applied this approach to study the interactions of the H1 and H2 human asialoglycoprotein receptor subunits with coated pits. The lateral mobilities of singly expressed and coexpressed H1 and H2B (the H2 species that reaches the cell surface) were measured by fluorescence photobleaching recovery. They were compared with mutant proteins, H1(5A) (Tyr-5 replaced by Ala) and H2(5A) (Phe-5 replaced by Ala). While the mobile fractions of H1, H2B, and their mutants were similar, the lateral diffusion rate (measured by D, the lateral diffusion coefficient) was significantly slower for H1, whether expressed alone or with H2B. Coexpression with H1 reduced D of H2B to that of H1. Disruption of the clathrin lattices by hypertonic medium elevated D of H1, H1(5A), H2B, and H2(5A) to the same final level, without affecting their mobile fractions. Cytosol acidification, which retains altered clathrin lattices attached to the membrane and prevents coated vesicle formation, immobilized part of the H1 molecules, reflecting stable entrapment in "frozen" coated pits. H1(5A), H2B, and H2(5A) were not affected; however, coexpression of H2B with H1 conferred the sensitivity to cytosol acidification on H2B. Our results suggest that H1 lateral mobility is inhibited by dynamic interactions with coated pits in which Tyr-5 is involved. H2B resembles H1(5A) rather than H1, and its interactions with coated pits are weaker; efficient interaction of H2B with coated pits depends on complex formation with H1

    Biochemical characterization of New Delhi metallo-beta-lactamase variants reveals differences in protein stability

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    Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Rhodes Trust (UK); a Clarendon Scholarship; a St Hugh's College W. Louey Scholarship; the Biotechnology & Biological Sciences Research Council (BBSRC); a Royal Society Dorothy Hodgkin Research Fellowship; and the Medical Research Council (MRC)/Canadian Grant G1100135

    Complementary Control of Sensory Adaptation by Two Types of Cortical Interneurons

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    Reliably detecting unexpected sounds is important for environmental awareness and survival. By selectively reducing responses to frequently, but not rarely, occurring sounds, auditory cortical neurons are thought to enhance the brain\u27s ability to detect unexpected events through stimulus-specific adaptation (SSA). The majority of neurons in the primary auditory cortex exhibit SSA, yet little is known about the underlying cortical circuits. We found that two types of cortical interneurons differentially amplify SSA in putative excitatory neurons. Parvalbumin-positive interneurons (PVs) amplify SSA by providing non-specific inhibition: optogenetic suppression of PVs led to an equal increase in responses to frequent and rare tones. In contrast, somatostatin-positive interneurons (SOMs) selectively reduce excitatory responses to frequent tones: suppression of SOMs led to an increase in responses to frequent, but not to rare tones. A mutually coupled excitatory-inhibitory network model accounts for distinct mechanisms by which cortical inhibitory neurons enhance the brain\u27s sensitivity to unexpected sounds

    Duration and compliance with antidepressant treatment in immigrant and native-born populations in Spain: a four year follow-up descriptive study

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    <p>Abstract</p> <p>Background</p> <p>Non-compliance with antidepressant treatment continues to be a complex problem in mental health care. In immigrant populations non-compliance is one of several barriers to adequate management of mental illness; some data suggest greater difficulties in adhering to pharmacological treatment in these groups and an increased risk of therapeutic failure.</p> <p>The aim of this study is to assess differences in the duration and compliance with antidepressant treatment among immigrants and natives in a Spanish health region.</p> <p>Methods</p> <p>Population-based (n=206,603), retrospective cohort study including all subjects prescribed ADT between 2007 and 2009 and recorded in the national pharmacy claims database. Compliance was considered adequate when the duration was longer than 4months and when patients withdrew more than 80% of the packs required.</p> <p>Results</p> <p>5334 subjects (8.5% of them being immigrants) initiated ADT. Half of the immigrants abandoned treatment during the second month (median for natives=3months). Of the immigrants who continued, only 29.5% presented good compliance (compared with 38.8% in natives). The estimated risk of abandoning/ending treatment in the immigrant group compared with the native group, adjusted for age and sex, was 1.28 (95%CI 1.16-1.42).</p> <p>Conclusions</p> <p>In the region under study, immigrants of all origins present higher percentages of early discontinuation of ADT and lower median treatment durations than the native population. Although this is a complex, multifactor situation, the finding of differences between natives and immigrants in the same region suggests the need to investigate the causes in greater depth and to introduce new strategies and interventions in this population group.</p

    The asialoglycoprotein receptor in human hepatocellular carcinomas: its expression on proliferating cells

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    The expression of the asialoglycoprotein receptor (ASGP-R) on human hepatocellular carcinoma (HCC) cells might be exploited to reduce the extrahepatic toxicity of DNA synthesis inhibitors by their conjugation with galactosyl-terminating peptides. In the present study we first assessed the frequency of ASGP-R expression in 60 HCCs. Secondly, we investigated whether the receptor was maintained on the plasma membranes of DNA synthesizing cancer cells. Needle biopsies of HCC were evaluated. Diagnosis and grading of HCC were performed on routine haematoxylin and eosin-stained sections according to Edmondson and Steiner (1953). Thirty-five tumours were grade I and II and were classified as well differentiated, while 25 tumours were grade III and IV and were classified as poorly differentiated. Sections from formalin-fixed, paraffin-embedded samples were incubated, after antigen retrieval, with an anti-ASGP-R monoclonal antibody revealed by secondary biotinylated antibody and streptavidin–biotin–peroxidase–diaminobenzidine reaction. A clear immunolabelling of plasma membranes of HCC cells was observed in 28 out of 35 (80%) well differentiated (grade I and II) and in five out of 25 (20%) poorly differentiated (grade III and IV) HCCs. The presence of the ASGP-R on the surface of DNA synthesizing cancer cells was also investigated after in vitro bromodeoxyuridine (BrdU) labelling of HCC samples by immunohistochemical visualization of both the ASGP-R and incorporated BrdU on the same section. The results obtained clearly demonstrated that DNA synthesizing cancer cells expressed the ASGP-R on their surface. The presence of ASGP-R on cell plasma membrane in the majority of differentiated HCCs and its maintenance on proliferating cells encourages studies in order to restrict the action of the inhibitors of DNA synthesis of HCC cells by their conjugation with galactosyl-terminating carriers internalized through this receptor. © 1999 Cancer Research Campaig

    SiDroForest: a comprehensive forest inventory of Siberian boreal forest investigations including drone-based point clouds, individually labeled trees, synthetically generated tree crowns, and Sentinel-2 labeled image patches

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    The SiDroForest (Siberian drone-mapped forest inventory) data collection is an attempt to remedy the scarcity of forest structure data in the circumboreal region by providing adjusted and labeled tree-level and vegetation plot-level data for machine learning and upscaling purposes. We present datasets of vegetation composition and tree and plot level forest structure for two important vegetation transition zones in Siberia, Russia; the summergreen–evergreen transition zone in Central Yakutia and the tundra–taiga transition zone in Chukotka (NE Siberia). The SiDroForest data collection consists of four datasets that contain different complementary data types that together support in-depth analyses from different perspectives of Siberian Forest plot data for multi-purpose applications. i. Dataset 1 provides unmanned aerial vehicle (UAV)-borne data products covering the vegetation plots surveyed during fieldwork (Kruse et al., 2021, https://doi.org/10.1594/PANGAEA.933263). The dataset includes structure-from-motion (SfM) point clouds and red–green–blue (RGB) and red–green–near-infrared (RGN) orthomosaics. From the orthomosaics, point-cloud products were created such as the digital elevation model (DEM), canopy height model (CHM), digital surface model (DSM) and the digital terrain model (DTM). The point-cloud products provide information on the three-dimensional (3D) structure of the forest at each plot.ii. Dataset 2 contains spatial data in the form of point and polygon shapefiles of 872 individually labeled trees and shrubs that were recorded during fieldwork at the same vegetation plots (van Geffen et al., 2021c, https://doi.org/10.1594/PANGAEA.932821). The dataset contains information on tree height, crown diameter, and species type. These tree and shrub individually labeled point and polygon shapefiles were generated on top of the RGB UVA orthoimages. The individual tree information collected during the expedition such as tree height, crown diameter, and vitality are provided in table format. This dataset can be used to link individual information on trees to the location of the specific tree in the SfM point clouds, providing for example, opportunity to validate the extracted tree height from the first dataset. The dataset provides unique insights into the current state of individual trees and shrubs and allows for monitoring the effects of climate change on these individuals in the future.iii. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch (Larix gmelinii and Larix cajanderi) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, https://doi.org/10.1594/PANGAEA.932795). As machine-learning algorithms need a large dataset to train on, the synthetic dataset was specifically created to be used for machine-learning algorithms to detect Siberian larch species.iv. Dataset 4 contains Sentinel-2 (S-2) Level-2 bottom-of-atmosphere processed labeled image patches with seasonal information and annotated vegetation categories covering the vegetation plots (van Geffen et al., 2021b, https://doi.org/10.1594/PANGAEA.933268). The dataset is created with the aim of providing a small ready-to-use validation and training dataset to be used in various vegetation-related machine-learning tasks. It enhances the data collection as it allows classification of a larger area with the provided vegetation classes. The SiDroForest data collection serves a variety of user communities. The detailed vegetation cover and structure information in the first two datasets are of use for ecological applications, on one hand for summergreen and evergreen needle-leaf forests and also for tundra–taiga ecotones. Datasets 1 and 2 further support the generation and validation of land cover remote-sensing products in radar and optical remote sensing. In addition to providing information on forest structure and vegetation composition of the vegetation plots, the third and fourth datasets are prepared as training and validation data for machine-learning purposes. For example, the synthetic tree-crown dataset is generated from the raw UAV images and optimized to be used in neural networks. Furthermore, the fourth SiDroForest dataset contains S-2 labeled image patches processed to a high standard that provide training data on vegetation class categories for machine-learning classification with JavaScript Object Notation (JSON) labels provided. The SiDroForest data collection adds unique insights into remote hard-to-reach circumboreal forest regions.</p

    An exploratory study on the contribution of graduate entry students personality to the diversity of medical student populations

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    Studies conducted in medical education show that personality influences undergraduate medical students academic and clinical performances and also their career interests. Our aims with this exploratory study were: to assess the contribution of graduate entry students to the diversity of personality in medical student populations; to assess whether eventual differences may be explained by programme structure or student age and sex. We performed a cross-sectional study underpinned by the five-factor model of personality, with students attending three medical schools in Portugal. The five personality dimensions were assessed with the Portuguese version of the NEO-Five Factor Inventory. MANOVA and MANCOVA analyses were performed to clarify the contributions of school, programme structure, age and sex. Student personality dimensions were significantly different between the three medical schools [F (10,1026)  = 3.159, p < .001, [Formula: see text] = 0.03, π = 0.987]. However, taking sex and age into account the differences became non-significant. There were institutional differences in personality dimensions. However, those were primarily accounted for by sex and age effects and not by the medical school attended. Diversifying age and sex of the admitted students will diversify the personality of the medical student population
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