Medical University of South Carolina

About: Medical University of South Carolina is a education organization based out in Charleston, South Carolina, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 23436 authors who have published 45440 publications receiving 1769397 citations. The organization is also known as: MUSC & Medical College of the State of South Carolina.

Towards an understanding of the psychological impact of natural disasters : an application of the conservation resources stress model

Abstract: The current study employed the Conservation of Resources (COR) stress model as a template for understanding short-term adjustment following a natural disaster (Hobfoll, 1989). The following three hypotheses were supported: resource loss was positively related to psychological distress; resource loss was relatively more important in predicting psychological distress than personal characteristics and coping behavior; and, resource loss constitutes a risk factor for the development of clinically significant psychological distress. The theoretical importance of the current findings is discussed, particularly the tendency within disaster literature to confound crisis experiences (e.g., terror) with resource loss experiences (e.g., loss of possessions, loss of social support) when defining degree of disaster exposure. Also, the practical importance of considering resource loss in planning intervention services is highlighted.

Structural-mechanical characterization of nanoparticle exosomes in human saliva, using correlative AFM, FESEM, and force spectroscopy.

Abstract: All living systems contain naturally occurring nanoparticles with unique structural, biochemical, and mechanical characteristics. Specifically, human saliva exosomes secreted by normal cells into saliva via exocytosis are novel biomarkers showing tumor-antigen enrichment during oral cancer. Here we show the substructure of single human saliva exosomes, using a new ultrasensitive low force atomic force microscopy (AFM) exhibiting substructural organization unresolvable in electron microscopy. We correlate the data with field emission scanning electron microscopy (FESEM) and AFM images to interpret the nanoscale structures of exosomes under varying forces. Single exosomes reveal reversible mechanical deformation displaying distinct elastic, 70-100 nm trilobed membrane with substructures carrying specific transmembrane receptors. Further, we imaged and investigated, using force spectroscopy with antiCD63 IgG functionalized AFM tips, highly specific and sensitive detection of antigenCD63, potentially useful cancer markers on individual exosomes. The quantitative nanoscale morphological, biomechanical, and surface biomolecular properties of single saliva exosomes are critical for the applications of exosomes for cancer diagnosis and as a model for developing new cell delivery systems.

The smallest stroke: Occlusion of one penetrating vessel leads to infarction and a cognitive deficit

Abstract: Microinfarctions are present in the aged and injured human brain. Their clinical relevance is controversial, with postulated sequelae ranging from cognitive sparing to vascular dementia. To address the consequences of microinfarcts, we used controlled optical methods to create occlusions of individual penetrating arterioles or venules in rat cortex. Single microinfarcts, targeted to encompass all or part of a cortical column, impaired performance in a macrovibrissa-based behavioral task. Furthermore, the targeting of multiple vessels resulted in tissue damage that coalesced across cortex, even though the intervening penetrating vessels were acutely patent. Post-occlusion administration of memantine, a glutamate receptor antagonist that reduces cognitive decline in Alzheimer's disease, ameliorated tissue damage and perceptual deficits. Collectively, these data imply that microinfarcts likely contribute to cognitive decline. Strategies that have received limited success in the treatment of ischemic injury, which include therapeutics against excitotoxicity, may be successful against the progressive nature of vascular dementia.

Nanostructural and Transcriptomic Analyses of Human Saliva Derived Exosomes

Abstract: Author(s): Palanisamy, Viswanathan; Sharma, Shivani; Deshpande, Amit; Zhou, Hui; Gimzewski, James; Wong, David T | Abstract: BackgroundExosomes, derived from endocytic membrane vesicles are thought to participate in cell-cell communication and protein and RNA delivery. They are ubiquitous in most body fluids (breast milk, saliva, blood, urine, malignant ascites, amniotic, bronchoalveolar lavage, and synovial fluids). In particular, exosomes secreted in human saliva contain proteins and nucleic acids that could be exploited for diagnostic purposes. To investigate this potential use, we isolated exosomes from human saliva and characterized their structural and transcriptome contents.MethodologyExosomes were purified by differential ultracentrifugation and identified by immunoelectron microscopy (EM), flow cytometry, and Western blot with CD63 and Alix antibodies. We then described the morphology, shape, size distribution, and density using atomic force microscopy (AFM). Microarray analysis revealed that 509 mRNA core transcripts are relatively stable and present in the exosomes. Exosomal mRNA stability was determined by detergent lysis with RNase A treatment. In vitro, fluorescently labeled saliva exosomes could communicate with human keratinocytes, transferring their genetic information to human oral keratinocytes to alter gene expression at a new location.ConclusionOur findings are consistent with the hypothesis that exosomes shuttle RNA between cells and that the RNAs present in the exosomes may be a possible resource for disease diagnostics.

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging

Abstract: Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within the medical community, and specifically within the domain of cardiovascular diseases. In this review, we present a brief overview of ML methodologies that are used for the construction of inferential and predictive data-driven models. We highlight several domains of ML application such as echocardiography, electrocardiography, and recently developed non-invasive imaging modalities such as coronary artery calcium scoring and coronary computed tomography angiography. We conclude by reviewing the limitations associated with contemporary application of ML algorithms within the cardiovascular disease field.