218 research outputs found

    Emerin and inherited disease

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    Thesis (M. Eng.)--Harvard-MIT Division of Health Sciences and Technology, 2004.Includes bibliographical references (p. 54-55).(cont.) nucleus and at the nuclear surface.Mutations in the lamin A/C gene (Lmna) and the lamin-associated protein emerin gene (EM) cause a variety of human diseases including Emery-Dreifuss muscular dystrophy, dilated cardiomyopathy, familial partial lipodystrophy, Charcot-Marie-Tooth Neuropathy and Hutchinson-Gilford progeria syndrome. The molecular mechanisms underlying the varied phenotypes are unknown, and both a mechanical stress hypothesis and an altered gene expression hypothesis have been proposed to explain the tissue specific effects observed in laminopathies. To investigate the role of emerin in mechanotransduction, lamin A/C deficient (Lmna⁻/⁻) fibroblasts, and emerin deficient (EM⁻/y) fibroblasts were studied for nuclear mechanical properties, cytoskeletal stiffness, and mechanical strain-induced signaling. EM⁻/y fibroblasts exhibited similar cell sensitivity, nuclear and cytoskeletal properties compared to wild type cells under stress and strain. Interestingly, both Lmna⁻/⁻ and EM⁻/y fibroblasts had impaired mechanotransduction, characterized by attenuated expression of the mechanosensitive genes egr-1, iex-1, and txnip in response to mechanical stimulation. In addition, NF-rB signaling appeared disturbed in Lmna⁻/⁻ cells, but normal in EM⁻/y fibroblasts. The relationship between changes in cytoskeletal stiffness recently discovered in Lmna⁻/⁻ cells and nuclear mechanics under strain was explored using a computational finite elemental model. Analysis of the several models using variations in material properties and cell geometry revealed that nuclear shape, material properties of the cytoskeleton and nucleus, as well as the size and location of strain application on the cell are important parameters in determining the magnitude of stress and strain within theby Janet Hsiao.M.Eng

    Explanation Strategies for Image Classification in Humans vs. Current Explainable AI

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    Explainable AI (XAI) methods provide explanations of AI models, but our understanding of how they compare with human explanations remains limited. In image classification, we found that humans adopted more explorative attention strategies for explanation than the classification task itself. Two representative explanation strategies were identified through clustering: One involved focused visual scanning on foreground objects with more conceptual explanations diagnostic for inferring class labels, whereas the other involved explorative scanning with more visual explanations rated higher for effectiveness. Interestingly, XAI saliency-map explanations had the highest similarity to the explorative attention strategy in humans, and explanations highlighting discriminative features from invoking observable causality through perturbation had higher similarity to human strategies than those highlighting internal features associated with higher class score. Thus, humans differ in information and strategy use for explanations, and XAI methods that highlight features informing observable causality match better with human explanations, potentially more accessible to users

    Predicting an observer's task using multi-fixation pattern analysis

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    Since Yarbus's seminal work in 1965, vision scientists have argued that people's eye movement patterns differ depending upon their task. This suggests that we may be able to infer a person's task (or mental state) from their eye movements alone. Recently, this was attempted by Greene et al. [2012] in a Yarbus-like replication study; however, they were unable to successfully predict the task given to their observer. We reanalyze their data, and show that by using more powerful algorithms it is possible to predict the observer's task. We also used our algorithms to infer the image being viewed by an observer and their identity. More generally, we show how off-the-shelf algorithms from machine learning can be used to make inferences from an observer's eye movements, using an approach we call Multi-Fixation Pattern Analysis (MFPA)

    Abnormal nuclear shape and impaired mechanotransduction in emerin-deficient cells

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    Emery-Dreifuss muscular dystrophy can be caused by mutations in the nuclear envelope proteins lamin A/C and emerin. We recently demonstrated that A-type lamin-deficient cells have impaired nuclear mechanics and altered mechanotransduction, suggesting two potential disease mechanisms (Lammerding, J., P.C. Schulze, T. Takahashi, S. Kozlov, T. Sullivan, R.D. Kamm, C.L. Stewart, and R.T. Lee. 2004. J. Clin. Invest. 113:370–378). Here, we examined the function of emerin on nuclear mechanics and strain-induced signaling. Emerin-deficient mouse embryo fibroblasts have abnormal nuclear shape, but in contrast to A-type lamin-deficient cells, exhibit nuclear deformations comparable to wild-type cells in cellular strain experiments, and the integrity of emerin-deficient nuclear envelopes appeared normal in a nuclear microinjection assay. Interestingly, expression of mechanosensitive genes in response to mechanical strain was impaired in emerin-deficient cells, and prolonged mechanical stimulation increased apoptosis in emerin-deficient cells. Thus, emerin-deficient mouse embryo fibroblasts have apparently normal nuclear mechanics but impaired expression of mechanosensitive genes in response to strain, suggesting that emerin mutations may act through altered transcriptional regulation and not by increasing nuclear fragility

    Cultural orientation of self-bias in perceptual matching

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    This work was supported by grants from the Economic and Social Research Council (ES/K013424/1), the National Natural Science Foundation of China (31371017), and the Research Grants Council of Hong Kong (HKU758412H)Peer reviewedPublisher PD
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