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Involvement of Bruton's tyrosine kinase in FcepsilonRI-dependent mast cell degranulation and cytokine production.
We investigated the role of Bruton's tyrosine kinase (Btk) in FcepsilonRI-dependent activation of mouse mast cells, using xid and btk null mutant mice. Unlike B cell development, mast cell development is apparently normal in these btk mutant mice. However, mast cells derived from these mice exhibited significant abnormalities in FcepsilonRI-dependent function. xid mice primed with anti-dinitrophenyl monoclonal IgE antibody exhibited mildly diminished early-phase and severely blunted late-phase anaphylactic reactions in response to antigen challenge in vivo. Consistent with this finding, cultured mast cells derived from the bone marrow cells of xid or btk null mice exhibited mild impairments in degranulation, and more profound defects in the production of several cytokines, upon FcepsilonRI cross-linking. Moreover, the transcriptional activities of these cytokine genes were severely reduced in FcepsilonRI-stimulated btk mutant mast cells. The specificity of these effects of btk mutations was confirmed by the improvement in the ability of btk mutant mast cells to degranulate and to secrete cytokines after the retroviral transfer of wild-type btk cDNA, but not of vector or kinase-dead btk cDNA. Retroviral transfer of Emt (= Itk/Tsk), Btk's closest relative, also partially improved the ability of btk mutant mast cells to secrete mediators. Taken together, these results demonstrate an important role for Btk in the full expression of FcepsilonRI signal transduction in mast cells
Human Activity Recognition Using Deep Models and Its Analysis from Domain Adaptation Perspective
© 2019, Springer Nature Switzerland AG. Human activity recognition (HAR) is a broad area of research which solves the problem of determining a user’s activity from a set of observations recorded on video or low-level sensors (accelerometer, gyroscope, etc.) HAR has important applications in medical care and entertainment. In this paper, we address sensor-based HAR, because it could be deployed on a smartphone and eliminates the need to use additional equipment. Using machine learning methods for HAR is common. However, such, methods are vulnerable to changes in the domain of training and test data. More specifically, a model trained on data collected by one user loses accuracy when utilised by another user, because of the domain gap (differences in devices and movement pattern results in differences in sensors’ readings.) Despite significant results achieved in HAR, it is not well-investigated from domain adaptation (DA) perspective. In this paper, we implement a CNN-LSTM based architecture along with several classical machine learning methods for HAR and conduct a series of cross-domain tests. The result of this work is a collection of statistics on the performance of our model under DA task. We believe that our findings will serve as a foundation for future research in solving DA problem for HAR
Influence of viscous dissipation and Joule heating on MHD bio-convection flow over a porous wedge in the presence of nanoparticles and gyrotactic microorganisms
Performance enhancement of high order Hahn polynomials using multithreading
Orthogonal polynomials and their moments have significant role in image processing and computer vision field. One of the polynomials is discrete Hahn polynomials (DHaPs), which are used for compression, and feature extraction. However, when the moment order becomes high, they suffer from numerical instability. This paper proposes a fast approach for computing the high orders DHaPs. This work takes advantage of the multithread for the calculation of Hahn polynomials coefficients. To take advantage of the available processing capabilities, independent calculations are divided among threads. The research provides a distribution method to achieve a more balanced processing burden among the threads. The proposed methods are tested for various values of DHaPs parameters, sizes, and different values of threads. In comparison to the unthreaded situation, the results demonstrate an improvement in the processing time which increases as the polynomial size increases, reaching its maximum of 5.8 in the case of polynomial size and order of 8000 × 8000 (matrix size). Furthermore, the trend of continuously raising the number of threads to enhance performance is inconsistent and becomes invalid at some point when the performance improvement falls below the maximum. The number of threads that achieve the highest improvement differs according to the size, being in the range of 8 to 16 threads in 1000 × 1000 matrix size, whereas at 8000 × 8000 case it ranges from 32 to 160 threads
Syncope: experience at a tertiary care hospital in Karachi, Pakistan
Introduction:Our aim was to determine the characteristics of Patients presenting with syncope at a tertiary care hospital in Karachi, Pakistan.Methods: A review of medical records was conducted retrospectively at the Department of Medicine, Aga Khan University Hospital, Karachi. Patients aged 16 and above, admitted from January 2000 to December 2005 with the diagnosis of syncope made by the attending physician were included.Results:A total of 269 Patients were included (75% males, mean age: 57.4 years). Neurogenic (vasovagal) syncope was the most common cause (47%), followed by cardiogenic syncope (18%) and orthostatic syncope (9%). A total of 24% were discharged undiagnosed. Twenty Patients (7.4%) did not have any prodrome. Common prodromal symptoms included dizziness (61%), sweating (25%), palpitations (19%), nausea/vomiting (19%) and visual symptoms (17%). The distribution of symptoms according to cause of syncope revealed only breathlessness to be significantly associated with cardiogenic syncope (p = 0.002). Most Patients with cardiogenic syncope were aged above 40 (98%, p \u3c 0.001), had coronary artery disease (72%, p \u3c 0.001) and abnormal electrocardiogram at presentation (92%, p \u3c 0.001).Conclusion:Despite differences in burden of diseases, our findings were similar to those of published syncope literature. Further studies are needed to develop a protocol to expedite the evaluation and limit the work-up and admission in low-risk Patients
Trapped in the prison of the mind: notions of climate-induced (im)mobility decision-making and wellbeing from an urban informal settlement in Bangladesh
The concept of Trapped Populations has until date mainly referred to people ‘trapped’ in environmentally high-risk rural areas due to economic constraints. This article attempts to widen our understanding of the concept by investigating climate-induced socio-psychological immobility and its link to Internally Displaced People’s (IDPs) wellbeing in a slum of Dhaka. People migrated here due to environmental changes back on Bhola Island and named the settlement Bhola Slum after their home. In this way, many found themselves ‘immobile’ after having been mobile—unable to move back home, and unable to move to other parts of Dhaka, Bangladesh, or beyond. The analysis incorporates the emotional and psychosocial aspects of the diverse immobility states. Mind and emotion are vital to better understand people’s (im)mobility decision-making and wellbeing status. The study applies an innovative and interdisciplinary methodological approach combining Q-methodology and discourse analysis (DA). This mixed-method illustrates a replicable approach to capture the complex state of climate-induced (im)mobility and its interlinkages to people’s wellbeing. People reported facing non-economic losses due to the move, such as identity, honour, sense of belonging and mental health. These psychosocial processes helped explain why some people ended up ‘trapped’ or immobile. The psychosocial constraints paralysed them mentally, as well as geographically. More empirical evidence on how climate change influences people’s wellbeing and mental health will be important to provide us with insights in how to best support vulnerable people having faced climatic impacts, and build more sustainable climate policy frameworks
Are prescribing doctors sensitive to the price that their patients have to pay in the Spanish National Health System?
Future therapeutic targets in rheumatoid arthritis?
Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by persistent joint inflammation. Without adequate treatment, patients with RA will develop joint deformity and progressive functional impairment. With the implementation of treat-to-target strategies and availability of biologic therapies, the outcomes for patients with RA have significantly improved. However, the unmet need in the treatment of RA remains high as some patients do not respond sufficiently to the currently available agents, remission is not always achieved and refractory disease is not uncommon. With better understanding of the pathophysiology of RA, new therapeutic approaches are emerging. Apart from more selective Janus kinase inhibition, there is a great interest in the granulocyte macrophage-colony stimulating factor pathway, Bruton's tyrosine kinase pathway, phosphoinositide-3-kinase pathway, neural stimulation and dendritic cell-based therapeutics. In this review, we will discuss the therapeutic potential of these novel approaches
Measurement of the branching fraction and CP content for the decay B(0) -> D(*+)D(*-)
This is the pre-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2002 APS.We report a measurement of the branching fraction of the decay B0→D*+D*- and of the CP-odd component of its final state using the BABAR detector. With data corresponding to an integrated luminosity of 20.4  fb-1 collected at the Υ(4S) resonance during 1999–2000, we have reconstructed 38 candidate signal events in the mode B0→D*+D*- with an estimated background of 6.2±0.5 events. From these events, we determine the branching fraction to be B(B0→D*+D*-)=[8.3±1.6(stat)±1.2(syst)]×10-4. The measured CP-odd fraction of the final state is 0.22±0.18(stat)±0.03(syst).This work is supported by DOE and NSF (USA), NSERC (Canada), IHEP (China), CEA and CNRS-IN2P3 (France), BMBF (Germany), INFN (Italy), NFR (Norway), MIST (Russia), and PPARC (United Kingdom). Individuals have received support from the A.P. Sloan Foundation, Research Corporation, and Alexander von Humboldt Foundation
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