225 research outputs found
Entanglement Wedge Cross Section Growth During Thermalization
Motivated by exploring the thermalization process in relativistic and
non-relativistic holographic field theories after a non-local quench, we
investigate some features in the time evolution of the entanglement wedge cross
section (EWCS). This quantity is a possible holographic dual to some non-local
information measures such as entanglement of purification. In particular, we
focus on the time dependence of EWCS during black hole formation in D+2
dimensional AdS spacetime as well as geometries with Lifshitz and hyperscaling
violating exponents. A combination of analytic and numerical results for large
symmetric strip shaped boundary subregions shows that the scaling of EWCS at
early times only depends on the Lifshitz exponent. In addition, this early
growth regime is followed by a linear growth regime whose velocity depends on
the dimensions of spacetime, the Lifshitz exponent, and the hyperscaling
parameter. This velocity is the same as the entanglement velocity and for
nontrivial dynamical exponent depends on the temperature of the final
equilibrium state.Comment: 22 pages, 7 figures, references added, updated to match the published
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Correction: Product diversity and spectrum of choice in hospital eprescribing systems in England.
There are two errors in the author byline in the XML version of the article. The sixth author’s name is spelled incorrectly. The correct name is: Aziz Sheikh. Jamie Coleman should not be listed as an author. The correct author byline is: Hajar Mozaffar, Robin Williams, Kathrin Cresswell, Zoe Morison, Ann Slee, Aziz Sheikh on behalf of the ePrescribing Programme Team
Predictors of mortality in brain abscess
Objective: Brain abscess carries significant morbidity and mortality. Our objective was to elucidate the clinical presentation of brain abscess and to assess predictors of mortality in these patients.Methods: All patients with a brain abscess presenting to the Aga Khan University Hospital, a tertiary care referral center in Karachi, Pakistan, were studied retrospectively. Statistical analysis involved univariate analysis and a logistic regression model.Results: Among the 66 patients analyzed, a distant metastatic focus of infection was the most commonly identified predisposing factor (29%). Otogenic infection was the commonest contiguous source and sinusitis was noticeably absent. Multiple abscesses were frequent (35%). Streptococci were the most common isolates (39%). Lumbar puncture was performed in 44% and steroids administered in 33%. Treatment was surgical in 58%. Most comatose patients were treated conservatively. Overall mortality was 29%. Univariate analysis identified comatose presentation and identification of a distant focus of infection as predictors of mortality. The logistic regression model, however, identified a distant focus of infection as the only independent predictor.Conclusion: Age greater than 30 years, corticosteroid use, multiple abscesses, performance of lumbar puncture and conservative management had no affect on outcome
QuantiMus: A Machine Learning-Based Approach for High Precision Analysis of Skeletal Muscle Morphology.
Skeletal muscle injury provokes a regenerative response, characterized by the de novo generation of myofibers that are distinguished by central nucleation and re-expression of developmentally restricted genes. In addition to these characteristics, myofiber cross-sectional area (CSA) is widely used to evaluate muscle hypertrophic and regenerative responses. Here, we introduce QuantiMus, a free software program that uses machine learning algorithms to quantify muscle morphology and molecular features with high precision and quick processing-time. The ability of QuantiMus to define and measure myofibers was compared to manual measurement or other automated software programs. QuantiMus rapidly and accurately defined total myofibers and measured CSA with comparable performance but quantified the CSA of centrally-nucleated fibers (CNFs) with greater precision compared to other software. It additionally quantified the fluorescence intensity of individual myofibers of human and mouse muscle, which was used to assess the distribution of myofiber type, based on the myosin heavy chain isoform that was expressed. Furthermore, analysis of entire quadriceps cross-sections of healthy and mdx mice showed that dystrophic muscle had an increased frequency of Evans blue dye+ injured myofibers. QuantiMus also revealed that the proportion of centrally nucleated, regenerating myofibers that express embryonic myosin heavy chain (eMyHC) or neural cell adhesion molecule (NCAM) were increased in dystrophic mice. Our findings reveal that QuantiMus has several advantages over existing software. The unique self-learning capacity of the machine learning algorithms provides superior accuracy and the ability to rapidly interrogate the complete muscle section. These qualities increase rigor and reproducibility by avoiding methods that rely on the sampling of representative areas of a section. This is of particular importance for the analysis of dystrophic muscle given the "patchy" distribution of muscle pathology. QuantiMus is an open source tool, allowing customization to meet investigator-specific needs and provides novel analytical approaches for quantifying muscle morphology
Ischemic stroke subtypes in Pakistan: The Aga Khan University stroke data bank
Objective: Frequency of ischemic stroke subtypes is influenced by ethnic and geographic variables. Our objective was to identify various stroke subtypes and its determinants at a tertiary care hospital.
Methods: We prospectively collected data on ischemic stroke subtypes admitted to The Aga Khan University Hospital in Karachi.
Results: A total of 596 patients were enrolled in 22 months in the Aga Khan Universtiy Stroke Registry. These included 393 patients with Ischemic stroke, 126 patients with intracerebral hemorrhage, 50 patients with subarachnoid hemorrhage and others. The ischemic stroke group was classified according to the TOAST criteria and comprised of lacunar 168/393 (42.7%); large artery atherosclerosis 106/393 (26.9°/x); cardioembolic 24/393 (6.1%); undetermined 80/393 (20.3°!0); and other determined types 15/393 (3.8%). The high proportion of lacunar strokes in our population may be due to high burden of inadequately treated hypertension and diabetes. Clear cut cardioembolic stroke was relatively infrequent in our population. Conclusion: Lacunar stroke is the most common subtype of stroke in our patient population. This is most likely secondary to uncontrolled hypertension (JPMA 53:584;2003)
Thermal Correlators in Holographic Models with Lifshitz scaling
We study finite temperature effects in two distinct holographic models that
exhibit Lifshitz scaling, looking to identify model independent features in the
dual strong coupling physics. We consider the thermodynamics of black branes
and find different low-temperature behavior of the specific heat. Deformation
away from criticality leads to non-trivial temperature dependence of
correlation functions and we study how the characteristic length scale in the
two point function of scalar operators varies as a function of temperature and
deformation parameters.Comment: 28 pages, 8 figures; typos corrected, references added, published
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IgG regulation through FcRn blocking: A novel mechanism for the treatment of myasthenia gravis
The neonatal Fc receptor (FcRn) is an MHC class I–like molecule that is widely distributed in mammalian organs, tissues, and cells. FcRn is critical to maintaining immunoglobulin G (IgG) and albumin levels through rescuing these molecules from lysosomal degradation. IgG autoantibodies are associated with many autoimmune diseases, including myasthenia gravis (MG), a rare neuromuscular autoimmune disease that causes debilitating and, in its generalized form (gMG), potentially life-threatening muscle weakness. IgG autoantibodies are directly pathogenic in MG and target neuromuscular junction proteins, causing neuromuscular transmission failure. Treatment approaches that reduce autoantibody levels, such as therapeutic plasma exchange and intravenous immunoglobulin, have been shown to be effective for gMG patients but are not indicated as ongoing maintenance therapies and can be associated with burdensome side effects. Agents that block FcRn-mediated recycling of IgG represent a rational and promising approach for the treatment of gMG. Blocking FcRn allows targeted reduction of all IgG subtypes without decreasing concentrations of other Ig isotypes; therefore, FcRn blocking could be a safe and effective treatment strategy for a broad population of gMG patients. Several FcRn-blocking antibodies and one antibody Fc fragment have been developed and are currently in various stages of clinical development. This article describes the mechanism of FcRn blockade as a novel approach for IgG-mediated disease therapy and reviews promising clinical data using such FcRn blockers for the treatment of gMG
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