Inclusion body myositis: therapeutic approaches.

The idiopathic inflammatory myopathies are a heterogeneous group of diseases that include dermatomyositis (DM), polymyositis (PM), inclusion body myositis (IBM) and other less common myopathies. These are clinically and histopathologically distinct diseases with many shared clinical features. IBM, the most commonly acquired inflammatory muscle disease occurs in individuals aged over 50 years, and is characterized by slowly progressive muscle weakness and atrophy affecting proximal and distal muscle groups, often asymmetrically. Unlike DM and PM, IBM is typically refractory to immunotherapy. Although corticosteroids have not been tested in randomized controlled trials, the general consensus is that they are not efficacious. There is some suggestion that intravenous immunoglobulin slows disease progression, but its long-term effectiveness is unclear. The evidence for other immunosuppressive therapies has been derived mainly from case reports and open studies and the results are discouraging. Only a few clinical trials have been conducted on IBM, making it difficult to provide clear recommendations for treatment. Moreover, IBM is a slowly progressive disease so assessment of treatment efficacy is problematic due to the longer-duration trials needed to determine treatment effects. Newer therapies may be promising, but further investigation to document efficacy would be expensive given the aforementioned need for longer trials. In this review, various treatments that have been employed in IBM will be discussed even though none of the interventions has sufficient evidence to support its routine use

Towards Explainability of UAV-Based Convolutional Neural Networks for Object Classification

f autonomous systems using trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR), a new NASA Convergent Aeronautical Solutions (CAS) Project. One critical research element of ATTRACTOR is explainability of the decision-making across relevant subsystems of an autonomous system. The ability to explain why an autonomous system makes a decision is needed to establish a basis of trustworthiness to safely complete a mission. Convolutional Neural Networks (CNNs) are popular visual object classifiers that have achieved high levels of classification performances without clear insight into the mechanisms of the internal layers and features. To explore the explainability of the internal components of CNNs, we reviewed three feature visualization methods in a layer-by-layer approach using aviation related images as inputs. Our approach to this is to analyze the key components of a classification event in order to generate component labels for features of the classified image at different layers of depths. For example, an airplane has wings, engines, and landing gear. These could possibly be identified somewhere in the hidden layers from the classification and these descriptive labels could be provided to a human or machine teammate while conducting a shared mission and to engender trust. Each descriptive feature may also be decomposed to a combination of primitives such as shapes and lines. We expect that knowing the combination of shapes and parts that create a classification will enable trust in the system and insight into creating better structures for the CNN

Monte Carlo simulation of the classical two-dimensional one component plasma

Monte Carlo simulation, lattice dynamics in the harmonic approximation, and solution of the hypernetted chain equation were used to study the classical two-dimensional one component plasma. The system consists of a single species of charged particles immersed in a uniform neutralizing background. The particles interact via a l/r potential, where r is the two dimensional separation. Equations of state were calculated for both the liquid and solid phases. Results of calculation of the thermodynamic functions and one and two particle correlation functions are presented

Monopole Operators in U(1)U(1) Chern-Simons-Matter Theories

We study monopole operators at the infrared fixed points of $U(1)$ Chern-Simons-matter theories (QED$_3$, scalar QED$_3$, ${\cal N} =1$ SQED$_3$, and ${\cal N} = 2$ SQED$_3$) with $N$ matter flavors and Chern-Simons level $k$. We work in the limit where both $N$ and $k$ are taken to be large with $\kappa = k/N$ fixed. In this limit, we extract information about the low-lying spectrum of monopole operators from evaluating the $S^2 \times S^1$ partition function in the sector where the $S^2$ is threaded by magnetic flux $4 \pi q$. At leading order in $N$, we find a large number of monopole operators with equal scaling dimensions and a wide range of spins and flavor symmetry irreducible representations. In two simple cases, we deduce how the degeneracy in the scaling dimensions is broken by the $1/N$ corrections. For QED$_3$ at $\kappa=0$, we provide conformal bootstrap evidence that this near-degeneracy is in fact maintained to small values of $N$. For ${\cal N} = 2$ SQED$_3$, we find that the lowest dimension monopole operator is generically non-BPS.Comment: 52 pages plus appendices, 9 figures, v2: minor correction

Bootstrapping O(N)O(N) Vector Models with Four Supercharges in 3≤d≤43 \leq d \leq4

We analyze the conformal bootstrap constraints in theories with four supercharges and a global $O(N) \times U(1)$ flavor symmetry in $3 \leq d \leq 4$ dimensions. In particular, we consider the 4-point function of $O(N)$-fundamental chiral operators $Z_i$ that have no chiral primary in the $O(N)$-singlet sector of their OPE. We find features in our numerical bounds that nearly coincide with the theory of $N+1$ chiral super-fields with superpotential $W = X \sum_{i=1}^N Z_i^2$, as well as general bounds on SCFTs where $\sum_{i=1}^N Z_i^2$ vanishes in the chiral ring.Comment: 25 pages, 8 figure

A review of school approaches to increasing pupil resilience

The purpose of this review is to evaluate the literature on whole school approaches to increasing resilience in pupils. This is pertinent with the increase in children and young people’s mental health needs creating extra pressure on schools to foster young people’s ability to withstand stress and adversity. Whilst previous reviews have considered the ways in which schools support their pupils, the extent to which resilience has been reliably measured has varied. Recently, several validated resilience measures have been developed which allows for potentially more robust research to take place. This systematic review therefore summarises and critiques the literature exploring whole school approaches to resilience development only where a validated measure has been used. Eleven studies were reviewed and demonstrate that there is a trend between school factors and pupil resilience. The importance of supportive relationships with both peers and staff in school is highlighted in several studies as well as the positive effect of including a robust health promoting school’s agenda situated within local communities. However, the number of limitations identified within the current literature suggests that this review is not able to offer clear recommendations to schools. This review will, however, be helpful to schools, local authorities and the government in allowing them to take more of a critical stance in understanding resilience within a school context

Ion laser plasmas

The typical noble gas ion laser plasma consists of a high-current-density glow discharge in a noble gas, in the presence of a magnetic field. Typical CW plasma conditions are current densities of 100 to 2000 A/cm^2, tube diameters of 1 to 10 mm, filling pressures of 0.1 to 1.0 torr, and an axial magnetic field of the order of 1000 G. Under these conditions the typical fractional ionization is about 2 percent and the electron temperature between 2 and 4 eV. Pulsed ion lasers typically use higher current densities and lower operating pressures. This paper discusses the properties of ion laser plasmas, in terms of both their external discharge parameters and their internal ion and excited state densities. The effect these properties have on laser operation is explained. Many interesting plasma effects, which are important in ion lasers, are given attention. Among these are discharge nonuniformity near tube constrictions, extremely high ion radial drift velocities, wall losses intermediate between ambipolar diffusion and free fall, gas pumping effects, and radiation trapping. The current status of ion laser technology is briefly reviewed

The Supreme Court Confirmation Process and Its Implications

In recent history, there has been a trend of increasing partisan polarization throughout most of the American political system. Some of the impacts of this polarization are obvious; however, there is reason to believe that we miss some of the indirect effects of polarization. Accompanying the trend of increased polarization has been an increase in the contentiousness of the Supreme Court confirmation process. I believe that these two trends are related. Furthermore, I argue that these trends have an impact on judicial behavior. This is an issue worth exploring, since the Supreme Court is the most isolated branch of the federal government. The Constitution structured the Supreme Court to ensure that it was as isolated as possible from short-term political pressures and interests. This study attempts to show how it may be possible that those goals are no longer being fully achieved. My first hypothesis in this study is that increases in partisan polarization are a direct cause of the increase in the level of contention during the confirmation process. I then hypothesize that the more contention a justice faces during his or her confirmation process, the more ideologically extreme that justice will then vote on the bench. This means that a nominee appointed by a Republican president will tend to vote even more conservatively than was anticipated following a contentious confirmation process, and vice versa for Democratic appointees. In order to test these hypotheses, I developed a data set for every Supreme Court nominee dating back to President Franklin D. Roosevelt¿s appointments (1937). With this data set, I ran a series of regression models to analyze these relationships. Statistically speaking, the results support my first hypothesis in a fairly robust manner. My regression results for my second hypothesis indicate that the trend I am looking for is present for Republican nominees. For Democratic nominees, the impacts are less robust. Nonetheless, as the results will show, contention during the confirmation process does seem to have some impact on judicial behavior. Following my quantitative analysis, I analyze a series of case studies. These case studies serve to provide tangible examples of these statistical trends as well as to explore what else may be going on during the confirmation process and subsequent judicial decision-making. I use Justices Stevens, Rehnquist, and Alito as the subjects for these case studies. These cases will show that the trends described above do seem to be identifiable at the level of an individual case. These studies further help to indicate other potential impacts on judicial behavior. For example, following Justice Rehnquist¿s move from Associate to Chief Justice, we see a marked change in his behavior. Overall, this study serves as a means of analyzing some of the more indirect impacts of partisan polarization in modern politics. Further, the study offers a means of exploring some of the possible constraints (both conscious and subconscious) that Supreme Court justices may feel while they decide how to cast a vote in a particular case. Given the wide-reaching implications of Supreme Court decisions, it is important to try to grasp a full view of how these decisions are made

A plug-and-play approach to antibody-based therapeutics via a chemoselective dual click strategy.

Although recent methods for the engineering of antibody-drug conjugates (ADCs) have gone some way to addressing the challenging issues of ADC construction, significant hurdles still remain. There is clear demand for the construction of novel ADC platforms that offer greater stability, homogeneity and flexibility. Here we describe a significant step towards a platform for next-generation antibody-based therapeutics by providing constructs that combine site-specific modification, exceptional versatility and high stability, with retention of antibody binding and structure post-modification. The relevance of the work in a biological context is also demonstrated in a cytotoxicity assay and a cell internalization study with HER2-positive and -negative breast cancer cell lines