Effect of pulsed methylprednisolone on pain, in patients with HTLV-1-associated myelopathy

HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is an immune mediated myelopathy caused by the human T-lymphotropic virus type 1 (HTLV-1). The efficacy of treatments used for patients with HAM/TSP is uncertain. The aim of this study is to document the efficacy of pulsed methylprednisolone in patients with HAM/TSP. Data from an open cohort of 26 patients with HAM/TSP was retrospectively analysed. 1g IV methylprednisolone was infused on three consecutive days. The outcomes were pain, gait, urinary frequency and nocturia, a range of inflammatory markers and HTLV-1 proviral load. Treatment was well tolerated in all but one patient. Significant improvements in pain were: observed immediately, unrelated to duration of disease and maintained for three months. Improvement in gait was only seen on Day 3 of treatment. Baseline cytokine concentrations did not correlate to baseline pain or gait impairment but a decrease in tumour necrosis factor-alpha (TNF-α) concentration after pulsed methylprednisolone was associated with improvements in both. Until compared with placebo, treatment with pulsed methylprednisolone should be offered to patients with HAM/TSP for the treatment of pain present despite regular analgesia

ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches

Adversarial patches are optimized contiguous pixel blocks in an input image that cause a machine-learning model to misclassify it. However, their optimization is computationally demanding, and requires careful hyperparameter tuning, potentially leading to suboptimal robustness evaluations. To overcome these issues, we propose ImageNet-Patch, a dataset to benchmark machine-learning models against adversarial patches. The dataset is built by first optimizing a set of adversarial patches against an ensemble of models, using a state-of-the-art attack that creates transferable patches. The corresponding patches are then randomly rotated and translated, and finally applied to the ImageNet data. We use ImageNet-Patch to benchmark the robustness of 127 models against patch attacks, and also validate the effectiveness of the given patches in the physical domain (i.e., by printing and applying them to real-world objects). We conclude by discussing how our dataset could be used as a benchmark for robustness, and how our methodology can be generalized to other domains. We open source our dataset and evaluation code at https://github.com/pralab/ImageNet-Patch

Hypomethylation of FAM63B in bipolar disorder patients

Bipolar disorder (BD) and schizophrenia (SZ) are known to share common genetic and psychosocial risk factors. A recent epigenome-wide association study performed on blood samples from SZ patients found significant hypomethylation of FAM63B in exon 9. Here, we used iPLEX-based methylation analysis to investigate two CpG sites in FAM63B in blood samples from 459 BD cases and 268 controls. Both sites were significantly hypomethylated in BD cases (lowest p value = 3.94 × 10−8). The methylation levels at the two sites were correlated, and no strong correlation was found with nearby single nucleotide polymorphisms (SNPs), suggesting that methylation differences at these sites are not readably picked up by genome-wide association studies. Overall, FAM63B hypomethylation was found in BD patients, thus replicating the initial finding in SZ patients. This study suggests that FAM63B is a shared epigenetic risk gene for the two disorders

Exact solutions to the focusing nonlinear Schrodinger equation

A method is given to construct globally analytic (in space and time) exact solutions to the focusing cubic nonlinear Schrodinger equation on the line. An explicit formula and its equivalents are presented to express such exact solutions in a compact form in terms of matrix exponentials. Such exact solutions can alternatively be written explicitly as algebraic combinations of exponential, trigonometric, and polynomial functions of the spatial and temporal coordinates.Comment: 60 pages, 18 figure

Discordant associations of educational attainment with ASD and ADHD implicate a polygenic form of pleiotropy.

Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are complex co-occurring neurodevelopmental conditions. Their genetic architectures reveal striking similarities but also differences, including strong, discordant polygenic associations with educational attainment (EA). To study genetic mechanisms that present as ASD-related positive and ADHD-related negative genetic correlations with EA, we carry out multivariable regression analyses using genome-wide summary statistics (N = 10,610-766,345). Our results show that EA-related genetic variation is shared across ASD and ADHD architectures, involving identical marker alleles. However, the polygenic association profile with EA, across shared marker alleles, is discordant for ASD versus ADHD risk, indicating independent effects. At the single-variant level, our results suggest either biological pleiotropy or co-localisation of different risk variants, implicating MIR19A/19B microRNA mechanisms. At the polygenic level, they point to a polygenic form of pleiotropy that contributes to the detectable genome-wide correlation between ASD and ADHD and is consistent with effect cancellation across EA-related regions

Risk of schizophrenia in relation to parental origin and genome-wide divergence

Background. Second-generation immigrants have an increased risk of schizophrenia, a finding that still lacks a satisfactory explanation. Various operational definitions of second-generation immigrants have been used, including foreign parental country of birth. However, with increasing global migration, it is not clear that parental country of birth necessarily is informative with regard to ethnicity. We compare two independently collected measures of parental foreign ethnicity, parental foreign country of birth versus genetic divergence, based on genome-wide genotypic data, to access which measure most efficiently captures the increased risk of schizophrenia among second-generation immigrants residing in Denmark. Method. A case-control study covering all children born in Denmark since 1981 included 892 cases of schizophrenia and 883 matched controls. Genetic divergence was assessed using principal component analyses of the genotypic data. Independently, parental foreign country of birth was assessed using information recorded prospectively in the Danish Civil Registration System. We compared incidence rate ratios of schizophrenia associated with these two independently collected measures of parental foreign ethnicity. Results. People with foreign-born parents had a significantly increased risk of schizophrenia [relative risk (RR) 1.94 (95% confidence intervals (CI) 1.41-2.65)]. Genetically divergent persons also had a significant increased risk [RR 2.43 ( 95% CI 1.55-3.82)]. Mutual adjustment of parental foreign country of birth and genetic divergence showed no difference between these measures with regard to their potential impact on the results. Conclusions. In terms of RR of schizophrenia, genetic divergence and parental foreign country of birth are interchangeable entities, and both entities have validity with regard to identifying second-generation immigrants

Electrostatic Control of the Thermoelectric Figure of Merit in Ion-Gated Nanotransistors

Semiconductor nanostructures have raised much hope for the implementation of high-performance thermoelectric generators. Indeed, they are expected to make available reduced thermal conductivity without a heavy trade-off on electrical conductivity, a key requirement to optimize the thermoelectric figure of merit. Here, a novel nanodevice architecture is presented in which ionic liquids are employed as thermally-insulating gate dielectrics. These devices allow the field-effect control of electrical transport in suspended semiconducting nanowires in which thermal conductivity can be simultaneously measured using an all-electrical setup. The resulting experimental data on electrical and thermal transport properties taken on individual nanodevices can be combined to extract ZT, guide device optimization and dynamical tuning of the thermoelectric properties