Web-based therapy for hemianopic alexia is syndrome-specific

Rehabilitation studies rarely test the specificity of an intervention by using a control group who are matched to the therapy group in terms of baseline impairment, but who do not have the same causative syndrome. In this study, we tested the specificity of an eye movement therapy for a common, acquired reading disorder called hemianopic alexia, by comparing hemianopic participants with slow text reading, to age and reading speed matched controls without hemianopia. The study was carried out using an online therapy programme called ‘Read-Right’ that contains validated tests of the visual field and text reading speed, as well as an eye movement therapy: laterally scrolling text. 201 self-selected participants completed at least 5 h of online therapy. After excluding those with reading speeds incompatible with hemianopic alexia and those with bilateral abnormalities on their visual field test, we were left with 105 who were then classified into one of three groups depending on their visual field: (1) right-sided hemianopia (n=47); (2) left-sided hemianopia (n=36); (3) no hemianopia (n=22, control group). The three groups did not differ in terms of baseline text reading speed, but they were all significantly slower than expected based on normative data from the same age range. A repeated-measures analysis of variance showed a significant therapy by group interaction (p=0.039). Post hoc, paired t tests revealed that this was driven by reading speed improvements for the right-sided and left-sided hemianopic alexic groups but not the controls. This result demonstrates that a clinically validated therapy for hemianopic alexia improves text reading speed in hemianopic patients but not in participants matched for slow text reading but without hemianopia. This adds weight to the hypothesis that eye movement therapies are syndrome-specific. It also demonstrates an advantage of using web-based vehicles to deliver syndrome-specific therapies that can be accessed by patients worldwide

Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in 'hidden' physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups

<em>Enterococcus hirae</em> bacteremia associated with perinephric collection and renal abscesses in a diabetic woman

\ua9 The Author(s) 2022. Published by Oxford University Press. Enterococcus hirae infection accounts for about 1% of all enterococcal infections. This number is likely to be underestimated because of inadequate identification. Human infection due to E. hirae is rarely reported. We present the case of a young woman with diabetes mellitus who developed symptoms of pyelonephritis and diabetic ketoacidosis. Renal computed tomography scan revealed the presence of subcapsular perinephric collection and renal abscesses. Her blood culture yielded E. hirae. Our patient was successfully treated with antimicrobials based on the susceptibility result. To our knowledge, this is the first reported case of perinephric collection and renal abscesses associated with E. hirae bacteremia

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition

Study of the reaction e^{+}e^{-} -->J/psi\pi^{+}\pi^{-} via initial-state radiation at BaBar

We study the process $e^+e^-\to J/\psi\pi^{+}\pi^{-}$ with initial-state-radiation events produced at the PEP-II asymmetric-energy collider. The data were recorded with the BaBar detector at center-of-mass energies 10.58 and 10.54 GeV, and correspond to an integrated luminosity of 454 $\mathrm{fb^{-1}}$. We investigate the $J/\psi \pi^{+}\pi^{-}$ mass distribution in the region from 3.5 to 5.5 $\mathrm{GeV/c^{2}}$. Below 3.7 $\mathrm{GeV/c^{2}}$ the $\psi(2S)$ signal dominates, and above 4 $\mathrm{GeV/c^{2}}$ there is a significant peak due to the Y(4260). A fit to the data in the range 3.74 -- 5.50 $\mathrm{GeV/c^{2}}$ yields a mass value $4244 \pm 5$ (stat) $\pm 4$ (syst)$\mathrm{MeV/c^{2}}$ and a width value $114 ^{+16}_{-15}$ (stat)$\pm 7$(syst)$\mathrm{MeV}$ for this state. We do not confirm the report from the Belle collaboration of a broad structure at 4.01 $\mathrm{GeV/c^{2}}$. In addition, we investigate the $\pi^{+}\pi^{-}$ system which results from Y(4260) decay

Toxoplasma Effector MAF1 Mediates Recruitment of Host Mitochondria and Impacts the Host Response

Recent information has revealed the functional diversity and importance of mitochondria in many cellular processes including orchestrating the innate immune response. Intriguingly, several infectious agents, such as Toxoplasma, Legionella, and Chlamydia, have been reported to grow within vacuoles surrounded by host mitochondria. Although many hypotheses have been proposed for the existence of host mitochondrial association (HMA), the causes and biological consequences of HMA have remained unanswered. Here we show that HMA is present in type I and III strains of Toxoplasma but missing in type II strains, both in vitro and in vivo. Analysis of F1 progeny from a type II×III cross revealed that HMA is a Mendelian trait that we could map. We use bioinformatics to select potential candidates and experimentally identify the polymorphic parasite protein involved, mitochondrial association factor 1 (MAF1). We show that introducing the type I (HMA+) MAF1 allele into type II (HMA-) parasites results in conversion to HMA+ and deletion of MAF1 in type I parasites results in a loss of HMA. We observe that the loss and gain of HMA are associated with alterations in the transcription of host cell immune genes and the in vivo cytokine response during murine infection. Lastly, we use exogenous expression of MAF1 to show that it binds host mitochondria and thus MAF1 is the parasite protein directly responsible for HMA. Our findings suggest that association with host mitochondria may represent a novel means by which Toxoplasma tachyzoites manipulate the host. The existence of naturally occurring HMA+ and HMA- strains of Toxoplasma, Legionella, and Chlamydia indicates the existence of evolutionary niches where HMA is either advantageous or disadvantageous, likely reflecting tradeoffs in metabolism, immune regulation, and other functions of mitochondria. © 2014 Pernas et al

Mosaic RAS/MAPK variants cause sporadic vascular malformations which respond to targeted therapy.

BACKGROUND: Sporadic vascular malformations (VMs) are complex congenital anomalies of blood vessels that lead to stroke, life-threatening bleeds, disfigurement, overgrowth, and/or pain. Therapeutic options are severely limited, and multidisciplinary management remains challenging, particularly for high-flow arteriovenous malformations (AVM). METHODS: To investigate the pathogenesis of sporadic intracranial and extracranial VMs in 160 children in which known genetic causes had been excluded, we sequenced DNA from affected tissue and optimized analysis for detection of low mutant allele frequency. RESULTS: We discovered multiple mosaic-activating variants in 4 genes of the RAS/MAPK pathway, KRAS, NRAS, BRAF, and MAP2K1, a pathway commonly activated in cancer and responsible for the germline RAS-opathies. These variants were more frequent in high-flow than low-flow VMs. In vitro characterization and 2 transgenic zebrafish AVM models that recapitulated the human phenotype validated the pathogenesis of the mutant alleles. Importantly, treatment of AVM-BRAF mutant zebrafish with the BRAF inhibitor vemurafinib restored blood flow in AVM. CONCLUSION: Our findings uncover a major cause of sporadic VMs of different clinical types and thereby offer the potential of personalized medical treatment by repurposing existing licensed cancer therapies. FUNDING: This work was funded or supported by grants from the AVM Butterfly Charity, the Wellcome Trust (UK), the Medical Research Council (UK), the UK National Institute for Health Research, the L'Oreal-Melanoma Research Alliance, the European Research Council, and the National Human Genome Research Institute (US)

Social navigation

In this chapter we present one of the pioneer approaches in supporting users in navigating the complex information spaces, social navigation support. Social navigation support is inspired by natural tendencies of individuals to follow traces of each other in exploring the world, especially when dealing with uncertainties. In this chapter, we cover details on various approaches in implementing social navigation support in the information space as we also connect the concept to supporting theories. The first part of this chapter reviews related theories and introduces the design space of social navigation support through a series of example applications. The second part of the chapter discusses the common challenges in design and implementation of social navigation support, demonstrates how these challenges have been addressed, and reviews more recent direction of social navigation support. Furthermore, as social navigation support has been an inspirational approach to various other social information access approaches we discuss how social navigation support can be integrated with those approaches. We conclude with a review of evaluation methods for social navigation support and remarks about its current state

Population genomics of cardiometabolic traits: design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium.

Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. © 2014 Erwin et al