Machine learning to detect brain lesions in focal epilepsy

PURPOSE: Identifying areas of abnormality on MRI brain scans in individuals with focal epilepsy is funda- mental to the diagnosis and treatment of the condition. However, in about a third of patients with focal epilepsy, brain scans appear to be normal (MRI-negative) as human observers cannot detect any abnormality with cur- rent imaging technology. The objective of this paper is to provide a novel approach in presenting localization using machine learning in order to locate areas of abnormality on patients with focal epilepsy on a per-voxel basis by comparing them with healthy controls. As a proof-of-concept, the technique is first applied to patients with visible lesions providing a ground truth (MRI-positive), but future work will extend this to MRI-negative subjects. METHODS: Our data consists of multi-modal brain MR images from 62 healthy control subjects and 44 MRI- positive patients with focal epilepsy. We utilized a support vector machine (SVM) as our probabilistic classifier and train it with two classes of data. We generate probability maps applying our machine learning classifier on all voxels of a test subjects to visualize the predictions. Overlap scores are used to evaluate the classifier performance in MRI-positive patients. RESULTS: Our model reached 83% specificity, 91% sensitivity, and an Area Under the Curve (AUC) of 0.896 for the task of voxel-based classification of normal versus abnormal voxels. In addition, Dice scores of up to 0.66 were achieved for the overlap measure of lesion probability map and the ground truth labels annotated by a neurologist. CONCLUSION: We demonstrated a novel approach in presenting localization using machine learning tech- niques to localize focal epilepsy lesions from multi-modal MR images

On peer reviewing: how to nourish an author’s mind and win a JLDHE editor’s heart

No embargo required.Editors and publishers of scholarly journals rarely agree on what makes for a good publication; they do, however, agree on the need for a robust peer review process as a crucial means to judge the merits of potential publications. While fraught with issues and inefficiencies, a critical and supportive peer review is not only what editors rely on when assessing scholarship presented for publication but also what authors hope for in order to improve their work. Understanding how peer review may best serve all parties involved: authors, editors, and reviewers, is thus at the heart of this article. The analysis offered here is based on a session the Journal for Learning Development in Higher Education editors gave at the 2020 LD@3 seminar series, entitled ‘The Art of Reviewing’. It explores the different aspects of the peer review process while formulating recommendations regarding best practices and outlining JLDHE initiatives for supporting reviewers’ vital work.</jats:p

Motor neuron diseases caused by a novel VRK1 variant – A genotype/phenotype study

Background: Motor neuron disorders involving upper and lower neurons are a genetically and clinically heterogenous group of rare neuromuscular disorders with overlap among spinal muscular atrophies (SMAs) and amyotrophic lateral sclerosis (ALS). Classical SMA caused by recessive mutations in SMN1 is one of the most common genetic causes of mortality in infants. It is characterized by degeneration of anterior horn cells in the spinal cord, leading to progressive muscle weakness and atrophy. Non-SMN1-related spinal muscular atrophies are caused by variants in a number of genes, including VRK1, encoding the vaccinia- related kinase 1 (VRK1). VRK1 variants have been segregated with motor neuron diseases including SMA phenotypes or hereditary complex motor and sensory axonal neuropathy (HMSN), with or without pontocerebellar hypoplasia or microcephaly. Results: Here, we report an association of a novel homozygous splice variant in VRK1 (c.1159 + 1G>A) with childhood-onset SMA or juvenile lower motor disease with brisk tendon reflexes without pontocerebellar hypoplasia and normal intellectual ability in a family with five affected individuals. We show that the VRK1 splice variant in patients causes decreased splicing efficiency and a mRNA frameshift that escapes the nonsensemediated decay machinery and results in a premature termination codon. Conclusions: Our findings unveil the impact of the variant on the VRK1 transcript and further support the implication of VRK1 in the pathogenesis of lower motor neuron diseases

Raman spectroscopy study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the thermal annealing pathway

We report a multi-wavelength Raman spectroscopy study of the structural changes along the thermal annealing pathway of a poly(furfuryl alcohol) (PFA) derived nanoporous carbon (NPC). The Raman spectra were deconvoluted utilizing G, D, D′, A and TPA bands. The appropriateness of these deconvolutions was confirmed via recovery of the correct dispersive behaviours of these bands. It is proposed that the ID/IG ratio is composed of two parts: one associated with the extent of graphitic crystallites (the Tuinstra–Koenig relationship), and a second related to the inter-defect distance. This model was used to successfully determine the variation of the in-plane size and intra-plane defect density along the annealing pathway. It is proposed that the NPC skeleton evolves along the annealing pathway in two stages: below 1600 °C it was dominated by a reduction of in-plane defects with a minor crystallite growth, and above this temperature growth of the crystallites accelerates as the in-plane defect density approaches zero. A significant amount of transpolyacetylene (TPA)-like structures was found to be remaining even at 2400 °C. These may be responsible for resistance to further graphitization of the PFA-based carbon at higher temperatures

Tuning the electrical conductance of metalloporphyrin supramolecular wires

In contrast with conventional single-molecule junctions, in which the current flows parallel to the long axis or plane of a molecule, we investigate the transport properties of M(II)-5,15-diphenylporphyrin (M-DPP) single-molecule junctions (M=Co, Ni, Cu, or Zn divalent metal ions), in which the current flows perpendicular to the plane of the porphyrin. Novel STM-based conductance measurements combined with quantum transport calculations demonstrate that current-perpendicular-to-the-plane (CPP) junctions have three-orders-of-magnitude higher electrical conductanc than their current in-plane (CIP) counterparts, ranging from 2.10−2 G0 for Ni-DPP up to 8.10−2 G0 for Zn-DPP. The metal ion in the center of the DPP skeletons is strongly coordinated with the nitrogens of the pyridyl coated electrodes, with a binding energy that is sensitive to the choice of metal ion. We find that the binding energies of Zn-DPP and Co-DPP are significantly higher than those of Ni-DPP and Cu-DPP. Therefore when combined with its higher conductance, we identify Zn-DPP as the favoured candidate for high conductance CPP single-molecule devices

Understanding mechanisms of asphaltene adsorption from organic solvent on mica

The adsorption process of asphaltene onto molecularly smooth mica surfaces from toluene solutions of various concentrations (0.01-1 wt %) was studied using a surface forces apparatus (SFA). Adsorption of asphaltenes onto mica was found to be highly dependent on adsorption time and asphaltene concentration of the solution. The adsorption of asphaltenes led to an attractive bridging force between the mica surfaces in asphaltene solution. The adsorption process was identified as being controlled by the diffusion of asphaltenes from the bulk solution to the mica surface with a diffusion coefficient on the order of 10-10 m2/s at room temperature, depending on the asphaltene bulk concentration. This diffusion coefficient corresponds to a hydrodynamic molecular radius of approximately 0.5 nm, indicating that asphaltene diffuses to mica surfaces as individual molecules at very low concentration (e.g., 0.01 wt %). Atomic force microscopy images of the adsorbed asphaltenes on mica support the results of the SFA force measurements. The results from the SFA force measurements provide valuable insights into the molecular interactions (e.g., steric repulsion and bridging attraction as a function of distance) of asphaltenes in organic media and hence their roles in crude oil and bitumen production

An ancestral 10-bp repeat expansion in VWA1 causes recessive hereditary motor neuropathy

The extracellular matrix comprises a network of macromolecules such as collagens, proteoglycans and glycoproteins. VWA1 (von Willebrand factor A domain containing 1) encodes a component of the extracellular matrix that interacts with perlecan/collagen VI, appears to be involved in stabilizing extracellular matrix structures, and demonstrates high expression levels in tibial nerve. Vwa1-deficient mice manifest with abnormal peripheral nerve structure/function; however, VWA1 variants have not previously been associated with human disease. By interrogating the genome sequences of 74 180 individuals from the 100K Genomes Project in combination with international gene-matching efforts and targeted sequencing, we identified 17 individuals from 15 families with an autosomal-recessive, non-length dependent, hereditary motor neuropathy and rare biallelic variants in VWA1. A single disease-associated allele p.(G25Rfs*74), a 10-bp repeat expansion, was observed in 14/15 families and was homozygous in 10/15. Given an allele frequency in European populations approaching 1/1000, the seven unrelated homozygote individuals ascertained from the 100K Genomes Project represents a substantial enrichment above expected. Haplotype analysis identified a shared 220 kb region suggesting that this founder mutation arose >7000 years ago. A wide age-range of patients (6–83 years) helped delineate the clinical phenotype over time. The commonest disease presentation in the cohort was an early-onset (mean 2.0 ± 1.4 years) non-length-dependent axonal hereditary motor neuropathy, confirmed on electrophysiology, which will have to be differentiated from other predominantly or pure motor neuropathies and neuronopathies. Because of slow disease progression, ambulation was largely preserved. Neurophysiology, muscle histopathology, and muscle MRI findings typically revealed clear neurogenic changes with single isolated cases displaying additional myopathic process. We speculate that a few findings of myopathic changes might be secondary to chronic denervation rather than indicating an additional myopathic disease process. Duplex reverse transcription polymerase chain reaction and immunoblotting using patient fibroblasts revealed that the founder allele results in partial nonsense mediated decay and an absence of detectable protein. CRISPR and morpholino vwa1 modelling in zebrafish demonstrated reductions in motor neuron axonal growth, synaptic formation in the skeletal muscles and locomotive behaviour. In summary, we estimate that biallelic variants in VWA1 may be responsible for up to 1% of unexplained hereditary motor neuropathy cases in Europeans. The detailed clinical characterization provided here will facilitate targeted testing on suitable patient cohorts. This novel disease gene may have previously evaded detection because of high GC content, consequential low coverage and computational difficulties associated with robustly detecting repeat-expansions. Reviewing previously unsolved exomes using lower QC filters may generate further diagnoses

MLSys: The New Frontier of Machine Learning Systems

Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains a significant obstacle, in large part due to the radically different development and deployment profile of modern ML methods, and the range of practical concerns that come with broader adoption. We propose to foster a new systems machine learning research community at the intersection of the traditional systems and ML communities, focused on topics such as hardware systems for ML, software systems for ML, and ML optimized for metrics beyond predictive accuracy. To do this, we describe a new conference, MLSys, that explicitly targets research at the intersection of systems and machine learning with a program committee split evenly between experts in systems and ML, and an explicit focus on topics at the intersection of the two