Analysis of Cognitive Deficits of Concussion Patients: Dual Task, Motor Cognition, and Memory

The severity of a concussion is determined by the magnitude of the force of impact and the symptoms expressed post-injury. The most current and widely used test to identify a concussion in college athletics is called the Immediate Post Concussion Assessment and Cognitive Testing (ImPACT). It is a computerized neurocognitive test battery that measures different cognitive abilities and compares baseline with post-injury results. In the current study we formulated a series of physical and psychological cognition tests that measure similar cognitive abilities as the ImPACT. The purpose of this study is to demonstrate that physical tests paired with neurocognitive tests are a better determinate of post-concussion symptoms in athletes than a sedentary neurocognitive battery test alone. Such tests included balance, memory, spatial relations, attention and reaction time. Three different groups of post-concussed history were statistically compared. Group one (controls), consisted of participants with no previous history of a concussion (n=32). Group two (concussed), consisted of participants with a concussion in the past three months and who had recently been cleared to resume full sports activities (n=11). Group three (multiple concussed), consisted of participants with at least five concussions in their lifespan (n=7). A one-way ANOVA and two-tailed independent t-test were ran to observe any differences in tests between groups (

Visualizing the Effect of an Electrostatic Gate with Angle-Resolved Photoemission Spectroscopy

Electrostatic gating is pervasive in materials science, yet its effects on the electronic band structure of materials has never been revealed directly by angle-resolved photoemission spectroscopy (ARPES), the technique of choice to non-invasively probe the electronic band structure of a material. By means of a state-of-the-art ARPES setup with sub-micron spatial resolution, we have investigated a heterostructure composed of Bernal-stacked bilayer graphene (BLG) on hexagonal boron nitride and deposited on a graphite flake. By voltage biasing the latter, the electric field effect is directly visualized on the valence band as well as on the carbon 1s core level of BLG. The band gap opening of BLG submitted to a transverse electric field is discussed and the importance of intralayer screening is put forward. Our results pave the way for new studies that will use momentum-resolved electronic structure information to gain insight on the physics of materials submitted to the electric field effect

Observations of Giant Pulses from Pulsar PSR B0950+08 using LWA1

We report the detection of giant pulse emission from PSR B0950+08 in 24 hours of observations made at 39.4 MHz, with a bandwidth of 16 MHz, using the first station of the Long Wavelength Array, LWA1. We detected 119 giant pulses from PSR B0950+08 (at its dispersion measure), which we define as having SNRs at least 10 times larger than for the mean pulse in our data set. These 119 pulses are 0.035% of the total number of pulse periods in the 24 hours of observations. The rate of giant pulses is about 5.0 per hour. The cumulative distribution of pulse strength $S$ is a steep power law, $N(>S)\propto S^{-4.7}$, but much less steep than would be expected if we were observing the tail of a Gaussian distribution of normal pulses. We detected no other transient pulses in a dispersion measure range from 1 to 90 pc cm$^{-3}$, in the beam tracking PSR B0950+08. The giant pulses have a narrower temporal width than the mean pulse (17.8 ms, on average, vs. 30.5 ms). The pulse widths are consistent with a previously observed weak dependence on observing frequency, which may be indicative of a deviation from a Kolmogorov spectrum of electron density irregularities along the line of sight. The rate and strength of these giant pulses is less than has been observed at $\sim$100 MHz. Additionally, the mean (normal) pulse flux density we observed is less than at $\sim$100 MHz. These results suggest this pulsar is weaker and produces less frequent giant pulses at 39 MHz than at 100 MHz.Comment: 27 pages, 12 figures, typos correcte

Control of Giant Topological Magnetic Moment and Valley Splitting in Trilayer Graphene

Bloch states of electrons in honeycomb two-dimensional crystals with multi-valley band structure and broken inversion symmetry have orbital magnetic moments of a topological nature. In crystals with two degenerate valleys, a perpendicular magnetic field lifts the valley degeneracy via a Zeeman effect due to these magnetic moments, leading to magnetoelectric effects which can be leveraged for creating valleytronic devices. In this work, we demonstrate that trilayer graphene with Bernal stacking, (ABA TLG) hosts topological magnetic moments with a large and widely tunable valley g-factor, reaching a value 1050 at the extreme of the studied parametric range. The reported experiment consists in sublattice-resolved scanning tunneling spectroscopy under perpendicular electric and magnetic fields that control the TLG bands. The tunneling spectra agree very well with the results of theoretical modeling that includes the full details of the TLG tight-binding model and accounts for a quantum-dot-like potential profile formed electrostatically under the scanning tunneling microscope tip.Comment: Manuscript and Supporting Information update

BET bromodomain inhibitors PFI-1 and JQ1 are identified in an epigenetic compound screen to enhance C9ORF72 gene expression and shown to ameliorate C9ORF72-associated pathological and behavioral abnormalities in a C9ALS/FTD model

BACKGROUND: An intronic GGGGCC (G4C2) hexanucleotide repeat expansion (HRE) in the C9ORF72 gene is the most common cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), referred to as C9ALS/FTD. No cure or effective treatment exist for C9ALS/FTD. Three major molecular mechanisms have emerged to explain C9ALS/FTD disease mechanisms: (1) C9ORF72 loss-of-function through haploinsufficiency, (2) dipeptide repeat (DPR) proteins mediated toxicity by the translation of the repeat RNAs, and more controversial, (3) RNA-mediated toxicity by bidirectional transcription of the repeats that form intranuclear RNA foci. Recent studies indicate a double-hit pathogenic mechanism in C9ALS/FTD, where reduced C9ORF72 protein levels lead to impaired clearance of toxic DPRs. Here we explored whether pharmacological compounds can revert these pathological hallmarks in vitro and cognitive impairment in a C9ALS/FTD mouse model (C9BAC). We specifically focused our study on small molecule inhibitors targeting chromatin-regulating proteins (epidrugs) with the goal of increasing C9ORF72 gene expression and reduce toxic DPRs. RESULTS: We generated luciferase reporter cell lines containing 10 (control) or \u3e /= 90 (mutant) G4C2 HRE located between exon 1a and 1b of the human C9ORF72 gene. In a screen of 14 different epidrugs targeting bromodomains, chromodomains and histone-modifying enzymes, we found that several bromodomain and extra-terminal domain (BET) inhibitors (BETi), including PFI-1 and JQ1, increased luciferase reporter activity. Using primary cortical cultures from C9BAC mice, we further found that PFI-1 treatment increased the expression of V1-V3 transcripts of the human mutant C9ORF72 gene, reduced poly(GP)-DPR inclusions but enhanced intranuclear RNA foci. We also tested whether JQ1, an BETi previously shown to reach the mouse brain by intraperitoneal (i.p.) injection, can revert behavioral abnormalities in C9BAC mice. Interestingly, it was found that JQ1 administration (daily i.p. administration for 7 days) rescued hippocampal-dependent cognitive deficits in C9BAC mice. CONCLUSIONS: Our findings place BET bromodomain inhibitors as a potential therapy for C9ALS/FTD by ameliorating C9ORF72-associated pathological and behavioral abnormalities. Our finding that PFI-1 increases accumulation of intranuclear RNA foci is in agreement with recent data in flies suggesting that nuclear RNA foci can be neuroprotective by sequestering repeat transcripts that result in toxic DPRs

Denoising Scanning Tunneling Microscopy Images of Graphene with Supervised Machine Learning

Machine learning (ML) methods are extraordinarily successful at denoising photographic images. The application of such denoising methods to scientific images is, however, often complicated by the difficulty in experimentally obtaining a suitable expected result as an input to training the ML network. Here, we propose and demonstrate a simulation-based approach to address this challenge for denoising atomic-scale scanning tunneling microscopy (STM) images, which consists of training a convolutional neural network on STM images simulated based on a tight-binding electronic structure model. As model materials, we consider graphite and its mono- and few-layer counterpart, graphene. With the goal of applying it to any experimental STM image obtained on graphitic systems, the network was trained on a set of simulated images with varying characteristics such as tip height, sample bias, atomic-scale defects, and non-linear background. Denoising of both simulated and experimental images with this approach is compared to that of commonly-used filters, revealing a superior outcome of the ML method in the removal of noise as well as scanning artifacts - including on features not simulated in the training set. An extension to larger STM images is further discussed, along with intrinsic limitations arising from training set biases that discourage application to fundamentally unknown surface features. The approach demonstrated here provides an effective way to remove noise and artifacts from typical STM images, yielding the basis for further feature discernment and automated processing.Comment: Includes S

Gastrointestinal tissue‐based molecular biomarkers: A practical categorization based on the 2019 WHO Classification of Epithelial Digestive Tumours

Molecular biomarkers have come to constitute one of the cornerstones of oncological pathology. The method of classification not only directly affects the manner in which patients are diagnosed and treated, but also guides the development of drugs and of artificial intelligence tools. The aim of this article is to organise and update gastrointestinal molecular biomarkers in order to produce an easy-to-use guide for routine diagnostics. For this purpose, we have extracted and reorganised the molecular information on epithelial neoplasms included in the 2019 World Health Organization classification of tumours. Digestive system tumours, 5th edn