Abnormal expression of an ADAR2 alternative splicing variant in gliomas downregulates adenosine-to-inosine RNA editing

BACKGROUND: RNA editing is catalyzed by adenosine deaminases acting on RNA (ADARs). ADAR2 is the main enzyme responsible for recoding editing in humans. Adenosine-to-inosine (A-to-I) editing at the Q/R site is reported to be decreased in gliomas; however, the expression of ADAR2 mRNA was not greatly affected. METHODS: We determined ADAR2 mRNA expression in human glioblastoma cell lines and in normal human glial cells by real-time RT-PCR. We also determined ADAR2 mRNA expression in 44 glioma tissues and normal white matter. After identifying an alternative splicing variant (ASV) of ADAR2 in gliomas, we performed sequencing. We then classified glioblastomas based on the presence (+) or absence (–) of the ASV to determine the correlations between ASV + and malignant features of glioblastomas, such as invasion, peritumoral brain edema, and survival time. RESULTS: There were no significant differences in ADAR2 mRNA expression among human glioblastoma cell lines or in gliomas compared with normal white matter (all p > 0.05). The ASV, which contained a 47-nucleotide insertion in the ADAR2 mRNA transcript, was detected in the U251 and BT325 cell lines, and in some glioma tissues. The expression rate of ASV differed among gliomas of different grades. ASV + glioblastomas were more malignant than ASV – glioblastomas. CONCLUSIONS: ADAR2 is a family of enzymes in which ASVs result in differences in enzymatic activity. The ADAR2 ASV may be correlated with the invasiveness of gliomas. Identification of the mechanistic characterization of ADAR2 ASV may have future potential for individualized molecular targeted-therapy for glioma

Integrative Imaging Informatics for Cancer Research: Workflow Automation for Neuro-oncology (I3CR-WANO)

Efforts to utilize growing volumes of clinical imaging data to generate tumor evaluations continue to require significant manual data wrangling owing to the data heterogeneity. Here, we propose an artificial intelligence-based solution for the aggregation and processing of multisequence neuro-oncology MRI data to extract quantitative tumor measurements. Our end-to-end framework i) classifies MRI sequences using an ensemble classifier, ii) preprocesses the data in a reproducible manner, iii) delineates tumor tissue subtypes using convolutional neural networks, and iv) extracts diverse radiomic features. Moreover, it is robust to missing sequences and adopts an expert-in-the-loop approach, where the segmentation results may be manually refined by radiologists. Following the implementation of the framework in Docker containers, it was applied to two retrospective glioma datasets collected from the Washington University School of Medicine (WUSM; n = 384) and the M.D. Anderson Cancer Center (MDA; n = 30) comprising preoperative MRI scans from patients with pathologically confirmed gliomas. The scan-type classifier yielded an accuracy of over 99%, correctly identifying sequences from 380/384 and 30/30 sessions from the WUSM and MDA datasets, respectively. Segmentation performance was quantified using the Dice Similarity Coefficient between the predicted and expert-refined tumor masks. Mean Dice scores were 0.882 ($\pm$0.244) and 0.977 ($\pm$0.04) for whole tumor segmentation for WUSM and MDA, respectively. This streamlined framework automatically curated, processed, and segmented raw MRI data of patients with varying grades of gliomas, enabling the curation of large-scale neuro-oncology datasets and demonstrating a high potential for integration as an assistive tool in clinical practice

Small fields change spike timing: A functional role of local-field potentials?

Small electric fields will polarize neurons by only a small amount; for this reason small electric fields have previously been suggested to have no physiologically relevant effects. However, in recent years evidence has been mounting that small fields can entrain network activity [1], and have indeed a causal effect on brain function [2]. To date, there is no proven mechanistic theory on how this causal interaction may occur. We propose a simple mechanism whereby an extracellular field incrementally polarizes the neuron’s membrane and thus advances (or delays) the timing of a synaptically driven action potential. Assuming a steady firing threshold and knowing that a membrane polarizes in proportion to field strength [3], i.e. ∆V = cE, one can make a number of quantitative predictions on the effects of extracellular fields on a neuron’s spike timing: (1) Spike timing changes linearly with increasing steady-state field strength: ∆t ∝ E. (2) This effect is proportional to the inverse of the driving synaptic membrane potential slope: ∆t = ∆V / ˙ V = cE / ˙ V. (3) Oscillating fields will shift firing times with their mean falling within 1/4 or the oscillatory cycle (the rising edge). (4) This mean firing time advances with increasing field strength and decreasing ramp slope, i.e. it increases with cE / ˙ V. (5) The strength of the coherence as measured by the Rayleigh coefficient (vector strength) also increases with cE / ˙ V. To test these predictions we measured the effect of applied uniform fields on the timing of action potential

Spectral Separation Resolves Partial Volume Effect in MRSI

Cancerous tissue exhibits altered metabolite concentrations as compared to normal brain tissue. Magnetic resonance spectroscopy imaging (MRSI) reveals such abnormalities in altered spectral profiles

Thermolytic dynamics and prediction of natural gas generation from marine source rocks in the deepwater area of Qiongdongnan Basin, China

149-162Present study is to quantify individual natural gas generation in the deepwater area of the Qiongdongnan Basin based on the basin modeling from the shallow-water, and to evaluate kinetic parameters and geological extrapolations using an optimization procedure. Kinetic model presented reproduces the detailed features of shale pyrolysis and coal processing. The idea of blending these two approaches is not new, but until now the most sophisticated attempts reproduced only the gross features of kerogen cracking. It will help to forecast preferable prospect area, and to accelerate the prospecting of natural gas in the deepwater area of the Qiongdongnan Basin

An automated method for high-definition transcranial direct current stimulation modeling

Abstract—Targeted transcranial stimulation with electric currents requires accurate models of the current flow from scalp electrodes to the human brain. Idiosyncratic anatomy of individual brains and heads leads to significant variability in such current flows across subjects, thus, necessitating accurate individualized head models. Here we report on an automated processing chain that computes current distributions in the head starting from a structural magnetic resonance image (MRI). The main purpose of automating this process is to reduce the substantial effort currently required for manual segmentation, electrode placement, and solving of finite element models. In doing so, several weeks of manual labor were reduced to no more than 4 hours of computation time and minimal user interaction, while current-flow results for the automated method deviated by less than 27.9 % from the man-ual method. Key facilitating factors are the addition of three tissue types (skull, scalp and air) to a state-of-the-art automated segmentation process, morphological processing to correct small but important segmentation errors, and automated placement of small electrodes based on easily reproducible standard electrode configurations. We anticipate that such an automated processing will become an indispensable tool to individualize transcranial direct current stimulation (tDCS) therapy. I

Spike timing amplifies the effect of electric fields on neurons: implications for endogenous field-effects

Despite compelling phenomenological evidence that small electric fields (<5 mV/mm) can affect brain function, a quantitative and experimentally verified theory is currently lacking. Here we demonstrate a novel mechanism by which the non-linear properties of single neurons 'amplify ' the effect of small electric fields: when concurrent to supra-threshold synaptic input, small electric fields can have significant effects on spike timing. For low-frequency fields our theory predicts a linear dependency of spike timing changes on field strength. For high-frequency fields (relative to the synaptic input), the theory predicts coherent firing; with mean firing phase and coherence each increasing monotonically with field strength. Importantly, in both cases, the effects of fields on spike timing are amplified with decreasing synaptic input slope and increased cell susceptibility (mV membrane polarization per field amplitude). We confirmed these predictions experimentally using CA1 hippocampal neurons in vitro exposed to static (DC) and oscillating (AC) uniform electric fields. In addition, we develop a robust method to quantify cell susceptibility using spike timing. Our results provide a precise mechanism for a functional role of endogenous field oscillations (e.g. gamma) in brain function, and introduce a framework for considering the effects of environmental fields and design of low-intensity therapeutic neuro-stimulation technologies

Layered access control for MPEG-4 FGS video

MPEG-4 has recently adopted the Fine Granularity Scalability (FGS) video coding technology which enables easy and flexible adaptation to bandwidth fluctuations and device capabilities. Encryption for FGS should preserve such adaptation capabilities and allow intermediate stages in the delivery to process the media on the ciphertext directly. In this paper, we propose a novel scalable access control scheme with this property for the MPEG-4 FGS format. It offers free browsing of the lowquality base layer video but controls the access to the enhancement layer at different service levels based on either PSNR or bitrates. Both types of service levels are supported simultaneously without jeopardizing each other’s security. The scheme is fast and degrades neither compression efficiency nor error resilience of the MPEG-4 FGS. The approach is also applicable to other scalable multimedia. 1