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      Circulating microRNAs as Potential Novel Diagnostic Biomarkers to Predict Drug Resistance in Temporal Lobe Epilepsy: A Pilot Study

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          Abstract

          MicroRNAs (miRNAs) are small noncoding RNAs that have emerged as new potential epigenetic biomarkers. Here, we evaluate the efficacy of six circulating miRNA previously described in the literature as biomarkers for the diagnosis of temporal lobe epilepsy (TLE) and/or as predictive biomarkers to antiepileptic drug response. We measured the differences in serum miRNA levels by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays in a cohort of 27 patients (14 women and 13 men; mean ± SD age: 43.65 ± 17.07) with TLE compared to 20 healthy controls (HC) matched for sex, age and ethnicity (11 women and 9 men; mean ± SD age: 47.5 ± 9.1). Additionally, patients were classified according to whether they had drug-responsive ( n = 17) or drug-resistant ( n = 10) TLE. We have investigated any correlations between miRNAs and several electroclinical parameters. Three miRNAs (miR-142, miR-146a, miR-223) were significantly upregulated in patients (expressed as average expression ± SD). In detail, miR-142 expression was 0.40 ± 0.29 vs. 0.16 ± 0.10 in TLE patients compared to HC ( t-test, p < 0.01), miR-146a expression was 0.15 ± 0.11 vs. 0.07 ± 0.04 ( t-test, p < 0.05), and miR-223 expression was 6.21 ± 3.65 vs. 1.23 ± 0.84 ( t-test, p < 0.001). Moreover, results obtained from a logistic regression model showed the good performance of miR-142 and miR-223 in distinguishing drug-sensitive vs. drug-resistant TLE. The results of this pilot study give evidence that miRNAs are suitable targets in TLE and offer the rationale for further confirmation studies in larger epilepsy cohorts.

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          Most cited references44

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          FSL.

          FSL (the FMRIB Software Library) is a comprehensive library of analysis tools for functional, structural and diffusion MRI brain imaging data, written mainly by members of the Analysis Group, FMRIB, Oxford. For this NeuroImage special issue on "20 years of fMRI" we have been asked to write about the history, developments and current status of FSL. We also include some descriptions of parts of FSL that are not well covered in the existing literature. We hope that some of this content might be of interest to users of FSL, and also maybe to new research groups considering creating, releasing and supporting new software packages for brain image analysis. Copyright © 2011 Elsevier Inc. All rights reserved.
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            Definition of drug resistant epilepsy: consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies.

            To improve patient care and facilitate clinical research, the International League Against Epilepsy (ILAE) appointed a Task Force to formulate a consensus definition of drug resistant epilepsy. The overall framework of the definition has two "hierarchical" levels: Level 1 provides a general scheme to categorize response to each therapeutic intervention, including a minimum dataset of knowledge about the intervention that would be needed; Level 2 provides a core definition of drug resistant epilepsy using a set of essential criteria based on the categorization of response (from Level 1) to trials of antiepileptic drugs. It is proposed as a testable hypothesis that drug resistant epilepsy is defined as failure of adequate trials of two tolerated, appropriately chosen and used antiepileptic drug schedules (whether as monotherapies or in combination) to achieve sustained seizure freedom. This definition can be further refined when new evidence emerges. The rationale behind the definition and the principles governing its proper use are discussed, and examples to illustrate its application in clinical practice are provided.
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              ROCR: visualizing classifier performance in R.

              ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It features over 25 performance measures that can be freely combined to create two-dimensional performance curves. Standard methods for investigating trade-offs between specific performance measures are available within a uniform framework, including receiver operating characteristic (ROC) graphs, precision/recall plots, lift charts and cost curves. ROCR integrates tightly with R's powerful graphics capabilities, thus allowing for highly adjustable plots. Being equipped with only three commands and reasonable default values for optional parameters, ROCR combines flexibility with ease of usage. http://rocr.bioinf.mpi-sb.mpg.de. ROCR can be used under the terms of the GNU General Public License. Running within R, it is platform-independent. tobias.sing@mpi-sb.mpg.de.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                12 January 2021
                January 2021
                : 22
                : 2
                : 702
                Affiliations
                [1 ]Department of Medical and Surgical Sciences, Institute of Neurology, University “Magna Graecia”, Germaneto, 88100 Catanzaro, Italy; selene.db90@ 123456gmail.com (S.D.B.); francescfortunato@ 123456gmail.com (F.F.); labate@ 123456unicz.it (A.L.); a.gambardella@ 123456unicz.it (A.G.)
                [2 ]Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Via F.Cervi 93, 20090 Segrate-Milan, Italy; claudia.cava@ 123456ibfm.cnr.it (C.C.); francesca.gallivanone@ 123456ibfm.cnr.it (F.G.)
                [3 ]Department of Experimental and Clinical Medicine, University “Magna Graecia” of Catanzaro, 88100 Catanzaro, Italy; iaccino@ 123456unicz.it
                [4 ]Neuroscience Research Center, University “Magna Graecia” of Catanzaro, 88100 Catanzaro, Italy; me.caligiuri@ 123456unicz.it
                [5 ]Department of Physics “Giuseppe Occhialini”, University of Milan-Bicocca, Piazza della Scienza 3, 20126 Milan, Italy; isabella.castiglioni@ 123456unimi.it
                [6 ]Institute of Molecular Bioimaging and Physiology (IBFM), National Research Council (CNR), Section of Germaneto, 88100 Catanzaro, Italy
                Author notes
                [†]

                These authors contributed equally.

                Author information
                https://orcid.org/0000-0002-5540-4104
                https://orcid.org/0000-0002-3565-7817
                https://orcid.org/0000-0002-5901-4269
                https://orcid.org/0000-0002-4777-7138
                https://orcid.org/0000-0002-8827-7324
                Article
                ijms-22-00702
                10.3390/ijms22020702
                7828221
                33445780
                65b5a26c-54a0-4e4e-b071-7d21ab3d17f7
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 22 December 2020
                : 10 January 2021
                Categories
                Article

                Molecular biology
                temporal lobe epilepsy,mirnas,diagnosis,prognosis,antiseizure medications,asms
                Molecular biology
                temporal lobe epilepsy, mirnas, diagnosis, prognosis, antiseizure medications, asms

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