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      Excessive rest time during active phase is reliably detected in a mouse model of myotonic dystrophy type 1 using home cage monitoring

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          Abstract

          Myotonic dystrophy type 1 (DM1) is a dominantly inherited neuromuscular disease caused by the abnormal expansion of CTG-repeats in the 3′-untranslated region of the Dystrophia Myotonica Protein Kinase (DMPK) gene, characterized by multisystemic symptoms including muscle weakness, myotonia, cardio-respiratory problems, hypersomnia, cognitive dysfunction and behavioral abnormalities. Sleep-related disturbances are among the most reported symptoms that negatively affect the quality of life of patients and that are present in early and adult-onset forms of the disease. DMSXL mice carry a mutated human DMPK transgene containing >1,000 CTGrepeats, modeling an early onset, severe form of DM1. They exhibit a pathologic neuromuscular phenotype and also synaptic dysfunction resulting in neurological and behavioral deficits similar to those observed in patients. Additionally, they are underweight with a very high mortality within the first month after birth presenting several welfare issues. To specifically explore sleep/rest-related behaviors of this frail DM1 mouse model we used an automated home cage-based system that allows 24/7 monitoring of their activity non-invasively. We tested male and female DMSXL mice and their wild-type (WT) littermates in Digital Ventilated Cages (DVCR) assessing activity and rest parameters on day and night for 5 weeks. We demonstrated that DMSXL mice show reduced activity and regularity disruption index (RDI), higher percentage of zero activity per each hour and longer periods of rest during the active phase compared to WT. This novel rest-related phenotype in DMSXL mice, assessed unobtrusively, could be valuable to further explore mechanisms and potential therapeutic interventions to alleviate the very common symptom of excessive daytime sleepiness in DM1 patients.

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          Most cited references42

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          nparLD: AnRSoftware Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments

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            Wearable Devices in Medical Internet of Things: Scientific Research and Commercially Available Devices

            Objectives Wearable devices are currently at the heart of just about every discussion related to the Internet of Things. The requirement for self-health monitoring and preventive medicine is increasing due to the projected dramatic increase in the number of elderly people until 2020. Developed technologies are truly able to reduce the overall costs for prevention and monitoring. This is possible by constantly monitoring health indicators in various areas, and in particular, wearable devices are considered to carry this task out. These wearable devices and mobile apps now have been integrated with telemedicine and telehealth efficiently, to structure the medical Internet of Things. This paper reviews wearable health care devices both in scientific papers and commercial efforts. Methods MIoT is demonstrated through a defined architecture design, including hardware and software dealing with wearable devices, sensors, smart phones, medical application, and medical station analyzers for further diagnosis and data storage. Results Wearables, with the help of improved technology have been developed greatly and are considered reliable tools for long-term health monitoring systems. These are applied in the observation of a large variety of health monitoring indicators in the environment, vital signs, and fitness. Conclusions Wearable devices are now used for a wide range of healthcare observation. One of the most important elements essential in data collection is the sensor. During recent years with improvement in semiconductor technology, sensors have made investigation of a full range of parameters closer to realization.
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              Muscleblind-like 2-mediated alternative splicing in the developing brain and dysregulation in myotonic dystrophy.

              The RNA-mediated disease model for myotonic dystrophy (DM) proposes that microsatellite C(C)TG expansions express toxic RNAs that disrupt splicing regulation by altering MBNL1 and CELF1 activities. While this model explains DM manifestations in muscle, less is known about the effects of C(C)UG expression on the brain. Here, we report that Mbnl2 knockout mice develop several DM-associated central nervous system (CNS) features including abnormal REM sleep propensity and deficits in spatial memory. Mbnl2 is prominently expressed in the hippocampus and Mbnl2 knockouts show a decrease in NMDA receptor (NMDAR) synaptic transmission and impaired hippocampal synaptic plasticity. While Mbnl2 loss did not significantly alter target transcript levels in the hippocampus, misregulated splicing of hundreds of exons was detected using splicing microarrays, RNA-seq, and HITS-CLIP. Importantly, the majority of the Mbnl2-regulated exons examined were similarly misregulated in DM. We propose that major pathological features of the DM brain result from disruption of the MBNL2-mediated developmental splicing program. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Front Behav Neurosci
                Front Behav Neurosci
                Front. Behav. Neurosci.
                Frontiers in Behavioral Neuroscience
                Frontiers Media S.A.
                1662-5153
                02 March 2023
                2023
                : 17
                : 1130055
                Affiliations
                [1] 1Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR) , Monterotondo, Italy
                [2] 2Tecniplast S.p.A. , Buguggiate, Italy
                [3] 3Sorbonne Université, INSERM, Institut de Myologie, Centre de Recherche en Myologie , Paris, France
                Author notes

                Edited by: Daniela D. Pollak, Medical University of Vienna, Austria

                Reviewed by: Eric Horstick, West Virginia University, United States; Ioannis Zalachoras, Université de Lausanne, Switzerland

                *Correspondence: Mara Rigamonti, mara.rigamonti@ 123456tecniplast.it

                These authors have contributed equally to this work

                This article was submitted to Pathological Conditions, a section of the journal Frontiers in Behavioral Neuroscience

                Article
                10.3389/fnbeh.2023.1130055
                10017452
                36935893
                d98aa0fa-1e6f-40c7-b289-a5cc9075c0ec
                Copyright © 2023 Golini, Rigamonti, Raspa, Scavizzi, Falcone, Gourdon and Mandillo.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 December 2022
                : 17 February 2023
                Page count
                Figures: 5, Tables: 0, Equations: 0, References: 42, Pages: 9, Words: 6330
                Funding
                This work was supported by Fondazione Telethon–Italy (Grant No. GGP19035).
                Categories
                Neuroscience
                Original Research

                Neurosciences
                dvc®,dmsxl,dm1,digital biomarker,sleep,excessive daytime sleepiness (eds),home cage monitoring

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