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Biomedicines
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New Insights into Motor Neuron Diseases
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New Insights into Motor Neuron Diseases

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Neurobiology and Clinical Neuroscience".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 7666

Special Issue Editor

Dr. Jessica Mandrioli

E-Mail Website
Guest Editor
Associate Professor, Department of Biomedical, Metabolic and Neural Sciences, Centre for Neuroscience and Nanotechnology, University of Modena and Reggio Emilia, Via Pietro Giardini 1355, 41126 Modena, Italy
Interests: amyotrophic lateral sclerosis; neurological diseases; neuroepidemiology; neurodegeneration; neuroinflammation; neurogenetics; microbiota
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Motor neuron diseases include a variety of rare diseases characterized by progressive disability and a significant psychological, social, and economic burden. Their extreme genetic, pathology, and phenotype heterogeneity make them major causes of clinical trial failure and the substantial absence of effective treatments. Furthermore, the still incomplete knowledge of their pathogenic mechanisms and risk factors, especially environmental ones, complicates the search for a personalized therapeutic approach.

Nonetheless, in the last few years, considerable progress has been made in the study of motor neuron diseases, especially in the genetic field, with consequent and important therapeutic implications.

This Special Issue aims to collect high-quality papers on the emerging research on motor neuron diseases, with special consideration of new insights into disease pathomechanisms and possible genetic and/or environmental risk factors, biological and clinical heterogeneity, biomarkers, and studies aimed at identifying potential treatment targets. As we believe this field could benefit from multidisciplinary approaches, contributions including basic, translational, and clinical studies are strongly encouraged.

Dr. Jessica Mandrioli
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • motor neuron diseases
  • epidemiology
  • environment
  • genetics
  • pathomechanisms
  • disease heterogeneity
  • biomarkers
  • treatment

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Published Papers (3 papers)

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Research

36 pages, 5054 KiB  
Article
Graphical Insight: Revolutionizing Seizure Detection with EEG Representation
by Muhammad Awais, Samir Brahim Belhaouari and Khelil Kassoul
Biomedicines 2024, 12(6), 1283; https://doi.org/10.3390/biomedicines12061283 - 10 Jun 2024
Viewed by 1519
Abstract
Epilepsy is characterized by recurring seizures that result from abnormal electrical activity in the brain. These seizures manifest as various symptoms including muscle contractions and loss of consciousness. The challenging task of detecting epileptic seizures involves classifying electroencephalography (EEG) signals into ictal (seizure) [...] Read more.
Epilepsy is characterized by recurring seizures that result from abnormal electrical activity in the brain. These seizures manifest as various symptoms including muscle contractions and loss of consciousness. The challenging task of detecting epileptic seizures involves classifying electroencephalography (EEG) signals into ictal (seizure) and interictal (non-seizure) classes. This classification is crucial because it distinguishes between the states of seizure and seizure-free periods in patients with epilepsy. Our study presents an innovative approach for detecting seizures and neurological diseases using EEG signals by leveraging graph neural networks. This method effectively addresses EEG data processing challenges. We construct a graph representation of EEG signals by extracting features such as frequency-based, statistical-based, and Daubechies wavelet transform features. This graph representation allows for potential differentiation between seizure and non-seizure signals through visual inspection of the extracted features. To enhance seizure detection accuracy, we employ two models: one combining a graph convolutional network (GCN) with long short-term memory (LSTM) and the other combining a GCN with balanced random forest (BRF). Our experimental results reveal that both models significantly improve seizure detection accuracy, surpassing previous methods. Despite simplifying our approach by reducing channels, our research reveals a consistent performance, showing a significant advancement in neurodegenerative disease detection. Our models accurately identify seizures in EEG signals, underscoring the potential of graph neural networks. The streamlined method not only maintains effectiveness with fewer channels but also offers a visually distinguishable approach for discerning seizure classes. This research opens avenues for EEG analysis, emphasizing the impact of graph representations in advancing our understanding of neurodegenerative diseases. Full article
(This article belongs to the Special Issue New Insights into Motor Neuron Diseases)
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22 pages, 10465 KiB  
Article
Inhibition of NF-κB with an Analog of Withaferin-A Restores TDP-43 Homeostasis and Proteome Profiles in a Model of Sporadic ALS
by Pooja Shree Mishra, Daniel Phaneuf, Hejer Boutej, Vincent Picher-Martel, Nicolas Dupre, Jasna Kriz and Jean-Pierre Julien
Biomedicines 2024, 12(5), 1017; https://doi.org/10.3390/biomedicines12051017 - 5 May 2024
Viewed by 3880
Abstract
The current knowledge on pathogenic mechanisms in amyotrophic lateral sclerosis (ALS) has widely been derived from studies with cell and animal models bearing ALS-linked genetic mutations. However, it remains unclear to what extent these disease models are of relevance to sporadic ALS. Few [...] Read more.
The current knowledge on pathogenic mechanisms in amyotrophic lateral sclerosis (ALS) has widely been derived from studies with cell and animal models bearing ALS-linked genetic mutations. However, it remains unclear to what extent these disease models are of relevance to sporadic ALS. Few years ago, we reported that the cerebrospinal fluid (CSF) from sporadic ALS patients contains toxic factors for disease transmission in mice via chronic intracerebroventricular (i.c.v.) infusion. Thus a 14-day i.c.v. infusion of pooled CSF samples from ALS cases in mice provoked motor impairment as well as ALS-like pathological features. This offers a unique paradigm to test therapeutics in the context of sporadic ALS disease. Here, we tested a new Withaferin-A analog (IMS-088) inhibitor of NF-κB that was found recently to mitigate disease phenotypes in mouse models of familial disease expressing TDP-43 mutant. Our results show that oral intake of IMS-088 ameliorated motor performance of mice infused with ALS-CSF and it alleviated pathological changes including TDP-43 proteinopathy, neurofilament disorganization, and neuroinflammation. Moreover, CSF infusion experiments were carried out with transgenic mice having neuronal expression of tagged ribosomal protein (hNfL-RFP mice), which allowed immunoprecipitation of neuronal ribosomes for analysis by mass spectrometry of the translational peptide signatures. The results indicate that treatment with IMS-088 prevented many proteomic alterations associated with exposure to ALS-CSF involving pathways related to cytoskeletal changes, inflammation, metabolic dysfunction, mitochondria, UPS, and autophagy dysfunction. The effective disease-modifying effects of this drug in a mouse model based on i.c.v. infusion of ALS-CSF suggest that the NF-κB signaling pathway represents a compelling therapeutic target for sporadic ALS. Full article
(This article belongs to the Special Issue New Insights into Motor Neuron Diseases)
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12 pages, 1629 KiB  
Article
Acoustic Voice Analysis as a Useful Tool to Discriminate Different ALS Phenotypes
by Giammarco Milella, Diletta Sciancalepore, Giada Cavallaro, Glauco Piccirilli, Alfredo Gabriele Nanni, Angela Fraddosio, Eustachio D’Errico, Damiano Paolicelli, Maria Luisa Fiorella and Isabella Laura Simone
Biomedicines 2023, 11(9), 2439; https://doi.org/10.3390/biomedicines11092439 - 31 Aug 2023
Cited by 3 | Viewed by 1622
Abstract
Approximately 80–96% of people with amyotrophic lateral sclerosis (ALS) become unable to speak during the disease progression. Assessing upper and lower motor neuron impairment in bulbar regions of ALS patients remains challenging, particularly in distinguishing spastic and flaccid dysarthria. This study aimed to [...] Read more.
Approximately 80–96% of people with amyotrophic lateral sclerosis (ALS) become unable to speak during the disease progression. Assessing upper and lower motor neuron impairment in bulbar regions of ALS patients remains challenging, particularly in distinguishing spastic and flaccid dysarthria. This study aimed to evaluate acoustic voice parameters as useful biomarkers to discriminate ALS clinical phenotypes. Triangular vowel space area (tVSA), alternating motion rates (AMRs), and sequential motion rates (SMRs) were analyzed in 36 ALS patients and 20 sex/age-matched healthy controls (HCs). tVSA, AMR, and SMR values significantly differed between ALS and HCs, and between ALS with prevalent upper (pUMN) and lower motor neuron (pLMN) impairment. tVSA showed higher accuracy in discriminating pUMN from pLMN patients. AMR and SMR were significantly lower in patients with bulbar onset than those with spinal onset, both with and without bulbar symptoms. Furthermore, these values were also lower in patients with spinal onset associated with bulbar symptoms than in those with spinal onset alone. Additionally, AMR and SMR values correlated with the degree of dysphagia. Acoustic voice analysis may be considered a useful prognostic tool to differentiate spastic and flaccid dysarthria and to assess the degree of bulbar involvement in ALS. Full article
(This article belongs to the Special Issue New Insights into Motor Neuron Diseases)
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