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Visualization of multichannel surface electromyography as a map of muscle component activation
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Introduction: Modern methods of analyzing surface electromyography (sEMG) from a matrix of electrodes allow for detailed muscle activation maps and interaction detection. While these activity maps show muscle response, they do not reveal muscle coordination during different gestures. Creating muscle component activity maps can aid in the development of rehabilitation programs and the creation of bionic prostheses by identifying signal localization in specific muscles. Methods: This study was conducted with healthy subjects (N=5). Trigno avanti sEMG sensors (n=8) (Delsys Inc, USA) were used, arranged in a circle on the superficial muscles of the forearm. The gestures chosen for visualization were fist clenching, finger extension, and thumb elevation. Results: When analyzing the data associated with the muscle component activation maps for the five subjects, it is possible to observe differences in the pattern of muscle co-activation depending on the gesture. During fist clenching, the largest contraction amplitude is observed in m. extensor carpi ulnaris and m. palmaris longus. For finger extension, the greatest activity was observed in m. extensor carpi ulnaris and m. extensor digitorum. Finally, for thumb elevation, m. extensor carpi radialis longus and m. extensor carpi ulnaris were the most involved, and m. palmaris longus was also consistently active. The other selected muscles were not activated, indicating precise muscle coordination to perform the different gestures. Conclusions: Forearm muscles are differentially involved in muscle signal formation. The segmentation of muscle signals allows for specific signal acquisition for further use in prosthetics and rehabilitation.

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From Childhood to Old Age: A Magnetoencephalography-Based Review of Motor Control Development

Background:

Motor control (MC) is crucial for coordinating movements, reflected by neural oscillations (NOs) such as movement-related beta desynchronization (MRBD), post-movement beta rebound (PMBR), and movement-related gamma synchrony (MRGS). Magnetoencephalography (MEG) has significantly advanced the study of brain development and MC due to its high temporal and spatial resolution. This study aims to elucidate changes in NOs throughout MC development and explore the underlying mechanisms from childhood to old age.

Methods:

A comprehensive literature search using keywords "magnetoencephalography," "motor control," "lifetime trajectory," and "aging" was conducted in Web of Science, PubMed, Scopus, PsycINFO, EBSCO, and Embase up to June 2024. Seventeen relevant studies were analyzed.

Results:

A systematic review of MEG studies revealed the following: 1) Childhood to adolescence: MC increases with enhanced MRBD in the primary motor cortex and decreased MRBD in the secondary motor cortex. Movement control improves, accompanied by enhanced PMBR and refined neural populations, leading to weakened MRGS. 2) Adolescence to early adulthood: MRBD, PMBR, and MRGS continue their trends, reaching maturity in early adulthood. 3) Early adulthood to old age: MC declines, but resting beta oscillations and MRBD are stronger than in young adults, while PMBR decreases with age.

Conclusion:

MC development follows a trajectory of growth to maturity and eventual decline with age, reflected by changes in NOs. Increased resting beta oscillations and MRBD in older adults suggest compensatory mechanisms, while PMBR and MRGS show age-related changes. Further research is needed to clarify these mechanisms.

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Elucidation of conserved genes and pathways in C. elegans as an animal model for Alzheimer's disease: A System bioinformatics approach

Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder that is primarily characterized by progressive cognitive decline and memory impairment. Caenorhabditis elegans (C. elegans), a nematode worm, is a valuable model organism because of its simplicity, genetic traceability, and well-mapped nervous system.

Methods: This study employs a systematic bioinformatics approach to identify and analyze conserved genes and pathways related to AD within the genomes of humans and C. elegans. Proteins altered in AD were obtained from NeuroPro (https://neuropro.biomedical.hosting/), including 4743 proteins.

Results: A total of 1642 genes in C. elegans orthologous to the most dysregulated AD-related genes in humans were identified, and the GO terms and pathways were compared to study the conserved pathways between the two species. A PPI network of dysregulated genes was constructed to infer the functions of AD-related orthologous genes in C. elegans. Orthologous gene protein–protein interaction (PPI) network analysis for dysregulated first neighbor genes reveals the hubs and important key regulators in C. elegans for upregulated genes are as follows: isw-1, enol-1, ruvb-2, tpi-1, eftu-2, ruvb-1, gpi-1, pgk-1, ubq-1, and let-716 for upregulated genes and rps-9, rps-18, rps-22, ubq-2, utx-1, T26E3.7, aco-2, rla-0, eef-1G, and tsfm-1 for downregulated genes.

Conclusion: Functional enrichment analysis and pathway mapping revealed the significant conservation of cellular mechanisms. Our findings highlight the utility of C. elegans as a model for AD, emphasizing the potential of bioinformatics in accentuating conserved biological processes and novel intervention strategies.

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Changes in the perception of the Müller-Lyer illusion in schizophrenic patients both at the start and during treatment
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Research in the literature suggests that patients with schizophrenia are particularly susceptible to the Müller-Lyer illusion and consider it a potential marker of vulnerability.

We hypothesized that the perception of the Müller-Lyer illusion might be influenced by the patient's mental state. To test this, we studied 12 patients with schizophrenia, aged 18 to 45 years, at both the second week (after the patient became available for contact and could perform cognitive tests) and the eighth week of therapy. Participants were asked to align two segments on a monitor screen to match in length. They were presented with both neutral segments of equal length and segments configured to produce the Müller-Lyer illusion.

Mental state was assessed using the PANSS scale. Only patients with positive symptom scores of less than 4 points were included in the study. Statistical analysis was conducted using a mixed regression model.

The study results indicated no significant differences in perception between patients at the second and eighth weeks of therapy, suggesting that the mental state during this period did not substantially influence the course of therapy. Our findings suggest that the perception of the Müller-Lyer illusion is not significantly influenced by the severity of the mental state, and that antipsychotic therapy does not appear to impact cognitive functions related to susceptibility to the Müller-Lyer illusion.

Financial statement: This work was supported by a grant from the Russian Science Foundation (project No. 22-18-00074) "Psychological mechanisms of perception and action mismatch when solving tasks under visual illusions”.

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Speech Generation using BCI

In this project, we aimed to develop a Steady-State Visually Evoked Potential (SSVEP)-based brain-computer interface (BCI) speller system to enable communication for individuals with severe physical disabilities. We utilized SSVEPs, a type of signal read from the occipital lobe of the brain in response to visual stimuli, to create an accessible and reliable solution for people with paralysis.

Our methodology involved several key components: a flicker-based data gathering interface, signal processing, and AI modeling, a prediction and auto-complete program, and a text-to-speech (TTS) API. We first worked on publicly available datasets then we gathered our own dataset using a G.Tec Unicorn Hybrid Black 8-channel EEG headset, then developed an AI model based on an unsupervised Transformer model to accurately interpret the user's intended selections.

The results of our project demonstrate the effectiveness of our SSVEP speller system. We were able to achieve 93% accuracy through our AI model on the available BETA dataset, which outperformed state-of-the-art methods. Additionally, the incorporation of prediction and auto-complete functionalities in our fully functional website further enhanced the user experience. We believe our work can provide a lifeline for severely disabled individuals, giving them a voice and improving their quality of life by reducing social and mental isolation.

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Differential expression analysis shows upregulated miRNAs that target PXN gene in glioblastoma

Glioblastoma (GBM) is the metastatic form of astrocytoma (ATC), and what is known about its biological mechanism in relation to non-coding RNA (ncRNA) is still unclear, especially in relation to microRNAs (miRNAs). Therefore, this research studies the presence of differentially expressed miRNAs (DEMs) in GBM compared to ATC to assess how these ncRNAs may behave in this type of metastatic neoplasm. Differential expression analysis (DEA) was performed on 155 samples of primary GBM and 194 samples of primary ATC tumor in miRNA data from TCGA. A DESeq2 package was used and DEMs were considered with Log2FoldChange = 1 (downregulated < -1 and upregulated > 1), and the p-value was adjusted using the Benjamini--Hochberg (BH) method (< 0.05). For functional verification and target gene binding, we took the DEMs to miRTargetLink 2.0, and only strongly validated miRNAs were accepted. Three DEMs were found to be upregulated (hsa-miR-210, hsa-miR-27b, and hsa-miR-145), while two were downregulated (hsa-mir-573 and hsa-miR-125b-1). After the input of the DEMs into miRTargetLink 2.0, one gene appears to be regulated by two of the upregulated miRNAs (hsa-miR-145 and hsa-miR-27b): the PXN gene. PXN is associated with glial cell junction and adhesion, promoting tumor invasion and, in glioma, this gene has been shown to be upregulated. Interestingly, in our study, PXN did not show any increase between GBM and ATC, which may indicate no significant difference in expression with the evolution of glioma. Here, we suggest five DEMs and a target gene of two of them that should be further explored.

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Analysis of differentially expressed miRNAs targeting mitochondrial apoptosis genes in glioblastoma compared to astrocytoma

Glioblastoma (GBM) is the metastatic stage of astrocytoma (ATC) in which several pathways act in a tumorigenic role, including apoptosis, regulated by other underlying mechanisms and molecules such as microRNAs (miRNAs). The aim of this study was to search for differentially expressed miRNAs (DEMs) in GBM when compared to ATC that may be related to the role of apoptosis. miRNAs targeted by apoptosis genes were selected using miRTargetLink 2.0. Apoptosis genes were selected from the MitoXplorer 2.0 platform, with the main aim of analyzing genes from the intrinsic (mitochondrial) pathway. Thus, differential expression analysis (DEA) was performed on 155 GBM samples and 194 ATC samples from TCGA in the R environment to check for differentially expressed miRNAs (DEMs) related to apoptosis genes. We subdivided those that are strongly validated according to miRTargetLink and both strong and weak validation. Three DEMs strongly validated were upregulated (hsa-miR-210, hsa-miR-221, and hsa-miR-145), but none were downregulated. In the broader search, besides the three DEMs highlighted, it is worth mentioning the upregulated hsa-miR-27b, while three were found to be downregulated (hsa-miR-657, hsa-miR-573, and hsa-miR-7158). The target gene in common between the four upregulated DEMs is BNIP3, a pro-apoptotic gene, suggesting a suppression of the mitochondrial apoptotic pathway in GBM compared to ATC. Regarding the downregulated genes, no common target genes were found. Thus, in addition to indicating seven target miRNAs to be studied, our work also indicates a target gene that may be correlated with a dysregulation of apoptotic activity in GBM.

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The role of the liver--brain axis in a rotenone-induced rat model of Parkinson's disease

Introduction: Recent studies investigate potential axes between the brain and peripheral organs that could be related to neurodegeneration. Emerging evidence showing the importance of the liver--brain axis in the development and prognosis of neurodegenerative diseases points to the liver as a possible critical organ in the neurodegeneration process. The present study on gene expression in the brain and liver aims to unveil molecular pathways involved in Parkinson’s disease (PD). Method: Basic levels of the cerebral and hepatic expression of genes related to α-synuclein production and transport, oxidative stress, and inflammation were assessed to reveal potential targets involved in the communication of both organs in rotenone-treated rats via a rodent model of PD as compared to control rats. Total RNA was extracted from brain and liver tissue, and the gene expression of SNCA, Nrf2, NF-κB, DJ-1, Atp13a2, LRRK2, PARK2, LRP-1 PINK1, IFN-γ, and TNF-α was determined by qPCR. Expression levels were normalized to the housekeeping gene, and the relative expression levels of their mRNAs were determined using the (2–ΔΔct) method. Result: Several genes affected in the liver of the rotenone treatment group, as compared to the control group, also demonstrated altered brain expression. Conclusion: The study suggests that changes in the liver may be involved in pathological conditions linked to PD and supports research on peripheral markers related to the liver--brain axis in this disease.

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LncRNA JINR1 regulates neuronal cell death and flavivirus replication by regulating the miR-216b-5p target gene.
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Introduction

CNS infections caused by flaviviruses, such as Japanese encephalitis virus (JEV) and West Nile viruses (WNV), lead to substantial neuroinflammation and neuronal apoptosis. Recent advancements in high-throughput sequencing techniques have revealed the emergence of numerous long non-coding RNAs (lncRNAs) as key regulators of viral infections. However, the precise role of lncRNAs in governing neuroinflammation and neuronal cell death during flavivirus infection remains inadequately understood. In our previous work, we demonstrated that the lncRNA JINR1 interacts with RNA binding protein (RBM10) and NF-κB, activating NF-κB target genes to enhance flavivirus-induced neuronal cell death and viral replication.

Methods

Cell culture, virus infection, titration, qRT-PCR, cloning and transfections, ChIP, Western blotting, and the dual luciferase assay were used.

Results and Conclusion

We found that JINR1 reduces the levels of mature, primary, and precursor miR-216b-5p in human neuronal cell lines. Mechanistically, JINR1 recruits H3K27me3 marks, reduces H3K4me3, and diminishes RNA polymerase-II recruitment at the miR-216b-5p promoter, thereby transcriptionally inhibiting the expression of miR-216b-5p. Furthermore, through dual-luciferase reporter assays, we demonstrated that JINR1 acts as a molecular sponge for miR-216b-5p, upregulating GRP78 expression through a competing endogenous RNA (ceRNA) regulatory mechanism. We are the pioneers in elucidating the regulatory function of JINR1, which involves suppressing the transcription of miR-216b-5p and serving as a ceRNA. Interestingly, we found that miR-216b-5p negatively regulates virus replication in a human neuronal cell line due to the presence of multiple binding sites in the viral genome.

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The correlation between prenatal depression, inflammation, and gut microbiota: an integrative analysis
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Prenatal depression represents a common psychological illness that affects women during pregnancy. The gut--brain axis, which encompasses bidirectional communication between the gut and the brain, is postulated to contribute to the development of depression.

This study aims to understand the relationship between intestinal microbiota, inflammation, and depression during pregnancy using a bioinformatics approach.

A total of 220 differentially expressed genes (DEGs) associated with prenatal depression and intestinal inflammation and with a fold change > 1 and an adjusted p-value < 0.05 were selected from different databases and scientific publications. The genes were analysed using STRING software to construct a PPI network, SRplot was used for GO analysis and for the identification of biological functions, and finally MetaboAnalyst was used for the analysis and interpretation of metabolomics data in biological systems.

The results demonstrated the existence of an interaction protein--protein network comprising 205 genes, which led to the identification of 16 key genes involved in neuroinflammation and immune regulation processes. The key pathways identified included cytokine--cytokine receptor interaction, IL-17, and MAPK signalling. A relationship was predicted between DEG and metabolites such as cortisol, serotonin, and tryptophan in cases of prenatal depression and neuroinflammation. Gut dysbiosis during pregnancy can potentially increase intestinal permeability, which may subsequently trigger immune responses and brain neuroinflammation.

This study has identified pivotal genes that contribute to our understanding of the molecular mechanisms underlying the development of prenatal depression and may serve as potential targets for early detection, prevention, and treatment.

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