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Enregistrement W4324148032 · doi:10.3389/fnmol.2023.1167747

Editorial: Biomarkers and therapeutic targets in the pathogenesis of neurodegenerative diseases: Functions, implications, and perspectives

2023· editorial· en· W4324148032 sur OpenAlexaff
Junhui Wang

Notice bibliographique

RevueFrontiers in Molecular Neuroscience · 2023
Typeeditorial
Langueen
DomaineMedicine
ThématiqueAlzheimer's disease research and treatments
Établissements canadiensMount Sinai HospitalSinai Health SystemLunenfeld-Tanenbaum Research Institute
Organismes subventionnairesnon disponible
Mots-clésPathogenesisNeuroscienceMedicineNeurodegenerationDiseaseBiologyPathology

Résumé

récupéré en direct d'OpenAlex

RNAs etc.) in NDs and their potentials as disgnostic biomarkers and therapeutic targets in these diseases.Adult Degenerative Scoliosis (ADS) is a debilitating spine condition with asymmetric spinal degeneration and multiaxial rotational deformity due to progressive degenerative changes (Philip et al., 2017). A research article from Shi et al. deployed whole-transcriptome sequencing to explore the difference between common disc degeneration and ADS, which could indicate the potential mechanism of ADS. In their study, varieties of RNA, including circRNA, long noncoding RNAs (lncRNA), miRNA, and mRNA expression profiles were investigated.Differentially expressed (DE) RNAs were conspicuously identified in ADS group compared to their counterparts in disc herniation group: 3322 DE mRNAs,221 DE lncRNAs,20 DE miRNAs,and 15 DE circRNAs in the ADS. Among RNAs, most of them were relevant with the biological function of endocytosis, apoptosis, etc. Therefore, this study provided the evidences supporting potential role of non-coding RNAs in ADS aetiology.He et al. summarized the recent progress of research on exploring the roles of non-coding RNAs in NDs (AD, PD, TBI, etc.) by especially focusing on circular RNAs (circRNAs). With a closed circular structure, CircRNAs are more stable in cells than their liner mRNA counterparts, and becoming very promising candidates for gene therapy (Wu et al., 2022). The review discussed the sponge function of circRNAs, emphasized the fact that individual circRNA could sponge different miRNAs and actively interacted with other mRNAs and noncoding RNAs and postulated a possible circRNA-miRNA-mRNA network which could be part of complicated regulation system during the development of NDs.Noncoding RNAs could also function as potential messengers between neurons and glial cells and circulate in the body fluids for communication since of their ability to cross the blood-brain barrier. Wang et al. has another review article delineated the exosomal noncoding RNAs including miRNAs, lncRNAs, circRNAs, and PIWI-interacting RNAs (piRNAs) about their role in Central Nervous System (CNS) diseases, especially NDs (AD, PD, etc.). Exosomes in the niches of CNS have crucial impacts on the interplay between cells (neuron-neuron, neuron-glia, etc.) by carrying small molecules, including RNAs. This review summarized the recent research progress of the exosomal noncoding RNAs in CNS disorders and discussed the potentials of the small molecules containing exosomes as diagnostic biomarkers and therapeutic applications.Fluid biomarkers (soluble amyloid, tau and α-synuclein, etc.) have been the hot topics in the decade for the research of NDs with the hope of finding diagnostic markers. Further understanding of exosomal noncoding RNAs will certainly make these molecules to be potential candidates in this field.Autophagy is the major intracellular mechanism for degrading accumulated misfolded proteins.The defect of autophagy pathways has been proved be closely associated with NDs at different stages (Fang et al., 2018). Basri et al. provided another literature review updating the recent research on how circRNAs participated in the regulation mechanism of NDs to make the autophagy cascade being orchestrated in a systemic way. The idea derived from the facts that circRNAs tendes to accumulate in the aging CNS and aging is the major predisposing factor of NDs. The interplay between circRNAs, autophagy and varieties of NDs (AD, PD, ALS, HD and SMA, ect.) was profiled in this review according to the recent publications.In another report with the proteome and transcriptome studies of ischemia, He et al. used hippocampal neuronal HT22 cell line to study NMDA receptor (NMDAR) mediated excitotoxicity and NMDAR hypofunction via a ischemic insult model or deleting the receptor.NMDA receptor has complex role in cerebral ischemia by exerting both pro-death and prosurvival signaling pathways (Li et al., 2022). The data presented here was aimed to depict the proteome and transcriptome profiles among "hyper" and "hypo" NMDA receptors. Interesting expression patterns of protein and RNA in these two groups were identified, which could provide indication for future study of the dynamic change of NMDA receptor during ischemic insult.Transplantation of neuronal stem cells in NDs has shown promising results and the stem cellbased therapy against NDs is the hot topic in the current therapeutic area of NDs (Singh et al., 2016). A research article from Gupta et al. found imidazole-based GSK-3β inhibitors could facilate the transdifferentiation of human mesenchymal stem cells (MSC) to neurons, which provided a novel platform with a potential single-molecule formula instead of a "chemical cocktail" solution to induce the transdifferentiation.Cerebral small vessel disease (CSVD) is considered as the most common etiology of vascular dementia or cognitive dysfunction and contributes to the pathogenesis of AD (Hae et al., 2020).Zou et al. performed the gene differential analysis of AD and CSVD patients from public databases to explore the underlying molecular mechanisms associated with both diseases.Differentially expressed genes (DEGs) were identified and most of DEGs were linked to endocytosis and oxytocin signaling pathways. Among the DEGs, SIRT1, a obesity and metabolic related gene was postulated as a key gene. These results were reasonable since aberrant lipid metabolism is strong risk for AD. Take together, this Research Topic mostly highlights the novel mechanism of NDs by focusing multiple types of RNAs, especially noncoding RNA and circular RNAs. The collected articles here will add significant value on further understanding of NDs via novel perspectives.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,745
Score d'incertitude au seuil0,808

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,294
Écart entre enseignants0,279 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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