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1.
Neurocrit Care ; 2024 Jul 24.
Article in English | MEDLINE | ID: mdl-39043983

ABSTRACT

BACKGROUND: The objective of this study was to investigate the value of mismatch negativity (MMN) and P300 event-related potentials for discriminating the consciousness state and predicting improvement of consciousness at 6 months in patients with coma and other disorders of consciousness (DOC). METHODS: We performed MMN and P300 on 42 patients with DOC with a mean onset time of 40.21 ± 19.43 days. These patients with DOC were categorized into coma, unresponsive wakefulness syndrome (UWS), minimal consciousness minus (MCS-), and minimal consciousness plus (MCS +) groups according to neurobehavioral assessment and the Coma Recovery Scale-Revised score. The primary outcome was the improvement of consciousness at 6 months in patients with DOC. We assessed the efficacy of MMN and P300 in quantitatively predicting the prognosis at 6 months and the capability of MMN and P300 parameters to differentiate between DOC. RESULTS: At least one significant difference in either MMN or P300 parameters was displayed among the DOC groups, but not between the MCS- and MCS+ groups (significance level: 0.05). Both MMN and P300 amplitudes showed desirable predictive accuracy at 6 months, with areas under the curve (AUCs) of 0.859 and 0.856, respectively. The optimal thresholds for MMN and P300 amplitudes were 2.044 and 1.095 µV. However, the combined MMN-P300 amplitude showed better 6-month predictive accuracy (AUC 0.934, 95% confidence interval 0.860-1.000), with a sensitivity of 85% and a specificity of 90.9%. CONCLUSIONS: MMN and P300 may help discriminate among coma, UWS, and MCS, but not between patients with MCS- and patients with MCS+ . The MMN amplitude, P300 amplitude, and especially combined MMN-P300 amplitude at 6 months may be interesting predictors of consciousness improvement at 6 months in patients with DOC. TRIAL REGISTRATION: Chinese Clinical Trial Registry identifier ChiCTR2400083798.

2.
Biomed Res Int ; 2020: 4980609, 2020.
Article in English | MEDLINE | ID: mdl-33123575

ABSTRACT

Epilepsy is most common in patients with tuberous sclerosis complex (TSC). However, in addition to the challenging treatment, the pathogenesis of epilepsy is still controversial. To determine the transcriptome characteristics of perituberal tissue (PT) and clarify its role in the pathogenesis of epilepsy, GSE16969 was downloaded from the GEO database for further study by comprehensive bioinformatics analysis. Identification of differentially expressed genes (DEGs), functional enrichment analysis, construction of protein-protein interaction (PPI) network, and selection of Hub genes were performed using R language, Metascape, STRING, and Cytoscape, respectively. Comparing with cortical tuber (CT), 220 DEGs, including 95 upregulated and 125 downregulated genes, were identified in PT and mainly enriched in collagen-containing extracellular matrix and positive regulation of receptor-mediated endocytosis, as well as the pathways of ECM-receptor interaction and neuroactive ligand-receptor interaction. As for normal cortex (NC), 1549 DEGs, including 30 upregulated and 1519 downregulated genes, were identified and mainly enriched in presynapse, dendrite and axon, and also the pathways of dopaminergic synapse and oxytocin signaling pathway. In the PPI network, 4 hub modules were found between PT and CT, and top 5 hub modules were selected between PT and NC. C3, APLNR, ANXA2, CD44, CLU, CP, MCHR2, HTR1E, CTSG, APP, and GNG2 were identified as Hub genes, of which, C3, CD44, ANXA2, HTR1E, and APP were identified as Hub-BottleNeck genes. In conclusion, PT has the unique characteristics different from CT and NC in transcriptome and makes us further understand its importance in the TSC-associated epilepsy.


Subject(s)
Epilepsy/genetics , Transcriptome/genetics , Tuberous Sclerosis/genetics , Computational Biology/methods , Databases, Genetic , Down-Regulation/genetics , Gene Expression Profiling/methods , Gene Ontology , Gene Regulatory Networks/genetics , Humans , Protein Interaction Maps/genetics , Signal Transduction/genetics , Up-Regulation/genetics
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