Neurobiology of Disease最新文献

Methamphetamine (METH) abuse increases worldwide. In addition to its acute life-threatening effects, METH is toxic for dopaminergic neurons, increasing the risk of developing Parkinson's disease. The impact of repeated METH binge consumption on dopaminergic and neurotoxicity markers remains unclear. We exposed mice to a repeated "binge-like" METH regime, consisting of three doses over a 6 h interval, repeated three times with 14-day intervals. After the first binge, spontaneous motor activity decreased markedly but remained normal after subsequent binges. Following the first binge, we observed a 25 % loss of nigral dopaminergic cell bodies and significant axon terminal damage as assessed through striatal silver staining, with minimal further degeneration after additional binges. Dopaminergic markers were substantially depleted after the first and second binges, despite partial recovery between binges, dropping to below 20 % of control levels. By one day after the third binge, tyrosine hydroxylase (TH) and vesicular monoamine transporter 2 (VMAT2) stabilized at 50-60 % of control levels, but the dopamine transporter (DAT) remained at only 25 %, showing less recovery. These changes were accompanied by an evolving neuroinflammation pattern, with a transient microglial surge after the first binge and persistent astroglial and temperature responses. Overall, our findings indicate partial recovery of dopaminergic markers and the development of tolerance to METH neurotoxicity. The robust reduction of DAT after the first binge may contribute to this tolerance to subsequence binges by limiting METH entry into neurons thereby mitigating its neurotoxic effects.

Mouse models of Fragile X Syndrome (FXS) have demonstrated impairments in sensory-evoked neuronal firing of excitatory and inhibitory neurons. Homeostatic plasticity does not compensate for these changes in activity. Previous work has shown that impairments in homeostatic plasticity mechanisms are observed in FXS, including deficits in synaptic scaling and intrinsic excitability. Here, we aimed to examine how sensory integration changes in vivo following a homeostatic perturbation, unilateral whisker deprivation (WD), in an Fmr1 knock out (KO) mouse model. We used multi-electrode array recordings of neurons in the lightly anesthetized juvenile mouse somatosensory cortex, and found that whisker-evoked responses in layer 5/6 (L5/6) excitatory neurons were weaker in the KO compared to the wild-type (WT). We show that WD in the WT leads to a compensatory increase in the proportion of L5/6 somatosensory neurons that were recruited following whisker stimulation, but this did not occur in the KO. On the other hand, certain compensatory responses were observed in the KO following WD; the firing rate of the whisker-responsive neurons was increased following both a 2- and 7-day WD. Similar to excitatory neurons, we observed increased recruitment of fast spiking (presumed inhibitory) neurons following WD in the WT, but not KO. Our results suggest that certain homeostatic mechanisms are impaired in the KO, while others appear to remain intact. Compromised homeostatic plasticity in development could influence adult sensory processing and long-term cortical organization.

Background: Glioblastoma (GB) is incurable with a dismal prognosis. Single-cell RNA sequencing (scRNA-seq) is a pivotal tool for studying tumor heterogeneity. The dysregulation of the urea cycle (UC) frequently occurs in tumors, but its characteristics in GB have not been illuminated. This study integrated scRNA-seq UC scores and bulk RNA-seq data to build a GB prognostic model.

Methods: Samples from 3 pairs of GB patients were collected for scRNA-seq analysis. GB-mRNA expression data, clinical data, and SNV mutation data were sourced from the Cancer Genome Atlas (TCGA). GB-mRNA expression data and clinical data were downloaded from the Chinese Glioma Genome Atlas (CGGA). GB RNA-seq data and clinical data were obtained from Gene Expression Omnibus (GEO) database. The R package Seurat was applied for scRNA-seq data processing. UMAP and TSNE were used for dimensionality reduction. UCell enrichment method was employed to score each astrocyte. Monocle algorithm was applied for pseudotime trajectory analysis. CellChat R package was applied for cell communication analysis. Cell labeling was performed on the results of the nine subclusters of astrocytes. The GSE138794 dataset was used to validate the results of single-cell classification. For bulk RNA-seq, univariate Cox and LASSO analyses were undertaken to screen prognostic genes, while multivariate Cox regression analysis was applied to set up a prognostic model. The differences between high-risk (HR) and low-risk (LR) groups were studied in terms of immune infiltration, sensitivity to anti-tumor drugs, etc. We verified the effect of the marker gene on the function of GB cells at the cellular level.

Results: The analysis of scRNA-seq data yielded 7 core cell types. Further clustering of the largest proportion of astrocytes resulted in 9 subclusters. UC score and pseudotime analysis revealed the heterogeneity and differentiation process among subclusters. Subcluster 8 was annotated as an immature astrocyte (marker: CXCL8), and this cell cluster had a higher UC score. The results were validated in the GSE138794 dataset. Combining UC scores, we performed univariate Cox and LASSO to select prognostic genes on bulk RNA-seq data. A prognostic model based on 5 feature genes (RGS4, CTSB, SERPINE2, ID1, and CALD1) was established through multivariate Cox analysis. In addition, patients in the HR group had higher immune infiltration and immune function. Final cell experiments demonstrated that 5 feature genes were highly expressed in GB cells. CALD1 promoted the malignant phenotype of GB cells.

Conclusion: We set up a novel prognostic model for predicting the survival of GB patients by integrating bulk RNA-seq and scRNA-seq data. The risk score was closely correlated with immune infiltration and drug sensitivity, pinpointing it as a promising independent prognostic factor.

Dentatorubral-pallidoluysian atrophy (DRPLA) is a neurodegenerative disorder that presents with ataxia, dementia and epilepsy. As a member of the polyglutamine family of diseases, DRPLA is caused by abnormal CAG triplet expansion beyond 48 repeats in the protein-coding region of ATROPHIN 1 (ATN1), a transcriptional co-repressor. To better understand DRPLA, we generated new Drosophila lines that can be induced to express full-length, human ATN1 with a normal (Q7) or pathogenic (Q88) repeat in a variety of cells, including neuronal, glial or any other type of tissue. Expression of ATN1 is toxic, with the polyglutamine-expanded version being consistently more problematic than wild-type ATN1. Fly motility, longevity and internal structures are negatively impacted by pathogenic ATN1. RNA-seq identified altered protein quality control and immune pathways in the presence of pathogenic ATN1. Based on these data, we conducted genetic experiments that confirmed the role of protein quality control components that ameliorate or exacerbate ATN1 toxicity. Hsc70-3, a chaperone, arose as a likely suppressor of toxicity. VCP (a proteasome-related AAA ATPase), Rpn11 (a proteasome-related deubiquitinase) and select DnaJ proteins (co-chaperones) were inconsistently protective, depending on the tissues where they were expressed. Lastly, informed by RNA-seq data that exercise-related genes may also be involved in this model of DRPLA, we conducted short-term exercise, which improved overall fly motility. This new model of DRPLA will prove important to understanding this understudied disease and will help to identify therapeutic targets for it.

Background: This study investigated the subthalamic nucleus (STN) function and deep brain stimulation (DBS) effects on single-unit activity (SUA) in Parkinson's disease (PD) patients with dysarthria.

Methods: After presurgical speech analysis, we recorded STN neuronal activities while PD patients (n = 16) articulated Chinese Pinyin consonants. The Pinyin consonants were categorized by the manner and place of articulation for SUA cluster analysis. The cohort was then divided into normal articulation and dysarthria groups based on diadochokinetic (DDK) assessments. The STN SUA patterns, represented by the mean firing rate (FR), peak time, and response intensity during articulation, were analyzed and compared between the two groups. Finally, a stimulation cohort of 7 PD patients was included to test articulation and SUA pattern changes following intraoperative DBS.

Results: Clustering analysis of STN neuronal firing patterns demonstrated that neurons encode articulation by grouping consonants with the same manner of articulation into distinct clusters. Using k-means clustering, we further classified SUAs into two waveform types: negative spikes (type 1) and positive spikes (type 2). Dysarthria patients exhibited an increased mean FR of type 1 spikes and a reduced response intensity of type 2 spikes. During intraoperative stimulation, PD patients showed accelerated DDK, accompanied by a decrease in type 1 mean FR and an increase in type 2 mean FR.

Conclusion: Our findings indicate the crucial role of the STN in consonant encoding and dysarthria at the single-unit level. Both SUA firing patterns in the STN and DDK performance can be modulated by DBS.