Non-neuronal cholinergic activity is potentiated in myasthenia gravis

Background: Non-neuronal acetylcholine (ACh) restricts autoimmune responses and attenuates inflammation by cholinergic anti-inflammation pathway. To date, the implication of ACh in myasthenia gravis (MG) remained unexplored. This study aimed to investigate the possible relationship between ACh levels, anti-muscle-specific tyrosine kinase (MuSK) antibody titers, main clinical features and outcomes of MG patients. Methods: We successfully measured ACh levels in human peripheral blood mononuclear cells (PBMCs) from 125 MG patients and 50 matched healthy controls by using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). We assessed the quantitative MG (QMG) scores for each patient and titered anti-MuSK antibody. Results: We found that PBMC-derived ACh level was significantly higher in MG patients, especially in patients of class III, IV-V, compared with that in controls (0.142 ± 0.108 vs. 0.075 ± 0.014 ng/million cells, p = 0.0003) according to the Myasthenia Gravis Foundation of America clinical classification. Importantly, we also found that ACh levels were positively correlated with QMG scores (r = 0.83, p \u3c 0.0001) and anti-MuSK Ab levels (r = 0.85, p \u3c 0.0001). Conclusions: Our demonstration of elevated ACh levels in PBMCs of MG patients foreshadows potential new avenues for MG research and treatment

TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentation

LiDAR semantic segmentation plays a crucial role in enabling autonomous driving and robots to understand their surroundings accurately and robustly. There are different types of methods, such as point-based, range-image-based, polar-based, and hybrid methods. Among these, range-image-based methods are widely used due to their efficiency. However, they face a significant challenge known as the ``many-to-one'' problem caused by the range image's limited horizontal and vertical angular resolution. As a result, around 20\% of the 3D points can be occluded. In this paper, we present TFNet, a range-image-based LiDAR semantic segmentation method that utilizes temporal information to address this issue. Specifically, we incorporate a temporal fusion layer to extract useful information from previous scans and integrate it with the current scan. We then design a max-voting-based post-processing technique to correct false predictions, particularly those caused by the ``many-to-one'' issue. We evaluated the approach on two benchmarks and demonstrate that the post-processing technique is generic and can be applied to various networks. We will release our code and models

Shared Biological Pathways Between Alzheimer’s Disease and Ischemic Stroke

Alzheimer’s disease (AD) and ischemic stroke (IS) are an immense socioeconomic burden worldwide. There is a possibility that shared genetic factors lead to their links at epidemiological and pathophysiological levels. Although recent genome-wide association studies (GWAS) have provided profound insights into the genetics of AD and IS, no shared genetic variants have been identified to date. This prompted us to initiate this study, which sought to identify shared pathways linking AD and IS. We took advantage of large-scale GWAS summary data of AD (17,008 AD cases and 37,154 controls) and IS (10,307 cases and 19,326 controls) to conduct pathway analyses using genetic pathways from multiple well-studied databases, including GO, KEGG, PANTHER, Reactome, and Wikipathways. Collectively, we discovered that AD and IS shared 179 GO categories (56 biological processes, 95 cellular components, and 28 molecular functions); and the following pathways: six KEGG pathways; two PANTHER pathways; four Reactome pathways; and one in Wikipathways pathway. The more fine-grained GO terms were mainly summarized into different functional categories: transcriptional and post-transcriptional regulation, synapse, endocytic membrane traffic through the endosomal system, signaling transduction, immune process, multi-organism process, protein catabolic metabolism, and cell adhesion. The shared pathways were roughly classified into three categories: immune system; cancer (NSCLC and glioma); and signal transduction pathways involving the cadherin signaling pathway, Wnt signaling pathway, G-protein signaling and downstream signaling mediated by phosphoinositides (PIPs). The majority of these common pathways linked to both AD and IS were supported by convincing evidence from the literature. In conclusion, our findings contribute to a better understanding of common biological mechanisms underlying AD and IS and serve as a guide to direct future research

Inflammation-Mediated Memory Dysfunction and Effects of a Ketogenic Diet in a Murine Model of Multiple Sclerosis

A prominent clinical symptom in multiple sclerosis (MS), a progressive disorder of the central nervous system (CNS) due to heightened neuro-inflammation, is learning and memory dysfunction. Here, we investigated the effects of a ketogenic diet (KD) on memory impairment and CNS-inflammation in a murine model of experimental autoimmune encephalomyelitis (EAE), using electrophysiological, behavioral, biochemical and in vivo imaging approaches. Behavioral spatial learning deficits were associated with motor disability in EAE mice, and were observed concurrently with brain inflammation. The KD improved motor disability in the EAE model, as well as CA1 hippocampal synaptic plasticity (long-term potentiation) and spatial learning and memory (assessed with the Morris Water Maze). Moreover, hippocampal atrophy and periventricular lesions in EAE mice were reversed in KD-treated EAE mice. Finally, we found that the increased expression of inflammatory cytokines and chemokines, as well as the production of reactive oxygen species (ROS), in our EAE model were both suppressed by the KD. Collectively, our findings indicate that brain inflammation in EAE mice is associated with impaired spatial learning and memory function, and that KD treatment can exert protective effects, likely via attenuation of the robust immune response and increased oxidative stress seen in these animals

Analysis of Density Wave Oscillations in Helically Coiled Tube Once-Through Steam Generator

Helically coiled tube Once-Through Steam Generator (H-OTSG) is one of the key equipment types for small modular reactors. The flow instability of the secondary side of the H-OTSG is particularly serious, because the working condition is in the range of low and medium pressure. This paper presents research on density wave oscillations (DWO) in a typical countercurrent H-OTSG. Based on the steady-state calculation, the mathematical model of single-channel system was established, and the transfer function was derived. Using Nyquist stability criterion of the single variable, the stability cases were studied with an in-house computer program. According to the analyses, the impact law of the geometrical parameters to the system stability was obtained. RELAP5/MOD3.2 code was also used to simulate DWO in H-OTSG. The theoretical analyses of the in-house program were compared to the simulation results of RELAP5. A correction factor was introduced to reduce the error of RELAP5 when modeling helical geometry. The comparison results agreed well which showed that the correction is effective

A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network

Effect of hyperbaric oxygen therapy on cognitive impairment after aneurysm subarachnoid hemorrhage

Purpose: To evaluate the effect of hyperbaric oxygen therapy (HBOT) on cognitive impairment after aneurysm subarachnoid hemorrhage (aSAH). Methods: The current study was carried out in a regional neurosurgical center in Taiyuan, Shanxi Province of China from January 2019 to September 2020. A total of 150 patients with persistent cognitive dysfunction at 3 months after aSAH onset were enrolled, which were randomly classified into group A (HBOT) and group B (control) via the random number table method. The outcome was evaluated by Montreal cognitive assessment (MoCA). Results: There were no significant differences between group A and group B with regard to MoCA score and proportions of normal MoCA patients at 3 months after HBOT (p > 0.05). Both groups showed no significant differences in proportions of normal MoCA patients at 6 months after HBOT (p > 0.05). However, there were significant differences between group A and group B with MoCA score of patients at 6 months after HBOT (p < 0.05). There were also significant differences in MoCA score and proportions of normal MoCA patients at 9 months after HBOT. Conclusion: HBOT alleviates cognitive impairment after aSAH, and thus may be used to manage cognitive impairment in patients after aSAH. However, further clinical trials are required prior to application in clinical practice

Upregulation Of Microglial Zeb1 Ameliorates Brain Damage After Acute Ischemic Stroke

Microglia are a key immune-competent cell type that respond to environmental and physiological changes during ischemic stroke. However, the molecular mechanisms controlling post-ischemic microglia activity are unclear. Understanding these mechanisms may ultimately reduce disease burden and allow the manipulation of microglia responses to shape the outcomes of stroke. Here, we report that, after experimentally induced stroke, ZEB1 is highly expressed in ipsilateral cerebral hemisphere, where it is upregulated mainly in microglia. Using a conditional transgenic mouse, we found that ZEB1 upregulation in microglia regulates immune responses in the CNS and alleviates brain injury after ischemic stroke. Our data indicate that ZEB1 overexpression mediates microglia responses and, in turn, inhibits the production of astrocytic CXCL1 through the TGF-β1-dependent pathway. Reduced CXCL1 leads to a decline in neutrophil infiltration into the brain, thereby reducing CNS inflammation. Our results demonstrate the importance of ZEB1 in microglia-orchestrated neuroinflammation and suggest a potential means for reducing stroke-induced neurological injury. Li et al. show that ZEB1 overexpression mediates microglia responses and, in turn, inhibits production of astrocytic CXCL1 through the TGF-β1-dependent pathway. Reduced CXCL1 leads to the decline of neutrophil infiltration into the brain. This demonstrates the importance of ZEB1 in microglia-orchestrated neuroinflammation and suggests a potential means for reducing stroke-induced neurological injury