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CD36 is a highly glycosylated integral membrane protein that belongs to the scavenger receptor class B family and regulates the pathological progress of metabolic diseases. CD36 was recently found to be widely expressed in various cell types in the nervous system, including endothelial cells, pericytes, astrocytes, and microglia. CD36 mediates a number of regulatory processes, such as endothelial dysfunction, oxidative stress, mitochondrial dysfunction, and inflammatory responses, which are involved in many central nervous system diseases, such as stroke, Alzheimer's disease, Parkinson's disease, and spinal cord injury. CD36 antagonists can suppress CD36 expression or prevent CD36 binding to its ligand, thereby achieving inhibition of CD36-mediated pathways or functions. Here, we reviewed the mechanisms of action of CD36 antagonists, such as Salvianolic acid B, tanshinone IIA, curcumin, sulfosuccinimidyl oleate, antioxidants, and small-molecule compounds. Moreover, we predicted the structures of binding sites between CD36 and antagonists. These sites can provide targets for more efficient and safer CD36 antagonists for the treatment of central nervous system diseases.
Excessive induction of inflammatory and immune responses is widely considered as one of vital factors contributing to the pathogenesis and progression of central nervous system (CNS) diseases. Neutrophils are well-studied members of inflammatory and immune cell family, contributing to the innate and adaptive immunity. Neutrophil-released neutrophil extracellular traps (NETs) play an important role in the regulation of various kinds of diseases, including CNS diseases. In this review, current knowledge on the biological features of NETs will be introduced. In addition, the role of NETs in several popular and well-studied CNS diseases including cerebral stroke, Alzheimer's disease, multiple sclerosis, amyotrophic lateral sclerosis (ALS), and neurological cancers will be described and discussed through the reviewing of previous related studies.
The complement system plays critical roles in development, homeostasis, and regeneration in the central nervous system (CNS) throughout life; however, complement dysregulation in the CNS can lead to damage and disease. Complement proteins, regulators, and receptors are widely expressed throughout the CNS and, in many cases, are upregulated in disease. Genetic and epidemiological studies, cerebrospinal fluid (CSF) and plasma biomarker measurements and pathological analysis of post-mortem tissues have all implicated complement in multiple CNS diseases including multiple sclerosis (MS), neuromyelitis optica (NMO), neurotrauma, stroke, amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). Given this body of evidence implicating complement in diverse brain diseases, manipulating complement in the brain is an attractive prospect; however, the blood-brain barrier (BBB), critical to protect the brain from potentially harmful agents in the circulation, is also impermeable to current complement-targeting therapeutics, making drug design much more challenging. For example, antibody therapeutics administered systemically are essentially excluded from the brain. Recent protocols have utilized "Trojan horse" techniques to transport therapeutics across the BBB or used osmotic shock or ultrasound to temporarily disrupt the BBB. Most research to date exploring the impact of complement inhibition on CNS diseases has been in animal models, and some of these studies have generated convincing data; for example, in models of MS, NMO, and stroke. There have been a few recent clinical trials of available anti-complement drugs in CNS diseases associated with BBB impairment, for example the use of the anti-C5 monoclonal antibody (mAb) eculizumab in NMO, but for most CNS diseases there have been no human trials of anti-complement therapies. Here we will review the evidence implicating complement in diverse CNS disorders, from acute, such as traumatic brain or spine injury, to chronic, including demyelinating, neuroinflammatory, and neurodegenerative diseases. We will discuss the particular problems of drug access into the CNS and explore ways in which anti-complement therapies might be tailored for CNS disease.
Studies recently accomplished on the Enteric Nervous System have shown that chronic degenerative diseases affect the Enteric Glial Cells (EGC) and, thus, the development of recognition methods able to identify whether or not the EGC are affected by these type of diseases may be helpful in its diagnoses. In this work, we propose the use of pattern recognition and machine learning techniques to evaluate if a given animal EGC image was obtained from a healthy individual or one affect by a chronic degenerative disease. In the proposed approach, we have performed the classification task with handcrafted features and deep learning-based techniques, also known as non-handcrafted features. The handcrafted features were obtained from the textural content of the ECG images using texture descriptors, such as the Local Binary Pattern (LBP). Moreover, the representation learning techniques employed in the approach are based on different Convolutional Neural Network (CNN) architectures, such as AlexNet and VGG16, with and without transfer learning. The complementarity between the handcrafted and non-handcrafted features was also evaluated with late fusion techniques. The datasets of EGC images used in the experiments, which are also contributions of this paper, are composed of three different chronic degenerative diseases: Cancer, Diabetes Mellitus, and Rheumatoid Arthritis. The experimental results, supported by statistical analysis, show that the proposed approach can distinguish healthy cells from the sick ones with a recognition rate of 89.30% (Rheumatoid Arthritis), 98.45% (Cancer), and 95.13% (Diabetes Mellitus), being achieved by combining classifiers obtained on both feature scenarios.
Neurological disorders are a massive challenge for modern medicine. Apart from the fact that this group of diseases is the second leading cause of death worldwide, the majority of patients have no access to any possible effective and standardized treatment after being diagnosed, leaving them and their families helpless. This is the reason why such great emphasis is being placed on the development of new, more effective methods to treat neurological patients. Regenerative medicine opens new therapeutic approaches in neurology, including the use of cell-based therapies. In this review, we focus on summarizing one of the cell sources that can be applied as a multimodal treatment tool to overcome the complex issue of neurodegeneration-mesenchymal stem cells (MSCs). Apart from the highly proven safety of this approach, beneficial effects connected to this type of treatment have been observed. This review presents modes of action of MSCs, explained on the basis of data from vast in vitro and preclinical studies, and we summarize the effects of using these cells in clinical trial settings. Finally, we stress what improvements have already been made to clarify the exact mechanism of MSCs action, and we discuss potential ways to improve the introduction of MSC-based therapies in clinics. In summary, we propose that more insightful and methodical optimization, by combining careful preparation and administration, can enable use of multimodal MSCs as an effective, tailored cell therapy suited to specific neurological disorders.
Manganese-enhanced magnetic resonance imaging (MEMRI) relies on the strong paramagnetism of Mn2+. Mn2+ is a calcium ion analog and can enter excitable cells through voltage-gated calcium channels. Mn2+ can be transported along the axons of neurons via microtubule-based fast axonal transport. Based on these properties, MEMRI is used to describe neuroanatomical structures, monitor neural activity, and evaluate axonal transport rates. The application of MEMRI in preclinical animal models of central nervous system (CNS) diseases can provide more information for the study of disease mechanisms. In this article, we provide a brief review of MEMRI use in CNS diseases ranging from neurodegenerative diseases to brain injury and spinal cord injury.
In this article, we review signal transduction pathways through which acupuncture treats nervous system diseases. We electronically searched the databases, including PubMed, MEDLINE, clinical Key, the Cochrane Library, and the China National Knowledge Infrastructure from their inception to December 2018 using the following MeSH headings and keywords alone or in varied combination: acupuncture, molecular, signal transduction, genetic, cerebral ischemic injury, cerebral hemorrhagic injury, stroke, epilepsy, seizure, depression, Alzheimer's disease, dementia, vascular dementia, and Parkinson's disease. Acupuncture treats nervous system diseases by increasing the brain-derived neurotrophic factor level and involves multiple signal pathways, including p38 MAPKs, Raf/MAPK/ERK 1/2, TLR4/ERK, PI3K/AKT, AC/cAMP/PKA, ASK1-JNK/p38, and downstream CREB, JNK, m-TOR, NF-κB, and Bcl-2/Bax balance. Acupuncture affects synaptic plasticity, causes an increase in neurotrophic factors, and results in neuroprotection, cell proliferation, antiapoptosis, antioxidant activity, anti-inflammation, and maintenance of the blood-brain barrier.
Quantifying O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation plays an essential role in assessing the potential efficacy of alkylating agents in the chemotherapy of malignant gliomas. MGMT promoter methylation is considered to be a characteristic of subgroups of certain malignancies but has also been described in various peripheral inflammatory diseases. However, MGMT promoter methylation levels have not yet been investigated in non-neoplastic brain diseases. This study demonstrates for the first time that one can indeed detect slightly enhanced MGMT promoter methylation in individual cases of inflammatory demyelinating CNS diseases such as multiple sclerosis and progressive multifocal leucencephalopathy (PML), as well as in other demyelinating diseases such as central pontine and exptrapontine myelinolysis, and diseases with myelin damage such as Wallerian degeneration. In this context, we identified a reduction in the expression of the demethylase TET1 as a possible cause for the enhanced MGMT promoter methylation. Hence, we show for the first time that MGMT hypermethylation occurs in chronic diseases that are not strictly associated to distinct pathogens, oncogenic viruses or neoplasms but that lead to damage of the myelin sheath in various ways. While this gives new insights into epigenetic and pathophysiological processes involved in de- and remyelination, which might offer new therapeutic opportunities for demyelinating diseases in the future, it also reduces the specificity of MGMT hypermethylation as a tumor biomarker.
Kaempferol (KPF) is a flavonoid antioxidant found in fruits and vegetables. Many studies have described the beneficial effects of dietary KPF in reducing the risk of chronic diseases, especially cancer. Nevertheless, little is known about the cellular and molecular mechanisms underlying KPF actions in the central nervous system (CNS). Also, the relationship between KPF structural properties and their glycosylation and the biological benefits of these compounds is unclear. The aim of this study was to review studies published in the PubMed database during the last 10 years (2010-2020), considering only experimental articles that addressed the isolated cell effect of KPF (C15H10O6) and its derivatives in neurological diseases such as Alzheimer's disease, Parkinson, ischemia stroke, epilepsy, major depressive disorder, anxiety disorders, neuropathic pain, and glioblastoma. 27 publications were included in the present review, which presented recent advances in the effects of KPF on the nervous system. KPF has presented a multipotential neuroprotective action through the modulation of several proinflammatory signaling pathways such as the nuclear factor kappa B (NF-kB), p38 mitogen-activated protein kinases (p38MAPK), serine/threonine kinase (AKT), and β-catenin cascade. In addition, there are different biological benefits and pharmacokinetic behaviors between KPF aglycone and its glycosides. The antioxidant nature of KPF was observed in all neurological diseases through MMP2, MMP3, and MMP9 metalloproteinase inhibition; reactive oxygen species generation inhibition; endogenous antioxidants modulation as superoxide dismutase and glutathione; formation and aggregation of beta-amyloid (β-A) protein inhibition; and brain protective action through the modulation of brain-derived neurotrophic factor (BDNF), important for neural plasticity. In conclusion, we suggest that KPF and some glycosylated derivatives (KPF-3-O-rhamnoside, KPF-3-O-glucoside, KPF-7-O-rutinoside, and KPF-4'-methyl ether) have a multipotential neuroprotective action in CNS diseases, and further studies may make the KPF effect mechanisms in those pathologies clearer. Future in vivo studies are needed to clarify the mechanism of KPF action in CNS diseases as well as the impact of glycosylation on KPF bioactivity.
Astrocyte activation plays an important role during disease-induced inflammatory response in the brain. Exosomes in the brain could be released from bone marrow (BM)-derived stem cells, neuro stem cells (NSC), mesenchymal stem cells (MSC), etc. We summarized that exosomes release and transport signaling to the target cells, and then produce function. Furthermore, we discussed the pathological interactions between astrocytes and other brain cells, which are related to brain diseases such as stroke, Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS) disease, multiple sclerosis (MS), psychiatric, traumatic brain injury (TBI), etc. We provide up-to-date, comprehensive and valuable information on the involvement of exosomes in brain diseases, which is beneficial for basic researchers and clinical physicians.
Cytokines are potent mediators of cellular communication that have crucial roles in the regulation of innate and adaptive immunoinflammatory responses. Clear evidence has emerged in recent years that the dysregulated production of cytokines may in itself be causative in the pathogenesis of certain immunoinflammatory disorders. Here we review current evidence for the involvement of two different cytokines, IFN-α and IL-6, as principal mediators of specific immunoinflammatory disorders of the CNS. IFN-α belongs to the type I IFN family and is causally linked to the development of inflammatory encephalopathy exemplified by the genetic disorder, Aicardi-Goutières syndrome. IL-6 belongs to the gp130 family of cytokines and is causally linked to a number of immunoinflammatory disorders of the CNS including neuromyelitis optica, idiopathic transverse myelitis and genetically linked autoinflammatory neurological disease. In addition to clinical evidence, experimental studies, particularly in genetically engineered mouse models with astrocyte-targeted, CNS-restricted production of IFN-α or IL-6 replicate many of the cardinal neuropathological features of these human cytokine-linked immunoinflammatory neurological disorders giving crucial evidence for a direct causative role of these cytokines and providing further rationale for the therapeutic targeting of these cytokines in neurological diseases where indicated.
Nowadays, the development of diagnosis and treatment technology is constantly changing the pedigree and classification of nervous system diseases. Analyzing changes in earlier disease pedigrees can help us understand the changes involved in disease diagnosis from a macro perspective, as well as predict changes in later disease pedigrees and the direction of diagnosis and treatment. The inpatients of the neurology department from January 2012 to December 2020 in Hunan Children's Hospital were retrospectively analyzed. There were 36,777 patients enrolled in this study. The next analysis was based on factors like age, gender, length of stay (LoS), number of patients per month and per year (MNoP and ANoP, respectively), and average daily hospital cost (ADHE). To evaluate the characteristics of neurological diseases, we applied a series of statistical tools such as numerical characteristics, boxplots, density charts, one-way ANOVA, Kruskal-Wallis tests, time-series plots, and seasonally adjusted indices. The statistical analysis of neurological diseases led to the following conclusions: First, children having neurological illnesses are most likely to develop them between the ages of 4 and 8 years. Benign intracranial hypertension was the youngest mean age of onset among the various neurologic diseases, and most patients with bacterial intracranial infection were young children. Some diseases have a similar mean age of onset, such as seizures (gastroenteritis/diarrhea) and febrile convulsions. Second, women made up most patients with autoimmune diseases of the central nervous system. Treatment options for inherited metabolic encephalopathy and epilepsy are similar, but they differ significantly for viral intracranial infection. Some neurologic diseases were found to have seasonal variations; for example, infectious diseases of the central nervous system were shown to occur more commonly in the warm season, whereas, autoimmune diseases primarily appeared in the autumn and winter months. Additionally, the number of patients admitted to hospitals with intracranial infections and encephalopathy has dramatically dropped recently, but the number of patients with autoimmune diseases of the central nervous system and hereditary metabolic encephalopathy has been rising year over year. Finally, we discovered apparent polycentric distributions in various illnesses' density distributions. The study offered an epidemiological basis for common nervous system diseases, including evidence from age of onset, number of cases, and so on. The pedigree of nervous system diseases has significantly changed. The proportion of patients with neuroimmune diseases and genetic metabolic diseases is rising while the number of patients with infection-related diseases and uncertain diagnoses is decreasing. The existence of a disease multimodal model suggests that there is still a lack of understanding of many diseases' diagnosis and treatment, which needs to be improved further because accurate diagnosis aids in the formulation of individualized treatment plans and the allocation of medical resources; additionally, there is still a lack of effective treatment for most genetic diseases. The seasonal characteristics of nervous system diseases suggest the need for the improvement of sanitation, living conditions, and awareness of daily health care.
Recently, a rising interest is given to neuroimmune communication in physiological and neuropathological conditions. Meningeal immunity is a complex immune environment housing different types of immune cells. Here, we focus on meningeal T cells, possibly the most explored aspect of neuro-immune cell interactions. Emerging data have shown that meningeal T cells play a crucial role in the pathogenesis of several neurodegenerative disorders, including multiple sclerosis, Alzheimer's, Parkinson's, and Huntington's diseases. This review highlights how meningeal T cells may contribute to immune surveillance of the central nervous system (CNS) and regulate neurobehavioral functions through the secretion of cytokines. Overall, this review assesses the recent knowledge of meningeal T cells and their effects on CNS functioning in both health and disease conditions and the underlying mechanisms.
Myriad infectious and noninfectious causes of encephalomyelitis (EM) have similar clinical manifestations, presenting serious challenges to diagnosis and treatment. Metabolomics of cerebrospinal fluid (CSF) was explored as a method of differentiating among neurological diseases causing EM using a single CSF sample.
The blood-brain barrier (BBB) is a selectively permeable barrier separating the periphery from the central nervous system (CNS). The BBB restricts the flow of most material into and out of the CNS, including many drugs that could be used as potent therapies. BBB permeability is modulated by several cells that are collectively called the neurovascular unit (NVU). The NVU consists of specialized CNS endothelial cells (ECs), pericytes, astrocytes, microglia, and neurons. CNS ECs maintain a complex "seal" via tight junctions, forming the BBB; breakdown of these tight junctions leads to BBB disruption. Pericytes control the vascular flow within capillaries and help maintain the basal lamina. Astrocytes control much of the flow of material that has moved beyond the CNS EC layer and can form a secondary barrier under inflammatory conditions. Microglia survey the border of the NVU for noxious material. Neuronal activity also plays a role in the maintenance of the BBB. Since astrocytes, pericytes, microglia, and neurons are all able to modulate the permeability of the BBB, understating the complex contributions of each member of the NVU will potentially uncover novel and effective methods for delivery of neurotherapies to the CNS.
Background: Diseases of the nervous system are widely considered to be caused by genetic mutations, and they have been shown to share pathogenic genes. Discovering the shared mechanisms of these diseases is useful for designing common treatments. Method: In this study, by reviewing 518 articles published after 2007 on 20 diseases of the nervous system, we compiled data on 1607 mutations occurring in 365 genes, totals that are 1.9 and 3.2 times larger than those collected in the Clinvar database, respectively. A combination with the Clinvar data gives 2434 pathogenic mutations and 424 genes. Using this information, we measured the genetic similarities between the diseases according to the number of genes causing two diseases simultaneously. Further detection was carried out on the similarity between diseases in terms of cell types. Disease-related cell types were defined as those with disease-related gene enrichment among the marker genes of cells, as ascertained by analyzing single-cell sequencing data. Enrichment profiles of the disease-related genes over 25 cell types were constructed. The disease similarity in terms of cell types was obtained by calculating the distances between the enrichment profiles of these genes. The same strategy was applied to measure the disease similarity in terms of brain regions by analyzing the gene expression data from 10 brain regions. Results: The disease similarity was first measured in terms of genes. The result indicated that the proportions of overlapped genes between diseases were significantly correlated to the DMN scores (phenotypic similarity), with a Pearson correlation coefficient of 0.40 and P-value = 6.0×10-3. The disease similarity analysis for cell types identified that the distances between enrichment profiles of the disease-related genes were negatively correlated to the DMN scores, with Spearman correlation coefficient = -0.26 (P-value = 1.5 × 10-2). However, the brain region enrichment profile distances of the disease-related genes were not significantly correlated with the DMN score. Besides the similarity of diseases, this study identified novel relationships between diseases and cell types. Conclusion: We manually constructed the most comprehensive dataset to date for genes with mutations related to 20 nervous system diseases. By using this dataset, the similarities between diseases in terms of genes and cell types were found to be significantly correlated to their phenotypic similarity. However, the disease similarities in terms of brain regions were not significantly correlated with the phenotypic similarities. Thus, the phenotypic similarity between the diseases is more likely to be caused by dysfunctions of the same genes or the same types of neurons rather than the same brain regions. The data are collected into the database NeurodisM, which is available at http://biomed-ai.org/neurodism.
Several central nervous system diseases are associated with disturbed cerebrospinal fluid (CSF) flow patterns and have typically been characterized in vivo by phase-contrast magnetic resonance imaging (MRI). This technique is, however, limited by its applicability in space and time. Phase-contrast MRI has yet to be compared directly with CSF tracer enhanced imaging, which can be considered gold standard for assessing long-term CSF flow dynamics within the intracranial compartment.
Network medicine has been applied successfully to elicit the structure of large-scale molecular interaction networks. Its main proponents have claimed that this approach to integrative medical investigation should make it possible to identify functional modules of interacting molecular biological units as well as interactions themselves. This paper takes a significant step in this direction. Based on a large-scale analysis of the nervous system molecular medicine literature, this study analyzes and visualizes the complex structure of associations between diseases on the one hand and all types of molecular substances on the other. From this analysis it then identifies functional co-association groups consisting of several types of molecular substances, each consisting of substances that exhibit a pattern of frequent co-association with similar diseases. These groups in turn exhibit interlinking in a complex pattern, suggesting that such complex interactions between functional molecular modules may play a role in disease etiology. We find that the patterns exhibited by the networks of disease - molecular substance associations studied here correspond well to a number of recently published research results, and that the groups of molecular substances identified by statistical analysis of these networks do appear to be interesting groups of molecular substances that are interconnected in identifiable and interpretable ways. Our results not only demonstrate that networks are a convenient framework to analyze and visualize large-scale, complex relationships among molecular networks and diseases, but may also provide a conceptual basis for bridging gaps in experimental and theoretical knowledge.
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