Activation of 5-HT2C Receptor Promotes the Expression of Neprilysin in U251 Human Glioma Cells

Tian, Xiao-Lu; Yu, Linhui; Li, Wen-Qin; Hu, Yue; Yin, Ming; Wang, Zejian

doi:10.1007/s10571-014-0138-6

Cited by 6 publications

(2 citation statements)

References 40 publications

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“…In good agreement, pharmacological activation of 5-HT 4 receptors was shown to enhance short- and long-term memory function (Meneses, 2007), endorsing the hypothesis of a putative role of these drugs for the amelioration of symptomatology of depression in AD. With regard to other receptor subtypes, it has been shown that APP can be released upon activation of 5-HT 2A and 5-HT 2C , and activation of 5-HT 2C receptor promotes the expression of neprilysin, a well-characterized Aβ degrading enzymes (Tian et al., 2015). However, it should be considered that both 5-HT 2C agonists and antagonists have been evaluated as antidepressants (Cryan and Lucki, 2000; Steardo et al., 2000; Cryan et al., 2005).…”

Section: Monoamine System In Depression and Alzheimer’s Diseasementioning

confidence: 99%

Monoaminergic System Modulation in Depression and Alzheimer’s Disease: A New Standpoint?

Morgese

Trabace

2019

Front. Pharmacol.

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The prevalence of depression has dramatically increased, and it has been estimated that over 300 million people suffer from depression all over the world. Depression is highly comorbid with many central and peripheral disorders. In this regard, depressive states have been associated with the development of neurological disorders such as Alzheimer’s disease (AD). Accordingly, depression is a risk factor for AD and depressive symptomatology is common in pre-clinical AD, representing an early manifestation of this disease. Neuropsychiatric symptoms may represent prodromal symptoms of dementia deriving from neurobiological changes in specific cerebral regions; thus, the search for common biological substrates is becoming an imperative and intriguing field of research. Soluble forms of beta amyloid peptide (Aβ) have been implicated both in the development of early memory deficits and neuropsychiatric symptoms. Indeed, soluble Aβ species have been shown to induce a depressive-like phenotype in AD animal models. Alterations in monoamine content are a common feature of these neuropathologies. Interestingly, serotonergic system modulation has been implicated in alteration of Aβ production. In addition, noradrenaline is considered crucially involved in compensatory mechanisms, leading to increased Aβ degradation via several mechanisms, including microglia modulation. In further agreement, antidepressant drugs have also been shown to potentially modulate cognitive symptoms in AD and depression. Thus, the present review summarizes the main knowledge about biological and pathological substrates, such as monoamine and related molecules, commonly involved in AD and depression pathology, thus shading light on new therapeutic approaches.

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Section: Monoamine System In Depression and Alzheimer’s Diseasementioning

confidence: 99%

Monoaminergic System Modulation in Depression and Alzheimer’s Disease: A New Standpoint?

Morgese

Trabace

2019

Front. Pharmacol.

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“…As a transcript that is specifically expressed in the brain, HBII-52-14 may target the serotonin receptor (5HT-2C) in the brain, and regulate its functional methylation status [30,31]. Recent publications confirmed that the expression pattern of 5HT-2C, regulated by our identified snoRNA, is pathogenic and may be involved in the initiation and progression of low-grade glioma (LGG) [32]. This result implies that this parameter may be effective in differentiating glioma from other tumor subtypes.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Expression Pattern of snoRNAs in Different Cancer Types with Machine Learning Algorithms

Pan

Lei

Kong

et al. 2019

IJMS

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Small nucleolar RNAs (snoRNAs) are a new type of functional small RNAs involved in the chemical modifications of rRNAs, tRNAs, and small nuclear RNAs. It is reported that they play important roles in tumorigenesis via various regulatory modes. snoRNAs can both participate in the regulation of methylation and pseudouridylation and regulate the expression pattern of their host genes. This research investigated the expression pattern of snoRNAs in eight major cancer types in TCGA via several machine learning algorithms. The expression levels of snoRNAs were first analyzed by a powerful feature selection method, Monte Carlo feature selection (MCFS). A feature list and some informative features were accessed. Then, the incremental feature selection (IFS) was applied to the feature list to extract optimal features/snoRNAs, which can make the support vector machine (SVM) yield best performance. The discriminative snoRNAs included HBII-52-14, HBII-336, SNORD123, HBII-85-29, HBII-420, U3, HBI-43, SNORD116, SNORA73B, SCARNA4, HBII-85-20, etc., on which the SVM can provide a Matthew’s correlation coefficient (MCC) of 0.881 for predicting these eight cancer types. On the other hand, the informative features were fed into the Johnson reducer and repeated incremental pruning to produce error reduction (RIPPER) algorithms to generate classification rules, which can clearly show different snoRNAs expression patterns in different cancer types. The analysis results indicated that extracted discriminative snoRNAs can be important for identifying cancer samples in different types and the expression pattern of snoRNAs in different cancer types can be partly uncovered by quantitative recognition rules.

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Putative pathological mechanisms of late-life depression and Alzheimer’s disease

Hasan,

Clarke,

Strand

et al. 2023

Brain Research

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Activation of 5-HT2C Receptor Promotes the Expression of Neprilysin in U251 Human Glioma Cells

Cited by 6 publications

References 40 publications

Monoaminergic System Modulation in Depression and Alzheimer’s Disease: A New Standpoint?

Monoaminergic System Modulation in Depression and Alzheimer’s Disease: A New Standpoint?

Analysis of Expression Pattern of snoRNAs in Different Cancer Types with Machine Learning Algorithms

Putative pathological mechanisms of late-life depression and Alzheimer’s disease

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