InSpectro-Gadget:估算 MRS 体素的神经递质和神经调节剂受体分布的工具

IF 2.7 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Neuroinformatics Pub Date : 2024-02-22 DOI:10.1007/s12021-024-09654-w
Elizabeth McManus, Nils Muhlert, Niall W. Duncan
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引用次数: 0

摘要

磁共振光谱(MRS)被广泛用于估算活体人脑特定区域中谷氨酸和(\γ)-氨基丁酸(GABA)的浓度。由于整个大脑的细胞结构特性各不相同,因此了解所研究的 MRS 区域的此类特性有助于解释这些测量结果。特别是,对可能的局部神经递质受体模式有所了解,就有可能深入了解 GABA 和谷氨酸能神经元运作的机制环境。在比较两个或更多区域时,这一点可能特别有用,因为不同区域的受体群可能有很大不同。同时,在研究来自多个参与者或时间点的 MRS 数据时,样本的同质性也变得非常重要,因为来自不同细胞结构区域的测量结果可能难以比较。为了深入了解用户定义的感兴趣区域可能存在的细胞结构环境,我们制作了一个易于使用的工具--InSpectro-Gadget,该工具可与艾伦人脑图谱的受体 mRNA 表达信息对接。这款 Python 工具允许用户输入掩码,并自动获得其中可能存在的受体群的图形概览。这包括在相关情况下对多个掩码或参与者进行比较。受体和受体亚基基因包括 GABA 和谷氨酸能类,以及多种神经调节剂。本文对该工具的功能进行了说明,并通过一组示例分析对其使用进行了演示。该工具可在 https://github.com/lizmcmanus/Inspectro-Gadget 上获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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InSpectro-Gadget: A Tool for Estimating Neurotransmitter and Neuromodulator Receptor Distributions for MRS Voxels

Magnetic resonance spectroscopy (MRS) is widely used to estimate concentrations of glutamate and \(\gamma\)-aminobutyric acid (GABA) in specific regions of the living human brain. As cytoarchitectural properties differ across the brain, interpreting these measurements can be assisted by having knowledge of such properties for the MRS region(s) studied. In particular, some knowledge of likely local neurotransmitter receptor patterns can potentially give insights into the mechanistic environment GABA- and glutamatergic neurons are functioning in. This may be of particular utility when comparing two or more regions, given that the receptor populations may differ substantially across them. At the same time, when studying MRS data from multiple participants or timepoints, the homogeneity of the sample becomes relevant, as measurements taken from areas with different cytoarchitecture may be difficult to compare. To provide insights into the likely cytoarchitectural environment of user-defined regions-of-interest, we produced an easy to use tool - InSpectro-Gadget - that interfaces with receptor mRNA expression information from the Allen Human Brain Atlas. This Python tool allows users to input masks and automatically obtain a graphical overview of the receptor population likely to be found within. This includes comparison between multiple masks or participants where relevant. The receptors and receptor subunit genes featured include GABA- and glutamatergic classes, along with a wide range of neuromodulators. The functionality of the tool is explained here and its use is demonstrated through a set of example analyses. The tool is available at https://github.com/lizmcmanus/Inspectro-Gadget.

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来源期刊
Neuroinformatics
Neuroinformatics 医学-计算机:跨学科应用
CiteScore
6.00
自引率
6.70%
发文量
54
审稿时长
3 months
期刊介绍: Neuroinformatics publishes original articles and reviews with an emphasis on data structure and software tools related to analysis, modeling, integration, and sharing in all areas of neuroscience research. The editors particularly invite contributions on: (1) Theory and methodology, including discussions on ontologies, modeling approaches, database design, and meta-analyses; (2) Descriptions of developed databases and software tools, and of the methods for their distribution; (3) Relevant experimental results, such as reports accompanie by the release of massive data sets; (4) Computational simulations of models integrating and organizing complex data; and (5) Neuroengineering approaches, including hardware, robotics, and information theory studies.
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