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海洋甲壳类动物大脑的生物成像:一种鼓虾微计算机断层扫描标本的定量比较

Bioimaging marine crustacean brain: quantitative comparison of micro-CT preparations in an Alpheid snapping shrimp.

作者信息

Chapuis Lucille, Andres Cara-Sophia, Gerneke Dane A, Radford Craig A

机构信息

Leigh Marine Laboratory, Institute of Marine Science, University of Auckland, Leigh, New Zealand.

Bioengineering Institute, University of Auckland, Auckland, New Zealand.

出版信息

Front Neurosci. 2024 Nov 26;18:1428825. doi: 10.3389/fnins.2024.1428825. eCollection 2024.

DOI:10.3389/fnins.2024.1428825
PMID:39659887
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11628493/
Abstract

Non-invasive bioimaging techniques like X-ray micro-computed tomography (μCT), combined with contrast-enhancing techniques, allow the 3D visualization of the central nervous system , without the destruction of the sample. However, quantitative comparisons of the most common fixation and contrast-enhancing protocols are rare, especially in marine invertebrates. Using the snapping shrimp () as a model, we test three common fixation and staining agents combinations to prepare specimens prior to μCT scanning. The contrast ratios of the resulting images are then quantitatively compared. Our results show that a buffered iodine solution on a specimen fixed with 10% formalin offers the best nervous tissue discriminability. This optimal combination allows a semi-automated segmentation of the central nervous system organs from the μCT images. We thus provide general guidance for μCT applications, particularly suitable for marine crustaceans. Species-specific morphological adaptations can then be characterized and studied in the context of evolution and behavioral ecology.

摘要

像X射线微计算机断层扫描(μCT)这样的非侵入性生物成像技术,结合造影增强技术,可以在不破坏样本的情况下实现中枢神经系统的三维可视化。然而,对于最常见的固定和造影增强方案的定量比较却很少见,尤其是在海洋无脊椎动物中。以鼓虾()为模型,我们测试了三种常见的固定和染色剂组合,以便在μCT扫描前制备标本。然后对所得图像的对比度进行定量比较。我们的结果表明,用10%福尔马林固定的标本上使用缓冲碘溶液可提供最佳的神经组织辨别能力。这种最佳组合允许从μCT图像中对中枢神经系统器官进行半自动分割。因此,我们为μCT应用提供了一般指导,特别适用于海洋甲壳类动物。然后可以在进化和行为生态学的背景下对特定物种的形态适应进行表征和研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/ac4367c058e8/fnins-18-1428825-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/0d4cedd5bb09/fnins-18-1428825-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/829a025bcd7e/fnins-18-1428825-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/910886adcbf9/fnins-18-1428825-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/25af05bd1638/fnins-18-1428825-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/ac4367c058e8/fnins-18-1428825-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/0d4cedd5bb09/fnins-18-1428825-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/829a025bcd7e/fnins-18-1428825-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/910886adcbf9/fnins-18-1428825-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/25af05bd1638/fnins-18-1428825-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83a9/11628493/ac4367c058e8/fnins-18-1428825-g005.jpg

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Micro-CT and deep learning: Modern techniques and applications in insect morphology and neuroscience.
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Environmental exposure to metallic pollution impairs honey bee brain development and cognition.金属污染对环境的暴露会损害蜜蜂的大脑发育和认知能力。
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