脊椎动物跨物种脑磁共振成像和组织学数据库。

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Tomokazu Tsurugizawa, Yuji Komaki, Illia Aota, Makoto Suematsu, Chiaki Ohtaka-Maruyama, Takuma Kumamoto
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引用次数: 0

摘要

理解大脑进化需要对不同物种的大脑结构进行详细的比较分析。然而,除了少数经过充分研究的模式生物之外,大多数脊椎动物的高分辨率解剖和连接数据仍然有限。为了填补这一空白,我们收集了一系列脊椎动物(主要是小羊膜动物)的死后脑样本,并进行了磁共振成像和组织学染色。在这里,我们展示了“动物大脑收集(ABC)”,这是一个免费访问的数据库,使研究人员能够检查和比较不同物种的细胞和组织水平的大脑结构。这一资源为跨物种研究大脑结构和发育提供了基础,为研究脊椎动物大脑的多样性和进化提供了新的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Cross-Species Brain Magnetic Resonance Imaging and Histology Database of Vertebrates.

Understanding brain evolution requires detailed comparative analyses of brain structures across species. However, high-resolution anatomical and connective data remain limited for most vertebrates beyond a few well-studied model organisms. To address this gap, we collected postmortem brain samples from a range of vertebrates, primarily small amniotes, and performed magnetic resonance imaging and histological staining. Here, we present the "Animal Brain Collection (ABC)," a freely accessible database that enables researchers to examine and compare cellular and tissue-level brain architectures across species. This resource provides a foundation for cross-species investigations of brain structure and development, offering new opportunities for research into the diversity and evolution of vertebrate brains.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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