Multimodal Image Fusion Workflow Incorporating MALDI Imaging Mass Spectrometry and Microscopy for the Study of Small Pharmaceutical Compounds

质谱成像 质谱法 马尔迪成像 显微镜 化学 人工智能 图像分辨率 荧光寿命成像显微镜 计算机科学 基质辅助激光解吸/电离 病理 光学 荧光 物理 色谱法 医学 有机化学 吸附 解吸
作者
Zhongling Liang,Yingchan Guo,Abhisheak Sharma,Christopher R. McCurdy,Boone M. Prentice
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:96 (29): 11869-11880
标识
DOI:10.1021/acs.analchem.4c01553
摘要

Multimodal imaging analyses of dosed tissue samples can provide more comprehensive insights into the effects of a therapeutically active compound on a target tissue compared to single-modal imaging. For example, simultaneous spatial mapping of pharmaceutical compounds and endogenous macromolecule receptors is difficult to achieve in a single imaging experiment. Herein, we present a multimodal workflow combining imaging mass spectrometry with immunohistochemistry (IHC) fluorescence imaging and brightfield microscopy imaging. Imaging mass spectrometry enables direct mapping of pharmaceutical compounds and metabolites, IHC fluorescence imaging can visualize large proteins, and brightfield microscopy imaging provides tissue morphology information. Single-cell resolution images are generally difficult to acquire using imaging mass spectrometry but are readily acquired with IHC fluorescence and brightfield microscopy imaging. Spatial sharpening of mass spectrometry images would thus allow for higher fidelity coregistration with other higher-resolution microscopy images. Imaging mass spectrometry spatial resolution can be predicted to a finer value via a computational image fusion workflow, which models the relationship between the intensity values in the mass spectrometry image and the features of a high-spatial resolution microscopy image. As a proof of concept, our multimodal workflow was applied to brain tissue extracted from a Sprague-Dawley rat dosed with a kratom alkaloid, corynantheidine. Four candidate mathematical models, including linear regression, partial least-squares regression, random forest regression, and two-dimensional convolutional neural network (2-D CNN), were tested. The random forest and 2-D CNN models most accurately predicted the intensity values at each pixel as well as the overall patterns of the mass spectrometry images, while also providing the best spatial resolution enhancements. Herein, image fusion enabled predicted mass spectrometry images of corynantheidine, GABA, and glutamine to approximately 2.5 μm spatial resolutions, a significant improvement compared to the original images acquired at 25 μm spatial resolution. The predicted mass spectrometry images were then coregistered with an H&E image and IHC fluorescence image of the μ-opioid receptor to assess colocalization of corynantheidine with brain cells. Our study also provides insights into the different evaluation parameters to consider when utilizing image fusion for biological applications.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
俗丨发布了新的文献求助10
1秒前
1秒前
1秒前
1秒前
难过云朵完成签到 ,获得积分10
1秒前
顺心的夜香完成签到,获得积分10
1秒前
冷艳又菱完成签到,获得积分10
2秒前
hbpu230701完成签到,获得积分10
3秒前
3秒前
wzy关闭了wzy文献求助
3秒前
Cecily完成签到,获得积分10
3秒前
牛曙东完成签到,获得积分10
3秒前
是酷不是凶完成签到,获得积分10
3秒前
HAHA完成签到,获得积分10
4秒前
xiaobao完成签到,获得积分0
4秒前
Singularity应助Lyllllll采纳,获得10
4秒前
4秒前
陈章zz完成签到,获得积分10
4秒前
领导范儿应助无限紫槐采纳,获得10
5秒前
细腻的冷珍完成签到,获得积分10
5秒前
pink完成签到,获得积分10
5秒前
fan完成签到,获得积分10
5秒前
lk完成签到 ,获得积分10
5秒前
6秒前
Wguan完成签到,获得积分10
6秒前
晓风残月完成签到,获得积分10
6秒前
YPST完成签到,获得积分10
7秒前
正直的焦发布了新的文献求助10
7秒前
田様应助lyouang采纳,获得10
8秒前
仙林AK47发布了新的文献求助20
8秒前
万幸鹿完成签到,获得积分10
8秒前
冷静的访天完成签到 ,获得积分0
8秒前
橙橙完成签到 ,获得积分10
9秒前
高高完成签到,获得积分10
10秒前
yunwen完成签到,获得积分10
10秒前
付艳完成签到,获得积分10
11秒前
小龙虾完成签到,获得积分10
11秒前
bawei发布了新的文献求助10
11秒前
HTF完成签到,获得积分10
12秒前
封似狮完成签到,获得积分10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Developing Genetic Editing Tools for Lysobacter 2000
卤化钙钛矿人工突触的研究 2000
Моделирование процессов самоорганизации в кристаллообразующих системах 1000
History of U.S. Space Surveillance and Satellite Cataloging 1000
Signals, Systems, and Signal Processing 610
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6519089
求助须知:如何正确求助?哪些是违规求助? 8311741
关于积分的说明 17771023
捐赠科研通 5621123
什么是DOI,文献DOI怎么找? 2926632
邀请新用户注册赠送积分活动 1903458
关于科研通互助平台的介绍 1764139