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Jin S, Cho HJ. Cerebral hemodynamics as biomarkers for neuropathic pain in rats: a longitudinal study using a spinal nerve ligation model. Pain 2024:00006396-990000000-00655. [PMID: 38985168 DOI: 10.1097/j.pain.0000000000003332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 06/07/2024] [Indexed: 07/11/2024]
Abstract
ABSTRACT Neuropathic pain is one of the most challenging types of pain to diagnose and treat, a problem exacerbated by the lack of a quantitative biomarker. Recently, several clinical and preclinical studies have shown that neuropathic pain induces cerebral hemodynamic changes as a result of neuroplasticity in the brain. Our hypothesis in this study is that neuropathic pain leads to cerebral hemodynamic changes over postoperative time in a spinal nerve ligation (SNL) rat model, which has not been longitudinally explored previously. Furthermore, by identifying multiple regional hemodynamic features that are the most distinct between SNL and sham groups, where the sham group underwent only an incision without SNL, it may be possible to classify the SNL group regardless of when the onset of pain occurs. We investigate cerebral hemodynamic changes using dynamic susceptibility contrast magnetic resonance imaging in a rat model up to 28 days after ligating L5/L6 spinal nerves. We trained a linear support vector machine with relative cerebral blood volume data from different brain regions and found that the prediction model trained on the nucleus accumbens, motor cortex, pretectal area, and thalamus classified the SNL group and sham group at a 79.27% balanced accuracy, regardless of when the onset of pain occurred (SNL/sham: 60/45 data points). From the use of the SNL model without prior knowledge of the onset time of pain, the current findings highlight the potential of relative cerebral blood volume in the 4 highlighted brain regions as a biomarker for neuropathic pain.
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Affiliation(s)
- Seokha Jin
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
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Li H, Jiang T, An S, Xu M, Gou L, Ren B, Shi X, Wang X, Yan J, Yuan J, Xu X, Wu QF, Luo Q, Gong H, Bian WJ, Li A, Yu X. Single-neuron projectomes of mouse paraventricular hypothalamic nucleus oxytocin neurons reveal mutually exclusive projection patterns. Neuron 2024; 112:1081-1099.e7. [PMID: 38290516 DOI: 10.1016/j.neuron.2023.12.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 11/07/2023] [Accepted: 12/29/2023] [Indexed: 02/01/2024]
Abstract
Oxytocin (OXT) plays important roles in autonomic control and behavioral modulation. However, it is unknown how the projection patterns of OXT neurons align with underlying physiological functions. Here, we present the reconstructed single-neuron, whole-brain projectomes of 264 OXT neurons of the mouse paraventricular hypothalamic nucleus (PVH) at submicron resolution. These neurons hierarchically clustered into two groups, with distinct morphological and transcriptional characteristics and mutually exclusive projection patterns. Cluster 1 (177 neurons) axons terminated exclusively in the median eminence (ME) and have few collaterals terminating within hypothalamic regions. By contrast, cluster 2 (87 neurons) sent wide-spread axons to multiple brain regions, but excluding ME. Dendritic arbors of OXT neurons also extended outside of the PVH, suggesting capability to sense signals and modulate target regions. These single-neuron resolution observations reveal distinct OXT subpopulations, provide comprehensive analysis of their morphology, and lay the structural foundation for better understanding the functional heterogeneity of OXT neurons.
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Affiliation(s)
- Humingzhu Li
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; School of Life Sciences, Peking-Tsinghua Center for Life Sciences, and Peking University McGovern Institute, Peking University, Beijing 100871, China
| | - Tao Jiang
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215123, China
| | - Sile An
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Mingrui Xu
- University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Lingfeng Gou
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Biyu Ren
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaoxue Shi
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaofei Wang
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jun Yan
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jing Yuan
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215123, China; Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Xiaohong Xu
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qing-Feng Wu
- University of Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qingming Luo
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215123, China; Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Hui Gong
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215123, China; Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Wen-Jie Bian
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China; School of Life Sciences, Westlake University, Hangzhou 310024, China.
| | - Anan Li
- HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou 215123, China; Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Xiang Yu
- Institute of Neuroscience and State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; School of Life Sciences, Peking-Tsinghua Center for Life Sciences, and Peking University McGovern Institute, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing 102206, China.
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Kim MK, Choi W, Moon HJ, Han S, Shin HJ. Targeted photothrombotic subcortical small vessel occlusion using in vivo real-time fiber bundle endomicroscopy in mice. BIOMEDICAL OPTICS EXPRESS 2023; 14:687-702. [PMID: 36874485 PMCID: PMC9979683 DOI: 10.1364/boe.473407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 11/18/2022] [Accepted: 12/23/2022] [Indexed: 06/18/2023]
Abstract
The development of an accurate subcortical small vessel occlusion model for pathophysiological studies of subcortical ischemic stroke is still insignificant. In this study, in vivo real-time fiber bundle endomicroscopy (FBEµ) was applied to develop subcortical photothrombotic small vessel occlusion model in mice with minimal invasiveness. Our FBFµ system made it possible to precisely target specific blood vessels in deep brain and simultaneously observe the clot formation and blood flow blockage inside the target blood vessel during photochemical reactions. A fiber bundle probe was directly inserted into the anterior pretectal nucleus of the thalamus in brain of live mice to induce a targeted occlusion in small vessels. Then, targeted photothrombosis was performed using a patterned laser, observing the process through the dual-color fluorescence imaging. On day one post occlusion, infarct lesions are measured using TTC staining and post hoc histology. The results show that FBEµ applied to targeted photothrombosis can successfully generate a subcortical small vessel occlusion model for lacunar stroke.
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Affiliation(s)
- Min-kyung Kim
- Bionics Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
| | - Wonseok Choi
- Bionics Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
- Department of Biomedical Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Gangwon-do, 26493, Republic of Korea
| | - Hyuk-June Moon
- Bionics Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
| | - Sungmin Han
- Bionics Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
| | - Hyun-joon Shin
- Bionics Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
- Division of Bio-Medical Science & Technology, KIST School, Korea University of Science and Technology (UST), Seoul, 02792, Republic of Korea
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