Journal of Neuroscience Methods最新文献_第7页

Characterization of neuronal differentiation in human adipose-derived stromal cells: morphological, molecular, and ultrastructural insights 人脂肪基质细胞神经元分化的特征：形态学、分子和超微结构的见解。

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-30 DOI: 10.1016/j.jneumeth.2024.110296

Xiaodong Yuan , Wen Li , Yi Yuan , Xuhong Zhu , Yan Meng , Qi Wu , Qi Yan , Pingshu Zhang

Objective

Adipose-derived stromal cells (ADSCs) have shown promise as a potential source of neural differentiation. In this study, we investigated the morphological, molecular and ultrastructural features of ADSCs during neuronal differentiation.

Methods

ADSCs were induced in vitro and their differentiation was examined at different time points. Immunocytochemical staining was performed to detect the expression of neuron-specific markers NSE and MAP-2. Immunofluorescence double labeling and Western blot detected the co-expression of presynaptic markers (CaMKII, SynCAM1, SYN) and postsynaptic markers (PSD-95, Synapsin I). Scanning electron microscopy (SEM) was performed to detect the synaptic structural features of differentiated neurons.

Results

ADSCs showed diverse morphological features during differentiation, gradually acquiring a neuron-like spindle shape and organized arrangement. The expression of neuron-specific markers and synaptic markers peaked at 5 h of induction. Scanning electron microscopy showed polygonal protrusions of ADSC-derived neurons, and transmission electron microscopy showed characteristic ultrastructures such as nidus, synaptic vesicle-like structures, and tight junctions.

Conclusion

Our findings suggest that ADSCs differentiated for 5 h have neuronal features, including morphological, molecular, and ultrastructural resemblance to neurons, as well as the formation of synaptic structures. These insights contribute to a better understanding of ADSC-based neuronal differentiation and pave the way for future applications in regenerative medicine and neurodegenerative diseases.

目的：脂肪源性基质细胞（ADSCs）有望成为神经分化的潜在来源。本研究调查了 ADSCs 在神经元分化过程中的形态、分子和超微结构特征：方法：在体外诱导 ADSCs，并在不同时间点检测其分化情况。免疫细胞化学染色检测神经元特异性标志物 NSE 和 MAP-2 的表达。免疫荧光双标记和 Western 印迹检测突触前标记（CaMKII、SynCAM1、SYN）和突触后标记（PSD-95、Synapsin I）的共同表达。扫描电子显微镜（SEM）检测了分化神经元的突触结构特征：结果：ADSCs在分化过程中表现出多种形态特征，逐渐形成类似神经元的纺锤形和有序排列。神经元特异性标记和突触标记的表达在诱导5小时后达到高峰。扫描电镜显示 ADSC 衍生的神经元呈多边形突起，透射电镜显示出特征性的超微结构，如神经节、突触囊泡样结构和紧密连接：我们的研究结果表明，分化 5 小时的 ADSCs 具有神经元特征，包括形态、分子和超微结构与神经元相似，以及突触结构的形成。这些见解有助于更好地理解基于 ADSC 的神经元分化，并为未来在再生医学和神经退行性疾病中的应用铺平了道路。

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引用次数: 0

A method for quantitative spatial analysis of immunolabeled fibers at regenerative electrode interfaces 再生电极界面免疫标记纤维定量空间分析方法

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-24 DOI: 10.1016/j.jneumeth.2024.110295

Michael Rosario , Jingyuan Zhang , Muhammad Irfan Kaleem , Nikhil Chandra , Ying Yan , Daniel Moran , Matthew Wood , Wilson Z. Ray , Matthew MacEwan

Background

Regenerative electrodes are being explored as robust peripheral nerve interfaces for neuro-prosthetic control and sensory feedback. Current designs differ in electrode number, spatial arrangement, and porosity which impacts the regeneration, activation, and spatial distribution of fibers at the device interface. Knowledge of sensory and motor fiber distributions are important in optimizing selective fiber activation and recording.

New Method

We use confocal microscopy and immunofluorescence methods to conduct spatial analysis of immunolabeled fibers across whole nerve cross sections.

Results

This protocol was implemented to characterize motor fiber distribution within 3 macro-sieve electrode regenerated (MSE), 3 silicone-conduit regenerated, and 3 unmanipulated control rodent sciatic nerves. Total motor fiber counts were 1485 [SD: +/- 50.11], 1899 [SD: +/- 359], and 5732 [SD: +/- 1410] for control, MSE, and conduit nerves respectively. MSE motor fiber distributions exhibited evidence of deviation from complete spatial randomness and evidence of dispersion and clustering tendencies at varying scales. Notably, MSE motor fibers exhibited clustering within the central portion of the cross section, whereas conduit regenerated motor fibers exhibited clustering along the periphery.

Comparison with Existing Methods

Prior exploration of fiber distributions at regenerative interfaces was limited to either quadrant-based density analysis of randomly sampled subregions or qualitative description. This method extends existing sample preparation and microscopy techniques to quantitatively assess immunolabeled fiber distributions within whole nerve cross-sections.

Conclusions

This approach is an effective way to examine the spatial organization of fiber subsets at regenerative electrode interfaces, enabling robust assessment of fiber distributions relative to electrode arrangement.

背景：人们正在探索将再生电极作为神经假体控制和感觉反馈的强大外周神经接口。目前的设计在电极数量、空间布局和孔隙率方面存在差异，这影响了装置接口处纤维的再生、激活和空间分布。了解感觉和运动纤维的分布对于优化选择性纤维激活和记录非常重要：新方法：我们使用免疫荧光和共聚焦显微镜观察和分割整个神经，对再生电极界面上的免疫标记纤维进行空间分析：结果：采用这种方法分析了3条大筛电极再生（MSE）、3条硅胶导管再生和3条未操控的对照啮齿动物坐骨神经的运动纤维分布特征。对照组、MSE 和导管神经的运动纤维总数分别为 1485 [SD: +/- 50.11]、1899 [SD: +/- 359] 和 5732 [SD: +/- 1410]。MSE 运动纤维分布显示出偏离完全空间随机性的证据，以及在不同尺度上的分散和集群趋势的证据。值得注意的是，MSE 运动纤维在横截面中央部分表现出集群，而导管再生运动纤维则沿外围表现出集群：与现有方法的比较：之前对再生界面纤维分布的研究仅限于对随机取样的子区域进行象限密度分析或定性描述。这种方法扩展了现有的样本制备和显微镜技术，可定量评估整个神经横截面内的免疫标记纤维分布：结论：该方法是检查再生电极界面免疫标记纤维亚群空间排列的有效方法，可对相对于电极排列的纤维分布进行稳健评估。

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引用次数: 0

Corrigendum to “Isolation of ependymal cilia from mouse brain” [J. Neurosci. Method. 409 (2024) 110198] 小鼠脑内上皮纤毛的分离》[J. Neurosci. Method. 409 (2024) 110198]的更正。

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-21 DOI: 10.1016/j.jneumeth.2024.110293

Akihiro Mizuno , Kazuhito Takeuchi , Yuichi Nagata , Hideyuki Harada , Taiki Yamamoto , Takayuki Ishikawa , Sachi Maeda , Fumiharu Ohka , Hironori Ueno , Ryuta Saito

引用次数: 0

Functional MRI study with conductivity signal changes during visual stimulation 视觉刺激时传导信号变化的功能磁共振成像研究

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-19 DOI: 10.1016/j.jneumeth.2024.110288

Hyug-Gi Kim , Youngeun Yoon , Mun Bae Lee , Jeongin Jeong , Jiyoon Lee , Oh In Kwon , Geon-Ho Jahng

Background

Although blood oxygen level-dependent (BOLD) functional MRI (fMRI) is a standard method, major BOLD signals primarily originate from intravascular sources. Magnetic resonance electrical properties tomography (MREPT)-based fMRI signals may provide additional insights into electrical activity caused by alterations in ion concentrations and mobilities.

Purpose

This study aimed to investigate the neuronal response of conductivity during visual stimulation and compare it with BOLD.

Materials and methods

A total of 30 young, healthy volunteers participated in two independent experiments using BOLD and MREPT techniques with a visual stimulation paradigm at 3 T MRI. The first set of MREPT fMRI data was obtained using a multi-echo spin-echo (SE) echo planar imaging (EPI) sequence from 14 participants. The second set of MREPT fMRI data was collected from 16 participants using both a single-echo SE-EPI and a single-echo three-dimensional (3D) balanced fast-field-echo (bFFE) sequence. We reconstructed the time-course Larmor frequency conductivity to evaluate hemodynamics.

Results

Conductivity values slightly increased during visual stimulation. Activation strengths were consistently stronger with BOLD than with conductivity for both SE-EPI MREPT and bFFE MREPT. Additionally, the activated areas were always larger with BOLD than MREPT. Some participants also exhibited decreased conductivity values during visual stimulations. In Experiment 1, conductivity showed significant differences between the fixation and visual stimulation blocks in the secondary visual cortex (SVC) and cuneus, with conductivity differences of 0.43 % and 0.47 %, respectively. No significant differences in conductivity were found in the cerebrospinal fluid (CSF) areas between the two blocks. In Experiment 2, significant conductivity differences were observed between the two blocks in the SVC, cuneus, and lingual gyrus for SE-EPI MREPT, with differences of 0.90 %, 0.67 %, and 0.24 %, respectively. Again, no significant differences were found in the CSF areas.

Conclusion

Conductivity values increased slightly during visual stimulation in the visual cortex areas but were much weaker than BOLD responses. The conductivity change during visual stimulation was less than 1 % compared to the fixation block. No significant differences in conductivity were observed between the primary visual cortex (PVC)-CSF and SVC-CSF during fixation and visual stimulations, suggesting that the observed conductivity changes may not be related to CSF changes in the visual cortex but rather to diffusion changes. Future research should explore the potential of MREPT to detect neuronal electrical activity and hemodynamic changes, with further optimization of the MREPT technique.

背景：虽然血氧水平依赖性（BOLD）功能磁共振成像（fMRI）是一种标准方法，但主要的BOLD信号主要来自血管内。基于磁共振电特性断层扫描（MREPT）的 fMRI 信号可为离子浓度和迁移率的改变所引起的电活动提供额外的见解：共有 30 名年轻、健康的志愿者参加了两项独立实验，在 3T 磁共振成像上使用 BOLD 和 MREPT 技术进行视觉刺激范式。第一组 MREPT fMRI 数据是使用多回波自旋回波（SE）回波平面成像（EPI）序列从 14 名参与者中获得的。第二组 MREPT fMRI 数据是使用单回波 SE-EPI 和单回波三维（3D）平衡快速场回波（bFFE）序列从 16 名参与者身上采集的。我们重建了拉莫尔频率传导的时程，以评估血液动力学：结果：电导率值在视觉刺激时略有增加。在 SE-EPI MREPT 和 bFFE MREPT 中，BOLD 的激活强度始终强于电导率。此外，BOLD 激活区域始终大于 MREPT 激活区域。在视觉刺激过程中，一些参与者还表现出传导性降低。在实验 1 中，第二视皮层（SVC）和楔状突起的电导率在固定区块和视觉刺激区块之间存在显著差异，电导率差异分别为 0.43% 和 0.47%。脑脊液（CSF）区域的电导率在两个区块之间没有发现明显差异。在实验 2 中，在 SE-EPI MREPT 的 SVC、楔状回和舌回中观察到两个区组之间存在明显的传导性差异，差异分别为 0.90%、0.67% 和 0.24%。同样，在 CSF 区域也未发现明显差异：结论：在视觉刺激期间，视觉皮层区域的传导值略有增加，但比 BOLD 反应弱得多。与固定区块相比，视觉刺激时的传导性变化不到 1%。在固定和视觉刺激期间，未观察到初级视皮层（PVC）-CSF 和 SVC-CSF 的电导率有明显差异，这表明观察到的电导率变化可能与视皮层中 CSF 的变化无关，而是与扩散变化有关。未来的研究应进一步优化 MREPT 技术，探索 MREPT 检测神经元电活动和血液动力学变化的潜力。

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引用次数: 0

Artificial intelligence-based analysis of behavior and brain images in cocaine-self-administered marmosets 基于人工智能的可卡因自控狨猴行为和大脑图像分析。

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-19 DOI: 10.1016/j.jneumeth.2024.110294

Wonmi Gu , Juhui Gim , Dohyun Lee , Heejong Eom , Jae Jun Lee , Seong Shoon Yoon , Tae-Young Heo , Jaesuk Yun

Background

The sophisticated behavioral and cognitive repertoires of non-human primates (NHPs) make them suitable subjects for studies involving cocaine self-administration (SA) schedules. However, ethical considerations, adherence to the 3Rs principle (replacement, reduction and refinement), and other factors make it challenging to obtain NHPs individuals for research. Consequently, there is a need for methods that can comprehensively analyze small datasets using artificial intelligence (AI).

New methods

We employed AI to identify cocaine dependence patterns from collected data. First, we collected behavioral data from cocaine SA marmosets (Callithrix jacchus) to develop a dependence prediction model. SHapley Additive exPlanations (SHAP) values were used to demonstrate the importance of various variables. Additionally, we collected positron emission tomographic (PET) images showing dopamine transporter (DAT) binding potential and developed an algorithm for PET image segmentation.

Results

The prediction model indicated that the Random Forest (RF) algorithm performed best, with an area under the curve (AUC) of 0.92. The top five variables influencing the model were identified using SHAP values. The PET image segmentation model achieved an accuracy of 0.97, a mean squared error of 0.02, an intersection over union (IoU) of 0.845, and a Dice coefficient of 0.913.

Comparison with existing methods and conclusion

Utilizing data from the marmoset SA experiment, we developed an ML-based dependence prediction model and analyzed variable importance rankings using SHAP. AI-based imaging segmentation methods offer a valuable tool for evaluating DAT availability in NHPs following chronic cocaine administration.

背景：非人灵长类动物（NHPs）具有复杂的行为和认知能力，适合作为可卡因自我给药（SA）计划的研究对象。然而，由于伦理方面的考虑、对 3R 原则（替代、减少和完善）的遵守以及其他因素，要获得用于研究的非人灵长类个体具有挑战性。因此，我们需要能利用人工智能（AI）全面分析小型数据集的方法：我们利用人工智能从收集到的数据中识别可卡因依赖模式。首先，我们收集了可卡因SA狨猴（Callithrix jacchus）的行为数据，以开发依赖性预测模型。使用SHAPLE Additive exPlanations（SHAP）值来证明各种变量的重要性。此外，我们还收集了显示多巴胺转运体（DAT）结合电位的正电子发射断层扫描（PET）图像，并开发了PET图像分割算法：预测模型显示，随机森林（RF）算法表现最佳，曲线下面积（AUC）为 0.92。利用 SHAP 值确定了影响模型的前五个变量。PET 图像分割模型的准确率为 0.97，平均平方误差为 0.02，交集大于联合（IoU）为 0.845，Dice 系数为 0.913：利用狨猴 SA 实验的数据，我们开发了一个基于 ML 的依赖性预测模型，并利用 SHAP 分析了变量重要性排名。基于人工智能的成像分割方法为评估慢性可卡因给药后NHPs的DAT可用性提供了一种有价值的工具。

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引用次数: 0

Generating and maintaining brain organoids at various levels of complexity 生成和维持不同复杂程度的大脑有机体"。

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-17 DOI: 10.1016/j.jneumeth.2024.110291

Floris G. Wouterlood

引用次数: 0

A novel DRL-guided sparse voxel decoding model for reconstructing perceived images from brain activity 从大脑活动中重建感知图像的新型 DRL 引导稀疏体素解码模型

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-17 DOI: 10.1016/j.jneumeth.2024.110292

Xu Yin , Zhengping Wu , Haixian Wang

Background

Due to the sparse encoding character of the human visual cortex and the scarcity of paired training samples for {images, fMRIs}, voxel selection is an effective means of reconstructing perceived images from fMRI. However, the existing data-driven voxel selection methods have not achieved satisfactory results.

New method

Here, a novel deep reinforcement learning-guided sparse voxel (DRL-SV) decoding model is proposed to reconstruct perceived images from fMRI. We innovatively describe voxel selection as a Markov decision process (MDP), training agents to select voxels that are highly involved in specific visual encoding.

Results

Experimental results on two public datasets verify the effectiveness of the proposed DRL-SV, which can accurately select voxels highly involved in neural encoding, thereby improving the quality of visual image reconstruction.

Comparison with existing methods

We qualitatively and quantitatively compared our results with the state-of-the-art (SOTA) methods, getting better reconstruction results. We compared the proposed DRL-SV with traditional data-driven baseline methods, obtaining sparser voxel selection results, but better reconstruction performance.

Conclusions

DRL-SV can accurately select voxels involved in visual encoding on few-shot, compared to data-driven voxel selection methods. The proposed decoding model provides a new avenue to improving the image reconstruction quality of the primary visual cortex.

背景由于人类视觉皮层的稀疏编码特性以及{图像、fMRI}配对训练样本的稀缺性，体素选择是一种从fMRI重建感知图像的有效手段。在此，我们提出了一种新的深度强化学习引导的稀疏体素（DRL-SV）解码模型，用于从 fMRI 重建感知图像。我们创新性地将体素选择描述为马尔可夫决策过程（MDP），训练代理选择高度参与特定视觉编码的体素。结果在两个公开数据集上的实验结果验证了所提出的 DRL-SV 的有效性，它可以准确选择高度参与神经编码的体素，从而提高视觉图像重建的质量。我们将提议的 DRL-SV 与传统的数据驱动基线方法进行了比较，得到了更稀疏的体素选择结果，但重建性能更好。所提出的解码模型为提高初级视觉皮层的图像重建质量提供了一条新途径。

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引用次数: 0

Optimizing magnetometers arrays and analysis pipelines for multivariate pattern analysis 为多元模式分析优化磁强计阵列和分析管道。

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-17 DOI: 10.1016/j.jneumeth.2024.110279

Yulia Bezsudnova, Andrew J. Quinn, Ole Jensen

Background

Multivariate pattern analysis (MVPA) has proven an excellent tool in cognitive neuroscience. It also holds a strong promise when applied to optically-pumped magnetometer-based magnetoencephalography.

New method

To optimize OPM-MEG systems for MVPA experiments this study examines data from a conventional MEG magnetometer array, focusing on appropriate noise reduction techniques for magnetometers. We determined the least required number of sensors needed for robust MVPA for image categorization experiments.

Results

We found that the use of signal space separation (SSS) without a proper regularization significantly lowered the classification accuracy considering a sub-array of 102 magnetometers or a sub-array of 204 gradiometers. We also found that classification accuracy did not improve when going beyond 30 sensors irrespective of whether SSS has been applied.

Comparison with existing methods

The power spectra of data filtered with SSS has a substantially higher noise floor that data cleaned with SSP or HFC. Consequently, MVPA decoding results obtained from the SSS-filtered data are significantly lower compared to all other methods employed.

Conclusions

When designing MEG system based on SQUID magnetometers optimized for multivariate analysis for image categorization experiments, about 30 magnetometers are sufficient. We advise against applying SSS filters without a proper regularization to data from MEG and OPM systems prior to performing MVPA as this method, albeit reducing low-frequency external noise contributions, also introduces an increase in broadband noise. We recommend employing noise reduction techniques that either decrease or maintain the noise floor of the data like signal-space projection, homogeneous field correction and gradient noise reduction.

背景：多变量模式分析（MVPA）已被证明是认知神经科学中的一种优秀工具。新方法：为了优化用于 MVPA 实验的 OPM-MEG 系统，本研究检查了传统 MEG 磁强计阵列的数据，重点是磁强计的适当降噪技术。我们确定了图像分类实验中稳健 MVPA 所需的最少传感器数量：我们发现，使用信号空间分离（SSS）而不进行适当的正则化，会显著降低由 102 个磁强计组成的子阵列或由 204 个梯度计组成的子阵列的分类准确性。我们还发现，无论是否使用了 SSS，当传感器数量超过 30 个时，分类准确率并没有提高：与现有方法的比较：与使用 SSP 或 HFC 净化的数据相比，使用 SSS 过滤的数据的功率谱具有更高的本底噪声。因此，与采用的所有其他方法相比，从 SSS 过滤数据中获得的 MVPA 解码结果要低得多：在设计基于 SQUID 磁强计的 MEG 系统时，为图像分类实验的多元分析进行优化，大约 30 个磁强计就足够了。我们建议，在进行 MVPA 之前，不要对 MEG 和 OPM 系统的数据应用 SSS 滤波器而不进行适当的正则化处理，因为这种方法虽然能减少低频外部噪声，但也会增加宽带噪声。我们建议采用降噪技术，如信号空间投影、均质场校正和梯度降噪，以降低或保持数据的本底噪声。

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引用次数: 0

Research on shared control of robots based on hybrid brain-computer interface 基于混合脑机接口的机器人共享控制研究

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-11 DOI: 10.1016/j.jneumeth.2024.110280

Ziqi Zhang , Mengfan Li , Ran Wei , Wenzhe Liao , Fuyong Wang , Guizhi Xu

Background

With the arrival of the new generation of artificial intelligence wave, new human-robot interaction technologies continue to emerge. Brain–computer interface (BCI) offers a pathway for state monitoring and interaction control between human and robot. However, the unstable mental state reduce the accuracy of human brain intent decoding, and consequently affects the precision of BCI control.

New methods

This paper proposes a hybrid BCI-based shared control (HB-SC) method for brain-controlled robot navigation. Hybrid BCI fuses electroencephalogram (EEG) and electromyography (EMG) for mental state monitoring and interactive control to output human perception and decision. The shared control based on multi-sensory fusion integrates the special obstacle information perceived by humans with the regular environmental information perceived by the robot. In this process, valid BCI commands are screened by mental state assessment and output to a layered costmap for fusion.

Results

Eight subjects participated in the navigation experiment with dynamically changing mental state levels to validate the effects of a hybrid brain-computer interface through two shared control modes. The results show that the proposed HB-SC reduces collisions by 37.50 %, improves the success rate of traversing obstacles by 25.00 %, and the navigation trajectory is more consistent with expectations.

Conclusions

The HB-SC method can dynamically and intelligently adjust command output according to different brain states, helping to reduce errors made by subjects in a unstable mental state, thereby greatly enhancing the system's safety.

背景随着新一代人工智能浪潮的到来，新的人机交互技术不断涌现。脑机接口（BCI）为人与机器人之间的状态监测和交互控制提供了一条途径。本文提出了一种基于混合 BCI 的共享控制（HB-SC）方法，用于脑控机器人导航。混合BCI融合了脑电图（EEG）和肌电图（EMG），用于精神状态监测和交互控制，以输出人类的感知和决策。基于多感官融合的共享控制将人类感知到的特殊障碍物信息与机器人感知到的常规环境信息整合在一起。在此过程中，有效的 BCI 命令通过精神状态评估进行筛选，并输出到分层成本图中进行融合。结果八名受试者参与了精神状态水平动态变化的导航实验，通过两种共享控制模式验证了混合脑机接口的效果。结果表明，所提出的 HB-SC 减少了 37.50 % 的碰撞，提高了 25.00 % 的穿越障碍物的成功率，导航轨迹与预期更加一致。结论 HB-SC 方法可以根据不同的大脑状态动态、智能地调整指令输出，有助于减少受试者在不稳定的精神状态下产生的错误，从而大大提高系统的安全性。

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引用次数: 0

Strategies for the development of in vitro models of spinal cord ischemia-reperfusion injury: Oxygen-glucose deprivation and reoxygenation 脊髓缺血再灌注损伤体外模型的开发策略：氧气-葡萄糖剥夺和再氧

IF 2.7 4区医学 Q2 BIOCHEMICAL RESEARCH METHODS

Journal of Neuroscience Methods

Pub Date : 2024-09-10 DOI: 10.1016/j.jneumeth.2024.110278

Jiyoun Lee , Sung-Hee Han , Jin-Hee Kim , Hyun-Jung Shin , Jin-Woo Park , Jin-Young Hwang

Background

In vitro models tailored for spinal cord ischemia-reperfusion injury are pivotal for investigation of the mechanisms underlying spinal cord injuries. We conducted a two-phased study to identify the optimal conditions for establishing an in vitro model of spinal cord ischemia–reperfusion injury using primary rat spinal motor neurons.

New method

In the first phase, cell cultures were subjected to oxygen deprivation (OD) only, glucose deprivation (GD) only, or simultaneous deprivation of oxygen and glucose [oxygen-glucose deprivation (OGD)] for different durations (1, 2, and 6 h). In the second phase, different durations of re-oxygenation (1, 12, and 24 h) were applied after 1 h of OGD to determine the optimal duration simulating reperfusion injury.

Results and comparison with existing method(s)

GD for 6 h significantly reduced cell viability (91 % of control, P<0.001) and increase cytotoxicity (111 % of control, P<0.001). OGD for 1 h and 2 h, resulted in a significant decrease in cell viability (80 % of control P<0.001, respectively), and increase in cytotoxicity (130 % of control, P<0.001, respectively). Re-oxygenation for 1, 12, and 24 h worsened ischemic injury following 1 h of OGD (all P<0.05).

Conclusions

Our results may provide a valuable guide to devise in vitro models of spinal cord ischemia–reperfusion injury using primary spinal motor neurons.

背景适合脊髓缺血再灌注损伤的体外模型对于研究脊髓损伤的机制至关重要。我们分两个阶段进行了一项研究，以确定利用原代大鼠脊髓运动神经元建立脊髓缺血再灌注损伤体外模型的最佳条件。在第二阶段，OGD 1 小时后进行不同持续时间的再氧合（1、12 和 24 小时），以确定模拟再灌注损伤的最佳持续时间。结果及与现有方法的比较6 小时的 GD 显著降低了细胞活力（对照组的 91%，P<0.001），增加了细胞毒性（对照组的 111%，P<0.001）。缺氧 1 小时和 2 小时会导致细胞存活率显著下降（分别为对照组的 80%，P<0.001）和细胞毒性增加（分别为对照组的 130%，P<0.001）。结论我们的研究结果可为利用原发性脊髓运动神经元设计脊髓缺血再灌注损伤的体外模型提供有价值的指导。

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引用次数: 0