大鼠毛发再生与药物成瘾易感性的相关性分析
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深圳市杰出青年基础研究项目(RCJC20200714114556103);深圳市药物成瘾重点实验室项目(ZDSYS20190902093610675);广东省基础与应用基础研究基金项目(2021A1515010729)

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Correlation Between Hair Regrowth and Drug Addiction Susceptibility in Rats
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Shenzhen Science Fund for Distinguished Young Scholars (RCJC20200714114556103); Shenzhen Key Laboratory of Drug Addiction (ZDSYS20190902093601675) and Guangdong Basic and Applied Basic Research Foundation (2021A1515010729)

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    摘要:

    药物成瘾是一种顽固的慢性神经精神疾病,会引发一系列严重的社会问题。在不同个体间,药物成瘾易感性存在差异。成瘾易感性研究对药物成瘾的神经机制研究和评估、预测个体成瘾风险具有重要意义。针对 Sprague-Dawley 大鼠毛发再生能力差异和药物成瘾易感性,该文进行了 Pearson 相关分析,采用灰度分析法观察毛发再生差异,进行条件性位置偏好实验和大鼠自给药实验,评估大鼠成瘾易感性。实验结果表明:毛发再生能力与大鼠成瘾易感性呈负相关,即毛发再生能力较强的大鼠对吗啡条件性位置偏好显著降低,甲基苯丙胺自给药次数相对较低。此外,毛发再生能力对大鼠运动能力和焦虑水平无影响。该文的研究结果有助于评估、预测药物成瘾风险,进一步探讨其神经机制。

    Abstract:

    Drug addiction is an intractable chronic neuropsychiatric disorder that raises serious social problems. The study of individual susceptibility in drug addiction may contribute to our understanding of neurobiological mechanism underlying addiction and making risk assessment of individual vulnerability. Use the gray-scale analysis evaluate the hair regrowth ability, and assess the addiction susceptibility with conditioned place preference and intravenous self-administration paradigm in rats. The results revealed a significant negative correlation between addiction susceptibility and hair regrowth ability. The rats with fast hair regrowth ability exhibited less CPP score and reduced drug-seeking behavior in the methamphetamine self-administration model. The open field test showed no differences in the locomotor activity and anxiety level between the two groups. The findings may be helpful for predicting drug addiction risk and further exploring the neurobiological mechanisms of addiction susceptibility based on this phenotypic difference.

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引文格式
蒋辰宇,许云龙,柳昱彤,等.大鼠毛发再生与药物成瘾易感性的相关性分析 [J].集成技术,2022,11(5):23-33

Citing format
JIANG Chenyu, XU Yunlong, LIU Yutong, et al. Correlation Between Hair Regrowth and Drug Addiction Susceptibility in Rats[J]. Journal of Integration Technology,2022,11(5):23-33

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  • 在线发布日期: 2022-09-21
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