基于共生菌群调控诠释外用中药治疗慢性创面机制的认知与思考

CHEN Jun,WANG Yi-wei,XU Ze-yu,ZHAO Hong-yu,YE Liang,YIN Shao-ping,DUAN Jin-ao

Chinese Traditional and Herbal Drugs（2022）

南京中医药大学江苏省中医外用药开发与应用工程研究中心 210023 | 南京中医药大学附属南京医院临床科研中心 210003 | 南京中医药大学江苏省中药资源产业化过程协同创新中心 210023

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Abstract

在老龄化背景下慢性创面已成为严重威胁人民生命健康的重大公共卫生问题,在中医理论的指导下,外用中药在慢性创面治疗方面形成了独特的理论和治法,并且特别重视寒热药性的影响,但其科学内涵与作用机制还有待于深入诠释以更好地服务于临床应用.最新研究表明,共生菌群能够发挥免疫调节和促愈作用,故而对于慢性创面治疗具有重要意义,绝对无菌反而不利于创面愈合.因此提出通过创面菌群调控认知探讨以马勃Calvatia gigantean为代表的外用中药"煨脓长肉"治疗慢性创面作用机制的研究思路,以及基于创面菌群-肠道菌群调控的创面外用中药寒热药性作用机制的研究思路,为科学认知和充分发挥外用中药临床独特疗效和医学生物学机制提供参考和借鉴,为外用中药治疗慢性创面的现代研究提供新思路.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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