Selenium-enriched Bifidobacterium Longum DD98 Significantly Improves the Efficacy of Mesalazine and Cyclosporin A in Colitis Mice
Food Bioscience(2024)
Shanghai Jiao Tong Univ
Abstract
The incidence of ulcerative colitis (UC) is increasing worldwide and therapeutic drugs for UC are limited. Improvement of microbiome composition with the use of probiotics has the potential to increase the therapeutic index of UC drugs. Several lines of evidence suggested that Bifidobacterium significantly improve colitis by restoring the altered gut microbiota in DSS-treated mice, however the adjuvant effect of Bifidobacterium with UC drugs remains unknown. In this study, we tested the adjuvant potential of probiotic selenium-enriched Bifidobacterium Longum DD98 (SeDD98) on Mesalazine and Cyclosporin A (CsA) two medications used in the treatment of UC. We found that SeDD98 significantly improved the efficacy of Mesalazine and CsA in UC. The combination of SeDD98 and CsA showed the strongest efficacy in decreasing colitis histological scores, inflammation, and oxidative stress. Next we demonstrated that the combination of SeDD98 and CsA shifted the gut microbiota composition and increased with higher alpha diversity as well as beneficial bacteria such as Ruminococcaceae_UCG-014 and Lachnospiraceae_NK4A136. In parallel, we assessed if the adjuvant of SeDD98 with CsA had an impact on CsA-induced kidney injury which represents one of the major side effects. We found that SeDD98 significantly improved CsA nephrotoxicity in UC mice. We then validated this observation using chronic kidney disease (CKD) mice induced by CsA administration. These results demonstrated that SeDD98 in combination with CsA was associated with increased efficacy and reduced nephrotoxicity altogether, providing the scientific basis for the adjuvant therapy of probiotics in UC.
MoreTranslated text
Key words
Ulcerative colitis,Mesalazine,Cyclosporin A,Probiotic,CsA-induced nephrotoxicity,Gut microbiome
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- 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
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined