Evidence map›Paper›PMID 42720692›Full record

ArticleCurrent microbiology2026

The Metabolic Reprogramming Mechanism by Pueraria Lobata Fermentation Enhances Saccharomyces cerevisiae Reducing-Sugar-Releasing Activity and Polypeptide Synthesis.

Ji Yin, Yongtao Zhang, Fangyu Guo, Xiaoyu Wang, Dongdong Wang, Dan Zhao, Changtao Wang, Meng Li

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Article in Current microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ji YinSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
Yongtao ZhangSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
Fangyu GuoSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
Xiaoyu WangSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
Dongdong WangSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
Dan ZhaoSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
Changtao WangSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
Meng LiSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China. limeng@btbu.edu.cn.ORCID https://orcid.org/0000-0002-7354-6480

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pueraria lobata is a widely distributed traditional Chinese medicinal herb, and its active constituents have potential value in food, pharmaceutical, cosmetic, and industrial fermentation applications. In this study, P. lobata was used as the substrate and Saccharomyces cerevisiae as the fermenting organism. Response surface methodology was employed to optimize fermentation conditions using peptide concentration in the broth as the target response. The effects of P. lobata on S. cerevisiae were evaluated by measuring yeast colony counts, protease activity, and sodium alginate-based reducing-sugar-releasing activity. Transcriptomic profiling combined with GO/KEGG enrichment analyses and qRT-PCR validation was further used to analyze gene expression differences in S. cerevisiae at 5, 24, and 48 h. The optimal fermentation conditions were 71 h, 22.41 °C, and a solid-to-liquid ratio of 1:20, under which the peptide concentration reached 32.37 mg/mL. Relative to conventional yeast medium, protease activity and reducing-sugar-releasing activity in the P. lobata fermentation broth increased by 2.37-fold and 10.1-fold, respectively. Supplementation with 10% P. lobata most effectively promoted S. cerevisiae proliferation, resulting in the highest colony count of 6.8 × 10

Indexed as

Peptide BiosynthesisPeptidesPuerariaSaccharomyces cerevisiaeFermentationGene Expression ProfilingPeptides

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.