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Hu, Y.-F.

Publications and source records attributed to Hu, Y.-F..

2 recordsLinked to original sources

Characterization and identification of a novel daidzein reductase involved in (S)-equol biosynthesis in Clostridium C1

(S)-equol is an isoflavone with high estrogen-like activity and no toxic effects in the human body, and is only produced by some gut bacteria in vivo. It plays an important role in maintaining individual health, however, the dearth of resources associated with (S)-equol-producing bacteria has seriously restricted the production and application of (S)-equol. We report here a novel functional gene C1-07020 that was identified from a chick (S)-equol-producing bacterium (Clostridium C1). We found that recombinant protein of C1-07020 possessed similar function to daidzein reductase (DZNR), which can convert daidzein (DZN) into R/S-dihydrodaidzein (R/S-DHD). Interestingly, C1-07020 can reverse convert (R/S)-DHD (DHD oxidases) into DZN even without cofactors or anaerobic conditions. Additionally, high concentrations of (S)-equol can directly promote DHD oxidase but inhibit DZNR activity. Molecular docking and site-directed mutagenesis revealed that the amino acid Arg 75 was the active site of DHD oxidases. Subsequently, an engineered E. coli strain based on C1-07020 was constructed and showed higher yield of (S)-equol than the engineered bacteria from our previous work. Metagenomics analysis and PCR detection surprisingly revealed that C1-07020 and related bacteria may be prevalent in the gut of humans and animals and their (S)-equol production state may cause differed between (S)-equol producer and non-producer. Overall, a novel DZNR from Clostridium C1 was found and identified in this study, and its bidirectional enzyme activities and wide distribution in the gut of humans and animals provide alternative strategies for revealing the individual regulatory mechanisms of (S)-equol-producing bacteria. Importance(S)-equol is a final product of DZN that metabolized by some enteric bacteria. Although (S)-equol played very important roles in maintaining human health, larger differences in equol production varied between different populations. Here, a novel DZNR gene C1-07020, which related to (S)-equol production, was reported. The bidirectional enzyme functions and wide distribution of C1-07020 in human and animal gut provided additional insights into the metabolic regulation of (S)-equol. Additionally, C1-07020 can be used for improving the production of (S)-equol in vitro.

microbiology↗

Detection and Classification of Cardiac Arrhythmias by a Challenge-Best Deep Learning Neural Network Model

BackgroundElectrocardiogram (ECG) is widely used to detect cardiac arrhythmia (CA) and heart diseases. The development of deep learning modeling tools and publicly available large ECG data in recent years has made accurate machine diagnosis of CA an attractive task to showcase the power of artificial intelligence (AI) in clinical applications.\n\nMethods and FindingsWe have developed a convolution neural network (CNN)-based model to detect and classify nine types of heart rhythms using a large 12-lead ECG dataset (6877 recordings) provided by the China Physiological Signal Challenge (CPSC) 2018. Our model achieved a median overall F1-score of 0.84 for the 9-type classification on CPSC2018s hidden test set (2954 ECG recordings), which ranked first in this latest AI competition of ECG-based CA diagnosis challenge. Further analysis showed that concurrent CAs observed in the same patient were adequately predicted for the 476 patients diagnosed with multiple CA types in the dataset. Analysis also showed that the performances of using only single lead data were only slightly worse than using the full 12 lead data, with leads aVR and V1 being the most prominent. These results are extensively discussed in the context of their agreement with and relevance to clinical observations.\n\nConclusionsAn AI model for automatic CA diagnosis achieving state-of-the-art accuracy was developed as the result of a community-based AI challenge advocating open-source research. In- depth analysis further reveals the models ability for concurrent CA diagnosis and potential use of certain single leads such as aVR in clinical applications.\n\nAbbreviationsCA, cardiac arrhythmia; AF, Atrial fibrillation; I-AVB, first-degree atrioventricular block; LBBB, left bundle branch block; RBBB, right bundle branch block; PAC, premature atrial contraction; PVC, premature ventricular contraction; STD, ST-segment depression; STE, ST-segment elevation.

bioinformatics↗