Optimization of tetrastigma hemsleyanum extraction process based on GA-BPNN model and analysis of its antioxidant effect

Shu, Jianhao; Zhao, Yali; Zhou, Yehui; Lin, Feifei; Song, Jingmei; Li, Xiaohong

doi:10.1016/j.heliyon.2023.e20200

Cited by 2 publications

(2 citation statements)

References 37 publications

(39 reference statements)

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“…In the experiment, the activation function is ReLU [ 21 ], the loss function adopts mean square error (MSE), and the optimizer is Adam [ 22 ]. The input of the network is 205 groups of mixed molecular descriptors, and the output is the measured value of ternary mixed liquid AIT.…”

Section: Model Developmentmentioning

confidence: 99%

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Neural network-based prediction of auto-ignition temperature of ternary mixed liquids

Guo,

Cheng,

2024

Heliyon

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Section: Model Developmentmentioning

confidence: 99%

“…The BP algorithm is a gradient descent algorithm that makes learning of feedforward networks easier [ 21 , 22 ]. Fig.…”

Section: Model Developmentmentioning

confidence: 99%

Neural network-based prediction of auto-ignition temperature of ternary mixed liquids

Guo,

Cheng,

2024

Heliyon

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Studies on Differentially Expressed Genes of Tetrastigma hemsleyanum and Its Antitumor Activity

Chen,

Li,

et al. 2024

Natural Product Communications

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Objective: To analyze highly expressed genes in Tetrastigma hemsleyanum roots and the in vitro antitumor effects of extracts from different parts of this plant. Methods: The expression profiles of the roots, stems, and leaves of T hemsleyanum were analyzed via high-throughput sequencing technology with the Illumina Genome Analyzer platform. Then, gene ontology (GO) functional and pathway enrichment analyses of the significantly differentially expressed genes were performed. The inhibition rates of the extracts from different plant parts were determined through the CCK-8 method. Results: Genes related to catalytic activity and cytochrome P450 were upregulated in roots compared with leaves. The genes that we screened that were expressed at high levels in the roots may play an important role in the accumulation of active ingredients. GO functional enrichment analysis revealed that there were substantial differences in genes related to metabolic processes in roots compared with those in stems, and KEGG analysis revealed significant differences in genes related to the zeatin biosynthesis and diterpenoid biosynthesis pathways. Moreover, the expression of genes related to catalytic activity, ion binding, and hydrolase activity differed significantly between the roots and leaves, and KEGG analysis revealed significant differences in the expression of genes related to terpenoid biosynthesis and flavonoid biosynthesis pathways. Quantitative PCR indicated that Thhg was highly expressed in roots. The total triterpene content was also high in the tissue. The CCK-8 assays showed that the root ethanol extract had the highest antitumor activity. Conclusion: The genes we screened that were expressed at high levels in the roots may play an important role in the accumulation of active ingredients. Importantly, stem and leaf ethanol extracts also showed certain antitumor effects on human HCC Huh-7 and Hep3B cells in vitro and may also have medicinal value.

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Optimization of tetrastigma hemsleyanum extraction process based on GA-BPNN model and analysis of its antioxidant effect

Cited by 2 publications

References 37 publications

Neural network-based prediction of auto-ignition temperature of ternary mixed liquids

Neural network-based prediction of auto-ignition temperature of ternary mixed liquids

Studies on Differentially Expressed Genes of Tetrastigma hemsleyanum and Its Antitumor Activity

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