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1,015 results on '"Zhu, Lixia"'

13. High Throughput Sequencing Analysis of Dynamic Changes in Fungal Community Structure of Melon during Storage

Author

ZHENG Heyun, ZHU Lixia, YAO Jun, LI Chao, ZHANG Cuihuan, WANG Zhiwei, GENG Xinli

Subjects
melon, storage period, fungal community structure, high-throughput sequencing, Food processing and manufacture, TP368-456
Abstract

In order to explore the structure and dynamic changes of fungal communities in melon fruit during storage, the internal transcribed spacer (ITS) region of fungi in melon peel and pulp stored for 0, 7, 14, or 21 d was sequenced using Illumina MiSeq high-throughput sequencing technology. Species annotation and species composition analysis were used to determine the dominant fungal communities in the fruit tissues at each storage time point. The results showed that Vishniacozyma, Papiliotrema, and Metarhizium were dominant in the peel on day 0, while Aspergillus, Trichothecium, and Penicillium became dominant as storage time increased. The dominant fungal communities in the flesh also changed as storage time increased, with Vishniacozyma, Trichothecium, and Pichia being the dominant fungi on the 21th day of storage. Diversity analysis showed that fungal abundance and diversity were higher in the peel than in the flesh. In summary, the abundance and diversity of fungal communities in melon tissues changed significantly during storage, and the interaction of pathogenic fungi such as Aspergillus, Trichothecium, and Penicillium resulted in deterioration of melon fruit quality. This study provides a theoretical basis for the development of preservation methods and biological control strategies for melons in the future.

Published
2023
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26. Aroma Threshold and Binary Synergy of Furanone, 5-Methylfurfural and 3-Methylthiopropanol in Msalais Wine

Author

QIAO Tongtong, ZHU Lixia

Subjects
msalais wine, aroma threshold, s-curve, σ-τ plot, synergy, Food processing and manufacture, TP368-456
Abstract

In this study, the three-alternative forced-choice (3-AFC) method was used to determine the odor thresholds of three important aroma compounds in Msalais wine including 5-methylfurfural (5-MF), 2,5-dimethyl-4-hydroxy-3(2H)-furanone (DMHF) and 3-methylthiopropanol (3-MTP), and the S-curve and the σ-τ plot were used to analyze the binary interaction of these compounds. The threshold values of 5-MF, DMHF and 3-MTP in simulated wine with an alcohol content of 12% were 190.000, 45.000 and 382.000 μg/L, respectively, and those in dearomatized Msalais wine with 12% alcohol content (sugar contents of 7.4–7.9 °Brix) were 97.580, 798.950 and 196.533 μg/L, respectively. In addition, it was found that sugar contents of dearomatized Msalais wine (with 12% alcohol content) in the range of 7.4–7.9 °Brix and 6.4–7.9 °Brix had little effect on the thresholds of the three aroma compounds. There was no significant difference in the thresholds of these aroma compounds in dearomatized Msalais wine (with sugar contents of 7.4–7.9 °Brix) with 8%, 10%, 12% and 14% alcohol contents. The binary mixtures of these compounds in simulated wine with 12% alcohol content and in dearomatized Msalais with sugar contents of 7.4–7.9 °Brix and 12% alcohol content showed additive effects in the S-curve and the σ-τ plot.

Published
2023
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36. Multi-Task Deep Learning with Dynamic Programming for Embryo Early Development Stage Classification from Time-Lapse Videos

Author

Liu, Zihan, Huang, Bo, Cui, Yuqi, Xu, Yifan, Zhang, Bo, Zhu, Lixia, Wang, Yang, Jin, Lei, and Wu, Dongrui

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computers and Society, Computer Science - Machine Learning
Abstract

Time-lapse is a technology used to record the development of embryos during in-vitro fertilization (IVF). Accurate classification of embryo early development stages can provide embryologists valuable information for assessing the embryo quality, and hence is critical to the success of IVF. This paper proposes a multi-task deep learning with dynamic programming (MTDL-DP) approach for this purpose. It first uses MTDL to pre-classify each frame in the time-lapse video to an embryo development stage, and then DP to optimize the stage sequence so that the stage number is monotonically non-decreasing, which usually holds in practice. Different MTDL frameworks, e.g., one-to-many, many-to-one, and many-to-many, are investigated. It is shown that the one-to-many MTDL framework achieved the best compromise between performance and computational cost. To our knowledge, this is the first study that applies MTDL to embryo early development stage classification from time-lapse videos.

Published
2019

42. Guidelines for the clinical application of the Xihuang pill for the prevention and treatment of breast hyperplasia diseases

Author

Tang, Hongmei, primary, Lu, Qin, additional, Feng, Shiyin, additional, Xiao, Zhiwei, additional, Wu, Wanyin, additional, Chen, Gaofeng, additional, Deng, Li, additional, Yu, Tianqi, additional, Wu, Junyan, additional, Lin, Hua, additional, Ji, Bo, additional, Lin, Jietao, additional, Zhang, Chengguang, additional, Li, Liming, additional, Liu, Tao, additional, Ouyang, Yong, additional, Lei, Kaijun, additional, Chen, Jun, additional, Peng, Weiwen, additional, Qiu, Zhenwen, additional, Cai, Qingqun, additional, Liang, Qi, additional, Liu, Cuiling, additional, Li, Yuzhen, additional, Zhu, Lixia, additional, Zhang, Zexin, additional, Liu, Xueting, additional, Lin, Lizhu, additional, and Zheng, Zhihua, additional

Published
2024
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