LIVIVO - Search results -

Search results

Result 1 - 10 of total 84

Search options

Article ; Online: Characterization and Biological Activities of Four Biotransformation Products of Diosgenin from Rhodococcus erythropolis

Yanjie Li / Chengyu Zhang / Kexin Kong / Xiaohui Yan

Molecules, Vol 28, Iss 3093, p

2023 Volume 3093

Abstract: Diosgenin (DSG), a steroidal sapogenin derived from the tuberous roots of yam, possesses multiple biological properties. DSG has been widely used as a starting material for the industrial production of steroid drugs. Despite its significant ... ...

Abstract	Diosgenin (DSG), a steroidal sapogenin derived from the tuberous roots of yam, possesses multiple biological properties. DSG has been widely used as a starting material for the industrial production of steroid drugs. Despite its significant pharmacological activities, moderate potency and low solubility hinder the medicinal application of DSG. Biotransformation is an efficient method to produce valuable derivatives of natural products. In this work, we performed the biotransformation of DSG using five Rhodococcus strains. Compounds 1 – 4 were isolated and identified from Rhodococcus erythropolis . Compounds 1 and 2 showed potent cytotoxicity against the A549, MCF-7, and HepG2 cell lines. Compounds 3 and 4 are novel entities, and each possesses a terminal carboxyl group attached to the spiroacetal ring. Remarkably, 4 exhibited significant cell protective effects for kidney, liver, and vascular endothelial cells, suggesting the therapeutic potential of this compound in chronic renal diseases, atherosclerosis, and hypertension. We further optimized the fermentation conditions aiming to increase the titer of compound 4 . Finally, the yield of compound 4 was improved by 2.9-fold and reached 32.4 mg/L in the optimized conditions. Our study lays the foundation for further developing compound 4 as a cell protective agent.
Keywords	diosgenin ; biotransformation ; Rhodococcus erythropolis ; cyto-protection ; Organic chemistry ; QD241-441
Subject code	540
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Editorial

Yanjie Li / Cong Xu / Weiqi Yan

Frontiers in Forests and Global Change, Vol

Forest phenomics: how does developing sensor technology improve the growth of forest plantations?

2023 Volume 6

Keywords	forest management ; high-precision ; high-throughput ; forest phenomics ; sensor-based plant phenomics ; Forestry ; SD1-669.5 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Evaluation and Construction of College Students’ Growth and Development Index System Based on Data Association Mining and Deep Learning Model

Yanjie Li / He Mao

Security and Communication Networks, Vol

2021 Volume 2021

Abstract: The rise of big data in the field of education provides an opportunity to solve college students’ growth and development. The establishment of a personalized student management mode based on big data in universities will promote the change of ... ...

Abstract	The rise of big data in the field of education provides an opportunity to solve college students’ growth and development. The establishment of a personalized student management mode based on big data in universities will promote the change of personalized student management from the empirical mode to the scientific mode, from passive response to active warning, from reliance on point data to holistic data, and thus improve the efficiency and quality of personalized student management. In this paper, using the latest ideas and techniques in deep learning such as self-supervised learning and multitask learning, we propose an open-source educational big data pretrained language model F-BERT based on the BERT model architecture. Based on the BERT architecture, F-BERT can effectively and automatically extract knowledge from educational big data and memorize it in the model without modifying the model structure specific to educational big data tasks so that it can be directly applied to various educational big data domain tasks downstream. The experiment demonstrates that Vanilla F-BERT outperformed the two Vanilla BERT-based models, Vanilla BERT and BERT tasks, by 0.0.6 and 0.03 percent, respectively, in terms of accuracy.
Keywords	Technology (General) ; T1-995 ; Science (General) ; Q1-390
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Hindawi-Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Classification of tree symbiotic fungi based on hyperspectral imagery and hybrid convolutional neural networks

Zhuo Liu / Mahmoud Al-Sarayreh / Yanjie Li / Zhilin Yuan

Frontiers in Forests and Global Change, Vol

2023 Volume 6

Abstract: Hyperspectral imagery and machine learning have proven to be powerful, non-invasive, and chemical-free tools for studying tree symbiotic fungi. However, traditional machine learning requires manual feature extraction (feature engineering) of spectral and ...

Abstract	Hyperspectral imagery and machine learning have proven to be powerful, non-invasive, and chemical-free tools for studying tree symbiotic fungi. However, traditional machine learning requires manual feature extraction (feature engineering) of spectral and spatial features of tree symbiotic fungi. Deep convolutional neural networks (CNNs) can extract self and robust features directly from the raw data. In the current study, a deep CNN architecture is proposed to recognize the isolates of dark septate endophytic (DSE) fungal in hyperspectral images. The performance of different CNN approaches (two-dimensional and three-dimensional CNNs) was compared and evaluated based on two independent datasets collected using visible-near-infrared (VNIR) and short-wave-infrared (SWIR) hyperspectral imaging systems. Moreover, the impact of different spectral pre-processing techniques was investigated. The results show that a hybrid CNN architecture (3D-2D CNN), which combines three and two-dimensional CNNs, achieved the best performance for the classification of fungal isolates on SWIR hyperspectral data compared to the same architecture on VNIR hyperspectral data. The best performance is 100% for precision, recall, and overall accuracy. The results also demonstrate that combining different pre-processing techniques on raw SWIR spectra can significantly improve the performance of the CNN models for fungal classification. The hybrid CNN approach with SWIR hyperspectral data provides an efficient method for classifying fungal isolates, which can contribute to the development of accurate and non-destructive tools for evaluating the occurrence of fungal isolates on trees. Such tools can be beneficial for both sustainable agriculture and preserving fungal diversity.
Keywords	dark septate endophytes (DSEs) ; 2D-CNN ; 3D-CNN ; deep learning ; spectral pre-processing ; hyperspectral imaging (HSI) ; Forestry ; SD1-669.5 ; Environmental sciences ; GE1-350
Subject code	571
Language	English
Publishing date	2023-05-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Spectrometric Prediction of Nitrogen Content in Different Tissues of Slash Pine Trees

Yanjie Li / Honggang Sun / Federico Tomasetto / Jingmin Jiang / Qifu Luan

Plant phenomics. 2022, v. 2022

2022

Abstract: The internal cycling of nitrogen (N) storage and consumption in trees is an important physiological mechanism associated with tree growth. Here, we examined the capability of near-infrared spectroscopy (NIR) to quantify the N concentration across tissue ... ...

Abstract	The internal cycling of nitrogen (N) storage and consumption in trees is an important physiological mechanism associated with tree growth. Here, we examined the capability of near-infrared spectroscopy (NIR) to quantify the N concentration across tissue types (needle, trunk, branch, and root) without time and cost-consuming. The NIR spectral data of different tissues from slash pine trees were collected, and the N concentration in each tissue was determined using standard analytical method in laboratory. Partial least squares regression (PLSR) models were performed on a set of training data randomly selected. The full-length spectra and the significant multivariate correlation (sMC) variable selected spectra were used for model calibration. Branch, needle, and trunk PLSR models performed well for the N concentration using both full length and sMC selected NIR spectra. The generic model preformatted a reliable accuracy with R2C and R2CV of 0.62 and 0.66 using the full-length spectra, and 0.61 and 0.65 using sMC-selected spectra, respectively. Individual tissue models did not perform well when being used in other tissues. Five significantly important regions, i.e., 1480, 1650, 1744, 2170, and 2390 nm, were found highly related to the N content in plant tissues. This study evaluates a rapid and efficient method for the estimation of N content in different tissues that can help to serve as a tool for tree N storage and recompilation study.
Keywords	Pinus elliottii ; models ; near-infrared spectroscopy ; nitrogen ; nitrogen content ; phenomics ; prediction ; spectral analysis ; tree growth ; trees
Language	English
Publishing place	American Association for the Advancement of Science (AAAS)
Document type	Article
ISSN	2643-6515
DOI	10.34133/2022/9892728
Database	NAL-Catalogue (AGRICOLA)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Rapid monitoring of flavonoid content in sweet tea (Lithocarpus litseifolius (Hance) Chun) leaves using NIR spectroscopy

Zhaoxia Tian / Zifeng Tan / Yanjie Li / Zhiling Yang

Plant Methods, Vol 18, Iss 1, Pp 1-

2022 Volume 9

Abstract: Abstract Background Sweet tea, which functions as tea, sugar and medicine, was listed as a new food resource in 2017. Flavonoids are the main medicinal components in sweet tea and have significant pharmacological activities. Therefore, the quality of ... ...

Abstract	Abstract Background Sweet tea, which functions as tea, sugar and medicine, was listed as a new food resource in 2017. Flavonoids are the main medicinal components in sweet tea and have significant pharmacological activities. Therefore, the quality of sweet tea is related to the content of flavonoids. Flavonoid content in plants is normally determined by time-consuming and expensive chemical analyses. The aim of this study was to develop a methodology to measure three constituents of flavonoids, namely, total flavonoids, phloridin and trilobatin, in sweet tea leaves using near-infrared spectroscopy (NIR). Results In this study, we demonstrated that the combination of principal component analysis (PCA) and NIR spectroscopy can distinguish sweet tea from different locations. In addition, different spectral preprocessing methods are used to establish partial least squares (PLS) models between spectral information and the content of the three constituents. The best total flavonoid prediction model was obtained with NIR spectra preprocessed with Savitzky–Golay combined with second derivatives (SG + D2) (RP 2 = 0.893, and RMSEP = 0.131). For trilobatin, the model with the best performance was developed with raw NIR spectra (RP 2 = 0.902, and RMSEP = 2.993), and for phloridin, the best model was obtained with NIR spectra preprocessed with standard normal variate (SNV) (RP 2 = 0.818, and RMSEP = 1.085). The coefficients of determination for all calibration sets, validation sets and prediction sets of the best PLS models were higher than 0.967, 0.858 and 0.818, respectively. Conclusions The conclusion indicated that NIR spectroscopy has the ability to determine the flavonoid content of sweet tea quickly and conveniently.
Keywords	Sweet tea ; Flavonoids content ; Near-infrared (NIR) spectroscopy ; Partial least squares (PLS) model ; Model calibration ; Plant culture ; SB1-1110 ; Biology (General) ; QH301-705.5
Subject code	571
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: A Two-Objective ILP Model of OP-MATSP for the Multi-Robot Task Assignment in an Intelligent Warehouse

Jianqi Gao / Yanjie Li / Yunhong Xu / Shaohua Lv

Applied Sciences, Vol 12, Iss 4843, p

2022 Volume 4843

Abstract: Multi-robot task assignment is one of the main processes in an intelligent warehouse. This paper models multi-robot task assignment in an intelligent warehouse as an open-path multi-depot asymmetric traveling salesman problem (OP-MATSP). A two-objective ... ...

Abstract	Multi-robot task assignment is one of the main processes in an intelligent warehouse. This paper models multi-robot task assignment in an intelligent warehouse as an open-path multi-depot asymmetric traveling salesman problem (OP-MATSP). A two-objective integer linear programming (ILP) model for solving OP-MDTSP is proposed. The theoretical bound on the computational time complexity of this model is <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mo>!</mo><mo>)</mo></mrow></semantics></math> . We can solve the small multi-robot task assignment problem by solving the two-objective ILP model using the Gurobi solver. The multi-chromosome coding-based genetic algorithm has a smaller search space, so we use it to solve large-scale problems. The experiment results reveal that the two-objective ILP model is very good at solving small-scale problems. For large-scale problems, both EGA and NSGA3 genetic algorithms can efficiently obtain suboptimal solutions. It demonstrates that this paper’s multi-robot work assignment methods are helpful in an intelligent warehouse.
Keywords	multi-robot task assignment ; intelligent warehouse ; OP-MATSP ; ILP ; genetic algorithm ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	629
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Comparative Assessment of Sustainable Consumption Based on the Digital Information Environment Content-Thematic Component Differentiation

Yanjie Li / Daria Terenteva / Olga Konnikova / Evgenii Konnikov

Sustainability, Vol 13, Iss 7215, p

2021 Volume 7215

Abstract: The modern culture of consumption often does not correspond to the principles of sustainable development, which leads to environmental pollution. As a possible solution to this problem, the authors propose to analyze the concept of sustainable ... ...

Abstract	The modern culture of consumption often does not correspond to the principles of sustainable development, which leads to environmental pollution. As a possible solution to this problem, the authors propose to analyze the concept of sustainable consumption, following which can reduce the negative impact of mankind on the environment, which is an urgent issue at the global level. The aim of the study is to build a tool for comparative analysis of the level of sustainable consumption. The analysis is carried out in the digital environment, since this space provides a relative freedom of expression of the opinion of individuals, and the obtained data reflect the real level of “sustainability” of the behavior of participants in thematic social communities. The result of the research is an analytical tool tested on thematic social communities of the VK.com social network. In the process of building an analytical tool, primary and secondary tokenization were carried out using computer linguistics tools, an analytical dataframe was formed for a source reflecting the studied content-thematic component. To automate the process of forming a set of tokens, Python 3 programming language was used. The proposed tool can be used to determine the level of sustainable consumption in different social communities relative to each other. This approach can be used by companies to find target audiences and to promote environmentally friendly products. Moreover, this tool can be applied to attract consumers by increasing the level of sustainability in the corporate culture based on the research results. A separate problematic of realizing the developed methodology is the ethical component of analyzing natural digital information and the use of the results obtained on the basis of its analysis.
Keywords	sustainable consumption ; information environment ; content-thematic component ; tonal component ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Estimation of Plant Height and Aboveground Biomass of Toona sinensis under Drought Stress Using RGB-D Imaging

Wenjian Liu / Yanjie Li / Jun Liu / Jingmin Jiang

Forests, Vol 12, Iss 1747, p

2021 Volume 1747

Abstract: Rapid and accurate plant growth and biomass estimation is essential for formulating and implementing targeted forest cultivation measures. In this study, RGB-D imaging technology was used to obtain the RGB and depth imaging data for a Toona sinensis ... ...

Abstract	Rapid and accurate plant growth and biomass estimation is essential for formulating and implementing targeted forest cultivation measures. In this study, RGB-D imaging technology was used to obtain the RGB and depth imaging data for a Toona sinensis seedling canopy to estimate plant growth and aboveground biomass (AGB). Three hundred T. sinensis seedlings from 20 varieties were planted under five different drought stress treatments. The U-Net model was applied first to achieve highly accurate segmentation of plants from complex backgrounds. Simple linear regression (SLR) was used for plant height prediction, and the other three models, including multivariate linear (ML), random forest (RF) and multilayer perceptron (MLP) regression, were applied to predict the AGB and compared for optimal model selection. The results showed that the SLR model yields promising and reliable results for the prediction of plant height, with R 2 and RMSE values of 0.72 and 1.89 cm, respectively. All three regression methods perform well in the prediction of AGB estimation. MLP yields the highest accuracy in predicting dry and fresh aboveground biomass compared to the other two regression models, with R 2 values of 0.77 and 0.83, respectively. The combination of Gray, Green minus red (GMR) and Excess green index (ExG) was identified as the key predictor by RReliefF for predicting dry AGB. GMR was the most important in predicting fresh AGB. This study demonstrated that the merits of RGB-D and machine learning models are effective phenotyping techniques for plant height and AGB prediction, and can be used to assist dynamic responses to drought stress for breeding selection.
Keywords	RGB-D imaging ; Toona sinensis seedling ; aboveground biomass ; plant height ; machine learning ; Plant ecology ; QK900-989
Subject code	580
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: RhoA vesicle trafficking–mediated transglutaminase 2 membrane translocation promotes IgA1 mesangial deposition in IgA nephropathy

Zhong Zhong / Zhijian Li / Yanjie Li / Lanping Jiang / Qingyu Kong / Wei Chen / Shaozhen Feng

JCI Insight, Vol 8, Iss

2023 Volume 19

Abstract: Transglutaminase 2 (TGase2) has been shown to contribute to the mesangial IgA1 deposition in a humanized mouse model of IgA nephropathy (IgAN), but the mechanism is not fully understood. In this study, we found that inhibition of TGase2 activity could ... ...

Abstract	Transglutaminase 2 (TGase2) has been shown to contribute to the mesangial IgA1 deposition in a humanized mouse model of IgA nephropathy (IgAN), but the mechanism is not fully understood. In this study, we found that inhibition of TGase2 activity could dramatically decrease the amount of polymeric IgA1 (pIgA1) isolated from patients with IgAN that interacts with human mesangial cells (HMC). TGase2 was expressed both in the cytosol and on the membrane of HMC. Upon treatment with pIgA1, there were more TGase2 recruited to the membrane. Using a cell model of mesangial deposition of pIgA1, we identified 253 potential TGase2-associated proteins in the cytosolic fraction and observed a higher concentration of cellular vesicles and increased expression of Ras homolog family member A (RhoA) in HMC after pIgA1 stimulation. Both the amount of pIgA1 deposited on HMC and membrane TGase2 level were decreased by inhibition of the vesicle trafficking pathway. Mechanistically, TGase2 was found to be coprecipitated with RhoA in the cellular vesicles. Membrane TGase2 expression was greatly increased by overexpression of RhoA, while it was reduced by knockdown of RhoA. Our in vitro approach demonstrated that TGase2 was transported from the cytosol to the membrane through a RhoA-mediated vesicle-trafficking pathway that can facilitate pIgA1 interaction with mesangium in IgAN.
Keywords	Nephrology ; Medicine ; R
Subject code	570
Language	English
Publishing date	2023-10-01T00:00:00Z
Publisher	American Society for Clinical investigation
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED