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Article: Dynamic distribution of

Xu, Ailing / Liu, Congcong / Zhao, Shuke / Song, Zhiwen / Sun, Hui

2023 Volume 14, Page(s) 1211649

Abstract: Introduction: Massilia: Methods: In this paper, the in-house-designed primers were used to construct a 16S rDNA clone library of : Results: The results showed that the 16S rDNA clone library in primer 5 worked well. According to the clone library ... ...

Abstract	Introduction: Massilia Methods: In this paper, the in-house-designed primers were used to construct a 16S rDNA clone library of Results: The results showed that the 16S rDNA clone library in primer 5 worked well. According to the clone library diversity index analysis, the richness of Discussion: The above results indicated that the species of
Language	English
Publishing date	2023-07-27
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2587354-4
ISSN	1664-302X
ISSN	1664-302X
DOI	10.3389/fmicb.2023.1211649
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A predictive model for social participation of middle-aged and older adult stroke survivors

Yan Liu / Tian Li / Linlin Ding / ZhongXiang Cai / Shuke Nie

Frontiers in Public Health, Vol

the China Health and Retirement Longitudinal Study

2024 Volume 11

Abstract: ObjectiveThis study aims to develop and validate a prediction model for evaluating the social participation in the community middle-aged and older adult stroke survivors.MethodsThe predictive model is based on data from the China Health and Retirement ... ...

Abstract	ObjectiveThis study aims to develop and validate a prediction model for evaluating the social participation in the community middle-aged and older adult stroke survivors.MethodsThe predictive model is based on data from the China Health and Retirement Longitudinal Study (CHARLS), which focused on individuals aged 45 years or older. The study utilized subjects from the CHARLS 2015 and 2018 wave, eighteen factors including socio-demographic variables, behavioral and health status, mental health parameters, were analyzed in this study. To ensure the reliability of the model, the study cohort was randomly split into a training set (70%) and a validation set (30%). The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to identify the most effective predictors of the model through a 10-fold cross-validation. The logistic regression model was employed to investigate the factors associated with social participation in stroke patients. A nomogram was constructed to develop a prediction model. Calibration curves were used to assess the accuracy of the nomogram model. The model’s performance was evaluated using the area under the curve (AUC) and decision curve analysis (DCA).ResultA total of 1,239 subjects with stroke from the CHARLS database collected in 2013 and 2015 wave were eligible in the final analysis. Out of these, 539 (43.5%) subjects had social participation. The model considered nineteen factors, the LASSO regression selected eleven factors, including age, gender, residence type, education level, pension, insurance, financial dependence, physical function (PF), self-reported healthy,cognition and satisfaction in the prediction model. These factors were used to construct the nomogram model, which showed a certain extent good concordance and accuracy. The AUC values of training and internal validation sets were 0.669 (95%CI 0.631–0.707) and 0.635 (95% CI 0.573–0.698), respectively. Hosmer–Lemeshow test values were p = 0.588 and p = 0.563. Calibration curves showed agreement ...
Keywords	stroke ; middle-aged and older adults ; social participation ; prediction model ; nomogram ; Public aspects of medicine ; RA1-1270
Subject code	300
Language	English
Publishing date	2024-01-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Directed Evolution and Immobilization of Lactobacillus brevis Alcohol Dehydrogenase for Chemo-Enzymatic Synthesis of Rivastigmine.

Su, Guorong / Ran, Lu / Liu, Chang / Qin, Zhaoyang / Teng, Huailong / Wu, Shuke

Chemistry (Weinheim an der Bergstrasse, Germany)

2024 , Page(s) e202400454

Abstract: Rivastigmine is one of the several pharmaceuticals widely prescribed for the treatment of Alzheimer's disease. However, its practical synthesis still faces many issues, such as the involvement of toxic metals and harsh reaction conditions. Herein, we ... ...

Abstract	Rivastigmine is one of the several pharmaceuticals widely prescribed for the treatment of Alzheimer's disease. However, its practical synthesis still faces many issues, such as the involvement of toxic metals and harsh reaction conditions. Herein, we report a chemo-enzymatic synthesis of Rivastigmine. The key chiral intermediate was synthesized by an engineered alcohol dehydrogenase from Lactobacillus brevis (LbADH). A semi-rational approach was employed to improve its catalytic activity and thermal stability. Several LbADH variants were obtained with a remarkable increase in activity and melting temperature. Exploration of the substrate scope of these variants demonstrated improved activities toward various ketones, especially acetophenone analogs. To further recycle and reuse the biocatalyst, one LbADH variant and glucose dehydrogenase were co-immobilized on nanoparticles. By integrating enzymatic and chemical steps, Rivastigmine was successfully synthesized with an overall yield of 66 %. This study offers an efficient chemo-enzymatic route for Rivastigmine and provides several efficient LbADH variants with a broad range of potential applications.
Language	English
Publishing date	2024-04-03
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1478547-X
ISSN	1521-3765 ; 0947-6539
ISSN (online)	1521-3765
ISSN	0947-6539
DOI	10.1002/chem.202400454
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Article ; Online: A predictive model for social participation of middle-aged and older adult stroke survivors: the China Health and Retirement Longitudinal Study.

Liu, Yan / Li, Tian / Ding, Linlin / Cai, ZhongXiang / Nie, Shuke

Frontiers in public health

2024 Volume 11, Page(s) 1271294

Abstract: Objective: This study aims to develop and validate a prediction model for evaluating the social participation in the community middle-aged and older adult stroke survivors.: Methods: The predictive model is based on data from the China Health and ... ...

Abstract	Objective: This study aims to develop and validate a prediction model for evaluating the social participation in the community middle-aged and older adult stroke survivors. Methods: The predictive model is based on data from the China Health and Retirement Longitudinal Study (CHARLS), which focused on individuals aged 45 years or older. The study utilized subjects from the CHARLS 2015 and 2018 wave, eighteen factors including socio-demographic variables, behavioral and health status, mental health parameters, were analyzed in this study. To ensure the reliability of the model, the study cohort was randomly split into a training set (70%) and a validation set (30%). The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to identify the most effective predictors of the model through a 10-fold cross-validation. The logistic regression model was employed to investigate the factors associated with social participation in stroke patients. A nomogram was constructed to develop a prediction model. Calibration curves were used to assess the accuracy of the nomogram model. The model's performance was evaluated using the area under the curve (AUC) and decision curve analysis (DCA). Result: A total of 1,239 subjects with stroke from the CHARLS database collected in 2013 and 2015 wave were eligible in the final analysis. Out of these, 539 (43.5%) subjects had social participation. The model considered nineteen factors, the LASSO regression selected eleven factors, including age, gender, residence type, education level, pension, insurance, financial dependence, physical function (PF), self-reported healthy,cognition and satisfaction in the prediction model. These factors were used to construct the nomogram model, which showed a certain extent good concordance and accuracy. The AUC values of training and internal validation sets were 0.669 (95%CI 0.631-0.707) and 0.635 (95% CI 0.573-0.698), respectively. Hosmer-Lemeshow test values were Conclusion: The nomogram constructed in this study can be used to evaluate the probability of social participation in middle-aged individuals and identify those who may have low social participation after experiencing a stroke.
MeSH term(s)	Middle Aged ; Humans ; Aged ; Retirement ; Longitudinal Studies ; Reproducibility of Results ; Social Participation ; China
Language	English
Publishing date	2024-01-12
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2023.1271294
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Article ; Online: Enhancing urban ecological resilience through integrated green technology progress: evidence from Chinese cities.

Fu, Shuke / Liu, Jiabei / Wang, Jinwei / Tian, Jiali / Li, Xiaofan

Environmental science and pollution research international

2023

Abstract: The effective resolution of environmental pollution caused by carbon haze through coordinated progress in green technology and urban ecological resilience is a crucial approach towards promoting sustainable development in Chinese cities. In this study, ... ...

Abstract	The effective resolution of environmental pollution caused by carbon haze through coordinated progress in green technology and urban ecological resilience is a crucial approach towards promoting sustainable development in Chinese cities. In this study, panel data from 281 cities in China from 2007 to 2019 were analyzed using the entropy method and the coupling coordination degree model to determine the coupling coordination degree between green technology progress and urban ecological resilience. The coordinated influence model and threshold model were applied to investigate coupled coordination types and influencing factors. Results indicate that green technology progress levels have shown an upward trend with increasing volatility from east to west and decreasing volatility with urban scale expansion. Ecological resilience levels have also steadily increased, albeit at a reduced rate. The coupling coordination degree of green technology progress and urban ecological resilience has evolved overall from low to high levels; however, the coupling coordination type has regressed to some extent, with most regions exhibiting lagging green technological progress. Pressure resilience has a positive impact on the coupling coordination degree, while state resilience and response resilience have a negative impact. Green technology progress has a dual threshold effect on the coupling coordination degree. By exploring the coupling and coordination mechanism between green technology progress and urban ecological resilience, this study not only facilitates collaborative management of pollutants and greenhouse gases in cities but also provides a comprehensive reference for the construction of an institutional system for collaborative carbon and haze management.
Language	English
Publishing date	2023-08-28
Publishing country	Germany
Document type	Journal Article
ZDB-ID	1178791-0
ISSN	1614-7499 ; 0944-1344
ISSN (online)	1614-7499
ISSN	0944-1344
DOI	10.1007/s11356-023-29451-3
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Article: Impact of Insect-Resistant Transgenic Maize 2A-7 on Diversity and Dynamics of Bacterial Communities in Rhizosphere Soil.

Xu, Xiaohui / Liu, Xin / Li, Fan / Hao, Chaofeng / Sun, Hongwei / Yang, Shuke / Jiao, Yue / Lu, Xingbo

Plants (Basel, Switzerland)

2023 Volume 12, Issue 10

Abstract: Artificial modification ... ...

Abstract	Artificial modification of
Language	English
Publishing date	2023-05-21
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2704341-1
ISSN	2223-7747
ISSN	2223-7747
DOI	10.3390/plants12102046
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Article ; Online: Addition of amino acids modulates the in vitro digestibility of corn starch.

Yue, Shuke / Wang, Huaibin / Xu, Huixian / Liu, Hongsheng / Yu, Wenwen

Carbohydrate polymers

2022 Volume 293, Page(s) 119745

Abstract: The addition of amino acids (AAs) including glycine (Gly), lysine (Lys) and glutamic acid (Glu) with different concentrations on starch morphological, physicochemical and in vitro digestion properties were studied. While AAs showed no effects on neither ... ...

Abstract	The addition of amino acids (AAs) including glycine (Gly), lysine (Lys) and glutamic acid (Glu) with different concentrations on starch morphological, physicochemical and in vitro digestion properties were studied. While AAs showed no effects on neither morphology nor crystalline characters, they all significantly influenced the starch relative crystallinity and swelling capacity in an order of Glu > Lys > Gly. For all samples, both fastly- and slowly- digestible starch fractions (S
MeSH term(s)	Acids ; Amino Acids/chemistry ; Digestion ; Lysine ; Starch/chemistry ; Zea mays/metabolism
Chemical Substances	Acids ; Amino Acids ; Starch (9005-25-8) ; Lysine (K3Z4F929H6)
Language	English
Publishing date	2022-06-21
Publishing country	England
Document type	Journal Article
ZDB-ID	1501516-6
ISSN	1879-1344 ; 0144-8617
ISSN (online)	1879-1344
ISSN	0144-8617
DOI	10.1016/j.carbpol.2022.119745
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Article ; Online: SS-GNN: A Simple-Structured Graph Neural Network for Affinity Prediction.

Zhang, Shuke / Jin, Yanzhao / Liu, Tianmeng / Wang, Qi / Zhang, Zhaohui / Zhao, Shuliang / Shan, Bo

ACS omega

2023 Volume 8, Issue 25, Page(s) 22496–22507

Abstract: Efficient and effective drug-target binding affinity (DTBA) prediction is a challenging task due to the limited computational resources in practical applications and is a crucial basis for drug screening. Inspired by the good representation ability of ... ...

Abstract	Efficient and effective drug-target binding affinity (DTBA) prediction is a challenging task due to the limited computational resources in practical applications and is a crucial basis for drug screening. Inspired by the good representation ability of graph neural networks (GNNs), we propose a simple-structured GNN model named SS-GNN to accurately predict DTBA. By constructing a single undirected graph based on a distance threshold to represent protein-ligand interactions, the scale of the graph data is greatly reduced. Moreover, ignoring covalent bonds in the protein further reduces the computational cost of the model. The graph neural network-multilayer perceptron (GNN-MLP) module takes the latent feature extraction of atoms and edges in the graph as two mutually independent processes. We also develop an edge-based atom-pair feature aggregation method to represent complex interactions and a graph pooling-based method to predict the binding affinity of the complex. We achieve state-of-the-art prediction performance using a simple model (with only 0.6 M parameters) without introducing complicated geometric feature descriptions. SS-GNN achieves Pearson's
Language	English
Publishing date	2023-06-15
Publishing country	United States
Document type	Journal Article
ISSN	2470-1343
ISSN (online)	2470-1343
DOI	10.1021/acsomega.3c00085
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Associations between underlying diseases with COVID-19 and its symptoms among adults

Binghan Wang / Shuyan Yuan / Shuke Ruan / Xiuyuan Ning / Hanrui Li / Yuanhao Liu / Xiuyang Li

Frontiers in Public Health, Vol

a cross-sectional study

2023 Volume 11

Abstract: BackgroundSpecific underlying diseases were reported to be associated with severe COVID-19 outcomes, but little is known about their combined associations. The study was aimed to assess the relations of number of and specific underlying diseases to COVID- ...

Abstract	BackgroundSpecific underlying diseases were reported to be associated with severe COVID-19 outcomes, but little is known about their combined associations. The study was aimed to assess the relations of number of and specific underlying diseases to COVID-19, severe symptoms, loss of smell, and loss of taste.MethodsA total of 28,204 adult participants in the National Health Interview Survey 2021 were included. Underlying diseases (including cardiovascular diseases, cancer, endocrine diseases, respiratory diseases, neuropsychiatric diseases, liver and kidney diseases, fatigue syndrome, and sensory impairments), the history of COVID-19, and its symptoms were self-reported by structured questionnaires. Multivariable logistic regression models were used to assess the combined relation of total number of underlying diseases to COVID-19 and its symptoms, while mutually adjusted logistic models were used to examine their independent associations.ResultsAmong the 28,204 participants (mean ± standard deviation: 48.2 ± 18.5 years), each additional underlying disease was related to 33, 20, 37, and 39% higher odds of COVID-19 (odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.29–1.37), severe symptoms (OR: 1.20, 95% CI: 1.12–1.29), loss of smell (OR: 1.37, 95% CI: 1.29–1.46), and loss of taste (OR: 1.39, 95% CI: 1.31–1.49). In addition, independent associations of sensory impairments with COVID-19 (OR: 3.73, 95% CI: 3.44–4.05), severe symptoms (OR: 1.37, 95% CI: 1.13–1.67), loss of smell (OR: 8.17, 95% CI: 6.86–9.76), and loss of taste (OR: 6.13, 95% CI: 5.19–7.25), cardiovascular diseases with COVID-19 (OR: 1.13, 95% CI: 1.03–1.24), neuropsychiatric diseases with severe symptoms (OR: 1.41, 95% CI: 1.15–1.74), and endocrine diseases with loss of taste (OR: 1.28, 95% CI: 1.05–1.56) were observed.ConclusionA larger number of underlying diseases were related to higher odds of COVID-19, severe symptoms, loss of smell, and loss of taste in a dose–response manner. Specific underlying diseases might be individually associated ...
Keywords	underlying diseases ; COVID-19 ; severe symptoms ; loss of sensory ; cross-sectional study ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Research on depression in Parkinson disease: A bibliometric and visual analysis of studies published during 2012-2021.

Liu, Yan / Ding, Linlin / Xianyu, Yunyan / Nie, Shuke / Yang, Jiying

Medicine

2022 Volume 101, Issue 31, Page(s) e29931

Abstract: Background: The diagnosis and treatment rate of Parkinson disease (PD) with depression has a low diagnostic rate, and there is no consensus on the choice of treatment mode. This study evaluates the global research trends of scientific outputs related to ...

Abstract	Background: The diagnosis and treatment rate of Parkinson disease (PD) with depression has a low diagnostic rate, and there is no consensus on the choice of treatment mode. This study evaluates the global research trends of scientific outputs related to depression in PD from multiple perspectives, using a bibliometric analysis and visualization tool to scientifically analyze the knowledge from the literature. Methods: Literature related to depression in PD published from 2012 to 2021 was included and selected from the Web of Science Core Collection database in October 2021. CiteSpace software was used to visualize and analyze co-occurrence analyses for countries, institutions, authors, and keywords. Results: A total of 4533 articles from the Web of Science database were included. The United States made the largest contribution with the majority of publications (1215; 29.40%). Toronto University was the most productive institution. PD, depression, quality of life, dementia, nonmotor symptom, prevalence, anxiety, Alzheimer disease, symptom, and disorder would be significantly correlated with depression in PD. The current hot spots in this field focus on the following: risk factors for depression in PD, assessment scale of depression in PD, and rehabilitation of depression in PD. Conclusions: This analysis not only reveals the current research trends and hotspots but also provides some instructive suggestions on the development of depression in PD.
MeSH term(s)	Bibliometrics ; Depression/epidemiology ; Depression/etiology ; Humans ; Parkinson Disease/complications ; Parkinson Disease/epidemiology ; Parkinson Disease/therapy ; Publications ; Quality of Life ; United States
Language	English
Publishing date	2022-08-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	80184-7
ISSN	1536-5964 ; 0025-7974
ISSN (online)	1536-5964
ISSN	0025-7974
DOI	10.1097/MD.0000000000029931
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