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Article ; Online: Study on boron removal performance of covalent organic skeleton membrane by hydroxyl groups

Xing Yan / Lyu Qiang / Hu Songqing / Sun Shuangqing

E3S Web of Conferences, Vol 393, p

2023 Volume 03038

Abstract: Growing demand for water desalination promoted the vigorous development of reverse osmosis (RO) membrane. How to effectively remove boron from seawater is the key problem to be solved by RO membrane. It is important to select suitable membrane materials ... ...

Abstract	Growing demand for water desalination promoted the vigorous development of reverse osmosis (RO) membrane. How to effectively remove boron from seawater is the key problem to be solved by RO membrane. It is important to select suitable membrane materials for experimental design before complicated and expensive experimental attempts. In this paper, we demonstrate that pore chemistry plays a key role in boron removal capability of RO membranes via nonequilibrium molecular dynamics simulations. This study shows that the introduction of hydroxyl (-OH) groups into the Covalent organic frameworks (COFs) pore allows for better boron removal without changing water permeability. The optimal boron rejection of AB-COF membranes is 76.67%, and that of ATFG-COF membranes with hydroxyl groups can achieve 90%. This is caused by the hydrophilic pore of ATFG-COF that will preferentially adsorb water molecules to prevent the passage of boric acid molecules through membrane zone. Additionally, -OH groups on the pore will also adsorb a part of boric acid in the membranes, reducing the amount of boric acid entering into the permeate side. The results obtained in this paper can provide guidance for the rational design of RO membranes to achieve more efficient boron removal.
Keywords	Environmental sciences ; GE1-350
Subject code	612
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	EDP Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Review on Thermal Properties of Hydrogels for Electronic Devices Applications.

Xin, Fei / Lyu, Qiang

Gels (Basel, Switzerland)

2022 Volume 9, Issue 1

Abstract: Hydrogels, as a series of three-dimensional, crosslinked, hydrophilic network polymers, exhibit extraordinary properties in softness, mechanical robustness and biocompatibility, which have been extensively utilized in various fields, especially for ... ...

Abstract	Hydrogels, as a series of three-dimensional, crosslinked, hydrophilic network polymers, exhibit extraordinary properties in softness, mechanical robustness and biocompatibility, which have been extensively utilized in various fields, especially for electronic devices. However, since hydrogels contain plenty of water, the mechanical and electrochemical properties are susceptible to temperature. The thermal characteristics of hydrogels can significantly affect the performance of flexible electronic devices. In this review, recent research on the thermal characteristics of hydrogels and their applications in electronic devices is summarized. The focus of future work is also proposed. The thermal stability, thermoresponsiveness and thermal conductivity of hydrogels are discussed in detail. Anti-freezing and anti-drying properties are the critical points for the thermal stability of hydrogels. Methods such as introducing soluble ions and organic solvents into hydrogels, forming ionogels, modifying polymer chains and incorporating nanomaterials can improve the thermal stability of hydrogels under extreme environments. In addition, the critical solution temperature is crucial for thermoresponsive hydrogels. The thermoresponsive capacity of hydrogels is usually affected by the composition, concentration, crosslinking degree and hydrophilic/hydrophobic characteristics of copolymers. In addition, the thermal conductivity of hydrogels plays a vital role in the electronics applications. Adding nanocomposites into hydrogels is an effective way to enhance the thermal conductivity of hydrogels.
Language	English
Publishing date	2022-12-23
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2813982-3
ISSN	2310-2861 ; 2310-2861
ISSN (online)	2310-2861
ISSN	2310-2861
DOI	10.3390/gels9010007
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Book ; Online: Compositional Prototypical Networks for Few-Shot Classification

Lyu, Qiang / Wang, Weiqiang

2023

Abstract: It is assumed that pre-training provides the feature extractor with strong class transferability and that high novel class generalization can be achieved by simply reusing the transferable feature extractor. In this work, our motivation is to explicitly ... ...

Abstract	It is assumed that pre-training provides the feature extractor with strong class transferability and that high novel class generalization can be achieved by simply reusing the transferable feature extractor. In this work, our motivation is to explicitly learn some fine-grained and transferable meta-knowledge so that feature reusability can be further improved. Concretely, inspired by the fact that humans can use learned concepts or components to help them recognize novel classes, we propose Compositional Prototypical Networks (CPN) to learn a transferable prototype for each human-annotated attribute, which we call a component prototype. We empirically demonstrate that the learned component prototypes have good class transferability and can be reused to construct compositional prototypes for novel classes. Then a learnable weight generator is utilized to adaptively fuse the compositional and visual prototypes. Extensive experiments demonstrate that our method can achieve state-of-the-art results on different datasets and settings. The performance gains are especially remarkable in the 5-way 1-shot setting. The code is available at https://github.com/fikry102/CPN. Comment: Accepted by AAAI 2023
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	004
Publishing date	2023-06-11
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Intermittent short-duration reoxygenation relieves high-altitude pulmonary hypertension via NOX4/H2O2/PPAR-γ axis.

Li, Shaohua / Lyu, Qiang / Shi, Qixin / Bai, Yungang / Ren, Xinling / Ma, Jin

Clinical science (London, England : 1979)

2024 Volume 138, Issue 3, Page(s) 103–115

Abstract: High-altitude pulmonary hypertension (HAPH) is a severe and progressive disease that can lead to right heart failure. Intermittent short-duration reoxygenation at high altitude is effective in alleviating HAPH; however, the underlying mechanisms are ... ...

Abstract	High-altitude pulmonary hypertension (HAPH) is a severe and progressive disease that can lead to right heart failure. Intermittent short-duration reoxygenation at high altitude is effective in alleviating HAPH; however, the underlying mechanisms are unclear. In the present study, a simulated 5,000-m hypoxia rat model and hypoxic cultured pulmonary artery smooth muscle cells (PASMCs) were used to evaluate the effect and mechanisms of intermittent short-duration reoxygenation. The results showed that intermittent 3-h/per day reoxygenation (I3) effectively attenuated chronic hypoxia-induced pulmonary hypertension and reduced the content of H2O2 and the expression of NADPH oxidase 4 (NOX4) in lung tissues. In combination with I3, while the NOX inhibitor apocynin did not further alleviate HAPH, the mitochondrial antioxidant MitoQ did. Furthermore, in PASMCs, I3 attenuated hypoxia-induced PASMCs proliferation and reversed the activated HIF-1α/NOX4/PPAR-γ axis under hypoxia. Targeting this axis offset the protective effect of I3 on hypoxia-induced PASMCs proliferation. The present study is novel in revealing a new mechanism for preventing HAPH and provides insights into the optimization of intermittent short-duration reoxygenation.
MeSH term(s)	Animals ; Rats ; Altitude ; Altitude Sickness ; Cell Proliferation ; Cells, Cultured ; Hydrogen Peroxide/metabolism ; Hypertension, Pulmonary/etiology ; Hypertension, Pulmonary/prevention & control ; Hypertension, Pulmonary/metabolism ; Hypoxia/metabolism ; Myocytes, Smooth Muscle/metabolism ; NADPH Oxidase 4/genetics ; NADPH Oxidase 4/metabolism ; PPAR gamma/metabolism ; Pulmonary Artery/metabolism ; Signal Transduction
Chemical Substances	Hydrogen Peroxide (BBX060AN9V) ; NADPH Oxidase 4 (EC 1.6.3.-) ; PPAR gamma ; Nox4 protein, rat (EC 1.6.3.-)
Language	English
Publishing date	2024-01-19
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	206835-7
ISSN	1470-8736 ; 0301-0538 ; 0009-0360 ; 0143-5221
ISSN (online)	1470-8736
ISSN	0301-0538 ; 0009-0360 ; 0143-5221
DOI	10.1042/CS20231508
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Article ; Online: How Deepbics Quantifies Intensities of Transcription Factor-DNA Binding and Facilitates Prediction of Single Nucleotide Variant Pathogenicity With a Deep Learning Model Trained On ChIP-Seq Data Sets.

Quan, Lijun / Chu, Xiaomin / Sun, Xiaoyu / Wu, Tingfang / Lyu, Qiang

IEEE/ACM transactions on computational biology and bioinformatics

2023 Volume 20, Issue 2, Page(s) 1594–1599

Abstract: The binding of DNA sequences to cell type-specific transcription factors is essential for regulating gene expression in all organisms. Many variants occurring in these binding regions play crucial roles in human disease by disrupting the cis-regulation ... ...

Abstract	The binding of DNA sequences to cell type-specific transcription factors is essential for regulating gene expression in all organisms. Many variants occurring in these binding regions play crucial roles in human disease by disrupting the cis-regulation of gene expression. We first implemented a sequence-based deep learning model called deepBICS to quantify the intensity of transcription factors-DNA binding. The experimental results not only showed the superiority of deepBICS on ChIP-seq data sets but also suggested deepBICS as a language model could help the classification of disease-related and neutral variants. We then built a language model-based method called deepBICS4SNV to predict the pathogenicity of single nucleotide variants. The good performance of deepBICS4SNV on 2 tests related to Mendelian disorders and viral diseases shows the sequence contextual information derived from language models can improve prediction accuracy and generalization capability.
MeSH term(s)	Humans ; Chromatin Immunoprecipitation Sequencing ; Deep Learning ; Virulence ; Binding Sites/genetics ; DNA/genetics ; Transcription Factors/genetics ; Transcription Factors/metabolism ; Nucleotides
Chemical Substances	DNA (9007-49-2) ; Transcription Factors ; Nucleotides
Language	English
Publishing date	2023-04-03
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1557-9964
ISSN (online)	1557-9964
DOI	10.1109/TCBB.2022.3170343
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Article: Visualization and Heat Transfer Performance of Mini-Grooved Flat Heat Pipe Filled with Different Working Fluids.

Xin, Fei / Lyu, Qiang / Tian, Wenchao

Micromachines

2022 Volume 13, Issue 8

Abstract: Mini-grooved flat heat pipe (MGFHP) possesses the advantages of high compactness, no mechanical component, super thermal conductivity, and excellent temperature uniformity, which can meet the demand for electronic devices efficiently cooling. In this ... ...

Abstract	Mini-grooved flat heat pipe (MGFHP) possesses the advantages of high compactness, no mechanical component, super thermal conductivity, and excellent temperature uniformity, which can meet the demand for electronic devices efficiently cooling. In this research, visual and heat transfer experiments were performed to investigate the flow and thermal characteristics inside the MGFHP. Fluid flow and distribution are observed to be quite different in the MGFHP containing different working fluids, which is affected by the physical properties of working fluid, the surface state of the grooved wick, and limited working space. Additionally, the input heat, working fluid type, filling ratio, and wettability obviously affect the thermal conductivity and temperature uniformity of the MGFHP. The deionized water-filled MGFHP possesses lower thermal resistance and higher heat transfer capacity than anhydrous ethanol or hexane filled MGFHP, especially for the copper oxide MGFHP filled with deionized water with a filling ratio of 1.0. Thermal resistance, maximum temperature, and temperature nonuniformity at the condensation section of deionized water-filled copper oxide MGFHP are lower than those of the original copper MGFHP by 31.1%, 3.7 °C, and 0.11 °C for the anhydrous ethanol filled MGFHP and 34.4%, 3.1 °C, and 0.13 °C for the hexane filled MGFHP, respectively.
Language	English
Publishing date	2022-08-18
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2620864-7
ISSN	2072-666X
ISSN	2072-666X
DOI	10.3390/mi13081341
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Article ; Online: MCnebula: Critical Chemical Classes for the Classification and Boost Identification by Visualization for Untargeted LC–MS/MS Data Analysis

Huang, Lichuang / Shan, Qiyuan / Lyu, Qiang / Zhang, Shuosheng / Wang, Lu / Cao, Gang

Analytical Chemistry. 2023 June 14, v. 95, no. 26 p.9940-9948

2023

Abstract: Untargeted mass spectrometry is a robust tool for biology, but it usually requires a large amount of time on data analysis, especially for system biology. A framework called Multiple-Chemical nebula (MCnebula) was developed herein to facilitate the LC–MS ...

Abstract	Untargeted mass spectrometry is a robust tool for biology, but it usually requires a large amount of time on data analysis, especially for system biology. A framework called Multiple-Chemical nebula (MCnebula) was developed herein to facilitate the LC–MS data analysis process by focusing on critical chemical classes and visualization in multiple dimensions. This framework consists of three vital steps as follows: (1) abundance-based classes (ABC) selection algorithm, (2) critical chemical classes to classify “features” (corresponding to compounds), and (3) visualization as multiple Child-Nebulae (network graph) with annotation, chemical classification, and structure. Notably, MCnebula can be used to explore the classification and structural characteristic of unknown compounds beyond the limit of the spectral library. Moreover, it is intuitive and convenient for pathway analysis and biomarker discovery because of its function of ABC selection and visualization. MCnebula was implemented in the R language. A series of tools in R packages were provided to facilitate downstream analysis in an MCnebula-featured way, including feature selection, homology tracing of top features, pathway enrichment analysis, heat map clustering analysis, spectral visualization analysis, chemical information query, and output analysis reports. The broad utility of MCnebula was illustrated by a human-derived serum data set for metabolomics analysis. The results indicated that “Acyl carnitines” were screened out by tracing structural classes of biomarkers, which was consistent with the reference. A plant-derived data set was investigated to achieve a rapid annotation and discovery of compounds in E. ulmoides.
Keywords	algorithms ; analytical chemistry ; biomarkers ; blood serum ; data collection ; heat ; mass spectrometry ; metabolomics
Language	English
Dates of publication	2023-0614
Size	p. 9940-9948.
Publishing place	American Chemical Society
Document type	Article ; Online
ZDB-ID	1508-8
ISSN	1520-6882 ; 0003-2700
ISSN (online)	1520-6882
ISSN	0003-2700
DOI	10.1021/acs.analchem.3c01072
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Enhanced water treatment performance of ceramic-based forward osmosis membranes via MOF interlayer.

Sun, Kuo / Lyu, Qiang / Zheng, Xiangyong / Liu, Renlan / Tang, Chuyang Y / Zhao, Min / Dong, Yingchao

Water research

2024 Volume 254, Page(s) 121395

Abstract: Forward osmosis (FO) membrane processes could operate without hydraulic pressures, enabling the efficient treatment of wastewaters with mitigated membrane fouling and enhanced efficiency. Designing a high-performance polyamide (PA) layer on ceramic ... ...

Abstract	Forward osmosis (FO) membrane processes could operate without hydraulic pressures, enabling the efficient treatment of wastewaters with mitigated membrane fouling and enhanced efficiency. Designing a high-performance polyamide (PA) layer on ceramic substrates remains a challenge for FO desalination applications. Herein, we report the enhanced water treatment performance of thin-film nanocomposite ceramic-based FO membranes via an in situ grown Zr-MOF (UiO-66-NH
MeSH term(s)	Membranes, Artificial ; Osmosis ; Wastewater ; Sodium Chloride ; Water Purification ; Ceramics ; Nylons
Chemical Substances	Membranes, Artificial ; Wastewater ; Sodium Chloride (451W47IQ8X) ; Nylons
Language	English
Publishing date	2024-02-28
Publishing country	England
Document type	Journal Article
ZDB-ID	202613-2
ISSN	1879-2448 ; 0043-1354
ISSN (online)	1879-2448
ISSN	0043-1354
DOI	10.1016/j.watres.2024.121395
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Article ; Online: RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding.

Wang, Xuejiao / Wu, Tingfang / Jiang, Yelu / Chen, Taoning / Pan, Deng / Jin, Zhi / Xie, Jingxin / Quan, Lijun / Lyu, Qiang

Bioinformatics (Oxford, England)

2024 Volume 40, Issue 1

Abstract: Motivation: Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the development ... ...

Abstract	Motivation: Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the development of cancer therapeutic vaccines. While recent deep learning-based methods have achieved significant performance in predicting MHC-peptide binding affinity, most of them separately encode MHC molecules and peptides as inputs, potentially overlooking critical interaction information between the two. Results: In this work, we propose RPEMHC, a new deep learning approach based on residue-residue pair encoding to predict the binding affinity between peptides and MHC, which encode an MHC molecule and a peptide as a residue-residue pair map. We evaluate the performance of RPEMHC on various MHC-II-related datasets for MHC-peptide binding prediction, demonstrating that RPEMHC achieves better or comparable performance against other state-of-the-art baselines. Moreover, we further construct experiments on MHC-I-related datasets, and experimental results demonstrate that our method can work on both two MHC classes. These extensive validations have manifested that RPEMHC is an effective tool for studying MHC-peptide interactions and can potentially facilitate the vaccine development. Availability: The source code of the method along with trained models is freely available at https://github.com/lennylv/RPEMHC.
MeSH term(s)	Deep Learning ; Protein Binding ; Peptides/chemistry ; Major Histocompatibility Complex ; Histocompatibility Antigens Class I/metabolism
Chemical Substances	Peptides ; Histocompatibility Antigens Class I
Language	English
Publishing date	2024-01-04
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btad785
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Article ; Online: Proteomic analysis of multiple organ dysfunction induced by rhabdomyolysis.

Zhang, Yan / Lyu, Qiang / Han, Xiao / Wang, Xu / Liu, Ran / Hao, Jing / Zhang, Li / Chen, Xiang-Mei

Journal of proteomics

2024 Volume 298, Page(s) 105138

Abstract: Rhabdomyolysis (RM) leads to dysfunction in the core organs of kidney, lung and heart, which is an important reason for the high mortality and disability rate of this disease. However, there is a lack of systematic research on the characteristics of ... ...

Abstract	Rhabdomyolysis (RM) leads to dysfunction in the core organs of kidney, lung and heart, which is an important reason for the high mortality and disability rate of this disease. However, there is a lack of systematic research on the characteristics of rhabdomyolysis-induced injury in various organs and the underlying pathogenetic mechanisms, and especially the interaction between organs. We established a rhabdomyolysis model, observed the structural and functional changes in kidney, heart, and lung. It is observed that rhabdomyolysis results in significant damage in kidney, lung and heart of rats, among which the pathological damage of kidney and lung was significant, and of heart was relatively light. Meanwhile, we analyzed the differentially expressed proteins (DEPs) in the kidney, heart and lung between the RM group and the sham group based on liquid chromatography-tandem mass spectrometry (LC-MS/MS). In our study, Serpina3n was significantly up-regulated in the kidney, heart and lung. Serpina3n is a secreted protein and specifically inhibits a variety of proteases and participates in multiple physiological processes such as complement activation, inflammatory responses, apoptosis pathways, and extracellular matrix metabolism. It is inferred that Serpina3n may play an important role in multiple organ damage caused by rhabdomyolysis and could be used as a potential biomarker. This study comprehensively describes the functional and structural changes of kidney, heart and lung in rats after rhabdomyolysis, analyzes the DEPs of kidney, heart and lung, and determines the key role of Serpina3n in multiple organ injury caused by rhabdomyolysis. SIGNIFICANCE: This study comprehensively describes the functional and structural changes of kidney, heart and lung in rats after rhabdomyolysis, analyzes the DEPs of kidney, heart and lung, and determines the key role of Serpina3n in multiple organ injury caused by rhabdomyolysis.
MeSH term(s)	Rats ; Animals ; Acute Kidney Injury/metabolism ; Proteomics/methods ; Chromatography, Liquid ; Multiple Organ Failure/complications ; Tandem Mass Spectrometry ; Rhabdomyolysis/complications ; Rhabdomyolysis/chemically induced ; Rhabdomyolysis/metabolism
Language	English
Publishing date	2024-02-24
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2400835-7
ISSN	1876-7737 ; 1874-3919
ISSN (online)	1876-7737
ISSN	1874-3919
DOI	10.1016/j.jprot.2024.105138
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