ACS Nano
·
2024
·
IF 15.8
Jia-Jia Zheng,Xiaoyu Wang,Zeqi Li,Xiaomei Shen,Gen Wei,Pufeihong Xia,Yi-Ge Zhou,Hui Wei,Xingfa Gao
Nanomedicine is promising for disease prevention and treatment, but there are still many challenges that hinder its rapid development. A major challenge is to efficiently seek candidates with the desired therapeutic functions from tremendously available materials. Here, we report an integrated computational and experimental framework to seek alloy nanoparticles from the Materials Project library for antibacterial applications, aiming to learn the inverse screening concept from traditional medicine for nanomedicine. Because strong peroxidase-like catalytic activity and weak toxicity to normal cells are the desired material properties for antibacterial usage, computational screening implementing theoretical prediction models of catalytic activity and cytotoxicity is first conducted to select the candidates. Then, experimental screening based on scanning probe block copolymer lithography is used to verify and refine the computational screening results. Finally, the best candidate AuCu3 is synthesized in solution and its antibacterial performance over other nanoparticles against S. aureus and E. coli. is experimentally confirmed. The results show the power of inverse screening in accelerating the research and development of antibacterial nanomedicine, which may inspire similar strategies for other nanomedicines in the future.
研究领域:
材料科学
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生物医学工程
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纳米技术
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产品关联
DOI
PubMed
高影响因子
JOURNAL OF PHYSICAL CHEMISTRY B
·
2025
·
IF 2.9
Yang He,Guowei Chen,Yiping Zhao,Li Chen
The hydrophilicity of two-dimensional (2D) transition-metal carbides, carbonitrides, and nitrides (MXene) nanochannels plays a critical role in water transport during filtration, yet its specific effects on MXene membranes remain inadequately understood. Herein, we systematically investigated water transport through Ti3C2TX MXene nanochannels using molecular dynamics simulations coupled with experimental validation, addressing a significant knowledge gap in MXene-based separation membranes. Our simulations demonstrated that strong interactions between water molecules and hydrophilic nanochannel MXene surfaces (Ti3C2(OH)2 MXene or Ti3C2(NH)2 MXene) facilitated the formation of ordered molecular arrangements, substantially improving water permeability. Conversely, hydrophobic nanochannels (Ti3C2O2 MXene or Ti3C2F2 MXene) exhibited disordered water molecule distributions, leading to reduced permeability. Experimental validation corroborated these simulation results, demonstrating a direct correlation between the hydrophilicity of the Ti3C2TX surface and the water flux. The highly hydrophilic Ti3C2(OH)2 MXenes exhibited water flux maximum, whereas the more hydrophobic Ti3C2F2 MXenes had the lowest water flux. By integrating molecular dynamics simulations with experimental analyses, we gained comprehensive insights into the influence of nanochannel hydrophilicity on water transport mechanisms in MXene membranes. These findings provide critical guidelines for designing high-performance MXene-based membranes for advanced water treatment and separation applications.
研究领域:
材料科学
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环境科学
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计算化学
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产品关联
DOI
PubMed
高影响因子
CHEMISTRY OF MATERIALS
·
2024
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IF 7.2
Zhongxiong Sun,Jinjin Yang,Yifeng Han,Man-Rong Li
Harsh synthetic conditions and high cost seriously hinder the discoveries of metastable materials under extreme conditions. Extending the big-data-driven high-throughput calculation (HTC) to depict the chemically negative pressure (NP) zone enables the creation of efficient and accurate prediction models over the full pressure range. This approach significantly expedites the exploration and discovery of novel multifunctional metastable materials. Here, double perovskites Ag2B(IV)B′(VI)O6 were adopted to illustrate the comprehensive process of big-data-mining, HTC, and experimental realization under chemically NP. High-throughput screening of 32 Ag2BB′O6 compounds, encompassing 9 possible crystal structures and 23 derived magnetic structures, resulting in 1024 potential candidates. Ag2MnTeO6 (AMTO) and Ag2TiTeO6 (ATTO) were selected for the experimental validation. We captured a new polymorph of AMTO (R-3, 3R) at ambient pressure through ion-exchange reaction, a phase theoretically predicted to be stable under NP about −6.6 GPa. Moreover, as predicted by density functional theory calculations, the P-31c (2H) AMTO is an antiferromagnetic semiconductor with magnetic transition at 3 K and direct band gap ∼0.97 eV. This work is expected to guide the exploration of hidden metastable phase by providing a methodological framework and novel conceptual approach for future research.
研究领域:
材料科学
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数据科学
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DOI
高影响因子
Heliyon
·
2024
·
IF 3.4
Ao Sun,Yu-fei Li,Yang Miao,Hong-xia Wang,Lin-lin Zhang
The objective of this study was to investigate the potential targets and mechanisms of UA in the treatment of PD. The efficacy of UA in PD was assessed through network pharmacology, molecular docking, and experimental methods. Common target protein-protein interaction (PPI) networks were constructed and visualized using Cytoscape. As a result, 9 key genes, namely CASP3, IL6, IL1B, PTGS2, CREB1, TNF, MAPK3, JUN, and CASP8, were selected. Molecular docking simulations were performed using Discovery Studio 2019 to validate the correlation between UA and the core targets. The results demonstrated a favorable binding affinity between UA and CASP8, IL1B, CASP3, TNF, MAPK3 and IL6. In vivo studies showed UA ameliorated motor dysfunction, and UA can significantly increase the protein expression of tyrosine hydroxylase (TH) in PD mice model. In addition, in vitro experiments confirmed that UA effectively reduced the protein expression of CASP8, CASP3 and MAPK3 in PD cell models and suppressed the gene expression of TNF-α, IL-6, and IL-1β. These findings indicate that the therapeutic effects of UA on PD could be due to its influence on various targets within both the apoptosis and neuroinflammatory signaling pathways. Consequently, this study provides a methodological and theoretical foundation for further elucidating the pharmacological mechanism of UA.
研究领域:
药理学
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神经科学
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生物信息学
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产品关联
DOI
PubMed
高影响因子
CERAMICS INTERNATIONAL
·
2021
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IF 4.527
Zhiqiang Zhou,Xiumin Chen,Zhongqian Zhao,Youli Xu,Bingyang He,Li Liu,Bin Yang,Baoqiang Xu,Dachun Liu
The Ab initio molecular dynamics (AIMD) simulation was adopted to elucidate the alumina vacuum carbothermal reduction and nitridation (VCRN) reaction mechanism, and an experimental method was adopted to verify the AIMD results. According to the results, the VCRN reaction occurs only when N 2 is adsorbed on both the C and Al atoms. C plays two important roles during the reaction of alumina VCRN: one is to act as a charge exchange carrier for N and Al atoms to catalyze N 2 molecule decomposition, and the other is to react with O atoms and reduce Al 2 O 3 .
研究领域:
材料科学
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化学工程
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产品关联
DOI
高影响因子
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
·
2022
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IF 6.772
Yiheng Sun,Guijing Dou,Kang Wu,Peijian Chen,Taihua Zhang,Guangjian Peng
Characterization of the rupture behavior is of great significance to evaluate the service life for microcapsules. Due to the small dimension, complex core-shell structure and curved surface of microcapsules, it is challenging to quantitatively determine the rupture position and rupture strength. In the present work, a microsphere-compression model for characterizing the rupture behavior of microcapsules was established. Through the quantitative investigation of the compression rupture behaviors of microcapsules from the extended finite element models, the cracks were found to initiate at the same parallel circle (latitude) of microcapsule where the curvature change of the deformed shell (i.e., prime vertical strain) is the largest. With the increase of compression displacement, microcapsules show three crack propagation modes. Based on such findings, a maximum prime vertical strain criterion, i.e., cracks initiate when the maximum prime vertical strain exceeds a critical value, for estimating the rupture initiation of microcapsules under compression was proposed. The proposed criterion was validated by both numerical simulations and experiments. It demonstrates that the critical prime vertical strain of rupture is independent of the microcapsule dimensions and is an intrinsic parameter to judge the rupture of microcapsules. The critical prime vertical strain of rupture for n-hexadecane@PMMA microcapsules is 0.023±0.003. The proposed model avoids complicated stress analysis and provides an intrinsic criterion.
研究领域:
材料科学
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力学
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产品关联
DOI
高影响因子
Journal of Materials Informatics
·
2024
·Vol. 4
·期 4
·N
·
IF 0
Hongwei Liu,Zhenming Cui,Zhennan Qiao,Xiaokang An,Yongzhen Wang
Porous carbon materials (PCMs) are preferred as electrode materials for supercapacitor energy storage applications due to their superior characteristics. However, the optimal performance of these electrodes requires trial and error experimental exploration due to the complexity of influencing factors. To address this limitation, we develop a machine learning (ML) combined experimental validation approach to predict, screen and interpret ideal PCMs for supercapacitors. Four ML models are used for predicting the specific capacitance (SC) properties of PCMs and the light gradient boosting machine (LGBM) model exhibits the best prediction performance with an R2 value of 0.92. Through comprehensive interpretability analysis of ML, important variables influencing SC properties are identified and their impact range is determined. By analyzing the deviation of key values during experimental verification, accurate predictions of SC properties of PCMs are made, facilitating precise material screening. Additionally, the accuracy and applicability of the ML model predictions are evaluated. This research pioneered a key eigenvalue fall-point screening approach based on a combination of ML experiments for accurately predicting SC performance and screening of superior energy storage materials, providing a compelling strategy for advancing energy storage materials technology.
研究领域:
材料科学
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能源存储
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人工智能应用
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DOI
BIOMEDICAL CHROMATOGRAPHY
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2024
·Vol. 38
·期 7
·e5887
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IF 1.8
Shuai-nan Zhang,Qi Liu,Xu-zhao Li
Omics, bioinformatics, molecular docking, and experimental validation were used to elucidate the hepatoprotective effects, mechanisms, and active compounds of Shandougen (SDG) based on the biolabel-led research pattern. Integrated omics were used to explore the biolabels of SDG intervention in liver tissue. Subsequently, bioinformatics and molecular docking were applied to topologically analyze its therapeutic effects, mechanisms, and active compounds based on biolabels. Finally, an animal model was used to verify the biolabel analysis results. Omics, bioinformatics, and molecular docking revealed that SDG may exert therapeutic effects on liver diseases in the multicompound and multitarget synergistic modes, especially liver cirrhosis. In the validation experiment, SDG and its active compounds (betulinic acid and gallic acid) significantly improved the liver histopathological damage in the CCl 4 -induced liver cirrhosis model. Meanwhile, they also produced significant inhibitory effects on the focal adhesion pathway (integrin alpha-1, myosin regulatory light chain 2, laminin subunit gamma-1, etc.) and alleviated the associated pathological processes: focal adhesion (focal adhesion kinase 1)–extracellular matrix (collagen alpha-1(IV) chain, collagen alpha-1(VI) chain, and collagen alpha-2(VI) chain) dysfunction, carcinogenesis (alpha-fetoprotein, NH 3 , and acetylcholinesterase), inflammation (tumor necrosis factor alpha, interleukin-1 [IL-1], IL-6, and IL-10), and oxidative stress (reactive oxygen species, malonaldehyde, and superoxide dismutase). This study provides new evidence and insights for the hepatoprotective effects, mechanisms, and active compounds of SDG.
研究领域:
中药学
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生物信息学
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肝脏病学
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产品关联
DOI
PubMed
高影响因子
COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING
·
2024
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IF 1.6
Jianghong Wang,Xiaoyuan Wang,Yanru Song,Zilin Huang,Han Wu,Liang Chang,Bingjie Huo,Guanwei Fan
Background: The Precancerous Lesion of Gastric Cancer (PLGC) is an early stage in the development of gastric cancer. The clinical application of HPXLD has been found to be effective in treating PLGC, but the mechanism of how HPXLD acts on PLGC is still unclear. Objective: The objectives of this study were to reveal the molecular mechanism of how HPXLD can be used to treat PLGC and investigate this mechanism through bioinformatics and experimental validation. Methods: PLGC-associated target genes were identified through bioinformatics analysis. A rat model of PLGC was induced using N-methyl-N'-nitro-N-nitrosoquanidine (MNNG) in combination with ranitidine, hot saline, ethanol, and intermittent fasting, with interventions by HPXLD. The pathological alterations in gastric mucosa were assessed through Hematoxylin-eosin staining (HE). Immunohistochemistry (IHC) and Western blot analyses were employed to evaluate the changes in expression levels of inflammation-related proteins. Results: After conducting bioinformatics analysis, it was found that there were 23 HPXLDPLGC crossover genes, which were significantly enriched in the IL-17 signaling pathway, TNF signaling pathway, and NF-kappa B signaling pathway. The results of HE showed that HPXLD was effective in improving gastric mucosal histopathological changes. Additionally, the IHC results demonstrated that HPXLD was able to downregulate the expression of IL-6, COX-2, MCP- 1, and MMP-9. Furthermore, Western blot analysis revealed that HPXLD was able to downregulate the expressions of IL-6, IL-17RA, ACT1, NF-κB, and TNF-α. Conclusion: HPXLD has been shown to improve PLGC by reducing the expression of inflammation- related proteins. This suggests that HPXLD may potentially be a treatment option for PLGC.
研究领域:
肿瘤学
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中医药学
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分子生物学
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DOI
PubMed
高影响因子
RSC Advances
·
2015
·Vol. 5
·期 108
·89015-89024
·
IF 3.84
Yanqiu Pan,Wenjuan Wang,Wei Wang,Tonghua Wang
Theoretical and experimental investigations were conducted to predict particle deposition and layer growth during formation of a dynamic membrane using cross-flow microfiltration. A critical particle size model was developed and solved in radial, circumferential and axial directions by analyzing the forces acting on a single particle. The model accounted for the normal drag, lateral lift, shear-induced and Brownian diffusion forces in the depositional direction, the van der Waals force in the circumferential direction, and the cross-flow drag and van der Waals forces in the axial direction. Cross-flow velocity and feed temperature were selected as representative influencing factors to examine variations of the critical particle sizes with permeate flux. Experiments were then conducted with carbon tubes as the support and zirconium dioxide particles as the coating material to verify the model. Results showed that a dynamic layer with non-uniform thickness along the circumferential direction was formed within the horizontal tube due to gravity. The layer thickness decreased as the cross-flow velocities were increased under a given trans-membrane pressure difference and feed concentration. An appropriately large cross-flow velocity was beneficial to achieve thickness uniformity during formation. The effect of the feed temperature on the critical particle size and layer thickness can be ignored. Comparisons between the theoretical predictions and experimental data of the layer thicknesses displayed good agreements. The effects of trans-membrane pressure differences and feed concentrations were finally examined in the present work.
研究领域:
环境工程
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化学工程
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产品关联
DOI
高影响因子
JOURNAL OF MOLECULAR MODELING
·
2024
·Vol. 30
·期 8
·1-9
·
IF 2.1
Wang Shuya,Liu Yifan,Wang Jianhua,Chen Jinjian,Liu Yucun
Context Ammonium perchlorate (NH 4 ClO 4 , abbreviated as AP) has the advantages of high oxygen content, high density, and good compatibility, and has significant application prospects in the field of energetic materials. The crystal morphology has a great influence on the properties and sensibility of energetic materials, and a single experimental means is difficult in exploring the crystals; therefore, the crystal morphology of AP is investigated using molecular dynamics simulation complemented with experiments, to theoretically analyze the differences in AP crystal habit and the interactions between solvent molecules and the main growing crystal surfaces of AP. The results show that AP crystal is mainly composed of five independent crystal surfaces (0 0 1), (0 1 0), (1 0 0), (1 0 1), and (1 0 −1) in vacuum using the BFDH laws, with (0 0 1) surface being the main growth crystal surface. In contrast, in H 2 O solvent, the (1 0 1) and (1 0 −1) surfaces disappear, and the AP mainly consists of (0 0 1), (0 1 0), and (1 0 0) surfaces with a rectangular shape. The crystal morphology obtained from theoretical prediction is in good agreement with that obtained from experimental culture. This paper can provide a new idea for the cultivation and preparation of AP large crystals, and promote the application of AP crystals in energetic materials. Methods The crystal morphologies of AP in vacuum and H 2 O solvent under Dreiding force field were predicted based on attachment energy model by using molecular dynamics method in Materials Studio 2019 software. The entire molecular dynamics simulation was carried out under the NTV system, the temperature control method was selected as Anderson, and the system temperature was set to 298 K. The simulation time was set to 40 ps, the step size was set to 1 fs, and the data were outputted every 5000 steps.
研究领域:
材料科学
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化学
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产品关联
DOI
PubMed
高影响因子
AICHE JOURNAL
·
2024
·
IF 3.5
Xiaomin Liu,Jiahui Chen,Yuxin Qiu,Kunchi Xie,Jie Cheng,Xinze You,Guzhong Chen,Zhen Song,Zhiwen Qi
Although eutectic solvents (ESs) have garnered significant attention as promising solvents for carbon dioxide (CO 2 ) capture, systematic studies on discovering novel ESs linking machine learning (ML) and experimental validation are scarce. For the reliable prediction of CO 2 -in-ES solubility, ensemble ML modeling based on random forest and extreme gradient boosting with inputs of COSMO-RS derived molecular descriptors is rigorously performed, for which an extensive experimental CO 2 -in-ES solubility database of 2438 data points in 162 ESs involving 106 ES systems are collected. With the best-performing model obtained, the CO 2 solubilities of 4735 novel combinations of ES components are first predicted for estimating their potential in CO 2 capture. The top-ranked candidate combinations are subsequently evaluated by examining the environmental health and safety properties of individual components and assessing the potential operating window based on solid–liquid equilibrium (SLE) prediction. Three most promising ES systems are finally retained, which are thoroughly studied by SLE and CO 2 absorption experiments.
研究领域:
化学工程
·
环境科学
·
数据科学
✓ 已验证
产品关联
DOI
高影响因子
危险品化学品经营许可证（带存储）