| 1. |
- Li, Han, et al.
(author)
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A co-doped oxygen reduction catalyst with FeCu promotes the stability of microbial fuel cells
- 2022
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In: Journal of Colloid and Interface Science. - : ACADEMIC PRESS INC ELSEVIER SCIENCE. - 0021-9797 .- 1095-7103. ; 628, s. 652-662
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Journal article (peer-reviewed)abstract
- Air cathode microbial fuel cell (AC-MFC) cannot be used on a large scale because of its low oxygen reduction reaction (ORR) efficiency. Despite the fact that bimetallic catalysts can greatly enhance the oxygen reduction rate by regulating the electronic structure of the active site, the flaws of insufficient exposure of the active site and easy metal agglomeration limit its catalytic activity. Herein, we report on the preparation of a stable heteroatomic substrate using a copper material organic framework as a precursor, covered by Fe-based active sites. As a result of dipole-dipole interactions, the reduced product Fe2+ forms a weak Fe-O surface that is conducive to the adsorption of active substances. The presence of Fe-0 enhances the electrical conductivity of the catalytic, thus promoting ORR efficiency. Through redox coupling, the D -band center of Fe at FeCu@CN is optimized and brought close to the Fermi level to facilitate electron transfer. Notably, FeCu@CN demonstrates a superior power density of 2796.23 +/- 278.58 mW m(-3), far exceeding that of Pt/C (1363.93 +/- 102.56 mW m(-3)), in the application of microbial fuel cells (MFCs). Meanwhile, the MFC-loaded FeCu@CN maintains excellent stability and outstanding output voltage after 1000 h, which provides feasibility for large-scale application. (C) 2022 Elsevier Inc. All rights reserved.
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| 2. |
- Liu, Fang, et al.
(author)
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Quantitative proteomic analysis of gastric cancer tissue reveals novel proteins in platelet-derived growth factor B signaling pathway
- 2017
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In: Oncotarget. - : IMPACT JOURNALS LLC. - 1949-2553. ; 8:13, s. 22059-22075
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Journal article (peer-reviewed)abstract
- Gastric cancer is one of the most common cancers in Asian countries. Searching for reliable biomarkers involving the development of gastric cancer is important for clinical practice. Quantitative proteomics has become an important method contributed to the discovery of novel diagnostic or therapeutic targets for the management of cancer. Here, we identified differently expressed proteins in gastric cancer and normal gastric tissues by using the high resolution mass spectrometer. Among the total of 2280 identified proteins, 87 were differentially expressed between gastric cancer and normal gastric tissues. Notably, several significant proteins are in the PDGF-B signaling pathway, including peroxiredoxin5 (PRDX5), S100A6, calreticulin (CALR) and cathepsin D (CTSD), which were validated by western blot. Furthermore, upstream regulators including PDGF-B, PDGFR-beta, Akt, eIF4E and p70s6K were found significantly increased in the gastric cancer tissues. In addition, silencing of PRDX5 and PDGF-B suppressed the proliferation of gastric cancer cells in vitro. The administration of exogenous PDGF-BB recovered the reduced expression of PDGF-B signaling pathway in PDGF-B knockdown cells. Taken together, our findings suggested that PDGF-B signaling pathway plays an important role in the regulation of gastric cancer proliferation and the inhibition of this pathway may be a potential approach for treatment of gastric cancer.
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| 3. |
- Xiao, Wenming, et al.
(author)
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Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing
- 2021
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In: Nature Biotechnology. - : Springer Nature. - 1087-0156 .- 1546-1696. ; 39:9, s. 1141-1150
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Journal article (peer-reviewed)abstract
- Recommendations are given on optimal read coverage and selection of calling algorithm to maximize the reproducibility of cancer mutation detection in whole-genome or whole-exome sequencing. Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.
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| 4. |
- Zhang, Haiyang, et al.
(author)
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Evaluation of Generalized Born Models for Large Scale Affinity Prediction of Cyclodextrin Host-Guest Complexes
- 2016
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In: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 56:10, s. 2080-2092
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Journal article (peer-reviewed)abstract
- Binding affinity prediction with implicit solvent models remains a challenge in virtual screening for drug discovery. In order to assess the predictive power of implicit solvent models in docking techniques with Amber scoring, three generalized Born models (GB(HCT), GB(OBC)I, and GB(OBC)II) available in Dock 6.7 were utilized, for determining the binding affinity of a large set of beta-cydodextrin complexes with 75 neutral guest molecules. The results were compared to potential of mean force (PMF) free energy calculations with four GB models (GB(Still), GB(HCT), GB(OBC)I, and GB(OBC)II and to experimental data. Docking results yield similar accuracy to the computationally demanding PMF method with umbrella sampling. Neither docking nor PMF calculations reproduce the experimental binding affinities, however, as indicated by a small Spearman rank order coefficient (similar to 0.5). The binding energies obtained from GB models were decomposed further into individual contributions of the binding partners and solvent environments and compared to explicit solvent simulations for five complexes allowing for rationalizing the difference between explicit and implicit solvent models. An important observation is that the explicit solvent screens the interaction between host and guest much stronger than GB models. In contrast, the screening in GB models is too strong in solutes, leading to overestimation of short-range interactions and too strong binding. It is difficult to envision a way of overcoming these two opposite effects.
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| 5. |
- Zhang, Haiyang, et al.
(author)
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Free-Energy Calculations of Ionic Hydration Consistent with the Experimental Hydration Free Energy of the Proton
- 2017
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In: The Journal of Physical Chemistry Letters. - : AMER CHEMICAL SOC. - 1948-7185. ; 8:12, s. 2705-2712
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Journal article (peer-reviewed)abstract
- Computational free-energy correction strategies and the choice of experimental proton hydration free energy, Delta G(s)*(H+), are analyzed to investigate the apparent controversy in experimental thermodynamics of ionic hydration. Without corrections, the hydration free-energy (Delta G(hyd)) calculations match experiments with Delta G(s)*(H+) = -1064 kJ/mol as reference. Using the Galvani surface potential the resulting (real) Delta G(s)* are consistent with Delta G(s)*(H+) = -1098 kJ/mol. When applying, in an ad hoc manner, the discrete solvent correction, G(hyd) matching the "consensus" Delta G(s)*(H+) of -1112 kJ/mol are obtained. This analysis rationalizes reports on Delta G(hyd) calculations for ions using different experimental references. For neutral amino acid side chains Delta G(hyd) are independent of the water model, whereas there are large differences in Delta G(hyd) due to the water model for charged species, suggesting that long-range ordering of water around ions yields an important contribution to the Delta G(hyd). These differences are reduced significantly when applying consistent corrections, but to obtain the most accurate results it is recommended to use the water model belonging to the force field.
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