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合成生物学 5

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合成橡胶 2

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开放的复杂巨系统 2

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2016年熊本地震 1

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High-entropy catalysts for electrochemical water-electrolysis of hydrogen evolution and oxygen evolution reactions

《能源前沿（英文）》 2024年第18卷第3期页码 265-290 doi: 10.1007/s11708-023-0892-6

摘要： High entropy materials (HEMs) have developed rapidly in the field of electrocatalytic water-electrolysis for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) due to their unique properties. In particular, HEM catalysts are composed of many elements. Therefore, they have rich active sites and enhanced entropy stability relative to single atoms. In this paper, the preparation strategies and applications of HEM catalysts in electrochemical water-electrolysis are reviewed to explore the stabilization of HEMs and their catalytic mechanisms as well as their application in support green hydrogen production. First, the concept and four characteristics of HEMs are introduced based on entropy and composition. Then, synthetic strategies of HEM catalysts are systematically reviewed in terms of the categories of bottom-up and top-down. The application of HEMs as catalysts for electrochemical water-electrolysis in recent years is emphatically discussed, and the mechanisms of improving the performance of electrocatalysis is expounded by combining theoretical calculation technology and ex-situ/in situ characterization experiments. Finally, the application prospect of HEMs is proposed to conquer the challenges in HEM catalyst fabrications and applications.

关键词： high-entropy electrocatalysis synthetic methods water-electrolysis hydrogen and oxygen evolutions

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Genome reprogramming for synthetic biology

Kylie Standage-Beier,Xiao Wang

《化学科学与工程前沿（英文）》 2017年第11卷第1期页码 37-45 doi: 10.1007/s11705-017-1618-2

摘要： The ability to go from a digitized DNA sequence to a predictable biological function is central to synthetic biology. Genome engineering tools facilitate rewriting and implementation of engineered DNA sequences. Recent development of new programmable tools to reengineer genomes has spurred myriad advances in synthetic biology. Tools such as clustered regularly interspace short palindromic repeats enable RNA-guided rational redesign of organisms and implementation of synthetic gene systems. New directed evolution methods generate organisms with radically restructured genomes. These restructured organisms have useful new phenotypes for biotechnology, such as bacteriophage resistance and increased genetic stability. Advanced DNA synthesis and assembly methods have also enabled the construction of fully synthetic organisms, such as J. Craig Venter Institute (JCVI)-syn 3.0. Here we summarize the recent advances in programmable genome engineering tools.

关键词： CRISPR genome engineering synthetic biology rational design

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Renewable synthetic fuel: turning carbon dioxide back into fuel

《能源前沿（英文）》 2022年第16卷第2期页码 145-149 doi: 10.1007/s11708-022-0828-6

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Fire resistance evaluation through synthetic fire tests and generative adversarial networks

《结构与土木工程前沿（英文）》 2024年第18卷第4期页码 587-614 doi: 10.1007/s11709-024-1052-8

摘要： This paper introduces a machine learning approach to address the challenge of limited data resulting from costly and time-consuming fire experiments by enlarging small fire test data sets and predicting the fire resistance of reinforced concrete columns. Our approach begins by creating deep learning models, namely generative adversarial networks and variational autoencoders, to learn the spatial distribution of real fire tests. We then use these models to generate synthetic tabular samples that closely resemble realistic fire resistance values for reinforced concrete columns. The generated data are employed to train state-of-the-art machine learning techniques, including Extreme Gradient Boost, Light Gradient Boosting Machine, Categorical Boosting Algorithm, Support Vector Regression, Random Forest, Decision Tree, Multiple Linear Regression, Polynomial Regression, Support Vector Machine, Kernel Support Vector Machine, Naive Bayes, and K-Nearest Neighbors, which can predict the fire resistance of the columns through regression and classification. Machine learning analyses achieved highly accurate predictions of fire resistance values, outperforming traditional models that relied solely on limited experimental data. Our study highlights the potential for using machine learning and deep learning analyses to revolutionize the field of structural engineering by improving the accuracy and efficiency of fire resistance evaluations while reducing the reliance on costly and time-consuming experiments.

关键词： deep learning fire resistance generative adversarial networks machine learning

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Inter-chromosomal insertions into wild-type chromosomes induced by SCRaMbLE

《化学科学与工程前沿（英文）》 doi: 10.1007/s11705-024-2458-5

摘要： Genomic rearrangements play a crucial role in shaping biological phenotypic diversity and driving species evolution. Synthetic chromosome rearrangement and modification by LoxP-mediated evolution (SCRaMbLE) has been applied to explore large-scale genomic rearrangements, yet it has been observed that these rearrangements occur exclusively in genomic regions containing loxPsym sites. Here, we found that SCRaMbLE of synthetic yeast harboring synthetic chromosome V and X can generate a variety of synthetic segment insertions into wild-type chromosomes, ranging from 1 to 300 kb. Furthermore, it was revealed that the novel insertions impacted the transcriptional level of neighboring regions and affected the production of exemplar pathway of zeaxanthin. Collectively, our results improve the understanding of the ability of SCRaMbLE to generate complex structural variations in nonsynthetic regions and provide a potential model to explore genomic transposable events.

关键词： genomic rearrangements synthetic yeast genome SCRaMbLE inter-chromosomal insertions synthetic biology

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Targeting “undruggable” c-Myc protein by synthetic lethality

Chen Wang, Hui Fang, Jiawei Zhang, Ying Gu

《医学前沿（英文）》 2021年第15卷第4期页码 541-550 doi: 10.1007/s11684-020-0780-y

摘要： Synthetic lethal screening, which exploits the combination of mutations that result in cell death, is a promising method for identifying novel drug targets. This method provides a new avenue for targeting “undruggable” proteins, such as c-Myc. Here, we revisit current methods used to target c-Myc and discuss the important functional nodes related to c-Myc in non-oncogene addicted network, whose inhibition may cause a catastrophe for tumor cell destiny but not for normal cells. We further discuss strategies to identify these functional nodes in the context of synthetic lethality. We review the progress and shortcomings of this research field and look forward to opportunities offered by synthetic lethal screening to treat tumors potently.

关键词： synthetic lethality undruggable transcription factor c-Myc

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SCRaMbLE drive application of synthetic yeast genome

Jin Jin, Yuan Ma, Duo Liu

《化学科学与工程前沿（英文）》 2018年第12卷第4期页码 832-834 doi: 10.1007/s11705-018-1749-0

摘要：

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Water-soluble BODIPY and aza-BODIPY dyes: synthetic progress and applications

Gang FAN,Le YANG,Zhijian CHEN

《化学科学与工程前沿（英文）》 2014年第8卷第4期页码 405-417 doi: 10.1007/s11705-014-1445-7

摘要： In recent years, boron-dipyrromethene (BODIPY) and boron-azadipyrromethene (aza-BODIPY) dyes have attracted considerable multidisciplinary attention due to their diverse applications. By introducing various hydrophilic groups, such as quaternary ammonium, sulfonate or oligo-ethyleneglycol moieties into the BODIPY core, the solubilities of these dyes in aqueous solution can be greatly improved while maintaining their high fluorescence quantum yields. Accordingly, applying these fluorescent dyes in aqueous systems to areas such as chemosensors, biomacromolecule labeling, bio-imaging and photodynamic therapy has been achieved. In this article, the recent progress on the synthesis, optical properties and application of water-soluble BODIPY dyes and aza-BODIPY dyes is reviewed.

关键词： boron-dipyrromethene boron-azadipyrromethene synthetic progress applications

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Epigenetic silencing of BEND4, a novel DNA damage repair gene, is a synthetic lethal marker for ATM inhibitor

《医学前沿（英文）》 doi: 10.1007/s11684-023-1053-3

摘要： Synthetic lethality is a novel model for cancer therapy. To understand the function and mechanism of BEN domain-containing protein 4 (BEND4) in pancreatic cancer, eight cell lines and a total of 492 cases of pancreatic neoplasia samples were included in this study. Methylation-specific polymerase chain reaction, CRISPR/Cas9, immunoprecipitation assay, comet assay, and xenograft mouse model were used. BEND4 is a new member of the BEN domain family. The expression of BEND4 is regulated by promoter region methylation. It is methylated in 58.1% (176/303) of pancreatic ductal adenocarcinoma (PDAC), 33.3% (14/42) of intraductal papillary mucinous neoplasm, 31.0% (13/42) of pancreatic neuroendocrine tumor, 14.3% (3/21) of mucinous cystic neoplasm, 4.3% (2/47) of solid pseudopapillary neoplasm, and 2.7% (1/37) of serous cystic neoplasm. BEND4 methylation is significantly associated with late-onset PDAC (> 50 years, P < 0.01) and tumor differentiation (P < 0.0001), and methylation of BEND4 is an independent poor prognostic marker (P < 0.01) in PDAC. Furthermore, BEND4 plays tumor-suppressive roles in vitro and in vivo. Mechanistically, BEND4 involves non-homologous end joining signaling by interacting with Ku80 and promotes DNA damage repair. Loss of BEND4 increased the sensitivity of PDAC cells to ATM inhibitor. Collectively, the present study revealed an uncharacterized tumor suppressor BEND4 and indicated that methylation of BEND4 may serve as a potential synthetic lethal marker for ATM inhibitor in PDAC treatment.

关键词： BEND4 DNA methylation synthetic lethality NHEJ pathway

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Cell-free systems in the new age of synthetic biology

Fernando Villarreal,Cheemeng Tan

《化学科学与工程前沿（英文）》 2017年第11卷第1期页码 58-65 doi: 10.1007/s11705-017-1610-x

摘要： The advent of synthetic biology has ushered in new applications of cell-free transcription-translation systems. These cell-free systems are reconstituted using cellular proteins, and are amenable to modular control of their composition. Here, we discuss the historical advancement of cell-free systems, as well as their new applications in the rapid design of synthetic genetic circuits and components, directed evolution of biomolecules, diagnosis of infectious diseases, and synthesis of vaccines. Finally, we present our vision on the future direction of cell-free synthetic biology.

关键词： cell-free system application

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Hollow-fiber gas penetration electrodes efficiently produce renewable synthetic fuels

《能源前沿（英文）》 2022年第16卷第5期页码 700-705 doi: 10.1007/s11708-022-0842-8

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Removal efficiencies of natural and synthetic progesterones in hospital wastewater treated by different

《环境科学与工程前沿（英文）》 2022年第16卷第10期 doi: 10.1007/s11783-022-1558-z

摘要：

● The concentrations of 61 progesterones in HWW, PFTE, SBTE were evaluated.

关键词： Progesterones Hospital wastewater Primary filtration treatment effluent Secondary biological treatment effluent Disinfection process

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合成橡胶化学及技术进展

武冠英

《中国工程科学》 1999年第1卷第3期页码 79-85

摘要：

文章从合成橡胶的化学基础出发，叙述了合成橡胶工业二十世纪以来的过去、现状，并展望未来。着重讨论了合成化学基础及相应聚合工艺过程的进步这两方面的问题。指出合成橡胶化学基础中活性聚合、可控聚合，包括茂金属催化剂仍为近期的重点；气相聚合工艺将会得到较大的发展；高效聚合釜的研究仍是核心问题；环保问题应更受到重视。

关键词：合成橡胶合成化学活性/控制聚合气相聚合

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A review of optimization modeling and solution methods in renewable energy systems

《工程管理前沿（英文）》 2023年第10卷第4期页码 640-671 doi: 10.1007/s42524-023-0271-3

摘要： The advancement of renewable energy (RE) represents a pivotal strategy in mitigating climate change and advancing energy transition efforts. A current of research pertains to strategies for fostering RE growth. Among the frequently proposed approaches, employing optimization models to facilitate decision-making stands out prominently. Drawing from an extensive dataset comprising 32806 literature entries encompassing the optimization of renewable energy systems (RES) from 1990 to 2023 within the Web of Science database, this study reviews the decision-making optimization problems, models, and solution methods thereof throughout the renewable energy development and utilization chain (REDUC) process. This review also endeavors to structure and assess the contextual landscape of RES optimization modeling research. As evidenced by the literature review, optimization modeling effectively resolves decision-making predicaments spanning RE investment, construction, operation and maintenance, and scheduling. Predominantly, a hybrid model that combines prediction, optimization, simulation, and assessment methodologies emerges as the favored approach for optimizing RES-related decisions. The primary framework prevalent in extant research solutions entails the dissection and linearization of established models, in combination with hybrid analytical strategies and artificial intelligence algorithms. Noteworthy advancements within modeling encompass domains such as uncertainty, multienergy carrier considerations, and the refinement of spatiotemporal resolution. In the realm of algorithmic solutions for RES optimization models, a pronounced focus is anticipated on the convergence of analytical techniques with artificial intelligence-driven optimization. Furthermore, this study serves to facilitate a comprehensive understanding of research trajectories and existing gaps, expediting the identification of pertinent optimization models conducive to enhancing the efficiency of REDUC development endeavors.

关键词： renewable energy system bibliometrics mathematical programming optimization models solution methods

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Intelligent methods for the process parameter determination of plastic injection molding

Huang GAO, Yun ZHANG, Xundao ZHOU, Dequn LI

《机械工程前沿（英文）》 2018年第13卷第1期页码 85-95 doi: 10.1007/s11465-018-0491-0

摘要：

Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system-based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

关键词： injection molding intelligent methods process parameters optimization