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Metal-organic frameworks with dinuclear metal centers for synergistically boosting CO2 photoreduction

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Science China Chemistry 2025年第1期68卷 201-208页

作者： Hui-Feng Wang Wen-Jie Shi Yu-Xin Yang Bao-Xia Dong Tong-Bu Lu Di-Chang Zhong School of Chemistry and Chemical Engineering Yangzhou University Institute for New Energy Materials and Low Carbon Technologies School of Materials Science and Engineering Tianjin University of Technology

Dinuclear metal synergistic catalysis （DMSC） has been proved powerful in boosting CO2reduction,while this has not been achieved in heterogeneous catalysts with long-range order *** this study,we,by introduction of metal catalytic centers into an indium-based metal-organic framework （MOF）,obtained a series of isostructural In-MOFs,including three MOFs with mononuclear metal catalytic center （M-In）,three MOFs with dinuclear homometallic catalytic centers （MM-In）,and three MOFs with dinuclear heterometallic catalytic centers (MM’-In,M/M’=Co（II）,Ni（II）,Zn（II）).It was found that all these MOFs can serve as catalysts for photochemical CO2reduction to *** with M-In,the catalytic activities of MM-In were obviously enhanced,and that of MM’-In was further significantly *** example,the CO yield of Co Zn-In reaches a record value of 12,700μmol g-1h-1,which is 4.0,8.1,9.4,and 18.6-fold higher than that of Co Co-In,Zn Zn-In,Co-In,and Zn-In,***,the catalytic activities of Co Ni-In and Ni Zn-In also show different fold increase than those of corresponding dinuclear homometallic and mononuclear metallic *** results of control experiments and theoretical calculation reveal that the higher catalytic activities of MM-In over M-In can be ascribed to the DMSC effect,and the higher catalytic activity of MM’-In over MM-In can be ascribed to the strengthened DMSC *** work reveals the relationship between DMSC effect and bimetal centers in CO2reduction,which provides new insights into the DMSC and paves a new way to design highly active catalysts for photochemical CO2reduction.

关键词： metal-organic frameworks dinuclear metal centers synergistic catalysis CO2 reduction photocatalysis

Lenalidomide regulates the CCL21/CCR7/ERK1/2 axis to inhibit migration and proliferation in diffuse large B-cell lymphoma

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Oncology Research 2025年第1期33卷 199-212页

作者： WEN YANG BIN TANG DAN XU WENXIU YANG Department of Pathology Guizhou Medical UniversityThe Affiliated Hospital of Guizhou Medical UniversityGuiyang550004China

Background:The prognostic significance of the chemokine receptor CCR7 in diffuse large B-cell lymphoma(DLBCL)has been reported ***,the detailed mechanisms of CCR7 in DLBCL,particularly regarding its interaction with lenalidomide treatment,are not fully ***:Our study utilized bioinformatics approaches to identify hub genes in SU-DHL-2 cell lines treated with lenalidomide compared to control *** data and clinical information from 122 patients with DLBCL were analyzed to assess the correlation of CCR7 and p-ERK1/2 expression with the prognosis of ***,in vitro and in vivo experiments were conducted to clarify the role of CCR7 in the response of DLBCL to lenalidomide ***:Our bioinformatics analysis pinpointed CCR7 as a hub gene in the context of lenalidomide treatment in ***,31.14%and 36.0%(44/122)of DLBCL cases showed positive expression for CCR7 and ERK1/2 respectively,establishing them as independent prognostic factors for adverse outcomes in DLBCL via multivariate Cox regression ***,our studies demonstrated that the external application of the protein CCL21 promoted proliferation,migration,invasion,and activation of the ERK1/2 pathway in SU-DHL-2 and OCI-LY3 cell lines with high levels of CCR7 *** effect was mitigated by CCR7 silencing through siRNA,application of ERK inhibitors,or lenalidomide *** vivo experiments reinforced the efficacy of lenalidomide,significantly reducing tumor growth rate,tumor mass,serum total LDH levels,and expression of CCR7 and p-ERK1/2 in a SUDHL-2 xenograft model in nude mice(p<0.05).Conclusion:Our study clarifies the potential role of the CCL21/CCR7/ERK1/2 axis in the therapeutic effects of lenalidomide in DLBCL treatment.

关键词： CCR7 CCL21 ERK1/2 Lenalidomide Diffuse large B-cell lymphoma(DLBCL)

Universal design of three-dimensional porous graphene-iron based promotors for kinetically rationalized lithium-sulfur chemistry

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Journal of Energy Chemistry 2025年第1期100卷 192-200页

作者： Hua Gao Yunfeng Zhang Menglei Wang Ruoxuan Yang Shuai Feng Xuan Cao Yaping Zhang Zhongyuan Lu Yingze Song State Key Laboratory of Environment-Friendly Energy Materials School of Materials and Chemistry Southwest University of Science and Technology School of Material Science and Engineering Henan University of Technology College of Chemistry and Chemical Engineering Taishan University

Lithium-sulfur （Li-S） batteries are widely deemed to be one of the most potential candidates for future secondary batteries because of their remarkable energy ***,notorious polysulfide shuttling and retarded sulfur reaction kinetics pose significant obstacles to the further application of Li-S *** rationally designed highly active electrocatalysts can facilitate polysulfide conversion,the universal and scalable synthesis strategies need to be ***,a universal synthetic strategy to construct a series of three-dimensional （3D） porous graphene-iron （3DGr-Fe） based electrocatalysts involving 3DGr-FeP,3DGr-Fe3C,and 3DGr-Fe3Se4is exploited for manipulating the Li-S redox *** has been observed that the implementation of a 3D porous Gr architecture leads to the well-designed conductive networks,while the uniformly dispersed iron nanoparticles introduce an abundance of active sites,fostering the lithium polysulfide conversion,thereby bolstering the overall electrochemical *** Li-S battery with the 3DGr-Fe based electrocatalyst exhibits remarkable capacity retention of 94.8%upon 100 times at 0.2 ***,the soft-packaged Li-S pouch cell based on such a 3DGr-Fe electrocatalyst delivers superior capacity of 1060.71 mA h g-1and guarantees for the continuous 30 min work of fan *** investigation gives comprehensive insights into the design,synthesis,and mechanism of 3DGr-Fe based electrocatalysts with high activity toward efficient and durable Li-S batteries.

关键词： Redox reactions

Genes and proteins expressed at different life cycle stages in the model protist Euplotes vannus revealed by both transcriptomic and proteomic approaches

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Science China Life Sciences 2025年第1期68卷 232-248页

作者： Yaohan Jiang Xiao Chen Chundi Wang Liping Lyu Saleh A.Al-Farraj Naomi A.Stover Feng Gao Key Laboratory of Evolution & Marine Biodiversity (Ministry of Education) and Institute of Evolution & Marine Biodiversity Ocean University of China Marine College Shandong University Zoology Department College of ScienceKing Saud University Department of Biology Bradley University Laboratory for Marine Biology and Biotechnology Qingdao Marine Science and Technology Center

Sexual reproduction first appeared in unicellular protists and has continued to be an essential biological process in almost all *** protists, which contain both germline and somatic genomes within a single cell, have evolved a special form of sexual reproduction called conjugation that involves mitosis, meiosis, fertilization, nuclear differentiation, genome rearrangement, and the development of unique cellular structures. The molecular basis and mechanisms of conjugation vary dramatically among ciliates, and many details of the process and its regulation are still largely unknown. In order to better comprehend these processes and mechanisms from an evolutionary perspective, this study provides the first comprehensive overview of the transcriptome and proteome profiles during the entire life cycle of the newly-established marine model ciliate Euplotes vannus. Transcriptome analyses from 14 life cycle stages(three vegetative stages and 11 sexual stages) revealed over 26,000 genes that are specifically expressed at different stages, many of which are related to DNA replication,transcription, translation, mitosis, meiosis, nuclear differentiation, and/or genome rearrangement. Quantitative proteomic analyses identified 338 proteins with homologs associated with conjugation and/or somatic nuclear development in other ciliates, including dicer-like proteins, Hsp90 proteins, RNA polymerase Ⅱ and transcription elongation factors, ribosomal-associated proteins, and ubiquitin-related proteins. Four of these homologs belong to the PIWI family, each with different expression patterns identified and confirmed by RT-qPCR,which may function in small RNA-mediated genome rearrangement. Proteins involved in the nonhomologous end-joining pathway are induced early during meiosis and accumulate in the developing new somatic nucleus, where more than 80% of the germline sequences are eliminated from the somatic genome. A number of new candidate genes and proteins likely t

关键词： sexual reproduction transcriptomic proteomic genome rearrangement PIWI NHEJ

Maximizing biomass utilization: An integrated strategy for coproducing multiple chemicals

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Journal of Energy Chemistry 2025年第1期100卷 180-191页

作者： Byeongchan Ahn Sua Jo Jonggeol Na J.Jay Liu Young-Ju Kim Wangyun Won Department of Chemical and Biological Engineering Korea University Department of Chemical Engineering (Integrated process) Kyung Hee University Department of Chemical Engineering and Materials Science Ewha Womans University Department of Chemical Engineering Pukyong National University Resources Engineering Plant Research Department Korea Institute of Geoscience and Mineral Resources

Lignocellulosic biomass is one of the viable solutions to alleviate the global warming. However, the limited utilization of biomass majorly focused on cellulose and hemicellulose restricts the economic and environmental feasibilities. To cope with this issue, we proposed an integrated process of co-producing 1,6-hexanediol（1,6-HDO） with tetrahydrofuran and adipic acid from biomass, referred to as Strategy A. To compare the impacts of lignin upgrading and feedstock, Strategy B, which co-produces tetrahydrofuran alone, and Strategy C, which is the traditional route to produce 1,6-HDO from fossil fuels, were used. Heat networks are also designed to reduce operating costs and indirect carbon emissions due to energy consumption, saving 87% and 83% of the heat and cooling requirements, respectively, in Strategy A. The market competitiveness of Strategy A was evaluated by determining the minimum selling price through techno-economic analysis, and sustainability was thoroughly investigated by quantifying the environmental impacts through both midpoint and endpoint life-cycle assessments（LCAs）.Strategy A was found to be the most favorable both economically（USRDSCHARDOLLAR3,402/ton） and environmentally（-26.9 kg CO2eq.）. This indicates that lignin valorization is not only economically but also environmentally preferred. Finally, changes in economic and environmental feasibilities depending on economic, process, and environmental parameters were investigated using sensitivity and uncertainty analyses. The results of these analyses provide valuable insight into bio-based chemical production.

关键词： Carbon capture and utilization

Optimizing battery deployment: Aging trajectory prediction enabling homogenous performance grouping

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Journal of Energy Chemistry 2025年第1期100卷 565-577页

作者： Shuquan Wang Feng Gao Zhan Ma Hao Tian Yusen Zhang School of Control Science and Engineering Shandong University Key Lab of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University

As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and *** on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and *** robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.

关键词： Lithium-ion battery Battery prognostics Fusion model Convolutional neural network Transfer learning

An efficient quantum proactive incremental learning algorithm

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 49-57页

作者： Lingxiao Li Jing Li Yanqi Song Sujuan Qin Qiaoyan Wen Fei Gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications School of Cyberspace Security Beijing University of Posts and Telecommunications

In scenarios where a large amount of data needs to be learned, incremental learning can make full use of old knowledge, significantly reduce the computational cost of the overall learning process, and maintain high performance. In this paper, taking the MaxCut problem as our example, we introduce the idea of incremental learning into quantum computing, and propose a Quantum Proactive Incremental Learning algorithm(QPIL). Instead of a one-off training of quantum circuit, QPIL contains a multi-phase training on gradually-increased subgraphs of all vertices, proactively reducing large-scale problems to smaller ones to solve in steps, providing an efficient solution for MaxCut. Specifically, some vertices and corresponding edges are randomly selected for training to obtain optimized parameters of the quantum circuit at first. Then, in each incremental phase, the remaining vertices and corresponding edges are gradually added and the parameters obtained from the previous phase are reused in the parameter initialization of the current phase. We perform experiments on 120 different small-scale graphs, and it shows that QPIL performs superior to prevalent quantum and classical baselines in terms of approximation ratio(AR), time cost, anti-forgetting, and solving stability. In particular, QPIL's AR surpasses 20% of mainstream quantum baselines, and the time cost is less than 1/5 of them. The idea of QPIL is expected to inspire efficient and high-quality solutions in large-scale Max Cut and other combinatorial optimization problems.

关键词： variational quantum algorithm incremental learning multi-phase training MaxCut quantum computing

lncRNA SNHG4 enhanced gastric cancer progression by modulating miR-409-3p/CREB1 axis

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Oncology Research 2025年第1期33卷 185-198页

作者： ZHOUYANG CHENG YUCHEN HUA YANG CAO JUN QIN Department of General Surgery Affiliated Hospital of Nantong UniversityNantong226001China Department of Surgery Affiliated Hospital of Nantong UniversityMedical School of Nantong UniversityNantong226001China Department of Operation Affiliated Hospital of Nantong UniversityNantong226001China

Objective:Gastric cancer(GC)is a globally common cancer characterized by high incidence and mortality *** in the molecular understanding of GC provide promising targets for GC diagnosis and *** non-coding RNAs(lncRNAs)and their downstream regulators are regarded to be implicated in the progression of multiple types of *** have shown that the lncRNA small nucleolar RNA host gene 4(SNHG4)serves as a tumor promoter in various malignancies,while its function in GC has yet to be ***,our study aimed to explore the role and underlying mechanism of SNHG4 in ***:We used qRT-PCR to analyze SNHG4 expression in GC tissues and ***-Meier analysis was used to assess the correlation between SNHG4 expression and the survival rate of GC *** function experiments such as CCK-8,BrdU,colony formation,flow cytometry analysis,and transwell were performed to explore the effects of SNHG4 on GC cell proliferation,apoptosis,cell cycle,migration,and *** also established xenograft mouse models to explore the effect of SNHG4 on GC tumor ***,dual luciferase reporter assay was used to verify the interaction between SNHG4 and miR-409-3p and between miR-409-3p and cAMP responsive element binding protein 1(CREB1).Results:The results indicated that SNHG4 was overexpressed in GC tissues and cell lines,and was linked with poor survival rate of GC ***4 promoted GC cell proliferation,migration,and invasion while inhibiting cell apoptosis and cell cycle arrest in *** in vivo experiment indicated that SNHG4 facilitated GC tumor ***,SNHG4 was demonstrated to bind to ***,CREB1 was directly targeted by *** assays demonstrated that miR-409-3p deficiency reversed the suppressive impact of SNHG4 knockdown on GC cell ***,miR-409-3p was also revealed to inhibit GC cell proliferation,migration,and invasion by targeting CREB1

关键词： Gastric cancer Small nucleolar RNA host gene 4(SNHG4) MicroRNA-409-3p(miR-409-3p) cAMP responsive element binding protein 1(CREB1)

Deep learning-based software engineering: progress,challenges, and opportunities

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Science China(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking university) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey