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Deep learning-based multi-task prediction of response to neoadjuvant chemotherapy using multiscale whole slide images in breast cancer:A multicenter study

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Chinese Journal of Cancer Research 2025年第01期 28-54页

作者： qin Wang Feng Zhao Haicheng Zhang Tongpeng Chu Qi Wang Xipeng Pan Yuqian Chen Heng Zhou Tiantian Zheng Ziyin Li Fan Lin Haizhu Xie Heng Ma Lan Liu Lina Zhang qin Li Weiwei Wang yi Dai Ruijun Tang Jigang Wang Ping Yang Ning Mao School of Information and Electronic Engineering Shandong Technology and Business University Big Data and Artificial Intelligence Laboratory Yantai Yuhuangding Hospital of Qingdao University Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women's Diseases Yantai Yuhuangding Hospital Department of Radiology Yantai Yuhuangding Hospital of Qingdao University School of Computer Science and Technology Shandong Technology and Business University School of Computer Science and Information Security Guilin University of Electronic Technology School of Medical Imaging Binzhou Medical University Department of Radiology Jiangxi Cancer Hospital the Second Affiliated Hospital of Nanchang Medical College Department of Radiology the First Affiliated Hospital of China Medical University Department of Radiology Weifang Hospital of Traditional Chinese Medicine Department of Medical Imaging Affiliated Hospital of Jining Medical University Department of Radiology the Peking University Shenzhen Hospital Department of Pathology Guilin Traditional Chinese Medicine Hospital Department of Pathology the Affiliated Hospital of Qingdao University Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women’s Diseases Yantai Yuhuangding Hospital Department of Pathology Yantai Yuhuangding Hospital of Qingdao University

Objective: Early predicting response before neoadjuvant chemotherapy(NAC) is crucial for personalized treatment plans for locally advanced breast cancer patients. We aim to develop a multi-task model using multiscale whole slide images(WSIs) features to predict the response to breast cancer NAC more ***: This work collected 1,670 whole slide images for training and validation sets, internal testing sets,external testing sets, and prospective testing sets of the weakly-supervised deep learning-based multi-task model(DLMM) in predicting treatment response and pCR to NAC. Our approach models two-by-two feature interactions across scales by employing concatenate fusion of single-scale feature representations, and controls the expressiveness of each representation via a gating-based attention ***: In the retrospective analysis, DLMM exhibited excellent predictive performance for the prediction of treatment response, with area under the receiver operating characteristic curves(AUCs) of 0.869 [95% confidence interval(95% CI): 0.806-0.933] in the internal testing set and 0.841(95% CI: 0.814-0.867) in the external testing sets. For the pCR prediction task, DLMM reached AUCs of 0.865(95% CI: 0.763-0.964) in the internal testing and 0.821(95% CI: 0.763-0.878) in the pooled external testing set. In the prospective testing study, DLMM also demonstrated favorable predictive performance, with AUCs of 0.829(95% CI: 0.754-0.903) and 0.821(95% CI:0.692-0.949) in treatment response and pCR prediction, respectively. DLMM significantly outperformed the baseline models in all testing sets(P<0.05). Heatmaps were employed to interpret the decision-making basis of the model. Furthermore, it was discovered that high DLMM scores were associated with immune-related pathways and cells in the microenvironment during biological basis ***: The DLMM represents a valuable tool that aids clinicians in selecting personalized treatment strategies for breast

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Transcriptome Analysis of Derris fordii and Derris elliptica to Identify Potential Genes Involved in Rotenoid Biosynthesis

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Phyton-International Journal of Experimental Botany 2025年第1期94卷 123-136页

作者： Yanlin Pan yibin Zhang Xingui Wang Hongbo qin Lunfa Guo Guangxi Institute of Botany Guangxi Zhuangzu Autonomous Region and the Chinese Academy of SciencesGuilin541006China Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain Guangxi Institute of BotanyGuangxi Zhuangzu Autonomous Region and the Chinese Academy of SciencesGuilin541006China

Derris fordii and Derris elliptica belong to the Derris genus of the Fabaceae family, distinguished by their high isoflavonoid content, particularly rotenoids, which hold significance in pharmaceuticals and agriculture. Rotenone, as a prominent rotenoid, has a longstanding history of use in pesticides, veterinary applications, medicine, and medical research. The accumulation of rotenoids within Derris plants adheres to species-specific and tissue-specific patterns and is also influenced by environmental factors. Current research predominantly addresses extraction techniques, pharmacological applications, and pesticide formulations, whereas investigations into the biosynthesis pathway and regulatory mechanism of rotenoids remain relatively scarce. In this study, we observed notable differences in rotenone content across the roots, stems, and leaves of D. fordii, as well as within the roots of D. elliptica. Utilizing RNA sequencing (RNA-seq), we analyzed the transcriptomes and expression profiles of unigenes from these four tissues, identifying a total of 121,576 unigenes. Differentially expressed genes (DEGs) across four comparison groups demonstrated significant enrichment in the phenylpropanoid and flavonoid biosynthesis pathways. Key unigenes implicated in the rotenoid biosynthesis pathway were identified, with PAL, C4H, CHS, CHI, IFS, and HI4OMT playing critical roles in D. fordii, while IFS and HI4OMT were determined to be essential for rotenoid biosynthesis in D. elliptica. These findings enhance our understanding of the biosynthesis mechanism of rotenoids in Derris species. The unigenes identified in this study represent promising candidates for future investigations aimed at validating their roles in rotenoid biosynthesis.

关键词： Derris fordii Derris elliptica RNA-seq rotenoid comparative transcriptomic analysis

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基于权衡协同效应的安徽省生态功能区识别及情景模拟

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中国环境科学 2025年第1期45卷 450-464页

作者：黄木易汤玉茹郭芹吴雪安徽建筑大学环境与能源工程学院安徽合肥230601 安徽省生态文明研究院安徽合肥230601 安徽省环境污染控制与资源化重点实验室安徽合肥230601 安徽建筑大学建筑与规划学院安徽合肥230601

基于生态系统服务及其权衡/协同效应的时空分布特征进行生态功能区划,能有效满足特定区域在协调多种生态系统服务方面存在的现实需求,根据不同生态系统服务的特定生态属性,制订相应的管理策略,有助于研究区的可持续发展.基于生态系统服... 详细信息

基于生态系统服务及其权衡/协同效应的时空分布特征进行生态功能区划,能有效满足特定区域在协调多种生态系统服务方面存在的现实需求,根据不同生态系统服务的特定生态属性,制订相应的管理策略,有助于研究区的可持续发展.基于生态系统服务权衡/协同效应识别生态功能区可为生态功能修复与治理提供精准和差异化调控依据.以安徽省为例,应用InVEST模型评估和分析2000~2020年间安徽省典型生态系统服务时空演变及权衡/协同效应,基于SOM(自组织映射)模型提取的生态系统服务簇,划分生态功能区,最后运用PLUS模型模拟2050年综合生态系统服务演变趋势并提出调控思路.结果表明:①安徽省2000~2020年期间,产水服务、土壤保持不断增加,而固碳服务、生境质量及粮食供给则呈降低趋势.安徽省综合生态系统服务指数空间格局为“南高北低”.研究区能提供两类生态系统服务的区域约占50%,能提供全部生态服务的区域仅约占11%,不能提供生态系统服务的区域分别由2000年的0.07%上升到2020年的4.85%.②产水服务、固碳服务、生境质量和土壤保持这4种生态系统服务间存在密切的协同效应,而产水服务和粮食生产存在明显的权衡效应.③据此为研究区提取了4种生态系统服务簇,分别为粮食供给簇、生态保育簇、人居环境簇和森林防护簇.最终将安徽省域划分为农业生态区、生态涵养区、城镇发展区和森林生态防护区,并提出差异化调控对策.④多情景模拟分析显示,生态保护情景下的生境质量和固碳服务最优,粮食生产在耕地保护情景下最高,在生态保护情景下,综合生态系统服务呈现出显著提升的态势.研究结果可为安徽省可持续发展和生态环境优化提供科学依据.

关键词：生态系统服务权衡协同效应生态功能分区多情景模拟安徽省

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Hemoglobin integrated red blood cell membrane-coated metalorganic framework nano-platform for improving the self-adaptive blood glucose management

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Nano Research 2025年第1期18卷 618-627页

作者： Shuai Wu Li Zhu Sheng Ni Xiong Zhao Meng Yan Yuan Zhong Karissa Kusuma yi Liang Kaiwen Bao Kai Qu Xian qin Kun Zhang Wuquan Deng Da Sun Wei Wu Key Laboratory of Biorheological Science and Technology Ministry of EducationCollege of BioengineeringChongqing UniversityChongqing 400044China Chongqing University Three Gorges Hospital Chongqing Municipality Clinical Research Center for Endocrinology and Metabolic DiseasesChongqing 404000China Institute of Life Sciences&Biomedical Collaborative Innovation Center of Zhejiang Province Wenzhou UniversityWenzhou 325035China Department of Endocrinology School of MedicineChongqing Emergency Medical CenterChongqing University Central HospitalChongqing 400014China

Diabetes,a prevalent chronic metabolic disorder,often leads to severe ***,existing treatment methods may pose life-threatening risks due to poor patient compliance and inaccurate dosing of subcutaneous insulin ***,a biomimetic red blood cell(RBC)membrane-coated glucose-responsive nanoplatform is developed for controlling insulin *** nanoplatforms with RBC membrane can prolong the half-life of nano-formulation in vivo mediated by the biomimetic immune ***,the cascade catalytic effect of glucose oxidase(GOx)encapsulated in metal-organic frameworks(MOFs)and hemoglobin(Hb)in the RBC membrane are able to not only facilitate glucose-responsive insulin release,but also eliminate the detrimental by-product hydrogen peroxide(H_(2)O_(2))resulting from the Hb mediated H_(2)O_(2)*** in vitro and in vivo studies have demonstrated the favorable glucose-responsive performances of this advanced nano-platform with a single intravenous injection maintaining blood glucose balance in Type 1 Diabetes(T1D)mice for an extended duration without the hypoglycemia ***,this biomimetic insulin delivery system is poised to function as a strategy for the intravenous insulin administration,offering a promising drug candidate for the self-adaptive long-term T1D treatment.

关键词： glucose-responsive metal-organic frameworks red blood cell membrane insulin delivery glucose oxidase hemoglobin

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煤矿井下自动钻机集控技术应用研究

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矿山机械 2025年第1期53卷 11-15页

作者：秦怡煤矿灾害防控全国重点实验室重庆400039 中煤科工集团重庆研究院有限公司重庆400039

针对煤矿井下自动钻机单兵作战模式,提出“一站多控”方案,即一台远程交互控制站可控制多台自动钻机。采用现代数字信息处理、建模和通信技术,将同一区域的自动钻机联网,实现了钻机群的协同控制及管理。通过井下试验研究,结果表明:该方... 详细信息

针对煤矿井下自动钻机单兵作战模式,提出“一站多控”方案,即一台远程交互控制站可控制多台自动钻机。采用现代数字信息处理、建模和通信技术,将同一区域的自动钻机联网,实现了钻机群的协同控制及管理。通过井下试验研究,结果表明:该方案可以较大地减少钻机操作人员数量及管理成本,降低了钻进事故率及钻机故障率,提高了钻孔作业安全性,为煤矿安全智能化开采提供新技术。

关键词：自动钻机集控技术一站多控协同控制

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Compact source for quadripartite deterministically entangled optical fields

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Fundamental Research 2025年第1期5卷 132-137页

作者： Liu, Yanhong Zhou, Yaoyao Wu, Liang qin, Jiliang Yan, Zhihui Jia, Xiaojun Department of Physics Taiyuan Normal University Jinzhong 030619 China Institute of Computational and Applied Physics Taiyuan Normal University Jinzhong 030619 China State Key Laboratory of Quantum Optics and Quantum Optics Devices Institute of Opto-Electronics Shanxi University Taiyuan 030006 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan 030006 China College of Information Engineering Shanxi Vocational University of Engineering Science and Technology Jinzhong 030619 China

Since entangled multiple optical fields were identified as the building blocks of quantum networks, the quadripartite entangled optical fields have been produced by using four degenerate optical parametric amplifiers or two nondegenerate optical parametric amplifiers (NOPAs). However, realizing an efficient and compact source for multiple quantum users has remained an outstanding challenge, hindering their practical applications. Here, we proposed a compact and feasible scheme to deterministically entangle four spatially separated optical fields, employing only a single NOPA. Accordingly, two-sided output NOPA-based optical fields were coupled on a beam splitter network to form the quadripartite entangled state, causing the deterministic generation of both the Greenberger–Horne–Zeilinger (GHZ) and the linear cluster states in this compact entanglement source. We also obtained the optimal experimental parameters based on the simulation results, thereby providing a direct reference for experimental implementation. Our findings propose that the resultant GHZ and linear cluster states can be potentially applied in quantum-enhanced information science, specifically in quantum secret sharing, controlled quantum teleportation networks, and quantum-entangled atomic ensemble networks. © 2022 The Authors

关键词： Cluster state Compact source GHZ state Quadripartite entanglement Single NOPA

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Multi boron-doping effects in hard carbon toward enhanced sodium ion storage

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Journal of Energy Chemistry 2025年第1期100卷 730-738页

作者： Peng Zheng Wang Zhou ying Mo Biao Zheng Miaomiao Han qin Zhong Wenwen Yang Peng Gao Lezhi Yang Jilei Liu College of Materials Science and Engineering Hunan Joint International Laboratory of Advanced Materials and Technology for Clean EnergyHunan Province Key Laboratory for Advanced Carbon Materials and Applied TechnologyHunan UniversityChangsha 410082HunanChina Greater Bay Area Institute for Innovation Hunan UniversityGuangzhou 511300GuangdongChina Changsha Research Institute of Mining&Metallurgy Co. LTD.Changsha 410017HunanChina

Hard carbon (HC) has been considered as promising anode material for sodium-ion batteries (SIBs).The optimization of hard carbon’s microstructure and solid electrolyte interface (SEI) property are demonstrated effective in enhancing the Na+storage capability,however,a one-step regulation strategy to achieve simultaneous multi-scale structures optimization is highly ***,we have systematically investigated the effects of boron doping on hard carbon’s microstructure and interface chemistry.A variety of structure characterizations show that appropriate amount of boron doping can increase the size of closed pores via rearrangement of carbon layers with improved graphitization degree,which provides more Na+storage ***-situ Fourier transform infrared spectroscopy/electrochemical impedance spectroscopy (FTIR/EIS) and X-ray photoelectron spectroscopy (XPS) analysis demonstrate the presence of more BC3and less B–C–O structures that result in enhanced ion diffusion kinetics and the formation of inorganic rich and robust SEI,which leads to facilitated charge transfer and excellent rate *** a result,the hard carbon anode with optimized boron doping content exhibits enhanced rate and cycling *** general,this work unravels the critical role of boron doping in optimizing the pore structure,interface chemistry and diffusion kinetics of hard carbon,which enables rational design of sodium-ion battery anode with enhanced Na+storage performance.

关键词： Hard carbon Sodium-ion batteries Boron doping Pore structure Electrode/electrolyte interphases

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Reduced mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor contributes to neurodegeneration in a model of spinal and bulbar muscular atrophy pathology

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Neural Regeneration Research 2025年第9期20卷 2655-2666页

作者： yiyang qin Wenzhen Zhu Tingting Guo yiran Zhang Tingting Xing Peng yin Shihua Li Xiao-Jiang Li Su Yang Guangdong Key Laboratory of Non-human Primate Research Key Laboratory of CNS Regeneration(Ministry of Education)Guangdong–HongKong–Macao Institute of CNS RegenerationJinan UniversityGuangzhouGuangdong ProvinceChina

Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto *** mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy *** aggregates alter protein-protein interactions and compromise transcriptional *** this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic *** n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor *** down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor *** findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy.

关键词： androgen receptor mesencephalic astrocyte-derived neurotrophic factor mouse model neurodegeneration neuronal loss neurotrophic factor polyglutamine disease protein misfolding spinal and bulbar muscular atrophy transcription factor

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基于能量优化和超时传输的水声传感器网络路由协议研究

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控制与决策 2025年第1期40卷 55-63页

作者：王雪怡刘妹琴张森林浙江大学电气工程学院杭州310027 西安交通大学人机混合增强智能全国重点实验室西安710049 浙江大学金华研究院浙江金华321036

高性能水声路由协议要求协议具有高吞吐量的同时,能耗尽可能小,这是提高能源利用效率的关键.针对这一问题,提出基于能量优化和超时传输的水声传感器网络路由协议.首先,路由寻找阶段融合能量均衡策略并利用退避机制尽可能接收多的路由请... 详细信息

高性能水声路由协议要求协议具有高吞吐量的同时,能耗尽可能小,这是提高能源利用效率的关键.针对这一问题,提出基于能量优化和超时传输的水声传感器网络路由协议.首先,路由寻找阶段融合能量均衡策略并利用退避机制尽可能接收多的路由请求再进行回复来控制路由开销;然后,数据传输阶段引入超时传输机制,利用主备份路由协同传输并监听和判断链路有效性,融合碰撞避免机制规避碰撞;最后,通过仿真和水下实验与按需平面距离向量路由协议(Ad Hoc on-demand distance vector routing,AODV)和矢量转发路由协议(vector based forwarding,VBF)进行对比.仿真实验结果表明:所提出协议相比于AODV与VBF,吞吐量和数据包成功接收率均有提升,且具有更低的单位字节能耗;水下实验结果表明:相比于AODV,所提出协议吞吐量提升了11.84%,数据包成功接收率提升了15.62%,单位字节能耗可降低0.10 J.

关键词：水声传感器网络路由协议能量优化超时传输退避机制碰撞避免机制

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Machine learning-based grayscale analyses for lithofacies identification of the Shahejie formation, Bohai Bay Basin, China

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Petroleum Science 2025年第1期22卷 42-54页

作者： Yu-Fan Wang Shang Xu Fang Hao Hui-Min Liu qin-Hong Hu Ke-Lai Xi Dong Yang National Key Laboratory of Deep Oil and Gas China University of Petroleum (East China) Shengli Oilfield Branch Company SINOPEC

It is of great significance to accurately and rapidly identify shale lithofacies in relation to the evaluation and prediction of sweet spots for shale oil and gas reservoirs. To address the problem of low resolution in logging curves, this study establishes a grayscale-phase model based on high-resolution grayscale curves using clustering analysis algorithms for shale lithofacies identification, working with the Shahejie Formation, Bohai Bay Basin, China. The grayscale phase is defined as the sum of absolute grayscale and relative amplitude as well as their features. The absolute grayscale is the absolute magnitude of the gray values and is utilized for evaluating the material composition(mineral composition + total organic carbon) of shale, while the relative amplitude is the difference between adjacent gray values and is used to identify the shale structure type. The research results show that the grayscale phase model can identify shale lithofacies well, and the accuracy and applicability of this model were verified by the fitting relationship between absolute grayscale and shale mineral composition, as well as corresponding relationships between relative amplitudes and laminae development in shales. Four lithofacies are identified in the target layer of the study area: massive mixed shale, laminated mixed shale, massive calcareous shale and laminated calcareous shale. This method can not only effectively characterize the material composition of shale, but also numerically characterize the development degree of shale laminae, and solve the problem that difficult to identify millimeter-scale laminae based on logging curves, which can provide technical support for shale lithofacies identification, sweet spot evaluation and prediction of complex continental lacustrine basins.

关键词： Shale Machine learning Absolute grayscale Relative amplitude Grayscale phase model Lithofacies identification

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