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Unlocking the future:Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response

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World Journal of Clinical Oncology 2025年第1期16卷 43-52页

作者： Zhi-Jian Tang Yuan-ming Pan Wei li Rui-Qiong Ma Jian-liu Wang Department of Obstetrics and Gynecology Peking University People’s HospitalBeijing 100044China Cancer Research Center Beijing Chest HospitalBeijing 101149China Department of Thoracic Surgery Sichuan Provincial People's HospitalChengdu 610072Sichuan ProvinceChina

BACKGROUND Mitochondrial genes are involved in tumor metabolism in ovarian cancer(OC)and affect immune cell infiltration and treatment *** To predict prognosis and immunotherapy response in patients diagnosed with OC using mitochondrial genes and neural *** Prognosis,immunotherapy efficacy,and next-generation sequencing data of patients with OC were downloaded from The Cancer Genome Atlas and Gene Expression *** genes were sourced from the MitoCarta3.0 *** discovery cohort for model construction was created from 70% of the patients,whereas the remaining 30% constituted the validation *** the expression of mitochondrial genes as the predictor variable and based on neural network algorithm,the overall survival time and immunotherapy efficacy(complete or partial response)of patients were *** In total,375 patients with OC were included to construct the prognostic model,and 26 patients were included to construct the immune efficacy *** average area under the receiver operating characteristic curve of the prognostic model was 0.7268[95% confidence interval(CI):0.7258-0.7278]in the discovery cohort and 0.6475(95%CI:0.6466-0.6484)in the validation *** average area under the receiver operating characteristic curve of the immunotherapy efficacy model was 0.9444(95%CI:0.8333-1.0000)in the discovery cohort and 0.9167(95%CI:0.6667-1.0000)in the validation *** The application of mitochondrial genes and neural networks has the potential to predict prognosis and immunotherapy response in patients with OC,providing valuable insights into personalized treatment strategies.

关键词： Ovarian cancer Mitochondria Prognosis Immunotherapy Neural network

High-throughput screening of CO_(2) cycloaddition MOF catalyst with an explainable machine learning model

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Green Energy & Environment 2025年第1期10卷 132-138页

作者： Xuefeng Bai Yi li Yabo Xie Qiancheng Chen Xin Zhang Jian-Rong li Beijing Key Laboratory for Green Catalysis and Separation and Department of Chemical Engineering College of Materials Science&EngineeringBeijing University of TechnologyBeijing100124China

The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design ***-throughput screening of catalytic performance is feasible since the large MOF structure database is *** this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition *** descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification *** feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were *** them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.

关键词： Metal-organic frameworks High-throughput screening Machine learning Explainable model CO_(2)cycloaddition

参与食品可追溯体系对农户绿色生产转型的影响

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西北农林科技大学学报（社会科学版） 2025年第1期25卷 89-100页

作者：陈哲李晓静司伟西北农林科技大学经济管理学院陕西杨凌712100 烟台大学经济管理学院山东烟台264005 中国农业大学经济管理学院北京100083

基于2022年山东和陕西2省6县(市、区)1 248户苹果种植户的微观调查数据,在使用有限混合模型(FMM)测度农户绿色生产转型程度的基础上,实证检验参与食品可追溯体系对农户绿色生产转型的影响。研究结果表明:(1)参与食品可追溯体系会显著促... 详细信息

基于2022年山东和陕西2省6县(市、区)1 248户苹果种植户的微观调查数据,在使用有限混合模型(FMM)测度农户绿色生产转型程度的基础上,实证检验参与食品可追溯体系对农户绿色生产转型的影响。研究结果表明:(1)参与食品可追溯体系会显著促进农户绿色生产转型,这一结论在解决潜在的内生性问题和经过多种稳健性检验后依然成立;(2)异质性分析表明,参与食品可追溯体系对大规模种植户、参与组织和受教育水平更高的农户绿色生产转型的促进作用更为明显;(3)机制分析结果表明,参与食品可追溯体系可以通过产品收益激励、绿色认知提升、社会声誉维护三条路径影响农户绿色生产转型。据此提出加大食品可追溯体系建设,提高农户参与比率;明晰转型关键制约因素,增强农户绿色生产转型意愿;充分考虑不同资源禀赋农户特征,给予针对性的政策引导等对策建议。

关键词：食品可追溯体系绿色生产转型溢价激励随机前沿模型苹果种植户

机器学习在智能反射面辅助的通信系统中的应用综述

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北京工业大学学报 2025年第1期51卷 87-99页

作者：司鹏搏李双缘刘畅李萌北京工业大学信息学部北京100124 先进信息网络北京实验室北京100124

智能反射面(intelligent reflecting surfaces,IRS)可以通过大量低成本的无源反射元件巧妙地调整信号反射,从而动态改变无线信道,提高通信性能,目前已成为无线通信研究的焦点。然而,由于IRS的加入,整个通信系统变得更加复杂,系统的动态... 详细信息

智能反射面(intelligent reflecting surfaces,IRS)可以通过大量低成本的无源反射元件巧妙地调整信号反射,从而动态改变无线信道,提高通信性能,目前已成为无线通信研究的焦点。然而,由于IRS的加入,整个通信系统变得更加复杂,系统的动态性也更高,使通信系统面临着许多新的挑战。机器学习(machine learning,ML)具有很强的数据处理与自适应能力,能够不断适应变化的环境和需求,可以很好地应对通信系统中的许多挑战。因此,使用ML解决IRS辅助的通信系统中的问题,已经成为当前研究的重点。基于此,对ML在IRS系统中的应用进行了系统性的概述,从IRS辅助的通信系统中存在的问题入手,分别从反射因子的设计与优化、信道处理与建模、资源分配和管理、安全性增强4个方面对ML在IRS系统中的应用进行阐述和分析,并讨论了将ML应用在IRS系统中的优势及未来的发展趋势与挑战。

关键词：智能反射面(intelligent reflecting surfaces,IRS) 无线通信反射因子信道资源分配通信安全机器学习(machine learning,ML)

A Hybrid Approach for Pavement Crack Detection Using Mask R-CNN and Vision Transformer Model

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Computers, Materials & Continua 2025年第1期82卷 561-577页

作者： Shorouq Alshawabkeh li Wu Daojun Dong Yao Cheng liping li Faculty of Engineering China University of GeosciencesWuhan430074China

Detecting pavement cracks is critical for road safety and infrastructure *** methods,relying on manual inspection and basic image processing,are time-consuming and prone to *** deep-learning(DL)methods automate crack detection,but many still struggle with variable crack patterns and environmental *** study aims to address these limitations by introducing the Masker Transformer,a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network(Mask R-CNN)with the global contextual awareness of Vision Transformer(ViT).The research focuses on leveraging the strengths of both architectures to enhance segmentation accuracy and adaptability across different pavement *** evaluated the performance of theMaskerTransformer against other state-of-theartmodels such asU-Net,TransformerU-Net(TransUNet),U-NetTransformer(UNETr),SwinU-NetTransformer(Swin-UNETr),You Only Look Once version 8(YoloV8),and Mask R-CNN using two benchmark datasets:Crack500 and *** findings reveal that the MaskerTransformer significantly outperforms the existing models,achieving the highest Dice similarityCoefficient(DSC),precision,recall,and F1-Score across both ***,the model attained a DSC of 80.04%on Crack500 and 91.37%on DeepCrack,demonstrating superior segmentation accuracy and *** high precision and recall rates further substantiate its effectiveness in real-world applications,suggesting that the Masker Transformer can serve as a robust tool for automated pavement crack detection,potentially replacing more traditional methods.

关键词： Pavement crack segmentation transportation deep learning vision transformer Mask R-CNN image segmentation

Activatable chemiluminescence probe based on four-arm PEGconjugated-pyropheophorbide-a for in vivo autofluorescence-free imaging of peroxynitrite

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Science China Chemistry 2025年

作者： Jianmei Ke Lei Ding Ronggui lian Cheng Zheng Wenjun li Aixian Zheng Yupeng Sun ming Wu Yongyi Zeng Xiaolong liu Maochun Hong Xiaolong Zhang The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province Mengchao Hepatobiliary Hospital of Fujian Medical University Ganjiang Innovation Academy Chinese Academy of Sciences School of Rare Earths University of Science and Technology of China College of Chemistry Fuzhou University State Key Laboratory of Structure Chemistry Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences

Peroxynitrite（ONOO-） is a highly reactive nitrogen species that plays pivotal roles in cell signal transduction and physiological or pathological progresses. However, commonly used ONOO-optical imaging probes are still hampered by high background/autofluorescence（fluorescence probe）, short emission wavelength, or poor selectivity in the case of chemiluminescence. Herein,we report a facile method to prepare an activatable chemiluminescence probe（PPA-PEG） with good biocompatibility and functionality for in vivo autofluorescence-free imaging of ONOO-. The PPA-PEG consists of pyropheophorbide-a（PPA）, a typical deep red photosensitizer that acts as both the recognition and signaling element, and 4-arm poly（ethylene glycol）(4-arm PEG), which improves the biosafety and water solubility of probe. These components can self-assemble into nanoparticles（namely PPA-PEG nanoprobe） in aqueous solution. The PPA-PEG nanoprobe showed an ultra-low chemiluminescence signal before interacting with ONOO-, but exhibited good selectivity, high sensitivity and a fast response toward ONOO-. The PPAPEG was successfully applied to image cellular ONOO-changes, as well as the endogenous ONOO-changes in inflammation models and subcutaneous or orthotopic hepatocellular carcinoma（HCC） tumors models in living mice. In vitro and in vivo studies verified the good detection and imaging capabilities of PPA-PEG for peroxynitrite, demonstrating suitable tissue penetration and a high signal-to-background ratio（SBR）. Thus, our nanoprobe can serve as a valuable activatable chemiluminescence imaging tool for studying important peroxynitrite-related chemical and biological applications.

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Ultra‑High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

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Nano-Micro Letters 2025年第2期17卷 432-446页

作者： Hao Yin Yanting li Zhiying Tian Qichao li Chenhui Jiang Enfu liang Yiping Guo State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China Beijing Vacuum Electronics Research Institute Beijing 100015People’s Republic of China Fundamental Science On Vibration Shock and Noise LaboratoryState Key Laboratory of Mechanical System and VibrationSchool of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing ***,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also ***,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic *** as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse *** ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate ***,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%*** structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.

关键词： Flexible piezoelectric filaments Anisotropic Ultra-high sensitivity Structural health detection Texture recognition

Optimization Strategies of Na_(3)V_(2)(PO_(4))_(3) Cathode Materials for Sodium‑Ion Batteries

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Nano-Micro Letters 2025年第2期17卷 204-251页

作者： Jiawen Hu Xinwei li Qianqian liang li Xu Changsheng Ding Yu liu Yanfeng Gao School of Materials Science and Engineering Shanghai UniversityShanghai 200444People’s Republic of China Shanghai Institute of Ceramics Chinese Academy of SciencesShanghai 200050People’s Republic of China

Na_(3)V_(2)(PO_(4))_(3)(NVP)has garnered great attentions as a prospective cathode material for sodium-ion batteries(siBs)by virtue of its decent theoretical capacity,superior ion conductivity and high structural ***,the inherently poor electronic conductivity and sluggish sodium-ion diffusion kinetics of NVP material give rise to inferior rate performance and unsatisfactory energy density,which strictly confine its further application in ***,it is of significance to boost the sodium storage performance of NVP cathode *** to now,many methods have been developed to optimize the electrochemical performance of NVP cathode *** this review,the latest advances in optimization strategies for improving the electrochemical performance of NVP cathode material are well summarized and discussed,including carbon coating or modification,foreign-ion doping or substitution and nanostructure and morphology *** foreign-ion doping or substitution is highlighted,involving Na,V,and PO_(4)^(3−)sites,which include single-site doping,multiple-site doping,single-ion doping,multiple-ion doping and so ***,the challenges and prospects of high-performance NVP cathode material are also put *** is believed that this review can provide a useful reference for designing and developing high-performance NVP cathode material toward the large-scale application in siBs.

关键词： Sodium-ion batteries Na_(3)V_(2)(PO_(4))_(3) Cathode materials Electrochemical performance Optimization strategies

Quantitative reconstruction of salinity and precipitation changes in Central Asia over the past 3200 years using diatom and pollen records of lacustrine sediment in Aibi Lake of SW Junggar Basin

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Journal of Earth Science 2025年

作者： Long Pan Guoqiang li Xiaoyan Wang ming Jin Xinrong He Luo Qin Zhong Wang Wenwei Zhao Chunzhu Chen Yuanlu liu Jin Yang Lele Shu Key Laboratory of Western China's Environmental Systems (Ministry of Education)， College of Earth and Environmental Sciences， Lanzhou University College of Earth Sciences， Chengdu University of Technology School of Geographic Science， Nantong University Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions， Northwest Institute of Eco-Environment and Resources， Chinese Academy of Sciences

The response of lake environments in arid Central Asia to climate change during the Late Holocene over the centennial to millennial timescales remains contentious. The reason that primarily paleoenvironmental proxies interpreting diverse and the scarcity of accurate quantitative reconstruction records. In this study， we employed diatoms and pollen records from lacustrine sediment in the Aibi Lake of SW Junggar Basin to quantitatively reconstruct salinity and watershed precipitation amounts while exploring the associated forcing mechanism. The results indicate that Aibi Lake salinity varied between 2 g/L and 47 g/L during the Late Holocene period， indicating a generally brackish environment， and corresponding to prevailing Tryblionella granulata diatom in the lake basin. Westerly-dominated annual precipitation varied between 250 mm and 320 mm during the Late Holocene period in the basin， exhibiting a generally semi-arid environment and prevailing desert steppe vegetation. The Aibi Lake has a low salinity of average value of ～15 g/L. It exhibits elevated precipitation (average value of ～280 mm) during the periods of the Roman Warm Period (2900-1990 cal yr BP)， Dark Age Cold Period (1570-1140 cal yr BP)， and little Ice Age (590-120 cal yr BP). The reconstructed precipitation and salinity exhibit a periodicity of ～200 years， which is consistent with the cycle of phase changes of the North Atlantic Oscillation (NAO) and Total Solar Irradiance (Tsi). This correlation suggests that variations in NOA and Tsi significantly influence the precipitation and salinity changes in Central Asia over centennial to millennial timescales.

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