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Blood diagnostic and prognostic biomarkers in amyotrophic lateral sclerosis

Neural Regeneration Research 2025年第9期20卷 2556-2570页

作者： Yongting Lv Hongfu li Department of Neurology Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang ProvinceChina Department of Medical Genetics and Center for Rare disease Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang ProvinceChina Nanhu Brain-Computer Interface Institute HangzhouZhejiang Province

Amyotrophic lateral sclerosis is a devastating neurodegenerative disease for which the current treatment approaches remain severely *** principal pathological alterations of the disease include the selective degeneration of motor neurons in the brain,brainstem,and spinal cord,as well as abnormal protein deposition in the cytoplasm of neurons and glial *** biological markers under extensive scrutiny are predominantly located in the cerebrospinal fluid,blood,and even *** these biomarke rs,neurofilament proteins and glial fibrillary acidic protein most accurately reflect the pathologic changes in the central nervous system,while creatinine and creatine kinase mainly indicate pathological alterations in the peripheral nerves and *** light chain levels serve as an indicator of neuronal axonal injury that remain stable throughout disease progression and are a promising diagnostic and prognostic biomarker with high specificity and ***,there are challenges in using neurofilament light chain to diffe rentiate amyotrophic lateral sclerosis from other central nervous system diseases with axonal *** fibrillary acidic protein predominantly reflects the degree of neuronal demyelination and is linked to non-motor symptoms of amyotrophic lateral sclerosis such as cognitive impairment,oxygen saturation,and the glomerular filtration *** DNA-binding protein 43,a pathological protein associated with amyotrophic lateral sclerosis,is emerging as a promising biomarker,particularly with advancements in exosome-related *** is currently lacking for the value of creatinine and creatine kinase as diagnostic markers;however,they show potential in predicting disease *** the vigorous progress made in the identification of amyotrophic lateral sclerosis biomarkers in recent years,the quest for definitive diagnostic and prognostic biomarke rs remains a formidable *** review summarizes the lat

关键词： amyotrophic lateral sclerosis biomarker blood biomarkers diagnosis glial fibrillary acidic protein neurofilament light chain prognosis TAR DNA-binding protein 43

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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

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The Mechanism of Heating Rate on the Secondary Recrystallization Evolution in Grain Oriented Silicon Steel

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 275-282页

作者： GAO Qian li Jun WANG Xianhui CAO Laifu GONG Jian li Bo Central Iron and Steel Research Institute Group Beijing 100081China Shougang Zhixin Electromagnetic Material R&D(Beijing)Co. Ltd.Beijing 101300China Beijing Shougang Co. Ltd.Qian’an 064404China

Grain-oriented silicon steels were prepared at different heating rates during high temperature annealing,in which the evolution of magnetic properties,grain orientations and precipitates were *** illustrate the Zener factor,the diameter and number density of precipitates of interrupted testing samples were statistically *** effect of precipitate ripening on the Goss texture and magnetic property was *** indicated that the trend of Zener factor was similar under different heating rates,first increasing and then decreasing,and that the precipitate maturing was greatly inhibited as the heating rate *** recrystallization was developed at the temperature of 1010℃when a heating rate of 5℃/h was used,resulting in Goss,Brass and{110}oriented grains growing abnormally and a magnetic induction intensity of ***,increasing the heating rate to 20℃/h would inhibit the development of undesirable oriented grains and obtain a sharp Goss ***,when the heating rate was extremely fast,such as 40℃/h,poor secondary recrystallization was developed with many island grains,corresponding to a decrease in magnetic induction intensity to 1.87 *** a suitable heating rate of 20℃/h,the sharpest Goss texture and the highest magnetic induction of 1.94 T with an onset secondary recrystallization temperature of 1020℃were found among the experimental variables in this *** heating rate affected the initial temperature of secondary recrystallization by controlling the maturation of precipitates,leading to the deviation and dispersion of Goss texture,thereby reducing the magnetic properties.

关键词： high temperature annealing heating rate secondary recrystallization grain oriented silicon steel

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腹部推拿对内脏高敏感腹泻型肠易激综合征大鼠肠道肥大细胞、TRPV1的影响

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辽宁中医杂志 2024年第3期51卷 191-195,I0008页

作者：李华南王毓岩张小凡张玮马菲董桦王金贵天津中医药大学第一附属医院国家中医针灸临床医学研究中心天津300193 国家中医药管理局推拿手法生物效应三级实验室天津300193 天津市中医药研究院附属医院天津300120

目的观察腹部推拿对内脏高敏感腹泻型肠易激综合征(diarrhea-type irritable bowel syndrome,IBS-D)模型大鼠肠道肥大细胞(mastcell,MC)及TRPV1表达水平的影响,探讨腹部推拿调控内脏高敏感IBS-D作用机制。方法40只SD雄性大鼠随机分为空... 详细信息

目的观察腹部推拿对内脏高敏感腹泻型肠易激综合征(diarrhea-type irritable bowel syndrome,IBS-D)模型大鼠肠道肥大细胞(mastcell,MC)及TRPV1表达水平的影响,探讨腹部推拿调控内脏高敏感IBS-D作用机制。方法40只SD雄性大鼠随机分为空白组、模型组、腹部推拿组、MC阻断剂组,每组10只。采用母婴分离法+慢性应激法制备IBS-D大鼠模型。应用粪便性状(Bristol)评分、旷场试验评价干预效果,透射电镜观察结肠组织MC变化,定量PCR检测TRPV1 mRNA表达,免疫荧光法检测瞬时感受器电位香草酸亚型1(transient receptor potential vanilloid subfamily 1,TRPV1)阳性细胞数。结果(1)Bristol评分:与空白组比较,模型组Bristol评分增加(P<0.05);与模型组比较,腹部推拿组、MC阻断剂组评分降低(P<0.01)。(2)旷场试验:与空白组比较,模型组穿行方格次数、中央停留次数、中央停留时间和站立次数均显著减少(P<0.01);与模型组比较,腹部推拿组、MC阻断剂组各评分升高(P<0.05,P<0.01);与MC阻断剂组比较,腹部推拿组在站立次数方面低于MC阻断剂组(P<0.01)。(3)透射电镜:与空白组比较,模型组肠道MC微绒毛形态不规则,呈脱颗粒状态;腹部推拿组较模型组MC形态规整,脱颗粒程度不明显。MC阻断剂组形态规则与空白组近似。(4)TRPV1 mRNA表达:与空白组比较,模型组表达量明显升高(P<0.01);与模型组比较,腹部推拿组和MC阻断剂组表达量明显降低(P<0.01);与MC阻断剂组比较,腹部推拿组TRPV1 mRNA的表达略高(P<0.05)。(5)免疫荧光检测:与空白组比较,模型组TRPV1阳性细胞数显著增多,且荧光强度明显增高;与模型组比较,腹部推拿组和MC阻断剂组模型组TRPV1阳性细胞数显著减少,且荧光强度明显降低。结论腹部推拿可能借助调控肠道MC脱颗粒,降低TRPV1表达,从而对内脏高敏感IBS-D大鼠起到干预作用。

关键词：腹部推拿腹泻型肠易激综合征内脏高敏感作用机制

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Cell polarization in ischemic stroke: molecular mechanisms and advances

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Neural Regeneration Research 2025年第3期20卷 632-645页

作者： Yuanwei li Xiaoxiao Xu Xuan Wu Jiarui li Shiling Chen Danyang Chen Gaigai li Zhouping Tang Department of Neurology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei ProvinceChina

Ischemic stroke is a cerebrovascular disease associated with high mortality and disability rates. Since the inflammation and immune response play a central role in driving ischemic damage, it becomes essential to modulate excessive inflammatory reactions to promote cell survival and facilitate tissue repair around the injury site. Various cell types are involved in the inflammatory response, including microglia, astrocytes, and neutrophils, each exhibiting distinct phenotypic profiles upon stimulation. They display either proinflammatory or anti-inflammatory states, a phenomenon known as ‘cell polarization.’ There are two cell polarization therapy strategies. The first involves inducing cells into a neuroprotective phenotype in vitro, then reintroducing them autologously. The second approach utilizes small molecular substances to directly affect cells in vivo. In this review, we elucidate the polarization dynamics of the three reactive cell populations(microglia, astrocytes, and neutrophils) in the context of ischemic stroke, and provide a comprehensive summary of the molecular mechanisms involved in their phenotypic switching. By unraveling the complexity of cell polarization, we hope to offer insights for future research on neuroinflammation and novel therapeutic strategies for ischemic stroke.

关键词： astrocyte polarization immune regulation inflammation ischemic injury microglia polarization neutrophil polarization signaling pathways stroke

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An NIR-Ⅱ-emissive Ru(Ⅱ) metallacycle for efficient and safe immunotherapy

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Science China Chemistry 2025年第1期68卷 5-7页

作者： Chonglu li Jianbo Zhan Biao Dong Institute of Health Inspection and Testing Hubei Provincial Center for Disease Control and Prevention State Key Laboratory on Integrated Optoelectronics College of Electronic Science and Engineering Jilin University

Immunotherapy, as a groundbreaking cancer treatment, has gained considerable attention for its utilization of the body’s immune system to combat tumors [1]. This therapy induces tumor cell apoptosis, triggering a sustained anti-tumor immune response and effectively preventing tumor recurrence and metastasis [2]. The fundamental principle lies in inducing tumor cell death through specific treatment modalities, leading to the release of a cascade of signaling molecules and antigens, thereby mobilizing the immune system to actively identify and attack tumor cells [3].

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近5年推拿修复骨骼肌损伤的作用机制研究进展

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天津中医药 2024年第7期41卷 939-944页

作者：商蔚然李华南李进阳王金贵赵娜天津中医药大学第一附属医院国家中医针灸临床医学研究中心天津300193 天津中医药大学研究生院天津301617 国家中医药管理局推拿手法生物效应三级实验室天津300193

牵拉伤、钝挫伤以及失神经支配损伤等常见损伤都可以造成骨骼肌的损害,若修复不完全则容易形成瘢痕,影响肌肉功能。骨骼肌损伤在中医学中属于“筋伤”的范畴,推拿作为传统治疗筋伤病的重要方式之一,在治疗骨骼肌损伤中有广泛的应用。近... 详细信息

牵拉伤、钝挫伤以及失神经支配损伤等常见损伤都可以造成骨骼肌的损害,若修复不完全则容易形成瘢痕,影响肌肉功能。骨骼肌损伤在中医学中属于“筋伤”的范畴,推拿作为传统治疗筋伤病的重要方式之一,在治疗骨骼肌损伤中有广泛的应用。近些年逐渐开展了关于推拿修复骨骼肌损伤机制的研究,通过文献总结,发现推拿可通过磷脂酰肌醇激酶(PI3K)、丝裂原活化蛋白激酶(MAPK)、Notch、Wnt及过氧化物酶体增殖因子活化受体(PPAR)信号通路对骨骼肌的修复产生影响。推拿以肌卫星细胞为重点,通过促进如成肌调节因子(MRFs)、胰岛素样生长因子-1(IGF-1)、碱性成纤维细胞生长因子(bFGF)等正向调节因子的表达,抑制如转化生长因子-β(TGF-β)、生长分化因子-8(GDF-8)、结缔组织生长因子(CTGF)等负向调节因子的表达,以及下调肿瘤坏死因子-α(TNF-α)及白细胞介素-6(IL-6)等炎性因子的浓度,来发挥促进肌纤维重塑、防止细胞外基质过度沉积、减轻炎症反应以及减缓骨骼肌纤维化的作用。除此之外,推拿还可以通过促进细胞合理自噬、修复细胞膜、调节氧化应激及脂肪代谢等反应促进组织修复。本文聚焦于推拿修复骨骼肌损伤的机制,以期为进一步研究提供参考。

关键词：骨骼肌损伤推拿修复作用机制

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痛风清消颗粒急性毒性实验研究

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中国中医药现代远程教育 2017年第6期15卷 132-133页

作者：李华南陈浩顾兵王力涂宏邓运明江西中医药大学附属医院骨伤三科南昌330006 江西科技师范大学生命科学学院南昌330013

目的观察痛风清消颗粒的急性毒性反应,评价其临床用药的安全性。方法采用清洁级昆明种小鼠40只,随机分为2组,分别给予痛风清消颗粒混悬液和生理盐水0.78 ml/次灌胃,24小时内3次,连续观察小鼠的体重、饮食、毒性反应和死亡情况14天。结... 详细信息

目的观察痛风清消颗粒的急性毒性反应,评价其临床用药的安全性。方法采用清洁级昆明种小鼠40只,随机分为2组,分别给予痛风清消颗粒混悬液和生理盐水0.78 ml/次灌胃,24小时内3次,连续观察小鼠的体重、饮食、毒性反应和死亡情况14天。结果 2组小鼠在第1天、第7天和第14天的体重无显著性差异(P>0.05),小鼠一次性口服痛风清消颗粒的最大耐受量为86.88 g durg·kg-1,为成人每日临床常用量的253倍。结论痛风清消颗粒口服临床常用剂量安全。

关键词：痛风清消颗粒急性毒性实验最大耐受量中成药疗法痹证

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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

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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

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