短周期密集台阵深部地壳结构探测研究进展

由于穿透能力强,天然地震接收函数成为壳幔结构探测中最为广泛使用的方法.随着人们对地球内部结构和动力学过程认识程度的提高,台间距相对较大的宽频带台阵已无法满足壳幔结构高分辨率探测的需求.短周期密集台阵采用频率较高的便携式数字地震仪,通过百米级台间距的密集观测,可在短时间内(1~2个月)获得大量地震数据.其优势主要表现在三个方面:(1)地壳内射线交叉覆盖好,有利于提高分辨率;(2)射线密集分布,通过相干叠加压制噪声,可实现高频接收函数的成像;(3)观测时间短,效率高.因此,短短几年内,短周期密集台阵已经成为地壳深部结构探测的常规手段之一.本文主要介绍短周期密集台阵深部地壳结构探测的由来,以及通过几个典型的探测实例,展示探测效果及其在不同构造域的应用.

骨科学领域组织透明化技术的应用与展望

背景:骨组织作为高度矿化且结构复杂的结缔组织,在维持生物体形态和功能中扮演关键角色,传统的成像技术难以满足对其深入观察的需求。组织透明化技术的出现使得研究者能够更加清晰地观察到骨内的细微结构,如骨小梁、骨髓腔以及与骨组织相互作用的神经和血管网络,为骨科学的研究和临床应用开辟了新的视角。目的:旨在全面梳理组织透明化技术在骨科学领域的应用,并探讨其在骨组织结构与功能研究、疾病机制解析以及治疗策略创新中的潜力,同时对其创新点进行展望。方法:检索覆盖中国知网和PubMed数据库,英文检索词为“tissue clearing,tissue optical,bone”等,中文检索词为“组织透明化、骨、骨缺损”等,结合布尔逻辑以优化检索策略。纳入与组织透明化技术和骨科学研究直接相关的期刊论文和学位论文,排除关联性不强、重复或数据不完整的文献。最终纳入82篇文献进行分析,关注点包括透明化技术的效能、应用范围及对骨科学研究的贡献。结果与结论:①组织透明化技术在骨结构分析、骨代谢研究、骨肿瘤的病理学特征、骨折愈合过程、骨感染的机制研究以及骨移植和植入物材料的生物相容性评价等多个领域均展现出其独特的应用优势;②该技术的应用不仅加速了骨科学领域的基础研究进展,也为临床治疗提供了新的策略和方法,其在骨科学研究领域具有广阔的应用前景。

From text to image:challenges in integrating vision into ChatGPT for medical image interpretation

Large language models(LLMs),such as ChatGPT developed by OpenAI,represent a significant advancement in artificial intelligence(AI),designed to understand,generate,and interpret human language by analyzing extensive text data.Their potential integration into clinical settings offers a promising avenue that could transform clinical diagnosis and decision-making processes in the future(Thirunavukarasu et al.,2023).This article aims to provide an in-depth analysis of LLMs’current and potential impact on clinical practices.Their ability to generate differential diagnosis lists underscores their potential as invaluable tools in medical practice and education(Hirosawa et al.,2023;Koga et al.,2023).

Advancement in utilization of magnetic resonance imaging and biomarkers in the understanding of schizophrenia

Historically,psychiatric diagnoses have been made based on patient’s reported symptoms applying the criteria from diagnostic and statistical manual of mental disorders.The utilization of neuroimaging or biomarkers to make the diagnosis and manage psychiatric disorders remains a distant goal.There have been several studies that examine brain imaging in psychiatric disorders,but more work is needed to elucidate the complexities of the human brain.In this editorial,we examine two articles by Xu et al and Stoyanov et al,that show developments in the direction of using neuroimaging to examine the brains of people with schizo-phrenia and depression.Xu et al used magnetic resonance imaging to examine the brain structure of patients with schizophrenia,in addition to examining neurotransmitter levels as biomarkers.Stoyanov et al used functional magnetic resonance imaging to look at modulation of different neural circuits by diagnostic-specific scales in patients with schizophrenia and depression.These two studies provide crucial evidence in advancing our understanding of the brain in prevalent psychiatric disorders.

Multilocular thymic cysts-a diagnostic challenge on computed tomography

A recent case report provided a patient scenario,wherein,a 39-year-old male patient presented with occasional palpitations,headache,and fever.Evaluation of tumor markers did not show any abnormal results.Subsequently,a computed tomography(CT)scan was undertaken,and its findings were affirmative of thymic cancer.Finally,the postoperative histopathological assessment of the mass,after its resection,confirmed it as an anterior mediastinal multilocular thymic cyst(MTC),with concurrent acute upper respiratory tract infection and acute myocarditis.Accordingly,this case report advocates the need for a preoperative histopathological examination with CT imaging to minimize the risk of confusing an MTC with a malignant thymic tumor.

Recognition and quality mapping of traditional herbal drugs:way forward towards artificial intelligence

The use of traditional herbal drugs derived from natural sources is on the rise due to their minimal side effects and numerous health benefits.However,a major limitation is the lack of standardized knowledge for identifying and mapping the quality of these herbal medicines.This article aims to provide practical insights into the application of artificial intelligence for quality-based commercialization of raw herbal drugs.It focuses on feature extraction methods,image processing techniques,and the preparation of herbal images for compatibility with machine learning models.The article discusses commonly used image processing tools such as normalization,slicing,cropping,and augmentation to prepare images for artificial intelligence-based models.It also provides an overview of global herbal image databases and the models employed for herbal plant/drug identification.Readers will gain a comprehensive understanding of the potential application of various machine learning models,including artificial neural networks and convolutional neural networks.The article delves into suitable validation parameters like true positive rates,accuracy,precision,and more for the development of artificial intelligence-based identification and authentication techniques for herbal drugs.This article offers valuable insights and a conclusive platform for the further exploration of artificial intelligence in the field of herbal drugs,paving the way for smarter identification and authentication methods.

A new horizon for neuroscience:terahertz biotechnology in brain research

Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences.In this article,we review the development of terahertz biotechnology and its applications in the field of neuropsychiatry.Available evidence indicates promising prospects for the use of terahertz spectroscopy and terahertz imaging techniques in the diagnosis of amyloid disease,cerebrovascular disease,glioma,psychiatric disease,traumatic brain injury,and myelin deficit.In vitro and animal experiments have also demonstrated the potential therapeutic value of terahertz technology in some neuropsychiatric diseases.Although the precise underlying mechanism of the interactions between terahertz electromagnetic waves and the biosystem is not yet fully understood,the research progress in this field shows great potential for biomedical noninvasive diagnostic and therapeutic applications.However,the biosafety of terahertz radiation requires further exploration regarding its two-sided efficacy in practical applications.This review demonstrates that terahertz biotechnology has the potential to be a promising method in the field of neuropsychiatry based on its unique advantages.

A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis

To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.

Temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries on magnetic resonance imaging

Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in~1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability.Detailed assessment is important to help identify highrisk infants,to help families,and to support appropriate interventions.A wide range of monitoring tools is available to assess changes over time,including urine and blood biomarkers,neurological examination,and electroencephalography.At present,magnetic resonance imaging is unique as although it is expensive and not suited to monitoring the early evolution of hypoxic-ischemic encephalopathy by a week of life it can provide direct insight into the anatomical changes in the brain after hypoxic-ischemic encephalopathy and so offers strong prognostic information on the long-term outcome after hypoxic-ischemic encephalopathy.This review investigated the temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries,with a particular emphasis on exploring the correlation between the prognostic implications of magnetic resonance imaging scans in the first week of life and their relationship to long-term outcome prediction,particularly for infants treated with therapeutic hypothermia.A comprehensive literature search,from 2016 to 2024,identified 20 pertinent articles.This review highlights that while the optimal timing of magnetic resonance imaging scans is not clear,overall,it suggests that magnetic resonance imaging within the first week of life provides strong prognostic accuracy.Many challenges limit the timing consistency,particularly the need for intensive care and clinical monitoring.Conversely,although most reports examined the prognostic value of scans taken between 4 and 10 days after birth,there is evidence from small numbers of cases that,at times,brain injury may continue to evolve for weeks after birth.This suggests that in the future it will be important to explore a wider range of times after hypoxic-ischemic encephalopathy to fully understand the optimal timing for predicting long-term outcomes.

Radiomics and molecular analysis:Bridging the gap for predicting hepatocellular carcinoma prognosis

This editorial examines a recent study that used radiomics based on computed tomography(CT)to predict the expression of the fibroblast-related gene enhancer of zeste homolog 2(EZH2)and its correlation with the survival of patients with hepatocellular carcinoma(HCC).By integrating radiomics with molecular analysis,the study presented a strategy for accurately predicting the expression of EZH2 from CT scans.The findings demonstrated a strong link between the radiomics model,EZH2 expression,and patient prognosis.This noninvasive approach provides valuable insights into the therapeutic management of HCC.

Magnetic resonance imaging evaluation and nuclear receptor binding SET domain protein 1 mutation in the Sotos syndrome with attention-deficit/hyperactivity disorder

Sotos syndrome is characterized by overgrowth features and is caused by alterations in the nuclear receptor binding SET domain protein 1 gene.Attentiondeficit/hyperactivity disorder(ADHD)is considered a neurodevelopment and psychiatric disorder in childhood.Genetic characteristics and clinical presentation could play an important role in the diagnosis of Sotos syndrome and ADHD.Magnetic resonance imaging(MRI)has been used to assess medical images in Sotos syndrome and ADHD.The images process is considered to display in MRI while wavelet fusion has been used to integrate distinct images for achieving more complete information in single image in this editorial.In the future,genetic mechanisms and artificial intelligence related to medical images could be used in the clinical diagnosis of Sotos syndrome and ADHD.

Multisensory mechanisms of gait and balance in Parkinson’s disease:an integrative review

Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.

基于CT影像儿童枢椎正常发育与变异的解剖特征

背景:枢椎发育演变过程复杂,研究报道较少。CT成像可以显示枢椎的正常发育过程、解剖结构、发育变异与畸形,明确枢椎骨化中心出现与骺板闭合时间及其演变过程和规律具有重要的临床价值。目的:基于CT影像展示儿童枢椎正常发育与变异的解剖结构。方法:回顾性分析2016年6月至2019年11月行颈部扫描的732例0-15岁儿童CT图像。观察指标包括枢椎齿状突、双侧椎弓、椎体骨化中心,齿突尖部二次骨化中心,椎弓、齿突基底部及后正中骺板,以及枢椎发育变异或畸形。分析与比较各项指标在不同年龄下的变化情况,并利用SPSS 17.0统计学软件包进行数据分类处理及统计学分析。结果与结论:(1)732例研究对象包括枢椎正常发育718例(98.1%),畸形或发育异常14例(1.9%);(2)枢椎5个骨化中心,其中双侧椎弓及齿突、椎体骨化中心在出生时已出现;齿突尖部二次骨化中心出现的中位年龄是5.7岁,年龄四分位差(IQR)是4.1-7岁,最早出现的为8个月22 d,最迟未出现的为12岁10个月;(3)齿突尖骺板融合的中位年龄是6岁,IQR是5-8岁,未融合最大年龄是8岁9个月,融合的最小年龄是4岁3个月;(4)双侧椎弓骺板闭合的中位年龄约3.8岁,IQR约2.9-4.6岁,闭合的最小年龄是2岁3个月,未闭合的最大年龄是6岁;(5)齿突基底部骺板闭合的中位数5.2岁,IQR为3.5-6.8岁,闭合最小年龄是2岁6个月,最晚未闭合年龄是9岁6个月;(6)后正中骺板闭合年龄中位数为1.5岁,IQR为1.0-2.1岁,最晚未闭合2例分别为2岁5个月、14岁,最早闭合为6个月20 d;(7)枢椎畸形或发育异常,包括出现副骨化中心及副骺板7例、枢椎游离骨化小骨3例、后正中骺板不闭合2例、无齿突尖部二次骨化中心2例及枢椎齿突骨化中心未出现1例;(8)提示多层螺旋CT扫描、结合多平面重组技术可以完整显示枢椎的解剖结构,评估其正常发育变异及畸形。

Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

Persistent alterations in gray matter in COVID-19 patients experiencing sleep disturbances:a 3-month longitudinal study

Sleep disturbances are among the most prevalent neuropsychiatric symptoms in individuals who have recovered from severe acute respiratory syndrome coronavirus 2 infections.Previous studies have demonstrated abnormal brain structures in patients with sleep disturbances who have recovered from coronavirus disease 2019(COVID-19).However,neuroimaging studies on sleep disturbances caused by COVID-19 are scarce,and existing studies have primarily focused on the long-term effects of the virus,with minimal acute phase data.As a result,little is known about the pathophysiology of sleep disturbances in the acute phase of COVID-19.To address this issue,we designed a longitudinal study to investigate whether alterations in brain structure occur during the acute phase of infection,and verified the results using 3-month follow-up data.A total of 26 COVID-19 patients with sleep disturbances(aged 51.5±13.57 years,8 women and 18 men),27 COVID-19 patients without sleep disturbances(aged 47.33±15.98 years,9 women and 18 men),and 31 age-and gender-matched healthy controls(aged 49.19±17.51 years,9 women and 22 men)were included in this study.Eleven COVID-19 patients with sleep disturbances were included in a longitudinal analysis.We found that COVID-19 patients with sleep disturbances exhibited brain structural changes in almost all brain lobes.The cortical thicknesses of the left pars opercularis and left precuneus were significantly negatively correlated with Pittsburgh Sleep Quality Index scores.Additionally,we observed changes in the volume of the hippocampus and its subfield regions in COVID-19 patients compared with the healthy controls.The 3-month follow-up data revealed indices of altered cerebral structure(cortical thickness,cortical grey matter volume,and cortical surface area)in the frontal-parietal cortex compared with the baseline in COVID-19 patients with sleep disturbances.Our findings indicate that the sleep disturbances patients had altered morphology in the cortical and hippocampal structures during the acute phase of infection and persistent changes in cortical regions at 3 months post-infection.These data improve our understanding of the pathophysiology of sleep disturbances caused by COVID-19.

基于图像处理技术的棚室番茄果实识别

我国番茄的产量居世界前列,种植的主要方式为棚室种植,大多采用人工采摘,成本高、效率低,不利于种植产业的发展。为此,提出了一种基于A-ENet模型的图像处理技术,用于棚室番茄果实的识别。A-ENet模型在EfficientNet运行时引入注意力机制,用于优化深度网络运算结果。EfficientNet通过调整、完善网络的宽度、深度等网络参数提升网络的识别准确率,同时在网络提取输入信号特征时引入注意力机制用于捕捉输入信号特征的权重信息,主动忽略环境因素对目标信号的干扰。A-ENet模型能够解决由于识别目标之间的细微差异产生的识别错误的问题,且能够减少随机环境因素对识别过程的干扰,提高识别成功率,对棚室番茄果实识别问题起到积极的影响作用。实验结果表明:所提出的基于图像处理技术的A-ENet模型能够构建出效率更高、鲁棒性更强的目标识别系统。

深度学习在口腔影像分析中的应用

背景:近年来深度学习技术越来越多地被运用于口腔医学领域,提高了口腔影像分析的效率及准确率,推动了口腔智能医学的迅速发展。目的:基于口腔影像,阐述深度学习在口腔疾病诊断和治疗方案决策方面的研究现状、优势与局限性,探讨深度学习技术背景下口腔医学变革的新方向。方法:应用计算机检索PubMed数据库中2017年1月至2024年1月发表的深度学习在口腔医学影像领域应用的相关文献,检索词为“deep learning,artificial intelligence,stomatology,oral medical imaging”等,按入组标准筛选后最终纳入80篇文献进行综述。结果与结论:(1)经典的深度学习模型包括人工神经网络、卷积神经网络、递归神经网络和生成对抗网络等,学者们以或竞争或联合的形式运用这些模型,实现更高效的对口腔医学影像的解释。(2)在口腔医学领域,疾病诊断和治疗方案的制定在很大程度上依赖医学影像资料的判读,而深度学习技术拥有强大的图像处理能力,无论是在辅助诊断龋齿、根尖周炎、牙根纵裂、牙周病、颌骨囊肿等疾病方面,还是在辅助第三磨牙拔除术、颈淋巴结清扫术等治疗操作的术前评估方面,深度学习都能帮助临床医生提高决策的准确率与效率。(3)尽管深度学习有望成为口腔疾病诊治的重要辅助工具,但它在模型技术、安全伦理、法律监管方面仍有一定的局限性,未来的研究应侧重于证明深度学习的可推广性、稳健性和临床实用性,寻找将深度学习自动化决策支持系统应用于常规临床工作流程中的最佳方式。

北宋定窑茶叶末釉的微观结构与矿物形态学研究

茶叶末釉古瓷作为最早出现的结晶釉之一,开展深入研究可明确其矿物晶体特征、呈色机理以及古代烧制工艺,丰富古陶瓷数据库。目前相关研究多来源于二十世纪末,样本稀少且囊括的年代和窑口严重不足,所用科学仪器多已淘汰,亟需更多实验分析与数据支撑。本文采用光学显微镜(OM)、激光剥蚀电感耦合等离子体质谱(LA-ICP-MS)、扫描电镜-能谱(SEM-EDS)、激光共聚焦拉曼光谱(LRS)、飞行时间二次离子质谱(ToF-SIMS)等现代科学仪器对北宋定窑茶叶末釉样本中矿物晶体开展了分析和表征。结果表明,釉中主晶相与辽金龙泉务窑一致,为钙长石和辉石;釉面整体表现为酱-黑色釉基质富铁(Fe2O3含量均值9.73%)和矿物结晶富铁(Fe2O3含量均值11.33%),除α-Fe2O3和Fe3O4晶体等熔后重结晶矿物,还有铁镁尖晶石、残余高岭石等未融熔矿物,反演出制釉原料中有镁的加入以及烧成温度可能低于1200℃,异于前人高温烧制的观点。SIMS离子成像揭示了胎釉交界处为厚约20~80μm的钙长石晶体层,而非化妆土或玻璃态的致密反应层。研究揭示了茶叶末古瓷中Fe元素不均匀富集,部分区域过饱和而析出含铁矿物晶体,釉面颜色则主要由黄褐色的矿物晶体斑点和酱-黑色玻璃基质共同组成,同时ToF-SIMS在古瓷微区原位的形貌结构和元素分析上效果显著,能够辨别钙长石、碱性长石等微米级矿物。

基于图像处理和BP神经网络的森林防火无人机系统

对无人机设计方案、图像处理和火焰分割算法的技术原理进行了介绍,并利用BP神经网络对图像中的火焰面积变化率和火焰尖角等特征进行识别,实现了对森林火灾的快速监测。实验结果表明:系统的准确率为98.5%,比普通神经网络的84.5%更高;耗时仅22 s,比普通神经网络159 s缩短很多。这表明,BP神经网络是更可靠且更有效率的火灾识别方案。

聚集诱导发光纳米探针在前列腺癌光热诊疗中的应用

背景:基于“分子内运动受限”这一机制构筑的新型聚集诱导发光荧光探针可用于疾病标志物的检测、肿瘤诊断、细菌成像识别等多个方面。目的:构建基于聚集诱导发光的近红外二区纳米探针FA-DSPE-PEG-AIE@NPs,探讨其用于前列腺癌靶向近红外二区荧光成像及光热治疗的潜能。方法:以卵磷脂、聚乙二醇磷脂、叶酸-聚乙二醇磷脂、聚集诱导发光分子2TT-oC26B为原料,采用纳米沉淀法合成叶酸靶向纳米探针FA-DSPE-PEG-AIE@NPs,对其进行基本表征。选取PC3人前列腺癌细胞、人脐静脉内皮细胞为实验对象,检测纳米探针FA-DSPE-PEG-AIE@NPs的细胞毒性与光照毒性;选取PC3人前列腺癌细胞为实验对象,采用流式细胞术和钙黄绿素/碘化丙啶染色法检测该纳米探针的光热治疗效果。选取BALB/C裸鼠腹部皮下注射PC3人前列腺癌细胞建立肿瘤模型,尾静脉注射纳米探针FA-DSPE-PEG-AIE@NPs后立即对小鼠进行近红外二区荧光成像,12 h后激光照射肿瘤5 min,14 d内观察光热治疗效果。结果与结论:①纳米探针FA-DSPE-PEG-AIE@NPs呈球形,平均粒径(171.0±0.3)nm,具有广谱光吸收能力和延伸至近红外二区的尾部发射,在激光辐照下可发出明亮的近红外二区荧光信号;②纳米探针FA-DSPE-PEG-AIE@NPs的细胞毒性低、光毒性高;流式细胞术及钙黄绿素/碘化丙啶染色法显示,纳米探针FA-DSPE-PEG-AIE@NPs对PC3人前列腺癌细胞具有明显的光热杀伤效果;③纳米探针FA-DSPE-PEG-AIE@NPs成功实现了对活体小鼠血管的近红外二区荧光成像,并确认了在肿瘤部位的最大富集时间为12 h,估算后肢腿部及腹部单根血管的血管宽度分别为0.63 mm和0.42 mm,治疗后14 d小鼠肿瘤体积明显减小;④结果表明,纳米探针FA-DSPE-PEG-AIE@NPs能有效实现前列腺癌的近红外二区荧光成像及光热治疗,有望为前列腺癌的早期诊断及联合治疗提供新手段。