Human Platelet Membrane Functionalized Microchips with Plasmonic Codes for Cancer Detection

The possibility of functional roles played by platelets in close alliance with cancer cells has inspired the design of new biomimetic systems that exploit platelet–cancer cell interactions. Here, the role of platelets in cancer diagnostics is leveraged to design a microfluidic platform capable of detecting cancer‐derived extracellular vesicles (EVs) from ultrasmall volumes (1 µL) of human plasma samples. Further, the captured EVs are counted by direct optical coding of plasmonic nanoprobes modified with EV‐specific antibodies. Owing to the inherent properties of platelets for multifaceted interaction with cancer cells, the microfluidic chip equipped with a biologically interfaced platelet membrane‐cloaked surface (denoted “PLT‐Chip”) can capture a significantly higher number of EVs from multiple types of cancer cell lines (prostate, lung, bladder, and breast) than the normal cell‐derived EVs. Furthermore, this chip allows the monitoring of the growth of tumor spheroids (100 µm–2.5 mm) and clearly distinguishes the plasma of cancer patients from that of normal healthy controls. This robust, multifaceted, and cancer‐specific binding affinity, coupled with excellent biocompatibility, is a unique feature of platelet membrane‐cloaked surfaces, which therefore represent promising alternatives to antibodies for application in EVs‐based cancer theranostics.     

High Strength Conductive Composites with Plasmonic Nanoparticles Aligned on Aramid Nanofibers

Rapidly evolving fields of biomedical, energy, and (opto)electronic devices bring forward the need for deformable conductors with constantly rising benchmarks for mechanical properties and electronic conductivity. The search for conductors with improved strength and strain have inspired the multiple studies of nanocomposites and amorphous metals. However, finding conductors that defy the boundaries of classical materials and exhibit simultaneously high strength, toughness, and fast charge transport while enabling their scalable production, remains a difficult materials engineering challenge. Here, composites made from aramid nanofibers (ANFs) and gold nanoparticles (Au NPs) that offer a new toolset for engineering high strength flexible conductors are described. ANFs are derived from Kevlar macrofibers and retain their strong mechanical properties and temperature resilience. Au NPs are infiltrated into a porous, free‐standing aramid matrix, becoming aligned on ANFs, which reduces the charge percolation threshold and facilitates charge transport. Further thermal annealing at 300 °C results in the Au‐ANF composites with an electrical conductivity of 1.25 × 10⁴ S cm^?1 combined with a tensile strength of 96 MPa, a Young's modulus of 5.29 GPa, and a toughness of 1.3 MJ m^?3. These parameters exceed those of most of the composite materials, and are comparable to those of amorphous metals but have no volume limitations. The plasmonic optical frequencies characteristic for constituent NPs are present in the composites with ANFs enabling plasmon‐based optoelectronic applications.     

金蒸气激光光敏疗法治疗膀胱癌的临床研究

报道经多种治疗后再生的膀胱癌患者７０例，共３１６个肿瘤，用光纤输出功率２Ｗ，带有球型弥散刀头石英光纤传输的金蒸气激光，通过膀胱镜作肿瘤及全膀胱血卟啉光敏治疗，经６～４６个月的随访，痊愈５４例，占７７．１４％，显效１２例占１７．１４％，好转４例，占５．７％，再生８例，占１１．４３％。     

Bioinspired Tumor Calcification Enables Early Detection and Elimination of Lung Cancer

Precise diagnosis of cancer in an early stage and treatments with a reliable response, high selectivity, and negligible side effects is urgently needed. However, current cancer management involves low-resolution metrics and delayed visual confirmation of tumor foci in imaging findings, and the toxicity of chemo- and radiotherapy unavoidably damages normal tissue and disrupts the immune balance of cancer patients. Here, a polypeptide is synthesized that preferentially targets lung cancer cells rather than normal lung epithelial cells and induces calcium precipitation specifically on the plasma membrane of lung cancer cells without additional supplementary calcium. Polypeptide-induced cellular calcification can ideally facilitate medical imaging for identifying early-stage lung cancer and distinguish cancer from benign nodules. Physiological and spontaneous calcification of tumors is induced by polypeptides and sharply prolongs the survival of tumor-bearing mice without evidence of systemic side effects. This tumor cell-selective calcification process provides an attractive, safe, and unprecedented approach for accurately visualizing and treating cancer in patients with early-stage disease in the clinic. It has broad implications in developing simple physiological reactions for diagnosing and treating cancer and provides a new horizon for drug discovery.     

一种基于CT影像的肺癌病灶检测新方法

 肺癌病灶的检测一直是重要与困难的工作,本文提出了一种基于三维CT影像的肺结节计算机辅助检测新方法.基于自适应阈值等方法分割肺实质区域;由于肺血管是肺结节检测的重要干扰,建立一种形变模型精确分割并过滤肺内血管组织;基于Hessian矩阵特征值构造可选择形状滤波器检测疑似结节,并进一步过滤剩余的细小血管组织;提取多个结节特征,并采用基于规则分类器进行分类.实验结果表明,该方法可以有效帮助医生提高肺癌疾病的诊断准确率.     

肺癌组织红外光谱的统计分析

使用统计的方法,应用傅里叶变换红外光谱法对肺癌及癌旁正常组织粉末样品的红外光谱进行了统计分析.结果表明,肺癌组织和癌旁正常组织的红外光谱有显著的差异性:3306cm-1处的N-H峰在肺癌组织中向低频移动了约3cm-1;1167cm-1处的C-OH伸缩振动谱带在肺癌组织中向高波数移动约6cm-1;1080cm-l处的PO-2对称伸缩振动谱带在肺癌组织中向高波数移动约4cm-1.体现了在肺癌组织中细胞形态和组织结构发生的变化,说明傅里叶变换红外光谱法可以用于对良、恶性肺部组织鉴别诊断.     

肺癌组织的红外光谱研究

应用傅里叶变换红外光谱法对肺癌及癌旁正常组织粉末样品进行了分析,结果表明, 肺癌组织和癌旁正常组织的红外光谱表现出较大的差异性: N2H峰在肺癌组织中向低波数频移, 1536cm- 1处蛋白质酰胺Ⅱ带与1169cm- 1处蛋白质分子C2OH伸缩振动谱带在肺癌组织中向高波数频移; CH2 和CH3 的相对强度比值I2854 / I2872及I2929 / I2959在正常组织中的比值要比肺癌组织中的比值明显减小;肺癌组织中核酸分子磷酸二脂基团PO2- 的对称伸缩振动的相对吸收强度明显增强;正常组织中脂类分子弯曲振动谱带吸收峰相对强度明显强于甲基变角振动谱带的相对强度,而在肺癌组织中这两处吸收峰的相对强度大小基本相等。说明傅里叶变换红外光谱法可用于对良、恶性肺部组织进行鉴别诊断,有希望发展成为肺癌快速诊断的一种新方法。     

新型肺癌压电DNA传感器的研制

在压电石英金电极上自组装半胱胺膜,通过1-乙基-3-(3-甲基氨丙基)碳二亚胺盐酸盐和N-羟基琥珀酰亚胺活化的羧基化碳纳米管交联半胱胺和DNA探针,构建新的压电DNA传感器,实现对肺癌特征DNA的压电检测。该传感器检测灵敏度为27.617Hz/(μg/mL),线性范围为0.02～7.50μg/mL,再生性能好。样本分析结果与聚合酶链式反应(PCR)法无显著差异,可用于临床检测。     

Novel Insights into Combating Cancer Chemotherapy Resistance Using a Plasmonic Nanocarrier: Enhancing Drug Sensitiveness and Accumulation Simultaneously with Localized Mild Photothermal Stimulus of Femtosecond Pulsed Laser

Chemotherapy resistance remains a large obstacle to successful clinical cancer therapy, mainly due to little accumulation and low sensitivity of drugs and the effective clinical strategy still lacks. Herein, a novel yet simple strategy to combat cancer drug resistance using the plasmonic feature‐based photothermal properties is reported. Rather than directly killing cancer cells using nanoparticle‐mediated hyperthermia, for the first time, localized plasmonic heating of gold nanorod at a mild laser power density can modulate the drug‐resistance related genes. This photothermal effect triggers higher expression of heat shock factor (HSF‐1) trimers and depresses the expression of P‐glycoprotein (Pgp) and mutant p53. In turn, both drug accumulation in the breast cancer resistant cells (MCF‐7/ADR) and their sensitiveness to drugs can be greatly enhanced. Considering the universality and feasibility of this strategy, it points out a new unique way to challenge drug resistance.     

Advanced Functional Structure‐Based Sensing and Imaging Strategies for Cancer Detection: Possibilities,Opportunities, Challenges,and Prospects

Cancer is the second most common cause of death in the world. The principal limitations thus far encountered in the clinical practice of probing cancer are diverse and include low sensitivity, time consumption, bulkiness, and cost. In this respect, nanomaterial (NM)‐based sensing techniques are recognized as a superior alternative to efficiently resolve such limitations. A better understanding of NM‐based sensing platforms is thus important so that these novel avenues can easily be explored for clinical applications. These platforms have the merits of high sensitivity, high specificity, rapid response, and easy‐to‐read signals. This review offers a comprehensive survey of NM‐based advanced cancer‐sensing techniques and will help the scientific community establish optimum sensing strategies based on an accurate assessment of the interactions between cancer biomarkers and NM‐based platforms.     

基于模式识别方法的肺癌分型比较

根据不同特征对分型准确率的影响,使用Logistic回归分析进行特征选择及优选实验研究,并采用神经网络和支持向量机方法对常见的周围型肺癌进行分型比较。通过实验,说明了神经网络和支持向量机在肺癌分型的应用方法,比较了两种模式识别方法在肺癌分型中的运用情况,验证了支持向量机在小样本情况下比神经网络具有更强的泛化能力。     

基于虚拟气体传感器阵列的肺癌检测电子鼻

提出了一种无创电子鼻诊断肺癌的新方法。该方法结合虚拟声表面波(SAW)传感器阵列的概念和图像识别方法,对肺癌病人、正常人和老慢支病人的呼出气体进行了检测,确定11种挥发性有机成分(VOCs)为肺癌特征气体。此外,在细胞水平上进行研究,证明了肺癌细胞培养液中存在的特征性VOCs是肺癌细胞新陈代谢的产物,可以作为判定特定肺癌细胞的依据,为确定肺癌病人呼吸中的特征性气体提供病理根据。     

基于虚拟气体传感器阵列的肺癌检测电子鼻

提出了一种无创电子鼻诊断肺癌的新方法。该方法结合虚拟声表面波（SAW）传感器阵列的概念和图像识别方法，对肺癌病人、正常人和老慢支病人的呼出气体进行了检测，确定11种挥发性有机成分（VOCs）为肺癌特征气体。此外，在细胞水平上进行研究，证明了肺癌细胞培养液中存在的特征性VOCs是肺癌细胞新陈代谢的产物，可以作为判定特定肺癌细胞的依据，为确定肺癌病人呼吸中的特征性气体提供病理根据。     

基于CT影像组学的非小细胞肺癌预后分析方法

为了辅助医生规划非小细胞肺癌（Non-Small Cell Lung Cancer,NSCLC）患者治疗和复查方案,提出了一种基于CT影像组学的NSCLC预后分析方法.首先,对患者肺部CT影像中的肿瘤区域进行分割;然后,对肿瘤区域进行影像组学特征提取、优化;最后,将优化后的特征数据与患者的预后生存情况作为输入,利用机器学习的方法构建预后分析模型,预测患者的预后生存时间范围.选用124例NSCLC患者数据进行实验,以具有临床意义的3年生存期为预测界限,对患者预后生存时间范围进行预测.实验结果表明,预后分析模型的预测准确率达到91.9%,可以有效地辅助医生对非小细胞肺癌患者的预后情况进行更加精准的评估,制定出更具个性化的治疗与复查方案.     

基于胸部CT图像的肺癌识别方法的研究

 针对医学影像中小结节容易被漏诊的问题,提出了基于胸部CT图像的肺癌计算机辅助诊断新方法.首先从胸部CT图像分割出关心区域(ROI);然后提取ROI的特征;其次采用RS理论选择有效特征;最后基于这些有效特征建立面向不同需求的肺癌识别模型.即如果需要快速诊断,则利用SONN建立肺癌识别模型;如果需要进行准确诊断,则利用SPAM建立肺癌识别模型和非肺癌识别模型,并根据待识别样本与模型的相似度判断所属类别.但是当相似度较小时,则利用HMM进一步识别.通过实验验证了该方法的有效性.     

利用跨模态轻量级YOLOv5模型的PET/CT肺部肿瘤检测

多模态医学图像可在同一病灶处提供更多语义信息,针对跨模态语义相关性未充分考虑和模型复杂度过高的问题,该文提出基于跨模态轻量级YOLOv5(CL-YOLOv5)的肺部肿瘤检测模型。首先,提出学习正电子发射型断层显像(PET)、 计算机断层扫描(CT)和PET/CT不同模态语义信息的3分支网络;然后,设计跨模态交互式增强块充分学习多模态语义相关性,余弦重加权计算Transformer高效学习全局特征关系,交互式增强网络提取病灶的能力;最后,提出双分支轻量块, 激活函数簇(ACON)瓶颈结构降低参数同时增加网络深度和鲁棒性,另一分支为密集连接的递进重参卷积,特征传递达到最大化,递进空间交互高效地学习多模态特征。在肺部肿瘤PET/CT多模态数据集中,该文模型获得94.76% mAP最优性能和3238 s最高效率,以及0.81 M参数量,较YOLOv5s和EfficientDet-d0降低7.7倍和5.3倍,多模态对比实验中总体上优于现有的先进方法,消融实验和热力图可视化进一步验证。     

Lung‐Endothelium‐Targeted Nanoparticles Based on a pH‐Sensitive Lipid and the GALA Peptide Enable Robust Gene Silencing and the Regression of Metastatic Lung Cancer

The development of efficient gene delivery systems targeting the lung endothelium remains a serious challenge. This study reports on the design and optimization of a multifunctional envelope‐type nanodevice (MEND) for an efficient siRNA delivery to the lung endothelium based on GALA‐peptide targeting ability. The incorporation of a pH‐sensitive lipid (YSK05) results in a dramatic improvement in silencing efficiency by enhancing endosomal escape, but this also causes a reduction in the lung selectivity. Contrary to the assumption that active targeting is largely dependent on the presence of a targeting ligand, the findings of the present study indicate that nanocarrier composition is critical for achieving the organ selectivity. Interestingly, helper lipids substantially mask the liver delivery resulting in optimum lung targeting. The optimized YSK05‐MEND is 40‐fold more efficient than a previously developed MEND, with a robust lung endothelium gene knockdown at small doses. The YSK05‐MEND strongly inhibits a metastatic lung cancer model and exerts superior control over lung metastasis compared to chemotherapy or the previously developed MEND. The YSK05‐MEND is well‐tolerated in mice after acute or chronic administration. As far as it is known, YSK05‐MEND achieves the most efficient lung endothelium gene silencing reported thus far with a median effective dose of 0.01 mg siRNA kg^?1 while minimally affecting the endothelium of other organs.