Microfluidic‐Assisted Blade Coating of Compositional Libraries for Combinatorial Applications: The Case of Organic Photovoltaics

Microfluidic technologies are highly adept at generating controllable compositional gradients in fluids, a feature that has accelerated the understanding of the importance of chemical gradients in biological processes. That said, the development of versatile methods to generate controllable compositional gradients in the solid‐state has been far more elusive. The ability to produce such gradients would provide access to extensive compositional libraries, thus enabling the high‐throughput exploration of the parametric landscape of functional solids and devices in a resource‐, time‐, and cost‐efficient manner. Herein, the synergic integration of microfluidic technologies is reported with blade coating to enable the controlled formation of compositional lateral gradients in solution. Subsequently, the transformation of liquid‐based compositional gradients into solid‐state thin films using this method is demonstrated. To demonstrate efficacy of the approach, microfluidic‐assisted blade coating is used to optimize blending ratios in organic solar cells. Importantly, this novel technology can be easily extended to other solution processable systems that require the formation of solid‐state compositional lateral gradients.     

Efficient Exploration of the Composition Space in Ternary Organic Solar Cells by Combining High‐Throughput Material Libraries and Hyperspectral Imaging

Organic solar cells based on ternary active layers can lead to higher power conversion efficiencies than corresponding binaries, and improved stability. The parameter space for optimization of multicomponent systems is considerably more complex than that of binaries, due to both, a larger number of parameters (e.g., two relative compositions rather than one) and intricate morphology–property correlations. Most experimental reports to date reasonably limit themselves to a relatively narrow subset of compositions (e.g., the 1:1 donor/s:acceptor/s trajectory). This work advances a methodology that allows exploration of a large fraction of the ternary phase space employing only a few (<10) samples. Each sample is produced by a designed sequential deposition of the constituent inks, and results in compositions gradients with ≈5000 points/sample that cover about 15%–25% of the phase space. These effective ternary libraries are then colocally imaged by a combination of photovoltaic techniques (laser and white light photocurrent maps) and spectroscopic techniques (Raman, photoluminescence, absorption). The generality of the methodology is demonstrated by investigating three ternary systems, namely PBDB‐T:ITIC:PC₇₀BM, PTB7‐Th:ITIC:PC₇₀BM, and P3HT:O‐IDFBR:O‐IDTBR. Complex performance‐structure landscapes through the ternary diagram as well as the emergence of several performance maxima are discovered.     

用于可视化光治疗的Mn3O4@CuS纳米粒的制备研究

摘要 目的：本研究旨在制备用于肿瘤可视化光治疗的多功能Mn₃O₄@CuS核壳型纳米粒,在磁共振成像的引导下,使用近红外光定点辐照,实现局部光热消融治疗。方法：（1）采用高温热解法制备油胺稳定的Mn₃O₄纳米粒,在其表面构建CuS壳层,并进行聚乙二醇修饰,得到分散于水相中的Mn₃O₄@CuS核壳型纳米粒。（2）通过透射电镜、紫外可见近红外吸收光谱等方法对该纳米粒进行理化性质表征,并研究其体外磁共振成像、光热升温等性能。结果：制备的水相分散的Mn₃O₄@CuS纳米粒,粒径均一且分散性较好,形态为近圆形,粒径为9.30±2.29 nm;紫外可见近红外吸收光谱图表明Mn₃O₄@CuS纳米粒在近红外区有较强吸收,最大吸收峰位于1100~1200 nm范围;磁共振成像分析结果可计算出Mn₃O₄@CuS纳米粒的纵向弛豫率r1为1.662 mM^-1s^-1,表明其具有较好的磁共振增强造影效果;光热升温曲线显示Mn₃O₄@CuS纳米粒可在785 nm近红外激光下升温至73.5 ℃,具备较好的光热治疗潜力。结论：本文成功制备出水相分散的Mn₃O₄@CuS核壳型纳米粒,具有良好的磁共振造影成像性能和光热升温效应,有望应用于磁共振成像引导下的肿瘤可视化光治疗。     

CT与MRI扫描三维重建在四肢骨关节隐匿性骨折诊断中的应用

摘要 目的：探讨电子计算机断层扫描(Computed Tomography,CT)与磁共振成像(Magnetic resonance imaging,MRI)扫描三维重建在四肢骨关节隐匿性骨折诊断中的应用。方法：2016年9月到2019年10月选择在本院诊治的下拟诊为四肢骨关节隐匿性骨折118例,所有患者都给予CT与MRI扫描三维重建诊断,记录影像学特征与判断诊断价值。结果：在118例患者中,最终确诊为四肢骨关节隐匿性骨折98例,无骨折20例,其中腕关节骨折34例,踝关节骨折22例,膝关节骨折15例,肘关节骨折15例,肩关节骨折8例,髋关节骨折4例。在98例确诊的四肢骨关节隐匿性骨折中,MRI三维重建显示双边征、骨质破坏、充气征、软组织影等比例显著都高于CT (P<0.05)。CT与MRI三维重建诊断四肢骨关节隐匿性骨折的敏感性为89.8 %和99.0 %,特异性为95.0 %和100.0 %,误诊率分别为9.3 %和0.8 %,MRI三维重建诊断的敏感性高于CT ,漏诊率低于CT。结论：CT与MRI扫描三维重建在四肢骨关节隐匿性骨折诊断中的应用都有很好的价值,特别是MRI三维重建能清晰显示骨折特征,具有更高的诊断敏感性,能减少漏诊率,可作为四肢骨关节隐匿性骨折的首选检查方法。     

DCE-MRI联合DWI对直肠癌患者术前T、N分期及系膜淋巴结良恶性的诊断价值

摘要 目的：探讨动态对比增强磁共振(DCE-MRI)联合弥散加权成像（DWI）诊断直肠癌术前T、N分期和系膜淋巴结良恶性的价值。方法：收集2017年2月至2019年10月中国医科大学附属本溪中心医院和中国医科大学附属盛京医院接诊的80例直肠癌患者,均进行常规核磁共振成像（MRI）、DCE-MRI、DWI扫描,获得DCE-MRI、DWI定量参数[转运常数（K ^trans ）、细胞外血管外空间的体积分数（V _e ）、速率常数（K _ep ）、表观扩散系数(ADC)],比较不同T、N分期、不同性质系膜淋巴结DCE-MRI、DWI参数,及其对T、N分期和系膜淋巴结性质的诊断效能。结果：直肠癌癌灶K ^trans 、 K _ep 、V _e 高于正常肠壁,ADC低于正常肠壁（P＜0.05）。TNM分期为T_Ⅲ～Ⅳ期的患者K ^trans 、 K _ep 、V _e 高于T_Ⅰ～Ⅱ期,ADC低于T_Ⅰ～Ⅱ期（P＜0.05）;TNM分期为N₁期的患者K ^trans 、K _ep 、V _e 高于N₀期,ADC低于N₀期（P＜0.05）。联合诊断的灵敏度、特异度、阳性预测值、阴性预测值较高。结论：DCE-MRI联合DWI对直肠癌术前T、N分期、系膜淋巴结性质诊断价值较高。     

ToolBox: Live Imaging of intracellular organelle transport in induced pluripotent stem cell‐derived neurons

Induced pluripotent stem cells (iPSCs) hold promise to revolutionize studies of intracellular transport in live human neurons and to shed new light on the role of dysfunctional transport in neurodegenerative disorders. Here, we describe an approach for live imaging of axonal and dendritic transport in iPSC‐derived cortical neurons. We use transfection and transient expression of genetically‐encoded fluorescent markers to characterize the motility of Rab‐positive vesicles, including early, late and recycling endosomes, as well as autophagosomes and mitochondria in iPSC‐derived neurons. Comparing transport parameters of these organelles with data from primary rat hippocampal neurons, we uncover remarkable similarities. In addition, we generated lysosomal‐associated membrane protein 1 (LAMP1)‐enhanced green fluorescent protein (EGFP) knock‐in iPSCs and show that knock‐in neurons can be used to study the transport of endogenously labeled vesicles, as a parallel approach to the transient overexpression of fluorescently labeled organelle markers.     

Multifrequency Microwave Imaging for Brain Stroke Detection

CT and MRI are often used in the diagnosis and monitoring of stroke. However, they are expensive, time-consuming, produce ionizing radiation (CT), and not suitable for continuous monitoring stroke. Microwave imaging (MI) has been extensively investigated for identifying several types of human organs, including breast, brain, lung, liver, and gastric. The authors recently developed a holographic microwave imaging (HMI) algorithm for biological object detection. However, this method has difficulty in providing accurate information on embedded small inclusions. This paper describes the feasibility of the use of a multifrequency HMI algorithm for brain stroke detection. A numerical system, including HMI data collection model and a realistic head model, was developed to demonstrate the proposed method for imaging of brain tissues. Various experiments were carried out to evaluate the performance of the proposed method. Results of experiments carried out using multifrequency HMI have been compared with the results obtained from single frequency HMI. Results showed that multifrequency HMI could detect strokes and provide more accurate results of size and location than the single frequency HMI algorithm.     

Simulated four-dimensional CT for markerless tumor tracking using a deep learning network with multi-task learning

IntroductionOur markerless tumor tracking algorithm requires 4DCT data to train models. 4DCT cannot be used for markerless tracking for respiratory-gated treatment due to inaccuracies and a high radiation dose. We developed a deep neural network (DNN) to generate 4DCT from 3DCT data.MethodsWe used 2420 thoracic 4DCT datasets from 436 patients to train a DNN, designed to export 9 deformation vector fields (each field representing one-ninth of the respiratory cycle) from each CT dataset based on a 3D convolutional autoencoder with shortcut connections using deformable image registration. Then 3DCT data at exhale were transformed using the predicted deformation vector fields to obtain simulated 4DCT data. We compared markerless tracking accuracy between original and simulated 4DCT datasets for 20 patients. Our tracking algorithm used a machine learning approach with patient-specific model parameters. For the training stage, a pair of digitally reconstructed radiography images was generated using 4DCT for each patient. For the prediction stage, the tracking algorithm calculated tumor position using incoming fluoroscopic image data.ResultsDiaphragmatic displacement averaged over 40 cases for the original 4DCT were slightly higher (<1.3 mm) than those for the simulated 4DCT. Tracking positional errors (95th percentile of the absolute value of displacement, “simulated 4DCT” minus “original 4DCT”) averaged over the 20 cases were 0.56 mm, 0.65 mm, and 0.96 mm in the X, Y and Z directions, respectively.ConclusionsWe developed a DNN to generate simulated 4DCT data that are useful for markerless tumor tracking when original 4DCT is not available. Using this DNN would accelerate markerless tumor tracking and increase treatment accuracy in thoracoabdominal treatment.     

Higher patient doses through X-ray imaging procedures

Medical imaging using X-rays has been one of the most popular imaging modalities ever since the discovery of X-rays 125 years ago. With unquestionable benefits, concerns about radiation risks have frequently been raised. Computed tomography (CT) and fluoroscopic guided interventional procedures have the potential to impart higher radiation exposure to patients than radiographic examinations. Despite technological advances, there have been instances of increased doses per procedure mainly because of better diagnostic information in images. However, cumulative dose from multiple procedures is creating new concerns as effective doses >100 mSv are not uncommon. There is a need for action at all levels. Manufacturers must produce equipment that can provide a quality diagnostic image at substantially lesser dose and better implementation of optimization strategies by users. There is an urgent need for the industry to develop CT scanners with sub-mSv radiation dose, a goal that has been lingering. It appears that a new monochromatic X-ray source will lead to replacement of X-ray tubes all over the world in coming years and will lead to a drastic reduction in radiation doses. This innovation will impact all X-ray imaging and will help dose reduction. For interventional procedures, the likely employment of robotic systems in practice may drastically reduce radiation exposures to operators- but patient exposure will still remain an issue. Training needs always need to be emphasized and practiced.     

Four-dimensional imaging with virtual reality to quantitatively explore jigsaw puzzle-like morphogenesis of Arabidopsis cotyledon pavement cells

In most dicotyledonous plants, leaf pavement cells exhibit complex jigsaw puzzle-like cell morphogenesis during leaf expansion. Although detailed molecular biological information and mathematical modeling of this jigsaw puzzle-like cell morphogenesis are now available, a full understanding of this process remains elusive. Recent reports have highlighted the importance of three-dimensional (3D) structures (i.e., anticlinal and periclinal cell wall) in understanding the mechanical models that describe this morphogenetic process. We believe that it is important to acquire 3D shapes of pavement cells over time, i.e., acquire and analyze four-dimensional (4D) information when studying the relationship between mechanical modeling and simulations and the actual cell shape. In this report, we have developed a framework to capture and analyze 4D morphological information of Arabidopsis thaliana cotyledon pavement cells by using both direct water immersion observations and computational image analyses, including segmentation, surface modeling, virtual reality and morphometry. The 4D cell models allowed us to perform time-lapse 3D morphometrical analysis, providing detailed quantitative information about changes in cell growth rate and shape, with cellular complexity observed to increase during cell growth. The framework should enable analysis of various phenotypes (e.g., mutants) in greater detail, especially in the 3D deformation of the cotyledon surface, and evaluation of theoretical models that describe pavement cell morphogenesis using computational simulations. Additionally, our accurate and high-throughput acquisition of growing cell structures should be suitable for use in generating in silico model cell structures.