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.     

Applications of second harmonic generation (SHG)/sum-frequency generation (SFG) imaging for biophysical characterization of the plasma membrane

The plasma membrane is a lipid bilayer of < 10 nm width that separates intra- and extra-cellular environments and serves as the site of cell-cell communication, as well as communication between cells and the extracellular environment. As such, biophysical phenomena at and around the plasma membrane play key roles in determining cellular physiology and pathophysiology. Thus, the selective visualization and characterization of the plasma membrane are crucial aspects of research in wide areas of biology and medicine. However, the specific characterization of the plasma membrane has been a challenge using conventional imaging techniques, which are unable to effectively distinguish between signals arising from the plasma membrane and those from intracellular lipid structures. In this regard, interface-specific second harmonic generation (SHG) and sum-frequency generation (SFG) imaging demonstrate great potential. When combined with exogenous SHG/SFG active dyes, SHG/SFG can specifically highlight the plasma membrane as the most prominent interface associated with cells. Furthermore, SHG/SFG imaging can be readily extended to multimodal multiphoton microscopy with simultaneous occurrence of other multiphoton phenomena, including multiphoton excitation and coherent Raman scattering, which shed light on the biophysical properties of the plasma membrane from different perspectives. Here, we review traditional and current applications, as well as the prospects of long-known but unexplored SHG/SFG imaging techniques in biophysics, with special focus on their use in the biophysical characterization of the plasma membrane.     

大鼠脑缺血/再灌注过程中血流量和脑组织含水量的变化趋势*

目的:研究大鼠脑缺血/再灌注过程中血流量及与脑组织水含量变化的趋势。方法:选取5只成年SD雄性大鼠(n=5),参照改良Zea-Longa线栓法制备大鼠大脑中动脉缺血/再灌注模型,2 h后拔出线栓。利用PeriCam PSI血流灌注成像系统实时监测大鼠在缺血前及缺血5 min、30 min、1 h、2 h、再灌注5 min、30 min、1 h、2 h、4 h、6 h及24 h的血流灌注量,记录在ROI(感兴趣区)测量的数值。再选取15只成年SD雄性大鼠,分为Control组、缺血2 h、再灌注30 min、4 h及24 h组(n=3)。正常组不做任何处理,实验组按上述线栓法制备MCAO模型。取新鲜脑组织用干湿重法测定其左、右半球的水含量。结果:栓塞时缺血侧血流量逐渐下降,缺血2 h下降最低(P＜0.05);再灌注早期血流量恢复较大(P＜0.05),30 min时显著下降(P＜0.05),4 h明显上升(P＜0.05),24 h再次上升(P＜0.05)但低于缺血前血流量(P＞0.05)。脑组织水含量测量,缺血2 h组和再灌注30 min组与正常组无明显差异(P＞0.05);再灌4 h组和再灌24 h组明显增高(P＜0.05),且再灌24 h组明显高于再灌4 h组(P＜0.05)。结论:大鼠脑缺血/再灌注过程中血流量和脑组织中水含量的变化存在一定的规律,且脑组织中水含量与再灌注过程中血流量的变化有一定关系。     

铽(Ⅲ)离子及其复合物:从发光特性到传感应用

稀土元素也称镧系元素,因其独特的发光性质和配位性质,其发光复合物被广泛研究于生物技术领域。其中稀土铽(Ⅲ)离子复合物因具有优异的光谱特性,关于其研究呈现出快速的发展趋势。主要从其发光特性的角度出发,探讨了其发光机理,并对铽(Ⅲ)离子与不同有机化合物结合形成的发光铽配合物以及铽(Ⅲ)离子及其配合物与不同纳米材料形成的复合物进行了分类综述。此外,还详细地阐述了铽离子及其复合物在荧光探针、生物传感器、药物递送、细胞成像、癌症治疗等相关领域的应用。最后,对其今后发展趋势和潜在的研究价值进行了展望。     

Single‐molecule tracking reveals that the nucleoid‐associated protein HU plays a dual role in maintaining proper nucleoid volume through differential interactions with chromosomal DNA

HU (Histone‐like protein from Escherichia coli strain U93) is the most conserved nucleoid‐associated protein in eubacteria, but how it impacts global chromosome organization is poorly understood. Using single‐molecule tracking, we demonstrate that HU exhibits nonspecific, weak, and transitory interactions with the chromosomal DNA. These interactions are largely mediated by three conserved, surface‐exposed lysine residues (triK), which were previously shown to be responsible for nonspecific binding to DNA. The loss of these weak, transitory interactions in a HUα(triKA) mutant results in an over‐condensed and mis‐segregated nucleoid. Mutating a conserved proline residue (P63A) in the HUα subunit, deleting the HUβ subunit, or deleting nucleoid‐associated naRNAs, each previously implicated in HU’s high‐affinity binding to kinked or cruciform DNA, leads to less dramatically altered interacting dynamics of HU compared to the HUα(triKA) mutant, but highly expanded nucleoids. Our results suggest HU plays a dual role in maintaining proper nucleoid volume through its differential interactions with chromosomal DNA. On the one hand, HU compacts the nucleoid through specific DNA structure‐binding interactions. On the other hand, it decondenses the nucleoid through many nonspecific, weak, and transitory interactions with the bulk chromosome. Such dynamic interactions may contribute to the viscoelastic properties and fluidity of the bacterial nucleoid to facilitate proper chromosome functions.