Design and synthesis of a new fluorescent probe for cascade detection of Zn2+ and H2PO4− in water and targeted imaging of living cells

Design and synthesis of new fluorescence probes with good water‐solubility is of great importance to better understanding the significant role of ions which are related to biology and the environment. As important ions, zinc ion (Zn²⁺) and dihydrogen phosphate ion (H₂PO₄^?) display essential roles in living systems, and quantitative detection of these ions in water is still a challenge. In order to consider the significant role of the galactose moiety in the design of a water‐soluble fluorescence sensor, herein, we have developed a novel probe, Gal‐AQTF, for the cascade detection of Zn²⁺ and H₂PO₄^? with excellent selectivity in water. Through the introduction of the galactose moiety onto the sensor AQTF, which has been reported earlier by us, the water‐solubility, cell compatibility and targeting ability were enhanced. Gal‐AQTF has been successfully applied in the imaging of the living cells of HepG2 and A549, and illustrated good selectivity for the HepG2 cells which overly express the asialoglycoprotein (ASGP) receptor.     

Quantitative assessment of optical clearing methods in various intact mouse organs

Various tissue optical clearing techniques have sprung up for large volume imaging. However, there are few methods showed clearing and imaging data on different organs while most of them were focused on mouse brain, and as a result, it is difficult to select the suitable method for organs in practical applications due to lack of quantitative evaluation and comprehensive comparison. Therefore, it is necessary to evaluate and compare the performances of clearing methods for different organs. In this paper, several typical optical clearing methods were applied, including 3DISCO, uDISCO, SeeDB, FRUIT, CUBIC, ScaleS and PACT to clear intact brain, heart, kidney, liver, spleen, stomach, lung, small intestine, skin and muscle. The clearing efficiency, sample deformation, fluorescence preservation and imaging depth of these methods were quantitatively evaluated. Finally, based on the systemic evaluation of various parameters described above, the appropriate clearing method for specific organ including kidney or intestine was screened out. This paper will provide important references for selection of appropriate clearing methods in related researches.      

3.0 T磁共振T2×mapping成像技术定量评估膝关节骨性关节炎的临床价值及与WOMAC评分的相关性分析

摘要 目的：研究3.0 T磁共振T2×mapping成像技术定量评估膝关节骨性关节炎（OA）的临床价值及与西安大略和麦克马斯特大学骨关节炎指数（WOMAC）评分的相关性。方法：将我院于2017年4月～2019年12月期间收治的膝关节OA患者80例纳入研究。根据K-L分级标准将膝关节OA患者分成轻度组（K-L分级为Ⅰ～Ⅱ级）32例,重度组（K-L分级为Ⅲ～Ⅴ级）48例。另取同期于我院进行体检的健康者30例作为对照组。所有受试者均接受3.0 T磁共振T2×mapping扫描,比较各组膝关节不同部位软骨T2值、WOMAC评分以及血清炎症因子水平,以Pearson相关性分析膝关节OA患者膝关节不同部位软骨T2值和WOMAC评分的关系。结果：重度组膝关节不同部位软骨T2值均高于轻度组以及对照组,且轻度组膝关节不同部位软骨T2值均高于对照组（均P＜0.05）。重度组各项WOMAC评分及总分均高于轻度组以及对照组,且轻度组各项WOMAC评分及总分均高于对照组（均P＜0.05）。经Pearson相关性分析发现：膝关节OA患者膝关节不同部位软骨T2值和各项WOMAC评分及总分均呈正相关（均P＜0.05）。重度组血清白介素-1β（IL-1β）、白介素-18（IL-18）、肿瘤坏死因子α（TNF-α）均高于轻度组以及对照组,且轻度组血清IL-1β、IL-18、TNF-α均高于对照组（均P＜0.05）。结论：3.0 T磁共振T2×mapping成像技术定量评估膝关节OA的临床价值较高,且患者膝关节不同部位软骨T2值与WOMAC评分密切相关。     

冠状动脉磁共振血管成像和CT对可疑冠心病患者心脏事件的预测价值的比较研究

摘要 目的：探讨与比较冠状动脉核磁共振(MR)血管成像和CT对可疑冠心病患者心脏事件的预测价值。方法：2018年4月到2020年10月选择在本院诊治的103例可疑冠心病患者作为研究对象,所有患者都给予冠状动脉MRI血管成像与64层螺旋CT冠状动脉成像检查,记录影像学特征。随访患者的预后并进行预测价值分析。结果：103例可疑冠心病患者随访到2021年4月1日,发生心血管不良终点事件23例(不良事件组),发生率为22.3%。不良事件组的MRI血管成像显示右冠状动脉血管长度与内径都低于非不良事件组(P<0.05)。不良事件组的CT显示斑块率、斑块性质等与非不良事件组对比差异有统计学意义(P<0.05),两组斑块位置对比差异无统计学意义(P>0.05)。多因素Cox回归分析显示斑块性质、斑块率、右冠状动脉血管长度与内径都为导致心血管不良终点事件的重要因素(P<0.05)。结论：冠状动脉MRI血管成像和CT都可有效预测可疑冠心病患者心脏事件发生情况,能满足临床诊断可疑冠心病与预测预后的要求。     

Quantitative IR microscopy and spectromics open the way to 3D digital pathology

Currently, only mass‐spectrometry (MS) microscopy brings a quantitative analysis of chemical contents of tissue samples in 3D. Here, the reconstruction of a 3D quantitative chemical images of a biological tissue by FTIR spectro‐microscopy is reported. An automated curve‐fitting method is developed to extract all intense absorption bands constituting IR spectra. This innovation benefits from three critical features: (1) the correction of raw IR spectra to make them quantitatively comparable; (2) the automated and iterative data treatment allowing to transfer the IR‐absorption spectrum into a IR‐band spectrum; (3) the reconstruction of an 3D IR‐band matrix (x, y, z for voxel position and a 4^th dimension with all IR‐band parameters). Spectromics, which is a new method for exploiting spectral data for tissue metadata reconstruction, is proposed to further translate the related chemical information in 3D, as biochemical and anatomical tissue parameters. An example is given with oxidative stress distribution and the reconstruction of blood vessels in tissues. The requirements of IR microscopy instrumentation to propose 3D digital histology as a clinical routine technology is briefly discussed.

     

Deep learning for computational biology

Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within them, and for making accurate predictions. In this review, we discuss applications of this new breed of analysis approaches in regulatory genomics and cellular imaging. We provide background of what deep learning is, and the settings in which it can be successfully applied to derive biological insights. In addition to presenting specific applications and providing tips for practical use, we also highlight possible pitfalls and limitations to guide computational biologists when and how to make the most use of this new technology.     

Wearable scanning photoacoustic brain imaging in behaving rats

A wearable scanning photoacoustic imaging (wPAI) system is presented for noninvasive brain study in behaving rats. This miniaturized wPAI system consists of four pico linear servos and a single transducer‐based PAI probe. It has a dimension of 50 mm × 35 mm × 40 mm, and a weight of 26 g excluding cablings. Phantom evaluation shows that wPAI achieves a lateral resolution of ～0.5 mm and an axial resolution of ～0.1 mm at a depth of up to 11 mm. Its imaging ability is also tested in a behaving rat, and the results indicate that wPAI is able to image blood vessels at a depth of up to 5 mm with intact scalp and skull. With its noninvasive, deep penetration, and functional imaging ability in behaving animals, wPAI can be used for behavior, cognition, and preclinical brain disease studies.

     

High frequency residues: A new set of signals for detectability studies of an X-ray imaging system

A new set of signals for studying detectability of an X-ray imaging system is presented. The results obtained with these signals are intended to complement the NEQ results.The signals are generated from line spread profiles by progressively removing their lower frequency components and the resulting high frequency residues (HFRs) form the set of signals to be used in detectability studies. Detectability indexes for these HFRs are obtained using a non-prewhitening (NPW) observer and a series of edge images are used to obtain the HFRs, the covariance matrices required by the NPW model and the MTF and NPS used in NEQ calculations. The template used in the model is obtained by simulating the processes of blurring and sampling of the edge images. Comparison between detectability indexes for the HFRs and NEQ are carried out for different acquisition techniques using different beam qualities and doses.The relative sensitivity shown by detectability indexes using HFRs is higher than that of NEQ, especially at lower doses. Also, the different observers produce different results at high doses: while the ideal Bayesian observer used by NEQ distinguishes between beam qualities, the NPW used with the HFRs produces no differences between them.Delta functions used in HFR are the opposite of complex exponential functions in terms of their support in the spatial and frequency domains. Since NEQ can be interpreted as detectability of these complex exponential functions, detectability of HFRs is presented as a natural complement to NEQ in the performance assessment of an imaging system.     

ROI-Based Compression Strategy of 3D MRI Brain Datasets for Wireless Communications

ObjectivesBecause of the large amount of medical imaging data, the transmission process becomes complicated in telemedicine applications. Thus, in order to adapt the data bit streams to the constraints related to the limitation of the bandwidths a reduction of the size of the data by compression of the images is essential. Despite the improvements in the field of compression, the transmission itself can also introduce errors. For this reason, it is important to develop an adequate strategy which will help reduce this volume of data without having to introduce some distortion and resist the errors introduced by the channel noise during transmission. Thus, in this paper, we propose a ROI-based coding strategy and unequal bit stream protection to meet this dual constraint.Material and methodsThe proposed ROI-based compression strategy with unequal bit stream protection is composed of three parts: the first one allows the extraction of the ROI region, the second one consists of a ROI-based coding and the third one allows an unequal protection of the ROI bit stream.First, the Regions Of Interest (ROI) are extracted by hierarchical segmentation of these regions according to a segmentation method based on the technique of Marker-based-watershed combined with the technique of active contours by level set. The resulting regions are selectively encoded by a 3D coder based on a shape adaptive discrete wavelet transform 3D-BISK, where the compression ratio of each region depends on its relevance in diagnosis. These obtained regions of interest are protected with an error-correcting code of Reed-Solomon type with a code rate that varies according to the relevance of the region by an unequal protection strategy (UEP).ResultsThe performance of the proposed compression scheme is evaluated in several ways. First, tests are performed to study the impact of errors on the different bit streams. In the first place, these tests are carried out in order to study the effect of the variation of the compression rates on the different bit streams. Secondly, different Reed Solomon error-correcting codes of different code rates are tested at different compression rates on a BSC channel. Finally, the performances of this coding strategy are compared with those of SPIHT 3D in the case of transmission on a BSC channel.ConclusionThe obtained results show that the proposed method is quite efficient in transmission time reduction. Therefore, our proposed scheme will reduce the volume of data without having to introduce some distortion and resist the errors introduced by the channel noise in the case of telemedicine.     

Molecular network strategy in multi-omics and mass spectrometry imaging

Human physiological activities and pathological changes arise from the coordinated interactions of multiple molecules. Mass spectrometry (MS)-based multi-omics and MS imaging (MSI)-based spatial omics are powerful methods used to investigate molecular information related to the phenotype of interest from homogenated or sliced samples, including the qualitative, relative quantitative and spatial distributions. Molecular network strategy provides efficient methods to help us understand and mine the biological patterns behind the phenotypic data. It illustrates and combines various relationships between molecules, and further performs the molecule identification and biological interpretation. Here, we describe the recent advances of network-based analysis and its applications for different biological processes, such as, obesity, central nervous system diseases, and environmental toxicology.