CT联合MRI在早期肝癌诊断临床价值分析

摘要 目的：探究CT联合MRI在早期肝癌诊断中的应用价值。方法：选择2016年6月至2019年6月于我院接受诊断治疗的78例已知或疑似肝癌患者,分别对其实施CT及MRI检测,以病灶部位病理学检查结果为金标准（50例确诊为早期肝癌,28例为良性病变）,分别评估CT、MRI、CT联合MRI对早期肝癌的诊断价值,将确诊为肝癌的50例患者按照病灶大小区分为直径≤3 cm组（21例）和>3 cm组（29例）,对比CT与MRI对不同直径肝癌诊断率。结果：（1）检测发现,CT对早期肝癌诊断一致性为73.08 %,灵敏度为72.00 %,特异度为75.00 %;（2）MRI对早期肝癌诊断一致性为82.05 %,灵敏度为82.00 %,特异度为82.14 %;（3）CT联合MRI检测对早期肝癌诊断一致性为93.59 %,灵敏度为92.00 %,特异度为96.43 %;（4）对比发现,对直径≤3 cm的早期肝癌患者,MRI诊断率明显高于CT（95.24 % vs 76.19 %,P<0.05）。结论：CT及MRI对早期肝癌均具有较好的诊断价值,但联合检测明显优于任一单独检测,同时对病灶直径≤3 cm的早期肝癌患者,MRI诊断准确率更高。     

Use of milk electrical conductivity for the differentiation of mastitis causing pathogens in Holstein cows

Mastitis is one of the most prevalent and costly diseases in dairy cattle. Key components for adequate mastitis control are the detection of early stages of infection, as well as the selection of appropriate management interventions and therapies based on the causal pathogens associated with the infection. The objective was to characterize the pattern of electrical conductivity (EC) in milk during intramammary infection, considering specific mastitis-causing pathogen groups involvement. Cows (n = 200) identified by an in-line mastitis detection system with a positive deviation ≥15% in the manufacturer’s proprietary algorithm for EC (high electrical conductivity (HEC)) were considered cases and enrolled in the study at the subsequent milking. One control (CON) cow, within normal ranges for EC, was matched to each case. A composite milk sample was collected aseptically from each cow for bacteriological culture. Milk yield (MY) and EC were recorded for each milking during ±7 days relative to enrollment. Milk cultures were categorized into gram positive (GP), gram negative (GN), other (OTH) and no growth (NOG). Data were submitted for repeated-measures analysis with EC as the dependent variable and EC status at day −1, bacteriological culture category, parity number, stage of lactation and days relative to sampling as main independent variables. Average (± standard error (SE)) EC was greater in HEC than in CON cows (12.5 ± 0.5 v. 10.8 ± 0.5 mS/cm) on the day of identification (day −1). Milk yield on day −1 was greater in CON than in HEC (37.6 ± 5.1 v. 33.5 ± 5.2 kg). For practical management purposes, average EC on day −1 was similar for the different bacteriological culture categories: 11.4 ± 0.6, 11.7 ± 0.5, 12.3 ± 0.8 and 11.7 ± 0.5 mS/cm in GN, GP, OTH and NOG, respectively. Parity number was only associated with day −1 EC in HEC group, with the greatest EC values in parity 3 (12.3 ± 0.3 mS/cm), followed by parity 2 (11.9 ± 0.2 mS/cm), parity >3 (11.6 ± 0.5 mS/cm) and primiparous cows (11.2 ± 0.2 mS/cm). An effect on EC for the interaction of day relative to identification by pathogen gram category was observed. The same interaction effect was observed on daily MY. Overall, the level of variation for MY and EC between- and within-cows was substantial, and as indicated by the model diagnostic procedures, the magnitude of the variance in the cows in the CON group resulted in deviations from normality in the residuals. We concluded that characteristic temporal patterns in EC and MY in particular pathogen groups may provide indications for differentiation of groups of mastitis-causing pathogens. Further research to build detection models including EC, MY and cow-level factors is required for accurate differentiation.     

Review: Helicobacter pylori infection in children

Helicobacter pylori infection in children and adolescents differs in comparison to adults with respect to epidemiology, host responses, and disease manifestations. Furthermore, treatment options are limited in this population and antibiotic resistance rates continue to increase. Therefore, ongoing research is vital to understand disease pathogenesis and provide optimal management of children with infection. This review summarizes relevant publications from April 2019 to March 2020. Similar to adults, recent studies show a decreasing prevalence of infection in the pediatric population. Studies of pathogenesis investigated serum immune responses and the potential inverse association of infection and allergy. Several studies investigated the effect of H pylori and related inflammation on the gut microbiome. The recommendation of endoscopy‐based testing to identify the cause of symptoms and not just H pylori, reserving noninvasive UBT or stool antigen tests for post‐eradication follow‐up, was supported by the current literature.     

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.     

基于CRISPR/Cas9的基因分析方法研究进展

自2012年首次证明了CRISPR/Cas9可以在体外进行DNA切割试验以来,CRISPR技术逐渐在基因编辑研究中获得了迅速的发展,除了应用于基因编辑领域之外,它在基因表达调控、基因成像、基因分析等方面也展现出了巨大的应用潜力。尤其在基因分析领域,CRISPR技术由于其精确的基因识别、室温的反应条件、易设计性和操作性等特色,使得一系列新型的基因检测技术得以发展,并取得了超越常规技术的一些检测参数。本文以Cas9蛋白为对象,综述了近些年来在该领域取得的研究进展。主要论述Cas9蛋白的功能、改造、引导RNA(sgRNA)的设计及其在基因分析方法上的应用。     

Plasmonic Biosensor Controlled by DNAzyme for On‐Site Genetic Detection of Pathogens

On‐site predetection of pathogens could significantly decrease of a disease outbreak or national loss in most of the countries. However, conventional detection techniques are limited in use for on‐site detection due to the necessity of specialized skill or equipment. Therefore, it is necessary to develop a new technique that can predetect pathogens in the field without special skills or equipment. Here, a DNAzyme strategy to control a plasmonic biosensor for rapid and simple visual detection of Salmonella choleraesuis is adopted. Multicomponent DNAzyme formed by target addition can cleave the linker effectively at 50 °C. Linker cleavage induces dispersion of two DNA‐immobilized gold nanoparticles and color change. Under optimized assay conditions, the target could be detected via visual discrimination sensitively and specifically. Moreover, the biosensor shows the possibility of practical use with contaminants and a 16S rRNA real target. As a result, the proposed plasmonic biosensor can visually detect S. choleraesuis without unstable enzymes, a specialized technique, or equipment. Therefore, these advantages could allow that this biosensor would be used for on‐site predetection to lower the risk of transmission of infectious diseases.     

Mdm2 inhibitors as a platform for the design of P-glycoprotein inhibitors

Chemoresistance is thought to be the cause of low treatment efficacy and mortality in more than 90% of patients with advanced cancer. The activation of drug efflux by P-glycoprotein is the key mechanism of resistance. All known P-gp inhibitors are used only in the combination therapy. We propose a new approach based on the multitarget rational design of drugs, which possess both the antitumor and efflux pump inhibitory activity. In this work, the principle possibility of combining the ability to inhibit P-gp and p53-Mdm2 protein-protein interaction in one structure is considered. The biological activity of a number of known and newly synthesized compounds was evaluated using cell lines with different p53 status. The possibility of using computer modeling for the search for P-glycoprotein inhibitors among Mdm2 inhibitors was analyzed; P-gp interaction site and binding modes of substrates and inhibitors were identified. The results obtained in cells that have the native balance of drug resistance and sensitivity showed the ability of the cells to both actively throw out xenobiotics and to lose this ability using P-gp inhibitors. The data obtained indicate that Mdm2 inhibitors are a promising platform for the development of multitarget drugs that can overcome tumor resistance by inhibiting the P-glycoprotein activity.     

血清sST2在心力衰竭诊断、预后中的应用价值

心力衰竭(心衰)的发病率正随着人口老龄化的加速而显著上升,目前仍然是一个重大的公共健康问题。尽管近年来在心衰治疗方面取得了显著成效,但患者的生存率依旧很低,预后差,确诊心衰后5年内死亡率高达50%。如果能够对心衰进行快速有效的诊断并按危险程度进行合理分层,将为临床医生制定治疗方案提供重要的参考依据。生物标志物在心衰的诊断、疗效评估及预后判断方面都具有重要的意义。心力衰竭是一种复杂的疾病,涉及多种生理病理过程。心力衰竭时,神经内分泌系统被激活,同时伴随着血容量和心室壁压力增加,心室肌细胞分泌NT-proBNP/BNP,因此,其可作为心衰诊断和预后生物标志物。然而血浆中NT-proBNP/BNP易受到年龄、性别、体型、左室肥大、心动过速、右心室过载、低氧血症、肾脏功能等诸多因素影响。sST2作为一种新型心力衰竭标志物,近年来备受关注,它不仅能够反映心肌纤维化程度并预测是否发生心室重构,且不受年龄、性别、肾功能等因素的影响,同时具有更低的参考变化值和个体指数,更适合用于连续监测和指导治疗,是评价心力衰竭的理想指标之一。文中对近年来sST2在心衰诊断和预后方面的研究进展进行总结归纳,并对其发展趋势进行展望。     

2011-2017年大连市输入性卵形疟原虫感染病例的实验室诊断

目的分析大连市2011-2017年7例输入性卵形疟原虫感染病例的病原、抗原及核酸检测结果,以提高卵形疟原虫诊断的准确率和效率。方法收集7例疑似疟疾患者的血样,对血样进行血涂片镜检、快速疟疾诊断试纸条检测(RDT)及荧光定量PCR检测。结果血涂片镜检结果显示7例患者均感染卵形疟原虫。RDT检测结果显示2例阴性,另外5例为泛疟原虫抗原阳性。荧光定量PCR结果显示7例患者均检出疟原虫属和卵形疟原虫核酸。结论综合镜检、RDT及荧光定量PCR检测结果确定该7例患者均为卵形疟原虫感染。     

Machine Learning Approach to Detect Cardiac Arrhythmias in ECG Signals: A Survey

Cardiac arrhythmia is a condition when the heart rate is irregular either the beat is too slow or too fast. It occurs due to improper electrical impulses that coordinates the heart beats. Sudden cardiac death may occurs due to some dangerous arrhythmias conditions. Hence the main objective of the electrocardiogram (ECG) analysis is to detect the life-threatening arrhythmias accurately for appropriate treatment in order to save life. Since the last decades, several methods were reported for automatic ECG beat classifications. In this work, we present a systematic review of the current state-of-the-art methods used to detect cardiac arrhythmia using on ECG signals. It includes the signal decomposition, feature extraction and machine learning approaches used for automatic detection and decision making process. The articles covers the pre-processing, detection of QRS complex, feature extraction and classification of ECG beats. Based on the past studies, it is understood that the automated approach using computer-aided decision making process is highly required for real-time detection of cardiac arrhythmias. The advantages and limitations of different methods are discussed and also the future scopes is highlighted in the process of effective detection of cardiac arrhythmias. This study could be beneficial for researchers to analyze the existing state-of-art techniques used in detection of arrhythmia conditions.