凉血通瘀方干预高血压大鼠急性脑出血模型对脑组织中差异miRNA表达的影响＊

目的 研究凉血通瘀方对高血压大鼠急性脑出血模型脑组织miRNA表达的影响，对差异表达的miRNA靶基因进行分析，探索凉血通瘀方可能的药效机制。方法 将自发性高血压大鼠随机分成对照组（B）和实验组（C）。适应性饲养一周后，C组灌胃凉血通瘀方，B组灌胃等体积生理盐水，连续5天，每天1次。构建脑出血模型后收集脑组织，借助全转录组测序技术获得miRNA表达量，与miRBase数据库比对获取已知miRNA，使用miRDeep2预测新miRNA。差异分析软件为DESeq2，筛选阈值为|log₂FC| ≥1 并且P <0.05。对显著差异表达的miRNA进行靶基因预测，对靶基因进行GO功能、KEGG通路富集和PPI网络分析。结果 实验组和对照组对比，共发现21个显著差异表达的miRNA，上调有9个，下调有12个，共预测得到1243个有统计学意义的靶基因。GO富集分析发现，生物过程中突触囊泡分泌的调节、神经递质分泌的调节和神经递质运输的调节占前三位，神经元投射终点、全膜、质膜区域和细胞投射则是主要的细胞成分。分子功能分别为小GTPase绑定、底物特异性跨膜转运蛋白活性和离子跨膜转运体活性。通路分析结果显示，靶基因在癌证通路、pI3K-Akt信号通路、人类乳头瘤病毒感染、神经活性配体-受体相互作用和MAPK通路等分布广泛。采用STRING网站和Cytoscape软件，根据MCC算法筛选出ADRA2C、CASR、CCL28、CCR1、DRD2、GNAT3、GRM2、DYNC1LI1、GABBR1、GNAI1等核心靶基因。结论 凉血通瘀方对脑出血急性期鼠脑组织内miRNA的表达有重要影响；显著差异表达miRNAs可能通过靶向核心基因调控凉血通瘀方干预急性脑出血的病理过程及预后。     

Case Report: Transient Stress Hyperglycemia in the Patient With ST-Elevation Myocardial Infarction

Transient stress hyperglycemia in the setting of acute myocardial infarction is a frequent phenomenon. Its transient nature should not dissuade the clinician from management of elevated blood glucose in a patient after an ST-elevation myocardial infarction. This case presents an adult patient after an ST-elevation myocardial infarction with transient stress hyperglycemia and the evidence used to identify optimal pharmacologic management and secondary prevention.     

Perivascular fat attenuation for predicting adverse cardiac events in stable patients undergoing invasive coronary angiography

BackgroundInflammation surrounding the coronary arteries can be non-invasively assessed using pericoronary adipose tissue attenuation (PCAT). While PCAT holds promise for further risk stratification of patients with low coronary artery disease (CAD) prevalence, its value in higher risk populations remains unknown.MethodsCORE320 enrolled patients referred for invasive coronary angiography with known or suspected CAD. Coronary computed tomography angiography (CCTA) images were collected for 381 patients for whom clinical outcomes were assessed 5 years after enrollment. Using semi-automated image analysis software, PCAT was obtained and normalized for the right coronary (RCA), left anterior descending (LAD), and left circumflex arteries (LCx). The association between PCAT and major adverse cardiovascular events (MACE) during follow up was assessed using Cox regression models.ResultsThirty-seven patients were excluded due to technical failure. For the remaining 344 patients, median age was 62 (interquartile range, 55–68) with 59% having ≥1 coronary artery stenosis of ≥50% by quantitative coronary angiography. Mean attenuation values for PCAT in RCA, LAD, and LCx were ?74.9, ?74.2, and ?71.2, respectively. Hazard ratios and 95% confidence intervals (CI) for normalized PCAT in the RCA, LAD, and LCx for MACE were 0.96 (CI: 0.75–1.22, p ?= ?0.71), 1.31 (95% CI: 0.96–1.78, p ?= ?0.09), and 0.98 (95% CI: 0.78–1.22, p ?= ?0.84), respectively. For death, stroke, or myocardial infarction only, hazard ratios were 0.68 (0.44–1.07), 0.85 (0.56–1.29), and 0.57 (0.41–0.80), respectively.ConclusionsIn patients referred for invasive coronary angiography with suspected CAD, PCAT did not predict MACE during long term follow up. Further studies are needed to understand the relationship of PCAT with CAD risk.     

Assessing the Effects of Geniculate Artery Embolization in a Nonsurgical Animal Model of Osteoarthritis

PurposeTo create a nonsurgical animal model of osteoarthritis (OA) to evaluate the effects of embolotherapy during geniculate artery embolization (GAE).Materials and MethodsFluoroscopy-guided injections of 700 mg of sodium monoiodoacetate were performed into the left stifle in 6 rams. Kinematic data were collected before and after induction. At 10 weeks after induction, Subjects 1 and 4–6 underwent magnetic resonance (MR) imaging with dynamic contrast enhancement (DCE) and Subjects 1, 3, and 4–6 underwent angiography with angiographic scoring to identify regions with greatest disease severity for superselective embolization (75–250-μm microspheres). Target vessel size was measured. At 24 weeks after angiography, DCE-MR imaging, angiography, and euthanasia were performed, and bilateral stifles were harvested. Medial/lateral tibial and femoral condylar, patellar, and synovial samples were cut, preserved, decalcified, and scored using the Osteoarthritis Research Society International criteria. The stifle and synovium Whole-Organ Magnetic Resonance Imaging Score and Multicenter Osteoarthritis Study score were determined. The volume transfer constant (K_trans) and extracellular volume fraction (v_e) were calculated from DCE-MR imaging along the lateral synovial regions of interest.ResultsThe mean gross and microscopic pathological scores were elevated at 38 and 61, respectively. Mean synovitis score was elevated at 9.2. Mean pre-embolization and postembolization angiographic scores were 5 and 3.8, respectively. Mean superior, transverse, and inferior geniculate artery diameters were 3.1 mm ± 1.21, 2.0 mm ± 0.50, and 1.6 mm ± 0.41 mm, respectively. Mean pre-embolization and postembolization cartilage and synovitis scores were elevated at 35.13 and 73.3 and 5.5 and 9.2, respectively. The K_trans/v_e values of Subjects 4, 5, and 6 were elevated at 0.049/0.38, 0.074/0.53, and 0.065/0.51, respectively. Altered gait of the hind limb was observed in all subjects after induction, with reduced joint mobility. No skin necrosis or osteonecrosis was observed.ConclusionsA nonsurgical ovine animal knee OA model was created, which allowed the collection of angiographic, histopathological, MR imaging, and kinematic data to study the effects of GAE.     

Examining Acute Coronary Syndrome Across Ethnicity,Sex, and Age

Acute coronary syndrome (ACS) remains one of the leading causes of death in the United States. With its heightened prevalence, considerable variabilities in the disease process exist across ethnicities, sex, and age. This creates substantial disparities in the recognition and management of ACS, which consequently contributes to poor outcomes. It is of utmost importance that nurse practitioners remain vigilant, cognizant, and maintain a high index of suspicion to accurately identify ACS presentations and thus efficaciously intervene to successfully manage the disease process.     

Automatic segmentation of thoracic CT images using three deep learning models

PurposeDeep learning (DL) techniques are widely used in medical imaging and in particular for segmentation. Indeed, manual segmentation of organs at risk (OARs) is time-consuming and suffers from inter- and intra-observer segmentation variability. Image segmentation using DL has given very promising results. In this work, we present and compare the results of segmentation of OARs and a clinical target volume (CTV) in thoracic CT images using three DL models.Materials and methodsWe used CT images of 52 patients with breast cancer from a public dataset. Automatic segmentation of the lungs, the heart and a CTV was performed using three models based on the U-Net architecture. Three metrics were used to quantify and compare the segmentation results obtained with these models: the Dice similarity coefficient (DSC), the Jaccard coefficient (J) and the Hausdorff distance (HD).ResultsThe obtained values of DSC, J and HD were presented for each segmented organ and for the three models. Examples of automatic segmentation were presented and compared to the corresponding ground truth delineations. Our values were also compared to recent results obtained by other authors.ConclusionThe performance of three DL models was evaluated for the delineation of the lungs, the heart and a CTV. This study showed clearly that these 2D models based on the U-Net architecture can be used to delineate organs in CT images with a good performance compared to other models. Generally, the three models present similar performances. Using a dataset with more CT images, the three models should give better results.