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61.
《Journal of microbiology, immunology, and infection》2020,53(3):425-435
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has emerged in Chinese people in December 2019 and has currently spread worldwide causing the COVID-19 pandemic with more than 150,000 deaths. In order for a SARS-CoV like virus circulating in wild life for a very long time to infect the index case-patient, a number of conditions must be met, foremost among which is the encounter with humans and the presence in homo sapiens of a cellular receptor allowing the virus to bind. Recently it was shown that the SARS-CoV-2 spike protein, binds to the human angiotensin I converting enzyme 2 (ACE2). This molecule is a peptidase expressed at the surface of lung epithelial cells and other tissues, that regulates the renin-angiotensin-aldosterone system. Humans are not equal with respect to the expression levels of the cellular ACE2. Moreover, ACE2 polymorphisms were recently described in human populations. Here we review the most recent evidence that ACE2 expression and/or polymorphism could influence both the susceptibility of people to SARS-CoV-2 infection and the outcome of the COVID-19 disease. Further exploration of the relationship between the virus, the peptidase function of ACE2 and the levels of angiotensin II in SARS-CoV-2 infected patients should help to better understand the pathophysiology of the disease and the multi-organ failures observed in severe COVID-19 cases, particularly heart failure. 相似文献
62.
Sophocarpine attenuates toll‐like receptor 4 in steatotic hepatocytes to suppress pro‐inflammatory cytokines synthesis
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64.
This is the first Japanese autopsy case of Leucine-rich repeat kinase 2 (LRRK2) G2019S mutation with atypical TDP43 proteinopathy. Our case is important that presented clinically dysphagia and pathologically TDP-43 proteinopathy. TDP43 may play an important role of clinical presentation with LRRK2 G2019S mutation carriers. 相似文献
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66.
《Diagnostic and interventional imaging》2020,101(12):821-830
PurposeTo compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC).Materials and methodsPatients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared.ResultsThirty-seven patients (21 men, 16 women; mean age, 56 ± 13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60 ± 46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70 ± 51 [SD] mm [range: 18 - 196 mm] vs. 42 ± 24 [SD] mm [range: 8 - 94 mm], respectively; P = 0.039), with more tumor necrosis (75% vs. 33%, respectively; P = 0.030) and lower attenuation on precontrast (30 ± 4 [SD] HU [range: 25-39 HU] vs. 37 ± 6 [SD] [range: 25-45 HU], respectively; P = 0.002) and on portal venous phase CT images (75 ± 18 [SD] HU [range: 43 - 108 HU] vs. 92 ± 19 [SD] HU [range: 46 - 117 HU], respectively; P = 0.014). Hemorrhagic content on MRI was only observed in NEC (P = 0.007). The mean ADC value was lower in NEC ([1.1 ± 0.1 (SD)] × 10−3 mm2/s [range: (0.91 - 1.3) × 10−3 mm2/s] vs. [1.4 ± 0.2 (SD)] × 10−3 mm2/s [range: (1.1 - 1.6) × 10−3 mm2/s]; P = 0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7 ± 0.2 [SD] [range: 4.2-5.1] vs. 4.5 ± 0.4 [SD] [range: 3.7-4.9]; P = 0.023).ConclusionPancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI. 相似文献
67.
《Diagnostic and interventional imaging》2020,101(9):555-564
PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%. 相似文献
68.
Ahmed M. Abu El-Asrar Ajmal Ahmad Eef Allegaert Mohammad Mairaj Siddiquei Priscilla W. Gikandi Gert De Hertogh 《Ocular immunology and inflammation》2020,28(4):575-588
ABSTRACT
Purpose
To investigate the expression of IL-11 and its receptor IL-11Rα and to quantify density of CD163+ M2 macrophages in proliferative diabetic retinopathy (PDR). 相似文献69.
70.
目前新型冠状病毒肺炎(COVID-19)疫情在全球蔓延,形势严峻,并对全球公共卫生事业构成巨大挑战,快速准确的诊断COVID-19对疫情的防控有重要意义。本文报道1例COVID-19患者的调查和确诊过程,以对COVID-19确诊和疫情防控提供有价值的参考。患者为赴渝务工于2020年1月23日返乡人员,在渝期间,其同工地的一同事确诊为COVID-19,之后该工地接连有另外8位同事被确诊。患者返乡后2月2日被当地疫情防控单位采取医学隔离。患者于隔离后不久出现咳嗽,阵发性,干咳为主,偶可咳出黄色痰液等COVID-19相关临床症状,遂被当地新型冠状病毒肺炎定点医疗单位收治,后经市级新型冠状病毒肺炎诊治专家组远程视频会诊转入四川大学华西医院资阳医院。患者先后经历9次核酸检测,在前8次核酸检测均为阴性的情况下,于第9次核酸检测结果为阳性,2月21日最终确诊为新型冠状病毒肺炎。 相似文献