A case of sudden cardiac death due to mitochondrial disease

A 25-year-old, emaciated man without medical treatment was found to have died suddenly at home by his mother. At autopsy, there were no injuries to his body, but significant circulatory insufficiency was observed. Electron microscopy revealed abnormal mitochondria in cells of the cardiac conduction system. The conduction system was filled with mitochondrial size abnormalities and mitochondrial cristae abnormalities. No notable abnormal findings were observed in other organs. Genetic examination of the blood revealed the mitochondrial pathogenetic variant m.3243A>G. Epileptic seizures, diabetic ketoacidosis, and hyperosmolar hyperglycemic state were unlikely to be the cause of sudden death. The cause of death was diagnosed as arrhythmia possibly induced by the failure of the cardiac conduction system due to mitochondrial disease. This is a rare case of sudden death caused by an accumulation of abnormal mitochondria in the cardiac conduction system.     

舒芬太尼在肾母细胞瘤患儿术后镇痛中的应用效果及对患儿免疫功能的影响

目的探讨舒芬太尼在肾母细胞瘤患儿术后镇痛中的应用效果及对患儿免疫功能的影响。方法采用随机数字表法将42例肾母细胞瘤患儿分为低剂量、中剂量和高剂量组,每组14例,低剂量组、中剂量组、高剂量组患儿术后舒芬太尼镇痛剂量分别为1.0、2.5、4.0μg/kg。术后6、24、48 h,采用中文版儿童疼痛行为量表(FLACC)评估三组患儿的镇痛效果,以及不良反应发生情况;麻醉前和术后1、24、72 h,检测三组患儿免疫功能指标,包括免疫球蛋白(Ig)G、IgA、IgM。结果术后6、24、48 h,中剂量组、高剂量组患儿FLACC评分均低于低剂量组患儿,差异均有统计学意义(P﹤0.05)。术后1、24、72 h,低剂量组患儿IgG、IgA、IgM水平均低于本组麻醉前,差异均有统计学意义(P﹤0.05);术后1、24 h,中剂量组和高剂量组患儿IgG、IgA、IgM水平均低于本组麻醉前,差异均有统计学意义(P﹤0.05),但术后72 h,中剂量组和高剂量组患儿IgG、IgA、IgM水平与麻醉前比较,差异均无统计学意义(P﹥0.05)。低剂量组患儿未发生不良反应,中剂量组患儿发生恶心1例,高剂量组患儿发生恶心5例、呕吐3例。结论2.5μg/kg的舒芬太尼在肾母细胞瘤患儿术后镇痛中效果明显,且对患儿的免疫系统发挥一定的保护作用,可以减轻患儿术后免疫功能抑制。     

莫西沙星联合信必可都保对AECOPD疗效及免疫炎症反应的影响

目的探讨维生素D(VitD)联合鱼油对糖尿病前期(PDM)患者糖脂代谢、胰岛β细胞功能的影响。 方法选取PDM患者132例,随机均分为联合组(VitD+鱼油)、VitD组(VitD)和对照组(不干预)。比较各组糖脂代谢、胰岛β细胞功能、炎症反应、血管内皮功能等指标。 结果与干预前比较,干预后联合组甘油三酯降低,白细胞介素-10增高(P＜0.05),联合组和VitD组低密度脂蛋白胆固醇、肿瘤坏死因子-α、胰岛素抵抗指数、前列腺素E2、瘦素、抵抗素降低(P＜0.05),空腹胰岛素、胰岛β细胞功能指数、脂联素增高(P＜0.05),且联合组改善更为明显(P＜0.05)。 结论维生素D联合鱼油治疗PDM患者可改善其脂代谢和胰岛功能相关指标,具有一定临床应用价值。     

First Japanese autopsy case showing LRRK2 mutation G2019S and TDP-43 proteinopathy

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.     

Morphological imaging and CT histogram analysis to differentiate pancreatic neuroendocrine tumor grade 3 from neuroendocrine carcinoma

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.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

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%.