The usefulness of measuring n-butyric acid concentration as a new indicator of blood decomposition in forensic autopsy

In forensic medicine, although various alcohols have been reported as indicators of decomposition in collected blood, no studies have examined short-chain fatty acids as indicators. In this study, the blood n-butyric acid concentration was quantified, and the association between n-butyric acid and decomposition was investigated to determine whether the detection of n-butyric acid could be a new indicator of decomposition. Among the forensic autopsies performed from 2016 to 2018 in our laboratory, the cases were divided into decomposed (n = 20) and non-decomposed (n = 20) groups based on macroscopic findings. Blood samples collected at the time of autopsy were derivatized with 3-nitrophenylhydrazine hydrochloride after solid-phase extraction. The n-butyric acid concentration was measured using liquid chromatography–tandem mass spectrometry. In addition, ethanol and n-propanol were measured using a gas chromatography-flame ionization detector. There was a significant difference (p < 0.01) in the concentrations of n-butyric acid between the decomposed and non-decomposed groups (0.343 ± 0.259 [0.030–0.973] and 0.003 ± 0.002 [0.001–0.007] mg/mL, respectively). In the decomposed group, n-butyric acid was detected at high concentrations, even in cases where n-propanol was low. These results suggest that n-butyric acid is more likely to be an indicator of blood decomposition than n-propanol.     

Demarcation of arteriopulmonary segments: a novel and effective method for the identification of pulmonary segments

ObjectiveEach pulmonary segment is an anatomical and functional unit. However, it is fundamentally difficult to precisely distinguish every pulmonary segment using the conventional pulmonary intersegmental planes from computed tomography images. Building arteriopulmonary segments is likely to be an effective way to identify pulmonary segments.MethodsThe thoracic computed tomography images of 40 patients were collected. The anatomic structures of interest were extracted in the transverse, sagittal, and coronal planes using the semi-automated segmentation tools provided by Amira software. The intrapulmonary vessels were subsequently segmented and reconstructed. The distributions of the pulmonary arteries, veins, and bronchi were observed. In patients with pulmonary masses, the mass was also reconstructed.ResultsThe three-dimensional reconstructed images showed the branches of the pulmonary artery ramified up to their eighth order covering the entire lung as well as evident intersegmental gaps without pulmonary arteries. The segmental artery was closely accompanied by the segmental bronchi in 486 pulmonary segments (90% of total number of segments). The size and spatial location of the pulmonary mass within a pulmonary segment were also clearly visible.ConclusionsDemarcation of arteriopulmonary segments can be used to precisely distinguish every pulmonary segment and provide its detailed anatomical structure before pulmonary segmentectomy.     

李延应用泽泻汤合温胆汤治疗舒张压高的临床经验

随着社会的发展,人类生活方式的改变,高血压病越来越高发,具有低龄化趋势,代谢综合征常伴随发生,此种情况下的高血压往往是以舒张压升高为主,临床表现常与“亚健康”状态混淆,未能引起患者甚至部分医生的重视,然而事实上越来越多的科学研究证实舒张压高之危害十分明显,不容忽视。尽管现代医学对舒张压高的病因及病理机制有明确的阐述,但是暂时没有特效的药物。李延教授在治疗高血压病方面有着丰富的临床经验,临床中运用泽泻汤合温胆汤加减治疗舒张压高之眩晕,切中病机,加减灵活,屡有良效。文中从中医角度阐述舒张压高的病因病机,介绍李师辨病辨证思路,组方用药特点,附三则典型验案,另加个人心得体会,以期为舒张压高的有效治疗提供思路。     

Epidemiological evidence of increased waist circumference,but not body mass index,associated with impaired baroreflex sensitivity

Although an inverse relationship between body mass index (BMI) and baroreflex sensitivity (BRS) was found, the effect of waist circumference (WC) on BRS is still inconclusive. The contradictory results of previous studies may be related to the heterogeneity and relatively small sample size of the subjects examined. The aim of this population-based study was to investigate whether the influence of increased WC is more detrimental to BRS than BMI. A total of 760 community dwellers were recruited and they were classified into Q1 (n = 189), Q2 (n = 183), Q3 (n = 192) and Q4 (n = 196) groups, based on WC quartiles. Spontaneous BRS was determined by spectral α coefficient method. Valsalva ratio was the longest RR interval after release of Valsalva maneuver divided by the shortest RR interval during maneuver. Cardiac autonomic function was calculated by power spectrum of heart rate in low and high frequency (LF, 0.04–0.15 Hz; HF, 0.15–0.40 Hz), and LF/HF ratio in supine position for five minutes. There were significant differences in spontaneous BRS and Valsalva ratio among different WC groups. In multivariate analysis, obesity was inversely associated with spontaneous BRS and Valsalva ratio. However, these inverse relationships became insignificant after further adjustment for WC quartiles. In contrast, Q4 vs. Q1, Q3 vs. Q1 and Q2 vs. Q1 of WC were inversely related to spontaneous BRS. Q4 vs. Q1 and Q3 vs. Q1 of WC were negatively associated with the Valsalva ratio. In conclusion, increased and even high-normal WC had a stronger adverse effect on BRS than BMI, independent of cardio-metabolic risk factors.     

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%.