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1.
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. 相似文献
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《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
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This study evaluated the genetic variation of 17 autosomal short tandem repeat (STR) loci included in the PowerPlex® 18D Kit. Samples of 562 unrelated healthy Lahu individuals living in Yunnan Province in southwestern China were investigated. The data were analyzed to provide information on allele frequencies and other statistical parameters relevant to the forensic population. Of the 17 loci, 16 reached the Hardy–Weinberg equilibrium after Bonferroni correction. A total of 176 alleles were identified in 17 STR loci, and allele frequencies ranged from 0.000 890 to 0.578 292. The combined discrimination power (CPD) and probability of excluding paternity (CPE) of the 17 STR loci were 0.999 999 999 999 999 999 489 and 0.999 998 301 753 122. The genetic relationships among 28 populations were also estimated. 相似文献
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《Drug metabolism and pharmacokinetics》2019,34(1):87-94
The purpose of this study was to elucidate the involvement of Mate1 in the tubular secretion of trimethoprim and saturation of Mate1-mediated efflux to address the mechanisms underlying the pharmacokinetic drug interactions with trimethoprim. Trimethoprim is a more potent inhibitor of MATE2-K than MATE1 with Ki values (μM) of 0.030–0.28 and 2.4–5.9, respectively. Trimethoprim is a substrate of human MATE1 and MATE2-K with Km values of 2.3 ± 0.9 and 0.018 ± 0.004 μM, and mouse Mate1, but not human OCT2, mouse Oct1 and Oct2. Pyrimethamine significantly reduced the renal clearance (CLR) of trimethoprim (mL/min/kg) from 40.0 ± 5.1 to 20.1 ± 3.7 (p < 0.05). Trimethoprim was given to mice at three infusion rates (150, 500, and 1500 nmol/min/kg). Together with an increase in the plasma concentrations of trimethoprim, the CLR (mL/min/kg) of trimethoprim decreased to 25.9 ± 3.2, 13.5 ± 5.7, and 8.92 ± 1.50 at the respective rates. Trimethoprim decreased the CLR of rhodamine 123 in an infusion rate-dependent manner: 11.5 ± 1.3 (control), 5.17 ± 1.55, 1.31 ± 0.50, and 0.532 ± 0.180. These results suggest that Mate1 mediates the tubular secretion of trimethoprim, and at therapeutic doses, MATEs-mediated efflux can be saturated, and thereby, cause drug interactions with other MATE substrates. 相似文献
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董频 《山东医大基础医学院学报》2006,(4)
目的:运用软硬腭前移的手术方法扩大鼻咽下口,改善因鼻咽部狭小致阻塞性睡眠呼吸暂停综合征患者的呼吸暂停症状。方法:手术切除硬腭后份使其缩短、悬雍垂软腭成形并将软腭拉向前,扩大鼻咽下口。结果:患者术后自觉症状及客观评价疗效满意。结论:软硬腭前移鼻咽下口扩大显著改善鼻咽下口狭小导致的阻塞性睡眠呼吸暂停患者的症状。 相似文献
10.
Melissa Terpstra Ivan Tkác Raghavendra Rao Rolf Gruetter 《Magnetic resonance in medicine》2006,55(5):979-983
Both ultrashort echo-time STEAM and MEGA-PRESS-edited spectroscopy were used to validate noninvasive quantification of vitamin C (ascorbate) in the developing rat brain, where changes in ascorbate concentration have been reported. Despite strong overlap with resonances from glutamine, glutamate, glutathione, and macromolecules, reliable quantification of ascorbate (Cramer-Rao lower bounds<0.2 micromol/g) by LCModel analysis of STEAM (TE=2 ms) spectra was possible at 9.4 T. Ascorbate concentrations quantified from the STEAM spectra were in very good agreement with concentrations calculated from fully resolved ascorbate resonances in MEGA-PRESS-edited spectra measured from identical volumes of interest. Ascorbate concentrations measured using STEAM decreased with increasing postnatal rat age, in agreement with published brain ascorbate concentrations measured in vitro using high-performance liquid chromatography (HPLC). 相似文献