The complex evaluation of the larynx is profoundly supported by PMCT and the detection of the gas bubble sign as a diagnostic indicator of neck trauma. This relevant diagnostic finding might aid in not only post-mortem cases but also clinical cases, for patients who survive an assault to the neck. Advances in knowledge: (1) The gas bubble sign is a diagnostic indicator of neck trauma in not putrefied bodies. (2) PMCT supports evaluation of trauma to the neck in hanging tremendously. (3) The diagnostic finding of gas located at the laryngeal structures may not only aid in post-mortem cases but also clinical cases of people who survive an assault to the neck.
Neuroblastoma (NBL) and medulloblastoma (MB) are aggressive pediatric cancers which can benefit from therapies targeting gangliosides. Therefore, we compared the ganglioside profile of 9 MB and 14 NBL samples by thin layer chromatography and mass spectrometry. NBL had the highest expression of GD2 (median 0.54 nmol GD2/mg protein), and also expressed complex gangliosides. GD2-low samples expressed GD1a and were more differentiated. MB mainly expressed GD2 (median 0.032 nmol GD2/mg protein) or GM3. Four sonic hedgehog-activated (SHH) as well as one group 4 and one group 3 MBs were GD2-positive. Two group 3 MB samples were GD2-negative but GM3-positive. N-glycolyl neuraminic acid-containing GM3 was neither detected in NBL nor MB by mass spectrometry. Furthermore, a GD2-phenotype predicting two-gene signature (ST8SIA1 and B4GALNT1) was applied to RNA-Seq datasets, including 86 MBs and validated by qRT-PCR. The signature values were decreased in group 3 and wingless-activated (WNT) compared to SHH and group 4 MBs. These results suggest that while NBL is GD2-positive, only some MB patients can benefit from a GD2-directed therapy. The expression of genes involved in the ganglioside synthesis may allow the identification of GD2-positive MBs. Finally, the ganglioside profile may reflect the differentiation status in NBL and could help to define MB subtypes.
Objectives: Estimating the sex of decomposed corpses and skeletal remains of unknown individuals is one of the first steps in the identification process in forensic contexts.Although various studies have considered the femur for sex estimation, the focus has primarily been on a specific single or a handful of measurements rather than the entire shape of the bone. In this article, we use statistical shape modeling (SSM) for sex estimation. We hypothesize that the accuracy of sex estimation will be improved by using the entire shape.
Materials and Methods:For this study, we acquired a total of 61 femora from routine postmortem CT scans at the Institute for Forensic Medicine of the University of Zurich. The femora were extracted using segmentation technique. After building a SSM, we used the linear regression and nonlinear support vector machine technique for classification.Results: Using linear logistic regression and only the first principal component of the SSM, 76% of the femora were correctly classified by sex. Using the first five principal components, this value could be increased to 80%. Using nonlinear support vector machines and the first 20 principal components increased the rate of correctly classified femora to 87%.Discussion: Despite some limitations, the results obtained by using SSM for sex estimation in femur were promising and confirm the findings of other studies. Sex estimation accuracy, however, is not significantly improved over single or multiple linear measurements. Further research might improve the sex determination process in forensic anthropology by using SSM.
K E Y W O R D SCT, forensic anthropology, forensic imaging, sex estimation, statistical shape modeling
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