Hanging is a common method of committing suicide and a routine task in medico-legal autopsies. The hanging mark is the most relevant external sign and its characteristics are well known, but, for unknown reasons, there are major differences in reports on internal findings. We retrospectively studied 228 consecutive cases of hanging deaths. A complete standard autopsy was performed for every case. We investigated the association between the characteristics of the hanging mark and the frequency of bone, cartilage, soft tissue, and vascular injuries with the mode of suspension. Most cases (75.3%) presented some kind of bone or cartilage fracture, but these were unrelated to any of the variables studied. Vascular lesions are clearly more infrequent: intimal injuries were found in the carotid artery (9.1%), the jugular vein (2.2%), and ruptures of the carotid adventitial layer (21.7%). These could be partially associated with the use of a hard fixed noose and body weight.

We report a case of cribriform-morular variant (C-MV) of papillary thyroid carcinoma (PTC) in a 27-year-old woman. In addition to conventional cytologic features of typical PTC, the fine-needle aspirate showed numerous epithelial cells with abundant, eosinophilic, very elongated cytoplasm. Microscopically, the tumor was encapsulated and highly cellular and exhibited a mixture of cribriform, follicular, papillary, trabecular, solid, and spindle cell patterns of growth, with morular foci showing peculiar nuclear clearing (biotin-rich nuclei). The cells were cuboidal or tall, with frequent nuclear pseudostratification and abundant eosinophilic cytoplasm. The nuclei were usually hyperchromatic, with grooving, pallor, and pseudoinclusions. Angioinvasion and foci of capsular invasion were observed. Immunohistochemically, the neoplastic cells showed reactivity for thyroglobulin, epithelial membrane antigen, low- and high-molecular-weight cytokeratins, vimentin, neuron-specific enolase, CD15, estrogen and progesterone receptors, and bcl-2 protein. Molecular genetic analysis of the APC gene revealed a mutation in exon 15 at codon 1309 in tumoral tissue but not in peripheral lymphocytes. These findings support a relationship between the morphologic pattern of the C-MV of PTC and the APC gene and the existence of this variant as a sporadic counterpart of familial adenomatous polyposis-associated thyroid carcinoma.

The estimation of stature from of a variety of bones is an important aspect of forensic work. In order to obtain reliable results, it is important to have comparative data obtained from the same population group as the skeletal remains. However, lack of up to date information on the population groups of Southern Europe makes the estimation of stature from bones in this area subject to possible error. In this study, the stature of 104 healthy adults from Spain was measured, and an anteroposterior teleradiograph of the right lower and the right upper limb of every subject in the study was made in order to measure the lengths of the femur, tibia, fibula, humerus, cubitus and ulna. Pearson's regression formulae were obtained for both limbs. In males, we found the femur to be the most accurate predictor of stature (R = 0.851), whereas in females best results were obtained with the tibia (R = 0.876).

The relation between the potassium concentration in the vitreous humor, [K+], and the postmortem interval has been studied by several authors. Many formulae are available and they are based on a correlation test and linear regression using the PMI as the independent variable and [K+] as the dependent variable. The estimation of the confidence interval is based on this formulation. However, in forensic work, it is necessary to use [K+] as the independent variable to estimate the PMI. Although all authors have obtained the PMI by direct use of these formulae, it is, nevertheless, an inexact approach, which leads to false estimations. What is required is to change the variables, obtaining a new equation in which [K+] is considered as the independent variable and the PMI as the dependent. The regression line obtained from our data is [K+] = 5.35 + 0.22 PMI, by changing the variables we get PMI = 2.58[K+] − 9.30. When only nonhospital deaths are considered, the results are considerably improved. In this case, we get [K+] = 5.60 + 0.17 PMI and, consequently, PMI = 3.92[K+] − 19.04.