Age estimation based on visual parameters of the skin of cadavers

Three-Dimensional Bioprinted Skin Microrelief and Its Role in Skin Aging

Skin aging is a complex physiological process, in which cells and the extracellular matrix (ECM) interreact, which leads to a change in the mechanical properties of skin, which in turn affects the cell secretion and ECM deposition. The natural skin microrelief that exists from birth has rarely been taken into account when evaluating skin aging, apart from the common knowledge that microreliefs might serve as the starting point or initialize micro-wrinkles. In fact, microrelief itself also changes with aging. Does the microrelief have other, better uses? In this paper, owing to the fast-developing 3D printing technology, skin wrinkles with microrelief of different age groups were successfully manufactured using the Digital light processing (DLP) technology. The mechanical properties of skin samples with and without microrelief were tested. It was found that microrelief has a big impact on the elastic modulus of skin samples. In order to explore the role of microrelief in skin aging, the wrinkle formation was numerically analyzed. The microrelief models of different age groups were created using the modified Voronoi algorithm for the first time, which offers fast and flexible mesh formation. We found that skin microrelief plays an important role in regulating the modulus of the epidermis, which is the dominant factor in wrinkle formation. The wrinkle length and depth were also analyzed numerically for the first time, owing to the additional dimension offered by microrelief. The results showed that wrinkles are mainly caused by the modulus change of the epidermis in the aging process, and compared with the dermis, the hypodermis is irrelevant to wrinkling. Hereby, we developed a hypothesis that microrelief makes the skin adaptive to the mechanical property changes from aging by adjusting its shape and size. The native-like skin samples with microrelief might shed a light on the mechanism of wrinkling and also help with understanding the complex physiological processes associated with human skin.

Estimation of cadaveric age in crime scenes using Raman spectroscopy

The number of unidentified corpses has been increasing in recent years. There is a need for an objective and readily applicable method to estimate age, which is important information for identification. In previous reports, we reported that the protein folding ratio (RPF) of skin, as measured by Raman spectroscopy using cross sections of skin samples, is highly correlated with age. In this study, we investigated the possibility of estimating age by measuring Raman spectra from the skin surface of cadavers using a portable device. The resultant intercept, slope, and root mean square error were 97.9, - 63.7 (p < 0.0001), and 11.68, respectively. We evaluated this regression formula by using 10-fold cross-validation, resulting in a coefficient of determination of 0.51. The portable Raman spectrometer may be of assistance in estimating age at death of corpses at the scene of discovery.

A Raman algorithm to estimate human age from protein structural variations in autopsy skin samples: a protein biological clock

The recent increase of the number of unidentified cadavers has become a serious problem throughout the world. As a simple and objective method for age estimation, we attempted to utilize Raman spectrometry for forensic identification. Raman spectroscopy is an optical-based vibrational spectroscopic technique that provides detailed information regarding a sample’s molecular composition and structures. Building upon our previous proof-of-concept study, we measured the Raman spectra of abdominal skin samples from 132 autopsy cases and the protein-folding intensity ratio, R_PF, defined as the ratio between the Raman signals from a random coil an α-helix. There was a strong negative correlation between age and R_PF with a Pearson correlation coefficient of r = 0.878. Four models, based on linear (R_PF), squared (R_PF²), sex, and R_PF by sex interaction terms, were examined. The results of cross validation suggested that the second model including linear and squared terms was the best model with the lowest root mean squared error (11.3 years of age) and the highest coefficient of determination (0.743). Our results indicate that the there was a high correlation between the age and R_PF and the Raman biological clock of protein folding can be used as a simple and objective forensic age estimation method for unidentified cadavers.