A novel method for post-mortem interval estimation based on tissue nano-mechanics

  • Fabio De-Giorgio
  • Matteo Nardini
  • Federica Foti
  • Eleonora Minelli
  • Massimiliano Papi
  • Ernesto d’Aloja
  • Vincenzo L. PascaliEmail author
  • Marco De SpiritoEmail author
  • Gabriele Ciasca
Short Communication


Forensic estimation of post-mortem interval relies on different methods, most of which, however, have practical limitations or provide insufficient results, still lacking a gold standard method. In order to better understand the phenomenon of rigor mortis and its applicability to the post-mortem interval estimation, we decided to use atomic force microscopy, a tool often employed to measure mechanical properties of adherent cells. Thus, we surgically removed skeletal muscle samples of three forensic cases from 0 to 120 h post-mortem and quantitatively evaluate two parameters: the Young’s modulus (E), which gives information about the sample stiffness, and the hysteresis (H), which estimates the contribution of viscous forces. Despite being a preliminary study, the obtained results show that the temporal behavior of E well correlates with the expected evolution of rigor mortis between 0 and 48 h post-mortem, and then monotonically decreases over time. Unfortunately, it is strongly affected by inter-individual variability. However, we found that H provides measurable data along a time-dependent curve back to the starting point, and these data measured on different subjects collapse onto a single master curve, getting rid of the inter-individual variability. Although a larger sampling should be performed to improve the result reliability, this finding is strongly suggestive that the evaluation of rigor mortis should involve the measure of the nanoscale dissipative behavior of muscular tissues.


Time since death Rigor mortis Atomic force microscope Nano-mechanics 



Post-mortem interval


Atomic force microscope


Hours post-mortem


Supplementary material

414_2019_2034_MOESM1_ESM.jpg (87 kb)
Figure S1 Correlation plots between E and H for the three subjects with the corresponding Pearson’s correlation coefficients. A linear trend was fitted to data (black continuous line) and a set of three different slopes (m) and intercepts (q) were obtained, namely m = (−3,4 ± 0,9) 102 kPa, q = (1,9 ± 0,4) 102 kPa (subject 1), m = (−3,6 ± 1,2) 104 kPa, q = (2,0 ± 0,6) 104 kPa (subject 2) and m = (−1,1 ± 0,1) 105 kPa, q = (5,6 ± 0,6) 104 kPa (subject 3). (JPG 86 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Fabio De-Giorgio
    • 1
  • Matteo Nardini
    • 2
  • Federica Foti
    • 1
  • Eleonora Minelli
    • 2
  • Massimiliano Papi
    • 2
  • Ernesto d’Aloja
    • 3
  • Vincenzo L. Pascali
    • 1
    Email author
  • Marco De Spirito
    • 2
    Email author
  • Gabriele Ciasca
    • 2
  1. 1.Institute of Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCSUniversità Cattolica del Sacro CuoreRomeItaly
  2. 2.Institute of Physics, Fondazione Policlinico Universitario A. Gemelli IRCCSUniversità Cattolica del Sacro CuoreRomeItaly
  3. 3.Department of Medical Sciences and Public HealthUniversity of CagliariCagliariItaly

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