Identifying the crucial tipping point in the maturation process of cultured neurons using Raman spectroscopy and a dynamic network biomarker (DNB) analysis.

The present study aimed to identify crucial tipping points during neuronal development in a post-mitotic state using Raman spectroscopy and a dynamic network biomarker (DNB) analysis. A DNB analysis is a promising method to detect early signal during state transition. We previously developed an in vitro model that mimics neuronal development.

Establishing Monoclonal Gammopathy of Undetermined Significance as an Independent Pre-Disease State of Multiple Myeloma Using Raman Spectroscopy, Dynamical Network Biomarker Theory, and Energy Landscape Analysis.

Multiple myeloma (MM) is a cancer of plasma cells. Normal (NL) cells are considered to pass through a precancerous state, such as monoclonal gammopathy of undetermined significance (MGUS), before transitioning to MM. In the present study, we acquired Raman spectra at three stages-834 NL, 711 MGUS, and 970 MM spectra-and applied the dynamical network biomarker (DNB) theory to these spectra.

Application of the Dynamical Network Biomarker Theory to Raman Spectra.

The dynamical network biomarker (DNB) theory detects the early warning signals of state transitions utilizing fluctuations in and correlations between variables in complex systems. Although the DNB theory has been applied to gene expression in several diseases, destructive testing by microarrays is a critical issue. Therefore, other biological information obtained by non-destructive testing is desirable; one such piece of information is Raman spectra measured by Raman spectroscopy.