Practices, Potential, and Perspectives for Detecting Predisease Using Raman Spectroscopy

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. The neurodevelopmental model was generated from a principal component analysis (PCA) with a Raman spectral dataset obtained from rat hippocampal neurons cultured for 120 days. In the present study, a DNB analysis was employed to identify the tipping point during the maturation of neurons. We reused the Raman spectral dataset obtained in our previous study. Based on our previous PCA findings, the dataset obtained from neurons after 8 days of culture was used in the DNB analysis. Raman spectral fluctuations were observed after 15 days of culturing. The Raman band of lactate (1048 cm-1) was identified as a DNB Raman band. These results suggest that lactate acts as an energy source and a factor affecting neuronal development. The present study also indicates that PCA effectively established the control group for a DNB analysis.

Spectral insights: Navigating the frontiers of biomedical and microbiological exploration with Raman spectroscopy

Raman spectroscopy (RS), a powerful analytical technique, has gained increasing recognition and utility in the fields of biomedical and biological research. Raman spectroscopic analyses find extensive application in the field of medicine and are employed for intricate research endeavors and diagnostic purposes. Consequently, it enjoys broad utilization within the realm of biological research, facilitating the identification of cellular classifications, metabolite profiling within the cellular milieu, and the assessment of pigment constituents within microalgae. This article also explores the multifaceted role of RS in these domains, highlighting its distinct advantages, acknowledging its limitations, and proposing strategies for enhancement.

Infrared Raman spectroscopy enables noninvasive biochemical assessment of skin tissue and the thermal stability

Raman-active modes of human skin and pork belly have been studied systematically by a near-infrared Raman spectrometer with an exciting laser of 1064 nm. The main components and quantitative determination of pork belly are extracted by fitting the Raman spectra with the normalized Raman spectra of biochemical reagents such as collagen, elastin, triolein, fibronectin, fibrin, and hyaluronic acid. It demonstrates that the main components and quantity are various at different locations of pork belly, while the main components of human skin are similar to those of pig skin. In a further step, the evolution of the heating time-dependent Raman modes of isolated pig skin has been investigated for the mechanism of burnt skin. One can find that the spatial structure and main components of skin have an excellent thermal stability in the temperature range from -120 to 200 ∘C, which is confirmed by the temperature dependent Raman spectra of isolated pig skin, microporous acellular dermal matrix (MADM) as well as their corresponding biochemical reagents (collagen, elastin, triolein, etc.). These results help understand the mechanism of the living skin burnt by fire or hot water, and supplies an alternative technology for surgeons to diagnose the depth of a burn injury in time.

New Possibilities for Evaluating the Development of Age-Related Pathologies Using the Dynamical Network Biomarkers Theory

Aging is the slowest process in a living organism. During this process, mortality rate increases exponentially due to the accumulation of damage at the cellular level. Cellular senescence is a well-established hallmark of aging, as well as a promising target for preventing aging and age-related diseases. However, mapping the senescent cells in tissues is extremely challenging, as their low abundance, lack of specific markers, and variability arise from heterogeneity. Hence, methodologies for identifying or predicting the development of senescent cells are necessary for achieving healthy aging. A new wave of bioinformatic methodologies based on mathematics/physics theories have been proposed to be applied to aging biology, which is altering the way we approach our understand of aging. Here, we discuss the dynamical network biomarkers (DNB) theory, which allows for the prediction of state transition in complex systems such as living organisms, as well as usage of Raman spectroscopy that offers a non-invasive and label-free imaging, and provide a perspective on potential applications for the study of aging.