Raman microspectroscopy (rms) was used to identify, image, and quantify potential molecular markers for label-free monitoring the differentiation status of live neural stem cells (NSCs) in vitro. Label-free noninvasive techniques for characterization of NCSs in vitro are needed as they can be developed for real-time monitoring of live cells. Principal component analysis (PCA) and linear discriminant analysis (LDA) models based on Raman spectra of undifferentiated NSCs and NSC-derived glial cells enabled discrimination of NSCs with 89.4% sensitivity and 96.4% specificity. The differences between Raman spectra of NSCs and glial cells indicated that the discrimination of the NSCs was based on higher concentration of nucleic acids in NSCs. Spectral images corresponding to Raman bands assigned to nucleic acids for individual NSCs and glial cells were compared with fluorescence staining of cell nuclei and cytoplasm to show that the origin of the spectral differences were related to cytoplasmic RNA. On the basis of calibration models, the concentration of the RNA was quantified and mapped in individual cells at a resolution of ~700 nm. The spectral maps revealed cytoplasmic regions with concentrations of RNA as high as 4 mg/mL for NSCs while the RNA concentration in the cytoplasm of the glial cells was below the detection limit of our instrument (~1 mg/mL). In the light of recent reports describing the importance of the RNAs in stem cell populations, we propose that the observed high concentration of cytoplasmic RNAs in NSCs compared to glial cells is related to the repressed translation of mRNAs, higher concentrations of large noncoding RNAs in the cytoplasm as well as their lower cytoplasm volume. While this study demonstrates the potential of using rms for label-free assessment of live NSCs in vitro, further studies are required to establish the exact origin of the increased contribution of the cytoplasmic RNA.
We investigate the potential of Raman microspectroscopy (RMS) for automated evaluation of excised skin tissue during Mohs micrographic surgery (MMS). The main aim is to develop an automated method for imaging and diagnosis of basal cell carcinoma (BCC) regions. Selected Raman bands responsible for the largest spectral differences between BCC and normal skin regions and linear discriminant analysis (LDA) are used to build a multivariate supervised classification model. The model is based on 329 Raman spectra measured on skin tissue obtained from 20 patients. BCC is discriminated from healthy tissue with 90+/-9% sensitivity and 85+/-9% specificity in a 70% to 30% split cross-validation algorithm. This multivariate model is then applied on tissue sections from new patients to image tumor regions. The RMS images show excellent correlation with the gold standard of histopathology sections, BCC being detected in all positive sections. We demonstrate the potential of RMS as an automated objective method for tumor evaluation during MMS. The replacement of current histopathology during MMS by a "generalization" of the proposed technique may improve the feasibility and efficacy of MMS, leading to a wider use according to clinical need.
The aim of this research was to develop a novel approach to probe non-invasively the composition of inorganic chemicals buried deep in large volume biological samples. The method is based on advanced Transmission Raman Spectroscopy (TRS) permitting chemical specific detection within a large sampling volume. The approach could be beneficial to chemical identification of the breast calcifications detected during mammographic X-ray procedures. The chemical composition of a breast calcification reflects the pathology of the surrounding tissue, malignant or benign and potentially the grade of malignancy. However, this information is not available from mammography, leading to excisional biopsy and histopathological assessment for a definitive diagnosis. Here we present, for the first time, a design of a new high performance deep Raman instrument and demonstrate its capability to detect type II calcifications (calcium hydroxyapatite) at clinically relevant concentrations and depths of around 40 mm in phantom tissue. This is around double the penetration depth achieved with our previous instrument design and around two orders of magnitude higher than that possible when using conventional Raman spectroscopy.
Label-free imaging using Raman micro-spectroscopy (RMS) was used to characterize the spatio-temporal molecular changes of T. gondii tachyzoites and their host cell microenvironment. Raman spectral maps were recorded from isolated T. gondii tachyzoites and T. gondii-infected human retinal cells at 6 hr, 24 hr and 48 hr postinfection. Principal component analysis (PCA) of the Raman spectra of paraformaldehyde-fixed infected cells indicated a significant increase in the amount of lipids and proteins in the T. gondii tachyzoites as the infection progresses within host cells. These results were confirmed by experiments carried out on live T. gondii-infected cells and were correlated with an increase in the concentration of proteins and lipids required for the replication of this intracellular pathogen. These findings demonstrate the potential of RMS to characterize time-and spatially-dependent molecular interactions between intracellular pathogens and the host cells. Such information may be useful for discovery of pharmacological targets or screening compounds with potential neuroprotective activity for eminent effects of changes in brain infection control practices. 2
Raman microscopy was used as a label-free method to study the mineralisation of bone nodules formed by mesenchymal stem cells cultured in osteogenic medium in vitro. Monitoring individual bone nodules over 28 days revealed temporal and spatial changes in the crystalline phase of the hydroxyapatite components of the nodules.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.