scholarly journals Quantitative temporal interrogation in 3D of bioengineered human cartilage using multimodal label-free imaging

2018 ◽  
Vol 10 (10) ◽  
pp. 635-645 ◽  
Author(s):  
Catarina Costa Moura ◽  
Stuart A. Lanham ◽  
Tual Monfort ◽  
Konstantinos N. Bourdakos ◽  
Rahul S. Tare ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
Label Free ◽  
Human Cartilage ◽  
Phenotypic Characterisation

Multimodal label-free molecular imaging allows 3D phenotypic characterisation and quantitation of bioengineered cartilage non-invasively and non-destructively.

scholarly journals Optical Biomarkers for the Diagnosis of Osteoarthritis through Raman Spectroscopy: Radiological and Biochemical Validation Using Ex Vivo Human Cartilage Samples

Diagnostics ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 546
Author(s):  
Paula Casal-Beiroa ◽  
Vanesa Balboa-Barreiro ◽  
Natividad Oreiro ◽  
Sonia Pértega-Díaz ◽  
Francisco J. Blanco ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Articular Cartilage ◽  
Ex Vivo ◽  
Cartilage Degradation ◽  
Calcium Pyrophosphate ◽  
Calcium Pyrophosphate Dihydrate ◽  
Label Free ◽  
Molecular Fingerprint ◽  
Human Cartilage ◽  
Biochemical Validation

Osteoarthritis (OA) is the most common rheumatic disease, characterized by progressive articular cartilage degradation. Raman spectroscopy (RS) has been recently proposed as a label-free tool to detect molecular changes in musculoskeletal tissues. We used cartilage samples derived from human femoral heads to perform an ex vivo study of different Raman signals and ratios, related to major and minor molecular components of articular cartilage, hereby proposed as candidate optical biomarkers for OA. Validation was performed against the radiological Kellgren–Lawrence (K-L) grading system, as a gold standard, and cross-validated against sulfated glycosaminoglycans (sGAGs) and total collagens (Hyp) biochemical contents. Our results showed a significant decrease in sGAGs (SGAGs, A1063 cm−1/A1004 cm−1) and proteoglycans (PGs, A1375 cm−1/A1004 cm−1) and a significant increase in collagen disorganization (ColD/F, A1245 cm−1/A1270 cm−1), with OA severity. These were correlated with sGAGs or Hyp contents, respectively. Moreover, the SGAGs/HA ratio (A1063 cm−1/A960 cm−1), representing a functional matrix, rich in proteoglycans, to a mineralized matrix-hydroxyapatite (HA), was significantly lower in OA cartilage (K-L I vs. III–IV, p < 0.05), whilst the mineralized to collagenous matrix ratio (HA/Col, A960 cm−1/A920 cm−1) increased, being correlated with K-L. OA samples showed signs of tissue mineralization, supported by the presence of calcium crystals-related signals, such as phosphate, carbonate, and calcium pyrophosphate dihydrate (MGP, A960 cm−1/A1004 cm−1, MGC, A1070 cm−1/A1004 cm−1 and A1050 cm−1/A1004 cm−1). Finally, we observed an increase in lipids ratio (IL, A1450 cm−1/A1670 cm−1) with OA severity. As a conclusion, we have described the molecular fingerprint of hip cartilage, validating a panel of optical biomarkers and the potential of RS as a complementary diagnostic tool for OA.

scholarly journals Coarse Raman and optical diffraction tomographic imaging enable label-free phenotyping of isogenic breast cancer cells of varying metastatic potential

2020 ◽  
Author(s):  
Santosh Kumar Paidi ◽  
Vaani Shah ◽  
Piyush Raj ◽  
Kristine Glunde ◽  
Rishikesh Pandey ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Raman Spectroscopy ◽  
Molecular Imaging ◽  
Single Cell ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Metastatic Potential ◽  
Optical Diffraction ◽  
Multivariate Curve Resolution ◽  
Label Free

AbstractIdentification of the metastatic potential represents one of the most important tasks for molecular imaging of cancer. While molecular imaging of metastases has witnessed substantial progress as an area of clinical inquiry, determining precisely what differentiates the metastatic phenotype has proven to be more elusive underscoring the need to marry emerging imaging techniques with tumor biology. In this study, we utilize both the morphological and molecular information provided by 3D optical diffraction tomography and Raman spectroscopy, respectively, to propose a label-free route for optical phenotyping of cancer cells at single-cell resolution. By using an isogenic panel of cell lines derived from MDA-MB-231 breast cancer cells that vary in their metastatic potential, we show that 3D refractive index tomograms can capture subtle morphological differences among the parental, circulating tumor cells, and lung metastatic cells. By leveraging the molecular specificity of Raman spectroscopy, we demonstrate that coarse Raman microscopy is capable of rapidly mapping a sufficient number of cells for training a random forest classifier that can accurately predict the metastatic potential of cells at a single-cell level. We also leverage multivariate curve resolution – alternating least squares decomposition of the spectral dataset to demarcate spectra from cytoplasm and nucleus, and test the feasibility of identifying metastatic phenotypes using the spectra only from the cytoplasmic and nuclear regions. Overall, our study provides a rationale for employing coarse Raman mapping to substantially reduce measurement time thereby enabling the acquisition of reasonably large training datasets that hold the key for label-free single-cell analysis and, consequently, for differentiation of indolent from aggressive phenotypes.

scholarly journals Introduction to Infrared and Raman-Based Biomedical Molecular Imaging and Comparison with Other Modalities

Molecules ◽  
2020 ◽  
Vol 25 (23) ◽  
pp. 5547
Author(s):  
Carlos F. G. C. Geraldes
Keyword(s):  
Computed Tomography ◽  
Molecular Imaging ◽  
Single Photon ◽  
Ex Vivo ◽  
Photon Emission ◽  
Raman Imaging ◽  
Emission Computed Tomography ◽  
Label Free ◽  
Advantages And Disadvantages

Molecular imaging has rapidly developed to answer the need of image contrast in medical diagnostic imaging to go beyond morphological information to include functional differences in imaged tissues at the cellular and molecular levels. Vibrational (infrared (IR) and Raman) imaging has rapidly emerged among the molecular imaging modalities available, due to its label-free combination of high spatial resolution with chemical specificity. This article presents the physical basis of vibrational spectroscopy and imaging, followed by illustration of their preclinical in vitro applications in body fluids and cells, ex vivo tissues and in vivo small animals and ending with a brief discussion of their clinical translation. After comparing the advantages and disadvantages of IR/Raman imaging with the other main modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography/single-photon emission-computed tomography (PET/SPECT), ultrasound (US) and photoacoustic imaging (PAI), the design of multimodal probes combining vibrational imaging with other modalities is discussed, illustrated by some preclinical proof-of-concept examples.

Label-free molecular imaging

2014 ◽  
Author(s):  
Junqi Zhang ◽  
Qi Li ◽  
Rongxin Fu ◽  
Tongzhou Wang ◽  
Ruliang Wang ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
Label Free

Label-free molecular imaging of immunological synapses between dendritic and T cells by Raman micro-spectroscopy

The Analyst ◽  
2010 ◽  
Vol 135 (12) ◽  
pp. 3205 ◽  
Author(s):  
Alina Bogumila Zoladek ◽  
Ramneek Kaur Johal ◽  
Samuel Garcia-Nieto ◽  
Flavius Pascut ◽  
Kevin M. Shakesheff ◽  
...  
Keyword(s):  
T Cells ◽  
Molecular Imaging ◽  
Label Free ◽  
Immunological Synapses

scholarly journals Label-free in vivo molecular imaging of underglycosylated mucin-1 expression in tumour cells

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Xiaolei Song ◽  
Raag D. Airan ◽  
Dian R. Arifin ◽  
Amnon Bar-Shir ◽  
Deepak K. Kadayakkara ◽  
...  
Keyword(s):  
Molecular Imaging ◽  
Tumour Cells ◽  
Label Free ◽  
Mucin 1

scholarly journals Label-free molecular imaging of bacterial communities of the opportunistic pathogen Pseudomonas aeruginosa

2016 ◽  
Author(s):  
Nameera Baig ◽  
Sneha Polisetti ◽  
Nydia Morales-Soto ◽  
Sage J. B. Dunham ◽  
Jonathan V. Sweedler ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Molecular Imaging ◽  
Bacterial Communities ◽  
Opportunistic Pathogen ◽  
Label Free
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