Label-free cell membrane detection by Raman spectroscopy using biocompatible gold nanostructure microscale arrays on a ferroelectric template

2017 ◽  
Author(s):  
Rusul M. Al-Shammari ◽  
Nebras Alattar ◽  
Michele Manzo ◽  
Katia Gallo ◽  
Brian J. Rodriguez ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Cell Membrane ◽  
Free Cell ◽  
Label Free ◽  
Gold Nanostructure

Raman spectroscopy-based label-free cell identification using wavelet transform and support vector machine

RSC Advances ◽  
2016 ◽  
Vol 6 (55) ◽  
pp. 50027-50033 ◽  
Author(s):  
S. Bakhtiaridoost ◽  
H. Habibiyan ◽  
S. Muhammadnejad ◽  
M. Haddadi ◽  
H. Ghafoorifard ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Raman Spectroscopy ◽  
Wavelet Transform ◽  
Raman Spectra ◽  
Free Cell ◽  
Support Vector ◽  
Label Free ◽  
Cell Identification ◽  
Rare Cells

Wavelet transform and SVM applied to Raman spectra makes a powerful and accurate tool for identification of rare cells such as CTCs.

scholarly journals Subtyping on Live Lymphoma Cell Lines by Raman Spectroscopy

Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 546
Author(s):  
Klytaimnistra Katsara ◽  
Konstantina Psatha ◽  
George Kenanakis ◽  
Michalis Aivaliotis ◽  
Vassilis M. Papadakis
Keyword(s):  
Raman Spectroscopy ◽  
Quantitative Estimation ◽  
Free Cell ◽  
Spectroscopic Technique ◽  
Lymphoma Cell ◽  
Label Free ◽  
Limited Information ◽  
Non Invasive ◽  
Minimal Sample ◽  
Cell Measurement

Raman spectroscopy is a well-defined spectroscopic technique sensitive to the molecular vibrations of materials, since it provides fingerprint-like information regarding the molecular structure of the analyzed samples. It has been extensively used for non-destructive and label-free cell characterization, particularly in the qualitative and quantitative estimation of amino acids, lipids, nucleic acids, and carbohydrates. Lymphoma cell classification is a crucial task for accurate and prompt lymphoma diagnosis, prognosis, and treatment. Currently, it is mostly based on limited information and requires costly and time-consuming approaches. In this work, we are proposing a fast characterization and differentiation methodology of lymphoma cell subtypes based on Raman spectroscopy. The study was performed in the temperature range of 15–37 °C to identify the best cell measurement conditions. The proposed methodology is fast, accurate, and requires minimal sample preparation, resulting in a potentially promising, non-invasive strategy for early and accurate cell lymphoma characterization.

EXPRESS: Characterization of Drug Resistance in Chronic Myeloid Leukemia Cells Based on Laser Tweezers Raman Spectroscopy

2021 ◽  
pp. 000370282110245
Author(s):  
Qian Zhang ◽  
Minlu Ye ◽  
Lingyan Wang ◽  
Dongmei Jiang ◽  
Shuting Yao ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Chronic Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
K562 Cells ◽  
Laser Tweezers ◽  
Label Free ◽  
Multivariate Statistical ◽  
Analytical Strategy ◽  
Specificity And Sensitivity ◽  
Acid Protein

Multidrug resistance (MDR) is highly associated with poor prognosis of chronic myeloid leukemia (CML). This work aims to explore whether the laser tweezers Raman spectroscopy (LTRS) could be practical in separating adriamycin (ADR) resistance CML cells K562/ADR from its parental cells K562, and to explore the potential mechanisms. Detection of LTRS initially reflected the spectral differences caused by chemoresistance including bands assigned to carbohydrates, amino acid, protein, lipids and nucleic acid. In addition, principal components analysis (PCA) as well as the classification and regression trees (CRT) algorithms showed that the specificity and sensitivity were above 90%. Moreover, the band data-based CRT model and receiver operating characteristic (ROC) curve further determined some important bands and band intensity ratios to be reliable indexes in discriminating K562 chemoresistance status. Finally, we highlighted three metabolism pathways correlated with chemoresistance. This work demonstrates that the label-free LTRS analysis combined with multivariate statistical analyses have great potential to be a novel analytical strategy at the single-cell level for rapid evaluation the chemoresistance status of K562 cells.

Label-free cell phenotypic study of opioid receptors and discovery of novel mu opioid ligands from natural products

2021 ◽  
Vol 270 ◽  
pp. 113872
Author(s):  
Tao Hou ◽  
Fangfang Xu ◽  
Xingrong Peng ◽  
Han Zhou ◽  
Xiuli Zhang ◽  
...  
Keyword(s):  
Natural Products ◽  
Opioid Receptors ◽  
Free Cell ◽  
Label Free ◽  
Mu Opioid ◽  
Opioid Ligands

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 Applications of Vibrational Spectroscopy for Analysis of Connective Tissues

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 922
Author(s):  
William Querido ◽  
Shital Kandel ◽  
Nancy Pleshko
Keyword(s):  
Raman Spectroscopy ◽  
Vibrational Spectroscopy ◽  
Near Infrared ◽  
Ex Vivo ◽  
Biological Tissues ◽  
Label Free ◽  
Connective Tissues ◽  
Bone Properties ◽  
Composition And Structure

Advances in vibrational spectroscopy have propelled new insights into the molecular composition and structure of biological tissues. In this review, we discuss common modalities and techniques of vibrational spectroscopy, and present key examples to illustrate how they have been applied to enrich the assessment of connective tissues. In particular, we focus on applications of Fourier transform infrared (FTIR), near infrared (NIR) and Raman spectroscopy to assess cartilage and bone properties. We present strengths and limitations of each approach and discuss how the combination of spectrometers with microscopes (hyperspectral imaging) and fiber optic probes have greatly advanced their biomedical applications. We show how these modalities may be used to evaluate virtually any type of sample (ex vivo, in situ or in vivo) and how “spectral fingerprints” can be interpreted to quantify outcomes related to tissue composition and quality. We highlight the unparalleled advantage of vibrational spectroscopy as a label-free and often nondestructive approach to assess properties of the extracellular matrix (ECM) associated with normal, developing, aging, pathological and treated tissues. We believe this review will assist readers not only in better understanding applications of FTIR, NIR and Raman spectroscopy, but also in implementing these approaches for their own research projects.

scholarly journals Towards automated cancer screening: Label-free classification of fixed cell samples using wavelength modulated Raman spectroscopy

2018 ◽  
Vol 11 (4) ◽  
pp. e201700244 ◽  
Author(s):  
Lana Woolford ◽  
Mingzhou Chen ◽  
Kishan Dholakia ◽  
C. Simon Herrington
Keyword(s):  
Raman Spectroscopy ◽  
Cancer Screening ◽  
Label Free ◽  
Fixed Cell ◽  
Free Classification
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