Noninvasive detection of collagen regeneration after an isotretinoin treatment and ablative laser surgery in patients with acne scars by Raman spectroscopy

2018 ◽  
Author(s):  
Miguel Ghebre Ramírez-Elías ◽  
Francisco Pérez-Atamoros ◽  
Rodrigo Cabrera-Alonso ◽  
Fernando Sebastián Chiwo González ◽  
Carlos Eduardo Osornio-Martínez ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Laser Surgery ◽  
Noninvasive Detection ◽  
Acne Scars ◽  
Ablative Laser

Comment on “Use of Raman spectroscopy in the assessment of skin after CO 2 ablative fractional laser surgery on acne scars”

2019 ◽  
Vol 26 (1) ◽  
pp. 146-147
Author(s):  
Ivan A. Bratchenko ◽  
Lyudmila A. Bratchenko ◽  
Dmitry N. Artemyev ◽  
Yulia A. Khristoforova
Keyword(s):  
Raman Spectroscopy ◽  
Laser Surgery ◽  
Fractional Laser ◽  
Acne Scars ◽  
Ablative Fractional Laser

Use of Raman spectroscopy in the assessment of skin after CO 2 ablative fractional laser surgery on acne scars

2019 ◽  
Author(s):  
Fernando Sebastian Chiwo ◽  
Edgar Guevara ◽  
Miguel Ghebre Ramírez‐Elías ◽  
Claudio Cayetano Castillo‐Martínez ◽  
Carlos Eduardo Osornio‐Martínez ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Laser Surgery ◽  
Fractional Laser ◽  
Acne Scars ◽  
Ablative Fractional Laser

scholarly journals RAMAN SPECTROSCOPY OF HUMAN HEMOGLOBIN FOR DIABETES DETECTION

2014 ◽  
Vol 07 (01) ◽  
pp. 1350051 ◽  
Author(s):  
JUQIANG LIN ◽  
JINYONG LIN ◽  
ZUFANG HUANG ◽  
PENG LU ◽  
JING WANG ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Roc Curve ◽  
Principal Component ◽  
Diagnostic Algorithm ◽  
Noninvasive Detection ◽  
Human Hemoglobin ◽  
Linear Discriminant ◽  
Patients With Diabetes ◽  
The Difference ◽  
Diabetes Monitoring

Glycated hemoglobin (HbA1c) has been increasingly accepted as the gold standard for diabetes monitoring. In this study, Raman spectroscopy was tentatively employed for human hemoglobin (Hb) biochemical analysis aimed at developing a simple blood test for diabetes monitoring. Raman spectroscopy measurements were performed on hemoglobin samples of patients (n = 39) with confirmed diabetes and healthy volunteers (n = 37). The tentative assignments of the measured Raman bands were performed to compare the difference between these two groups. Meanwhile, principal component analysis (PCA) combined with linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification between normal controls and patients with diabetes. As a result, the spectral features of these two groups demonstrated two distinct clusters with a sensitivity and specificity of 92.3% and 73%, respectively. Then the effectiveness of the diagnostic algorithm based on PCA-LDA technique was confirmed by receiver operating characteristic (ROC) curve. The area under the ROC curve was 0.92, indicating a good diagnostic result. In summary, our preliminary results demonstrate that proposing Raman spectroscopy can provide a significant potential for the noninvasive detection of diabetes.

scholarly journals Raman Spectroscopy and Cancer Diagnosis

Proceedings ◽  
2019 ◽  
Vol 27 (1) ◽  
pp. 15
Author(s):  
Barbara Bravo ◽  
Luigi Ciani ◽  
Mario D’Acunto
Keyword(s):  
Raman Spectroscopy ◽  
Cancer Diagnosis ◽  
Bone Tumors ◽  
Noninvasive Detection ◽  
Osteosarcoma Cells ◽  
Detection Capability ◽  
High Chemical ◽  
Molecular Systems ◽  
Cartilaginous Tumors ◽  
Screening And Diagnosis

Raman spectroscopy is a technique based on inelastic scattering of molecular systems when illuminated by monochromatic radiation. Owing to its high chemical specificity and noninvasive detection capability, in the last decade, Raman scattering has found wide application in cancer screening and diagnosis. In this paper; we describe recent results obtained by applying Raman spectroscopy to osteosarcoma and chondrosarcoma; the two main bone tumors. The results show the remarkable potential of Thermo Scientific™ DXR™2 microscope to discriminate between subcellular components inside osteo-differentiated osteoblasts and osteosarcoma cells or; at level of tissues; to discriminate chondrogenic tumors giving the possibility to grade the level of malignancy the cartilaginous tumors under investigation.

scholarly journals Raman Spectroscopy Applied to the Noninvasive Detection of Monosodium Urate Crystal Deposits

2015 ◽  
Vol 8 ◽  
pp. CMAMD.S29061 ◽  
Author(s):  
Declan J. Curran ◽  
Laurence Rubin ◽  
Mark R. Towler
Keyword(s):  
Raman Spectroscopy ◽  
Signal Processing ◽  
Healthy Subject ◽  
Metatarsophalangeal Joint ◽  
Noninvasive Detection ◽  
Monosodium Urate ◽  
Raman Spectrometer ◽  
Healthy Control ◽  
Urate Crystal ◽  
Msu Crystals

An off-the-shelf Raman Spectrometer (RS) was used to noninvasively determine the presence of monosodium urate (MSU) crystals on the metatarsophalangeal joint (MTPJ) of a single gout sufferer. The spectrum sourced from the clinically diagnosed gout sufferer was compared to that sourced from an age-matched healthy subject scanned using the same protocol. Minimal signal processing was conducted on both spectra. Peaks characteristic of MSU crystals were evident on the spectrum sourced from the gout sufferer and not on the spectrum from the healthy control.

scholarly journals Noninvasive Detection of Inflammatory Changes in White Adipose Tissue by Label-Free Raman Spectroscopy

2016 ◽  
Vol 88 (4) ◽  
pp. 2140-2148 ◽  
Author(s):  
Abigail S. Haka ◽  
Erika Sue ◽  
Chi Zhang ◽  
Priya Bhardwaj ◽  
Joshua Sterling ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Adipose Tissue ◽  
White Adipose Tissue ◽  
Noninvasive Detection ◽  
Label Free ◽  
Inflammatory Changes

scholarly journals Noninvasive Detection of Differential Water Content Inside Biological Samples Using Deep Raman Spectroscopy

2020 ◽  
Vol 92 (14) ◽  
pp. 9449-9453
Author(s):  
Adrian Ghita ◽  
Thomas Hubbard ◽  
Pavel Matousek ◽  
Nicholas Stone
Keyword(s):  
Raman Spectroscopy ◽  
Water Content ◽  
Biological Samples ◽  
Noninvasive Detection

Noninvasive detection of glucose using Raman spectroscopy

1999 ◽  
Author(s):  
Johannes S. Kanger ◽  
Frits F. M. de Mul ◽  
Cees Otto
Keyword(s):  
Raman Spectroscopy ◽  
Noninvasive Detection
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