Label-free Raman spectroscopy: A potential tool for early diagnosis of diabetic keratopathy

Guan, Hongxin; Huang, Chunyan; Lu, Dechan; Chen, Guannan; Lin, Juqiang; Hu, Jianzhang; He, Yan; Huang, Zufang

doi:10.1016/j.saa.2021.119731

Cited by 8 publications

(3 citation statements)

References 39 publications

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“…It clearly confirms the fact that using only the RMSE criterion may be insufficient. Nevertheless, most papers [35][36][37][38] employed only the RMSE criterion that leads to incorrect number of PCs/LVs used and to possible overfitting of the proposed classification models. Using a higher number of LVs (LV4-LV10) results in the increased predictive capability of the proposed classification model (Table 3).…”

Section: Pls-da Analysis Of the Calibration Set And Cross-validationmentioning

confidence: 99%

Raman spectroscopy in chronic heart failure diagnosis based on human skin analysis

Khristoforova

Bratchenko

Skuratova

et al. 2023

Journal of Biophotonics

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This work aims at studying Raman spectroscopy in combination with chemometrics as an alternative fast noninvasive method to detect chronic heart failure (CHF) cases. Optical analysis is focused on the changes in the spectral features associated with the biochemical composition changes of skin tissues. A portable spectroscopy setup with the 785 nm excitation wavelength was used to record skin Raman features. In this in vivo study, 127 patients and 57 healthy volunteers were involved in measuring skin spectral features by Raman spectroscopy. The spectral data were analyzed with a projection on the latent structures and discriminant analysis. 202 skin spectra of patients with CHF and 90 skin spectra of healthy volunteers were classified with 0.888 ROC AUC for the 10-fold cross validated algorithm. To identify CHF cases, the performance of the proposed classifier was verified by means of a new test set that is equal to 0.917 ROC AUC.

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Section: Pls-da Analysis Of the Calibration Set And Cross-validationmentioning

confidence: 99%

Raman spectroscopy in chronic heart failure diagnosis based on human skin analysis

Khristoforova

Bratchenko

Skuratova

et al. 2023

Journal of Biophotonics

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“…Biosensors 2024, 14, 202 2 of 13 Surface-enhanced Raman spectroscopy (SERS) has demonstrated substantial potential in the fields of biomedicine, chemical analysis, and materials science due to its remarkably high sensitivity, selectivity, non-destructiveness, and resistance to photobleaching [11][12][13]. In biomedical applications, SERS mainly uses two methods: labeling and label-free techniques [14][15][16][17]. The label-free technique provides biomolecule-specific vibrational data through sample-substrate interaction, offering intrinsic fingerprint information, though it can be affected by impurities [14,18,19].…”

Section: Introductionmentioning

confidence: 99%

SERS-Based Microneedle Biosensor for In Situ and Sensitive Detection of Tyrosinase

Gu,

Zhao,

et al. 2024

Biosensors

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Tyrosinase (TYR) emerges as a key enzyme that exerts a regulatory influence on the synthesis of melanin, thereby assuming the role of a critical biomarker for the detection of melanoma. Detecting the authentic concentration of TYR in the skin remains a primary challenge. Distinguished from ex vivo detection methods, this study introduces a novel sensor platform that integrates a microneedle (MN) biosensor with surface-enhanced Raman spectroscopy (SERS) technology for the in situ detection of TYR in human skin. The platform utilized dopamine (DA)-functionalized gold nanoparticles (Au NPs) as the capturing substrate and 4-mercaptophenylboronic acid (4-MPBA)-modified silver nanoparticles (Ag NPs) acting as the SERS probe. Here, the Au NPs were functionalized with mercaptosuccinic acid (MSA) for DA capture. In the presence of TYR, DA immobilized on the MN is preferentially oxidized to dopamine quinone (DQ), a process that results in a decreased density of SERS probes on the platform. TYR concentration was detected through variations in the signal intensity emitted by the phenylboronic acid. The detection system was able to evaluate TYR concentrations within a linear range of 0.05 U/mL to 200 U/mL and showed robust anti-interference capabilities. The proposed platform, integrating MN-based in situ sensing, SERS technology, and TYR responsiveness, holds significant importance for diagnosing cutaneous melanoma.

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“…Due to the special optical and anatomical characteristics of the eye, RS can be directly used for in situ detection of cornea by using the advantages of non-invasive, non-destructive, high resolution and label-free. To date, some studies have used RS for preliminary analysis of corneas of animals such as mice [9][10], rabbits [11][12] and pigs [13]. However, there are few analyses of human cornea structure combined with RS.…”

Section: Introductionmentioning

confidence: 99%

Feasibility study of Raman spectroscopy in corneal stromal tissue of human myopic eye

Han

Wang

et al. 2023

Advanced Chemical Microscopy for Life Science and Translational Medicine 2023

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Myopia, a global public health problem, is recognized by the World Health Organization as the leading cause of visual impairment in uncorrected people. At present, a large number of reports focus on the pathological manifestations of retinal level myopia. However, corneal histological changes that may be associated with myopia have not been thoroughly investigated. Raman spectroscopy is a rapid and non-destructive analytical technique with the advantages including label-free, non-invasive and highly specific, providing detailed information at the molecular level. Important components of all the human tissue (proteins, nucleic acids, lipids, etc.) have corresponding Raman spectral characteristic peaks, which contribute to the study of myopia at the molecular level. In this study, a microscopic confocal Raman system (MCRS) was built to collect Raman spectrum of corneal stromal samples, which was obtained through femtosecond laser small incision corneal stroma lens extraction (SMLIE). One hundred fifty-nine corneal stromal Raman spectrum data were collected (54 low myopia, 69 moderate myopia and 36 high myopia). Ten characteristic peaks and corresponding components were further identified. K-nearest neighbor (KNN) was used with principal component analysis (PCA) to classify the samples and the classifications were validated by k-fold cross-validation. Three types of samples with different degrees of myopia were differentiated under the PCA-KNN model with an accuracy of 93.1%. Two characteristic peaks (1099 cm-1 and 2940 cm-1) show greatly contribution to the classification results. The results provide that Raman spectroscopy combined with PCA-KNN analysis can effectively distinguish the degree of myopia and is expected to explore the potential causes of myopia.

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Label-free Raman spectroscopy: A potential tool for early diagnosis of diabetic keratopathy

Cited by 8 publications

References 39 publications

Raman spectroscopy in chronic heart failure diagnosis based on human skin analysis

Raman spectroscopy in chronic heart failure diagnosis based on human skin analysis

SERS-Based Microneedle Biosensor for In Situ and Sensitive Detection of Tyrosinase

Feasibility study of Raman spectroscopy in corneal stromal tissue of human myopic eye

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