Response to Comment on "Feasibility of Raman spectroscopy as a potential in vivo tool to screen for pre-diabetes and diabetes".

This letter aims to reply to Bratchenko and Bratchenko's comment on our paper "Feasibility of Raman spectroscopy as a potential in vivo tool to screen for pre-diabetes and diabetes." Our paper analyzed the feasibility of using in vivo Raman measurements combined with machine learning techniques to screen diabetic and prediabetic patients. We argued that this approach yields high overall accuracy (94.3%) while retaining a good capacity to distinguish between diabetic (area under the receiver-operating curve [AUC] = 0.86) and control classes (AUC = 0.97) and a moderate performance for the prediabetic class (AUC = 0.76). Bratchenko and Bratchenko's comment focuses on the possible overestimation of the proposed classification models and the absence of information on the age of participants. In this reply, we address their main concerns regarding our previous manuscript.

Feasibility of Raman spectroscopy as a potential in vivo tool to screen for pre-diabetes and diabetes.

In this article, we investigated the feasibility of using Raman spectroscopy and multivariate analysis method to noninvasively screen for prediabetes and diabetes in vivo. Raman measurements were performed on the skin from 56 patients with diabetes, 19 prediabetic patients and 32 healthy volunteers. These spectra were collected along with reference values provided by the standard glycated hemoglobin (HbA1c) assay. A multiclass principal component analysis and support vector machine (PCA-SVM) model was created from the labeled Raman spectra and was validated through a two-layer cross-validation scheme. Classification accuracy of the model was 94.3% with an area under the receiver operating characteristic curve AUC of 0.76 (0.65-0.84) for the prediabetic group, 0.86 (0.71-0.93) for the diabetic group and 0.97(0.93-0.99) for the control group. Our results suggest the feasibility of using Raman spectroscopy for the classification of prediabetes and diabetes in vivo.

Use of Raman spectroscopy in the assessment of skin after CO2 ablative fractional laser surgery on acne scars.

BACKGROUND: Ablative fractional laser surgery is a common technique for treating acne scars. However, an in vivo and noninvasive analysis of the histologic variations between acne skin and the resulting resurfaced skin is needed in order to evaluate the wound healing process of the scars induced by the ablative fractional laser surgery. MATERIALS AND METHODS: Nine patients with acne scars underwent a single treatment with a CO2 ablative fractional laser surgery. Collagen presence on the resurfaced skin was noninvasively assessed by means of Raman spectroscopy and principal component analysis. RESULTS: Principal component analysis shows that all the patients presented a collagen regeneration on the resurfaced skin after the laser treatment. CONCLUSION: Collagen plays a crucial role in the wound healing process. By assessing the collagen presence on the skin, it was possible to quantify the regenerative effects of the ablative fractional laser in a noninvasive way.

The sticky platelet syndrome.

The sticky platelets syndrome (SPS) is a procoagulant condition based on either arterial, venous, or capillary thrombi caused by hyperesponsive and hyperaggregable platelets. This is a frequent disease, which often remains clinically inapparent, until stressful events or combination with other factors increase the risk of developing SPS. The condition is due to a congenital platelet defect with autosomal dominant characteristics, leading to the increased platelet aggregability when they are challenged with epinephrine and adenosine diphosphate. Nowadays classification of this disorder is based on platelet reactivity to both ADP and epinephrine (SPS type 1), epinephrine alone (SPS type 2), and ADP alone (SPS type 3). The diagnoses of the syndrome depend on the functional aggregometer assay. This condition should be taken into account whenever a patient with thrombophilia is considered.

Use of Raman spectroscopy in the analysis of nickel allergy.

Raman spectra of the skin of subjects with nickel allergy are analyzed and compared to the spectra of healthy subjects to detect possible biochemical differences in the structure of the skin that could help diagnose metal allergies in a noninvasive manner. Results show differences between the two groups of Raman spectra. These spectral differences can be classified using principal component analysis. Based on these findings, a novel computational technique to make a fast evaluation and classification of the Raman spectra of the skin is presented and proposed as a noninvasive technique for the detection of nickel allergy.

Noninvasive estimation of chronological and photoinduced skin damage using Raman spectroscopy and principal component analysis.

BACKGROUND: Skin aging can be attributed to endogenous and exogenous factors which modify the hydration and protein structure of the skin which can be measured using Raman spectroscopy. METHOD: This study included 21 healthy adult volunteers, aged 32-81 years, Raman spectra were obtained from sun-protected and sun-exposed skin, also three millimeter punch biopsies of sun-exposed skin were collected and analyzed. The Raman spectra were analyzed using principal component analysis and the results were correlated with clinical and histological findings. RESULTS: The principal component analysis of the Raman spectra shows that the first principal component (PC1) obtained from the sun-protected skin is related to the age of the subject, which can be taken as a measure of chronological aging, the second (PC2) and fourth (PC4) principal components obtained from Raman spectra of sun-exposed skin are related to the amount of solar elastosis and collagen, respectively. CONCLUSION: In this work a relationship was found between histological properties of photoaged skin and noninvasive measurements based on Raman and principal components analysis (PCA). These relationships can be used to assess noninvasively the photoinduced damage and chronological characteristics of skin.

Noninvasive detection of filaggrin gene mutations using Raman spectroscopy.

Knowledge of the existence of filaggrin (FLG) gene mutations might be helpful for a subclassification of patients with atopic dermatitis (AD) which can be used to introduce individualized treatments. In this work the filaggrin content in the skin is assessed using Raman spectroscopy and the results are compared to FLG genotyping of Mexican-mestizo patients. Results showed that the 2282del4 and R501X mutations present in the European population but absent in people of Asian or African descent are also present in the Mexican-mestizo population. The results also showed that patients with filaggrin gene mutations presented lower filaggrin concentrations measured using the vector correlation of their skin Raman spectra and a fixed spectrum of pure human recombinant filaggrin, these results indicate that Raman spectroscopy may be used as a noninvasive tool to detect FLG gene mutations.