Publications by authors named "Cyril Gobinet"

40 Publications

Combining Raman imaging and MCR-ALS analysis for monitoring retinol permeation in human skin.

Skin Res Technol 2021 Jun 11. Epub 2021 Jun 11.

Laboratory of Translational Biospectroscopy, BioSpecT EA 7506, University of Reims Champagne-Ardenne, France.

Background: Monitoring the transcutaneous permeation of exogenous molecules using conventional techniques generally requires long pre-analytical preparation or labelling of samples. However, Raman spectroscopy is a label-free and non-destructive method which provides spatial distribution of tracked actives in skin. The aim of our study was to prove the interest of Raman imaging coupled with multivariate curve resolution alternating least square (MCR-ALS) analysis in monitoring retinol penetration into frozen and living human skin.

Materials And Methods: After topical treatment of skin samples by free or encapsulated retinol, thin cross sections were analysed by Raman imaging (up to 100 µm depth). Mann-Whitney test was used to identify retinol spectroscopic markers in skin. MCR-ALS was used to estimate retinol contribution in Raman spectral images. Heat maps were constructed to compare the distribution of free and encapsulated retinol in skin models.

Results: We identified the bands at 1158, 1196 and 1591 cm as specific features for monitoring retinol in skin. Moreover, our MCR-ALS results showed an improvement of retinol penetration (up to 30 µm depth) with the encapsulated form as well as storage reservoir formation in stratum corneum, for each skin model. Finally, greater retinol penetration into living skin was observed.

Conclusion: This study shows a proof of concept for the evaluation of retinol penetration in skin using Raman imaging coupled with MCR-ALS. This concept needs to be validated on more subjects to include inter-individual variability but also other factors affecting skin permeation (age, sex, pH, etc). Our study can be extended to other actives.
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http://dx.doi.org/10.1111/srt.13069DOI Listing
June 2021

Automatic Identification of Paraffin Pixels on FTIR Images Acquired on FFPE Human Samples.

Anal Chem 2021 03 16;93(8):3750-3761. Epub 2021 Feb 16.

BioSpecT EA 7506, Université de Reims Champagne Ardenne, 51 rue Cognacq-Jay, 51097 Reims, France.

The transfer of mid-infrared spectral histopathology to the clinic will be possible provided that its application in clinical practice is simple. Rapid analysis of formalin-fixed paraffin-embedded (FFPE) tissue section is thus a prerequisite. The chemical dewaxing of these samples before image acquisition used by the majority of studies is in contradiction with this principle. Fortunately, the in silico analysis of the images acquired on FFPE samples is possible using extended multiplicative signal correction (EMSC). However, the removal of pure paraffin pixels is essential to perform a relevant classification of tissue spectra. So far, this task was possible only if using manual and subjective histogram analysis. In this article, we thus propose a new automatic and multivariate methodology based on the analysis of optimized combinations of EMSC regression coefficients by validity indices and KMeans clustering to separate paraffin and tissue pixels. The validation of our method is performed using simulated infrared spectral images by measuring the Jaccard index between our partitions and the image model, with values always over 0.90 for diverse baseline complexity and signal-to-noise ratio. These encouraging results were also validated on real images by comparing our method with classical ones and by computing the Jaccard index between our partitions and the KMeans partitions obtained on the infrared image acquired on the same samples but after chemical dewaxing, with values always over 0.84.
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http://dx.doi.org/10.1021/acs.analchem.0c03910DOI Listing
March 2021

New insights into hidradenitis suppurativa diagnosis via salivary infrared biosignatures: A pilot study.

J Biophotonics 2021 Mar 2;14(3):e202000327. Epub 2020 Dec 2.

Université de Reims Champagne-Ardenne, UFR Odontologie, Département de Biologie Orale, Reims, France.

Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease which can lead to a prolonged physical disability. HS diagnosis is exclusively clinical with the absence of biomarkers. Our study aims at assessing the HS-diagnostic potential of infrared spectroscopy from saliva, as a biofluid reflecting the body's pathophysiological state. Infrared spectra from 127 patients (57 HS and 70 non-HS) were processed by multivariate methods: principal component analysis coupled with Kruskal-Wallis or Mann-Whitney tests to identify discriminant spectral wavenumbers and linear discriminant analysis to evaluate the performances of HS-diagnostic approach. Infrared features, mainly in the 1300 cm -1600 cm region, were identified as discriminant for HS and prediction models revealed diagnostic performances of about 80%. Tobacco and obesity, two main HS risk factors, do not seem to alter the infrared diagnosis. This pilot study shows the potential of salivary "liquid biopsy" associated to vibrational spectroscopy to develop a personalized medical approach for HS patients' management.
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http://dx.doi.org/10.1002/jbio.202000327DOI Listing
March 2021

Analysis of Hepatic Fibrosis Characteristics in Cirrhotic Patients with and without Hepatocellular Carcinoma by FTIR Spectral Imaging.

Molecules 2020 Sep 7;25(18). Epub 2020 Sep 7.

Université de Reims Champagne-Ardenne, BioSpecT-EA7506, UFR de Pharmacie, 51097 Reims, France.

The evolution of cirrhosis is marked by quantitative and qualitative modifications of the fibrosis tissue and an increasing risk of complications such as hepatocellular carcinoma (HCC). Our purpose was to identify by FTIR imaging the spectral characteristics of hepatic fibrosis in cirrhotic patients with and without HCC. FTIR images were collected at projected pixel sizes of 25 and 2.7 μm from paraffinized hepatic tissues of five patients with uncomplicated cirrhosis and five cirrhotic patients with HCC and analyzed by k-means clustering. When compared to the adjacent histological section, the spectral clusters corresponding to hepatic fibrosis and regeneration nodules were easily identified. The fibrosis area estimated by FTIR imaging was correlated to that evaluated by digital image analysis of histological sections and was higher in patients with HCC compared to those without complications. Qualitative differences were also observed when fibrosis areas were specifically targeted at higher resolution. The partition in two clusters of the fibrosis tissue highlighted subtle differences in the spectral characteristics of the two groups of patients. These data show that the quantitative and qualitative changes of fibrosis tissue occurring during the course of cirrhosis are detectable by FTIR imaging, suggesting the possibility of subclassifying cirrhosis into different steps of severity.
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http://dx.doi.org/10.3390/molecules25184092DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570752PMC
September 2020

Correction: Confocal Raman microspectroscopy for skin characterization: a comparative study between human skin and pig skin.

Analyst 2020 07 3;145(13):4699-4700. Epub 2020 Jun 3.

MéDIAN Unit, CNRS UMR 6237, Faculty of Pharmacy, University of Reims Champagne - Ardenne (URCA), 51 rue Cognacq Jay, 51096 Reims, France.

Correction for 'Confocal Raman microspectroscopy for skin characterization: a comparative study between human skin and pig skin' by Sana Tfaili et al., Analyst, 2012, 137, 3673-3682, DOI: .
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http://dx.doi.org/10.1039/d0an90060eDOI Listing
July 2020

Correction: Towards normalization selection of Raman data in the context of protein glycation: application of validity indices to PCA processed spectra.

Analyst 2020 04;145(8):3157

BioSpecT EA n°7506, Laboratory of Translational Biospectroscopy, UFR - Pharmacie, Université de Reims Champagne-Ardenne, France. and Platform of Cellular and Tissular Imaging (PICT), University of Reims Champagne-Ardenne, Reims, France.

Correction for 'Towards normalization selection of Raman data in the context of protein glycation: application of validity indices to PCA processed spectra' by Fatima Alsamad et al., Analyst, 2020, DOI: 10.1039/c9an02155h.
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http://dx.doi.org/10.1039/d0an90034fDOI Listing
April 2020

Towards normalization selection of Raman data in the context of protein glycation: application of validity indices to PCA processed spectra.

Analyst 2020 04 28;145(8):2945-2957. Epub 2020 Feb 28.

BioSpecT EA n°7506, Laboratory of Translational Biospectroscopy, UFR - Pharmacie, Université de Reims Champagne-Ardenne, France.

Raman spectroscopy is a candidate technique for diagnosis applications in medicine due to its high molecular specificity. Optimizing the pre-treatment applied for Raman data is important for exploiting Raman signals and ensuring their relevance in medical diagnosis. One of the crucial steps in data pre-processing, normalization, can affect significantly the result interpretation. To select the appropriate normalization method, a strategy based on validity indices (VI) is proposed in this study. VI are based on measuring the quality of data partitioning without involving a full sequence of supervised classification. The approach was tested on Raman data acquired from control and in vitro glycated proteins (albumin and collagen). Protein glycation is a process involved in the molecular ageing of tissues that leads to the formation of products altering the functional and structural properties of proteins. Different methods of normalization were applied on the data sets: integrated intensity of the phenylalanine band, integrated intensity of the amide I band, standard normal variate (SNV), multiplicative signal correction (MSC), and extended multiplicative signal correction (EMSC) that performs simultaneously baseline correction and normalization. Following normalization, principal component analysis (PCA) was applied and VI were calculated from PCA scores resulting from each of the normalization methods mentioned. Based on VI quantitative values, our experiments permit to illustrate the effect of normalization on the data separability of control and glycated samples, and to determine the most appropriate normalization and simultaneously the most discriminant principal components to exploit vibrational information associated with glycation-induced modifications. In parallel, principal component analysis - linear discriminant analysis (PCA-LDA) was carried out for positioning the interest of VI in regard to a common chain of data processing.
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http://dx.doi.org/10.1039/c9an02155hDOI Listing
April 2020

New insights into spectral histopathology: infrared-based scoring of tumour aggressiveness of squamous cell lung carcinomas.

Chem Sci 2019 Apr 5;10(15):4246-4258. Epub 2019 Mar 5.

BioSpecT Unit , EA 7506 , University of Reims Champagne-Ardenne , Pharmacy Department , 51 rue Cognacq-Jay , 51096 Reims , France . Email:

Spectral histopathology, based on infrared interrogation of tissue sections, proved a promising tool for helping pathologists in characterizing histological structures in a quantitative and automatic manner. In cancer diagnosis, the use of chemometric methods permits establishing numerical models able to detect cancer cells and to characterize their tissular environment. In this study, we focused on exploiting multivariate infrared data to score the tumour aggressiveness in preneoplastic lesions and squamous cell lung carcinomas. These lesions present a wide range of aggressive phenotypes; it is also possible to encounter cases with various degrees of aggressiveness within the same lesion. Implementing an infrared-based approach for a more precise histological determination of the tumour aggressiveness should arouse interest among pathologists with direct benefits for patient care. In this study, the methodology was developed from a set of samples including all degrees of tumour aggressiveness and by constructing a chain of data processing steps for an automated analysis of tissues currently manipulated in routine histopathology.
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http://dx.doi.org/10.1039/c8sc04320eDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471539PMC
April 2019

Shedding light on confounding factors likely to affect salivary infrared biosignatures.

Anal Bioanal Chem 2019 Apr 16;411(11):2283-2290. Epub 2019 Feb 16.

BioSpecT EA7506, Faculty of Pharmacy, University of Reims Champagne-Ardenne, 51 rue Cognacq-Jay, 51096, Reims Cedex, France.

Total human saliva is a biofluid which can be considered as a "mirror" reflecting the state of the body's health. The "spectral mid-infrared fingerprint" represents a snapshot of the intrinsic biomolecular composition of a saliva sample translating multiple information about the patient, and likely to be related not only to his physiopathological status but also to his behavioral habits or even current medical treatments. These different patient-related characteristics are "confounding factors," which may strongly affect the infrared data of salivary samples and disrupt the search for specific salivary biomarkers in the detection of diseases, especially in the case of complex pathologies influenced by multiple risk factors such as genetic factors and behavioral factors, and also other comorbidities. In this study, dealing with the processing of infrared saliva spectra from 56 patients, our aim was to highlight spectral features associated with some patient characteristics, namely tobacco smoking, periodontal diseases, and gender. By using multivariate statistical methods of feature selection (principal component analysis coupled with Kruskal-Wallis test, linear discriminant analysis coupled with randfeatures function), we were able to identify the discriminant vibrations associated with a specific factor and to assess the related spectral variability. Based on the methodology demonstrated here, it could be very valuable in the future to develop processing aimed at neutralizing these variabilities, in order to determine specific spectroscopic markers related to a multifactorial disease for diagnostic or follow-up purposes.
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http://dx.doi.org/10.1007/s00216-019-01669-6DOI Listing
April 2019

Comprehensive Characterization of the Interaction between Pulsed Electric Fields and Live Cells by Confocal Raman Microspectroscopy.

Anal Chem 2017 10 5;89(20):10790-10797. Epub 2017 Oct 5.

Vectorology and Anticancer Therapies, UMR 8203, CNRS, Gustave Roussy, Univ. Paris-Sud, Université Paris-Saclay , 114 rue Edouard Vaillant, 94805 Villejuif, France.

This study reports a comprehensive analysis of the effect of 100 μs electric pulses on the biochemical composition of live cells using a label-free approach, confocal Raman microspectroscopy. We investigated different regions of interest around the nucleus of the cells and the dose-effect relationship related to different electric pulse parameters. We also extended the study to another cell type. Membrane resealing was monitored by pulsing the cells in reversible or irreversible electropermeabilization condition at different temperatures. Our results confirmed a previous publication showing that proteins and lipids were highly impacted by the delivery of electric pulses. These chemical changes were similar in different locations around the cell nucleus. By sweeping the field magnitude, the number of electric pulses, or their repetition rate, the Raman signatures of live cells appeared to be related to the electropermeabilization state, verified by Yo-Pro-1 uptake. We also demonstrated that the chemical changes in the Raman signatures were cell-dependent even if common features were noticed between the two cell types used.
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http://dx.doi.org/10.1021/acs.analchem.7b02079DOI Listing
October 2017

Lumican delays melanoma growth in mice and drives tumor molecular assembly as well as response to matrix-targeted TAX2 therapeutic peptide.

Sci Rep 2017 08 9;7(1):7700. Epub 2017 Aug 9.

Université de Reims Champagne-Ardenne, UFR Sciences Exactes et Naturelles, Campus Moulin de la Housse, 51100, Reims, France.

Lumican is a small leucine-rich proteoglycan (SLRP) being known as a key regulator of collagen fibrillogenesis. However, little attention has been given so far in studying its influence on tumor-associated matrix architecture. Here, we investigate the role of host lumican on tumor matrix organization as well as on disease progression considering an immunocompetent model of melanoma implanted in Lum vs. wild type syngeneic mice. Conjointly, lumican impact on tumor response to matrix-targeted therapy was evaluated considering a previously validated peptide, namely TAX2, that targets matricellular thrombospondin-1. Analysis of available genomics and proteomics databases for melanoma first established a correlation between lumican expression and patient outcome. In the B16 melanoma allograft model, endogenous lumican inhibits tumor growth and modulates response to TAX2 peptide. Indeed, IHC analyses revealed that lumican deficiency impacts intratumoral distribution of matricellular proteins, growth factor and stromal cells. Besides, innovative imaging approaches helped demonstrating that lumican host expression drives biochemical heterogeneity of s.c. tumors, while modulating intratumoral collagen deposition as well as organization. Altogether, the results obtained present lumican as a strong endogenous inhibitor of tumor growth, while identifying for the first time this proteoglycan as a major driver of tumor matrix coherent assembly.
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http://dx.doi.org/10.1038/s41598-017-07043-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5550434PMC
August 2017

Demonstration of the Protein Involvement in Cell Electropermeabilization using Confocal Raman Microspectroscopy.

Sci Rep 2017 01 19;7:40448. Epub 2017 Jan 19.

Vectorology and Anticancer Therapies, UMR 8203, CNRS, Gustave Roussy, Univ. Paris-Sud, Université Paris-Saclay, 114 rue Edouard Vaillant, 94805 Villejuif, France.

Confocal Raman microspectroscopy was used to study the interaction between pulsed electric fields and live cells from a molecular point of view in a non-invasive and label-free manner. Raman signatures of live human adipose-derived mesenchymal stem cells exposed or not to pulsed electric fields (8 pulses, 1 000 V/cm, 100 μs, 1 Hz) were acquired at two cellular locations (nucleus and cytoplasm) and two spectral bands (600-1 800 cm and 2 800-3 100 cm). Vibrational modes of proteins (phenylalanine and amide I) and lipids were found to be modified by the electropermeabilization process with a statistically significant difference. The relative magnitude of four phenylalanine peaks decreased in the spectra of the pulsed group. On the contrary, the relative magnitude of the amide I band at 1658 cm increased by 40% when comparing pulsed and control group. No difference was found between the control and the pulsed group in the high wavenumber spectral band. Our results reveal the modification of proteins in living cells exposed to pulsed electric fields by means of confocal Raman microspectroscopy.
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http://dx.doi.org/10.1038/srep40448DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5244372PMC
January 2017

Digital de-waxing on FTIR images.

Analyst 2017 Apr;142(8):1358-1370

Universidade de São Paulo, Avenida dos Bandeirantes, 3900, Ribeirão Preto, SP, Brazil.

This paper presents a procedure that digitally neutralizes the contribution of paraffin to FTIR hyperspectral images. A brief mathematical derivation of the procedure is demonstrated and applied on one normal human colon sample to exemplify the de-waxing procedure. The proposed method includes construction of a paraffin model based on PCA, EMSC normalization and application of two techniques for spectral quality control. We discuss every step in which the researcher needs to take a subjective decision during the de-waxing procedure, and we explain how to make an adequate choice of parameters involved. Application of this procedure to 71 hyperspectral images collected from 55 human colon biopsies (20 normal, 17 ulcerative colitis, and 18 adenocarcinoma) showed that paraffin was appropriately neutralized, which made the de-waxed images adequate for analysis by pattern-recognition techniques such as k-means clustering or PCA-LDA.
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http://dx.doi.org/10.1039/c6an01975gDOI Listing
April 2017

Raman-based detection of hydroxyethyl starch in kidney allograft biopsies as a potential marker of allograft quality in kidney transplant recipients.

Sci Rep 2016 09 9;6:33045. Epub 2016 Sep 9.

UMR CNRS 7369 MEDyC, Université de Reims Champagne-Ardennes, Reims, France.

In brain-dead donor resuscitation, hydroxyethyl starch (HES) use has been associated with presence of osmotic-nephrosis-like lesions in kidney transplant recipients. Our aim was to determine whether the presence of HES in protocol renal graft biopsies at three months (M3) after transplantation is associated with renal graft quality. According to the HES administered to the donor during the procurement procedure, two groups of patients were defined according graft exposition to HES: HES group, (N = 20) and control group (N = 6). Detection and relative quantification of HES was performed by Raman spectroscopy microimaging on M3 protocol renal graft biopsies. Statistical analyses were used to investigate the association between Raman data and graft characteristics. HES spectral signal was revealed negative in the control group, whereas it was positive in 40% of biopsies from the HES group. In the HES group, a stronger HES signal was associated with a lower risk of graft failure measured by the Kidney Donor Risk Index (KDRI) and was correlated with the allograft kidney function. Thus, HES accumulation in donor kidney, as probed by Raman biophotonic technique, is correlated with the quality of donor kidney and consequently the graft renal function and graft survival.
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http://dx.doi.org/10.1038/srep33045DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016807PMC
September 2016

Vibrational Analysis of Lung Tumor Cell Lines: Implementation of an Invasiveness Scale Based on the Cell Infrared Signatures.

Anal Chem 2016 09 17;88(17):8459-67. Epub 2016 Aug 17.

Equipe MéDIAN-Biophotonique et Technologies pour la Santé Université de Reims Champagne-Ardenne, UFR de Pharmacie, 51 rue Cognacq-Jay, 51096 Reims, France.

Assessing the tumor invasiveness is a paramount diagnostic step to improve the patients care. Infrared spectroscopy access the chemical composition of samples; and in combination with statistical multivariate processing, presents the capacity to highlight subtle molecular alterations associated with malignancy development. Our investigation demonstrated that infrared signatures of cell lines presenting various invasiveness phenotypes contain discriminant spectral features, which are useful informative signals to implement an objective invasiveness scale. This last development reflects the interest of vibrational approach as a candidate biophotonic label-free technique, usable in routine clinics, to characterize quantitatively tumor aggressiveness. In addition, the methodology can reveal the heterogeneity of cancer cells, opening the way to further researches in cancer science.
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http://dx.doi.org/10.1021/acs.analchem.6b00590DOI Listing
September 2016

Development of a memetic clustering algorithm for optimal spectral histology: application to FTIR images of normal human colon.

Analyst 2016 May;141(11):3296-304

Université de Reims Champagne-Ardenne, Equipe MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, 51 rue Cognacq-Jay, 51096 Reims Cedex, France and CNRS UMR 7369, Matrice Extracellulaire et Dynamique Cellulaire (MEDyC), Reims, France.

The coupling between Fourier-transform infrared (FTIR) imaging and unsupervised classification is effective in revealing the different structures of human tissues based on their specific biomolecular IR signatures; thus the spectral histology of the studied samples is achieved. However, the most widely applied clustering methods in spectral histology are local search algorithms, which converge to a local optimum, depending on initialization. Multiple runs of the techniques estimate multiple different solutions. Here, we propose a memetic algorithm, based on a genetic algorithm and a k-means clustering refinement, to perform optimal clustering. In addition, this approach was applied to the acquired FTIR images of normal human colon tissues originating from five patients. The results show the efficiency of the proposed memetic algorithm to achieve the optimal spectral histology of these samples, contrary to k-means.
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http://dx.doi.org/10.1039/c5an02227dDOI Listing
May 2016

Fully unsupervised inter-individual IR spectral histology of paraffinized tissue sections of normal colon.

J Biophotonics 2016 05 12;9(5):521-32. Epub 2016 Feb 12.

Université de Reims Champagne-Ardenne, Equipe MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, Reims, France.

In label-free Fourier-transform infrared histology, spectral images are individually recorded from tissue sections, pre-processed and clustered. Each single resulting color-coded image is annotated by a pathologist to obtain the best possible match with tissue structures revealed after Hematoxylin-Eosin staining. However, the main limitations of this approach are the empirical choice of the number of clusters in unsupervised classification, and the marked color heterogeneity between the clustered spectral images. Here, using normal murine and human colon tissues, we developed an automatic multi-image spectral histology to simultaneously analyze a set of spectral images (8 images mice samples and 72 images human ones). This procedure consisted of a joint Extended Multiplicative Signal Correction (EMSC) to numerically deparaffinize the tissue sections, followed by an automated joint K-Means (KM) clustering using the hierarchical double application of Pakhira-Bandyopadhyay-Maulik (PBM) validity index. Using this procedure, the main murine and human colon histological structures were correctly identified at both the intra- and the inter-individual levels, especially the crypts, secreted mucus, lamina propria and submucosa. Here, we show that batched multi-image spectral histology procedure is insensitive to the reference spectrum but highly sensitive to the paraffin model of joint EMSC. In conclusion, combining joint EMSC and joint KM clustering by double PBM application allows to achieve objective and automated batched multi-image spectral histology.
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http://dx.doi.org/10.1002/jbio.201500285DOI Listing
May 2016

Renal Graft Fibrosis and Inflammation Quantification by an Automated Fourier-Transform Infrared Imaging Technique.

J Am Soc Nephrol 2016 08 18;27(8):2382-91. Epub 2015 Dec 18.

Matrice Extracellulaire et Dynamique Cellulaire Unit, Centre National pour la Recherche Scientifique, Unité Mixte de Recherche 7369, and Nephrology and Renal Transplantation Department and.

Renal interstitial fibrosis and interstitial active inflammation are the main histologic features of renal allograft biopsy specimens. Fibrosis is currently assessed by semiquantitative subjective analysis, and color image analysis has been developed to improve the reliability and repeatability of this evaluation. However, these techniques fail to distinguish fibrosis from constitutive collagen or active inflammation. We developed an automatic, reproducible Fourier-transform infrared (FTIR) imaging-based technique for simultaneous quantification of fibrosis and inflammation in renal allograft biopsy specimens. We generated and validated a classification model using 49 renal biopsy specimens and subsequently tested the robustness of this classification algorithm on 166 renal grafts. Finally, we explored the clinical relevance of fibrosis quantification using FTIR imaging by comparing results with renal function at 3 months after transplantation (M3) and the variation of renal function between M3 and M12. We showed excellent robustness for fibrosis and inflammation classification, with >90% of renal biopsy specimens adequately classified by FTIR imaging. Finally, fibrosis quantification by FTIR imaging correlated with renal function at M3, and the variation in fibrosis between M3 and M12 correlated well with the variation in renal function over the same period. This study shows that FTIR-based analysis of renal graft biopsy specimens is a reproducible and reliable label-free technique for quantifying fibrosis and active inflammation. This technique seems to be more relevant than digital image analysis and promising for both research studies and routine clinical practice.
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http://dx.doi.org/10.1681/ASN.2015050601DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4978043PMC
August 2016

Diagnosis approach of chronic lymphocytic leukemia on unstained blood smears using Raman microspectroscopy and supervised classification.

Analyst 2015 Jul;140(13):4465-72

Université de Reims Champagne-Ardenne, Équipe MéDIAN Biophotonique et Technologies pour la Santé, UFR de Pharmacie, 51 rue Cognacq-Jay, 51096, Reims Cedex, France.

We have investigated the potential of Raman microspectroscopy combined with supervised classification algorithms to diagnose a blood lymphoproliferative disease, namely chronic lymphocytic leukemia (CLL). This study was conducted directly on human blood smears (27 volunteers and 49 CLL patients) spread on standard glass slides according to a cytological protocol before the staining step. Visible excitation at 532 nm was chosen, instead of near infrared, in order to minimize the glass contribution in the Raman spectra. After Raman measurements, blood smears were stained using the May-Grünwald Giemsa procedure to correlate spectroscopic data classifications with cytological analysis. A first prediction model was built using support vector machines to discriminate between the two main leukocyte subpopulations (lymphocytes and polymorphonuclears) with sensitivity and specificity over 98.5%. The spectral differences between these two classes were associated to higher nucleic acid content in lymphocytes compared to polymorphonuclears. Then, we developed a classification model to discriminate between neoplastic and healthy lymphocyte spectra, with a mean sensitivity and specificity of 88% and 91% respectively. The main molecular differences between healthy and CLL cells were associated with DNA and protein changes. These spectroscopic markers could lead, in the future, to the development of a helpful medical tool for CLL diagnosis.
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http://dx.doi.org/10.1039/c4an02085eDOI Listing
July 2015

Probing in vitro ribose induced DNA-glycation using Raman microspectroscopy.

Anal Chem 2015 Mar 20;87(5):2655-64. Epub 2015 Feb 20.

MéDIAN Biophotonique et Technologies pour la Santé, Université de Reims Champagne-Ardenne, CNRS UMR 7369 MEDyC, UFR de Pharmacie, SFR CAP Santé , 51096 Reims Cedex, France.

To identify and characterize glycation, induced modifications of DNA are crucial toward understanding their functional significance due to their significant role in the long term control of aging and age-related diseases. In this study, we present the ability of Raman microspectroscopy as a novel analytical technique for a rapid and reliable identification of glycated DNA in a reagent-free manner. We have demonstrated that this technique has potential to provide very small conformational modifications. The combination of principal component analysis (PCA) and two-dimensional (2D) correlation spectroscopy has assisted us to explore in vitro DNA-glycation and provide more insights into the dynamics of the DNA-glycation process in an easier fashion. PCA analysis of Raman spectra shows a clear discrimination between native and glycated DNA samples. On the other hand, 2D correlation Raman analysis provides sequential order of the mechanism of the DNA-glycation process, and most likely, it occurs in the following sequence: Structural modifications of individual nucleobases (G > A > C) → DNA backbone modifications → partial transition of DNA conformations (A to B form). Our observations clearly suggest that the structure of DNA is altered, i.e., a partial transition of DNA backbone conformation from A to B form when glycated, but does not induce any final transition in DNA double helix conformation, and eventually, DNA presents in an intermediate A-B form, more toward the B form.
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http://dx.doi.org/10.1021/acs.analchem.5b00182DOI Listing
March 2015

Development of a hierarchical double application of crisp cluster validity indices: a proof-of-concept study for automated FTIR spectral histology.

Analyst 2015 Apr;140(7):2439-48

Université de Reims Champagne-Ardenne, Equipe MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, 51 rue Cognacq-Jay, 51096 Reims, France.

Fourier-transform infrared (FTIR) spectral imaging is currently used as a non-destructive and label-free method for analyzing biological specimens. However, to highlight the different tissue regions, unsupervised clustering methods are commonly used leading to a subjective choice of the number of clusters. Here, we develop a hierarchical double application of 9 selected crisp cluster validity indices (CCVIs) using K-Means clustering. This approach when tested first on an artificial dataset showed that the indices Pakhira-Bandyopadhyay-Maulik (PBM) and Sym-Index (SI) perfectly estimated the expected 9 sub-clusters. Then, the concept was applied to a real dataset consisting of FTIR spectral images of normal human colon tissue samples originating from 5 patients. PBM and SI were revealed to be the most efficient indices that correctly identified the different colon histological components including crypts, lamina propria, muscularis mucosae, submucosa, and lymphoid aggregates. In conclusion, these results strongly suggest that the hierarchical double CCVI application is a promising method for automated and informative spectral histology.
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http://dx.doi.org/10.1039/c4an01937gDOI Listing
April 2015

Rapid screening of classic galactosemia patients: a proof-of-concept study using high-throughput FTIR analysis of plasma.

Analyst 2015 Apr;140(7):2280-6

Université de Reims Champagne-Ardenne, Equipe MéDIAN, Biophotonique et Technologies pour la Santé, UFR de Pharmacie, 51 rue Cognacq-Jay, 51096 Reims, France.

Classic galactosemia is an autosomal recessive metabolic disease involving the galactose pathway, caused by the deficiency of galactose-1-phosphate uridyltransferase. Galactose accumulation induces in newborns many symptoms, such as liver disease, cataracts, and sepsis leading to death if untreated. Neonatal screening is developed and applied in many countries using several methods to detect galactose or its derived product accumulation in blood or urine. High-throughput FTIR spectroscopy was investigated as a potential tool in the current screening methods. IR spectra were obtained from blood plasma of healthy, diabetic, and galactosemic patients. The major spectral differences were in the carbohydrate region, which was first analysed in an exploratory manner using principal component analysis (PCA). PCA score plots showed a clear discrimination between diabetic and galactosemic patients and this was more marked as a function of the glucose and galactose increased concentration in these patients' plasma respectively. Then, a support vector machine leave-one-out cross-validation (SVM-LOOCV) classifier was built with the PCA scores as the input and the model was tested on median, mean and all spectra from the three population groups. This classifier was able to discriminate healthy/diabetic, healthy/galactosemic, and diabetic/galactosemic patients with sensitivity and specificity rates ranging from 80% to 94%. The total accuracy rate ranged from 87% to 96%. High-throughput FTIR spectroscopy combined with the SVM-LOOCV classification procedure appears to be a promising tool in the screening of galactosemia patients, with good sensitivity and specificity. Furthermore, this approach presents the advantages of being cost-effective, fast, and straightforward in the screening of galactosemic patients.
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http://dx.doi.org/10.1039/c4an01942cDOI Listing
April 2015

Infrared spectral histopathology for cancer diagnosis: a novel approach for automated pattern recognition of colon adenocarcinoma.

Analyst 2014 Aug;139(16):4005-15

Université de Reims Champagne-Ardenne, MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, 51 rue Cognacq-Jay, 51096 Reims Cedex, France.

Histopathology remains the gold standard method for colon cancer diagnosis. Novel complementary approaches for molecular level diagnosis of the disease are need of the hour. Infrared (IR) imaging could be a promising candidate method as it probes the intrinsic chemical bonds present in a tissue, and provides a "spectral fingerprint" of the biochemical composition. To this end, IR spectral histopathology, which combines IR imaging and data processing techniques, was employed on seventy seven paraffinized colon tissue samples (48 tumoral and 29 non-tumoral) in the form of tissue arrays. To avoid chemical deparaffinization, a digital neutralization of the spectral interference of paraffin was implemented. Clustering analysis was used to partition the spectra and construct pseudo-colored images, for assigning spectral clusters to various tissue structures (normal epithelium, malignant epithelium, connective tissue etc.). Based on the clustering results, linear discriminant analysis was then used to construct a stringent prediction model which was applied on samples without a priori histopathological information. The predicted spectral images not only revealed common features representative of the colonic tissue biochemical make-up, but also highlighted additional features like tumor budding and tumor-stroma association in a label-free manner. This novel approach of IR spectral imaging on paraffinized tissues showed 100% sensitivity and allowed detection and differentiation of normal and malignant colonic features based purely on their intrinsic biochemical features. This non-destructive methodology combined with multivariate statistical image analysis appears as a promising tool for colon cancer diagnosis and opens up the way to the concept of numerical spectral histopathology.
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http://dx.doi.org/10.1039/c3an01022hDOI Listing
August 2014

Bile analysis using high-throughput FTIR spectroscopy for the diagnosis of malignant biliary strictures: a pilot study in 57 patients.

J Biophotonics 2014 Apr 28;7(3-4):241-53. Epub 2014 Mar 28.

Université de Reims Champagne-Ardenne, MéDIAN-Biophotonique et Technologies pour la Santé, UFR de Pharmacie, 51 rue Cognacq-Jay, 51096 REIMS cedex, France; CNRS UMR7369, Matrice Extracellulaire et Dynamique Cellulaire, MEDyC, Reims, France.

This study aimed at determining whether FTIR spectroscopy is able to distinguish bile samples from patients with and without malignant biliary strictures. Bile samples were collected in 19 patients with malignant biliary strictures and 38 with benign biliary diseases during endoscopic procedures. FTIR spectra were acquired on dried drops of whole bile, aqueous and organic phases obtained after lipid extraction. Data were analyzed by principal component analysis and by the support vector machine classification using a leave-n-out cross validation procedure. This was applied to the whole set of spectra and the mean and median spectra of each patient. By leaving one patient out, the classifier allowed discriminating patients with and without malignant biliary strictures with a sensitivity between 82% and 95% and a specificity between 85% and 100%. Using a randomized leave-n -out cross-validation with n = 2, 5 and 10 patients, the sensitivity decreased slightly by about 5 to 10% while the specificity remained stable, suggesting the robustness of the classifier. FTIR spectroscopy combined with chemometrics therefore shows potential to differentiate bile from patients with and without malignant biliary strictures. Although promising, the results of this pilot study cannot be generalized and needs to be confirmed in a larger population.
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http://dx.doi.org/10.1002/jbio.201300166DOI Listing
April 2014

Infrared and Raman imaging for characterizing complex biological materials: a comparative morpho-spectroscopic study of colon tissue.

Appl Spectrosc 2014 ;68(1):57-68

MÉDIAN Biophotonique et Technologies pour la Santé , Université de Reims Champagne-Ardenne, FRE CNRS 3481 MEDyC, UFR de Pharmacie, SFR Cap Santé , 51 rue Cognacq-Jay, 51096 Reims cedex, France.

Complementary diagnostic methods to conventional histopathology are currently being investigated for developing rapid and objective molecular-level understanding of various disorders, especially cancers. Spectral histopathology using vibrational spectroscopic imaging has been put in the frontline as potentially promising in this regard as it provides a "spectral fingerprint" of the biochemical composition of cells and tissues. In order to ascertain the feasible conditions of vibrational spectroscopic methods for tissue-imaging analysis, vibrational multimodal imaging (infrared transmission, infrared-attenuated total reflection, and Raman imaging) of the same colon tissue has been implemented. The spectral images acquired were subjected to multivariate clustering analysis in order to identify on a molecular level the constituent histological organization of the colon tissue such as the epithelium, connective tissue, etc., by comparing the cluster images with the histological reference images. Based on this study, a comparative analysis of important factors involved in the vibrational multimodal imaging approaches such as image resolution, time constraints, their advantages and limitations, and their applicability to biological tissues has been carried out. Out of the three different vibrational imaging modalities tested, infrared-attenuated total reflection mode of imaging appears to provide a good compromise between the tissue histology and the time constraints in achieving similar image contrast to that of Raman imaging at an approximately 33-fold faster measurement time. The present study demonstrates the advantages, the limitations of the important parameters involved in vibrational multimodal imaging approaches, and their potential application toward imaging of biological tissues.
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http://dx.doi.org/10.1366/13-07170DOI Listing
September 2014

Profiling serologic biomarkers in cirrhotic patients via high-throughput Fourier transform infrared spectroscopy: toward a new diagnostic tool of hepatocellular carcinoma.

Transl Res 2013 Nov 3;162(5):279-86. Epub 2013 Aug 3.

MéDIAN-Biophotonique et Technologies pour la Santé, Université de Reims Champagne-Ardenne, Reims, France; Department of Anesthesiology, Peking University Third Hospital, Beijing, People's Republic of China.

Identification of novel serum biomarkers of hepatocellular carcinoma (HCC) is needed for early-stage disease detection and to improve patients' survival. The aim of this study was to evaluate the potential of serum Fourier transform infrared (FTIR) spectroscopy for differentiating sera from cirrhotic patients with and without HCC. Serum samples were collected from 2 sets of patients: cirrhotic patients with HCC (n = 39) and without HCC (n = 40). The FTIR spectra (10 per sample) were acquired in the transmission mode, and data homogeneity was tested by cluster analysis to exclude outliers. After data preprocessing by extended multiplicative signal correction and principal component analysis, the Support Vector Machine (SVM) method was applied using a leave-one-out cross-validation algorithm to classify the spectra into 2 classes of cirrhotic patients with and without HCC. When SVM was applied to all spectra (n = 790), the sensitivity and the specificity for the diagnosis of HCC were, respectively, 82.02% and 82.5%. When applied to the subset of spectra excluding the outliers (n = 739), SVM classification led to a sensitivity and specificity of 87.18% and 85%, respectively. Using median spectra for each patient instead of all replicates, the sensitivity and specificity were 84.62% and 82.50%, respectively. The overall accuracy rate was 82%-86%. In conclusion, this study suggests that FTIR spectroscopy combined with advanced methods of pattern analysis shows potential for differentiating sera from cirrhotic patients with and without HCC.
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http://dx.doi.org/10.1016/j.trsl.2013.07.007DOI Listing
November 2013

Infrared imaging as a cancer diagnostic tool: introducing a new concept of spectral barcodes for identifying molecular changes in colon tumors.

Cytometry A 2013 Mar 9;83(3):294-300. Epub 2013 Jan 9.

MéDIAN Biophotonique et Technologies pour la Santé, Université de Reims Champagne-Ardenne, FRE CNRS 3481 MEDyC, UFR de Pharmacie, SFR Cap Santé, 51096 Reims Cedex, France.

Complementary diagnostic methods to conventional histopathology are under scrutiny for various types of cancers for rapid and molecular level diagnostics. In this perspective, a biophotonic approach based on infrared spectral micro-imaging combined with multivariate statistical analysis has been implemented on colon tissues. The ability of infrared imaging to investigate the intrinsic biochemical features of cells and tissues has been exploited to develop a new concept of spectral bar coding. To implement this concept, 10 frozen colon tissue samples (five nontumoral and tumoral pairs from five patients) were imaged using infrared spectral micro-imaging in a nondestructive manner. The spectral images were processed by a multivariate clustering method to identify the histological organization in a label-free manner. Spectral information from the epithelial components was then automatically recovered on the basis of their intrinsic biochemical composition, and compared using a statistical method (Mann-Whitney U-test) to construct spectral barcodes specific to each patient. The spectral barcodes representing the discriminant infrared spectral wavenumbers (900-1,800 cm(-1) ) enabled characterization of some of the malignancy-associated biochemical alterations associated with mucin, nucleotides, carbohydrates, and protein regions. This approach not only allowed the identification of common biochemical alterations among all the colon cancer patients, but also revealed a difference of gradient within individual patients. This new concept of spectral bar coding gives insight into the potential of infrared spectral micro-imaging as a complementary diagnostic tool to conventional histopathology, for biochemical level understanding of malignancy in colon cancers in an objective and label-free manner.
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http://dx.doi.org/10.1002/cyto.a.22249DOI Listing
March 2013

Vibrational spectroscopies for the analysis of cutaneous permeation: experimental limiting factors identified in the case of caffeine penetration.

Anal Bioanal Chem 2013 Feb 13;405(4):1325-32. Epub 2012 Nov 13.

MéDIAN Unit, CNRS FR3481, Faculty of Pharmacy, University of Reims Champagne-Ardenne (URCA), Reims, France.

Caffeine is utilised as a reference for permeation studies in dermatology and cosmetology. The present work aimed to monitor the permeation of a caffeine solution through the skin. For this purpose, Raman and infrared studies were performed. Raman microspectroscopy permitted a dynamic follow-up of the caffeine diffusion. In complementary, infrared microimaging provided information of the caffeine localization in the skin by applying multivariate statistical processing on skin tissue sections. Herein, we prove the possibility of tracking low concentrations of caffeine through the skin and we highlight some experimental limitations of vibrational spectroscopies.
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http://dx.doi.org/10.1007/s00216-012-6512-7DOI Listing
February 2013

Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis.

J Biomed Opt 2012 Nov;17(11):116013

Université de Reims Champagne-Ardenne, MéDIAN Biophotonique et Technologies pour la Santé, FRE CNRS 3481 MEDyC, UFR de Pharmacie, SFR Cap Santé, 51 rue Cognacq-Jay, 51096 Reims cedex, France.

Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.
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http://dx.doi.org/10.1117/1.JBO.17.11.116013DOI Listing
November 2012

Shedding light on the laser wavelength effect in Raman analysis of skin epidermises.

Analyst 2012 Sep 30;137(18):4241-6. Epub 2012 Jul 30.

MéDIAN Unit, CNRS UMR, Faculty of Pharmacy, University of Reims Champagne - Ardenne, Reims, France.

Confocal Raman microspectroscopy is a promising technique which enables measuring the molecular composition of the skin layers, non-destructively and without extrinsic markers. The Raman approach is increasingly used in skin research but with various experimental conditions. In addition to the different skin types, one of the varying parameters is the wavelength of laser excitation. This parameter contributes strongly in the skin Raman response. The present work aimed to evaluate this effect for 3 different wavelengths, 532, 633 and 785 nm, on pig ear skin models. The Raman signal was assessed in the spectral fingerprint region. According to the Raman response for stability, repeatability, variability and fluorescence contribution, the 785 nm excitation wavelength was shown to be the most suitable for epidermis depth profiling in the fingerprint region.
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http://dx.doi.org/10.1039/c2an16115jDOI Listing
September 2012