B. Closs

Autophagy in human keratinocytes: an early step of the differentiation?

Abstract:  Studies have established that autophagy constitutes an efficient process to recycle cellular components and certain proteins. The phenomenon was demonstrated primarily in response to nutrient starvation, and there are increasing evidences that it is implied in differentiation. Keratinocyte differentiation was going along an activation of lysosomal enzymes and organelle clearance, and terminal steps are sometimes described as a specialized form of cell death leading to corneocytes. We examined whether initiation of the process in human keratinocyte HaCaT involves autophagy. The KSFM™ culture medium was substituted by M199, which contains a low glucose concentration but a high calcium level (known to induce differentiation). Metabolic stress reduced enhanced cell number in G1 phase, without apoptotic features (ΔΨmt and membrane integrity are unchanged). Morphological changes were associated with a lower integrin ß1 expression and modifications of protein levels involved in keratinocyte differentiation (involucrin, keratin K10 and ΔNp63α). Whereas autophagic signalling was supported by SIRT1 and pAMPK (T172) increase according to time kinetic, which led to the disappearance of mTOR phosphorylated on S2448 residue. The significant Bcl‐XL level reduction with stress promoted autophagy, by the release of Beclin‐1, whereas ATG5‐ATG12 and LC3‐II that are involved in autophagosome formation were enhanced significantly. Then, the level of lysosomal protein cathepsin B rose to execute autophagy. Kinetic studies established that autophagy would constitute an early signalling process required for keratinocyte commitment in differentiation pathway.

Logarithmic Image Processing for Color Images

Abstract The logarithmic image processing (LIP) framework is classically devoted to grey-scale images. This study extends this framework to color images. This new model is denoted LIPC: LIP-color. It does not consist of applying the LIP model to each channel R, G, and B of a color image. We define the transmittance of color images to provide a physical justification, on which we base the definition of logarithmic operators such as addition, subtraction, and scalar multiplication, respectively noted in the LIPC as c , c , and c . As for the classical LIP model, the laws c and c define a vector space structure on the space of images that enables us to present notions requiring such a structure. For example, we define a color logarithmic interpolation by associating with a pair ( F , G ) of images the interval [ F , G ] set of barycenters of F and G . A new notion of color contrast is defined, which satisfies sub-additivity and homogeneity for scalar multiplication. This notion is proved to be efficient for edge detection. We note that the vector space structure opens the way for much new development concerning the definition of metrics, norms, scalar products, and so on and the transfer to LIPC gauges theory, duality theory, and so forth. In this chapter, we focus on applications of the LIPC model. For example, color prediction is presented and discussed, in addition to stabilization of images by dynamic range centering and enhancement of underlighted images. Concerning the implementation of the LIPC operators and algorithms, information is provided on their execution time.

Atopic skin: In vivo Raman identification of global molecular signature, a comparative study with healthy skin

Atopic dermatitis (AD) is the most common skin inflammatory disease, affecting up to 3% of adults and 20% of children. Skin barrier impairment is thought to be the primary factor in this disease. Currently, there is no method proposed to monitor non‐invasively the different molecular disorders involved in the upper layer of AD skin. Raman microspectroscopy has proved to be a powerful tool to characterize some AD molecular descriptors such as lipid content, global hydration level, filaggrin and its derivatives. Our investigations aimed to extend the use of in vivo Raman microspectroscopy as a rapid and non‐invasive diagnostic technique for lipid conformation and organization, protein secondary structure and bound water content analysis in atopic skin. Our approach was based on the analysis of Raman data collected on the stratum corneum (SC) of 11 healthy and 10 mild‐to‐moderate atopic patients. Atopic skin revealed a modification of lipid organization and conformation in addition to the decrease of the lipid‐to‐protein ratio. This study also highlighted a reduction of the bound water and an increase in protein organized secondary structure in atopic skin. All these descriptors worsen the barrier function, state and appearance of the skin in AD. This precise and relevant information will allow an in vivo follow‐up of the pathology and a better evaluation of the pharmacological activity of therapeutic molecules for the treatment of AD.

Quantification and Characterization of UVB-Induced Mitochondrial Fragmentation in Normal Primary Human Keratinocytes

UV irradiation is a major environmental factor causing skin dryness, aging and cancer. UVB in particular triggers cumulative DNA damage, oxidative stress and mitochondrial dysfunction. The objective of our study was to provide both qualitative and quantitative analysis of how mitochondria respond to UVB irradiation in normal human epidermal keratinocytes (NHEK) of healthy donors, with the rationale that monitoring mitochondrial shape will give an indication of cell population fitness and enable the screening of bioactive agents with UVB-protective properties. Our results show that NHEK undergo dose-dependent mitochondrial fragmentation after exposure to UVB. In order to obtain a quantitative measure of this phenomenon, we implemented a novel tool for automated quantification of mitochondrial morphology in live cells based on confocal microscopy and computational calculations of mitochondrial shape descriptors. This method was used to substantiate the effects on mitochondrial morphology of UVB irradiation and of knocking-down the mitochondrial fission-mediating GTPase Dynamin-related protein 1 (DRP1). Our data further indicate that all the major mitochondrial dynamic proteins are expressed in NHEK but that their level changes were stronger after mitochondrial uncoupler treatment than following UVB irradiation or DRP1 knock-down. Our system and procedures might be of interest for the identification of cosmetic or dermatologic UVB-protective agents.

Common reduced spaces of representation applied to multispectral texture analysis in cosmetology

Principal Component Analysis (PCA) is a technique of multivariate data analysis widely used in various fields like biology, ecology or economy to reduce data dimensionality while retaining most important information. It is becoming a standard practice in multispectral/hyperspectral imaging since those multivariate data generally suffer from a high redundancy level. Nevertheless, by definition, PCA is meant to be applied to a single multispectral/hyperspectral image at a time. When several images have to be treated, running a PCA on each image would generate specific reduced spaces, which is not suitable for comparison between results. Thus, we focus on two PCA based algorithms that could define common reduced spaces of representation. The first method arises from literature and is computed with the barycenter covariance matrix. On the contrary, we designed the second algorithm with the idea of correcting standard PCA using permutations and inversions of eigenvectors. These dimensionality reduction methods are used within the context of a cosmetological study of a foundation make-up. Available data are in-vivo multispectral images of skin acquired on different volunteers in time series. The main purpose of this study is to characterize the make-up degradation especially in terms of texture analysis. Results have to be validate by statistical prediction of time since applying the product. PCA algorithms produce eigenimages that separately enhance skin components (pores, radiance, vessels...). From these eigenimages, we extract morphological texture descriptors and intent a time prediction. Accuracy of common reduced spaces outperform classical PCA one. In this paper, we detail how PCA is extended to the multiple groups case and explain what are the advantages of common reduced spaces when it comes to study several multispectral images.

Lipid organization in xerosis: The key of the problem?

Although xerosis is a common skin disorder among the population, there is no in vivo global study focusing on xerotic skin. Hence, the objective of this study was to characterize xerotic skin from the surface to the molecular scale with in vivo and non‐invasive approaches.

Morphological Texture Description from Multispectral Skin Images in Cosmetology

In this paper, we propose methods to extract texture features from multispectral skin images. We first describe the acquisition protocol and corrections we applied on multispectral skin images. In the framework of a cosmetology application, a skin morphological texture evaluation is then proposed using either multivariate approach on multispectral dataset or marginal on a dataset whose dimensionality has been reduced by a multivariate analysis based on PCA.