Skin hyperpigmentation index: a new practical method for unbiased automated quantification of skin hyperpigmentation.
Ontology highlight
ABSTRACT:
SUBMITTER: Bossart S
PROVIDER: S-EPMC7496784 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Publications
Skin hyperpigmentation index: a new practical method for unbiased automated quantification of skin hyperpigmentation.
Bossart S S Cazzaniga S S Willenberg T T Ramelet A-A AA Baumgartner M M Hunger R E RE Seyed Jafari S M SM
Journal of the European Academy of Dermatology and Venereology : JEADV 20200406 7
Similar Datasets
Project description:BackgroundUltraviolet radiation is the main cause of skin pigmentation, but more recently visible light has been shown to be an important contributor especially in melano-competent subjects. Photoprotection from visible light can improve several hyperpigmentation disorders. Recently, a visible light photoprotection assessment method has been proposed based on in vivo pigmentation; the visible light photoprotection factor (VL-PF) is determined by assessment of the change in colorimetry parameter ITA over several days measured using a chromameter. Although in vivo methods remain the most representative of real life, in vitro methods are more suited to screening sunscreen formulations.ObjectiveThe aim of this study was to evaluate the correlation between in vivo and in vitro methods in assessing protection against visible light induced pigmentation.MethodsWe first analysed the in vitro protective properties of the 10 commercially available sunscreens using transmission measurements in the visible spectrum. Then, we performed a monocentric, double-blind, randomized controlled study with intra-individual comparisons in 20 healthy subjects and measure the VL-PF in vivo of those sunscreens. The correlation between the VL-PF and the percentage of blocked light was evaluated using the coefficient of determination R2 .ResultsA strong significant correlation was demonstrated between in vivo visible light protection factor and in vitro transmittance measurements, with the highest correlation factor at 420 nm and in the spectrum covering from 400 to 469 nm.ConclusionTransmittance measurements were found to be a good predictive tool to evaluate sunscreen visible light photoprotection efficacy and could be used to select formulations for final in vivo testing.
| S-EPMC9314032 | biostudies-literature
Project description:Background/Objectives: Skin hyperpigmentation is a biological process that results in an excessive production of melanin and is highly regulated by several mechanisms, tyrosinase being one of the key enzymes involved. Current reported inhibitors lack clinical efficacy, show toxic side effects, have poor bioavailability, or low formulation compatibility. The aim of this study was to design a new effective tyrosinase inhibitor for topical hyperpigmentation and anti-aging treatments. Methods: Homology modeling was used to build the tridimensional structure of human tyrosinase, and virtual docking was used to predict molecule-enzyme binding modes. The tyrosinase activity of the designed and synthesized compounds was assessed and water solubility was determined by HPLC. Cell assays were performed to determine melanin content, cytotoxicity, wound healing, anti-glycation, antioxidation, and autophagy efficacy. Gene expression and miRNA levels were quantified by qPCR and chromatin accessibility by ATAC-Seq. Human reconstructed epidermis was used to test the depigmenting efficacy as well as the skin irritation potential. Results: The 3D structure of human tyrosinase was designed and validated. The new molecule could effectively inhibit human tyrosinase and melanin synthesis in 2D monocultures and a 3D epidermis model. Two melanogenesis-related miRNAs were increased in treated cells. Anti-glycation, antioxidant, mitochondria protection, autophagy activation, and wound healing properties were also observed, with special emphasis on epigenetics. Conclusions: The designed molecule is a potential candidate to be used as a depigmenting and anti-aging agent, with suitable properties to be introduced in final product formulations for dermatology or cosmetics treatments.
| S-EPMC11597169 | biostudies-literature
Project description:Intraepidermal nerve fiber density (IENFD) measurements in skin biopsy are performed manually by 1-3 operators. To improve diagnostic accuracy and applicability in clinical practice, we developed an automated method for fast IENFD determination with low operator-dependency. Sixty skin biopsy specimens were stained with the axonal marker PGP9.5 and imaged using a widefield fluorescence microscope. IENFD was first determined manually by 3 independent observers. Subsequently, images were processed in their Z-max projection and the intradermal line was delineated automatically. IENFD was calculated automatically (fluorescent images automated counting [FIAC]) and compared with manual counting on the same fluorescence images (fluorescent images manual counting [FIMC]), and with classical manual counting (CMC) data. A FIMC showed lower variability among observers compared with CMC (interclass correlation [ICC] = 0.996 vs 0.950). FIMC and FIAC showed high reliability (ICC = 0.999). A moderate-to-high (ICC = 0.705) was observed between CMC and FIAC counting. The algorithm process took on average 15 seconds to perform FIAC counting, compared with 10 minutes for FIMC counting. This automated method rapidly and reliably detects small nerve fibers in skin biopsies with clear advantages over the classical manual technique.
| S-EPMC8357338 | biostudies-literature
Project description:The retention time provides critical information for glycan annotation and quantification from the Liquid Chromatography Mass Spectrometry (LC-MS) data. However, the variation of the precise retention time of glycans is highly dependent on the experimental conditions such as the specific separating columns, MS instruments and/or the buffer used. This variation hampers the exploitation of retention time for the glycan annotation from LC-MS data, especially when inter-laboratory data are compared. To incorporate the retention time of glycan across experiments, Glucose Unit Index (GUI) can be computed using the dextrin ladder as internal standard. The retention time of glycans are then calibrated with respect to glucose units derived from dextrin ladders. Despite the successful application of the GUI approach, the manual calibration process is quite tedious and often error prone. In this work, we present a standalone software tool GlycanGUI, with a graphic user interface to automatically carry out the GUI-based glycan annotation/quantification and subsequent data analysis. When tested on experimental data, GlycanGUI reported accurate GUI values compared with manual calibration, and thus is ready to be used for automated glycan annotation and quantification using GUI.
| S-EPMC8239159 | biostudies-literature
Project description:Over the past three decades, DNA-encoded library (DEL) technologies have become one of the most relevant strategies for hit-finding. Recent advances in synthetic methodologies for DNA-encoded libraries rendered the increased chemical space available, but it is unknown how every variety of chemistry affects DNA's integrity. Available assays to quantify DNA damage are restricted to electrophoresis, ligation efficiency, and mostly qPCR quantification and sequencing, which may contain predisposition and inconsistency. We developed an external standard method through LC-MS analysis to accurately quantify DNA damage throughout the chemical transformations. An assessment was conducted on on-DNA chemical reactions that are frequently employed in DEL synthesis, and these results were compared to traditional qPCR measurements. Our study provides a simple, practicable, and accurate measurement for DNA degradation during DEL synthesis. Our finding reveals substantial disagreement among the usual DNA-damaging assessment methods, which have been largely neglected so far.
| S-EPMC10733999 | biostudies-literature
Project description:Reproducible and unbiased methods to quantify alveolar structure are important for research on many lung diseases. However, manually estimating alveolar structure through stereology is time consuming and inter-observer variability is high. The objective of this work was to develop and validate a fast, reproducible and accurate (semi-)automatic alternative. A FIJI-macro was designed that automatically segments lung images to binary masks, and counts the number of test points falling on tissue and the number of intersections of the air-tissue interface with a set of test lines. Manual selection remains necessary for the recognition of non-parenchymal tissue and alveolar exudates. Volume density of alveolar septa ([Formula: see text]) and mean linear intercept of the airspaces (Lm) as measured by the macro were compared to theoretical values for 11 artificial test images and to manually counted values for 17 lungs slides using linear regression and Bland-Altman plots. Inter-observer agreement between 3 observers, measuring 8 lungs both manually and automatically, was assessed using intraclass correlation coefficients (ICC). [Formula: see text] and Lm measured by the macro closely approached theoretical values for artificial test images (R2 of 0.9750 and 0.9573 and bias of 0.34% and 8.7%). The macro data in lungs were slightly higher for [Formula: see text] and slightly lower for Lm in comparison to manually counted values (R2 of 0.8262 and 0.8288 and bias of -6.0% and 12.1%). Visually, semi-automatic segmentation was accurate. Most importantly, manually counted [Formula: see text] and Lm had only moderate to good inter-observer agreement (ICC 0.859 and 0.643), but agreements were excellent for semi-automatically counted values (ICC 0.956 and 0.900). This semi-automatic method provides accurate and highly reproducible alveolar morphometry results. Future efforts should focus on refining methods for automatic detection of non-parenchymal tissue or exudates, and for assessment of lung structure on 3D reconstructions of lungs scanned with microCT.
| S-EPMC7511023 | biostudies-literature
Project description:Data acquisition in (pre)clinical studies is often based on a hypothesis. Numerical algorithms, however, may help to find biomarkers from existing data without formulating any hypothesis. By simply assessing whether a statistical relationship exists between two parameters from a (unlimited) database, every (in)conceivable combination of data becomes a hypothesis. The aim was to create an unbiased and highly automated approach for secondary analysis of (pre)clinical research, including the possibility of a non-linear functional relationship. In our example, an almost homogeneous database was formed by overall 45 parameters (vital, blood and plasma parameters) measured in 11 individual experimental studies at 6 different time points using 57 rats without and 63 rats with systemic inflammation following lipopolysaccharide infusion. For each rat, four group classifiers (treatment, survival, study, ID) were used to get valid samples by a later filtering of the statistical base. Any information about the hypothesis leading to the respective studies was suppressed. In order to assess whether a statistical relationship exists, a total of six different functional prototypes (linear and non-linear) were postulated and examined for their regression. Regression quality, correlation and significance were obtained in form of matrices. In our example, ultimately 510 300 regressions were optimized, automatically evaluated and filtered. The developed algorithm is able to reveal statistical relationships from a nearly crude database with low effort by systematic and unbiased analysis. The finding of well-known correlations proves its reliability, whose validity could be increased by clean aggregation of different studies. In addition, new interesting hints for future research could be gained. Thus, unknown markers can be found which are associated with an increased risk of death during systemic inflammation and sepsis. A further development of the program is planned including multiple regressions (more than two parameters could be related to each other) or cluster analysis.
| S-EPMC6859257 | biostudies-literature
Project description:Assessing localization of the transient receptor potential vanilloid-1 (TRPV1) in skin nerve fibers is crucial for understanding its role in peripheral neuropathy and pain. However, information on the specificity and sensitivity of TRPV1 antibodies used for immunofluorescence (IF) on human skin is currently lacking. To find a reliable TRPV1 antibody and IF protocol, we explored antibody candidates from different manufacturers, used rat DRG sections and human skin samples for screening and human TRPV1-expressing HEK293 cells for further validation. Final specificity assessment was done on human skin samples. Additionally, we developed two automated image analysis methods: a Python-based deep-learning approach and a Fiji-based machine-learning approach. These methods involve training a model or classifier for nerve fibers based on pre-annotations and utilize a nerve fiber mask to filter and count TRPV1 immunoreactive puncta and TRPV1 fluorescence intensity on nerve fibers. Both automated analysis methods effectively distinguished TRPV1 signals on nerve fibers from those in keratinocytes, demonstrating high reliability as evidenced by excellent intraclass correlation coefficient (ICC) values exceeding 0.75. This method holds the potential to uncover alterations in TRPV1 associated with neuropathic pain conditions, using a minimally invasive approach.
| S-EPMC11574049 | biostudies-literature
Project description:Setup and optimisation of a high throughput pipeline for ChIPseq. The protocol used is ChIP carried out using the Agilent Bravo robot with subsequent Ilumina sequencing library preparation.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
2013-02-12 | E-ERAD-77 | biostudies-arrayexpress
Project description:Cryopreservation in a vitrified state has vast potential for long-term storage of tissues and organs that may be damaged by ice formation. However, the toxicity imparted by the high concentration of cryoprotectants (CPAs) required to vitrify these specimens remains a hurdle. To address this challenge, we previously developed a mathematical approach to design less toxic CPA equilibration methods based on the minimization of a toxicity cost function. This approach was used to design improved methods for equilibration of bovine pulmonary artery endothelial cells (BPAEC) with glycerol. To fully capitalize on the toxicity cost function approach, it is critical to describe the toxicity kinetics of additional CPAs, including multi-CPA mixtures that are commonly used for vitrification. In this work, we used automated liquid handling to characterize the toxicity kinetics of five of the most common CPAs (glycerol, dimethyl sulfoxide (DMSO), propylene glycol, ethylene glycol, and formamide), along with their binary and ternary mixtures for BPAEC. In doing so, we developed experimental methods that can be used to determine toxicity kinetics more quickly and accurately. Our results highlight some common CPA toxicity trends, including the relatively low toxicity of ethylene glycol and a general increase in toxicity as the CPA concentration increases. Our results also suggest potential new approaches to reduce toxicity, including a surprising toxicity neutralization effect of glycerol on formamide. In the future, this dataset will serve as the basis to expand our CPA toxicity model, enabling application of the toxicity cost function approach to vitrification solutions containing multiple CPAs.
| S-EPMC7897298 | biostudies-literature