Pigment Distribution Research Articles

Integrated deep learning approach for generating cross-polarized images and analyzing skin melanin and hemoglobin distributions.

Cross-polarized images are beneficial for skin pigment analysis due to the enhanced visualization of melanin and hemoglobin regions. However, the required imaging equipment can be bulky and optically complex. Additionally, preparing ground truths for training pigment analysis models is labor-intensive. This study aims to introduce an integrated approach for generating cross-polarized images and creating skin melanin and hemoglobin maps without the need for ground truth preparation for pigment distributions. We propose a two-component approach: a cross-polarized image generation module and a skin analysis module. Three generative adversarial networks (CycleGAN, pix2pix, and pix2pixHD) are compared for creating cross-polarized images. The regression analysis network for skin analysis is trained with theoretically reconstructed ground truths based on the optical properties of pigments. The methodology is evaluated using the VISIA VAESTRO clinical system. The cross-polarized image generation module achieved a peak signal-to-noise ratio of 35.514dB. The skin analysis module demonstrated correlation coefficients of 0.942 for hemoglobin and 0.922 for melanin. The integrated approach yielded correlation coefficients of 0.923 for hemoglobin and 0.897 for melanin, respectively. The proposed approach achieved a reasonable correlation with the professional system using actually captured images, offering a promising alternative to existing professional equipment without the need for additional optical instruments or extensive ground truth preparation.

Retinal G-protein-coupled receptor deletion exacerbates AMD-like changes via the PINK1-parkin pathway under oxidative stress.

The intake of high dietary fat has been correlated with the progression of age-related macular degeneration (AMD), affecting the function of the retinal pigment epithelium through oxidative stress. A high-fat diet (HFD) can lead to lipid metabolism disorders, excessive production of circulating free fatty acids, and systemic inflammation by aggravating the degree of oxidative stress. Deletion of the retinal G-protein-coupled receptor (RGR-d) has been identified in drusen. In this study, we investigated how the RGR-d exacerbates AMD-like changes under oxidative stress, both invivo and invitro. Fundus atrophy became evident, at 12 months old, particularly in the RGR-d + HFD group, and fluorescence angiography revealed narrower retinal vessels and a reduced perfusion area in the peripheral retina. Although rod electroretinography revealed decreasing trends in the a- and b-wave amplitudes in the RGR-d + HFD group at 12 months, the changes were not statistically significant. Mice in the RGR-d + HFD group showed a significantly thinner and more fragile retinal morphology than those in the WT + HFD group, with disordered and discontinuous pigment distribution in the RGR-d + HFD mice. Transmission electron microscopy revealed a thickened Bruch's membrane along the choriocapillaris endothelial cell wall in the RGR-d + HFD mice, and the outer nuclear layer structure appeared disorganized, with reduced nuclear density. Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated significantly lower levels of 25(OH)-vitamin D3 metabolites in the RGR-d + HFD group. Under oxidative stress, RGR-d localized to the mitochondria and reduced the levels of the PINK1-parkin pathway. RGR-d mice fed an HFD were used as a new animal model of dry AMD. Under high-fat-induced oxidative stress, RGR-d accumulated in the mitochondria, disrupting normal mitophagy and causing cellular damage, thus exacerbating AMD-like changes both invivo and invitro.

3-D Visualization of Atlantic salmon skin through Ultrasound and Photoacoustic Microscopy.

Three-dimensional photoacoustic imaging (PAM) has emerged as a promising technique for non-invasive label-free visualization and characterization of biological tissues with high spatial resolution and functional contrast. The application of PAM and ultrasound as a microscopy technique of study for Atlantic salmon skin is presented here. A custom ultrasound and photoacoustic experimental setup was used for conducting this experiment with a sample preparation method where the salmon skin is embedded in agarose and lifted from the bottom of the petridish. The results of C-scan, B-scan, and overlayed images of ultrasound and photoacoustic are presented. The results are then analyzed for understanding the pigment map and its relation to salmon behavior to external stimuli. The photoacoustic images are compared with the optical images and analyzed further. A custom colormap and alpha map is designed and the matrices responsible for PAM and ultrasound are inserted together to overlay the ultrasound image and PAM image on top of each other. In this study, we propose an approach that combines scanning acoustic microscopy (SAM) images with PAM images for providing a comprehensive understanding of the salmon skin tissue. Overlaying acoustic and photoacoustic images enabled unique visualization of tissue morphology, with respect to identification of structural features in the context of their pigment distribution.

A Study on Pigment Composition of Buddhist Cave Paintings Based on Hyperspectral Technology

The value of the Buddhist cave lies not only in the Buddha statues but also in the surface painting. Hyperspectral imaging technology, as an emerging and effective method for component identification, offers a non-contact and non-destructive approach to the preservation and restoration of oil paintings. This study employed hyperspectral cameras to capture common pigments on the surfaces of Buddhist caves. Then, the results were processed and used as a database to identify the paintings. Additionally, a series of experiments were conducted to examine the impact of binder, substrate types, and pigment sizes on the reflectance spectrum of the paints. The Spectral Angle Matching (SAM) algorithm was then used to analyze the Yuanjue Cave and Qiqushan Stone Carvings of the Tang Dynasty in China. The findings revealed that the position of absorption peaks in the reflectance spectra is not significantly influenced by the substrate but is affected by the binder. Moreover, the absorption depth varies regularly with particle size. Furthermore, the spectral matching results demonstrate that components can be accurately identified even for similar colors. Based on the pigment distribution, the study also inferred specific details of ancient paintings, including the painting steps and hidden information in the manuscript layout. These findings hold significant implications for the restoration of representative surface paintings of the Tang Dynasty Buddhist cave, providing a reference for the selection of restoration materials and methods.

Insights into phthalocyanine blue pigment dispersion: Modeling particle size distribution and grinding rate constants

The study presents an advanced mathematical model aimed at enhancing the understanding of pigment dispersion processes, with a particular focus on analyzing the dynamics of particle size distribution and determining grinding rate constants. Pigmented dispersions are crucial in various industries, including paints, coatings, and inks, where achieving optimal particle size distribution is vital for product quality. This investigates the relationship between grinding duration and pigment dispersion, aiming to establish empirical equations for the grinding rate constant as a function of particle size distribution and feed rate. Through experimental validation, the developed kinetic model provides insights into the dynamics of pigment dispersion and offers predictive capabilities for optimizing dispersion processes. Understanding the underlying mechanisms of pigment dispersion through mathematical modeling contributes to enhancing the performance and quality of final products in diverse industrial applications. The development of a new kinetic model, effective mathematical model is proposed to accurately simulate the evolution was applicable for the particle size from 32.67 to 122.4 nm distribution of pigment during comminution processes. In addition, it was observed that the kinetic model was not applicable for the particle size from 166.2 to 190.1 nm and also confirmed that the grinding was completed within 40 min, which was possible for uniform particle size distribution.

Adaptive superpixel segmentation and pigment identification of colored relics based on visible spectral images

This work explores the extraction of the spatial distribution and chemical composition information of pigments in colored relics through visible spectral images. An adaptive superpixel segmentation method is proposed to extract the spatial distribution information of pigments. Quadtree decomposition is applied to generate nonuniform initial seed points based on the image homogeneity. These seed points are used as the initial cluster centers in an extended simple linear iterative clustering (SLIC) algorithm for visible spectral images to create superpixels of varying sizes that reflect the homogeneity. Each superpixel is subsequently treated as an individual area in the colored relics, and a pigment identification method based on the visible spectral reflectance is proposed to identify the pigments in these areas. A standard reference database is constructed using samples that simulate the painting process of ancient wall paintings in the Mogao Grottoes. Geometric features, which are characterized by the linear combination of the normalized visible spectral reflectance, its slope and its curvature, are designed to represent the chemical composition of pigments. The geometric features of the superpixels are compared with those of the pigments in the database using the Euclidean distance to determine the pigments in each area of the colored relics. This work is expected to provide scientific guidance for pigment selection in the color restoration of colored relics.

Coloring Multilayer Zirconia May Affect Its Optical and Mechanical Properties

The coloring process of monolithic dental zirconia caused considerable debate on the possible effects of different coloring methods. The main objective of this study was to investigate the influence of pigments in 3 multilayer 5-mol% yttria partially stabilized zirconia (5Y-PSZ) disks (Lava Esthetic A2 [Zr-AGG_A2] and Bleach [Zr-AGG_BL], both 3M Oral Care, and Katana STML A2 [Zr-NoAGG], Kuraray Noritake). The influence of pigment addition on the translucency parameter (TP00), fracture toughness, Vickers hardness, biaxial strength, and hydrothermal stability was assessed and correlated with the microstructure and phase composition. The pigment composition and distribution were evaluated by light and fluorescence microscopy, electron probe microanalysis, and nano–scanning electron microscopy. The chemical and phase composition and aging behavior were assessed using X-ray fluorescence and X-ray diffraction, respectively, while the aging sensitivity of the pigments was evaluated using micro-Raman spectroscopy. In contrast to Zr-NoAGG, possessing a typical 5Y-PSZ microstructure, the pigment additions in both Zr-AGG_A2/BL zirconia resulted in large yellow and blue fluorescent Er-, Hf-, and Al-containing agglomerates composed of small grains (0.57 µm and 0.38 µm, respectively, vs. 0.92 µm for the surrounding grains) with lower Y2O3 content. Zr-AGG_A2 had the lowest aging resistance, with transformation degradation occurring exclusively within the pigment agglomerates. All zirconia grades had a high Y2O3 content (4.2%–5.7 mol%) tetragonal ZrO2 phase and a high (42%–55 wt%) cubic ZrO2 phase content. Although no statistical differences were measured for hardness and toughness, Zr-NoAGG had a significantly higher TP00, higher flexural strength, and lower mechanical reliability compared to both Zr-AGG_A2/BL zirconia. The rare-earth oxide-containing zirconia agglomerates that were added as pigments to the multilayered monolithic Zr-AGG_A2/BL zirconia are the cause for their lower optical and mechanical properties and reduced aging resistance.

Drug-Induced Pigmentation: A Review.

Drug-induced pigmentation (DIP) is estimated to account for 20% of all cases of acquired hyperpigmentation. Over 50 agents have been implicated, including antibiotics, antimalarials, antiretrovirals, antipsychotics, prostaglandin analogs, heavy metals, and chemotherapeutic agents. The skin, mucosal surfaces, nails, and hair can all be affected, with the color, distribution, onset, and duration of pigmentation varying between offending agents. Both a thorough physical examination and medication history are necessary to determine the offending agent. In terms of mechanism, DIP occurs most frequently through the accumulation of melanin within the dermis but also by drug accumulation, pigment synthesis, and iron deposition. Photoprotection, including applying a broad-spectrum sunscreen, wearing photoprotective clothing, and seeking shade, plays an important role in the prevention of exacerbation of DIP. Multiple lasers, including the picosecond alexandrite, Q-switched Nd:YAG, Q-switched alexandrite, and Q-switched ruby lasers, have been successful in obtaining clearance of DIP. In this review, we examine the unique characteristics of each of the inciting agents in terms of incidence, clinical presentation, time to onset and resolution, and pathogenesis.

New insights into the relationship between optical response and physicochemical properties in apple flesh: Hyperspectral microscope imaging technology

Hyperspectral microscope imaging (HMI) technique was employed to assess the changes in physicochemical parameters and microstructure of ‘Golden Delicious’ apples flesh during storage. Four regions of interest (ROIs), including whole-cell ROI, intercellular space ROI, cytoplasm ROI, and cell wall ROI were investigated to assess their relationships with physicochemical parameters. Different ROIs presented similar vibrational profiles, but with slight differences in spectral intensity, especially in the range of 800–1000 nm. Spectral angle mapper (SAM) was applied to the HMI of apple tissues at different storage stages to clearly show the structural changes of parenchyma cells, while principal component analysis (PCA) could highlight the distribution of sugars, water and pigments in apple flesh at the cellular scale. Simultaneously with the degradation of acid-soluble pectin (ASP), middle lamella dissolution and increased intercellular space were observed using SEM and TEM. Single feature variables were used to construct linear models based on pearson correlation analysis, with R2 of 0.96 for moisture at 982 nm, 0.85 for water-soluble pectin (WSP) at 420 nm, 0.82 for L* at 946 nm, 0.77 for soluble solids content (SSC) at 484 nm, and 0.66 for firmness at 490 nm. This work demonstrated the great potential of HMI technology as a fast, accurate and efficient solution for assessing the quality of ‘Golden Delicious’ apples.

High-resolution compound-specific mapping in works of art via data fusion of MA-XRPD with hyperspectral data (part 1: Method evaluation)

BackgroundHyperspectral imaging techniques have emerged as powerful tools for non-invasive investigation of artworks. This paper employs either reflectance imaging spectroscopy (RIS) or macroscopic X-ray fluorescence (MA-XRF) imaging in combination with macroscopic X-ray powder diffraction (MA-XRPD) for state-of-the-art chemical imaging of painted cultural heritage artefacts. While RIS can provide molecular information and MA-XRF can offer elemental distribution maps of paintings of high lateral resolution, the unique advantage of MA-XRPD lies in its ability to visualize the distributions of specific pigments and estimate in a quantitative manner the relative concentrations of the crystalline phases at the surface of artworks. However, MA-XRPD is more time-consuming and offers a lower lateral resolution than RIS and MA-XRF. ResultsThis study introduces a machine learning (ML) approach to obtain the distribution of specific compounds on the surface of artworks with a resolution that is comparable to that of RIS and MA-XRF data but with the compound specificity of MA-XRPD. The general aim is to expedite non-destructive artwork imaging analysis by fusing data from different imaging modalities via machine learning models. The effect of preprocessing techniques to enhance the predictive accuracy of the models is explored. The paper demonstrates the method's efficacy on a 16th-century illuminated manuscript, showcasing the feasibility of predicting compound-specific distribution maps. Three evaluation methods—visual examination of the predicted distribution, root mean square errors (RMSE), and feature permutation importance (FPI)—are employed to assess model performance. Fusing MA-XRF with MA-XRPD led to the best RMSE scores overall. However, fusing the RIS and MA-XRPD data blocks also yield very satisfactory and easily interpretable high-resolution compound maps. SignificanceWhile MA-XRPD allows for highly specific imaging of artworks, its time-consuming nature and limited resolution presents a bottleneck during non-invasive imaging of painted works of art. By integrating data from more time-efficient hyperspectral techniques such as MA-XRF and RIS, and employing machine learning, we expedite the process without compromising accuracy. The fusion process can also denoise the distribution maps, improving their readability for heritage professionals and art historical scholars.

Spatial phytoplankton community structure revealed by photosynthetic pigments in the tropical estuarine-coastal zone (Bangladesh)

To explore the variation of phytoplankton community along the Bakkhali river estuary and its adjacent coastal water in the north of the Bay of Bengal, total Chl-a (TChl-a) concentrations and group-specific photosynthetic pigments were investigated during April 2017. Distinct spatial distribution was observed in temperature, turbidity and nutrient concentrations as well as in TChl-a concentrations, showing a seaward decreasing pattern. The different distribution of phytoplankton pigments and functional groups along the gradients was also observed. Chlorophyll-b and zeaxanthin showed their highest abundance in the turbid riverine water, while alloxanthin and prasinoxanthin dominated in the coastal water. High concentrations of fucoxanthin, peridinin and hex-fucoxanthin were associated with high-light availability and showed a seaward increasing trend. Three phytoplankton groups can be classified: the riverine group (chlorophytes and cyanobacteria), the coastal group (cryptophytes and prasinophytes) and the offshore group (diatoms, dinoflagellate and haptophytes_type 6). The predominance of cryptophytes (avg. 48%) over diatoms (avg. 28%) was basically influenced by the scarcity of nitrogen and silicate relative to phosphate. Not only availability of nutrients, the photosynthetically active radiation also plays a key role in regulating TChl-a, photosynthetic pigments and functional groups in this tropical estuarine-coastal zone.

Sustainable pre-treatment of cellulose knitwear in digital pigment printing processes

PurposeIn the field of research on the application of digital printing to textile materials, there are still many research issues that arise from the very demanding interaction of digital printing technology and the complex, heterogeneous surface system of textile materials. This is precisely why the area of pre-treatment of textile materials is in need of research, and the purpose of this research was to establish the level of influence of physical and chemical activation of the textile surface with plasma and the possibility of improving the quality of the print and colour reproduction.Design/methodology/approachThe paper deals with the possibility of applying argon and oxygen cold low-pressure plasma in the processing of cellulose knitted fabrics, with the aim of improving the quality of the print and colour reproduction in digital pigment inkjet printing. The selected raw material samples were 100% raw cotton and lyocell. After plasma treatment, the samples were printed by digital ink jet printing with water-based pigment printing ink. An analysis of the micromorphological structure of untreated and plasma-treated samples before and after printing was carried out, and a comparative analysis of the colour of the printed elements was carried out depending on the pre-treatment.FindingsThe conducted research showed a positive influence of plasma pre-treatment on the coverage of the fibre surface with pigments, the uniformity of pigment distribution along the fibre surface and the uniformity of the distribution of the polymeric binder layer. This has a positive effect on colour reproduction. Also, certain improvements in colourfastness to washing were obtained.Research limitations/implicationsConsidering the complexity of the topic, although exhaustive, this research is not sufficient in itself, but opens up new questions and gives ideas for further research that must be carried out in this area.Practical implicationsAlso, this kind of research contributes to the possibility of adopting the idea of industrial plasma transformation, as an ecologically sustainable functionalisation of textiles, which has not yet been established.Originality/valueThis research is certainly a contribution to the establishment of acceptable textile pre-treatment methods in the field of digital printing, as one of the key quality factors in digital textile printing (DTP). Considering the still large number of obstacles and unanswered questions encountered in the field of digital printing on textiles, this kind of research is a strong contribution to the understanding of the fundamental mechanisms of the complex interaction between printing ink and textile.

Distinct genetic origins of eumelanin levels and barring patterns in cichlid fishes.

Pigment patterns are incredibly diverse across vertebrates and are shaped by multiple selective pressures from predator avoidance to mate choice. A common pattern across fishes, but for which we know little about the underlying mechanisms, is repeated melanic vertical bars. To understand the genetic factors that modify the level or pattern of vertical barring, we generated a genetic cross of 322 F2 hybrids between two cichlid species with distinct barring patterns, Aulonocara koningsi and Metriaclima mbenjii. We identify 48 significant quantitative trait loci that underlie a series of seven phenotypes related to the relative pigmentation intensity, and four traits related to patterning of the vertical bars. We find that genomic regions that generate variation in the level of eumelanin produced are largely independent of those that control the spacing of vertical bars. Candidate genes within these intervals include novel genes and those newly-associated with vertical bars, which could affect melanophore survival, fate decisions, pigment biosynthesis, and pigment distribution. Together, this work provides insights into the regulation of pigment diversity, with direct implications for an animal's fitness and the speciation process.

Multimodal phenotyping of foveal hypoplasia in albinism and albino-like conditions: a pediatric case series with adaptive optics insights

Aim of the present study is to evaluate the relationship between genetic and phenotypic data in a series of patients affected by grade I and II of foveal hypoplasia with stable fixation and good visual acuity using multimodal imaging techniques. All patients underwent complete clinical and instrumental assessment including structural Optical Coherence Tomography (OCT), OCT Angiography and Adaptive Optics (AO) imaging. Central macular thickness (CMT), inner nuclear layer (INL), vessel density in superficial capillary plexus were the main variables evaluated with OCT technology. Cone density, cone spacing, cone regularity, cone dispersion and angular density were the parameters evaluated with AO. Genetic evaluation and trio exome sequencing were performed in all affected individuals. Eight patients (3 males and 5 females) with a mean age of 12.62 years (range 8–18) were enrolled. The mean best corrected visual acuity (BCVA) was 0.18 ± 0.13 logMAR, mean CMT was 291.9 ± 16.6 µm and INL was 26.2 ± 4.6 µm. The absence of a foveal avascular zone (FAZ) was documented by examination of OCT-A in seven patients in the superficial capillary plexus. However, there was a partial FAZ in the deep plexus in patients P5 and P8. Of note, all the patients presented with major retinal vessels clearly crossing the foveal center. All individuals exhibited a grade I or II of foveal hypoplasia. In 5 patients molecular analyses showed an extremely mild form of albinism caused by compound heterozygosity of a TYR pathogenic variant and the hypomorphic p.[Ser192Tyr;Arg402Gln] haplotype. One patient had Waardenburg syndrome type 2A caused by a de novo variant in MITF. Two patients had inconclusive molecular analyses. All the patients displayed abnormalities on OCT-A. Photoreceptor count did not differ from normal subjects according to the current literature, but qualitative analysis of AO imaging showed distinctive features likely related to an abnormal pigment distribution in this subset of individuals. In patients with foveal hypoplasia, genetic and multimodal imaging data, including AO findings, can help understand the physiopathology of the foveal hypoplasia phenotype. This study confirms that cone density and visual function can both be preserved despite the absence of a pit.

Coat colour in marsupials: genetic variants at the ASIP locus determine grey and black fur of the brushtail possum.

The possession of fur or hair is a defining characteristic of mammals and can occur in a variety of colours and patterns. While genetic determinants of coat colour are well described in eutherian 'placental' mammals, the other major mammalian infraclass, marsupials, is grossly understudied. The fur of the common brushtail possum (Trichosurus vulpecula), an iconic native mammal found throughout Australia and introduced into Aotearoa New Zealand, possesses two main colour morphs: grey and black. To identify genetic variants associated with coat colour, we performed a genome-wide association study (GWAS) with genotype by sequencing (GBS) data. Single nucleotide variants (SNVs) on chromosome 3, close to the agouti signalling protein (ASIP) gene that controls the temporal and spatial distribution of pigments in eutherian mammals, were identified. Fine-mapping identified a C>T variant at chr3:100483705 that results in a ASIP:p.Arg115Cys missense substitution, and animals homozygous for this variant have black fur. In addition to uncovering the first genetic determinant of coat colour in a natural marsupial population, comparative analysis of ASIP in divergent marsupial species identified the dasyurids as having accelerated evolution, reflecting their well described diversity of coat colour and pattern.

THE REMEDIATION METHOD AS A FACTOR SHAPING THE PIGMENT PROFILE OF SCOTS PINE ON TECHNOGENIC LAND

Background. It is important to study how the remediation method influences the formation of the pigment complex in Scots pine, Pinus sylvestris L., growing on technogenic land. Thorough understanding of the influence produced by a heterogeneous environment on the content and distribution of pigments in conifers enables us to study the adaptive mechanisms of the species more comprehensively. In turn, information about these mechanisms can be used to create new methods for improving the quality and stability of tree stands. Purpose. The study was designed to explore the effect of the remediation method on the pigment complex forming in Scots pine during a post-technogenic succession in southern Karelia. Material and methods. Surveys were carried out in adjacent sample plots located in a decommissioned sand-and-gravel quarry and in a natural lingonberry-type pine forest site in July 2021 and 2022. The study objects were Scots pine trees growing in a natural forest site and in quarry sites remediated by forest planting. The optical density of the solutions was determined using SF-2000 spectrophotometer. Statistical data processing was done using Statistica 10 software (StatSoft Inc., USA). Results. During the two years of the study, the pigment content was the highest in needles of the trees growing on more fertile soils compared to those on poor man-made soils. The of Cl a /Cl b ratio in the needles of trees growing on poor soil was higher than in the fertilized area of the quarry or in the natural forest site in both years of the study, indicating that the plants’ pigment complex adapted to the unfavorable environmental conditions by increasing the proportion of Cl a among green pigments. Conclusions. The findings prove that the remediation method has a significant shaping effect on the pigment profile of Scots pine during post-technogenic successions.

An alternative macro‐Raman mapping algorithm, adapting the numbers of accumulations

AbstractMacro‐Raman mapping is an approach that is well suited to study the distribution of molecules over a surface of typically several cm2, such as the pigment distribution on a painting. During such an experiment, thousands Raman spectra are recorded in a predefined array of points. As there can be a huge difference in Raman sensitivity between different molecules, an alternative approach is proposed, where measurement times are adapted according to the quality of the Raman scatterer. Therefore, an iterative process is implemented, involving recording short accumulations, followed by a quick evaluation. As soon as the accumulated spectrum reaches a quality criterium, measurement of the next point is started, while in the other case further accumulations are added. The influence of using multiple accumulations opposite to a single measurement for a prolonged period has been assessed by comparing the overall measurement time and the spectral intensity of the main Raman band (520.5 cm−1) of silicon. Another prerequisite for this algorithm to be successful is the need for a quick and reliable evaluation of the spectral quality. This was examined by applying this function on the accumulations of Raman spectra of 49 paint samples from a colour chart. Finally, the variable‐accumulation algorithm is applied during a macro‐Raman mapping experiment of a watercolour painting on paper. Despite a significant gain in overall measuring time, this novel approach yields a qualitative data set that can be used for creating clear Raman maps, using different data processing methods.

Coloration in Equine: Overview of Candidate Genes Associated with Coat Color Phenotypes.

Variation in coat color among equids has attracted significant interest in genetics and breeding research. The range of colors is primarily determined by the type, concentration, and distribution of melanin pigments, with the balance between eumelanin and pheomelanin influenced by numerous genetic factors. Advances in genomic and sequencing technologies have enabled the identification of several candidate genes that influence coat color, thereby clarifying the genetic basis of these diverse phenotypes. In this review, we concisely categorize coat coloration in horses and donkeys, focusing on the biosynthesis and types of melanin involved in pigmentation. Moreover, we highlight the regulatory roles of some key candidate genes, such as MC1R, TYR, MITF, ASIP, and KIT, in coat color variation. Moreover, the review explores how coat color relates to selective breeding and specific equine diseases, offering valuable insights for developing breeding strategies that enhance both the esthetic and health aspects of equine species.

Coexistence of nonfluorescent chromoproteins and fluorescent proteins in massive Porites spp. corals manifesting a pink pigmentation response.

Several fluorescent proteins (FPs) and chromoproteins (CPs) are present in anthozoans and play possible roles in photoprotection. Coral tissues in massive corals often display discoloration accompanied by inflammation. Incidences of the pink pigmentation response (PPR) in massive Porites, described as inflammatory pink lesions of different shapes and sizes, has recently increased worldwide. FPs are reported to be present in PPR lesions, wherein a red fluorescent protein (RFP) appears to play a role in reducing reactive oxygen species. However, to date, the biochemical characterization and possible roles of the pigments involved are poorly understood. The present study aimed to identify and characterize the proteins responsible for pink discoloration in massive Porites colonies displaying PPRs, as well as to assess the differential distribution of pigments and the antioxidant properties of pigmented areas. CPs were extracted from PPR lesions using gel-filtration chromatography and identified via genetic analysis using liquid chromatography-tandem mass spectrometry. The coexistence of CPs and RFP in coral tissues was assessed using microscopic observation. Photosynthetic antivity and hydrogen peroxide-scavenging activitiy were measured to assess coral stress conditions. The present study revealed that the same CP (plut2.m8.16902.m1) isolated from massive Porites was present in both the pink spot and patch morphologies of the PPR. CPs were also found to coexist with RFP in coral tissues that manifested a PPR, with a differential distribution (coenosarc or tip of polyps' tentacles). High hydrogen peroxide-scavenging rates were found in tissues affected by PPR. The coexistence of CPs and RFP suggests their possible differential role in coral immunity. CPs, which are specifically expressed in PPR lesions, may serve as an antioxidant in the affected coral tissue. Overall, this study provides new knowledge to our understanding of the role of CPs in coral immunity.

Spectrum-based deep learning framework for dermatological pigment analysis and simulation

Background:Deep learning in dermatology presents promising tools for automated diagnosis but faces challenges, including labor-intensive ground truth preparation and a primary focus on visually identifiable features. Spectrum-based approaches offer professional-level information like pigment distribution maps, but encounter practical limitations such as complex system requirements. Methods:This study introduces a spectrum-based framework for training a deep learning model to generate melanin and hemoglobin distribution maps from skin images. This approach eliminates the need for manually prepared ground truth by synthesizing output maps into skin images for regression analysis. The framework is applied to acquire spectral data, create pigment distribution maps, and simulate pigment variations. Results:Our model generated reflectance spectra and spectral images that accurately reflect pigment absorption properties, outperforming spectral upsampling methods. It produced pigment distribution maps with correlation coefficients of 0.913 for melanin and 0.941 for hemoglobin compared to the VISIA system. Additionally, the model’s simulated images of pigment variations exhibited a proportional correlation with adjustments made to pigment levels. These evaluations are based on pigment absorption properties, the Individual Typology Angle (ITA), and pigment indices. Conclusion:The model produces pigment distribution maps comparable to those from specialized clinical equipment and simulated images with numerically adjusted pigment variations. This approach demonstrates significant promise for developing professional-level diagnostic tools for future clinical applications.