Color Enhancement Research Articles

Underwater Organism Color Fine-Tuning via Decomposition and Guidance

Due to the wavelength dependent light attenuation and scattering, the color of the underwater organism usually appears distorted. The existing underwater image enhancement methods mainly focus on designing networks capable of generating enhanced underwater organisms with fixed color. Due to the complexity of the underwater environment, ground truth labels are difficult to obtain, which results in the non-existence of perfect enhancement effects. Different from the existing methods, this paper proposes an algorithm with color enhancement and color fine-tuning (CECF) capabilities. The color enhancement behavior of CECF is the same as that of existing methods, aiming to restore the color of the distorted underwater organism. Beyond this general purpose, the color fine-tuning behavior of CECF can adjust the color of organisms in a controlled manner, which can generate enhanced organisms with diverse colors. To achieve this purpose, four processes are used in CECF. A supervised enhancement process learns the mapping from a distorted image to an enhanced image by the decomposition of color code. A self reconstruction process and a cross-reconstruction process are used for content-invariant learning. A color fine-tuning process is designed based on the guidance for obtaining various enhanced results with different colors. Experimental results have proven the enhancement ability and color fine-tuning ability of the proposed CECF. The source code is provided in https://github.com/Xiaofeng-life/CECF.

ChromaFusionNet (CFNet): Natural Fusion of Fine-Grained Color Editing

Digital image enhancement aims to deliver visually striking, pleasing images that align with human perception. While global techniques can elevate the image's overall aesthetics, fine-grained color enhancement can further boost visual appeal and expressiveness. However, colorists frequently face challenges in achieving accurate, localized color adjustments. Direct composition of these local edits can result in spatial color inconsistencies. Existing methods, including color style transfer and image harmonization, exhibit inconsistencies, especially at boundary regions. Addressing this, we present ChromaFusionNet (CFNet), a novel approach that views the color fusion problem through the lens of image color inpainting. Built on the Vision Transformer architecture, CFNet captures global context and delivers high-fidelity outputs, seamlessly blending colors while preserving boundary integrity. Empirical studies on ImageNet and COCO datasets demonstrate CFNet's superiority over existing methods in maintaining color harmony and color fidelity. Robustness evaluations and user studies have further validated the effectiveness of CFNet. In conclusion, CFNet introduces an innovative approach to seamless, fine-grained color fusion, paving the way for advancements in the domain of fine-grained color editing. Code and pretrained models are available at our project page: https://yidong.pro/projects/cfnet.

Learn to enhance the low-light image via a multi-exposure generation and fusion method

In low-light image enhancement, single-exposure images contain a limited dynamic range, which hinders the restoration of contrast and texture. To address these problems, we propose a multi-exposure generation and fusion method (MEGF), which simulates multi exposure images and performs feature fusion for low light image enhancement. First, we propose a Multi-Exposure Generation (MEG) block, which generates images with different exposure levels based on the input low-light images. The MEG block employs information entropy as an evaluation measure to prevent the underexposed or overexposed image generation. Then, the Perceptual Importance based Multi-Exposure Feature Enhancement (PIMEFE) module has been developed to fuse the multi-exposure features using the Perceptual Importance-based Feature Fusion (PIFF) module. The PIFF module selects the well-exposed features from the multi-exposure features processed by the Multi Scale Recursive Feature Enhancement (MSRFE) block. Finally, the fused features are input to the Curve Adjustment (CA) block for fine-tuning and provide color enhancement to the fused features. Moreover, we propose the Multiple Exposure Recursive Fusion (MERF) module which estimates the adjustment factors for the CA block with the guidance of multi-exposure features. Experimental results demonstrate that our method outperforms other techniques in terms of image signal-to-noise ratio, structural similarity, and color accuracy on both real and synthetic datasets.

Research on the electronic control system for multispectral infrared detectors

In order to acquire and fully exploit multispectral information of scenes, and to establish a foundation for the research of multispectral image algorithms, a laboratory has developed a multispectral infrared detector capable of detecting short-wave infrared, mid-wave infrared, and long-wave infrared in three bands. Additionally, a preliminary electronic control system has been designed. The system employs a field-programmable gate array (FPGA) to accomplish the timing control, data acquisition, preprocessing of individual channel images, and multispectral image fusion of the detector. The preprocessing involves black level correction, blind element correction, non-uniformity correction, and histogram equalization of the raw images. For trispectral fusion, color enhancement is applied to linearly combined images in the YUV color space using a color transfer method. The system utilizes a pipeline design to ensure algorithm efficiency. In simulation, the electronic control system for the multispectral infrared detector obtains trispectral information of the scenes, and through image preprocessing and fusion, enhances the understanding of scene information.

ENHANCEMENT OF UNDERWATER IMAGES WITH ARTIFICIAL INTELLIGENCE

Abstract. Camera systems using optical sensors have made great progress in recent years in obtaining underwater images. Very high-resolution images can be obtained with underwater cameras. However, it becomes difficult to process the image obtained due to many distorting factors such as inhomogeneous underwater lighting, low contrast, blur, sea snow. For this purpose, image enhancement algorithms are used to minimise the problems in the captured images. The physical characteristics of the underwater environment cause degradation effects that are not found in normal images captured in air. Due to the effects such as colour distortion, low contrast and brightness, blurred details in images captured in this type of environment, the usage area of these images is very limited. This project aims to use artificial intelligence methods for colour enhancement of underwater images. In addition, one of the main objectives of the project is to examine the effect of colour enhancement applied to images on other areas of use. Within the scope of the project, An Underwater Image Enhancement Benchmark Dataset and Beyond Dataset and Large Scale Underwater Image Dataset datasets were used. In our study, U-Shape Transformer architecture and Pix2Pix architecture were tested for their usability for image enhancement. According to the results obtained, Pix2Pix architecture achieved the highest accuracy. Accuracy results were obtained as 22.5884 and 0.8764 for PSNR and SSIM, respectively using UIEB dataset. The accuracy values for LSUI dataset are 25.1010 and 0.8440 for PSNR and SSIM, respectively.

Efficacy of texture and color enhancement imaging for short-type single-balloon enteroscopy-assisted biliary cannulation in patients with Roux-en-Y gastrectomy: Multicenter study (with video).

Texture and color enhancement imaging (TXI) reportedly improves the identification of the papilla of Vater for selective biliary cannulation compared with white light imaging (WLI). This multicenter study evaluated the efficacy of short-type single-balloon enteroscopy (SBE)-assisted biliary cannulation using a new-generation image-enhanced endoscopy processing system equipped with TXI in patients who underwent Roux-en-Y gastrectomy. Patients with Roux-en-Y gastrectomy with a native papilla, and underwent short SBE-assisted biliary cannulation during endoscopic retrograde cholangiopancreatography-related procedures between January 2019 and April 2023 were retrospectively reviewed. Outcomes of biliary cannulation using TXI and WLI were compared. The primary outcome was time to successful biliary cannulation. Thirty-three patients underwent biliary cannulation with TXI and 98 underwent WLI. The biliary cannulation success rates and median time to successful biliary cannulation with TXI and WLI were 93.9% (95% confidence interval [CI] 79.8-99.3%) and 83.7% (95% CI 74.8-90.4%), respectively (P = 0.14), and 10 min (interquartile range [IQR] 2.5-23.5) and 18 min (IQR 9.75-24), respectively (P = 0.04). Biliary cannulation with TXI required a shorter cannulation time than that required withWLI. Adverse event rates with TXI and WLI did not differsignificantly (P = 0.58). Multivariate linear regression analysis showed that the use of TXI and short length of oral protrusion were associated with a shorter successful biliary cannulation time. Short SBE-assisted biliary cannulation was effective and safe on TXI in patients who underwent Roux-en-Y gastrectomy, and achieved shorter successful biliary cannulation time.

Restoration of UAV-Based Backlit Images for Geological Mapping of a High-Steep Slope.

Unmanned aerial vehicle (UAV)-based geological mapping is significant for understanding the geological structure in the high-steep slopes, but the images obtained in these areas are inevitably influenced by the backlit effect because of the undulating terrain and the viewpoint change of the camera mounted on the UAV. To handle this concern, a novel backlit image restoration method is proposed that takes the real-world application into account and addresses the color distortion issue existing in backlit images captured in high-steep slope scenes. Specifically, there are two main steps in the proposed method, which consist of the backlit removal and the color and detail enhancement. The backlit removal first eliminates the backlit effect using the Retinex strategy, and then the color and detail enhancement step improves the image color and sharpness. The author designs extensive comparison experiments from multiple angles and applies the proposed method to different engineering applications. The experimental results show that the proposed method has potential compared to other main-stream methods both in qualitative visual effects and universal quantitative evaluation metrics. The backlit images processed by the proposed method are significantly improved by the process of feature key point matching, which is very conducive to the fine construction of 3D geological models of the high-steep slope.

Evaluating the Bioactive Compounds of Beetroot and Their Pharmacological Activities in Promoting Health

Purpose: Lifestyle modification and sedentary life have led to multiple comorbidities which necessitate exploitation of underutilized novel ingredients in daily life. This comprehensive review aimed at providing valuable insight into the diverse pharmacological activities of beetroot bioactive compounds and their health enhancing properties. Furthermore, this review explored emerging research by scientific community for utilization of beetroot in the development of novel functional food products. 
 Materials and Methods: The scientific studies focusing on the biological activity and therapeutic potential of beetroot for health parameters were included in this study. Database search was made using google scholar, PubMed and research gate which generated a total of 200 papers. Out of which, only 63 met the inclusion criteria of this study. Inclusion criteria included literature focusing on beetroot’s bioavailability, plant pigments, bioactive compounds, health benefits, as well as studies describing food applications. This review includes studies between 2014 and 2023.
 Findings: The main findings suggested that a prominent bioactive compound and natural betalain pigment in beetroot, exhibits potential anti-inflammatory, anti-carcinogenic and anti-depressive properties. The anti-oxidant activity of betalain is effective against oxidative stress and play a role in preventing and mitigating chronic diseases. Bioactive components including, nitrate content, betanin and betacyanin, potentially modulate blood pressure and promote cardiovascular health. Furthermore, beetroot derived polyphenols, carotenoids, vitamins and minerals contribute to bone health, immune function and overall well-being. Food product development based studies demonstrate an overall improvement in the nutritional and sensory profile. 
 Implications to Theory, Practice and Policy: Further research on bioactive components of multiple varieties of beetroot is recommended to reassess the underlying mechanisms and optimal dosage for unlocking their potential for medicinal, nutraceuticals and dietary interventions. More research is needed by food industrialists and scientists to explore the potential of beetroot pigments as non-synthetic food additives particularly color enhancer in various food formulations.

Ionic Liquids as Reconditioning Agents for Paper Artifacts.

This research explores the potential of ionic liquids (ILs) in restoring paper artifacts, particularly an aged book sample. Three distinct ILs-1-ethyl-3-propylimidazolium bis(trifluoromethylsulfonyl)imide, 1-methyl-3-pentylimidazolium bis(trifluoromethylsulfonyl)imide, and 1-methyl-3-heptylimidazolium bis(trifluoromethylsulfonyl)imide -both in their pure form and isopropanol mixtures, were examined for their specific consumption in conjunction with paper, with 1-ethyl-3-propylimidazolium bis(trifluoromethylsulfonyl)imide displaying the highest absorption. Notably, the methyl-3-heptylimidazolium ionic liquid displayed pronounced deacidification capabilities, elevating the paper pH close to a neutral 7. The treated paper exhibited significant color enhancements, particularly with 1-heptyl-3-methylimidazolium and 1-pentyl-3-methylimidazolium ILs, as evidenced by CIE-Lab* parameters. An exploration of ILs as potential UV stabilizers for paper unveiled promising outcomes, with 1-heptyl-3-methylimidazolium IL demonstrating minimal yellowing post-UV irradiation. FTIR spectra elucidated structural alterations, underscoring the efficacy of ILs in removing small-molecular additives and macromolecules. The study also addressed the preservation of inked artifacts during cleaning, showcasing ILs' ability to solubilize iron gall ink, particularly the one with the 1-ethyl-3-propylimidazolium cation. While exercising caution for prolonged use on inked supports is still recommended, ILs are shown here to be valuable for cleaning ink-stained surfaces, establishing their effectiveness in paper restoration and cultural heritage preservation.

Clinical usefulness of image-enhanced endoscopy for the diagnosis of ulcerative colitis-associated neoplasia.

Patients with a long history of ulcerative colitis (UC) are at risk of developing a significant complication known as UC-associated neoplasia (UCAN). To reduce the risk of UCAN and the associated mortality, the current guidelines recommend initiating surveillance colonoscopy 8-10 years after confirmation of UC diagnosis. In recent years, advancements in endoscopic diagnostic technologies, including magnifying and image-enhancing techniques, have allowed for the production of high-contrast images that emphasize mucosal structures, vascular patterns, and color tones. Recently, image-enhanced endoscopy technologies have become available and offer the potential to improve the qualitative endoscopic assessment of UCAN. The use of high-definition chromoendoscopy enables the evaluation of subtle mucosal patterns in the colon. Magnifying narrow-band imaging facilitates the visualization of mucosal vascular structures. Texture and color enhancement imaging processes structure, color tone, and brightness aspects more appropriately, whereas linked color imaging optimizes the emphasis on mucosal and vascular redness. Both techniques are expected to excel in the depiction of subtle color variations and mucosal changes characteristic of UCAN. This article provides an overview of the current status and future challenges regarding the use of various image-enhanced endoscopytechniques in the diagnosis of UCAN.

Improving X-ray images of historically significant textiles

The availability of information as to the inner structures and condition of historically significant textiles and clothing items is essential for monitoring, preservation and restoration processes. Visual inspection is usually the initial step in identifying any damage, such as tearing or rotting, but it is not sufficient for examining of detail below the surface of the objects. Radiography Testing (RT) is a useful non-destructive approach, capable of revealing hidden damage to under-sewing layers, clothing design, and connections, providing crucial information for developing a conservation plan. However, due to the mainly low atomic number of the constituting elements of textile material and also the low thickness of such items, X-ray radiographs suffer from low imaging contrast, which is further compromised by noise due to the unavoidable detection of scattered X-rays, which introduces fogginess in the acquired radiographs. Using digital RT images as a starting point, two image processing approaches using histogram equalization and the more complex Automatic Color Enhancement (ACE) methods were applied to enhance the imaging contrast of the original radiographs. The results demonstrated the effectiveness of these methods in better identifying defects, hidden designs, motifs, and destructive regions within the inner layers of textiles. It was found that the ACE method produced better outcomes than the simpler histogram equalization approach. Results indicated that the ACE processed image could be favored over the simpler histogram equalization approach by its enhanced capability of targeted expansion of the scale for evaluation of deterioration. The conservators and radiographers were able to utilize the further and complementary capability towards improved object assessment, monitoring, and restoration procedures.

Do color enhancement algorithms improve the experience of color-deficient people? An empirical study based on smartphones.

Approximately 8% of the global population experiences color-vision deficiency. It is important to note that "color-vision deficiency" is distinct from "color blindness," as used in this article, which refers to the difficulty in distinguishing certain shades of color. This study explores color enhancement algorithms based on the neural mechanisms of color blindness and color deficiency. The algorithms are then applied to smartphones to improve the user experience (UX) of color-enhancing features in different top-selling smartphone brands with different operating systems (OS). A color-enhancing application program was developed for individuals with color-vision deficiency and compared to two other mature color-enhancing programs found in top-selling smartphones with different mainstream operating systems. The study included both objective and subjective evaluations. The research materials covered three aspects: daily life, information visualization, and videos. Additionally, this research study examines various levels of color enhancement through three dimensions of subjective evaluation: color contrast, color naturalness, and color preference. The results indicate that all color-enhancing features are beneficial for individuals with color-vision deficiencies due to their strong color contrast. The users' color preference is closely linked to color naturalness. The application program preserves the naturalness of colors better than the other two color-enhancing features. The subjective evaluations show similar trends across different operating systems, with differences arising from the use of different color-enhancing algorithms. Therefore, different algorithms may result in different sizes of the color gamut.

ACCE: An Adaptive Color Compensation and Enhancement Algorithm for Underwater Image

ACCE: An Adaptive Color Compensation and Enhancement Algorithm for Underwater Image

Improved visibility of colorectal tumor by texture and color enhancement imaging with indigo carmine.

Accurate diagnosis and early resection of colorectal polyps are important to prevent the occurrence of colorectal cancer. However, technical factors and morphological factors of polyps itself can lead to missed diagnoses. Image-enhanced endoscopy and chromoendoscopy (CE) have been developed to facilitate an accurate diagnosis. There have been no reports on visibility using a combination of texture and color enhancement imaging (TXI) and CE for colorectal tumors. To investigate the visibility of margins and surfaces with the combination of TXI and CE for colorectal lesions. This retrospective study included patients who underwent lower gastrointestinal endoscopy at the Toyoshima Endoscopy Clinic. We extracted polyps that were resected and diagnosed as adenomas or serrated polyps (hyperplastic polyps and sessile serrated lesions) from our endoscopic database. An expert endoscopist performed the lower gastrointestinal endoscopies and observed the lesion using white light imaging (WLI), TXI, CE, and TXI + CE modalities. Indigo carmine dye was used for CE. Three expert endoscopists rated the visibility of the margin and surface patterns in four ranks, from 1 to 4. The primary outcomes were the average visibility scores for the margin and surface patterns based on the WLI, TXI, CE, and TXI + CE observations. Visibility scores between the four modalities were compared by the Kruskal-Wallis and Dunn tests. A total of 48 patients with 81 polyps were assessed. The histological subtypes included 50 tubular adenomas, 16 hyperplastic polyps, and 15 sessile serrated lesions. The visibility scores for the margins based on WLI, TXI, CE, and TXI + CE were 2.44 ± 0.93, 2.90 ± 0.93, 3.37 ± 0.74, and 3.75 ± 0.49, respectively. The visibility scores for the surface based on WLI, TXI, CE, and TXI + CE were 2.25 ± 0.80, 2.84 ± 0.84, 3.12 ± 0.72, and 3.51 ± 0.60, respectively. The visibility scores for the detection and surface on TXI were significantly lower than that on CE but higher than that on WLI (P < 0.001). The visibility scores for the margin and surface on TXI + CE were significantly higher than those on CE (P < 0.001). In the sub-analysis of adenomas, the visibility for the margin and surface on TXI + CE was significantly better than that on WLI, TXI, and CE (P < 0.001). In the sub-analysis of serrated polyps, the visibility for the margin and surface on TXI + CE was also significantly better than that on WLI, TXI, and CE (P < 0.001). TXI + CE enhanced the visibility of the margin and surface compared to WLI, TXI, and CE for colorectal lesions.

Detecting, mapping and digitising canopy geometry, fruit number and peel colour in pear trees with different architecture

Increasing farm labour and input costs and the requirement for more orchard data are leading to rapid advances in technology to improve management systems in fruit production. The study aimed to (i) validate a sensorised platform to estimate fruit number, peel colour and blush coverage in pear orchards with different pear selections and tree architectures, (ii) establish relationships between fruit number, peel colour and canopy geometry features, and (iii) evaluate the platform for mapping and digitising orchard features. The study was carried out over two years in an experimental ‘ANP-0131′ orchard and in one year in two commercial pear orchards (‘ANP-0131′ and ‘PremP009’). Predictions of fruit number and blush coverage were compared in traditional three-dimensional (3D) and modern high-density two-dimensional (2D) training systems. Overall, prediction errors for fruit number were < 6.5 % in all the training systems, but improved performance was achieved in vertical 2D configurations (% standard errors = 2.2 %). Fruit number and blush coverage per unit of leaf area were higher in 2D compared to 3D training systems. Blush coverage predictions in ‘ANP-0131′ were reliable (R2 = 0.67, RMSE = 3.70 %). Accurate predictions of blush coverage classes were achieved by modifying sample variance. Fruit number and blush coverage were negatively affected by increasing canopy size. The platform proved useful for mapping and digitisation. Spatial heatmaps of orchard features provided a valuable visual aid to identify zones for priority interventions for peel colour enhancement.

LodgeNet: an automated framework for precise detection and classification of wheat lodging severity levels in precision farming

Wheat lodging is a serious problem affecting grain yield, plant health, and grain quality. Addressing the lodging issue in wheat is a desirable task in breeding programs. Precise detection of lodging levels during wheat screening can aid in selecting lines with resistance to lodging. Traditional approaches to phenotype lodging rely on manual data collection from field plots, which are slow and laborious, and can introduce errors and bias. This paper presents a framework called ‘LodgeNet,’ that facilitates wheat lodging detection. Using Unmanned Aerial Vehicles (UAVs) and Deep Learning (DL), LodgeNet improves traditional methods of detecting lodging with more precision and efficiency. Using a dataset of 2000 multi-spectral images of wheat plots, we have developed a novel image registration technique that aligns the different bands of multi-spectral images. This approach allows the creation of comprehensive RGB images, enhancing the detection and classification of wheat lodging. We have employed advanced image enhancement techniques to improve image quality, highlighting the important features of wheat lodging detection. We combined three color enhancement transformations into two presets for image refinement. The first preset, ‘Haze &amp;amp; Gamma Adjustment,’ minimize atmospheric haze and adjusts the gamma, while the second, ‘Stretching Contrast Limits,’ extends the contrast of the RGB image by calculating and applying the upper and lower limits of each band. LodgeNet, which relies on the state-of-the-art YOLOv8 deep learning algorithm, could detect and classify wheat lodging severity levels ranging from no lodging (Class 1) to severe lodging (Class 9). The results show the mean Average Precision (mAP) of 0.952% @0.5 and 0.641% @0.50-0.95 in classifying wheat lodging severity levels. LodgeNet promises an efficient and automated high-throughput solution for real-time crop monitoring of wheat lodging severity levels in the field.

Texture and color enhancement imaging improves the visibility of gastric neoplasms: clinical trial with image catalogue assessment using conventional and newly developed endoscopes

BackgroundTexture and color enhancement imaging (TXI) enhances the changes in endoscopic features caused by gastric neoplasms, such as redness/whiteness and elevation/depression. This study aimed to demonstrate the effectiveness of TXI in improving the visibility of gastric neoplasms compared with white light imaging (WLI) using conventional (CE) and newly developed endoscopes (NE).MethodsWe recruited patients who were histologically diagnosed with gastric neoplasms; endoscopy was performed, and gastric neoplasms photographed using three imaging modalities, including WLI, TXI mode 1 (TXI-1) and TXI mode 2 (TXI-2). Two different endoscopes (CE and NE) were used for the same patients. Six endoscopists provided the visibility scale scores ranging from 1 (poor) to 4 (excellent) for gastric neoplasms. The primary outcome was the visibility scale scores based on each modality and endoscope. The secondary outcome was the identification of factors including H. pylori infection, atrophy, location, size, morphology, histological diagnosis and intestinal metaplasia that affect the differences in visibility scale scores between TXI-1/TXI-2 and WLI.ResultsFifty-two gastric neoplasms were analyzed. The mean visibility scale scores with the NE were 2.79 ± 1.07, 3.23 ± 0.96 and 3.14 ± 0.92 for WLI, TXI-1 and TXI-2, respectively. The mean visibility scales with the CE were 2.53 ± 1.10, 3.04 ± 1.05 and 2.96 ± 1.92 for WLI, TXI-1 and TXI-2, respectively. For both endoscopes, significant differences were observed in visibility scale scores between WLI and TXI-1 (p < 0.001) and between WLI and TXI-2 (p < 0.001). The visibility scale scores of NE were superior to those of CE in all modalities. In the secondary outcome, there was no factor affected the differences of visibility scale scores between TXI-1/TXI-2 and WLI.ConclusionsThis study demonstrated that TXI-1 and TXI-2 enhanced the visibility scale scores of gastric neoplasms compared with that of WLI. Moreover, newly developed endoscope has the potential to improve visibility compared to conventional endoscope.Trial RegistrationThis study was registered with the University Hospital Medical Information Network (UMIN000042429, 16/11/2020).

Classification and endoscopic diagnosis of colorectal polyps

Background: Colorectal cancer is a common malignancy and a major health concern in Korea. The increased use of screening colonoscopies has led to improved survival of patients with colorectal cancer despite its high prevalence; this highlights the importance of early detection and removal of neoplastic polyps such as adenoma and sessile serrated lesions. Therefore, optical diagnosis of colorectal polyps is crucial in deciding whether the lesion requires removal and if endoscopic procedures can be used for its removal.Current Concepts: Several image-enhanced endoscopy (IEE) techniques and classifications can be used to improve the optical diagnosis of different polyps that match the histopathologic findings. Kudo’s pit pattern classification is based on features of pit patterns observed from different types of polyps via chromoendoscopy. The Narrow-Band Imaging (NBI) International Colorectal Endoscopic (NICE) classification is an international classification based on patterns observed from NBI findings. The Japan NBI Expert Team (JNET) classification identifies different patterns observed from magnified images with NBI. The Workgroup serrAted polypS and Polyposis (WASP) classification helps to differentiate hyperplastic polyps from sessile serrated lesions. Endoscopy manufacturers have also developed IEE techniques such as I-scan, flexible spectral imaging color enhancement, and blue laser imaging/linked color imaging to highlight, delineate, and differentiate various polyps.Discussion and Conclusion: Optical diagnosis of colorectal polyps using IEE such as NBI with different classifications such as NICE, JNET, and WASP is important for differentiating neoplastic polyps and removing them with an appropriate method.

Synthetic astaxanthin has better effects than natural astaxanthins on growth performance, body color and n-3 PUFA deposition in black tiger prawn (Penaeus monodon)

Astaxanthin is an efficient nutrition strategy to relieve oxidative stress and enhance crustacean body color. Because of technological and economic benefits, synthetic astaxanthin is favored by the aquatic feed industry. However, whether synthetic astaxanthin can achieve the effects of natural astaxanthin needs further investigation. Here, we evaluated the effects of synthetic astaxanthin and natural astaxanthin (dietary supplementation with Haematococcus pluvialis and Phaffia rhodozyma) on the growth performance, body color, fatty acid composition and antioxidant capacity of black tiger prawn (Penaeus monodon). Compared with the control group (no astaxanthin supplementation), only synthetic astaxanthin significantly increased the weight gain rate (WG) and specific growth rate (SGR), together with the elevation of feed efficiency ratio (FER). All three types of astaxanthin enhanced body color by increasing astaxanthin deposition. The highest value of (a*) in the carapace and muscle occurred in the synthetic astaxanthin group. Synthetic astaxanthin significantly increased the n-3 polyunsaturated fatty acid (n-3 PUFA) contents in muscle. As expected, different sources of astaxanthin inhibited glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase (GPT) activities in the hemolymph and decreased the contents of reduced glutathione (GSH) and malondialdehyde (MDA) in the hepatopancreas. Correspondingly, the structure of hepatopancreas was enhanced by astaxanthin. In addition, three types of astaxanthin almost indistinguishably enhanced the ability of shrimps to resist stress caused by transportation simulation. In conclusion, these results indicate that dietary synthetic astaxanthin has a better effect than natural astaxanthin on growth promotion, body color enhancement and n-3 PUFA deposition in muscle of black tiger prawn. Hence, synthetic astaxanthin is a suitable feed additive to promote the healthy and sustainable development of the shrimp industry.

Distinguishable Colorimetric Biosensor for Diagnosis of Prostate Cancer Bone Metastases.

Castration-resistant prostate cancer (PCa) causes severe bone metastasis (BM), which significantly increases mortality in men with PCa. Imaging tests and radiometric scanning require long analysis times, expensive equipment, specialized personnel, and a slow turnaround. New visualization technologies are expected to solve the above problems. Nonetheless, existing visualization techniques barely meet the urgency for precise diagnosis because the human eyes cannot recognize and capture even slight variations in visual information. By using dye differentiated superposition enhancement colorimetric biosensors, an effective method to diagnose prostate cancer bone metastases (PCa-BM) with excellent accuracy for naked-eye quantitative detection of alkaline phosphatase (ALP) is developed. The biomarker ALP specific hydrolytic product ascorbic acid can be detected by rhodamine derivatives (Rd) as gold nanobipyramids (Au NBPs) are deposited and grown. Color-recombining enhancement effects between Rd and Au NBPs significantly improved abundance. The 150UL-1 threshold between normal and abnormal can be identified by color. And with color enhancement effect and double signal response, the ALP index is visually measured to diagnose PCa-BM and provide handy treatment recommendations. Additionally, the proposed colorimetric sensing strategy can be used to diagnose other diseases.