Self-similarity-based super-resolution of photoacoustic angiography from hand-drawn doodles

Deep-learning-based super-resolution photoacoustic angiography (PAA) is a powerful tool that restores blood vessel images from under-sampled images to facilitate disease diagnosis. Nonetheless, due to the scarcity of training samples, PAA super-resolution models often exhibit inadequate generalization capabilities, particularly in the context of continuous monitoring tasks. To address this challenge, we propose a novel approach that employs a super-resolution PAA method trained with forged PAA images. We start by generating realistic PAA images of human lips from hand-drawn curves using a diffusion-based image generation model. Subsequently, we train a self-similarity-based super-resolution model with these forged PAA images. Experimental results show that our method outperforms the super-resolution model trained with authentic PAA images in both original-domain and cross-domain tests. Specially, our approach boosts the quality of super-resolution reconstruction using the images forged by the deep learning model, indicating that the collaboration between deep learning models can facilitate generalization, despite limited initial dataset. This approach shows promising potential for exploring zero-shot learning neural networks for vision tasks.Comment: 12 pages, 6 figures, journa

Virtual Restoration of Stained Chinese Paintings Using Patch-Based Color Constrained Poisson Editing with Selected Hyperspectral Feature Bands

Stains, as one of most common degradations of paper cultural relics, not only affect paintings’ appearance, but sometimes even cover the text, patterns, and colors contained in the relics. Virtual restorations based on common red–green–blue images (RGB) which remove the degradations and then fill the lacuna regions with the image’s known parts with the inpainting technology could produce a visually plausible result. However, due to the lack of information inside the degradations, they always yield inconsistent structures when stains cover several color materials. To effectively remove the stains and restore the covered original contents of Chinese paintings, a novel method based on Poisson editing is proposed by exploiting the information inside the degradations of selected three feature bands as the auxiliary information to guide the restoration since the selected feature bands captured fewer stains and could expose the covered information. To make the Poisson editing suitable for stain removal, the feature bands were also exploited to search for the optimal patch for the pixels in the stain region, and the searched patch was used to construct the color constraint on the original Poisson editing to ensure the restoration of the original color of paintings. Specifically, this method mainly consists of two steps: feature band selection from hyperspectral data by establishing rules and reconstruction of stain contaminated regions of RGB image with color constrained Poisson editing. Four Chinese paintings (‘Fishing’, ‘Crane and Banana’, ‘the Hui Nationality Painting’, and ‘Lotus Pond and Wild Goose’) with different color materials were used to test the performance of the proposed method. Visual results show that this method can effectively remove or dilute the stains while restoring a painting’s original colors. By comparing values of restored pixels with nonstained pixels (reference of their same color materials), images processed by the proposed method had the lowest average root mean square error (RMSE), normalized absolute error (NAE), and average differences (AD), which indicates that it is an effective method to restore the stains of Chinese paintings

Characterization and Evaluation of Antioxidant and Anti-Inflammatory Activities of Flavonoids from the Fruits of Lycium barbarum

The fruits of Lycium barbarum are rich in flavonoids, which may contribute to the health-promoting function of Lycium barbarum. However, the composition of flavonoids in the fruits of Lycium barbarum (LBFs) has received little attention. Thus, the goal of this work was to identify more kinds of flavonoids from fruits of Lycium barbarum by liquid chromatography–mass spectrometry. The potential antioxidant and anti-inflammatory activities of LBFs in vitro were also investigated. Thirteen flavonoid compounds were identified in LBFs, of which daphnetin, 6,7-dihydroxycoumarin, astragalin, taxifolin, eriodictyol, naringenin, and chrysoeriol were identified for the first time in the fruits of Lycium barbarum, which greatly enriched the variety of flavonoids in the fruits of Lycium barbarum. LBFs showed a similar superior antioxidant activity to vitamin C. Furthermore, LBFs exhibited an anti-inflammatory activity by suppressing the production of nitric oxide and pro-inflammatory cytokines, including tumor necrosis factor-alpha, interleukin-1β, and interleukin-6, in lipopolysaccharide-treated RAW264.7 macrophage cells. This study demonstrated the potential development of LBFs as functional foods

Opinion on the development and research status of intelligent ophthalmology in China

This paper provides a comprehensive analysis of the current state of intelligent ophthalmology in China, including technological advancements, academic exchange platforms, policy support, future challenges, and potential solutions. Technologically, remarkable progress have been made in various areas of intelligent ophthalmology in China, including diabetic retinopathy, fundus image analysis, and crucial aspects such as quality assessment of medical artificial intelligence products, clinical research methods, technological evaluation, and industrial standards. Researchers are constantly improving the safety and standardization of intelligent ophthalmology technology by formulating clinical application guidelines and standards. Academic exchange platforms have been established to provide extensive collaboration opportunities for professionals across diverse fields, and various academic journals serve as publication platforms for intelligent ophthalmology research. Regarding public policy, the Chinese government has not only established a supportive policy environment for the advancement of intelligent ophthalmology through various documents and regulations, but provided a legal basis and management framework. However, there are still challenges to overcome, such as technological innovation, data privacy and security, outdated regulations, and talent shortages. To tackle these issues, there is a requirement for increased technological research and development, the establishment of regulatory frameworks, talent cultivation, and greater awareness and acceptance of new technologies among patients. By comprehensively addressing these challenges, intelligent ophthalmology in China is expected to continue leading the industry's global development, bringing more innovation and convenience to the field of ophthalmic healthcare

Prediction of postoperative complications of pediatric cataract patients using data mining

Abstract Background The common treatment for pediatric cataracts is to replace the cloudy lens with an artificial one. However, patients may suffer complications (severe lens proliferation into the visual axis and abnormal high intraocular pressure; SLPVA and AHIP) within 1 year after surgery and factors causing these complications are unknown. Methods Apriori algorithm is employed to find association rules related to complications. We use random forest (RF) and Naïve Bayesian (NB) to predict the complications with datasets preprocessed by SMOTE (synthetic minority oversampling technique). Genetic feature selection is exploited to find real features related to complications. Results Average classification accuracies in three binary classification problems are over 75%. Second, the relationship between the classification performance and the number of random forest tree is studied. Results show except for gender and age at surgery (AS); other attributes are related to complications. Except for the secondary IOL placement, operation mode, AS and area of cataracts; other attributes are related to SLPVA. Except for the gender, operation mode, and laterality; other attributes are related to the AHIP. Next, the association rules related to the complications are mined out. Then additional 50 data were used to test the performance of RF and NB, both of then obtained the accuracies of over 65% for three classification problems. Finally, we developed a webserver to assist doctors. Conclusions The postoperative complications of pediatric cataracts patients can be predicted. Then the factors related to the complications are found. Finally, the association rules that is about the complications can provide reference to doctors

In-Situ Transformed Ni, S-Codoped CoO from Amorphous Co–Ni Sulfide as an Efficient Electrocatalyst for Hydrogen Evolution in Alkaline Media

International audienc

Fast sulfurization of nickel foam-supported nickel-cobalt carbonate hydroxide nanowire array at room temperature for hydrogen evolution electrocatalysis

International audienc

The Main Anthocyanin Monomer from <i>Lycium ruthenicum</i> Murray Fruit Mediates Obesity via Modulating the Gut Microbiota and Improving the Intestinal Barrier

Anthocyanins have been shown to exert certain antiobesity properties, but the specific relationship between anthocyanin-induced beneficial effects and the gut microbiota remains unclear. Petunidin-3-O-[rhamnopyranosyl-(trans-p-coumaroyl)]-5-O-(β-D-glucopyranoside) (P3G) is the main anthocyanin monomer from the fruit of Lycium ruthenicum Murray. Therefore, in this study, we investigated the antiobesity and remodeling effects of P3G on gut microbiota through a high-fat diet (HFD)-induced obesity mouse model and a fecal microbiota transplantation experiment. P3G was found to reduce body weight gain, fat accumulation, and liver steatosis in HFD-induced obese mice. Moreover, supplementation with P3G alleviated the HFD-induced imbalance in gut microbiota composition, and transferring the P3G-regulated gut microbiota to recipient mice provided comparable protection against obesity. This is the first time evidence is provided that P3G has an antiobesity effect by changing the intestinal microbiota. Our present data highlight a link between P3G intervention and enhancement in gut barrier integrity. This may be a promising option for obesity prevention