Budesonide and N-acetylcysteine inhibit activation of the NLRP3 inflammasome by regulating miR-381 to alleviate acute lung injury caused by the pyroptosis-mediated inflammatory response.

Background: The anti-inflammatory effects of budesonide (BUN) and N-acetylcysteine (NAC) attenuate acute lung injury (ALI). The aim of this study was to investigate the effects of combination therapy consisting of BUN and NAC on ALI and the underlying mechanisms. Methods: In vitro and in vivo models of ALI were generated by LPS induction. Western blotting was used to detect the expression levels of pyroptosis-related proteins and inflammation-related factors, and RT-qPCR was used to detect the expression of miR-381. Cell proliferation and apoptosis were detected by CCK-8 and flow cytometry, respectively. ELISA was used to detect the levels of inflammation-related factors. HE staining was used to detect lung injury. Results: The results showed that LPS effectively induced pyroptosis in cells and promoted the expression of pyroptosis-related proteins (Caspase1, Gasdermin D and NLRP3) and inflammatory cytokines (TNF-α, IL-6 and IL-1ß). The combination of BUN and NAC significantly alleviated LPS-induced pyroptosis and inflammation. In addition, the combination of BUN and NAC effectively promoted miR-381 expression. Transfection of miR-381 mimics effectively alleviated LPS-induced pyroptosis and inflammation, while transfection of miR-381 inhibitors had the opposite effect. miR-381 negatively regulates NLRP3 expression. Treatment with a miR-381 inhibitor or pc-NLRP3 reversed the effects of the combination of BUN and NAC. In a mouse model of ALI, the combination of BUN and NAC effectively improved lung injury, while treatment with a miR-381 inhibitor or pc-NLRP3 effectively reversed this effect. Conclusion: Overall, this study revealed that BUN + NAC inhibits the activation of NLRP3 by regulating miR-381, thereby alleviating ALI caused by pyroptosis-mediated inflammation.

Stress mitigation mechanism of rice leaf microbiota amid atmospheric deposition of heavy metals.

Leaf microbiota have been extensively applied in the biological control of plant diseases, but their crucial roles in mitigating atmospheric heavy metal (HM) deposition and promoting plant growth remain poorly understood. This study demonstrates that elevated atmospheric HM deposition on rice leaves significantly shapes distinct epiphytic and endophytic microbiota across all growth stages. HM stress consistently leads to the dominance of epiphytic Pantoea and endophytic Microbacterium in rice leaves, particularly during the booting and filling stages. Leaf-bound HMs stimulate the differentiation of specialized microbial communities in both endophytic and epiphytic compartments, thereby regulating leaf microbial interactions. Metagenomic binning retrieved high-quality genomes of keystone leaf microorganisms, indicating their potential for essential metabolic functions. Notably, Pantoea and Microbacterium show significant HM resistance, plant growth-promoting capabilities, and diverse element cycling functions. They possess genes associated with metal(loid) resistance, such as ars and czc, suggesting their ability to detoxify arsenic(As) and cadmium(Cd). They also support carbon, nitrogen, and sulfur cycling, with genes linked to carbon fixation, nitrogen fixation, and sulfur reduction. Additionally, these bacteria may enhance plant stress resistance and growth by producing antioxidants, phytohormones, and other beneficial compounds, potentially improving HM stress tolerance and nutrient availability in rice plants. This study shows that atmospheric HMs affect rice leaf microbial communities, prompting plants to seek microbial help to combat stress. The unique composition and metabolic potential of rice leaf microbiota offer a novel perspective for mitigating adverse stress induced by atmospheric HM deposition. This contributes to the utilization of leaf microbiota to alleviate the negative impact of heavy metal deposition on rice development and food security.

Integration of molecular docking and molecular dynamics simulations with subtractive proteomics approach to identify the novel drug targets and their inhibitors in Streptococcus gallolyticus.

Streptococcus gallolyticus (Sg) is a non-motile, gram-positive bacterium that causes infective endocarditis (inflammation of the heart lining). Because Sg has gained resistance to existing antibiotics and there is currently no drug available, developing effective anti-Sg drugs is critical. This study combined core proteomics with a subtractive proteomics technique to identify potential therapeutic targets for Sg. Several bioinformatics approaches were used to eliminate non-essential and human-specific homologous sequences from the bacterial proteome. Then, virulence, druggability, subcellular localization, and functional analyses were carried out to specify the participation of significant bacterial proteins in various cellular processes. The pathogen's genome contained three druggable proteins, glucosamine-1phosphate N-acetyltransferase (GlmU), RNA polymerase sigma factor (RpoD), and pantetheine-phosphate adenylyltransferase (PPAT) which could serve as effective targets for developing novel drugs. 3D structures of target protein were modeled through Swiss Model. A natural product library containing 10,000 molecules from the LOTUS database was docked against therapeutic target proteins. Following an evaluation of the docking results using the glide gscore, the top 10 compounds docked against each protein receptor were chosen. LTS001632, LTS0243441, and LTS0236112 were the compounds that exhibited the highest binding affinities against GlmU, PPAT, and RpoD, respectively, among the compounds that were chosen. To augment the docking data, molecular dynamics simulations and MM-GBSA binding free energy were also utilized. More in-vitro research is necessary to transform these possible inhibitors into therapeutic drugs, though computer validations were employed in this study. This combination of computational techniques paves the way for targeted antibiotic development, which addresses the critical need for new therapeutic strategies against S. gallolyticus infections.

Evaluation of perceptual interactions between key aldehydes in Kung Pao Chicken.

Aldehydes are the strongest and most abundant aromatic compounds in Kung Pao Chicken. However, the perceptual interactions between these aldehydes are not fully understood. Therefore, the flavor contribution of nine key aldehydes was estimated by determining thresholds. Except for benzaldehyde, the thresholds of all aldehydes measured in tasteless chicken matrices (TM) were significantly larger than their comparable values in water. Based on these results, the perceptual interactions of nine aldehydes were evaluated using S-curves and σ-τ plots. The interactions indicated that 31 of their 36 binary mixtures exhibited additive effects, three had masking effects, while two had synergistic effects. Recombination experiments showed that the addition of aldehydes lowered the odor threshold of aldehyde reconstitution (AR), thereby enhancing the aroma intensity of AR. These findings contribute to a better understanding of Kung Pao Chicken's aroma and can be used to improve its aroma quality.

Integrating network pharmacology, molecular docking and simulation approaches with machine learning reveals the multi-target pharmacological mechanism of Berberis integerrima against diabetic nephropathy.

Diabetic nephropathy (DN) is one of the most feared complications of diabetes and key cause of end-stage renal disease (ESRD). Berberis integerrima has been widely used to treat diabetic complications, but exact molecular mechanism is yet to be discovered. Data on active ingredients of B. integerrima and target genes of both diabetic nephropathy and B.integerrima were obtained from public databases. Common results between B. integerrima and DN targets were used to create protein-protein interaction (PPI) network using STRING database and exported to Cytoscape software for the selection of hub genes based on degree of connectivity. Future, PPI network between constituents and overlapping targets was created using Cytoscape to investigate the network pharmacological effects of B. integerrima on DN. KEGG pathway analysis of core genes exposed their involvement in excess glucose-activated signaling pathway. Then, expression of core genes was validated through machine learning classifiers. Finally, PyRx and AMBER18 software was used for molecular docking and simulation. We found that Armepavine, Berberine, Glaucine, Magnoflorine, Reticuline, Quercetin inhibits the growth of diabetic nephropathy by affecting ICAM1, PRKCB, IKBKB, KDR, ALOX5, VCAM1, SYK, TBXA2R, LCK, and F3 genes. Machine learning revealed SYK and PRKCB as potential genes that could use as diagnostic biomarkers against DN. Furthermore, docking and simulation analysis showed the binding affinity and stability of the active compound with target genes. Our study revealed that B. integerrima has preventive effect on DN by acting on glucose-activated signaling pathways. However, experimental studies are needed to reveal biosafety profiles of B. integerrima in DN.Communicated by Ramaswamy H. Sarma.

Proteomics-based vaccine targets annotation and design of multi-epitope vaccine against antibiotic-resistant Streptococcus gallolyticus.

Streptococcus gallolyticus is a non-motile, gram-positive bacterium that causes infective endocarditis. S. gallolyticus has developed resistance to existing antibiotics, and no vaccine is currently available. Therefore, it is essential to develop an effective S. gallolyticus vaccine. Core proteomics was used in this study together with subtractive proteomics and reverse vaccinology approach to find antigenic proteins that could be utilized for the design of the S. gallolyticus multi-epitope vaccine. The pipeline identified two antigenic proteins as potential vaccine targets: penicillin-binding protein and the ATP synthase subunit. T and B cell epitopes from the specific proteins were forecasted employing several immunoinformatics and bioinformatics resources. A vaccine (360 amino acids) was created using a combination of seven cytotoxic T cell lymphocyte (CTL), three helper T cell lymphocyte (HTL), and five linear B cell lymphocyte (LBL) epitopes. To increase immune responses, the vaccine was paired with a cholera enterotoxin subunit B (CTB) adjuvant. The developed vaccine was highly antigenic, non-allergenic, and stable for human use. The vaccine's binding affinity and molecular interactions with the human immunological receptor TLR4 were studied using molecular mechanics/generalized Born surface area (MMGBSA), molecular docking, and molecular dynamic (MD) simulation analyses. Escherichia coli (strain K12) plasmid vector pET-28a ( +) was used to examine the ability of the vaccine to be expressed. According to the outcomes of these computer experiments, the vaccine is quite promising in terms of developing a protective immunity against diseases. However, in vitro and animal research are required to validate our findings.

A better method to evaluate the reliability of echocardiography for assessment of pulmonary hypertension: comparison of tricuspid regurgitant spectrum quality grading and tricuspid valve regurgitation degree.

Background: Transthoracic echocardiography (TTE) is recommended as the most important noninvasive screening tool for the diagnosis of pulmonary hypertension (PH), sonographers usually measure the volume of regurgitant flow rather than evaluating the spectral quality, so physicians will determine whether the ultrasound measurements of pulmonary arterial systolic pressure (US-PASP) are reliable based on the volume of tricuspid regurgitation (TR). Therefore, for the first time, we grade the quality of TR spectrum (TRS) based on its integrity and clarity, aiming to assess clinical application value of different tricuspid regurgitant spectrum quality grades (TR-SQG), and investigate whether the accuracy of US-PASP is more trustworthy than TR. Methods: We retrospectively analyzed 108 patients with chronic thromboembolic PH (CTEPH) to compare the correlation and agreement between US-PASP and right heart catheterization measurements of PASP (RHC-PASP). TR area (TRA) and TRS were measured in each patient, and TR-SQG was performed. Results: The correlation coefficients between US-PASP and RHC-PASP were r=0.622 (P<0.001), r=0.754 (P<0.001), r=0.595 (P<0.001) in mild, moderate, severe TR, and r=0.301 (P=0.135), r=0.747 (P<0.001), r=0.739 (P<0.001), r=0.828 (P<0.001) in TR-SQG I-IV, respectively. Bland-Altman analysis revealed the mean biases of 5.05, 3.06, 7.62 mmHg in mild, moderate, severe TR, and -16.47, -8.07, 1.82, 6.09 mmHg in TR-SQG I-IV, respectively. In mild TR with the TR-SQG III and IV, the correlation coefficients between US-PASP and RHC-PASP were r=0.779 (P<0.001), intraclass correlation coefficient (ICC) =0.774, paired t-test P=0.160, respectively; and the consistency was significantly higher than that of mild TR without considering TR-SQG. In moderate TR with the TR-SQG III and IV, the r=0.749, ICC =0.746, paired t-test P=0.298 between US-PASP and RHC-PASP. Conclusions: The US-PASP with TR-SQG III or IV is trustworthy, and its accuracy and consistency are better than those predicted by the traditional severity of TR. The establishment of the ultrasound evaluation system of TR-SQG helps clinicians to judge whether the US-PASP is accurate, credible, and reliable.

Sinoflavonoids NJ and NK, anti-inflammatory prenylated flavonoids from the fruits of Podophyllum hexandrum Royle.

Two new prenylated flavonoids named sinoflavonoids NJ and NK (1-2), along with ten known compounds were isolated from the fruits of Podophyllum hexandrum Royle. The chemical structures were determined through NMR spectroscopic data and MS analysis. Sinoflavonoid NJ (1) with an unusual 5,11-dioxabenzo[b]fluoren-10-one skeleton was firstly reported from Berberidaceae. The isolated flavonoids were tested with LPS-induced RAW 264.7 mouse macrophages model for their anti-inflammatory activity. Sinoflavonoid NJ (1) showed the most potent inhibition on nitric oxide production with IC50 value as 0.06 µM.

[Vertical Migration Characteristics and Fate of Heavy Metals from Zinc Smelting Slag in Soil Profile].

To investigate the influence of heavy metals in smelting waste residue on the quality of soil and groundwater, a simulation column experiment was conducted to study the migration characteristics of heavy metals from the leaching solution of zinc volatilizing kiln residue in the site soil profile under continuous or intermittent leaching for 90 days. The concentrations of Cd, Cu, Pb, and Zn in leachate and their accumulation, chemical fractions, and particle size distribution characteristics in the soil profile were analyzed, and the retention mechanism of heavy metals was also discussed. The results showed that the concentration of heavy metals in the soil column leachate decreased rapidly after reaching the peak at the earlier leaching stage, and the Cd concentration far exceeded the threshold limit of 0.1 mg·L-1(class Ⅳ) of the Quality Standard for Groundwater(GB/T 14848-2017), indicating that there was Cd pollution risk of groundwater. The soil profile had a great adsorption capacity for heavy metals in the waste residue. Cd, Cu, Pb, and Zn were predominately accumulated in the shallow soil depth(0-10 cm), which was 237-429, 1.25-16.2, 1.38-2.31, and 1.79-3.17 times of the content of corresponding heavy metals in the soil profile before leaching, respectively. The migration distance of heavy metals in the slag under continuous leaching was longer than that under intermittent leaching, and Cd was significantly accumulated in the deep layer of the soil column. The contribution of soil coarse particles(0.5-2.0 mm) to the total cumulative amount of Cd, Cu, and Zn was larger, whereas Pb was more prone to accumulate in the particle size of<0.25 mm. The results of BCR sequential extraction fraction showed that the accumulated Cd, Cu, and Zn in shallow soil depth were mainly present in the weak acid extraction, accounting for 62.4%-76.7%, 72.0%-95.8%, and 67.6%-85.8% of total content, respectively. The X-ray diffraction(XRD) and Fourier transform infrared spectroscopy(FTIR) analysis showed that exogenous heavy metals in slag entering the soil would not form a stable mineral phase within 90 days, and the soil hydroxyl(-OH) and carbonyl(C=O) functional groups and iron aluminum silicate oxides were the main retention factors.

Endophytic Microbes from Medicinal Plants in Fenghuang Mountain as a Source of Antibiotics.

One of the largest concerns with world health today is still antibiotic resistance, which is making it imperative to find efficient alternatives as soon as possible. It has been demonstrated that microbes are reliable sources for the creation of therapeutic antibiotics. This research intends to investigate the endophytic microorganisms from several medicinal plants in Fenghuang Mountain (Jiangsu Province, China) and to discover new antibiotics from their secondary metabolites. A total of 269 endophytic strains were isolated from nine distinct medicinal plants. Taxonomic analysis revealed that there were 20 distinct species among these endophytes, with Streptomyces being the most common genus. Three of the target strains were chosen for scale-up fermentation after preliminary screening of antibacterial activities and the metabolomics investigation using LC-MS. These strains were Penicillium sp. NX-S-6, Streptomyces sp. YHLB-L-2 and Streptomyces sp. ZLBB-S-6. Twenty-three secondary metabolites (1-23), including a new sorbicillin analogue (1), were produced as a result of antibacterial activity-guided isolation. Through spectroscopic analysis using MS and NMR, the structures of yield compounds were clarified. According to antibacterial data, S. aureus or B. subtilis were inhibited to varying degrees by sorrentanone (3), emodic acid (8), GKK1032 B (10), linoleic acid (14), toyocamycin (17) and quinomycin A (21). The most effective antimicrobial agent against S. aureus, B. subtilis, E. coli and A. baumannii was quinomycin A (21). In addition, quinomycin A showed strong antifungal activity against Aspergillus fumigatus, Cryptococcus neoformans, and two clinical isolated strains Aspergillus fumigatus #176 and #339, with MIC as 16, 4, 16 and 16 µg/mL, respectively. This is the first time that bioprospecting of actinobacteria and their secondary metabolites from medicinal plants in Fenghuang Mountain was reported. The finding demonstrates the potential of endophytic microbes in medical plants to produce a variety of natural products. Endophytic microbes will be an important source for new antibiotics.

Functional near-infrared spectroscopy approach to the emotional regulation effect of drawing: Venting versus distraction.

BACKGROUND: Drawing can regulate emotions through venting or distraction. Distraction is more helpful for short-term emotion recovery; however, the sustainability of this difference is yet to be clarified. This study used functional near-infrared spectroscopy (fNIRS) to explore potential differences between venting and distraction. METHODS: A total of 44 college students participated in the experiment. After inducing fear by video, they were divided into two groups: The venting group drew their emotional experience, and the distraction group drew a house. Subsequently, the participants were instructed to relax by a brief video. RESULTS: Although the distraction group had a higher valence than the venting group at the end of the drawing activity, there was no difference between the two groups after a relaxation period. Additionally, the activation pattern of the prefrontal cortex differed between the two groups. Compared to the distraction group, the venting group had fewer channels with elevated prefrontal activity during drawing, suggesting less cognitive control, and had more channels with reduced prefrontal activity during relaxation, suggesting a higher level of relaxation. Drawing coding and fNIRS data were both associated with variations in valence. CONCLUSION: The less the cognitive control over emotion and the more free the expression of emotion during drawing, the higher the increase in valence; inversely, the more the cognitive control over emotion and the less free the expression of emotion, the lower the increase in valence.

Visual-quality-driven unsupervised image dehazing.

Most of the existing learning-based dehazing methods require a diverse and large collection of paired hazy/clean images, which is intractable to obtain. Therefore, existing dehazing methods resort to training on synthetic images. This may result in a possible domain shift when treating real scenes. In this paper, we propose a novel unsupervised dehazing (lightweight) network without any reference images to directly predict clear images from the original hazy images, which consists of an interactive fusion module (IFM) and an iterative optimization module (IOM). Specifically, IFM interactively fuses multi-level features to make up for the missing information among deep and shallow features while IOM iteratively optimizes dehazed results to obtain pleasing visual effects. Particularly, based on the observation that hazy images usually suffer from quality degradation, four non-reference visual-quality-driven loss functions are designed to enable the network trained in an unsupervised way, including dark channel loss, contrast loss, saturation loss, and edge sharpness loss. Extensive experiments on two synthetic datasets and one real-world dataset demonstrate that our method performs favorably against the state-of-the-art unsupervised dehazing methods and even matches some supervised methods in terms of metrics such as PSNR, SSIM, and UQI.

Benzeneboronic-alginate/quaternized chitosan-catechol powder with rapid self-gelation, wet adhesion, biodegradation and antibacterial activity for non-compressible hemorrhage control.

Although hemostatic powders have excellent adaptability for irregular and inaccessible wounds, their hemostasis for continuous bleeding or bleeding wounds of non-compressible organs remains a critical challenge. Herein, a series of benzeneboronic acid-modified sodium alginate/catechol-modified quaternized chitosan (SA-BA/QCS-C, SBQCC) powders is developed by borate ester crosslinking for non-compressible hemorrhage control. SBQCC powders possess remarkable tissue adhesion, rapid self-gelation, good cytocompatibility and antibacterial activity against S. aureus and E. coil. The blood coagulation assays show that SBQCC powders display excellent blood clotting ability due to the synergistic effect of SA-BA and QCS-C. The SBQCC2 powder with the SA-BA to QCS-C mass ratio of 5 to 3 has the greatest effect on the blood-clotting rate. Upon depositing SBQCC2 powder to bleeding wounds of rabbit liver, the powder can absorb a large amount of blood and form a stable hydrogel physical barrier at the bleeding wounds in situ to achieve non-pressing rapid hemostasis. The SBQCC2 powder also has good biocompatibility and can be degraded in vivo. Altogether, the SBQCC powders can be a promising candidate for rapid hemostasis, and these findings may provide a new perspective for improving the hemostatic efficiency of the hemostatic powder in biomedical fields.

Gypenosides Synergistically Reduce the Extracellular Matrix of Hepatic Stellate Cells and Ameliorate Hepatic Fibrosis in Mice.

Liver fibrosis resulting from chronic liver damage is becoming one of the major threats to health worldwide. Active saponin constituents isolated from Gynostemma pentaphyllum were found to possess a protective effect in liver diseases. Here, we obtained a naturally abundant gypenoside, XLVI, and evaluated its liver protection activity in both animal and cellular models. The results showed that it ameliorated acute and chronic liver injuries and lightened the process of fibrogenesis in vivo. XLVI can inhibit TGF-ß-induced activation of hepatic stellate cells and ECM deposition in vitro. The underlying mechanism study verified that it upregulated the protein expression of protein phosphatase 2C alpha and strengthened the vitality of the phosphatase together with a PP2Cα agonist gypenoside NPLC0393. These results shed new light on the molecular mechanisms and the potential therapeutic function of the traditional herb Gynostemma pentaphyllum in the treatment of liver fibrosis.

Rice Plant Counting, Locating, and Sizing Method Based on High-Throughput UAV RGB Images.

Rice plant counting is crucial for many applications in rice production, such as yield estimation, growth diagnosis, disaster loss assessment, etc. Currently, rice counting still heavily relies on tedious and time-consuming manual operation. To alleviate the workload of rice counting, we employed an UAV (unmanned aerial vehicle) to collect the RGB images of the paddy field. Then, we proposed a new rice plant counting, locating, and sizing method (RiceNet), which consists of one feature extractor frontend and 3 feature decoder modules, namely, density map estimator, plant location detector, and plant size estimator. In RiceNet, rice plant attention mechanism and positive-negative loss are designed to improve the ability to distinguish plants from background and the quality of the estimated density maps. To verify the validity of our method, we propose a new UAV-based rice counting dataset, which contains 355 images and 257,793 manual labeled points. Experiment results show that the mean absolute error and root mean square error of the proposed RiceNet are 8.6 and 11.2, respectively. Moreover, we validated the performance of our method with two other popular crop datasets. On these three datasets, our method significantly outperforms state-of-the-art methods. Results suggest that RiceNet can accurately and efficiently estimate the number of rice plants and replace the traditional manual method.

Spin-Manipulated Photonic Skyrmion-Pair for Pico-Metric Displacement Sensing.

Photonic spin skyrmions with deep-subwavelength features have aroused considerable interest in recent years. However, the manipulation of spin structure in the skyrmions in a desired manner is still a challenge, while this is crucial for developing the skyrmion-based applications. Here, an approach of optical spin manipulation by utilizing the spin-momentum equation is proposed to investigate the spin texture in a photonic skyrmion-pair. With the benefit of the proposed approach, a unique spin texture with spin angular momentum varying linearly along the line connecting the two skyrmion centers is theoretically designed and experimentally verified. The optimized spin texture is then applied in a displacement-sensing system, which is capable of attaining pico-metric sensitivity. Compared with the conventional polarization and phase schemes, the spin-based manipulation mechanism provides a new pathway for optical modulation, which is of great value in nanophotonics from both fundamental and application.

Prevalence and clinical characteristics of T2DM patients with OTUD3 gene rs78466831 SNP at a single academic center in China.

Background: A novel, rare OTUD3 c.863G>A (rs78466831) in humans has been reported associated with diabetes, but the prevalence and clinical characteristics of T2DM patients with rs78466831 have not been reported before. Objective: To investigate the prevalence and clinical characteristics of T2DM patients with rs78466831 and provide a basis for clinical diagnosis and treatment. Methods: OTUD3 gene rs78466831 SNP was detected by Sanger sequencing in all the collected specimens of laboratory-confirmed T2DM patients and healthy people. Clinical characteristics indexes inconsisting of fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG) and a body mass index (BMI), T2DM-associated chronic complications (myocardial infarction, cerebrovascular disease, retinopathy, arterial plaque, peripheral neuropathy and nephropathy) were obtained from the clinical laboratory information systems and electronic medical record system. Clinical characteristic indicators were compared between the wild-type and variant (rs78466831) patients with T2DM. Results: The prevalence of rs78466831 in the T2DM patients group was significantly higher than the healthy control in our academic center. The general characteristic indicators were not significantly different between the wild-type and rs78466831 patients with T2DM, except the family history of diabetes. Clinical laboratory indicators including HbA1c, FBG, OGTT, TC, HDL-C, LDL-C and CP had no significant difference between the two groups. The therapeutic drug and target achievement rates were not significantly different between the two groups. The incidence of diabetic retinopathy in the variant group was significantly higher than the wild-type group. Conclusions: The OTUD3 gene rs78466831 was associated with T2DM and may be a biological risk factor of diabetes retinopathy.

Measuring the magnetic topological spin structure of light using an anapole probe.

Topological spin structures of light, including the Skyrmion, Meron, and bi-Meron, are intriguing optical phenomena that arise from spin-orbit coupling. They have promising potential applications in nano-metrology, data storage, super-resolved imaging and chiral detection. Aside from the electric part of optical spin, of equal importance is the magnetic part, particularly the H-type electromagnetic modes for which the spin topological properties of the field are dominated by the magnetic field. However, their observation and measurement remains absent and faces difficult challenges. Here, we design a unique type of anapole probe to measure specifically the photonic spin structures dominated by magnetic fields. The probe is composed of an Ag-core and Si-shell nanosphere, which manifests as a pure magnetic dipole with no electric response. The effectiveness of the method was validated by characterizing the magnetic field distributions of various focused vector beams. It was subsequently employed to measure the magnetic topological spin structures, including individual Skyrmions and Meron/Skyrmion lattices for the first time. The proposed method may be a powerful tool to characterize the magnetic properties of optical spin and valuable in advancing spin photonics.

Non-linear perceptual multi-scale network for single image super-resolution.

Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution (SISR) and achieved remarkable progress. However, most of the existing CNN-based SISR networks with a single-stream structure fail to make full use of the multi-scale features of low-resolution (LR) image. While those multi-scale SR models often integrate the information with different receptive fields by means of linear fusion, which leads to the redundant feature extraction and hinders the reconstruction performance of the network. To address both issues, in this paper, we propose a non-linear perceptual multi-scale network (NLPMSNet) to fuse the multi-scale image information in a non-linear manner. Specifically, a novel non-linear perceptual multi-scale module (NLPMSM) is developed to learn more discriminative multi-scale feature correlation by using high-order channel attention mechanism, so as to adaptively extract image features at different scales. Besides, we present a multi-cascade residual nested group (MC-RNG) structure, which uses a global multi-cascade mechanism to organize multiple local residual nested groups (LRNG) to capture sufficient non-local hierarchical context information for reconstructing high-frequency details. LRNG uses a local residual nesting mechanism to stack NLPMSMs, which aims to form a more effective residual learning mechanism and obtain more representative local features. Experimental results show that, compared with the state-of-the-art SISR methods, the proposed NLPMSNet performs well in both quantitative metrics and visual quality with a small number of parameters.

An antibacterial biomimetic adhesive with strong adhesion in both dry and underwater situations.

Adhesives have attracted extensive attention in biomedical applications in recent years. However, the development of adhesives with strong adhesion in both dry and underwater conditions and antibacterial properties is still a challenge. Herein, a biomimetic adhesive (DP@TA/Gel) was developed based on the adhesion mechanism of mussel in water, from adhesion and solidification to avoiding excessive oxidization processes. DP@TA/Gel exhibited rapid strong nonspecific adhesiveness to diverse materials including wood (485 kPa) metal (507 kPa), plastic (74 kPa), and even fresh biological tissue (39 kPa) in dry conditions. Specially, owing to its biomimetic design, DP@TA/Gel could imitate the mussel adhesion mechanism underwater, endowing it with robust (38 kPa), highly repeatable (at least 15 times) and long-term (at least 120 h) stable adhesion even in underwater conditions. Remarkably, DP@TA/Gel also exhibited high adhesiveness in various water environments, including seawater, and a wide range of pH (3-11) and NaCl concentration (0.9-10%) solutions without any stimulus. In addition, DP@TA/Gel showed excellent biocompatibility and antibacterial properties. Thus, the DP@TA/Gel adhesive has appealing potential biomedical applications such as sutureless wound closure and as a tissue adhesive.