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Blackleg disease, a major threat to Brassica crops worldwide, is primarily caused by the pathogen Leptosphaeria biglobosa. Investigating the genetic variation of L. biglobosa is crucial for managing and preventing the disease in Brassica napus. To date, there is scarce genomic variation information available for populations of L. biglobosa in China. In this study, 73 L. biglobosa strains of canola stalks were collected from 12 provinces in China and subjected to re-sequencing. The 73 assemblies averaged 1340 contigs, 72,123 bp N50, and 30.17 Mb in size. In total, 9409 core orthogroups and 867 accessory orthogroups were identified. A total of 727,724 mutation loci were identified, including 695,230 SNPs and 32,494 indels. Principal component analysis (PCA) and population structure analysis showed that these strains could be divided into seven subgroups. The strains in most provinces were clustered into a single subgroup, suggesting a strong influence of the geographic environment on strain variation. The average nucleotide diversity (θπ) of all strains was 1.03 × 10-3, indicating important genetic diversity among strains from different regions of China. This study provides valuable resources for future comparative genomics, gives new insights into the population evolution of L. biglobosa, and supports the development of strategies for managing blackleg disease in canola.

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BACKGROUND: Osthole is a natural active ingredient extracted from the traditional Chinese medicine Cnidium monnieri. It has been demonstrated to have anti-inflammatory, anti-fibrotic, and anti-hyperglycemic properties. However, its effect on diabetic kidney disease (DKD) remains uncertain. This study aims to assess the preventive and therapeutic effects of osthole on DKD and investigate its underlying mechanisms. METHODS: A streptozotocin/high-fat and high-sucrose diet induced Type 2 diabetic rat model was established. Metformin served as the positive drug control. Diabetic rats were treated with metformin or three different doses of osthole for 8 weeks. Throughout the treatment period, the progression of DKD was assessed by monitoring increases in urinary protein, serum creatinine, urea nitrogen, and uric acid, along with scrutinizing kidney pathology. Enzyme-linked immunosorbent assay (ELISA) was employed to detect inflammatory factors and oxidative stress levels. At the same time, immunohistochemical staining was utilized to evaluate changes in alpha-smooth muscle actin, fibronectin, E-cadherin, and apoptosis. The alterations in TGF-ß1/Smads signaling pathway were ascertained through western blot and immunofluorescence. Furthermore, we constructed a high glucose-stimulated HBZY-1 cells model to uncover its molecular protective mechanism. RESULTS: Osthole significantly reduced fasting blood glucose, insulin resistance, serum creatinine, uric acid, blood urea nitrogen, urinary protein excretion, and glomerular mesangial matrix deposition in diabetic rats. Additionally, significant improvements were observed in inflammation, oxidative stress, apoptosis, and fibrosis levels. The increase of ROS, apoptosis and hypertrophy in HBZY-1 cells induced by high glucose was reduced by osthole. Immunofluorescence and western blot results demonstrated that osthole down-regulated the TGF-ß1/Smads signaling pathway and related protein expression. CONCLUSION: Our findings indicate that osthole exhibits potential preventive and therapeutic effects on DKD. It deserves further investigation as a promising drug for preventing and treating DKD.

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Intelligent detection is vital for achieving the intelligent picking operation of daylily, but complex field environments pose challenges due to branch occlusion, overlapping plants, and uneven lighting. To address these challenges, this study selected an intelligent detection model based on YOLOv5s for daylily, the depth and width parameters of the YOLOv5s network were optimized, with Ghost, Transformer, and MobileNetv3 lightweight networks used to optimize the CSPDarknet backbone network of YOLOv5s, continuously improving the model's performance. The experimental results show that the original YOLOv5s model increased mean average precision (mAP) by 49%, 44%, and 24.9% compared to YOLOv4, SSD, and Faster R-CNN models, optimizing the depth and width parameters of the network increased the mAP of the original YOLOv5s model by 7.7%, and the YOLOv5s model with Transformer as the backbone network increased the mAP by 0.2% and the inference speed by 69% compared to the model after network parameter optimization. The optimized YOLOv5s model provided precision, recall rate, mAP, and inference speed of 81.4%, 74.4%, 78.1%, and 93 frames per second (FPS), which can achieve accurate and fast detection of daylily in complex field environments. The research results can provide data and experimental references for developing intelligent picking equipment for daylily.

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To explore the application of a traditional machine learning model in the intelligent management of pigs, in this paper, the influence of PCA pre-treatment on pig face identification with RF is studied. By this testing method, the parameters of two testing schemes, one adopting RF alone and the other adopting RF + PCA, were determined to be 65 and 70, respectively. With individual identification tests carried out on 10 pigs, accuracy, recall, and f1-score were increased by 2.66, 2.76, and 2.81 percentage points, respectively. Except for the slight increase in training time, the test time was reduced to 75% of the old scheme, and the efficiency of the optimized scheme was greatly improved. It indicates that PCA pre-treatment positively improved the efficiency of individual pig identification with RF. Furthermore, it provides experimental support for the mobile terminals and the embedded application of RF classifiers.

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BACKGROUND: Ursolic acid (UA) is a triterpenoid compound found in natural plants. It has been reported to have anti-inflammatory, antioxidant, and immunomodulatory properties. However, its role in atopic dermatitis (AD) is unknown. This study aimed to evaluate the therapeutic effect of UA in AD mice and explore the underlying mechanisms. METHODS: Balb/c mice were treated with 2, 4-dinitrochlorobenzene (DNCB) to induce AD-like lesions. During modeling and medication administration, dermatitis scores and ear thickness were measured. Subsequently, histopathological changes, levels of T helper cytokines, and oxidative stress markers levels were evaluated. Immunohistochemistry staining was used to assess changes in the expression of the nuclear factor of kappa B (NF-κB) and NF erythroid 2-related factor 2 (Nrf2). Furthermore, CCK8 assay, reactive oxygen species (ROS) assay, real-time PCR, and western blotting were employed to evaluate the effects of UA on ROS levels, inflammatory mediator production, and the NF-κB and Nrf2 pathways in TNF-α/IFN-γ-stimulated HaCaT cells. RESULTS: The results showed that UA significantly reduced dermatitis score and ear thickness, effectively inhibited skin proliferation and mast cell infiltration in AD mice, and decreased the expression level of T helper cytokines. Meanwhile, UA improved oxidative stress in AD mice by regulating lipid peroxidation and increasing the activity of antioxidant enzymes. In addition, UA inhibited ROS accumulation and chemokine secretion in TNF-α/IFN-γ-stimulated HaCaT cells. It might exert anti-dermatitis effects by inhibiting the TLR4/NF-κB pathway and activating the Nrf2/HO-1 pathway. CONCLUSION: Taken together, our results suggest that UA may have potential therapeutic effects on AD and could be further studied as a promising drug for AD treatment.

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The cross talk between immune and non-immune cells in the tumor microenvironment leads to immunosuppression, which promotes tumor growth and survival. Immunotherapy is an advanced treatment that boosts humoral and cellular immunity rather than using chemotherapy or radiation-based strategy associated with non-specific targets and toxic effects on normal cells. Immune checkpoint inhibitors and T cell-based immunotherapy have already exhibited significant effects against solid tumors and leukemia. Tumor cells that escape immune surveillance create a major obstacle to acquiring an effective immune response in cancer patients. Tremendous progress had been made in recent years on a wide range of innate and adaptive immune checkpoints which play a significant role to prevent tumorigenesis, and might therefore be potential targets to suppress tumor cells growth. This review aimed to summarize the underlying molecular mechanisms of existing immunotherapy approaches including T cell and NK-derived immune checkpoint therapy, as well as other intrinsic and phagocytosis checkpoints. Together, these insights will pave the way for new innate and adaptive immunomodulatory targets for the development of highly effective new therapy in the future.

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The worldwide pandemic of COVID-19 has become a global public health crisis. Various clinical diagnosis methods have been developed to distinguish COVID-19-infected patients from healthy people. The nucleic acid test is the golden standard for virus detection as it is suitable for early diagnosis. However, due to the low amount of viral nucleic acid in the respiratory tract, the sensitivity of nucleic acid detection is unsatisfactory. As a result, serological screening began to be widely used with the merits of simple procedures, lower cost, and shorter detection time. Serological tests currently include the enzyme-linked immunosorbent assay (ELISA), lateral flow immunoassay (LFIA), and chemiluminescence immunoassay (CLIA). This review describes various serological methods, discusses the performance and diagnostic effects of different methods, and points out the problems and the direction of optimization, to improve the efficiency of clinical diagnosis. These increasingly sophisticated and diverse serological diagnostic technologies will help human beings to control the spread of COVID-19.

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The spread of Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), resulting in a global pandemic with around four million deaths. Although there are a variety of nucleic acid-based tests for detecting SARS-CoV-2, these methods have a relatively high cost and require expensive supporting equipment. To overcome these limitations and improve the efficiency of SARS-CoV-2 diagnosis, we developed a microfluidic platform that collected serum by a pulling-force spinning top and paper-based microfluidic enzyme-linked immunosorbent assay (ELISA) for quantitative IgA/IgM/IgG measurements in an instrument-free way. We further validated the paper-based microfluidic ELISA analysis of SARS-CoV-2 receptor-binding domain (RBD)-specific IgA/IgM/IgG antibodies from human blood samples as a good measurement with higher sensitivity compared with traditional IgM/IgG detection (99.7% vs 95.6%) for early illness onset patients. In conclusion, we provide an alternative solution for the diagnosis of SARS-CoV-2 in a portable manner by this smart integration of pulling-force spinning top and paper-based microfluidic immunoassay.

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This study investigates the feasibility of collaborative use of recycled carbon fiber reinforced polymer (RCFRP) fibers and recycled aggregate (RA) in concrete, which is called RCFRP fiber reinforced RA concrete (RFRAC). The mechanical properties of the composite were studied through experimental investigation, considering different RCFRP fiber contents (0%, 0.5%, 1.0%, and 1.5% by volume) and different RA replacement rates (0%, 10%, 20%, and 30% by volume). Specifically, ten different mixes were designed to explore the flowability and compressive and flexural strengths of the proposed composite. Experimental results indicated that the addition of RCFRP fibers and RA had a relatively small influence on the compressive strength of concrete (less than 5%). Moreover, the addition of RA slightly decreased the flexural strength of concrete, while the addition of RCFRP fibers could significantly improve the flexural performance. For example, the flexural strength of RA concrete with 1.5% RCFRP fiber addition increased by 32.7%. Considering the good flexural properties of the composite and its potential in reducing waste CFRP and construction solid waste, the proposed RFRAC is promising for use in civil concrete structures with high flexural performance requirements.