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Glomerella leaf spot (GLS) caused by Glomerella cingulata is a newly emerging disease that results in severe defoliation and fruit spots in apples. In China, the compound of pyraclostrobin and tebuconazole was registered to control GLS in 2018 and has achieved excellent control efficiency. In this study, we showed that the high-level resistant isolates of G. cingulata to pyraclostrobin, caused by the point mutation at codon 143 (GGT→GCT, G143A) in the cytochrome b gene, has appeared in apple orchards in Shandong Province in 2020, and the resistance frequency was 4.8%. Based on the genotype of the resistant isolates, we developed a loop-mediated isothermal amplification (LAMP) assay for detection of the pyraclostrobin resistance. The LAMP assay was demonstrated to have good specificity, sensitivity, and repeatability, and it exhibited high accuracy in detecting pyraclostrobin resistance in the field. This study reported the resistance status of GLS to pyraclostrobin in Shandong Province and developed a molecular tool for the detection of pyraclostrobin resistance, which is of practical significance for the scientific control of GLS.

Purpose. We have demonstrated that peroxiredoxin 2 (Prx2) released from lytic erythrocytes and damaged neurons into the subarachnoid space could activate microglia and then result in neuronal apoptosis. In this study, we tested the possibility of using Prx2 as an objective indicator for severity of the subarachnoid hemorrhage (SAH) and the clinical status of the patient. Materials and Methods. SAH patients were prospectively enrolled and followed up for 3 months. Cerebrospinal fluid (CSF) and blood samples were collected 0-3 and 5-7 days after SAH onset. The levels of Prx2 in the CSF and the blood were measured by an enzyme-linked immunosorbent assay (ELISA). We used Spearman’s rank coefficient to assess the correlation between Prx2 and the clinical scores. Receiver operating characteristic (ROC) curves were used for Prx2 levels to predict the outcome of SAH by calculating the area under the curve (AUC). Unpaired Student’s t -test was used to analyze the differences in continuous variables across cohorts. Results. Prx2 levels in the CSF increased after onset while those in the blood decreased. Existing data showed that Prx2 levels within 3 days in the CSF after SAH were positively correlated with the Hunt-Hess score ( R = 0.761 , P < 0.001 ). Patients with CVS had higher levels of Prx2 in their CSF within 5-7 days after onset. Prx2 levels in the CSF within 5-7 days can be used as a predictor of prognosis. The ratio of Prx2 in the CSF and the blood within 3 days of onset was positively correlated with the Hunt-Hess score and negatively correlated with Glasgow Outcome Scale (GOS; R = ‐ 0.605 , P < 0.05 ). Conclusion. We found that the levels of Prx2 in the CSF and the ratio of Prx2 in the CSF and the blood within 3 days of onset can be used as a biomarker to detect the severity of the disease and the clinical status of the patient.

Severe uterine injury is a major cause of endometrial scar formation and female infertility. Currently, the methods for accelerating injured uterine healing are still lacking. Genetic engineering modification of mesenchymal stem cells (MSCs) has been shown great promise in preclinical studies on regeneration. Here, we constructed a type of UC-MSCs with overexpressed bFGF (UC-MSCbFGF) and investigated the effects of the UC-MSCbFGF/scaffold on functional regeneration of the full-thickness defect uterus of the rat model. At day 7, 14, 30 after treatments, the rats were euthanized and the injured uterus were observed. The structural and functional change of uterine were assessed by hematoxylin and eosin (HE) staining, immunohistochemical staining and fertility experiment. The UC-MSCbFGF/scaffold group exhibited anti-inflammatory effect, and the number of CD45+ cell in the UC-MSCbFGF/scaffold group was significantly less than that in UC-MSCs/scaffold group and scaffold group, but higher than sham-operated group at day 7 post-mending. At day 14, the UC-MSCbFGF/scaffold group exhibited dramatically pro-angiogenesis efficacy compared with UC-MSCs/scaffold group and scaffold group. At day 30, the endometrial thickness, structure of myometrium and blood vessels in the UC-MSCbFGF/scaffold were better than those of the UC-MSCs/scaffold group and scaffold group, even close to sham-operated group. Implantation rate at injury region post-operation 30 days in the UC-MSCbFGF/scaffold group (8/16) was significantly higher than that in UC-MSCs/scaffold group (1/16) and scaffold group (0/16). Taken together, the UC-MSCbFGF/scaffold system suppressed local inflammation, promoted angiogenesis and accelerated regeneration of the defected uterine wall, and thereby greatly shortened the healing time of the injured uterus.

Background. Spinal cord injury (SCI) is known to cause a more robust systemic inflammatory response than general trauma without CNS injury, inducing severe secondary organ damage, especially the lung and liver. Related studies are principally focused on the mechanisms underlying repair and regeneration in the injured spinal cord tissue. However, the specific mechanism of secondary injury after acute SCI is widely overlooked, compared with general trauma. Methods. Two datasets of GSE151371 and GSE45376 related to the blood samples and spinal cord after acute SCI were selected to identify the differentially expressed genes (DEGs). In GSE151371, functional enrichment analysis on specific DEGs of blood samples was performed. And the top 15 specific hub genes were identified from intersectional genes between the specific upregulated DEGs of blood samples in GSE151371 and the upregulated DEGs of the spinal cord in GSE45376. The specific functional enrichment analysis and the drug candidates of the hub genes and the miRNAs-targeted hub genes were also analyzed and predicted. Results. DEGs were identified, and a total of 64 specific genes were the intersection of upregulated genes of the spinal cord in GSE45376 and upregulated genes of human blood samples in GSE151371. The top 15 hub genes including HP, LCN2, DLGAP5, CEP55, HMMR, CDKN3, PRTN3, SKA3, MPO, LTF, CDC25C, MMP9, NEIL3, NUSAP1, and CD163 were calculated from the 64 specific genes. Functional enrichment analysis of the top 15 hub genes revealed inflammation-related pathways. The predicted miRNAs-targeted hub genes and drug candidates of hub genes were also performed to put forward reasonable treatment strategies. Conclusion. The specific hub genes of acute SCI as compared with trauma without CNS injury were identified. The functional enrichment analysis of hub genes showed a specific immune response. Several predicted drugs of hub genes were also obtained. The hub genes and the predicted miRNAs may be potential biomarkers and therapeutic targets and require further validation.

In the current work, a CuS nanoflower-modified ZnO nanorod heterojunction was synthesized by a two-step hydrothermal method.

We developed a high sensitivity (13.4 mK Hz−1/2) silicon carbide divacancy-based thermometer using the thermal dynamical decoupling method and used it to monitor the laboratory temperature variations for 24 hours.

A natural adsorbent that effectively removes the ciprofloxacin from water by altering biochar made from straw using an eco-friendly procedure.

Photocatalytic C–N cross-couplings of (hetero)aryl bromides and aliphatic amines were achieved with an easy to prepare heterogeneous nickel-coordinated carbon nitride, which tolerates a range of functional groups with good yields.

An efficient copper-catalyzed formal [4 + 1] annulation of N-propargyl ynamides with diketones has been developed, allowing practical and atom-economic synthesis of valuable pyrrole-substituted dioxoles in generally moderate to excellent yields.

Integrated sensing and communication (ISAC) is recognized as a promising technology with great potential in saving hardware and spectrum resources, since it simultaneously realizes radar detection and user communication functions in the fully-shared platform. Employing reconfigurable intelligent surface (RIS) in ISAC systems is able to provide a virtual line-of-sight (LoS) path to conquer blockage problem as well as introduce new degrees of freedom (DoFs) to further enhance system performance. Nevertheless, the multiplicative fading effect of passive RIS limits its applications in the absence of direct links, which promotes the development of active RIS. In this paper, we consider an active RIS-assisted ISAC system and aim to jointly design the transmit beamformer, the active RIS reflection and the radar receive filter to maximize the radar output signal-to-noise ratio (SNR) while guaranteeing pre-defined signal-to-interference-plus-noise ratios (SINRs) for communication users. To solve for this non-convex problem, an efficient algorithm is developed by leveraging the techniques of block coordinate descent (BCD), Dinkelbach's transform and majorization-minimization (MM). Simulation results verify the significant advancement of deploying active RIS in ISAC systems, which can achieve up to 32dB radar SNR enhancement compared with the passive RIS-assisted ISAC systems., accepted by IEEE TVT

Cationic pair substitution induces tunable ZPL emission of Mn4+ in LaAlO3:Mn4+, and the ZPL emission exhibits an octahedral-tilting dependent behavior.

Doping Li+/Ga3+ in ZnGa2O4:Cr3+ splits the energy level of electron traps into shallow traps and deep traps, which makes the developed phosphors be successfully excited by a low-energy NIR light and suitable for long-term biological imaging.

Diabetic foot ulcer (DFU) and poor wound healing are chronic complications in patients with diabetes. The increasing incidence of DFU has resulted in huge pressure worldwide. Diagnosing and treating this condition are therefore of great importance to control morbidity and improve prognosis. Finding new markers with potential diagnostic and therapeutic utility in DFU has gathered increasing interest. Wound healing is a process divided into three stages: Inflammation, proliferation, and regeneration. Non-coding RNAs (ncRNAs), which are small protected molecules transcribed from the genome without protein translation function, have emerged as important regulators of diabetes complications. The deregulation of ncRNAs may be linked to accelerated DFU development and delayed wound healing. Moreover, ncRNAs can be used for therapeutic purposes in diabetic wound healing. Herein, we summarize the role of microRNAs, long ncRNAs, and circular RNAs in diverse stages of DFU wound healing and their potential use as novel therapeutic targets.

Salidroside, a prominent active ingredient in traditional Chinese medicines, is garnering increased attention because of its unique pharmacological effects against ischemic heart disease via MAPK signaling, which plays a critical role in regulating the evolution of ventricular hypertrophy. However, the function of Salidroside on myocardial hypertrophy has not yet been elucidated. C57BL/6 mice were subjected to transverse aortic constriction (TAC), and treated with Salidroside (100 mg kg

In this paper, we propose an end-to-end structured multimodal attention (SMA) neural network to mainly solve the first two issues above. SMA first uses a structural graph representation to encode the object-object, object-text and text-text relationships appearing in the image, and then designs a multimodal graph attention network to reason over it. Finally, the outputs from the above modules are processed by a global-local attentional answering module to produce an answer splicing together tokens from both OCR and general vocabulary iteratively by following M4C. Our proposed model outperforms the SoTA models on TextVQA dataset and two tasks of ST-VQA dataset among all models except pre-training based TAP. Demonstrating strong reasoning ability, it also won first place in TextVQA Challenge 2020. We extensively test different OCR methods on several reasoning models and investigate the impact of gradually increased OCR performance on TextVQA benchmark. With better OCR results, different models share dramatic improvement over the VQA accuracy, but our model benefits most blessed by strong textual-visual reasoning ability. To grant our method an upper bound and make a fair testing base available for further works, we also provide human-annotated ground-truth OCR annotations for the TextVQA dataset, which were not given in the original release. The code and ground-truth OCR annotations for the TextVQA dataset are available at https://github.com/ChenyuGAO-CS/SMA, winner of TextVQA Challenge 2020, Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence

Multi-modal imaging data fusion has attracted much attention in medical data analysis because it can provide complementary information for more accurate analysis. Integrating functional and structural multi-modal imaging data has been increasingly used in the diagnosis of brain diseases, such as epilepsy. Most of the existing methods focus on the feature space fusion of different modalities but ignore the valuable high-order relationships among samples and the discriminative fused features for classification. In this paper, we propose a novel framework by fusing data from two modalities of functional MRI (fMRI) and diffusion tensor imaging (DTI) for epilepsy diagnosis, which effectively captures the complementary information and discriminative features from different modalities by high-order feature extraction with the attention mechanism. Specifically, we propose a triple network to explore the discriminative information from the high-order representation feature space learned from multi-modal data. Meanwhile, self-attention is introduced to adaptively estimate the degree of importance between brain regions, and the cross-attention mechanism is utilized to extract complementary information from fMRI and DTI. Finally, we use the triple loss function to adjust the distance between samples in the common representation space. We evaluate the proposed method on the epilepsy dataset collected from Jinling Hospital, and the experiment results demonstrate that our method is significantly superior to several state-of-the-art diagnosis approaches.