A novel mouse model of calcific aortic valve stenosis

Background:Calcific aortic valve stenosis(CAVS)is one of the most challenging heart diseases in clinical with rapidly increasing prevalence.However,study of the mecha-nism and treatment of CAVS is hampered by the lack of suitable,robust and efficient models that develop hemodynamically significant stenosis and typical calcium deposi-tion.Here,we aim to establish a mouse model to mimic the development and features of CAVS.Methods:The model was established via aortic valve wire injury(AVWI)combined with vitamin D subcutaneous injected in wild type C57/BL6 mice.Serial transthoracic echocardiography was applied to evaluate aortic jet peak velocity and mean gradi-ent.Histopathological specimens were collected and examined in respect of valve thickening,calcium deposition,collagen accumulation,osteogenic differentiation and inflammation.Results:Serial transthoracic echocardiography revealed that aortic jet peak velocity and mean gradient increased from 7 days post model establishment in a time depend-ent manner and tended to be stable at 28 days.Compared with the sham group,sim-ple AVWI or the vitamin D group,the hybrid model group showed typical pathological features of CAVS,including hemodynamic alterations,increased aortic valve thicken-ing,calcium deposition,collagen accumulation at 28 days.In addition,osteogenic dif-ferentiation,fibrosis and inflammation,which play critical roles in the development of CAVS,were observed in the hybrid model.Conclusions:We established a novel mouse model of CAVS that could be induced efficiently,robustly and economically,and without genetic intervention.It provides a fast track to explore the underlying mechanisms of CAVS and to identify more effec-tive pharmacological targets.

C-H-O Stable Isotope, Elements and Fluid Geochemistry of Uraniferous Leucogranites in Gaudeanmus Area, Southern Central Zone, Damara Orogen, Namibia

This paper focuses on the effect of the later hydrotherm on uraniferous leucogranites and the stages of uranium mineralization. Here, we review C-H-O stable isotope, elements and fluid geochemistry of uraniferous leucogranites in Gaudeanmus, Namibia. The results show that there is significant increasing amount of rare earth element from non-mineralized to uraniferous leucogra-nites, indicating the synchronization of REE enrichment and uranium mineralization. Uranium enrichment may have close relations with Pb, Th, Co, Ni, REE in this region, so REE and U evidently exist homology. There are at least two stages of uranium mineralization by later hydrothermal alteration: firstly, due to magnatic residual high temperature and low salinity fluid, the temperature of main metallogenetic epoch ranges from 470°C to 530°C, salinity ranges from 3.55% to 9.60% NaCleq, and C, H, O stable isotope is -23‰ - -13.6‰, -53.3‰ - -46.4‰, 7.71‰ - 8.81‰, respectively. Secondly, due to superim-posed hydrothermal fluid, the temperature, salinity, and C, H, O stable isotope is 150°C - 220°C, 4.65% - 19.05% NaCleq, -20.3‰ -?-3.7‰, -64.7‰ - -53.6‰, 1.49‰ - 1.99‰, respectively. The fluid for reformation is derived from postmagmatic fluid, mixed with a number of meteoric water.

The AaCBF4-AaBAM3.1 module enhances freezing tolerance of kiwifruit (Actinidia arguta)

Beta-amylase(BAM)plays an important role in plant resistance to cold stress.However,the specific role of the BAM gene in freezing tolerance is poorly understood.In this study,we demonstrated that a cold-responsive gene module was involved in the freezing tolerance of kiwifruit.In this module,the expression of AaBAM3.1,which encodes a functional protein,was induced by cold stress.AaBAM3.1-overexpressing kiwifruit lines showed increased freezing tolerance,and the heterologous overexpression of AaBAM3.1 in Arabidopsis thaliana resulted in a similar phenotype.The results of promoter GUS activity and cis-element analyses predicted AaCBF4 to be an upstream transcription factor that could regulate AaBAM3.1 expression.Further investigation of protein-DNA interactions by using yeast one-hybrid,GUS coexpression,and dual luciferase reporter assays confirmed that AaCBF4 directly regulated AaBAM3.1 expression.In addition,the expression of both AaBAM3.1 and AaCBF4 in kiwifruit responded positively to cold stress.Hence,we conclude that the AaCBF-AaBAM module is involved in the positive regulation of the freezing tolerance of kiwifruit.

Metric-based Few-shot Classification in Remote Sensing Image

Target recognition based on deep learning relies on a large quantity of samples,but in some specific remote sensing scenes,the samples are very rare.Currently,few-shot learning can obtain high-performance target classification models using only a few samples,but most researches are based on the natural scene.Therefore,this paper proposes a metric-based few-shot classification technology in remote sensing.First,we constructed a dataset(RSD-FSC)for few-shot classification in remote sensing,which contained 21 classes typical target sample slices of remote sensing images.Second,based on metric learning,a k-nearest neighbor classification network is proposed,to find multiple training samples similar to the testing target,and then the similarity between the testing target and multiple similar samples is calculated to classify the testing target.Finally,the 5-way 1-shot,5-way 5-shot and 5-way 10-shot experiments are conducted to improve the generalization of the model on few-shot classification tasks.The experimental results show that for the newly emerged classes few-shot samples,when the number of training samples is 1,5 and 10,the average accuracy of target recognition can reach 59.134%,82.553%and 87.796%,respectively.It demonstrates that our proposed method can resolve few-shot classification in remote sensing image and perform better than other few-shot classification methods.

Engineered M2 macrophage-derived extracellular vesicles with platelet membrane fusion for targeted therapy of atherosclerosis

Atherosclerosis is featured as chronic low-grade inflammation in the arteries,which leads to the formation of plaques rich in lipids.M_(2)macrophage-derived extracellular vesicles(M_(2)EV)have significant potential for anti-atherosclerotic therapy.However,their therapeutic effectiveness has been hindered by their limited targeting capability in vivo.The objective of this study was to create the P-M_(2)EV(platelet membrane-modified M_(2)EV)using the membrane fusion technique in order to imitate the interaction between platelets and macrophages.P-M_(2)EV exhibited excellent physicochemical properties,and microRNA(miRNA)-sequencing revealed that the extrusion process had no detrimental effects on miRNAs carried by the nanocarriers.Remarkably,miR-99a-5p was identified as the miRNA with the highest expression level,which targeted the mRNA of Homeobox A1(HOXA1)and effectively suppressed the formation of foam cells in vitro.In an atherosclerotic low-density lipoprotein receptor-deficient(Ldlr^(-/-))mouse model,the intravenous injection of P-M_(2)EV showed enhanced targeting and greater infiltration into atherosclerotic plaques compared to regular extracellular vesicles.Crucially,P-M_(2)EV successfully suppressed the progression of atherosclerosis without causing systemic toxicity.The findings demonstrated a biomimetic platelet-mimic system that holds great promise for the treatment of atherosclerosis in clinical settings.

UAV-based field watermelon detection and counting using YOLOv8s with image panorama stitching and overlap partitioning

Accurate watermelon yield estimation is crucial to the agricultural value chain,as it guides the allocation of agricultural resources as well as facilitates inventory and logistics planning.The conventional method of watermelon yield estimation relies heavily onmanual labor,which is both time-consuming and labor-intensive.To address this,this work proposes an algorithmic pipeline that utilizes unmanned aerial vehicle(UAV)videos for detection and counting of watermelons.This pipeline uses You Only Look Once version 8 s(YOLOv8s)with panorama stitching and overlap partitioning,which facilitates the overall number estimation ofwatermelons in field.The watermelon detection model,based on YOLOv8s and obtained using transfer learning,achieved a detection accuracy of 99.20%,demonstrating its potential for application in yield estimation.The panorama stitching and overlap partitioning based detection and counting method uses panoramic images as input and effectively mitigates the duplications comparedwith the video tracking based detection and countingmethod.The counting accuracy reached over 96.61%,proving a promising application for yield estimation.The high accuracy demonstrates the feasibility of applying this method for overall yield estimation in large watermelon fields.

Distributed formation control of multiple aerial vehicles based on guidance route

Formation control of fixed-wing aerial vehicles is an important yet rarely addressed problem because of their complex dynamics and various motion constraints,such as nonholonomic and velocity constraints.The guidance-route-based strategy has been demonstrated to be applicable to fixed-wing aircraft.However,it requires a global coordinator and there exists control lag,due to its own natures.For this reason,this paper presents a fully distributed guidance-route-based formation approach to address the aforementioned issues.First,a hop-count scheme is introduced to achieve distributed implementation,in which each aircraft chooses a neighbor with the minimum hop-count as a reference to generate its guidance route using only local information.Next,the model predictive control algorithm is employed to eliminate the control lag and achieve precise formation shape control.In addition,the stall protection and collision avoidance are also considered.Finally,three numerical simulations demonstrate that our proposed approach can implement precise formation shape control of fixed-wing aircraft in a fully distributed manner.

Satellite group autonomous operation mechanism and planning algorithm for marine target surveillance

In terms of fast response problem of unanticipated marine target, it is necessary to design the satellite-ground-combined operation mechanism and planning algorithm for autonomous task planning. Firstly, based on the autonomous operation and task planning of remote sensing satellite group, it is divided into two parts: ground planning and satellite autonomous planning. Secondly,the satellite-ground-combined operation mechanism and operation flow for task planning are proposed after fully considering the resource characteristics and task demand characteristics of the ground and satellite. The satellite autonomous task planning algorithm based on extended contract net is designed. Through the simulation operation of the self-developed distributed simulation demonstration software, it shows that the operation mechanism can coordinate and cooperate effectively between the satellite autonomous task planning and ground planning. It can give full play to the advantages of the ground computing resources, reflect the control intention, make full use of the real-time feature and flexibility of the satellite calculation, and respond fast to the unanticipated task. Besides, it has solved problems of the untimely response of ground control on unanticipated observation task, the limitation of satellite computing resources and satellite-ground planning and coordination, which can effectively improve the responsiveness of remote sensing satellite to the observation task of maritime unanticipated target.