Phylloxera infestation and the uptake and distribution of 13C and 15N tracers in grape vines

In order to study the reason phylloxera (Daktulosphaira vitifolia Fitch) feeding on roots leads to decreased plant productivity, the uptake and distribution of 13C photosynthates and 15N in the grape vine 'Wuhe 8612' in response to phylloxera infestation were investigated. Phylloxera and grapevines cocultivated in pots were treated with 13CO2 and 15N-urea. The plant weight, nitrogen concentration and accumulation, 15N utilization efficiency, Nitrogen derived from fertilizer (Ndff%), and carbon isotope ratio (δ13C) of different organs were measured. Phylloxera infestation significantly reduced grape weight, shoot length, and N concentration and accumulation in different organs, whereas it increased the ratio between N content of the of roots and above-ground organs. Phylloxera infestation reduced leaf and root nitrogen 15N utilization efficiency, by 24 % and 14 %, respectively compared to controls. Labeled leaves of infested plants took up rather more 13C and 15N and exported a substantial amount of these nutrients to roots. Labeled roots took up rather more 15N and exported a small amount of these nutrients to upper leaves. This study found that phylloxera infestation reduced 13C and 15N uptake in leaves and roots, but increased N and photosynthates, which were mostly distributed to the roots, but also to the upper leaves. These factors together led to weak grape vine growth.

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Three-Dimensional Microtumor Formation of Infantile Hemangioma-Derived Endothelial Cells for Mechanistic Exploration and Drug Screening

Infantile hemangioma (IH) is the most prevalent type of vascular tumor in infants. The pathophysiology of IH is unknown. The tissue structure and physiology of two-dimensional cell cultures differ greatly from those in vivo, and spontaneous regression often occurs during tumor formation in nude mice and has severely limited research into the pathogenesis and development of IH. By decellularizing porcine aorta, we attempted to obtain vascular-specific extracellular matrix as the bioink for fabricating micropattern arrays of varying diameters via microcontact printing. We then constructed IH-derived CD31+ hemangioma endothelial cell three-dimensional microtumor models. The vascular-specific and decellularized extracellular matrix was suitable for the growth of infantile hemangioma-derived endothelial cells. The KEGG signaling pathway analysis revealed enrichment primarily in stem cell pluripotency, RAS, and PI3KAkt compared to the two-dimensional cell model according to RNA sequencing. Propranolol, the first-line medication for IH, was also used to test the model’s applicability. We also found that metformin had some impact on the condition. The three-dimensional microtumor models of CD31+ hemangioma endothelial cells were more robust and efficient experimental models for IH mechanistic exploration and drug screening

An Intelligent System for Outfall Detection in UAV Images Using Lightweight Convolutional Vision Transformer Network

Unmanned aerial vehicle aerial photography technology has become a crucial tool for detecting outfalls that discharge into rivers and oceans. However, the current retrieval process in aerial images relies heavily on visual interpretation by skilled experts, which is time-consuming and inefficient. To address this issue, we propose a lightweight deep-learning model for detecting outfall objects in aerial images. Specifically, the backbone of our proposed model is a lightweight convolutional vision transformer network, which consists of two novel blocks: separated downsampled self-attention and convolutional feedforward network with a shortcut. These blocks are designed to capture information at different granularities in the feature map and build both local and global representations. The model utilizes a path aggregation feature pyramid network as the neck and a lightweight decoupled network as the head. The experiments demonstrate that our model achieves the highest accuracy of 81.5% while utilizing only 2.47 M parameters and 3.95 GFLOPs. Visualization analysis shows that our model pays more attention to true outfall objects. Additionally, we have developed an intelligent outfall detection system based on the proposed model, and the experimental results show that it performs well in the task of outfall detection

Calculation of Comprehensive Ecological Flow with Weighted Multiple Methods Considering Hydrological Alteration

Instream ecological flow is an essential determinant of river health. Intra- and interannual distribution characteristics of runoff have been altered to different degrees by dam construction. Historical runoff series with alterations, as basic data for ecological flow calculation, provide minimal instream hydrological process information, which affects the credibility of calculation results. Considering the influence of the alterations in runoff series on ecological flow calculation, the Gini coefficient (GI) is introduced to study the evenness degrees of the intra-annual runoff distribution of four hydrological stations located in the Naolihe basin of the Sanjiang Plain. The hydrological alteration diagnosis system is used to examine the alteration points in the GI series of each hydrological station for selecting reasonable subsequences. Based on the selected subsequences, the ecological flow of each station is calculated using three hydrological methods, and the comprehensive ecological flow is calculated using weighted calculation results from the three hydrological methods. The study results show that ecological flow and natural flow have similar processes with two peaks occurring in the process in May and August, respectively. Also, dams decrease the ecological water requirement damage frequency in dry seasons, but overuse of water resources increases the ecological water requirement damage frequency in flood seasons

Synergistic combination therapy of lung cancer using lipid-layered cisplatin and oridonin co-encapsulated nanoparticles

Lung cancer treatment using cisplatin (DDP) in combination with other drugs are effective for the treatment of non-small cell lung cancer (NSCLC). The aim of this study was to prepare a layer-by-layer nanoparticles (NPs) for the co-loading of DDP and oridonin (ORI) and to evaluate the antitumor activity of the system in vitro and in vivo. Novel DDP and ORI co-loaded layer-by-layer NPs (D/O-NPs) were constructed. The mean diameter, surface change stability and drug release behavior of NPs were evaluated. In vitro cytotoxicity of D/O-NPs was investigated against DDP resistant human lung cancer cell line (A549/DDP cells), and in vivo anti-tumor efficiency of D/O-NPs was tested on mice bearing A549/DDP cells xenografts. D/O-NPs have a diameter of 139.6 ± 4.4 nm, a zeta potential value of +13.8 ± 1.6 mV. D/O-NPs could significantly enhance in vitro cell toxicity and in vivo antitumor effect against A549/DDP cells and lung cancer animal model compared to the single drug loaded NPs and free drugs. The results demonstrated that the D/O-NPs could be used as a promising lung cancer treatment system