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Drought at the grain filling stage of wheat will cause premature leaf senescence, thus leading to considerable loss of wheat yield. Therefore, this paper aims to establish a cultivation technology for strong drought resistance, delayed senescence, and yield improvement based on the analysis of hormones homeostasis obtained by applying chemical control substances. Experiments were conducted with two genotypes of wheat. Four water irrigation treatments were applied to impose the water deficit, including well-watered control treatment (WW), mild water deficit (MiWD), moderate water deficit (MoWD), and severe water deficit (SWD). Exogenous abscisic acid (ABA) was sprayed on the plants at the anthesis stage of the wheat. As a result, exogenous ABA reduced initial senescence rate (r0), total duration of chlorophyll (Chltotal), rapid senescence phase (Chlloss), and the accumulated temperature at an inflection point (M) but improved the persistence phase (Chlper) of flag leaves under all of the four treatments. However, exogenous ABA produced inconsistent effects on photoassimilate relocation and grain weight under different treatments. It produced positive regulatory effects on grain weight under WW, MiWD, and MoWD treatments. On the one hand, spraying ABA during the persistence phase of flag leaves reduced the ratios of zeatin to gibberellin (Z/GA3), spermine to spermidine (Spm/Spd), and salicylic acid to ABA (SA/ABA), which prolonged active photosynthesis by stimulating high level of proline (Pro) and increased the activities of antioxidant enzymes, such as superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX). Therefore, drought tolerance was enhanced, and more photosynthetic assimilates were accumulated. On the other hand, the rapid senescence phase and the transport rate of assimilates into grains were accelerated, resulting in higher grain weight, yield, and water use efficiency (WUE). However, under SWD treatment, exogenous ABA improved the ratio of SA/ABA, leading to low Pro content and low antioxidant enzyme activity of flag leaves in the rapid loss phase. Meanwhile, drought resistance declined and the transport duration of assimilates into grains was shortened, thus making photosynthetic assimilates redundant. Therefore, exogenous ABA can lead to the reduction in grain weight, yield, and WUE of wheat under SWD treatment.

Kaidireyahan Wumaier,1 Wenqian Li,1 Jiuwei Cui2 1The First Hospital of Jilin University, Jilin University, Changchun, People’s Republic of China; 2Department of Cancer Center, the First Hospital of Jilin University, Changchun, People’s Republic of ChinaCorrespondence: Jiuwei Cui, Department of Cancer Center, the First Hospital of Jilin University, Changchun, Jilin, 130021, People’s Republic of China, Tel/Fax +86-0431-88782178, Email cuijw@jlu.edu.cnAbstract: Venous thromboembolism (VTE) is associated with increased morbidity and mortality, decreased quality of life, and higher economic burden in patients with cancer. Currently, the treatment of VTE in patients with cancer is particularly challenging. For many years, low molecular weight heparin (LMWHs) has been the standard for the treatment of cancer-associated VTE. Recently, the introduction of new oral anticoagulants (NOACs) may offer an oral anticoagulant option for some patients with cancer-associated thrombosis (CAT) as a growing body of literature supports the use of NOACs in the setting of CAT. With the use of NOAC as a new option in the management of CAT, clinicians now face several choices for the individual cancer patient with VTE. We need a more in-depth understanding of the drug properties, efficacy and safety, economic analysis that allows us to choose the most appropriate treatment for each patient. In the review, we will present an overview of CAT management, discuss the available evidence, economic costs for NOACs in the treatment of CAT, and seek to provide the best range of treatments for cancer patients.Keywords: new oral anticoagulants, low molecular weight heparin, venous thromboembolism, cancer-associated thrombosis, anticoagulants

Cellulose sulfates (CS) with low degree of substitution (DS) and high degree of polymerization (DP) were prepared via a controlled sulfation modification. The obtained CS with DS 0.42 and DP 293 showed an enhanced solubility of 14.7 g/100 g in the ionic liquid 1-ethyl-3-methylimidazolium acetate (EMIMAc) compared to unmodified cellulose. The rheological study revealed that the CS/EMIMAc solution behaved as polymers in a θ solvent with the unique three-region flow curves under shear stress. It also showed a property of typical polyelectrolyte solution with the overlap concentration (c*) of 0.2 wt% and the entanglement concentration (ce) of 3.0 wt%, respectively. The CS/EMIMAc solution with a concentration of 5 wt% was selected to develop polyelectrolyte complex (PEC) with chitosan using extrusion-spherization and emulsification-solvent evaporation. The produced PEC beads and magnetic microspheres had an average size of 1.0 mm and 22.1 µm, respectively. The PEC microspheres showed greater absorption capability for bovine serum albumin than the beads with the maximum adsorption value of 780 mg/g.

Causal discovery aims to uncover causal structure among a set of variables. Score-based approaches mainly focus on searching for the best Directed Acyclic Graph (DAG) based on a predefined score function. However, most of them are not applicable on a large scale due to the limited searchability. Inspired by the active learning in generative flow networks, we propose a novel approach to learning a DAG from observational data called GFlowCausal. It converts the graph search problem to a generation problem, in which direct edges are added gradually. GFlowCausal aims to learn the best policy to generate high-reward DAGs by sequential actions with probabilities proportional to predefined rewards. We propose a plug-and-play module based on transitive closure to ensure efficient sampling. Theoretical analysis shows that this module could guarantee acyclicity properties effectively and the consistency between final states and fully-connected graphs. We conduct extensive experiments on both synthetic and real datasets, and results show the proposed approach to be superior and also performs well in a large-scale setting.