A5045972450- Physiological and biochemical adaptations
- Aquaculture disease management and microbiota
- Aquaculture Nutrition and Growth
- Meat and Animal Product Quality
- Model Reduction and Neural Networks
- Neurobiology and Insect Physiology Research
- Computer Graphics and Visualization Techniques
- Adipose Tissue and Metabolism
- Fish Ecology and Management Studies
- Crustacean biology and ecology
- Seaweed-derived Bioactive Compounds
- Invertebrate Immune Response Mechanisms
- Plant nutrient uptake and metabolism
- Heat Transfer and Optimization
- Enzyme Production and Characterization
- Molecular Biology Techniques and Applications
- Photoreceptor and optogenetics research
- Advanced Data Storage Technologies
- Lattice Boltzmann Simulation Studies
- Bat Biology and Ecology Studies
- Animal Genetics and Reproduction
- Fire dynamics and safety research
- Parallel Computing and Optimization Techniques
- Legume Nitrogen Fixing Symbiosis
- Coal and Its By-products
Chinese Academy of Sciences
2013-2024
National University of Defense Technology
2022-2024
University of Chinese Academy of Sciences
2015-2024
Huazhong Agricultural University
2024
Tianjin Institute of Industrial Biotechnology
2019-2024
Institute of Crop Science
2022
Institute of Hydrobiology
2013-2020
Institute of Hydrobiology, Biology Centre, Academy of Sciences of the Czech Republic
2019-2020
Tianjin University of Science and Technology
2019
Temperature is one of key environmental parameters that affect the whole life fishes and an increasing number studies have been directed towards understanding mechanisms cold acclimation in fish. However, adaptation larvae to stress cold-specific transcriptional alterations fish remain largely unknown. In this study, we characterized development cold-tolerance zebrafish investigated profiles under using RNA-seq.Pre-exposure 96 hpf (16°C) for 24 h significantly increased their survival rates...
Hypoxia and temperature stress are two major adverse environmental conditions often encountered by fishes. The interaction between hypoxia stresses has been well documented oxygen is considered to be the limiting factor for thermal tolerance of fish. Although both high low can impair cardiovascular function cross-resistance heat found, it not clear whether acclimation protect fish from cold injury.
Kernel dehydration rate (KDR) is a crucial production trait that affects mechanized harvesting and kernel quality in maize; however, the underlying mechanisms remain unclear. Here, we identified quantitative locus (QTL), qKDR1, as non-coding sequence regulates expression of qKDR1 REGULATED PEPTIDE GENE (RPG). RPG encodes 31 amino acid micropeptide, microRPG1, which controls KDR by precisely modulating two genes, ZmETHYLENE-INSENSITIVE3-like 1 3, ethylene signaling pathway kernels after...
Alginase lyase is an important enzyme for the preparation of alginate oligosaccharides (AOS), that possess special biological activities and widely used in various fields, such as medicine, food, chemical industry. In this study, a novel bifunctional (AlgH) belonging to PL7 family was screened characterized. The AlgH exhibited highest activity at 45 °C pH 10.0, alkaline stable 6.0-10.0. showed no significant dependence on metal ions, unchanged high concentration NaCl. To determine function...
Abstract Optogenetics’ advancement has made light induction attractive for controlling biological processes due to its advantages of fine-tunability, reversibility, and low toxicity. The lactose operon system, commonly used in Escherichia coli, relies on the binding or isopropyl β-d-1-thiogalactopyranoside (IPTG) repressor protein LacI, playing a pivotal role operon. Here, we harnessed light-responsive light-oxygen-voltage 2 (LOV2) domain from Avena sativa phototropin 1 as tool control...
Abstract Background Closely related species of the carp family ( Cyprinidae ) have evolved distinctive abilities to survive under cold stress, but molecular mechanisms underlying generation resistance remain largely unknown. In this study, we compared transcriptomic profiles two identify key factors and pathways for tolerance acclimation. Results Larvae Songpu mirror Barbless that were pretreated at 18 °C 24 h significantly improved their survival rates lethal temperature 8 or 10 °C,...
Selective breeding for DIV1-resistant Macrobrachium rosenbergii is an effective strategy to mitigate aquaculture losses; however, the underlying resistance mechanisms remain poorly understood. In this study, approximately 2,300 prawns from 46 families were subjected a DIV1 challenge test. Based on survival rate, viral load, histopathological observations, and gene detection in transcriptome, one resistant family (R27-1) susceptible (S2-2) identified. Hepatopancreas transcriptomic (RNA-Seq)...
The farming of Macrobrachium rosenbergii faces significant challenges due to infections caused by Decapod iridovirus 1 (DIV1). To gain deeper insights into the dynamic immune regulatory processes M. in response DIV1 infection, RNA sequencing (RNA-seq) was employed profile transcriptome hepatopancreas at 24, 48, 72, and 96 hours post-infection (hpi). Time-course analysis revealed 3,339 differentially expressed genes (DEGs), which exhibited distinct expression patterns across various stages...
The present study investigated growth performance, body composition, hepatic and intestinal morphology, biochemical indices, transcriptomic responses, metabolomic profiles in giant freshwater prawn ( Macrobrachium rosenbergii ) fed six kinds of soy protein concentrate (SPC) diets over an 8‐week feeding trial. SPC were formulated by replacing varying proportions fishmeal (FM) with SPC, the final percentage FM set at 350, 280, 210, 140, 70, 0 g/kg, respectively, designated as F35, F28, F21,...
Partial differential equations (PDEs) are an essential computational kernel in physics and engineering. With the advance of deep learning, physics-informed neural networks (PINNs), as a mesh-free method, have shown great potential for fast PDE solving various applications. To address issue low accuracy convergence problems existing PINNs, we propose self-training network, ST-PINN. Specifically, ST-PINN introduces pseudo label based self-learning algorithm during training. It employs...
Abstract Temperature affects almost all aspects of the fish life. To cope with low temperature, have evolved ability cold acclimation for survival. However, intracellular signaling events underlying in remain largely unknown. Here, formation zebrafish embryonic fibroblasts (ZF4) is monitored and phosphorylation during process are investigated through a large‐scale quantitative phosphoproteomic approach. In total, 11 474 sites identified on 4066 proteins quantified 5772 phosphosites 2519...
Computational fluid dynamics (CFD) plays a critical role in many scientific and engineering applications, with aerodynamic design optimization being primary area of interest. Recently, there has been much interest using artificial intelligence approaches to accelerate this process. One promising method is the graph convolutional neural network (GCN), deep learning based on networks (ANNs). In paper, we propose novel GCN-based acceleration framework, framework. The framework significantly...
Combustion of agricultural organic solid waste (AOSW) was an ideal solution for their resource utilization in view massive annual production and great potential reduction fossil fuel utilization. However, high alkali alkaline earth metals (AAEMs) content the feedstock can arose severe fouling slagging issues thus prohibiting its vast In this study, a semi-continuous water washing method proposed to preliminarily remove AAEMs from effects on combustion behaviors washed product were...
Mesh generation remains a key technology in many areas where numerical simulations are required. As algorithms become more efficient and computers powerful, the percentage of time devoted to mesh becomes higher. In this paper, we present an improved structured method. The method formulates meshing problem as global optimization related physics-informed neural network. is obtained by intelligently solving physical boundary-constrained partial differential equations. To improve prediction...
Site-specific DNA double-strand breaks have been used to generate knock-in through the homology-dependent or -independent pathway. However, low efficiency and accompanying negative impacts such as undesirable indels tumorigenic potential remain problematic. In this study, we present an enhanced reduced-risk genome editing strategy named NEO, which either site-specific trans cis double-nicking facilitated by four bacterial recombination factors (RecOFAR). comparison currently available...
Physics-informed neural networks (PINNs) have emerged as promising surrogate modes for solving partial differential equations (PDEs). Their effectiveness lies in the ability to capture solution-related features through networks. However, original PINNs often suffer from bottlenecks, such low accuracy and non-convergence, limiting their applicability complex physical contexts. To alleviate these issues, we proposed auxiliary-task learning-based physics-informed (ATL-PINNs), which provide four...
Constitutive promoters are important tools for gene function studies and transgenesis. The Beta-actin (actb1) promoter has been isolated from many species but remains to be cloned the giant freshwater prawn (Macrobrachium rosenbergii). In this study, we characterized Mractb1 promoter. Two alternative were identified gene, which direct generation of two transcripts with different 5' untranslated regions. Three CpG islands predicted in upstream sequence, intimately related transcription...
Recent progress has shown that vacuolar Pi transporters (VPTs) are important for cellular homeostasis against external variations in Arabidopsis and rice, while it is poorly understood the identity regulatory mechanism of VPTs Brassica napus ( B. ). Here, we identified two influx BnA09PHT5;1b BnCnPHT5;1b uncovered their necessity through functional analysis. BnPHT5;1bs homologs AtPHT5;1 with similar sequence, structure, tonoplast localization, VPT activity. BnPHT5;1b double mutants had...
Partial differential equations (PDEs) are an essential computational kernel in physics and engineering. With the advance of deep learning, physics-informed neural networks (PINNs), as a mesh-free method, have shown great potential for fast PDE solving various applications. To address issue low accuracy convergence problems existing PINNs, we propose self-training network, ST-PINN. Specifically, ST-PINN introduces pseudo label based self-learning algorithm during training. It employs...