The functional decline of tomato plants infected by Candidatus Liberbacter solanacearum: an RNA-seq transcriptomic analysis

IntroductionCandidatus Liberibacter solanacearum (CLso) is a regulated plant pathogen in European and some Asian countries, associated with severe diseases in economically important Apiaceous and Solanaceous crops, including potato, tomato, and carrot. Eleven haplotypes of CLso have been identified based on the difference in rRNA and conserved genes and host and pathogenicity. Although it is pathogenic to a wide range of plants, the mechanisms of plant response and functional decline of host plants are not well defined. This study aims to describe the underlying mechanism of the functional decline of tomato plants infected by CLso by analyzing the transcriptomic response of tomato plants to CLso haplotypes A and B.MethodsNext-generation sequencing (NGS) data were generated from total RNA of tomato plants infected by CLso haplotypes A and B, and uninfected tomato plants, while qPCR analysis was used to validate the in-silico expression analysis. Gene Ontology and KEGG pathways were enriched using differentially expressed genes.ResultsPlants infected with CLso haplotype B saw 229 genes upregulated when compared to uninfected plants, while 1,135 were downregulated. Healthy tomato plants and plants infected by haplotype A had similar expression levels, which is consistent with the fact that CLso haplotype A does not show apparent symptoms in tomato plants. Photosynthesis and starch biosynthesis were impaired while starch amylolysis was promoted in plants infected by CLso haplotype B compared with uninfected plants. The changes in pathway gene expression suggest that carbohydrate consumption in infected plants was more extensive than accumulation. In addition, cell-wall-related genes, including steroid biosynthesis pathways, were downregulated in plants infected with CLso haplotype B suggesting a reduction in membrane fluidity, cell signaling, and defense against bacteria. In addition, genes in phenylpropanoid metabolism and DNA replication were generally suppressed by CLso infection, affecting plant growth and defense.DiscussionThis study provides insights into plants’ defense and functional decline due to pathogenic CLso using whole transcriptome sequencing and qPCR validation. Our results show how tomato plants react in metabolic pathways during the deterioration caused by pathogenic CLso. Understanding the underlying mechanisms can enhance disease control and create opportunities for breeding resistant or tolerant varieties

Multistage Effort and the Equity Structure of Venture Investment Based on Reciprocity Motivation

For venture capitals, it is a long process from an entry to its exit. In this paper, the activity of venture investment will be divided into multistages. And, according to the effort level entrepreneurs will choose, the venture capitalists will provide an equity structure at the very beginning. As a benchmark for comparison, we will establish two game models on multistage investment under perfect rationality: a cooperative game model and a noncooperative one. Further, as a cause of pervasive psychological preference behavior, reciprocity motivation will influence the behavior of the decision-makers. Given this situation, Rabin’s reciprocity motivation theory will be applied to the multistage game model of the venture investment, and multistage behavior game model will be established as well, based on the reciprocity motivation. By looking into the theoretical derivations and simulation studies, we find that if venture capitalists and entrepreneurs both have reciprocity preferences, their utility would have been Pareto improvement compared with those under perfect rationality

MoDA: Modeling Deformable 3D Objects from Casual Videos

In this paper, we focus on the challenges of modeling deformable 3D objects from casual videos. With the popularity of neural radiance fields (NeRF), many works extend it to dynamic scenes with a canonical NeRF and a deformation model that achieves 3D point transformation between the observation space and the canonical space. Recent works rely on linear blend skinning (LBS) to achieve the canonical-observation transformation. However, the linearly weighted combination of rigid transformation matrices is not guaranteed to be rigid. As a matter of fact, unexpected scale and shear factors often appear. In practice, using LBS as the deformation model can always lead to skin-collapsing artifacts for bending or twisting motions. To solve this problem, we propose neural dual quaternion blend skinning (NeuDBS) to achieve 3D point deformation, which can perform rigid transformation without skin-collapsing artifacts. In the endeavor to register 2D pixels across different frames, we establish a correspondence between canonical feature embeddings that encodes 3D points within the canonical space, and 2D image features by solving an optimal transport problem. Besides, we introduce a texture filtering approach for texture rendering that effectively minimizes the impact of noisy colors outside target deformable objects. Extensive experiments on real and synthetic datasets show that our approach can reconstruct 3D models for humans and animals with better qualitative and quantitative performance than state-of-the-art methods

Venture Investment Incentive Mechanisms and Simulation with Venture Entrepreneurs Having Multistage Efforts Based on Fairness Preference Theory

When venture capital has been invested into venture companies, venture capitalists and venture entrepreneurs form a principal-agent relationship. Take into account the fact that the venture entrepreneur’s effort is a long process, because the effort is not the same at different stage. Therefore, efforts variables are seen as the multistage dynamic variable, and venture investment principal-agent model with venture entrepreneurs having multistage efforts is constructed on the basis of the classic principal-agent theory in the paper. Further, in the later stage effort of venture entrepreneurs is affected by the size of prestage benefit with venture capitalists and venture entrepreneurs; thus the fairness preference model is improved, and venture investment principal-agent model with venture entrepreneurs having multistage efforts is constructed on the basis of fairness preference theory. Both theoretical derivation and simulation have demonstrated that, under the condition of information asymmetry, if the fairness preference of venture entrepreneurs holds, then (1) venture capitalists provide venture entrepreneurs with level higher than that without fairness preference, (2) in every single stage venture entrepreneurs make efforts higher than those without fairness preference, and (3) in two periods both venture investors and venture entrepreneurs gain total real gains higher than those in two periods without fair preference

Venture Investment Incentive Mechanisms and Simulation with Venture Entrepreneurs Having Multistage Efforts Based on Fairness Preference Theory

When venture capital has been invested into venture companies, venture capitalists and venture entrepreneurs form a principalagent relationship. Take into account the fact that the venture entrepreneur's effort is a long process, because the effort is not the same at different stage. Therefore, efforts variables are seen as the multistage dynamic variable, and venture investment principalagent model with venture entrepreneurs having multistage efforts is constructed on the basis of the classic principal-agent theory in the paper. Further, in the later stage effort of venture entrepreneurs is affected by the size of prestage benefit with venture capitalists and venture entrepreneurs; thus the fairness preference model is improved, and venture investment principal-agent model with venture entrepreneurs having multistage efforts is constructed on the basis of fairness preference theory. Both theoretical derivation and simulation have demonstrated that, under the condition of information asymmetry, if the fairness preference of venture entrepreneurs holds, then (1) venture capitalists provide venture entrepreneurs with level higher than that without fairness preference, (2) in every single stage venture entrepreneurs make efforts higher than those without fairness preference, and (3) in two periods both venture investors and venture entrepreneurs gain total real gains higher than those in two periods without fair preference

Clasnip: a web-based intraspecies classifier and multi-locus sequence typing for pathogenic microorganisms using fragmented sequences

Bioinformatic approaches for the identification of microorganisms have evolved rapidly, but existing methods are time-consuming, complicated or expensive for massive screening of pathogens and their non-pathogenic relatives. Also, bioinformatic classifiers usually lack automatically generated performance statistics for specific databases. To address this problem, we developed Clasnip (www.clasnip.com), an easy-to-use web-based platform for the classification and similarity evaluation of closely related microorganisms at interspecies and intraspecies levels. Clasnip mainly consists of two modules: database building and sample classification. In database building, labeled nucleotide sequences are mapped to a reference sequence, and then single nucleotide polymorphisms (SNPs) statistics are generated. A probability model of SNPs and classification groups is built using Hidden Markov Models and solved using the maximum likelihood method. Database performance is estimated using three replicates of two-fold cross-validation. Sensitivity (recall), specificity (selectivity), precision, accuracy and other metrics are computed for all samples, training sets, and test sets. In sample classification, Clasnip accepts inputs of genes, short fragments, contigs and even whole genomes. It can report classification probability and a multi-locus sequence typing table for SNPs. The classification performance was tested using short sequences of 16S, 16–23S and 50S rRNA regions for 12 haplotypes of Candidatus Liberibacter solanacearum (CLso), a regulated plant pathogen associated with severe disease in economically important Apiaceous and Solanaceous crops. The program was able to classify CLso samples with even only 1–2 SNPs available, and achieved 97.2%, 98.8% and 100.0% accuracy based on 16S, 16–23S, and 50S rRNA sequences, respectively. In comparison with all existing 12 haplotypes, we proposed that to be classified as a new haplotype, given samples have at least 2 SNPs in the combined region of 16S rRNA (OA2/Lsc2) and 16–23S IGS (Lp Frag 4–1611F/Lp Frag 4–480R) regions, and 2 SNPs in the 50S rplJ/rplL (CL514F/CL514R) regions. Besides, we have included the databases for differentiating Dickeya spp., Pectobacterium spp. and Clavibacter spp. In addition to bacteria, we also tested Clasnip performance on potato virus Y (PVY). 251 PVY genomes were 100% correctly classified into seven groups (PVYC, PVYN, PVYO, PVYNTN, PVYN:O, Poha, and Chile3). In conclusion, Clasnip is a statistically sound and user-friendly bioinformatic application for microorganism classification at the intraspecies level. Clasnip service is freely available at www.clasnip.com

5-Methyltetrahydrofolate Alleviates Memory Impairment in a Rat Model of Alzheimer’s Disease Induced by D-Galactose and Aluminum Chloride

The effects of 5-methyltetrahydrofolate (5-MTHF) on a rat model of Alzheimer’s disease (AD) induced by D-galactose (D-gal) and aluminum chloride (AlCl3) were investigated. Wistar rats were given an i.p. injection of 60 mg/kg D-gal and 10 mg/kg AlCl3 to induce AD and three doses of 1 mg/kg, 5 mg/kg or 10 mg/kg 5-MTHF by oral gavage. A positive control group was treated with 1 mg/kg donepezil by gavage. Morris water maze performance showed that 5 and 10 mg/kg 5-MTHF significantly decreased escape latency and increased the number of platform crossings and time spent in the target quadrant for AD rats. The administration of 10 mg/kg 5-MTHF decreased the brain content of amyloid β-protein 1-42 (Aβ1-42) and phosphorylated Tau protein (p-Tau) and decreased acetylcholinesterase and nitric oxide synthase activities. Superoxide dismutase activity, vascular endothelial growth factor level and glutamate concentration were increased, and malondialdehyde, endothelin-1, interleukin-6, tumor necrosis factor-alpha and nitric oxide decreased. The administration of 10 mg/kg 5-MTHF also increased the expression of disintegrin and metallopeptidase domain 10 mRNA and decreased the expression of β-site amyloid precursor protein cleavage enzyme 1 mRNA. In summary, 5-MTHF alleviates memory impairment in a D-gal- and AlCl3-exposed rat model of AD. The inhibition of Aβ1-42 and p-Tau release, reduced oxidative stress, the regulation of amyloid precursor protein processing and the release of excitatory amino acids and cytokines may be responsible

Ectopic Expression of a Maize Gene <i>ZmDUF1645</i> in Rice Increases Grain Length and Yield, but Reduces Drought Stress Tolerance

As the human population grows rapidly, food shortages will become an even greater problem; therefore, increasing crop yield has become a focus of rice breeding programs. The maize gene, ZmDUF1645, encoding a putative member of the DUF1645 protein family with an unknown function, was transformed into rice. Phenotypic analysis showed that enhanced ZmDUF1645 expression significantly altered various traits in transgenic rice plants, including increased grain length, width, weight, and number per panicle, resulting in a significant increase in yield, but a decrease in rice tolerance to drought stress. qRT-PCR results showed that the expression of the related genes regulating meristem activity, such as MPKA, CDKA, a novel crop grain filling gene (GIF1), and GS3, was significantly changed in the ZmDUF1645-overexpression lines. Subcellular colocalization showed that ZmDUF1645 was primarily localized on cell membrane systems. Based on these findings, we speculate that ZmDUF1645, like the OsSGL gene in the same protein family, may regulate grain size and affect yield through the cytokinin signaling pathway. This research provides further knowledge and understanding of the unknown functions of the DUF1645 protein family and may serve as a reference for biological breeding engineering to increase maize crop yield

Synthesis of magnetic cobalt Nanoparticles anchored on graphene nanosheets and catalytic decomposition of orange II

Magnetic cobalt nanoparticles (NPs) at a size of approximately 29.9 nm anchored on graphene sheets were prepared and tested for heterogeneous oxidation of a dyeing pollutant, Orange II, with peroxymonosulfate (PMS) in aqueous solutions. The physicochemical properties of Co–graphene hybrids were investigated by various characterization techniques, such as powder X-ray diffraction (XRD), thermogravimetric analysis (TGA), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectrometer (EDS), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The incorporation of Co NPs and graphene sheets produces much higher catalytic activity of Orange II degradation than pure Co. The Orange II decomposition rate increases with increasing temperature (25–45 °C), pH (4–10), and PMS dosage (0.04–0.60 g/L) but decreases with its increased concentration (30–120 mg/L). Kinetic studies show decomposition of Orange II on Co–graphene can be described by a pseudo-first-order kinetic model with activation energy of 49.5 kJ/mol