Expression analysis of OsbZIP transcription factors in resistance response by the rice blast resistance gene Pi36-mediated

Plant basic leucine zipper (bZIP) proteins play an essential role in the genes expression and regulation in higher plants. They have been shown to regulate diverse plant specific phenomena, including germination, floral induction and development, seed maturation, photomorphogenesis, biotic and abiotic stresses. Resistance response mediated by the rice blast resistance gene Pi36 is a typical signal transduction, in which 12 OsbZIP genes were differentially expressed by microarray analyses. To understand the potential function of OsbZIP genes during the defense responses against rice blast, the expression analysis of these OsbZIP genes, in response to the blast fungus inoculation and the related defense signal molecules induction, were further conducted using real-time fluorescent quantitative polymerase chain reaction (PCR) technique. Our data indicates that among the 12 OsbZIP genes, the expression level eight tested genes were differentially regulated and maintained to 96 h points post inoculation in rice resistant and susceptible cultivars during Magnaporthe oryzae infection, and all of them were also significantly up-regulated by one or several kinds of exogenous plant hormones stresses. Although, these genes were induced only at early time points (1 to 24 h); it is evident that the OsbZIP genes may be involved in different signaling pathway, and play potential important functions in the defense response to rice blast.Keywords: OsbZIP transcription factors, rice blast, resistance response, plant hormones stresses.African Journal of Biotechnology Vol. 12(34), pp. 5294-530

BOURNE: Bootstrapped Self-supervised Learning Framework for Unified Graph Anomaly Detection

Graph anomaly detection (GAD) has gained increasing attention in recent years due to its critical application in a wide range of domains, such as social networks, financial risk management, and traffic analysis. Existing GAD methods can be categorized into node and edge anomaly detection models based on the type of graph objects being detected. However, these methods typically treat node and edge anomalies as separate tasks, overlooking their associations and frequent co-occurrences in real-world graphs. As a result, they fail to leverage the complementary information provided by node and edge anomalies for mutual detection. Additionally, state-of-the-art GAD methods, such as CoLA and SL-GAD, heavily rely on negative pair sampling in contrastive learning, which incurs high computational costs, hindering their scalability to large graphs. To address these limitations, we propose a novel unified graph anomaly detection framework based on bootstrapped self-supervised learning (named BOURNE). We extract a subgraph (graph view) centered on each target node as node context and transform it into a dual hypergraph (hypergraph view) as edge context. These views are encoded using graph and hypergraph neural networks to capture the representations of nodes, edges, and their associated contexts. By swapping the context embeddings between nodes and edges and measuring the agreement in the embedding space, we enable the mutual detection of node and edge anomalies. Furthermore, we adopt a bootstrapped training strategy that eliminates the need for negative sampling, enabling BOURNE to handle large graphs efficiently. Extensive experiments conducted on six benchmark datasets demonstrate the superior effectiveness and efficiency of BOURNE in detecting both node and edge anomalies

A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data

Abstract Background Single-cell RNA sequencing (scRNAseq) data always involves various unwanted variables, which would be able to mask the true signal to identify cell-types. More efficient way of dealing with this issue is to extract low dimension information from high dimensional gene expression data to represent cell-type structure. In the past two years, several powerful matrix factorization tools were developed for scRNAseq data, such as NMF, ZIFA, pCMF and ZINB-WaVE. But the existing approaches either are unable to directly model the raw count of scRNAseq data or are really time-consuming when handling a large number of cells (e.g. n>500). Results In this paper, we developed a fast and efficient count-based matrix factorization method (single-cell negative binomial matrix factorization, scNBMF) based on the TensorFlow framework to infer the low dimensional structure of cell types. To make our method scalable, we conducted a series of experiments on three public scRNAseq data sets, brain, embryonic stem, and pancreatic islet. The experimental results show that scNBMF is more powerful to detect cell types and 10 - 100 folds faster than the scRNAseq bespoke tools. Conclusions In this paper, we proposed a fast and efficient count-based matrix factorization method, scNBMF, which is more powerful for detecting cell type purposes. A series of experiments were performed on three public scRNAseq data sets. The results show that scNBMF is a more powerful tool in large-scale scRNAseq data analysis. scNBMF was implemented in R and Python, and the source code are freely available at https://github.com/sqsun .https://deepblue.lib.umich.edu/bitstream/2027.42/148526/1/12918_2019_Article_699.pd

Proteomics analysis of rough endoplasmic reticulum in pancreatic beta cells

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111127/1/pmic8033.pd

IGFBP2 Plays an Essential Role in Cognitive Development during Early Life

Identifying the mechanisms underlying cognitive development in early life is a critical objective. The expression of insulin-like growth factor binding protein 2 (IGFBP2) in the hippocampus increases during neonatal development and is associated with learning and memory, but a causal connection has not been established. Here, it is reported that neurons and astrocytes expressing IGFBP2 are distributed throughout the hippocampus. IGFBP2 enhances excitatory inputs onto CA1 pyramidal neurons, facilitating intrinsic excitability and spike transmission, and regulates plasticity at excitatory synapses in a cell-type specific manner. It facilitates long-term potentiation (LTP) by enhancing N-methyl-d-aspartate (NMDA) receptor-dependent excitatory postsynaptic current (EPSC), and enhances neurite proliferation and elongation. Knockout of igfbp2 reduces the numbers of pyramidal cells and interneurons, impairs LTP and cognitive performance, and reduces tonic excitation of pyramidal neurons that are all rescued by IGFBP2. The results provide insight into the requirement for IGFBP2 in cognition in early life

Selected Translated Abstracts of Chinese-Language Climate Change Publications

This report contains English-translated abstracts of important Chinese-language literature concerning global climate change for the years 1995-1998. This body of abstracts includes the topics of adaption, ancient climate change, climate variation, the East Asia monsoon, historical climate change, impacts, modeling, and radiation, and trace gas emission. In addition to the bibliographic citations and abstracts translated into English, this report presents the original citations and abstracts in Chinese. Author and title index are included to assist the reader in locating abstracts of particular interest

Relationships between Hematopoiesis and Hepatogenesis in the Midtrimester Fetal Liver Characterized by Dynamic Transcriptomic and Proteomic Profiles

In fetal hematopoietic organs, the switch from hematopoiesis is hypothesized to be a critical time point for organogenesis, but it is not yet evidenced. The transient coexistence of hematopoiesis will be useful to understand the development of fetal liver (FL) around this time and its relationship to hematopoiesis. Here, the temporal and the comparative transcriptomic and proteomic profiles were observed during the critical time points corresponding to the initiation (E11.5), peak (E14.5), recession (E15.5), and disappearance (3 ddp) of mouse FL hematopoiesis. We found that E11.5-E14.5 corresponds to a FL hematopoietic expansion phase with distinct molecular features, including the expression of new transcription factors, many of which are novel KRAB (Kruppel-associated box)-containing zinc finger proteins. This time period is also characterized by extensive depression of some liver functions, especially catabolism/utilization, immune and defense, classical complement cascades, and intrinsic blood coagulation. Instead, the other liver functions increased, such as xenobiotic and sterol metabolism, synthesis of carbohydrate and glycan, the alternate and lectin complement cascades and extrinsic blood coagulation, and etc. Strikingly, all of the liver functions were significantly increased at E14.5-E15.5 and thereafter, and the depression of the key pathways attributes to build the hematopoietic microenvironment. These findings signal hematopoiesis emigration is the key to open the door of liver maturation

The water lily genome and the early evolution of flowering plants

Water lilies belong to the angiosperm order Nymphaeales. Amborellales, Nymphaeales and Austrobaileyales together form the so-called ANA-grade of angiosperms, which are extant representatives of lineages that diverged the earliest from the lineage leading to the extant mesangiosperms1–3. Here we report the 409-megabase genome sequence of the blue-petal water lily (Nymphaea colorata). Our phylogenomic analyses support Amborellales and Nymphaeales as successive sister lineages to all other extant angiosperms. The N. colorata genome and 19 other water lily transcriptomes reveal a Nymphaealean whole-genome duplication event, which is shared by Nymphaeaceae and possibly Cabombaceae. Among the genes retained from this whole-genome duplication are homologues of genes that regulate flowering transition and flower development. The broad expression of homologues of floral ABCE genes in N. colorata might support a similarly broadly active ancestral ABCE model of floral organ determination in early angiosperms. Water lilies have evolved attractive floral scents and colours, which are features shared with mesangiosperms, and we identified their putative biosynthetic genes in N. colorata. The chemical compounds and biosynthetic genes behind floral scents suggest that they have evolved in parallel to those in mesangiosperms. Because of its unique phylogenetic position, the N. colorata genome sheds light on the early evolution of angiosperms.Supplementary Tables: This file contains Supplementary Tables 1-21.National Natural Science Foundation of China, the open funds of the State Key Laboratory of Crop Genetics and Germplasm Enhancement (ZW201909) and State Key Laboratory of Tree Genetics and Breeding, the Fujian provincial government in China, the European Union Seventh Framework Programme (FP7/2007-2013) under European Research Council Advanced Grant Agreement and the Special Research Fund of Ghent University.http://www.nature.com/naturecommunicationsam2021BiochemistryGeneticsMicrobiology and Plant Patholog

Understanding consumers’ post-adoption behavior in sharing economy services

Sharing economy services such as bicycle-sharing have become quite popular. In these services, companies maintain systems which allow consumers to conduct sharing activities. Based upon expectation-confirmation theory, we develop a model investigating the antecedents of consumer confirmation and its consequences in the sharing economy context. Specially, we identify two antecedents including perceived performance and perceived risk. Using an empirical study, our results show that perceived performance has a positive impact on confirmation while perceived risk has a negative effect. Confirmation positively affects service satisfaction, which in turn increases continuance intention and recommendation intention. Further, confirmation is negatively related to dissatisfaction, which in turn increases switch intention. Our study clarifies the process of consumers’ decision-making about using sharing economy, and thus making contribution to the sharing economy literature. Practically, it delivers insights for companies into how to retain customers through increasing the value and reducing the risk associated with sharing economy

Corrosion Propagation Behavior of low-Cr steel Rebars in Simulated Concrete Environments

Corrosion Propagation Behavior of low-Cr steel Rebars in Simulated Concrete Environment