lncRNA LOC100911717-targeting GAP43-mediated sympathetic remodeling after myocardial infarction in rats

ObjectiveSympathetic remodeling after myocardial infarction (MI) is the primary cause of ventricular arrhythmias (VAs), leading to sudden cardiac death (SCD). M1-type macrophages are closely associated with inflammation and sympathetic remodeling after MI. Long noncoding RNAs (lncRNAs) are critical for the regulation of cardiovascular disease development. Therefore, this study aimed to identify the lncRNAs involved in MI and reveal a possible regulatory mechanism.Methods and resultsM0- and M1-type macrophages were selected for sequencing and screened for differentially expressed lncRNAs. The data revealed that lncRNA LOC100911717 was upregulated in M1-type macrophages but not in M0-type macrophages. In addition, the lncRNA LOC100911717 was upregulated in heart tissues after MI. Furthermore, an RNA pull-down assay revealed that lncRNA LOC100911717 could interact with growth-associated protein 43 (GAP43). Essentially, immunofluorescence assays and programmed electrical stimulation demonstrated that GAP43 expression was suppressed and VA incidence was reduced after lncRNA LOC100911717 knockdown in rat hearts using an adeno-associated virus.ConclusionsWe observed a novel relationship between lncRNA LOC100911717 and GAP43. After MI, lncRNA LOC100911717 was upregulated and GAP43 expression was enhanced, thus increasing the extent of sympathetic remodeling and the frequency of VA events. Consequently, silencing lncRNA LOC100911717 could reduce sympathetic remodeling and VAs

OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping

Accurately depicting the complex traffic scene is a vital component for autonomous vehicles to execute correct judgments. However, existing benchmarks tend to oversimplify the scene by solely focusing on lane perception tasks. Observing that human drivers rely on both lanes and traffic signals to operate their vehicles safely, we present OpenLane-V2, the first dataset on topology reasoning for traffic scene structure. The objective of the presented dataset is to advance research in understanding the structure of road scenes by examining the relationship between perceived entities, such as traffic elements and lanes. Leveraging existing datasets, OpenLane-V2 consists of 2,000 annotated road scenes that describe traffic elements and their correlation to the lanes. It comprises three primary sub-tasks, including the 3D lane detection inherited from OpenLane, accompanied by corresponding metrics to evaluate the model's performance. We evaluate various state-of-the-art methods, and present their quantitative and qualitative results on OpenLane-V2 to indicate future avenues for investigating topology reasoning in traffic scenes.Comment: Accepted by NeurIPS 2023 Track on Datasets and Benchmarks | OpenLane-V2 Dataset: https://github.com/OpenDriveLab/OpenLane-V

Investigating the efficacy of a novel therapeutic to mitigate traumatic brain injury : contributions of environmental exposures to overall healing.

Traumatic brain injury (TBI) is a leading cause of disability and premature death among both civilians and military. Morbidity and deaths are mainly caused by several secondary process that exacerbate brain dysfunction in the minutes to days following the primary injury when blood vessels and tissues are torn, stretched, or compressed. In previous studies, proper oxygen supply has been shown to help brain cells to grow and repair, remove the obstruction in blood flow, and alleviate brain edema to prevent secondary injury. OX-66, a novel therapeutic, potentially provides an efficient supply of oxygen to the cells. This therapeutic was investigated in this study to determine its cytotoxicity and potential mechanism of cellular repair in invitro-injured rat brain cells. The effects of exposure to polycyclic aromatic hydrocarbons (PAH) on TBI patients and the corresponding restorative influence of OX-66 were also evaluated

Changes of Fruit Abscission and Carbohydrates, Hormones, Related Gene Expression in the Fruit and Pedicel of Macadamia under Starvation Stress

In order toexplore the regulation mechanism of macadamia fruitlet abscission induced by ‘starvation stress’, a treatment of girdling and defoliation was applied to the bearing shoots of macadamia cultivar ‘H2’ at the early stage of fruit development, simulating the starvation stress induced by interrupting carbon supply to fruit. The levels of carbohydrates, hormones, and related gene expression in the different tissues (husk, seed, and pedicel) were investigated after treatment. The results showed that a severe fruit drop occurred 3~5 d after starvation stress treatment. The contents of glucose, fructose, and sucrose in both the husk and the seed were significantly decreased, as well as the fructose and sucrose in the pedicel; this large reduction occurred prior to the massive fruit shedding. Starvation stress significantly reduced the GA3 and ZR contents and enhanced the ABA level in the pedicel and the seed, whereas it did not obviously change these hormones in the husk. After treatment, IAA content decreased considerably in both the husk and seed but increased remarkably in the pedicel. In the husk, the expression of genes related to sugar metabolism and signaling (NI, HXK2, TPS, and TPP), as well as the biosynthesis of ethylene (ACO2 and ACS) and ABA (NCED1.1 and AAO3), was significantly upregulated by starvation stress, as well as the stress-responsive transcription factors (AP2/ERF, HD-ZIP12, bZIP124, and ABI5), whereas the BG gene associated with ABA accumulation and the early auxin-responsive genes (Aux/IAA22 and GH3.9) were considerably suppressed during the period of massive fruit abscission. Similar changes in the expression of all genes occurred in the pedicel, except for NI and AP2/ERF, the expression of which was significantly upregulated during the early stage of fruit shedding and downregulated during the period of severe fruit drop. These results suggest that complicated crosstalk among the sugar, IAA, and ABA signaling may be related to macadamia fruitlet abscission induced by carbohydrate starvation

Changes of Fruit Abscission and Carbohydrates, Hormones, Related Gene Expression in the Fruit and Pedicel of Macadamia under Starvation Stress

In order toexplore the regulation mechanism of macadamia fruitlet abscission induced by ‘starvation stress’, a treatment of girdling and defoliation was applied to the bearing shoots of macadamia cultivar ‘H2’ at the early stage of fruit development, simulating the starvation stress induced by interrupting carbon supply to fruit. The levels of carbohydrates, hormones, and related gene expression in the different tissues (husk, seed, and pedicel) were investigated after treatment. The results showed that a severe fruit drop occurred 3~5 d after starvation stress treatment. The contents of glucose, fructose, and sucrose in both the husk and the seed were significantly decreased, as well as the fructose and sucrose in the pedicel; this large reduction occurred prior to the massive fruit shedding. Starvation stress significantly reduced the GA3 and ZR contents and enhanced the ABA level in the pedicel and the seed, whereas it did not obviously change these hormones in the husk. After treatment, IAA content decreased considerably in both the husk and seed but increased remarkably in the pedicel. In the husk, the expression of genes related to sugar metabolism and signaling (NI, HXK2, TPS, and TPP), as well as the biosynthesis of ethylene (ACO2 and ACS) and ABA (NCED1.1 and AAO3), was significantly upregulated by starvation stress, as well as the stress-responsive transcription factors (AP2/ERF, HD-ZIP12, bZIP124, and ABI5), whereas the BG gene associated with ABA accumulation and the early auxin-responsive genes (Aux/IAA22 and GH3.9) were considerably suppressed during the period of massive fruit abscission. Similar changes in the expression of all genes occurred in the pedicel, except for NI and AP2/ERF, the expression of which was significantly upregulated during the early stage of fruit shedding and downregulated during the period of severe fruit drop. These results suggest that complicated crosstalk among the sugar, IAA, and ABA signaling may be related to macadamia fruitlet abscission induced by carbohydrate starvation

Flame response of solid propellant AP/Al/HTPB to a longitudinal acoustic wave

This paper is devoted to an experimental work which consists of the analysis of the flame of a small solid propellant sample, AP/Al/HTPB, subjected to a longitudinal acoustic wave. Experiments were conducted in a closed tube under two mean pressures: 1 and 2.5 MPa. The qualitative and quantitative analysis of the flame snapshots, using a microscope and a high-speed camera, revealed that the acoustic wave created at the end of the chamber by a pulser system strongly affects the flame and the combustion products dynamic above the solid propellant surface, namely, the flame and the hot products oscillate around a line perpendicular to the propellant surface. This dynamic of the hot gas disturbs the local burning rate and the regression surface profile. Thus, the thrust and the burning duration will change, therefore, the flight path of the rocket may shift and can lead to failure of the mission

Negative Impacts of School Class Segregation on Migrant Children’s Education Expectations and the Associated Mitigating Mechanism

This study thoroughly analyzes the impacts of school class segregation on the four dimensions of educational expectations of migrant children, and verifies the moderating effects of migrant children’s identification with the college entrance examination policy on the relationship between the two. A total of 1770 questionnaires were collected for this study. Through multiple regression analysis and moderating effect tests on the data, this study reveals that school class segregation has a significant negative impact on the educational expectations of migrant children; the migrant children’s identification with the college entrance examination policy also partially moderates the impacts of school class segregation on the academic achievement expectations and interpersonal expectations of migrant children. Informed by these results, this study proposes the following three mechanisms that can be used to mitigate the negative impacts of school class segregation on migrant children’s educational expectations: (a) an institutional mechanism involving the “unified urban–rural household registration”; (b) a cultural mechanism involving “promoting learning through examinations”; (c) a compensation mechanism involving the “principle of justice”. This paper provides a Chinese perspective on the issue of school class segregation by offering a policy reference for the improvement of the college entrance examination policy for migrant children and the reform of the household registration system

Graph attention network via node similarity for link prediction

Link prediction is a classic complex network analytical problem to predict the possible links according to the known network structure information. Considering similar nodes should present closer embedding vectors with network representation learning, in this paper, we propose a Graph ATtention network method based on node Similarity (SiGAT) for link prediction. Specifically, we calculate similar node set for each node in the network by traditional method. The similar nodes and first-order neighbors are assigned an optimal weight through the graph attention network mechanism. Then, we obtain the embedding vectors of nodes with aggregating the information of the similar nodes and first-order neighbor nodes. By incorporating similar nodes, the node embeddings preserve more structure information of the network in low-dimensional embedding space. Finally, the SiGAT represents the links between pairs of nodes with concatenating the node embedding vectors and then trains a classifier to predict novel potential network links. The results of experiments on five real datasets and large-scale artificial datasets, which are the Yeast dataset, Cora dataset, BIO-CE-HT dataset, Human proteins (Vidal) dataset, Human proteins (Stelzl) dataset, and LFR benchmark datasets, show that the SiGAT outperforms the existing popular approaches