Heterogeneous Graph Embedding with Dual Edge Differentiation.

Recently, heterogeneous graphs have attracted widespread attention as a powerful and practical superclass of traditional homogeneous graphs, which reflect the multi-type node entities and edge relations in the real world. Most existing methods adopt meta-path construction as the mainstream to learn long-range heterogeneous semantic messages between nodes. However, such schema constructs the node-wise correlation by connecting nodes via pre-computed fixed paths, which neglects the diversities of meta-paths on the path type and path range.

1,25(OH)2D3 promotes insulin secretion through the classical pyroptosis pathway in vitro and vivo.

Background: Diabetes is a chronic metabolic disorder characterized by persistently elevated levels of blood glucose. Research has demonstrated a close relationship between inflammation and the development of diabetes. Vitamin D has been shown to be significantly associated with type 2 diabetes; however, the mechanisms by which it regulates inflammation during the onset of the disease remain incompletely understood.

Concurrently Probing the Mechanical and Electrical Characteristics of Living Cells via an Integrated Microdevice.

The mechanical and electrical properties of cells serve as critical indicators of their physiological and pathological state. Currently, distinct setups are required to measure the electrical and mechanical responses of cells. In addition, most existing methods such as optical trapping (OT) and atomic force microscopy (AFM) are labor-intensive, expensive, and low-throughput.

Deciphering the role of nonylphenol adsorption in soil by microplastics with different polarities and ageing processes.

In the soil environment, microplastics (MPs) commonly coexist with organic pollutants such as nonylphenol (NP), affecting the migration of NP through adsorption/desorption. However, few studies have focused on the interaction between NP and MPs in soil, especially for MPs of different types and ageing characteristics. In this study, non-polar polypropylene (PP) and polar polyamide (PA) MPs were aged either photochemically (144 h) or within soil (60 days), then used to determine the effect of 5 % MPs on the adsorption behaviour of NP (0.

The Inhibition of Reactive Oxygen Species Modulator 1 Attenuates Sevoflurane-Induced Neural Injury via Reducing Apoptosis and Oxidative Stress.

Sevoflurane causes neural injury by promoting apoptosis and oxidative stress. Reactive oxygen species modulator 1 (ROMO1) regulates apoptosis and oxidative stress, while its role in sevoflurane-induced neural injury remains unclear. This study intended to investigate the effect of ROMO1 knockdown on viability, apoptosis, and oxidative stress in sevoflurane-treated HT22 cells and its downstream pathway.

Optimization of Selenization Condition for Efficiency CIGSe Solar Cells Based on Postselenization of CuInGa Precursors.

The degree of selenization of the CIGSe absorbers is controlled by regulating the parameters of the selenization reaction. The structure, element distribution, phase composition of the CIGSe absorbers, and the performances of the solar cells with different selenization degrees are studied. Insufficient selenization will lead to residual CuSe phase on the surface and insufficient Na diffusion, which will affect the V on the surface and the recombination at the front interface.

IRE1α-XBP1s axis regulates SREBP1-dependent MRP1 expression to promote chemoresistance in non-small cell lung cancer cells.

Background: Inositol-requiring enzyme 1 (IRE1) is an endoplasmic reticulum (ER)-resident transmembrane protein that senses ER stress and mediates an essential arm of the unfolded protein response (UPR). IRE1 reduces ER stress by upregulating the expression of multiple ER chaperones through activation of X-box-binding protein 1 (XBP1). Emerging lines of evidence have revealed that IRE1-XBP1 axis serves as a multipurpose signal transducer during oncogenic transformation and cancer development.

Spatial Continuity and Nonequal Importance in Salient Object Detection With Image-Category Supervision.

Due to the inefficiency of pixel-level annotations, weakly supervised salient object detection with image-category labels (WSSOD) has been receiving increasing attention. Previous works usually endeavor to generate high-quality pseudolabels to train the detectors in a fully supervised manner. However, we find that the detection performance is often limited by two types of noise contained in pseudolabels: 1) holes inside the object or at the edge and outliers in the background and 2) missing object portions and redundant surrounding regions.

Multi-view heterogeneous graph learning with compressed hypergraph neural networks.

Multi-view learning is an emerging field of multi-modal fusion, which involves representing a single instance using multiple heterogeneous features to improve compatibility prediction. However, existing graph-based multi-view learning approaches are implemented on homogeneous assumptions and pairwise relationships, which may not adequately capture the complex interactions among real-world instances. In this paper, we design a compressed hypergraph neural network from the perspective of multi-view heterogeneous graph learning.

Exploring the Mechanism of Asiatic Acid against Atherosclerosis Based on Molecular Docking, Molecular Dynamics, and Experimental Verification.

Asiatic acid (AA) is a pentacyclic triterpene derived from the traditional medicine . It is known for its anti-inflammatory, antioxidant, and lipid-regulating properties. Though previous studies have suggested its potential therapeutic benefits for atherosclerosis, its pharmacological mechanism is unclear.

Pancreatic STAT5 activation promotes Kras-induced and inflammation-induced acinar-to-ductal metaplasia and pancreatic cancer.

Objective: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy because it is often diagnosed at a late-stage. Signal transducer and activator of transcription 5 (STAT5) is a transcription factor implicated in the progression of various cancer types. However, its role in KRAS-driven pancreatic tumourigenesis remains unclear.

Heterogeneous graph convolutional network for multi-view semi-supervised classification.

This paper proposes a novel approach to semantic representation learning from multi-view datasets, distinct from most existing methodologies which typically handle single-view data individually, maintaining a shared semantic link across the multi-view data via a unified optimization process. Notably, even recent advancements, such as Co-GCN, continue to treat each view as an independent graph, subsequently aggregating the respective GCN representations to form output representations, which ignores the complex semantic interactions among heterogeneous data. To address the issue, we design a unified framework to connect multi-view data with heterogeneous graphs.

The mitochondrial stress-induced protein carboxyl-terminal alanine and threonine tailing (msiCAT-tailing) promotes glioblastoma tumorigenesis by modulating mitochondrial functions.

Unlabelled: The rapid and sustained proliferation in cancer cells requires accelerated protein synthesis. Accelerated protein synthesis and disordered cell metabolism in cancer cells greatly increase the risk of translation errors. ribosome-associated quality control (RQC) is a recently discovered mechanism for resolving ribosome collisions caused by frequent translation stalls.

Misclassification in Weakly Supervised Object Detection.

Weakly supervised object detection (WSOD) aims to train detectors using only image-category labels. Current methods typically first generate dense class-agnostic proposals and then select objects based on the classification scores of these proposals. These methods mainly focus on selecting the proposal having high Intersection-over-Union with the true object location, while ignoring the problem of misclassification, which occurs when some proposals exhibit semantic similarities with objects from other categories due to viewing perspective and background interference.

UMCGL: Universal Multi-View Consensus Graph Learning With Consistency and Diversity.

Existing multi-view graph learning methods often rely on consistent information for similar nodes within and across views, however they may lack adaptability when facing diversity challenges from noise, varied views, and complex data distributions. These challenges can be mainly categorized into: 1) View-specific diversity within intra-view from noise and incomplete information; 2) Cross-view diversity within inter-view caused by various latent semantics; 3) Cross-group diversity within inter-group due to data distribution differences. To this end, we propose a universal multi-view consensus graph learning framework that considers both original and generative graphs to balance consistency and diversity.

Upregulation of neuronal ER-phagy improves organismal fitness and alleviates APP toxicity.

ER-phagy, a selective autophagy targeting the endoplasmic reticulum (ER) for lysosomal degradation through cargo receptors, plays a critical role in ER quality control and is linked to various diseases. However, its physiological and pathological roles remain largely unclear due to a lack of animal model studies. This study establishes Drosophila as an in vivo ER-phagy model.

Identification of ClpB, a molecular chaperone involved in the stress tolerance and virulence of Streptococcus agalactiae.

Bacterial ClpB is an ATP-dependent disaggregate that belongs to the Hsp100/Clp family and facilitates bacterial survival under hostile environmental conditions. Streptococcus agalactiae, which is regarded as the major bacterial pathogen of farmed Nile tilapia (Oreochromis niloticus), is known to cause high mortality and large economic losses. Here, we report a ClpB homologue of S.

Multilayer regulatory landscape and new regulators identification for bud dormancy release and bud break in Populus.

For trees originating from boreal and temperate regions, the dormancy-to-active transition, also known as bud dormancy release and bud break, are crucial processes that allow trees to reactive growth in the spring. The molecular mechanisms underlying these two processes remain poorly understood. Here, through integrative multiomics analysis of the transcriptome, DNA methylome, and proteome, we gained insights into the reprogrammed cellular processes associated with bud dormancy release and bud break.

Fe-CGS Effectively Inhibits the Dynamic Migration and Transformation of Cadmium and Arsenic in Soil.

The iron-modified coal gasification slag (Fe-CGS) material has excellent performance in purifying heavy-metal-contaminated water due to its good surface properties and adsorption capacities. However, it is unclear whether it can provide long-term simultaneous stabilization of Cd and As in composite-contaminated soils in extreme environments. This study investigated the long-term stabilization of Cd and As in acidic (JLG) and alkaline (QD) soils by simulating prolonged heavy rainfall with the addition of Fe-CGS.

Unveiling unique alternative splicing responses to low temperature in Zoysia japonica through ZjRTD1.0, a high-quality reference transcript dataset.

Inadequate reference databases in RNA-seq analysis can hinder data utilization and interpretation. In this study, we have successfully constructed a high-quality reference transcript dataset, ZjRTD1.0, for Zoysia japonica, a widely-used turfgrass with exceptional tolerance to various abiotic stress, including low temperatures and salinity.