LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation

Recent works have demonstrated the benefits of capturing long-distance dependency in graphs by deeper graph neural networks (GNNs). But deeper GNNs suffer from the long-lasting scalability challenge due to the neighborhood explosion problem in large-scale graphs. In this work, we propose to capture long-distance dependency in graphs by shallower models instead of deeper models, which leads to a much more efficient model, LazyGNN, for graph representation learning. Moreover, we demonstrate that LazyGNN is compatible with existing scalable approaches (such as sampling methods) for further accelerations through the development of mini-batch LazyGNN. Comprehensive experiments demonstrate its superior prediction performance and scalability on large-scale benchmarks. The implementation of LazyGNN is available at https://github.com/RXPHD/Lazy_GNN

Parameter-Efficient Conformers via Sharing Sparsely-Gated Experts for End-to-End Speech Recognition

While transformers and their variant conformers show promising performance in speech recognition, the parameterized property leads to much memory cost during training and inference. Some works use cross-layer weight-sharing to reduce the parameters of the model. However, the inevitable loss of capacity harms the model performance. To address this issue, this paper proposes a parameter-efficient conformer via sharing sparsely-gated experts. Specifically, we use sparsely-gated mixture-of-experts (MoE) to extend the capacity of a conformer block without increasing computation. Then, the parameters of the grouped conformer blocks are shared so that the number of parameters is reduced. Next, to ensure the shared blocks with the flexibility of adapting representations at different levels, we design the MoE routers and normalization individually. Moreover, we use knowledge distillation to further improve the performance. Experimental results show that the proposed model achieves competitive performance with 1/3 of the parameters of the encoder, compared with the full-parameter model.Comment: accepted in INTERSPEECH 202

Lipid alternations in the plasma of COVID-19 patients with various clinical presentations.

BACKGROUND: COVID-19 is a highly infectious respiratory disease that can manifest in various clinical presentations. Although many studies have reported the lipidomic signature of COVID-19, the molecular changes in asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected individuals remain elusive. METHODS: This study combined a comprehensive lipidomic analysis of 220 plasma samples from 166 subjects: 62 healthy controls, 16 asymptomatic infections, and 88 COVID-19 patients. We quantified 732 lipids separately in this cohort. We performed a difference analysis, validated with machine learning models, and also performed GO and KEGG pathway enrichment analysis using differential lipids from different control groups. RESULTS: We found 175 differentially expressed lipids associated with SASR-CoV-2 infection, disease severity, and viral persistence in patients with COVID-19. PC (O-20:1/20:1), PC (O-20:1/20:0), and PC (O-18:0/18:1) better distinguished asymptomatic infected individuals from normal individuals. Furthermore, some patients tested positive for SARS-CoV-2 nucleic acid by RT-PCR but did not become negative for a longer period of time (≥60 days, designated here as long-term nucleic acid test positive, LTNP), whereas other patients became negative for viral nucleic acid in a shorter period of time (≤45 days, designated as short-term nucleic acid test positive, STNP). We have found that TG (14:1/14:1/18:2) and FFA (4:0) were differentially expressed in LTNP and STNP. CONCLUSION: In summary, the integration of lipid information can help us discover novel biomarkers to identify asymptomatic individuals and further deepen our understanding of the molecular pathogenesis of COVID-19

Prioritization of control factors for heavy metals in groundwater based on a source-oriented health risk assessment model

Heavy metals (HMs) in groundwater seriously threaten ecological safety and human health. To facilitate the effective management of groundwater contamination, priority control factors of HMs in groundwater need to be categorized. A total of 86 groundwater samples were collected from the Huangpi district of Wuhan city, China, during the dry and wet seasons. To determine priority control factors, a source-oriented health risk assessment model was applied to compare the pollution sources and health risks of seven HMs (Cu, Pb, Zn, Cr, Ni, As, and Fe). The results showed that the groundwater had higher As and Fe contents. The sources of HM pollution during the wet period were mainly industrial and agricultural activities and natural sources. During the dry period, origins were more complex due to the addition of domestic discharges, such as sewage wastewater. Industrial activities (74.10% during the wet period), agricultural activities (53.84% during the dry period), and As were identified as the priority control factors for groundwater HMs. The results provide valuable insights for policymakers to coordinate targeted management of HM pollution in groundwater and reduce the cost of HM pollution mitigation

Research on the Effect of Heat Pipe Inclination Angle on Temperature Distribution in Electrical Machines

Due to high equivalent thermal conductivity with lightweight and small size, heat pipes (HPs) are being extensively applied in the motor cooling system to improve its thermal performance. However, when practically installed in electrical machines, the inclination angle of the HP will affect its thermal conductivity and motor temperature distribution as well, which is still unclear. This article intends to figure out the effects of HP inclination angle on motor temperature distribution via both theoretical and experimental investigation. Based on the theoretical analysis of the HP inclination effect, the equivalent thermal conductivity of the HP with different inclination angles from 0° to 180° is experimentally investigated on a dedicated platform. Then, temperature distribution across a full-size stator-winding assembly with HPs is quantitatively studied using an established thermal model. Finally, the thermal simulation results are experimentally verified by testing on a processed specimen. The results indicate that the HP thermal performance degrades by over 80% with the inclination angle from 0° to 180°, which results in a significant temperature nonuniformity across the motor under liquid cooling conditions

Fibroblast Growth Factor Signaling Mediates Pulmonary Endothelial Glycocalyx Reconstitution

The endothelial glycocalyx is a heparan sulfate (HS)-rich endovascular structure critical to endothelial function. Accordingly, endothelial glycocalyx degradation during sepsis contributes to tissue edema and organ injury. We determined the endogenous mechanisms governing pulmonary endothelial glycocalyx reconstitution, and if these reparative mechanisms are impaired during sepsis. We performed intravital microscopy of wild-type and transgenic mice to determine the rapidity of pulmonary endothelial glycocalyx reconstitution after nonseptic (heparinase-III mediated) or septic (cecal ligation and puncture mediated) endothelial glycocalyx degradation. We used mass spectrometry, surface plasmon resonance, and in vitro studies of human and mouse samples to determine the structure of HS fragments released during glycocalyx degradation and their impact on fibroblast growth factor receptor (FGFR) 1 signaling, a mediator of endothelial repair. Homeostatic pulmonary endothelial glycocalyx reconstitution occurred rapidly after nonseptic degradation and was associated with induction of the HS biosynthetic enzyme, exostosin (EXT)-1. In contrast, sepsis was characterized by loss of pulmonary EXT1 expression and delayed glycocalyx reconstitution. Rapid glycocalyx recovery after nonseptic degradation was dependent upon induction of FGFR1 expression and was augmented by FGF-promoting effects of circulating HS fragments released during glycocalyx degradation. Although sepsis-released HS fragments maintained this ability to activate FGFR1, sepsis was associated with the downstream absence of reparative pulmonary endothelial FGFR1 induction. Sepsis may cause vascular injury not only via glycocalyx degradation, but also by impairing FGFR1/EXT1-mediated glycocalyx reconstitution

Distinct miRNAs associated with various clinical presentations of SARS-CoV-2 infection.

MicroRNAs (miRNAs) have been shown to play important roles in viral infections, but their associations with SARS-CoV-2 infection remain poorly understood. Here, we detected 85 differentially expressed miRNAs (DE-miRNAs) from 2,336 known and 361 novel miRNAs that were identified in 233 plasma samples from 61 healthy controls and 116 patients with COVID-19 using the high-throughput sequencing and computational analysis. These DE-miRNAs were associated with SASR-CoV-2 infection, disease severity, and viral persistence in the patients with COVID-19, respectively. Gene ontology and KEGG pathway analyses of the DE-miRNAs revealed their connections to viral infections, immune responses, and lung diseases. Finally, we established a machine learning model using the DE-miRNAs between various groups for classification of COVID-19 cases with different clinical presentations. Our findings may help understand the contribution of miRNAs to the pathogenesis of COVID-19 and identify potential biomarkers and molecular targets for diagnosis and treatment of SARS-CoV-2 infection

Neuronal Calcium Sensor Synaptotagmin-9 Is Not Involved in the Regulation of Glucose Homeostasis or Insulin Secretion

BACKGROUND:Insulin secretion is a complex and highly regulated process. It is well established that cytoplasmic calcium is a key regulator of insulin secretion, but how elevated intracellular calcium triggers insulin granule exocytosis remains unclear, and we have only begun to define the identities of proteins that are responsible for sensing calcium changes and for transmitting the calcium signal to release machineries. Synaptotagmins are primarily expressed in brain and endocrine cells and exhibit diverse calcium binding properties. Synaptotagmin-1, -2 and -9 are calcium sensors for fast neurotransmitter release in respective brain regions, while synaptotagmin-7 is a positive regulator of calcium-dependent insulin release. Unlike the three neuronal calcium sensors, whose deletion abolished fast neurotransmitter release, synaptotagmin-7 deletion resulted in only partial loss of calcium-dependent insulin secretion, thus suggesting that other calcium-sensors must participate in the regulation of insulin secretion. Of the other synaptotagmin isoforms that are present in pancreatic islets, the neuronal calcium sensor synaptotagmin-9 is expressed at the highest level after synaptotagmin-7. METHODOLOGY/PRINCIPAL FINDINGS:In this study we tested whether synaptotagmin-9 participates in the regulation of glucose-stimulated insulin release by using pancreas-specific synaptotagmin-9 knockout (p-S9X) mice. Deletion of synaptotagmin-9 in the pancreas resulted in no changes in glucose homeostasis or body weight. Glucose tolerance, and insulin secretion in vivo and from isolated islets were not affected in the p-S9X mice. Single-cell capacitance measurements showed no difference in insulin granule exocytosis between p-S9X and control mice. CONCLUSIONS:Thus, synaptotagmin-9, although a major calcium sensor in the brain, is not involved in the regulation of glucose-stimulated insulin release from pancreatic β-cells