Explainability in Graph Neural Networks

Deep neural networks have been predominant in AI applications during the past decade. Inspired by the success of deep learning in image and text domains, graph neural networks (GNNs) have been extensively developed for graphs in various applications. There are various topics in the current study for GNNs that have raised a great interest in the research community. In this thesis, we mainly focus on two of them, explainability and semi-supervised learning for GNNs. Semi-supervised learning is a major task for GNNs and exploring the explainability of GNNs helps us to understand these models better, which also benifits GNN based semi-supervised learning. The first problem is the explainability of GNNs. Similar to all other neural network based models, GNNs suffer from the black-box problem as people cannot understand the mechanism underlying them. To solve this problem, several GNN explainability methods have been proposed to explain the decisions made by GNNs. We conducted comprehensive experimental studies of the state-of-the-art GNN explainability methods based on the existing evaluation metrics. Furthermore, we proposed a new evaluation metric and benchmark the existing GNN explainability with our proposed novel metric on real-world datasets. The second problem is the semi-supervised learning for GNNs. A majority of GNNs studies focus on semi-supervised learning due to the challenge of labeled data shortage in graph-based tasks. To address this challenge, Graph Neural Networks (GNNs) use message passing frameworks to combine information from unlabeled data with labeled data. However, the use of unlabeled data under the message passing framework is indirect in the training process where unlabeled data does not supervise the training process. To tackle this problem, we propose a novel dual-view cooperative training framework, which allows the unlabeled data to directly supervise the training process. We further use a GNN explainability method to justify our framework and provide theoretical analysis

Permafrost Active Layer Microbes From Ny Ålesund, Svalbard (79°N) Show Autotrophic and Heterotrophic Metabolisms With Diverse Carbon-Degrading Enzymes

The active layer of permafrost in Ny Ålesund, Svalbard (79°N) around the Bayelva River in the Leirhaugen glacier moraine is measured as a small net carbon sink at the brink of becoming a carbon source. In many permafrost-dominating ecosystems, microbes in the active layers have been shown to drive organic matter degradation and greenhouse gas production, creating positive feedback on climate change. However, the microbial metabolisms linking the environmental geochemical processes and the populations that perform them have not been fully characterized. In this paper, we present geochemical, enzymatic, and isotopic data paired with 10 Pseudomonas sp. cultures and metagenomic libraries of two active layer soil cores (BPF1 and BPF2) from Ny Ålesund, Svalbard, (79°N). Relative to BPF1, BPF2 had statistically higher C/N ratios (15 ± 1 for BPF1 vs. 29 ± 10 for BPF2; n = 30, p < 10–5), statistically lower organic carbon (2% ± 0.6% for BPF1 vs. 1.6% ± 0.4% for BPF2, p < 0.02), statistically lower nitrogen (0.1% ± 0.03% for BPF1 vs. 0.07% ± 0.02% for BPF2, p < 10–6). The d13C values for inorganic carbon did not correlate with those of organic carbon in BPF2, suggesting lower heterotrophic respiration. An increase in the δ13C of inorganic carbon with depth either reflects an autotrophic signal or mixing between a heterotrophic source at the surface and a lithotrophic source at depth. Potential enzyme activity of xylosidase and N-acetyl-β-D-glucosaminidase increases twofold at 15°C, relative to 25°C, indicating cold adaptation in the cultures and bulk soil. Potential enzyme activity of leucine aminopeptidase across soils and cultures was two orders of magnitude higher than other tested enzymes, implying that organisms use leucine as a nitrogen and carbon source in this nutrient-limited environment. Besides demonstrating large variability in carbon compositions of permafrost active layer soils only ∼84 m apart, results suggest that the Svalbard active layer microbes are often limited by organic carbon or nitrogen availability and have adaptations to the current environment, and metabolic flexibility to adapt to the warming climate.Peer Reviewe

Hypericum japonicum extract inhibited porcine epidemic diarrhea virus in vitro and in vivo

Porcine epidemic diarrhea virus (PEDV) infection causes lethal watery diarrhea and high mortality in neonatal piglets, leading to huge economic losses in the global swine industry. Currently, the existing commercial vaccines cannot fully control PEDV, so it is urgent to develop effective antiviral agents to complement vaccine therapy. In the present study, we investigated the antiviral effect of Hypericum japonicum extract (HJ) against PEDV in vivo and in vitro. In in vitro assays, HJ could directly inactivate PEDV strains; moreover, it inhibited the proliferation of PEDV strains in Vero or IPI-FX cells at its non-cytotoxic concentrations. Time of addition assays revealed that HJ mainly inhibited PEDV at the later stages of the viral life cycle. In in vivo, compared with the model group, HJ could reduce the viral titers in the intestines of infected piglets, and improve their intestinal pathological, indicating that HJ could protect the newborn piglets from highly pathogenic PEDV variant infection. Furthermore, this effect may be related to the fact that HJ can not only directly inhibit viruses, but also regulate the structure of intestinal microbiota. In conclusion, our results indicate that Hypericum japonicum could inhibit PEDV replication in vitro and in vivo and might possess the potential to develop as the anti-PEDV drug

Naringenin suppresses BEAS-2B-derived extracellular vesicular cargoes disorder caused by cigarette smoke extract thereby inhibiting M1 macrophage polarization

Extracellular vesicles (EVs)-mediated epithelium-macrophage crosstalk has been proved to maintain lung homeostasis in cigarette smoke-induced lung diseases such as chronic obstructive pulmonary disease (COPD). In our previous study, we found that EVs derived from cigarette smoke extract (CSE) treated BEAS-2B promoted M1 macrophage polarization, which probably accelerated the development of inflammatory responses. Naringenin has been proved to suppress M1 macrophage polarization, but whether naringenin regulates macrophage polarization mediated by EVs has not been reported. In this study, we firstly found that EVs derived from naringenin and CSE co-treated BEAS-2B significantly inhibited the expression of CD86 and CD80 and the secretion of tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-1β, inducible nitric oxide synthase (iNOS), and IL-12 in macrophage induced by EVs derived from CSE-treated BEAS-2B. Further research revealed that naringenin downregulated BEAS-2B-derived EVs miR-21-3p which targeted phosphatase and tensin homolog deleted on chromosome ten/protein kinase B (PTEN/AKT) cascade in macrophages and then suppressed M1 macrophage polarization. Subsequent proteomics suggested that naringenin decreased BEAS-2B-derived EVs poly ADP-ribose polymerase (PARP)1 expression thereby suppressing M1 macrophage polarization probably. Our study provides novel pharmacological references for the mechanism of naringenin in the treatment of cigarette smoke-induced lung inflammatory diseases

Correlations among the plasma concentrations of first-line anti-tuberculosis drugs and the physiological parameters influencing concentrations

Background: The plasma concentrations of the four most commonly used first-line anti-tuberculosis (TB) drugs, isoniazid (INH), rifampicin (RMP), ethambutol (EMB), and pyrazinamide (PZA), are often not within the therapeutic range. Insufficient drug exposure could lead to drug resistance and treatment failure, while excessive drug levels may lead to adverse reactions. The purpose of this study was to identify the physiological parameters influencing anti-TB drug concentrations.Methods: A retrospective cohort study was conducted. The 2-h plasma concentrations of the four drugs were measured by using the high-performance liquid chromatography-tandem mass spectrometry method.Results: A total of 317 patients were included in the study. The proportions of patients with INH, RMP, EMB, and PZA concentrations within the therapeutic range were 24.3%, 31.5%, 27.8%, and 18.6%, respectively. There were positive associations between the concentrations of INH and PZA and RMP and EMB, but negative associations were observed between the concentrations of INH and RMP, INH and EMB, RMP and PZA, and EMB and PZA. In the multivariate analysis, the influencing factors of the INH concentration were the PZA concentration, total bile acid (TBA), serum potassium, dose, direct bilirubin, prealbumin (PA), and albumin; those of the RMP concentration were PZA and EMB concentrations, weight, α-l-fucosidase (AFU), drinking, and dose; those of the EMB concentration were the RMP and PZA concentrations, creatinine, TBA and indirect bilirubin; and those of the PZA concentration were INH, RMP and EMB concentrations, sex, weight, uric acid and drinking.Conclusion: The complex correlations between the concentrations of the four first-line anti-TB drugs lead to a major challenge in dose adjustment to maintain all drugs within the therapeutic window. Levels of TBA, PA, AFU, and serum potassium should also be considered when adjusting the dose of the four drugs

Impact of Steel Fiber Volume Fraction and Morphology on the Strength of Recycled Aggregate Concrete

Steel-fiber-reinforced recycled coarse aggregate concrete (SFRCAC) has great potential for use in structural members due to environmental and economic reasons. A comparison of SF’s reinforcing effect on the strength of RCAC with natural recycled coarse aggregate concrete (NCAC) was conducted through experiments and analysis. Three types of steel fiber—milling (MF), shear-wave (SWF), and both-end hooked (BF)—were used. The SF volume fraction (Vf) was taken as 0, 0.5%, 1.0%, 1.5%, and 2%. The results show that SF has a similar reinforcing effect on NCAC and RCAC. The reinforcing effect of SF on the strength of RCAC is relevant to the strength of the RCAC matrix. The suitable content range of SF is from 0.5% to 1.5% in terms of the reinforcement effects on the compressive strength (ffcu) and splitting tensile strength (ffts) of RCAC. SF with a higher aspect ratio (AR) has a better reinforcing effect on the splitting tensile strength (ffts) and flexural strength (fftm) of RCAC. The equations of ffts/fts and fftm/ftm with the characteristic parameters of steel fiber (λf) were put forward to accurately determine the dosage of SF