Mitigating Semantic Confusion from Hostile Neighborhood for Graph Active Learning

Graph Active Learning (GAL), which aims to find the most informative nodes in graphs for annotation to maximize the Graph Neural Networks (GNNs) performance, has attracted many research efforts but remains non-trivial challenges. One major challenge is that existing GAL strategies may introduce semantic confusion to the selected training set, particularly when graphs are noisy. Specifically, most existing methods assume all aggregating features to be helpful, ignoring the semantically negative effect between inter-class edges under the message-passing mechanism. In this work, we present Semantic-aware Active learning framework for Graphs (SAG) to mitigate the semantic confusion problem. Pairwise similarities and dissimilarities of nodes with semantic features are introduced to jointly evaluate the node influence. A new prototype-based criterion and query policy are also designed to maintain diversity and class balance of the selected nodes, respectively. Extensive experiments on the public benchmark graphs and a real-world financial dataset demonstrate that SAG significantly improves node classification performances and consistently outperforms previous methods. Moreover, comprehensive analysis and ablation study also verify the effectiveness of the proposed framework.Comment: Accepted by CIKM 202

Intracellular ROS Mediates Gas Plasma-Facilitated Cellular Transfection in 2D and 3D Cultures

This study reports the potential of cold atmospheric plasma (CAP) as a versatile tool for delivering oligonucleotides into mammalian cells. Compared to lipofection and electroporation methods, plasma transfection showed a better uptake efficiency and less cell death in the transfection of oligonucleotides. We demonstrated that the level of extracellular aqueous reactive oxygen species (ROS) produced by gas plasma is correlated with the uptake efficiency and that this is achieved through an increase of intracellular ROS levels and the resulting increase in cell membrane permeability. This finding was supported by the use of ROS scavengers, which reduced CAP-based uptake efficiency. In addition, we found that cold atmospheric plasma could transfer oligonucleotides such as siRNA and miRNA into cells even in 3D cultures, thus suggesting the potential for unique applications of CAP beyond those provided by standard transfection techniques. Together, our results suggest that cold plasma might provide an efficient technique for the delivery of siRNA and miRNA in 2D and 3D culture models

Alteration of Metabolite Profiling by Cold Atmospheric Plasma Treatment in Human Myeloma Cells

BACKGROUND: Despite new progress of chemotherapy in multiple myeloma (MM) clinical treatment, MM is still a refractory disease and new technology is needed to improve the outcomes and prolong the survival. Cold atmospheric plasma is a rapidly developed technology in recent years, which has been widely applied in biomedicine. Although plasma could efficiently inactivate various tumor cells, the effects of plasma on tumor cell metabolism have not been studied yet. METHODS: In this study, we investigated the metabolite profiling of He plasma treatment on myeloma tumor cells by gas-chromatography time-of-flight (GC-TOF) mass-spectrometry. Meanwhile, by bioinformatic analysis such as GO and KEGG analysis we try to figure out the metabolism pathway that was significantly affected by gas plasma treatment. RESULTS: By GC-TOF mass-spectrometry, 573 signals were detected and evaluated using PCA and OPLS-DA. By KEGG analysis we listed all the differential metabolites and further classified into different metabolic pathways. The results showed that beta-alanine metabolism pathway was the most significant change after He gas plasma treatment in myeloma cells. Besides, propanoate metabolism and linoleic acid metabolism should also be concerned during gas plasma treatment of cancer cells. CONCLUSIONS: Cold atmospheric plasma treatment could significantly alter the metabolite profiling of myeloma tumor cells, among which, the beta-alanine metabolism pathway is the most susceptible to He gas plasma treatment. © The Author(s) 2018

Alteration of Metabolite Profiling by Cold Atmospheric Plasma Treatment in Human Myeloma Cells

BACKGROUND: Despite new progress of chemotherapy in multiple myeloma (MM) clinical treatment, MM is still a refractory disease and new technology is needed to improve the outcomes and prolong the survival. Cold atmospheric plasma is a rapidly developed technology in recent years, which has been widely applied in biomedicine. Although plasma could efficiently inactivate various tumor cells, the effects of plasma on tumor cell metabolism have not been studied yet. METHODS: In this study, we investigated the metabolite profiling of He plasma treatment on myeloma tumor cells by gas-chromatography time-of-flight (GC-TOF) mass-spectrometry. Meanwhile, by bioinformatic analysis such as GO and KEGG analysis we try to figure out the metabolism pathway that was significantly affected by gas plasma treatment. RESULTS: By GC-TOF mass-spectrometry, 573 signals were detected and evaluated using PCA and OPLS-DA. By KEGG analysis we listed all the differential metabolites and further classified into different metabolic pathways. The results showed that beta-alanine metabolism pathway was the most significant change after He gas plasma treatment in myeloma cells. Besides, propanoate metabolism and linoleic acid metabolism should also be concerned during gas plasma treatment of cancer cells. CONCLUSIONS: Cold atmospheric plasma treatment could significantly alter the metabolite profiling of myeloma tumor cells, among which, the beta-alanine metabolism pathway is the most susceptible to He gas plasma treatment. © The Author(s) 2018

NO2- and NO3- Enhance Cold Atmospheric Plasma Induced Cancer Cell Death by Generation of ONOO-

Cold atmospheric plasma (CAP) is a rapidly developed technology that has been widely applied in biomedicine especially in cancer treatment. Due to the generation of various active species in plasma, CAP could induce various tumor cells death and showed a promising potential in cancer therapy. To enhance the biological effects of gas plasma, changing the discharging parameters is the most commonly used method, yet increasing discharging power will lead to a higher possibility of simultaneously damage surrounding tissues. In this study, by adding nontoxic concentration of additional nitrite and nitrate in the medium, we found that anti-tumor effect of CAP treatment was enhanced in the same discharging parameters. By microplate reader and cell flow cytometer we measured several extracellular and intracellular RONS and found that ONOO- was mostly correlated with the enhanced cancer cell killing effect. We proposed that more nitrogen supplies such as nitrite and nitrate could increase the production of RNS especially ONOO- and resulted in a better killing effect to cancer cells. Our results provided a new strategy to enhance the antitumor effect by plasma jet treatment without changing the discharging parameters. © 2018 Author(s)

Effect of Cold Atmospheric Plasma Treatment on the Metabolites of Human Leukemia Cells

Background Acute myeloid leukemia (AML) is a typically fatal malignancy and new drug and treatment need to be developed for a better survival outcome. Cold atmospheric plasma (CAP) is a novel technology, which has been widely applied in biomedicine, especially in various of cancer treatment. However, the changes in cell metabolism after CAP treatment of leukemia cells have been rarely studied. Methods In this study, we investigated the metabolite profiling of plasma treatment on leukemia cells based on Gas Chromatography Tandem Time-of-Flight Mass Spectrometry (GC-TOFMS). Simultaneously, we conducted a series of bioinformatics analysis of metabolites and metabolic pathways with significant differences after basic data analysis. Results 800 signals were detected by GC-TOF mass-spectrometry and then evaluated using PCA and OPLS-DA. All the differential metabolites were listed and the related metabolic pathways were analyzed by KEGG pathway. The results showed that alanine, aspartate and glutamate metabolism had a significant change after plasma treatment. Meanwhile, d-glutamine and d-glutamate metabolism were significantly changed by CAP. Glutaminase activity was decreased after plasma treatment, which might lead to glutamine accumulation and leukemia cells death. Conclusions We found the above two metabolic pathways vulnerable to plasma treatment, which might result in leukemia cells death and might be the cornerstone of further exploration of plasma treatment targets

Shufeng Jiedu Capsules Alleviate Lipopolysaccharide-Induced Acute Lung Inflammatory Injury via Activation of GPR18 by Verbenalin

Background/Aims: Acute respiratory tract infection (ARTI) is the most common reason for outpatient physician office visits. Although powerful and significant in the treatment of infections, antibiotics used for ARTI inappropriately have been an important contributor to antibiotic resistance. We previously reported that Shufeng Jiedu Capsule (SJC) can effectively amplify anti-inflammatory signaling during infection. In this study, we aimed to systematically explore its composition and the mechanism of its effects in ARTI. Methods: Pseudomonas aeruginosa (PAK) strain was used to generate a mouse model of ARTI, which were then treated with different drugs or compounds to determine the corresponding anti-inflammatory roles. High-performance liquid chromatography-quadrupole time of flight-tandem mass spectrometry. was conducted to detect the chemical compounds in SJC. RNAs from the lung tissues of mice were prepared for microarray analysis to reveal globally altered genes and the pathways involved after SJC treatment. Results: SJC significantly inhibited the expression and secretion of inflammatory factors from PAK-induced mouse lung tissues or lipopolysaccharide-induced peritoneal macrophages. Verbenalin, one of the bioactive compounds identified in SJC, also showed notable anti-inflammatory effects. Microarray data revealed numerous differentially expressed genes among the different treatment groups; here, we focused on studying the role of GPR18. We found that the anti-inflammatory role of verbenalin was attenuated in GPR18 knockout mice compared with wild-type mice, although no statistically significant difference was observed in the untreated PAK-induced mice types. Conclusion: Our data not only showed the chemical composition of SJC, but also demonstrated that verbenalin was a significant anti-inflammatory compound, which may function through GPR18

Model-enhanced Vector Index

Embedding-based retrieval methods construct vector indices to search for document representations that are most similar to the query representations. They are widely used in document retrieval due to low latency and decent recall performance. Recent research indicates that deep retrieval solutions offer better model quality, but are hindered by unacceptable serving latency and the inability to support document updates. In this paper, we aim to enhance the vector index with end-to-end deep generative models, leveraging the differentiable advantages of deep retrieval models while maintaining desirable serving efficiency. We propose Model-enhanced Vector Index (MEVI), a differentiable model-enhanced index empowered by a twin-tower representation model. MEVI leverages a Residual Quantization (RQ) codebook to bridge the sequence-to-sequence deep retrieval and embedding-based models. To substantially reduce the inference time, instead of decoding the unique document ids in long sequential steps, we first generate some semantic virtual cluster ids of candidate documents in a small number of steps, and then leverage the well-adapted embedding vectors to further perform a fine-grained search for the relevant documents in the candidate virtual clusters. We empirically show that our model achieves better performance on the commonly used academic benchmarks MSMARCO Passage and Natural Questions, with comparable serving latency to dense retrieval solutions