104 research outputs found

    Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Weighted Negative Samples

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    Heterogeneous graph contrastive learning has received wide attention recently. Some existing methods use meta-paths, which are sequences of object types that capture semantic relationships between objects, to construct contrastive views. However, most of them ignore the rich meta-path context information that describes how two objects are connected by meta-paths. On the other hand, they fail to distinguish hard negatives from false negatives, which could adversely affect the model performance. To address the problems, we propose MEOW, a heterogeneous graph contrastive learning model that considers both meta-path contexts and weighted negative samples. Specifically, MEOW constructs a coarse view and a fine-grained view for contrast. The former reflects which objects are connected by meta-paths, while the latter uses meta-path contexts and characterizes the details on how the objects are connected. We take node embeddings in the coarse view as anchors, and construct positive and negative samples from the fine-grained view. Further, to distinguish hard negatives from false negatives, we learn weights of negative samples based on node clustering. We also use prototypical contrastive learning to pull close embeddings of nodes in the same cluster. Finally, we conduct extensive experiments to show the superiority of MEOW against other state-of-the-art methods.Comment: Accepted by SDM 202

    An extremely bad-cavity laser

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    Lasing in the bad-cavity regime has promising applications in precision measurement and frequency metrology due to the reduced sensitivity of the laser frequency to cavity length fluctuations. Thus far, relevant studies have been mainly focused on conventional cavities whose finesse is high enough that the resonance linewidth is sufficiently narrow compared to the cavity's free spectral range, though still in the bad-cavity regime. However, lasing output from the cavity whose finesse is close to the limit of 2 has never been experimentally accessed. Here, we demonstrate an extremely bad-cavity laser, analyze the physical mechanisms limiting cavity finesse, and report on the worst ever laser cavity with finesse reaching 2.01. The optical cavity has a reflectance close to zero and only provides a weak optical feedback. The laser power can be as high as tens of μ\muW and the spectral linewidth reaches a few kHz, over one thousand times narrower than the gain bandwidth. In addition, the measurement of cavity pulling reveals a pulling coefficient of 0.0148, the lowest value ever achieved for a continuous wave laser. Our findings open up an unprecedentedly innovative perspective for future new ultra-stable lasers, which could possibly trigger the future discoveries in optical clocks, cavity QED, continuous wave superradiant laser, and explorations of quantum manybody physics

    Self-supervised Heterogeneous Graph Variational Autoencoders

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    Heterogeneous Information Networks (HINs), which consist of various types of nodes and edges, have recently demonstrated excellent performance in graph mining. However, most existing heterogeneous graph neural networks (HGNNs) ignore the problems of missing attributes, inaccurate attributes and scarce labels for nodes, which limits their expressiveness. In this paper, we propose a generative self-supervised model SHAVA to address these issues simultaneously. Specifically, SHAVA first initializes all the nodes in the graph with a low-dimensional representation matrix. After that, based on the variational graph autoencoder framework, SHAVA learns both node-level and attribute-level embeddings in the encoder, which can provide fine-grained semantic information to construct node attributes. In the decoder, SHAVA reconstructs both links and attributes. Instead of directly reconstructing raw features for attributed nodes, SHAVA generates the initial low-dimensional representation matrix for all the nodes, based on which raw features of attributed nodes are further reconstructed to leverage accurate attributes. In this way, SHAVA can not only complete informative features for non-attributed nodes, but rectify inaccurate ones for attributed nodes. Finally, we conduct extensive experiments to show the superiority of SHAVA in tackling HINs with missing and inaccurate attributes

    Long-term outcomes of infantile spasms in children treated with ketogenic diet therapy in combination with anti-seizure medications in a resource-limited region

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    ObjectiveDespite numerous guidelines, the overall outcome of infantile spasms is poor, with only a small number of patients being able to attend school. The purpose of this study was to investigate long-term outcomes. Patients had poor access to the recommended first-line anti-seizure medications (ASMs), such as hormones (corticotropin or prednisolone/prednisone) and vigabatrin, and their alternative treatment was other ASMs and a ketogenic diet.MethodsPatients suffering from infantile spasms who had at least 2 years of medical records in the electronic medical record system between January 2014 and August 2022 were included in this study. Patient information was retrospectively reviewed. All patients had received ketogenic diet therapy (mainly classical ketogenic diet therapy). The ketogenic diet therapy was combined with ASMs not used as first-line therapies. The primary endpoint outcome measure was the number of patients with seizure freedom. The secondary measures included the duration of ketogenic diet therapy, choice of ASMs, and patient development at the last visit.ResultsA total of 177 patients with infantile spasms were included, and 152 (86%) of them had seizure freedom. The median duration from the first to the last hospital visit was 53.27 months, and the number of visits was 47.00. The median age at the initial hospital visit was 8.00 months, and the median age at initiation of the ketogenic diet was 17.73 months. At the last visit, the proportions of patients with neurodevelopmental delay, developmental epileptic encephalopathy, drug-resistant epilepsy, and generalized seizures increased significantly. The frequently used ASMs were topiramate, valproic acid, levetiracetam, nitrazepam, and vitamin B6 injection, while the recommended first-line drugs corticotropin and vigabatrin were rarely selected. The study duration of 9.5 years was divided into three periods but the prescription of ASMs did not change significantly between these periods.ConclusionsAlthough the seizure freedom rate was high with ketogenic diet therapy combined with non-standard ASMs, the patients had a significant neurodevelopmental delay at the last visit, which was, however, similar to that of standard treatment. To improve the outcomes of infantile spasms, multicenter clinical trials of the ketogenic diet as a first-line treatment in combination with non-standard ASMs are needed

    Synthesis of a Dual Functional Anti-MDR Tumor Agent PH II-7 with Elucidations of Anti-Tumor Effects and Mechanisms

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    Multidrug resistance mediated by P-glycoprotein in cancer cells has been a major issue that cripples the efficacy of chemotherapy agents. Aimed for improved efficacy against resistant cancer cells, we designed and synthesized 25 oxindole derivatives based on indirubin by structure-activity relationship analysis. The most potent one was named PH II-7, which was effective against 18 cancer cell lines and 5 resistant cell lines in MTT assay. It also significantly inhibited the resistant xenograft tumor growth in mouse model. In cell cycle assay and apoptosis assay conducted with flow cytometry, PH II-7 induced S phase cell cycle arrest and apoptosis even in resistant cells. Consistently revealed by real-time PCR, it modulates the expression of genes related to the cell cycle and apoptosis in these cells, which may contributes to its efficacy against them. By side-chain modification and FITC-labeling of PH II-7, we were able to show with confocal microscopy that not only it was not pumped by P-glycoprotein, it also attenuated the efflux of Adriamycin by P-glycoprotein in MDR tumor cells. Real-time PCR and western blot analysis showed that PH II-7 down-regulated MDR1 gene via protein kinase C alpha (PKCA) pathway, with c-FOS and c-JUN as possible mediators. Taken together, PH II-7 is a dual-functional compound that features both the cytotoxicity against cancer cells and the inhibitory effect on P-gp mediated drug efflux

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data