Electrochemical Investigation of Exchange Current Density of Uranium and Rare-earths Couples (M3+/M0) in LiCl-KCl Eutectic Electrolyte

The objective of this work is to use electrochemical techniques to quantify the electrode reaction rate of some rare-earth elements and uranium in a LiCl-KCl eutectic electrolyte at 500oC. The exchange current densities of the oxidation-reduction couples of M3+/M0 (La3+/La0, Ce3+/Ce0, Pr3+/Pr0, Nd3+/Nd0,Gd3+/Gd0, Y3+/Y0, U3+/U0) on a tungsten electrode were measured by applying a linear polarization resistance technique. A region of linear dependence of potential on applied current could be found to describe the reaction rate of oxidation-reduction system. From these measurements, the estimated exchange current density was 0.38 mA/cm2 for uranium, and was within the range of 0.27 to 0.38mA/cm2 for rare-earth elements.open0

Signal transducer and activator of transcription 3-mediated CD133 up-regulation contributes to promotion of hepatocellular carcinoma

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Polynomial-based Self-Attention for Table Representation learning

Structured data, which constitutes a significant portion of existing data types, has been a long-standing research topic in the field of machine learning. Various representation learning methods for tabular data have been proposed, ranging from encoder-decoder structures to Transformers. Among these, Transformer-based methods have achieved state-of-the-art performance not only in tabular data but also in various other fields, including computer vision and natural language processing. However, recent studies have revealed that self-attention, a key component of Transformers, can lead to an oversmoothing issue. We show that Transformers for tabular data also face this problem, and to address the problem, we propose a novel matrix polynomial-based self-attention layer as a substitute for the original self-attention layer, which enhances model scalability. In our experiments with three representative table learning models equipped with our proposed layer, we illustrate that the layer effectively mitigates the oversmoothing problem and enhances the representation performance of the existing methods, outperforming the state-of-the-art table representation methods

PANDA: Expanded Width-Aware Message Passing Beyond Rewiring

Recent research in the field of graph neural network (GNN) has identified a critical issue known as "over-squashing," resulting from the bottleneck phenomenon in graph structures, which impedes the propagation of long-range information. Prior works have proposed a variety of graph rewiring concepts that aim at optimizing the spatial or spectral properties of graphs to promote the signal propagation. However, such approaches inevitably deteriorate the original graph topology, which may lead to a distortion of information flow. To address this, we introduce an expanded width-aware (PANDA) message passing, a new message passing paradigm where nodes with high centrality, a potential source of over-squashing, are selectively expanded in width to encapsulate the growing influx of signals from distant nodes. Experimental results show that our method outperforms existing rewiring methods, suggesting that selectively expanding the hidden state of nodes can be a compelling alternative to graph rewiring for addressing the over-squashing.Comment: Accepted at ICML 202

Stochastic Sampling for Contrastive Views and Hard Negative Samples in Graph-based Collaborative Filtering

Graph-based collaborative filtering (CF) has emerged as a promising approach in recommendation systems. Despite its achievements, graph-based CF models face challenges due to data sparsity and negative sampling. In this paper, we propose a novel Stochastic sampling for i) COntrastive views and ii) hard NEgative samples (SCONE) to overcome these issues. By considering that they are both sampling tasks, we generate dynamic augmented views and diverse hard negative samples via our unified stochastic sampling framework based on score-based generative models. In our comprehensive evaluations with 6 benchmark datasets, our proposed SCONE significantly improves recommendation accuracy and robustness, and demonstrates the superiority of our approach over existing CF models. Furthermore, we prove the efficacy of user-item specific stochastic sampling for addressing the user sparsity and item popularity issues. The integration of the stochastic sampling and graph-based CF obtains the state-of-the-art in personalized recommendation systems, making significant strides in information-rich environments

Efficient gene deletion of Integrin alpha 4 in primary mouse CD4 T cells using CRISPR RNA pair-mediated fragmentation

The functional specialization of CD4 T lymphocytes into various subtypes, including TH1 and TFH cells, is crucial for effective immune responses. TFH cells facilitate B cell differentiation within germinal centers, while TH1 cells are vital for cell-mediated immunity against intracellular pathogens. Integrin α4, a cell surface adhesion molecule, plays significant roles in cell migration and co-stimulatory signaling. In this study, we investigated the role of Integrin α4 in regulating TFH and TH1 cell populations during acute viral infection using CRISPR-Cas9 gene editing. To effectively delete the Itga4 in primary mouse CD4 T cells, we selected various combinations of crRNAs and generated ribonucleoprotein complexes with fluorochrome-conjugated tracrRNAs and Cas9 proteins. These crRNA pairs enhanced gene deletion by generating deletions in the gene. By analyzing the effects of Itga4 deficiency on TFH and TH1 cell differentiation during acute LCMV infection, we found that optimized crRNA pairs significantly increased the TH1 cell population. Our results highlight the importance of selecting and combining appropriate crRNAs for effective CRISPR-Cas9 gene editing in primary CD4 T cells. Additionally, our study demonstrates the role of Integrin α4 in regulating the differentiation of CD4 T cells, suggesting the potential molecular mechanisms driving T cell subset differentiation through integrin targeting

Speciation of common Gram-negative pathogens using a highly multiplexed high resolution melt curve assay

The identification of the bacterial species responsible for an infection remains an important step for the selection of antimicrobial therapy. Gram-negative bacteria are an important source of hospital and community acquired infections and frequently antimicrobial resistant. Speciation of bacteria is typically carried out by biochemical profiling of organisms isolated from clinical specimens, which is time consuming and delays the initiation of tailored treatment. Whilst molecular methods such as PCR have been used, they often struggle with the challenge of detecting and discriminating a wide range of targets. High resolution melt analysis is an end-point qPCR detection method that provides greater multiplexing capability than probe based methods. Here we report the design of a high resolution melt analysis assay for the identification of six common Gram-negative pathogens; Escherichia coli, Klebsiella pneumoniae, Klebsiella oxytoca, Pseudomonas aeruginosa, Salmonella Sp, and Acinetobacter baumannii, and a generic Gram-negative specific 16S rRNA control. The assay was evaluated using a well characterised collection of 113 clinically isolated Gram-negative bacteria. The agreement between the HRM assay and the reference test of PCR and sequencing was 98.2% (Kappa 0.96); the overall sensitivity and specificity of the assay was 97.1% (95% CI: 90.1–99.7%) and 100% (95% CI: 91.78–100%) respectively

The role of cGAMP via the STING pathway in modulating germinal center responses and CD4 T cell differentiation

Germinal center (GC) responses are essential for establishing protective, long-lasting immunity through the differentiation of GC B cells (BGC) and plasma cells (BPC), along with the generation of antigen-specific antibodies. Among the various pathways influencing immune responses, the STING (Stimulator of Interferon Genes) pathway has emerged as significant, especially in innate immunity, and extends its influence to adaptive responses. In this study, we examined how the STING ligand cGAMP can modulate these key elements of the adaptive immune response, particularly in enhancing GC reactions and the differentiation of BGC, BPC, and follicular helper T cells (TFH). Employing in vivo models, we evaluated various antigens and the administration of cGAMP in Alum adjuvant, investigating the differentiation of BGC, BPC, and TFH cells, along with the production of antigen-specific antibodies. cGAMP enhances the differentiation of BGC and BPC, leading to increased antigen-specific antibody production. This effect is shown to be type I Interferon-dependent, with a substantial reduction in BPC frequency upon interferon (IFN)-β blockade. Additionally, cGAMP’s influence on TFH differentiation varies over time, which may be critical for refining vaccine strategies. The findings elucidate a complex, antigen-specific influence of cGAMP on T and B cell responses, providing insights that could optimize vaccine efficacy

VLBI observations of bright AGN jets with KVN and VERA Array (KaVA): Evaluation of Imaging Capability

The Korean very-long-baseline interferometry (VLBI) network (KVN) and VLBI Exploration of Radio Astrometry (VERA) Array (KaVA) is the first international VLBI array dedicated to high-frequency (23 and 43 GHz bands) observations in East Asia. Here, we report the first imaging observations of three bright active galactic nuclei (AGNs) known for their complex morphologies: 4C 39.25, 3C 273, and M 87. This is one of the initial result of KaVA early science. Our KaVA images reveal extended outflows with complex substructure such as knots and limb brightening, in agreement with previous Very Long Baseline Array (VLBA) observations. Angular resolutions are better than 1.4 and 0.8 milliarcsecond at 23 GHz and 43 GHz, respectively. KaVA achieves a high dynamic range of ~1000, more than three times the value achieved by VERA. We conclude that KaVA is a powerful array with a great potential for the study of AGN outflows, at least comparable to the best existing radio interferometric arrays.Comment: 15 pages, 10 figures, 6 tables, accepted for publication in PAS