2,289 research outputs found

    SIRT3 Protects Rotenone-induced Injury in SH-SY5Y Cells by Promoting Autophagy through the LKB1-AMPK-mTOR Pathway.

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    SIRT3 is a class III histone deacetylase that modulates energy metabolism, genomic stability and stress resistance. It has been implicated as a potential therapeutic target in a variety of neurodegenerative diseases, including Parkinson's disease (PD). Our previous study demonstrates that SIRT3 had a neuroprotective effect on a rotenone-induced PD cell model, however, the exact mechanism is unknown. In this study, we investigated the underlying mechanism. We established a SIRT3 stable overexpression cell line using lentivirus infection in SH-SY5Y cells. Then, a PD cell model was established using rotenone. Our data demonstrate that overexpression of SIRT3 increased the level of the autophagy markers LC3 II and Beclin 1. After addition of the autophagy inhibitor 3-MA, the protective effect of SIRT3 diminished: the cell viability decreased, while the apoptosis rate increased; α-synuclein accumulation enhanced; ROS production increased; antioxidants levels, including SOD and GSH, decreased; and MMP collapsed. These results reveal that SIRT3 has neuroprotective effects on a PD cell model by up-regulating autophagy. Furthermore, SIRT3 overexpression also promoted LKB1 phosphorylation, followed by activation of AMPK and decreased phosphorylation of mTOR. These results suggest that the LKB1-AMPK-mTOR pathway has a role in induction of autophagy. Together, our findings indicate a novel mechanism by which SIRT3 protects a rotenone-induced PD cell model through the regulation of autophagy, which, in part, is mediated by activation of the LKB1-AMPK-mTOR pathway

    Multi-granularity Item-based Contrastive Recommendation

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    Contrastive learning (CL) has shown its power in recommendation. However, most CL-based recommendation models build their CL tasks merely focusing on the user's aspects, ignoring the rich diverse information in items. In this work, we propose a novel Multi-granularity item-based contrastive learning (MicRec) framework for the matching stage (i.e., candidate generation) in recommendation, which systematically introduces multi-aspect item-related information to representation learning with CL. Specifically, we build three item-based CL tasks as a set of plug-and-play auxiliary objectives to capture item correlations in feature, semantic and session levels. The feature-level item CL aims to learn the fine-grained feature-level item correlations via items and their augmentations. The semantic-level item CL focuses on the coarse-grained semantic correlations between semantically related items. The session-level item CL highlights the global behavioral correlations of items from users' sequential behaviors in all sessions. In experiments, we conduct both offline and online evaluations on real-world datasets, verifying the effectiveness and universality of three proposed CL tasks. Currently, MicRec has been deployed on a real-world recommender system, affecting millions of users. The source code will be released in the future.Comment: 17 pages, under revie

    Secure Direct Communication Based on Secret Transmitting Order of Particles

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    We propose the schemes of quantum secure direct communication (QSDC) based on secret transmitting order of particles. In these protocols, the secret transmitting order of particles ensures the security of communication, and no secret messages are leaked even if the communication is interrupted for security. This strategy of security for communication is also generalized to quantum dialogue. It not only ensures the unconditional security but also improves the efficiency of communication.Comment: To appear in Phys. Rev.

    A New Method for Figuring the Number of Hidden Layer Nodes in BP Algorithm

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    In the field of artificial neural network, BP neural network is a multi-layer feed-forward neural network. Because it is difficult to figure the number of hidden layer nodes in a BP neural network, the theoretical basis and the existing methods for BP network hidden layer nodes are studied. Then based on traditional empirical formulas, we propose a new approach to rapidly figure the quantity of hidden layer nodes in two-layer network. That is, with the assistance of experience formulas, the horizon of unit number in hidden layer can be confirmed and its optimal value will be found in this horizon. Finally, a new formula for figuring the quantity of hidden layer codes is obtained through fitting input dimension, output dimension and the optimal value of hidden layer codes. Under some given input dimension and output dimension, efficiency and precision of BP algorithm may be improved by applying the proposed formula

    Spatio-Temporal Tuples Transformer for Skeleton-Based Action Recognition

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    Capturing the dependencies between joints is critical in skeleton-based action recognition task. Transformer shows great potential to model the correlation of important joints. However, the existing Transformer-based methods cannot capture the correlation of different joints between frames, which the correlation is very useful since different body parts (such as the arms and legs in "long jump") between adjacent frames move together. Focus on this problem, A novel spatio-temporal tuples Transformer (STTFormer) method is proposed. The skeleton sequence is divided into several parts, and several consecutive frames contained in each part are encoded. And then a spatio-temporal tuples self-attention module is proposed to capture the relationship of different joints in consecutive frames. In addition, a feature aggregation module is introduced between non-adjacent frames to enhance the ability to distinguish similar actions. Compared with the state-of-the-art methods, our method achieves better performance on two large-scale datasets.Comment: 14 pages, 5 figure

    Characterization and Localization of Cyclin B3 Transcript in Both Oocyte and Spermatocyte of the Rainbow Trout (Oncorhynchus Mykiss)

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    B-type cyclins are regulatory subunits with distinct roles in the cell cycle. To date, at least three subtypes of B-type cyclins (B1, B2, and B3) have been identified in vertebrates. Previously, we reported the characterization and expression profiles of cyclin B1 and B2 during gametogenesis in the rainbow trout (Oncorhynchus mykiss). In this paper, we isolated another subtype of cyclin B, cyclin B3 (CB3), from a cDNA library of the rainbow trout oocyte. The full-length CB3 cDNA (2,093 bp) has an open reading frame (1,248 bp) that encodes a protein of 416 amino acid residues. The CB3 transcript was widely distributed in all the examined tissues, namely, eye, gill, spleen, brain, heart, kidney, stomach, skin, muscle, and, especially, gonad. Northern blot analysis indicated only one form of the CB3 transcript in the testis and ovary. In situ hybridization revealed that, in contrast to cyclin B1 and B2 transcripts, CB3 transcripts were localized in the oocytes, spermatocytes, and spermatogonia. These findings strongly suggest that CB3 plays a role not only as a mitotic cyclin in spermatogonial proliferation during early spermatogenesis but also during meiotic maturation of the spermatocyte and oocyte in the rainbow trout

    Empirical metallicity-dependent calibrations of effective temperature against colours for dwarfs and giants based on interferometric data

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    We present empirical metallicity-dependent calibrations of effective temperature against colours for dwarfs of luminosity classes IV and V and for giants of luminosity classes II and III, based on a collection from the literature of about two hundred nearby stars with direct effective temperature measurements of better than 2.5 per cent. The calibrations are valid for an effective temperature range 3,100 - 10,000 K for dwarfs of spectral types M5 to A0 and 3,100 - 5,700 K for giants of spectral types K5 to G5. A total of twenty-one colours for dwarfs and eighteen colours for giants of bands of four photometric systems, i.e. the Johnson (UBVRJIJJHKUBVR_{\rm J}I_{\rm J}JHK), the Cousins (RCICR_{\rm C}I_{\rm C}), the Sloan Digital Sky Survey (SDSS, grgr) and the Two Micron All Sky Survey (2MASS, JHKsJHK_{\rm s}), have been calibrated. Restricted by the metallicity range of the current sample, the calibrations are mainly applicable for disk stars ([Fe/H] ≳ −1.0\,\gtrsim\,-1.0). The normalized percentage residuals of the calibrations are typically 2.0 and 1.5 per cent for dwarfs and giants, respectively. Some systematic discrepancies at various levels are found between the current scales and those available in the literature (e.g. those based on the infrared flux method IRFM or spectroscopy). Based on the current calibrations, we have re-determined the colours of the Sun. We have also investigated the systematic errors in effective temperatures yielded by the current on-going large scale low- to intermediate-resolution stellar spectroscopic surveys. We show that the calibration of colour (g−Ksg-K_{\rm s}) presented in the current work provides an invaluable tool for the estimation of stellar effective temperature for those on-going or upcoming surveys.Comment: 28 pages, 19 figures, 8 tables, accepted for publication in MNRA
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