Neural Multi-network Diffusion towards Social Recommendation

Graph Neural Networks (GNNs) have been widely applied on a variety of real-world applications, such as social recommendation. However, existing GNN-based models on social recommendation suffer from serious problems of generalization and oversmoothness, because of the underexplored negative sampling method and the direct implanting of the off-the-shelf GNN models. In this paper, we propose a succinct multi-network GNN-based neural model (NeMo) for social recommendation. Compared with the existing methods, the proposed model explores a generative negative sampling strategy, and leverages both the positive and negative user-item interactions for users' interest propagation. The experiments show that NeMo outperforms the state-of-the-art baselines on various real-world benchmark datasets (e.g., by up to 38.8% in terms of NDCG@15)

FairGen: Towards Fair Graph Generation

There have been tremendous efforts over the past decades dedicated to the generation of realistic graphs in a variety of domains, ranging from social networks to computer networks, from gene regulatory networks to online transaction networks. Despite the remarkable success, the vast majority of these works are unsupervised in nature and are typically trained to minimize the expected graph reconstruction loss, which would result in the representation disparity issue in the generated graphs, i.e., the protected groups (often minorities) contribute less to the objective and thus suffer from systematically higher errors. In this paper, we aim to tailor graph generation to downstream mining tasks by leveraging label information and user-preferred parity constraint. In particular, we start from the investigation of representation disparity in the context of graph generative models. To mitigate the disparity, we propose a fairness-aware graph generative model named FairGen. Our model jointly trains a label-informed graph generation module and a fair representation learning module by progressively learning the behaviors of the protected and unprotected groups, from the `easy' concepts to the `hard' ones. In addition, we propose a generic context sampling strategy for graph generative models, which is proven to be capable of fairly capturing the contextual information of each group with a high probability. Experimental results on seven real-world data sets, including web-based graphs, demonstrate that FairGen (1) obtains performance on par with state-of-the-art graph generative models across six network properties, (2) mitigates the representation disparity issues in the generated graphs, and (3) substantially boosts the model performance by up to 17% in downstream tasks via data augmentation

The CCAAT box-binding transcription factor NF-Y regulates basal expression of human proteasome genes

AbstractProtein degradation by the proteasome plays an important role in all major cellular pathways. Aberrant proteasome activity is associated with numerous human diseases including cancer and neurological disorders, but the underlying mechanism is virtually unclear. At least part of the reason for this is due to lack of understanding of the regulation of human proteasome genes. In this study, we found that a large set of human proteasome genes carry the CCAAT box in their promoters. We further demonstrated that the basal expression of these CCAAT box-containing proteasome genes is regulated by the transcription factor NF-Y. Knockdown of NF-YA, an essential subunit of NF-Y, reduced proteasome gene expression and compromised the cellular proteasome activity. In addition, we showed that knockdown of NF-YA sensitized breast cancer cells to the proteasome inhibitor MG132. This study unveils a new role for NF-Y in the regulation of human proteasome genes and suggests that NF-Y may be a potential target for cancer therapy

A C. elegans neuron both promotes and suppresses motor behavior to fine tune motor output [preprint]

How neural circuits drive behavior is a central question in neuroscience. Proper execution of motor behavior requires the precise coordination of many neurons. Within a motor circuit, individual neurons tend to play discrete roles by promoting or suppressing motor output. How exactly neurons function in specific roles to fine tune motor output is not well understood. In C. elegans, the interneuron RIM plays important yet complex roles in locomotion behavior. Here, we show that RIM both promotes and suppresses distinct features of locomotion behavior to fine tune motor output. This dual function is achieved via the excitation and inhibition of the same motor circuit by electrical and chemical neurotransmission, respectively. Additionally, this bi-directional regulation contributes to motor adaptation in animals placed in novel environments. Our findings reveal that individual neurons within a neural circuit may act in opposing ways to regulate circuit dynamics to fine tune behavioral output

A C. elegans neuron both promotes and suppresses motor behavior to fine tune motor output

How neural circuits drive behavior is a central question in neuroscience. Proper execution of motor behavior requires precise coordination of many neurons. Within a motor circuit, individual neurons tend to play discrete roles by promoting or suppressing motor output. How exactly neurons function in specific roles to fine tune motor output is not well understood. In C. elegans, the interneuron RIM plays important yet complex roles in locomotion behavior. Here, we show that RIM both promotes and suppresses distinct features of locomotion behavior to fine tune motor output. This dual function is achieved via the excitation and inhibition of the same motor circuit by electrical and chemical neurotransmission, respectively. Additionally, this bi-directional regulation contributes to motor adaptation in animals placed in novel environments. Our findings reveal that individual neurons within a neural circuit may act in opposing ways to regulate circuit dynamics to fine tune behavioral output

Downregulation of Nuclear Protein H2B Induces Salicylic Acid Mediated Defense Against PVX Infection in Nicotiana benthamiana

Histone H2B protein is not only structurally important for chromosomal DNA packaging but is also involved in the regulation of gene expression, including the immune response of plants against pathogens. In this study, we show that the potato virus X (PVX) infection resulted in the reduced expression of H2B at both the mRNA and protein level in Nicotiana benthamiana. Tobacco rattle virus (TRV)-based virus-induced gene silencing (VIGS) was then used to down-regulate the expression of H2B in N. benthamiana and tests showed that the titre of TRV was similar in these plants to that in control treated plants. When these H2B-silenced plants were inoculated with PVX, the virus spread more slowly through the plant and there was a lower titre of PVX compared to non-silenced plants. Abnormal leaf development and stem necrosis were observed in the H2B-silenced plants, which were alleviated in H2B-silenced NahG transgenic plants suggesting the involvement of salicylic acid (SA) in the production of these symptoms. Indeed, quantitative reverse transcription (qRT)-PCR and liquid chromatography tandem mass spectroscopy (LC-MS) results showed that endogenous SA is increased in H2B-silenced N. benthamiana. Thus, downregulation of H2B induced the accumulation of endogenous SA, which was correlated with stem necrosis and a decreased accumulation of PVX in N. benthamiana

Genome-wide identification of new reference genes for RT-qPCR normalization in CGMMV-infected Lagenaria siceraria

Lagenaria siceraria is an economically important cucurbitaceous crop, but suitable reference genes (RGs) to use when the plants are infected by cucumber green mottle mosaic virus (CGMMV) have not been determined. Sixteen candidate RGs of both leaf and fruit and 18 candidate RGs mostly from separate RNA-Seq datasets of bottle gourd leaf or fruit were screened and assessed by RT-qPCR. The expression stability of these genes was determined and ranked using geNorm, NormFinder, BestKeeper and RefFinder. Comprehensive analysis resulted in the selection of LsCYP, LsH3, and LsTBP as the optimal RGs for bottle gourd leaves, and LsP4H, LsADP, and LsTBP for fruits. LsWD, LsGAPDH, and LsH3 were optimal for use in both leaves and fruits under the infection of CGMMV. Isopentenyl transferase (IPT) and DNA-directed RNA polymerase (DdRP) were used to validate the applicability of the most stable identified RGs from bottle gourd in response to CGMMV. All the candidate RGs performed in RT-qPCR consistently with the data from the transcriptome database. The results demonstrated that LsWD, LsGAPDH and LsH3 were the most suitable internal RGs for the leaf, and LsH3, LsGAPDH, LsP4H and LsCYP for the fruit