The Neuropeptide Y Single-nucleotide Polymorphism rs16147 Moderates the Effect of Alcohol Dependence on Depression

Wang, Fan; Zhou, Siyao; Chen, Li; Shen, Guanghui; Yang, Fan; Sun, Huankun; Hong, Liuzhi; Zou, Yang; Li, Hui; Chen, Yu‐Hsin; Liu, Yanlong; Wang, Wei

doi:10.21203/rs.3.rs-863544/v1

Cited by 3 publications

(5 citation statements)

References 25 publications

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“…The distinctive morphological features of hundreds of chitinous sclerites (Isobe et al, 2022) covering the dorsal foot in Scalyfoot Snail may be linked to its unique phylogeny position. Our mitogenome level molecular phylogeny also lends support to the convergent evolution scenario of endosymbiosis (Chen et al, 2015) in two divergent genera within Peltospiridae, i.e., Chrysomallon and Gigantopelta (Lan et al, 2021), since they are not recovered as sister genera and the other peltospirid snails are asymbiotic (Chen et al, 2015). Within Cocculinida, Coccocrater sp.…”

Section: Discussionsupporting

confidence: 62%

“…For Dracogyra subfusca, the published genome assembly (Lan et al, 2021) using a specimen collected in Longqi vent field ("Tiamat" chimney), Southwest Indian Ridge did not contain the complete mitogenome. Therefore, the raw sequencing reads of D. subfusca was downloaded from the NCBI SRA database in order to assemble its mitogenome anew.…”

Section: Sampling Sequencing and Data Curationmentioning

confidence: 99%

“…Hatoma, and Lamellomphalus manusensis after removing potential microbe contamination, low-quality, and adapter-contaminated reads. Taking an assumption that the genome size is similar to Gigantopelta aegis (1.27 Gb; Lan et al, 2021), a relatively large genome within Neomphaliones, the sequencing coverage of the genome is at least 12.5X.…”

Section: Assembly and Characterization Of The Newly Sequenced Mitogenomementioning

confidence: 99%

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New mitogenomes in deep-water endemic Cocculinida and Neomphalida shed light on lineage-specific gene orders in major gastropod clades

et al. 2022

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Gastropoda is the most speciose class in Mollusca, the second largest animal phylum. The internal relationships of major gastropod groups remain largely unsettled, partly due to the insufficient data from key deep-water endemic lineages such as the subclass Neomphaliones. Neomphaliones currently includes two orders: Cocculinida, best known from sunken wood habitats, and Neomphalida, best known from hydrothermal vents and often referred to as the “hot vent clade.” Phylogenetic controversy has also been observed in this subclass across different studies, requesting additional investigations. Here, we assembled nine new mitogenomes from two Cocculinida and seven Neomphalida species and analyzed them with published gastropod mitogenomes, with a particular focus on Neomphaliones. The phylogenetic reconstruction of Gastropoda based on 13 mitochondrial protein-coding genes resulted in a topology largely congruent with previous reconstructions based on morphological characters. Furthermore, we recovered characteristic mitochondrial gene order arrangements of Cocculinida and Neomphalida compared to the hypothetical ancestral gastropod gene order, at a level similar to other subclass-level clades. Divergence time estimation showed that Cocculinida and Neomphalida diverged approximately 322.68 million years ago. In addition to characteristic gene order arrangements for the clade, Cocculinida mitogenomes also exhibit some minor rearrangements even among congeners. Within Neomphalida, our tree adds support to monophyletic Peltospiridae and Neomphalidae, with unique gene arrangement recovered for each family. Our results offer new insights into the rearrangement of mitogenomes in Gastropoda, providing another clue to the evolutionary history of gastropods.

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Section: Discussionsupporting

confidence: 62%

Section: Sampling Sequencing and Data Curationmentioning

confidence: 99%

Section: Assembly and Characterization Of The Newly Sequenced Mitogenomementioning

confidence: 99%

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New mitogenomes in deep-water endemic Cocculinida and Neomphalida shed light on lineage-specific gene orders in major gastropod clades

et al. 2022

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“…Deep learning algorithm, as a subset of AI, provides an autocomputational method to predict disease-network, drugside-effect, drug-target, and drug-response, and offers an interpretable AI-based approach to prioritize the repurposed drugs. [109][110][111] Additionally, machine learning algorithm is a subtype of AI that automates decisionmaking and makes predictions based on massive observed data from existing drugs and diseases, characterizes the molecules and conformational changes of drugs, identifies drug-target interactions, and predicts drug-response status by using multi-omics datasets. [112][113][114] These AI-based approaches help understand many human diseases, such as COVID-19, SARS-CoV-2, monkeypox virus, Alzheimer's disease, malignancy, hyperlipidemia, muscle atrophy, and rare diseases, and further explore the target-specific repurposed drug for curing disease.…”

Section: Repurposing In Cancermentioning

confidence: 99%

PDE5 inhibitors against cancer via mediating immune cells in tumor microenvironment: AI‐based approach for future drug repurposing exploration

Zhang,

Huang,

Feng

et al. 2024

Interdisciplinary Medicine

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Phosphodiesterase‐5 (PDE5) inhibitors are used clinically for the treatment of erectile dysfunction, pulmonary arterial hypertension, and other urological diseases. Emerging evidences have suggested the therapeutic capacity of PDE5 inhibitors as the repurposed drugs in oncology. However, the essential immune function of PDE5 inhibitors against cancer in tumor microenvironment (TME) remains unclear. This review aimed to summarize the recent advances regarding the repurposing of PDE5 inhibitors as anti‐cancer agents for cancer management to enhance the anti‐tumor immune response by mediating various immune cells, which included the myeloid‐derived suppressor cells, macrophages, T cells, fibroblasts, and natural killer cells in TME. Moreover, artificial intelligence (AI), as a new approach, is composed of traditional machine learning and deep learning methods and could be potentially used to identify the targets of immune cells in TME and predict the efficacy for repurposed drug toward malignancies. In summary, these endeavors provide novel insights into the comprehensive strategies for PDE5 inhibitors mediating immune cells against cancer and AI‐based approach for future drug repurposing exploration.

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“…Toward this goal, an ad-hoc solution is to base the prediction with respect to edge (u, v) upon the concatenation of h u , h v and g uv . According to recent practices over pairwise learning on graphs [34], [35], incorporation of interactions between N (u) and N (v), or cross node interactions significantly improves prediction performance. However, the cross-node attention module proposed in [34] requires full attention between h N (u) and h N (v) , yielding a potentially large computation overhead.…”

Section: The Grande Architecturementioning

confidence: 99%

GRANDE: a neural model over directed multigraphs with application to anti-money laundering

Wu¹,

Ma²,

Jiang³

et al. 2023

Preprint

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The application of graph representation learning techniques to the area of financial risk management (FRM) has attracted significant attention recently. However, directly modeling transaction networks using graph neural models remains challenging: Firstly, transaction networks are directed multigraphs by nature, which could not be properly handled with most of the current off-the-shelf graph neural networks (GNN). Secondly, a crucial problem in FRM scenarios like anti-money laundering (AML) is to identify risky transactions and is most naturally cast into an edge classification problem with rich edgelevel features, which are not fully exploited by the prevailing GNN design that follows node-centric message passing protocols. In this paper, we present a systematic investigation of design aspects of neural models over directed multigraphs and develop a novel GNN protocol that overcomes the above challenges via efficiently incorporating directional information, as well as proposing an enhancement that targets edge-related tasks using a novel message passing scheme over an extension of edge-tonode dual graph. A concrete GNN architecture called GRANDE is derived using the proposed protocol, with several further improvements and generalizations to temporal dynamic graphs. We apply the GRANDE model to both a real-world anti-money laundering task and public datasets. Experimental evaluations show the superiority of the proposed GRANDE architecture over recent state-of-the-art models on dynamic graph modeling and directed graph modeling.

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The Neuropeptide Y Single-nucleotide Polymorphism rs16147 Moderates the Effect of Alcohol Dependence on Depression

Cited by 3 publications

References 25 publications

New mitogenomes in deep-water endemic Cocculinida and Neomphalida shed light on lineage-specific gene orders in major gastropod clades

New mitogenomes in deep-water endemic Cocculinida and Neomphalida shed light on lineage-specific gene orders in major gastropod clades

PDE5 inhibitors against cancer via mediating immune cells in tumor microenvironment: AI‐based approach for future drug repurposing exploration

GRANDE: a neural model over directed multigraphs with application to anti-money laundering

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