A novel species of earthstar from China, Geastrum sanglinense is described. Phylogenetic analyses based on sequences of the nuclear ribosomal DNA internal transcribed spacer (ITS), large subunit ...nuclear ribosomal RNA (nrLSU), and subunit 6 of ATP synthase (atp6) regions showed that the species belongs to subsect. Epigaea in sect. Myceliostroma. The sequences of the new taxon formed a sister group to G. yanshanense and G. rubellum. This species was mainly characterized by scattered or clustered basidiomata (1.9-2.2 cm in width × 2.3-2.5 cm in height), small to medium-sized saccate exoperidium (1.9-4.3 cm diam. when expanded), smooth endoperidial bodies (1.2-2.7 cm diam.), and globose to subglobose basidiospores (3.7-4.1 μm diam.), surface with short columnar warts. The species can also be distinguished by ITS, nrLSU, and atp6 sequences. The new species was described in detail and can provide a reference for the investigation of macrofungi resources in Shanxi Province, China.
Recently, Knowledge Graph Embedding (KGE) has attracted considerable research efforts, since it simplifies the manipulation while preserving the inherent structure of the KG. However to some extent, ...most existing KGE approaches ignore the historical changes of structural information involved in dynamic knowledge graphs (DKGs). To deal with this problem, this paper presents a Timespan-aware Dynamic knowledge Graph Embedding Evolution (TDG2E) method that considers temporal evolving process of DKGs. The major innovations of our paper are two-fold. Firstly, a Gated Recurrent Units (GRU) based model is utilized in TDG2E to deal with the dependency among sub-KGs that is inevitably involved in the learning process of the dynamic knowledge graph embedding. Furthermore, we incorporate an auxiliary loss to supervise the learning process of the next sub-KG by utilizing previous structural information (i.e., the hidden state of GRU). In contrast with existing approaches in the literature (e.g., HyTE and t-TransE), TDG2E preserves structural information of current sub-KG and the temporal evolving process of the DKG simultaneously. Secondly, to further deal with the time unbalance issue underlying the DKGs, a Timespan Gate is designed in GRU. It makes TDG2E possible to model the temporal evolving process of DKGs more effectively by incorporating the timespan between adjacent sub-KGs. Extensive experiments on two large temporal datasets (i.e., YAGO11k and Wikidata12k) extracted from real-world KGs validate that the proposed TDG2E significantly outperforms traditional KGE methods in terms of Mean Rank and Hit Rate.
Gene transcripts that show invariant abundance during development are ideal as reference genes (RGs) for accurate gene expression analyses, such as RNA blot analysis and reverse ...transcription-quantitative real time PCR (RT-qPCR) analyses. In a genome-wide analysis, we selected three "Commonly used" housekeeping genes (HKGs), fifteen "Traditional" HKGs, and nine novel genes as candidate RGs based on 80 publicly available transcriptome libraries that include data for receptacle development in eight strawberry cultivars.
The results of the multifaceted assessment consistently revealed that expression of the novel RGs showed greater stability compared with that of the "Commonly used" and "Traditional" HKGs in transcriptome and RT-qPCR analyses. Notably, the majority of stably expressed genes were associated with the ubiquitin proteasome system. Among these, two 26 s proteasome subunits, RPT6A and RPN5A, showed superior expression stability and abundance, and are recommended as the optimal RGs combination for normalization of gene expression during strawberry receptacle development.
These findings provide additional useful and reliable RGs as resources for the accurate study of gene expression during receptacle development in strawberry cultivars.
Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is the preferred method for gene expression research, but normalization based on suitable reference genes (RGs) is the key to ...obtaining reliable gene expression results. In this study, we selected six “commonly used” RGs, two “traditional” housekeeping genes (HKGs), and four novel genes as candidate RGs based on 54 publicly available peel transcriptome libraries that include data from development, bagging, and post-harvest cryopreservation studies of four pear cultivars. The results of this multifaceted assessment from transcriptome and qRT-PCR analyses consistently revealed that
ACT6/7/8/9
had the best expression stability among all candidate RGs, and expression of the novel RGs showed greater stability compared with the other “commonly used” RGs and “traditional” HKGs. Among the candidate RGs,
ACT6/7/8/9
and Nucleosome Assembly Protein 1 (
NAP1
) showed superior expression stability and abundance, and they were recommended as the optimal RG combination for gene expression normalization in pear peel. These genome-wide findings provide more reasonable RG usage specifications, and additional useful and reliable RGs as resources for accurate study of gene expression in pear peel studies of different cultivars.
Incorporating knowledge graphs (KGs) into recommender systems (knowledge-aware recommendation) to improve the recommendation accuracy and explainability has attracted considerable research efforts. ...However, existing methods largely assume that KGs are complete when transferring knowledge from them, which may lead to suboptimal performance for those KGs, can be hardly complete in real-life scenarios. In this paper, we present a robustly co-learning model (RCoLM) that takes the incompleteness nature of KGs into consideration when incorporating them into recommendation. The RCoLM aims at transferring knowledge between recommendation task and knowledge graph completion (KG completion) task by utilizing a transfer learning model. An earlier version of this paper appeared in KDD 2019. This version is an extension of the previous submission and two major innovations are presented here. At first, distinct from previous knowledge-aware recommendation methods, which mainly focus on transferring knowledge from KGs to item recommendations, the RCoLM attempts to exploit user-item interactions from recommendations for KG completion, and unifies the two tasks in a joint model for mutual enhancements. Second, the RCoLM provides a general task-oriented negative sampling strategy on KG completion task, which further improves the adaptive ability of the proposed algorithm and plays an essential role for obtaining superior performance in various sub-tasks of the KG completion. The extensive experiments on two real-world public datasets demonstrate that RCoLM outperforms not only state-of-the-art knowledge-aware recommendation methods but also existing KG completion methods.
In real-time bidding (RTB) systems for display advertising, a demand-side platform (DSP) serves as an agent for advertisers and plays an important role in competing for online advertising spaces by ...placing proper bidding prices. A critical function of the DSP is formulating proper bidding strategies to maximize key performance indicators, such as the number of clicks and conversions. However, many small and medium-sized advertisers' main goal is to maximize revenue with an acceptable return on investment (ROI), rather than simply increase clicks or conversions. Most existing approaches are inapplicable of satisfying the revenue-maximizing goals directly. To solve this problem, we first theoretically analyze the relationships among the conversion rate, ROI, and ad cost, and how they affect revenue. By doing so, we reveal that it is a challenge to increase revenue by relying solely on improving ROI without considering the impact of the ad cost. Based on this insight, the maximal revenue (MR) bidding strategy is proposed to maximize revenue by maximizing the ad cost with a desirable ROI constraint. Unlike previous studies, the proposed MR first distinguishes bid prices from ad costs explicitly, which makes it more applicable to the real second-price auction (GSP) auction mechanism in RTB systems. Then, the winning function is empirically defined in the form of tanh that provides a promising solution for estimating ad costs by jointly considering ad costs with the winning function. The experimental results based on two real-world public datasets demonstrate that the MR significantly outperforms five state-of-the-art models in terms of both revenue and ROI.
Multi-label learning deals with problems in which each instance is associated with a set of labels. Most multi-label learning algorithms ignore the potential distribution differences between the ...training domain and the test domain in the instance space and label space, as well as the intrinsic geometric information of the label space. These restrictive assumptions limit the ability of the existing multi-label learning algorithms to classify between domains. To solve this problem, in this paper, we propose a novel distribution-adaptation-based method, the multi-label metric transfer learning (MLMTL), to relax these two assumptions and handle more general multi-label learning tasks effectively. In particular, MLMTL extends the maximum mean discrepancy method into multi-label classification by learning and adjusting the weights for the multi-labeled training instances. In this way, MLMTL bridges the instance distribution and label distribution divergence between training and test datasets. In addition, based on the balanced multi-label training data, we explore the intrinsic geometric information of the label space by encoding it into a distance metric learning framework. Extensive experiments on five benchmark datasets show that the proposed approach significantly outperforms the state-of-the-art multi-label learning algorithms.
In real-time quantitative PCR (RT-qPCR), internal control genes (ICGs) are crucial for normalization. This study screened 6 novel ICGs: Pre-mRNA-splicing factor cwc15 (Cwf15); ER associated DnaJ ...chaperone (DnaJ); E3 ubiquitin-protein ligase NEDD4 (HUL4); ATP-binding cassette, subfamily B (MDR/TAP), member 1 (VAMP); Exosome complex exonuclease DIS3/RRP44 (RNB); V-type H+-transporting ATPase sub-unit A (V-ATP) from the 22-transcriptome data of 8 filamentous fungi. The six novel ICGs are all involved in the basic biological process of cells and share the different transcription levels from high to low. In order to further verify the stability of ICGs candidates, the six novel ICGs as well as three traditional housekeeping genes: β-actin (ACTB); β-tubulin (β-TUB); glyceraldehyde-3-phosphate dehydrogenase gene (GAPDH) and the previously screened reference genes: SPRY-domain-containing protein (SPRYp); Ras-2 protein (Ras); Vacuolar protein sorting protein 26 (Vps26) were evaluated by geNorm and NormFinder statistical algorithms. RT-qPCR of 12 ICGs were performed at different developmental stages in Flammulina filiformis and under different treatment conditions in Neurospora crassa. The consistent results of the two algorithms suggested that the novel genes, RNB, V-ATP, and VAMP, showed the highest stability in F. filiformis and N. crassa. RNB, V-ATP, and VAMP have high expression stability and universal applicability and therefore have great potential as ICGs for standardized calculation in filamentous fungi. The results also provide a novel guidance for the screening stable reference genes in RT-qPCR and a wide application in gene expression analysis of filamentous fungi.
On the basis of its close phylogenetic relationship with primates, the development of Tupaia belangeri as an infection animal model and drug metabolism model could provide a new option for ...preclinical studies, especially in hepatitis virus research. As a replacement for primary human hepatocytes (PHHs), primary tupaia hepatocytes (PTHs) have been widely used. Similar to human serum albumin, tupaia serum albumin (TSA) is the most common liver synthesis protein and is an important biomarker for PTHs and liver function. However, no detection or quantitative method for TSA has been reported. In this study, mouse monoclonal antibodies (mAbs) 4G5 and 9H3 against TSA were developed to recognize PTHs, and they did not show cross-reactivity with serum albumin from common experimental animals, such as the mouse, rat, cow, rabbit, goat, monkey, and chicken. The two mAbs also exhibited good performance in fluorescence activated cell sorting (FACS) analysis and immunofluorescence (IF) detection of PTHs. A chemiluminescent enzyme immune assay method using the two mAbs, with a linear range from 96.89 pg/ml to 49,609.38 pg/ml, was developed for the quantitative detection of TSA. The mAbs and the CLEIA method provide useful tools for research on TSA and PTHs.
Hepatitis B virus (HBV) is the leading cause of liver disease and hepatic carcinoma (HCC). Approximately 350 million people worldwide are infected with HBV and at risk of chronicity. An efficient ...HBV-tolerant murine model that mimics HBV infection in humans is desirable for HBV-related research. In this study, we investigated and established a murine model by hydrodynamic injection (HDI) of pAAV/HBV into the tail vein of AAVS1 site element-transgenic mice. In 80% of the injected mice, the serum level of HBsAg reached 103-4 IU/ml and persisted for more than half a year. Next, the model was used to evaluate RNA interference (RNAi)-based antiviral therapy. Data obtained using the model demonstrated that this model will facilitate the elucidation of the mechanisms underlying chronic HBV infection and will also be useful for evaluating new antiviral drugs.
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