Interferon regulatory factor 7- (IRF7-) mediated immune response affects Newcastle disease virus replication in chicken embryo fibroblasts

Interferon regulatory factor 7 (IRF7) is essential for the induction of an antiviral response. Previous studies have shown that virus replication causes the activation or expression of Type I interferon (IFN) in cells, which further activates IFN-stimulated genes (ISGs) to retard virus growth. In this study, after infection of chicken embryo fibroblasts (CEFs) with the lentogenic Newcastle disease virus (NDV) strain LaSota or the velogenic NDV strain GM, the mRNA and protein levels of IRF7 showed a significant increase, and part of the IRF7 protein was translocated from the cytoplasm to the nucleus. In order to further explore the effect of IRF7-mediated innate immune response on the replication of NDV in CEFs, the mRNA levels of IFN-α, IFN-β and STAT1 were measured and the replication kinetics of NDV determined. The results showed that specific siRNA could inhibit the expression of IRF7 and limit the mRNA level of IFN-α, IFN-β and STAT1 and, accordingly, the replication kinetics of both NDVs were enhanced after the inhibition of IRF7. In conclusion, IRF7 is an important nuclear transcription factor for the induction of Type I IFNs during the antiviral response, which can affect the replication of NDV and spread to CEFs in the early phase of viral infection

Neural Dynamic Data Valuation

Data constitute the foundational component of the data economy and its marketplaces. Efficient and fair data valuation has emerged as a topic of significant interest.\ Many approaches based on marginal contribution have shown promising results in various downstream tasks. However, they are well known to be computationally expensive as they require training a large number of utility functions, which are used to evaluate the usefulness or value of a given dataset for a specific purpose. As a result, it has been recognized as infeasible to apply these methods to a data marketplace involving large-scale datasets. Consequently, a critical issue arises: how can the re-training of the utility function be avoided? To address this issue, we propose a novel data valuation method from the perspective of optimal control, named the neural dynamic data valuation (NDDV). Our method has solid theoretical interpretations to accurately identify the data valuation via the sensitivity of the data optimal control state. In addition, we implement a data re-weighting strategy to capture the unique features of data points, ensuring fairness through the interaction between data points and the mean-field states. Notably, our method requires only training once to estimate the value of all data points, significantly improving the computational efficiency. We conduct comprehensive experiments using different datasets and tasks. The results demonstrate that the proposed NDDV method outperforms the existing state-of-the-art data valuation methods in accurately identifying data points with either high or low values and is more computationally efficient.Comment: 43 pages, 19 figure

A measure of cosmological distance using the C

We use the anticorrelation between the equivalent width (EW) of the C I

Phylogenetic and Codon Usage Analysis for Capsid and Replicase Genes of Porcine Circovirus 3

Abstract Porcine circovirus type 3 (PCV3) is a highly contagious virus belonging to the family Circoviridae that causes the severe dermatitis and nephropathy syndrome. To date, PCV3 has a worldwide distribution and bring huge economic loss in swine industry. Replicase protein (Rep) and capsid protein (Cap) are two major proteins of PCV3. Considering that the large number of new PCV3 isolates were reported in the past few years and the research for the codon usage pattern of Rep and Cap genes was still a gap, phylogenetic and codon usage analysis of these two genes was performed. Phylogenetic analysis with all strains showed no clear clusters were displayed, but almost all strains of one genotype were separated into same clade. Relative synonymous codon usage (RSCU) analysis revealed that the codon usage bias existed and effective number of codon (ENC) analysis showed that the bias was slight low. ENC-GC3s plot indicated that mutational pressure and other factors both play a role in PCV3 codon usage and neutrality plot analysis showed that natural selection was the main force influencing the codon usage pattern. In summary, the results provided the important basic data on codon usage pattern of Rep and Cap genes, and a better understanding of the evolution and potential origin of PCV3.</jats:p