Replication Strategy Research Articles

Infection of porcine enteroids and 2D differentiated intestinal epithelial cells with rotavirus A to study cell tropism and polarized immune response

ABSTRACT Intestinal epithelial cell interactions with enteric pathogens have been incompletely elucidated owing to the lack of model systems that recapitulate the cellular diversity, architecture and functionality of the intestine. To analyze rotavirus (RV) infection and the subsequent innate immune response, we established cultures of differentiated porcine intestinal epithelial cells in three different variations: basolateral-out enteroids, apical-out enteroids and two-dimensional (2D) filter-grown intestinal epithelial cells. Application of specific antibodies for fluorescent staining indicated that enteroids and enteroid-derived cell cultures contain multiple intestinal epithelial cell types. Infection studies indicated that both apical-out enteroids and 2D intestinal epithelial cells are susceptible to porcine RV infection. However, 2D intestinal epithelial cells are more useful for a detailed characterization and comparison of apical and basolateral infection than apical-out enteroids. Virus-induced apoptosis was observed in apical-out enteroids at 24 h post infection but not at earlier time points after infection. RV infected not only enterocytes but also goblet cells and Paneth cells in apical-out enteroids and 2D intestinal epithelial cells. Interestingly, despite the lack of significant differences in the efficiency of infection after apical and basolateral infection of 2D intestinal epithelial cells, stronger innate immune and inflammatory responses were observed after basolateral infection as compared to infection via the apical route. Therefore, apical-out enteroids and 2D intestinal epithelial cells provide useful primary cell culture models that can be extended to analyze invasion and replication strategies of agents implicated in enteric diseases or to study immune and inflammatory responses of the host induced by enteric pathogens.

Sensor-based cloud computing data system and long distance running fatigue assessment

Wireless sensor networks are widely used in sports training, medical and health care, smart home, environmental monitoring, cloud data and other fields because of their large scale, self-organization, reliability, dynamic, integration and data centralization. Based on this point, this article conducts a comprehensive analysis and research on cloud computing data systems, and designs and implements a dynamic replication strategy. Since different users have different demands for different data at different times, it is necessary to record and analyze recent users' data access, so as to actively adjust the number and location of data blocks. Subsequently, a multi-source blockchain transmission method was proposed and implemented, which can significantly reduce the time cost of data migration and improve the overall performance of cloud storage data systems. Finally, the article provides an in-depth analysis of long-distance running fatigue. This study will design a simulated specialized exercise load experiment to reproduce the load characteristics of excellent athletes during mid to long distance running, in order to induce exercise fatigue in the main muscles of different parts of their bodies. At the same time, the amplitude frequency joint analysis of the surface changes of EMG signal in this process is carried out. This article conducts research on sensor based cloud computing data systems and long-distance running fatigue assessment, promoting the development of cloud computing data systems and improving long-distance running fatigue assessment methods.

Improving Telehealth Equity in Response to COVID-19 in California: ACTIVATE and Lighthouse

Background In response to the significant stressors on health care delivery created by COVID-19, CITRIS Health and partner organizations developed 2 telehealth solutions through a rapid co-design process: Lighthouse and ACTIVATE. These programs were developed to support providers serving underserved and vulnerable populations who lack the tools and resources to support patients with chronic illness or who are isolated. These challenges were exacerbated by the COVID-19 pandemic, which increased the need for resources to support vulnerable patients who could not come into a clinic in person or were isolated and lacked access to services. ACTIVATE and Lighthouse apply 2 different telehealth strategies to reach vulnerable populations. Objective This paper presents lessons learned from the design, development, and implementation of 2 innovative telehealth programs developed to improve health care delivery, access to care, digital literacy, and patient outcomes: ACTIVATE and Lighthouse. Methods ACTIVATE is a comprehensive digital health pathway for community health centers that care for those who are medically underserved. ACTIVATE is an innovative, evidence-based, and sustainable telehealth program, designed to benefit vulnerable populations in rural and agricultural communities in the California Central Valley who experience significant health disparities. Lighthouse focuses on connecting older adults in congregate affordable housing, which are settings where residents are particularly vulnerable to isolation, the lack of health care resources, and limited to no access to the internet. Lighthouse provides digital literacy training as well as access to broadband internet with the goal of increasing communication, engagement, and access to health care. Results This presentation will discuss successful design and implementation strategies as well as organizational and policy barriers to program operations. Conclusions In addition to reviewing program and implementation outcomes, strategies for replication and sustainability will be discussed. Although developed in response to COVID-19, the ultimate success of Lighthouse and ACTIVATE is dependent upon its successful scaling beyond the pandemic. Conflicts of Interest None declared.

Hedging using reinforcement learning: Contextual k-armed bandit versus Q-learning

The construction of replication strategies for contingent claims in the presence of risk and market friction is a key problem of financial engineering. In real markets, continuous replication, such as in the model of Black, Scholes and Merton (BSM), is not only unrealistic but is also undesirable due to high transaction costs. A variety of methods have been proposed to balance between effective replication and losses in the incomplete market setting. With the rise of Artificial Intelligence (AI), AI-based hedgers have attracted considerable interest, where particular attention is given to Recurrent Neural Network systems and variations of the Q-learning algorithm. From a practical point of view, sufficient samples for training such an AI can only be obtained from a simulator of the market environment. Yet if an agent is trained solely on simulated data, the run-time performance will primarily reflect the accuracy of the simulation, which leads to the classical problem of model choice and calibration. In this article, the hedging problem is viewed as an instance of a risk-averse contextual k-armed bandit problem, which is motivated by the simplicity and sample-efficiency of the architecture, which allows for realistic online model updates from real-world data. We find that the k-armed bandit model naturally fits to the Profit and Loss formulation of hedging, providing for a more accurate and sample efficient approach than Q-learning and reducing to the Black-Scholes model in the absence of transaction costs and risks.

A Trauma-Informed Mentoring Framework for Forensic Nurses: An Overview of STEERR-Structure, Process, and Evaluation.

The STEERR Mentoring Framework, grounded in decolonized and feminist mentorship approaches, integrates foundational principles of mentoring with the unique and complex characteristics of the role of the forensic nurse. The primary objective of the program is to support a competent, sustainable, and resilient forensic nursing workforce. In this article, we describe the development process, framework structure, and evaluation approach implemented within a 1-year pilot initiative focused on forensic nurses in the sexual assault nurse examiner role. We reflect on strategies for broader application and replication in forensic nursing programs across the United States.

Bipartite genome and structural organization of the parvovirus Acheta domesticus segmented densovirus

Parvoviruses (family Parvoviridae) are currently defined by a linear monopartite ssDNA genome, T = 1 icosahedral capsids, and distinct structural (VP) and non-structural (NS) protein expression cassettes within their genome. We report the discovery of a parvovirus with a bipartite genome, Acheta domesticus segmented densovirus (AdSDV), isolated from house crickets (Acheta domesticus), in which it is pathogenic. We found that the AdSDV harbors its NS and VP cassettes on two separate genome segments. Its vp segment acquired a phospholipase A2-encoding gene, vpORF3, via inter-subfamily recombination, coding for a non-structural protein. We showed that the AdSDV evolved a highly complex transcription profile in response to its multipartite replication strategy compared to its monopartite ancestors. Our structural and molecular examinations revealed that the AdSDV packages one genome segment per particle. The cryo-EM structures of two empty- and one full-capsid population (3.3, 3.1 and 2.3 Å resolution) reveal a genome packaging mechanism, which involves an elongated C-terminal tail of the VP, “pinning” the ssDNA genome to the capsid interior at the twofold symmetry axis. This mechanism fundamentally differs from the capsid-DNA interactions previously seen in parvoviruses. This study provides new insights on the mechanism behind ssDNA genome segmentation and on the plasticity of parvovirus biology.

HIV-1 usurps transcription start site heterogeneity of host RNA polymerase II to maximize replication fitness

HIV-1 relies on host RNA polymeraseII (Pol II) to transcribe its genome and uses multiple transcription start sites (TSS), including three consecutive guanosines located near the U3-R junction, to generate transcripts containing three, two, and one guanosine at the 5' end, referred to as 3G, 2G, and 1G RNA, respectively. The 1G RNA is preferentially selected for packaging, indicating that these 99.9% identical RNAs exhibit functional differences and highlighting the importance of TSS selection. Here, we demonstrate that TSS selection is regulated by sequences between the CATA/TATA box and the beginning of R. Furthermore, we have generated two HIV-1 mutants with distinct 2-nucleotide modifications that predominantly express 3G RNA or 1G RNA. Both mutants can generate infectious viruses and undergo multiple rounds of replication in T cells. However, both mutants exhibit replication defects compared to the wild-type virus. The 3G-RNA-expressing mutant displays an RNA genome-packaging defect and delayed replication kinetics, whereas the 1G-RNA-expressing mutant exhibits reduced Gag expression and a replication fitness defect. Additionally, reversion of the latter mutant is frequently observed, consistent with sequence correction by plus-strand DNA transfer during reverse transcription. These findings demonstrate that HIV-1 maximizes its replication fitness by usurping the TSS heterogeneity of host RNA Pol II to generate unspliced RNAs with different specialized roles in viral replication. The three consecutive guanosines at the junction of U3 and R may also maintain HIV-1 genome integrity during reverse transcription. These studies reveal the intricate regulation of HIV-1 RNA and complex replication strategy.

Consistency issue and related trade-offs in distributed replicated systems and databases: a review

Distributed replicated databases play a crucial role in modern computer systems enabling scalable, fault-tolerant, and high-performance data management. However, achieving these qualities requires resolving a number of trade-offs between various properties during system design and operation. This paper reviews trade-offs in distributed replicated databases and provides a survey of recent research papers studying distributed data storage. The paper first discusses a compromise between consistency and latency that appears in distributed replicated data storages and directly follows from CAP and PACELC theorems. Consistency refers to the guarantee that all clients in a distributed system observe the same data at the same time. To ensure strong consistency, distributed systems typically employ coordination mechanisms and synchronization protocols that involve communication and agreement among distributed replicas. These mechanisms introduce additional overhead and latency and can dramatically increase the time taken to complete operations when replicas are globally distributed across the Internet. In addition, we study trade-offs between other system properties including availability, durability, cost, energy consumption, read and write latency, etc. In this paper we also provide a comprehensive review and classification of recent research works in distributed replicated databases. Reviewed papers showcase several major areas of research, ranging from performance evaluation and comparison of various NoSQL databases to suggest new strategies for data replication and putting forward new consistency models. In particular, we observed a shift towards exploring hybrid consistency models of causal consistency and eventual consistency with causal ordering due to their ability to strike a balance between operations ordering guarantees and high performance. Researchers have also proposed various consistency control algorithms and consensus quorum protocols to coordinate distributed replicas. Insights from this review can empower practitioners to make informed decisions in designing and managing distributed data storage systems as well as help identify existing gaps in the body of knowledge and suggest further research directions.

Genome-wide search identified DNA methylation sites that regulate the metabolome.

Background: Identifying DNA methylation sites that regulate the metabolome is important for several purposes. In this study, publicly available GWAS data were integrated to find methylation sites that impact metabolome through a discovery and replication scheme and by using Mendelian randomization. Results: The outcome of analyses revealed 107 methylation sites associated with 84 metabolites at the genome-wide significance level (p<5e-8) at both the discovery and replication stages. A large percentage of the observed associations (85%) were with lipids, significantly higher than expected (p = 0.0003). A number of CpG (methylation) sites showed specificity e.g., cg20133200 within PFKP was associated with glucose only and cg10760299 within GATM impacted the level of creatinine; in contrast, there were sites associated with numerous metabolites e.g., cg20102877 on the 2p23.3 region was associated with 39 metabolites. Integrating transcriptome data enabled identifying genes (N = 82) mediating the impact of methylation sites on the metabolome and cardiometabolic traits. For example, PABPC4 mediated the impact of cg15123755-HDL on type-2 diabetes. KCNK7 mediated the impact of cg21033440-lipids on hypertension. POC5, ILRUN, FDFT1, and NEIL2 mediated the impact of CpG sites on obesity through metabolic pathways. Conclusion: This study provides a catalog of DNA methylation sites that regulate the metabolome for downstream applications.

Review on data replication strategies in single vs. interconnected cloud systems: Focus on data correlation‐aware strategies

SummaryData replication is a well‐known technique in cloud systems for enhancing availability and performance. Various strategies and surveys have been proposed in this respect. These surveys include comprehensive analysis and classifications. However, to the best of the authors' knowledge, there is no survey concentrating on strategies designed for interconnected cloud systems. In this article, we provide an in‐depth analysis of existing data replication strategies in cloud systems, covering single and interconnected clouds. We also highlight data correlation‐aware strategies as well as their key steps. Furthermore, we examine the major strategies' features such as: () addressed replication issues, () orientation towards the provider and the consumer, () consideration of the service level agreement, () consideration of cost and economic aspects, and () evaluation tools. Finally, we provide a performance analysis through extensive simulations of several replication strategies dedicated for single and interconnected clouds.

Enhancing fault tolerance and scalability in multi-region Kafka clusters for high-demand cloud platforms

This study examines strategies for enhancing fault tolerance and scalability in multi-region Kafka clusters, essential for supporting high-demand cloud environments. As cloud-based applications expand globally, achieving seamless data streaming across regions requires advanced configurations in Apache Kafka. This paper provides a thorough analysis of key approaches, including replication strategies, dynamic resource management, and real-time monitoring techniques tailored for multi-region deployments. Through a comprehensive literature review and real-world case studies, the study identifies critical challenges in managing latency, data consistency, and resilience within distributed Kafka clusters. Findings reveal that fault tolerance can be significantly improved through hybrid replication models that balance latency and data integrity, while advanced partitioning and load balancing techniques optimize Kafka’s scalability under fluctuating demands. The integration of container orchestration tools such as Kubernetes has also proven effective in automating resource scaling and failover across distributed environments. Furthermore, the paper highlights future research directions, including edge computing integration, predictive scaling, and enhanced security protocols to address evolving data privacy requirements. In conclusion, while multi-region Kafka deployments offer robust solutions for distributed data streaming, achieving optimal performance and resilience requires a combination of adaptive replication, proactive resource management, and secure, compliant data flows. Future research should focus on refining edge-compatible solutions and regulatory-compliant frameworks to sustain Kafka’s role in global, real-time data processing.

Bioinspired Adaptable Indwelling Microneedles for Treatment of Diabetic Ulcers.

Microneedles provide an effective strategy for transdermal drug delivery. Many endeavors have been devoted to developing smart microneedles that can respond to and interact with pathophysiological environments. Here, novel bioinspired adaptable indwelling microneedles with therapeutic exosome encapsulation are presented for diabetic wound healing by a combined fabrication strategy of template replication and 3Dtransfer printing. Such microneedles are composed of mesenchymal stem cell (MSC)-exosomes-encapsulated adjustable poly(vinyl alcohol) (PVA) hydrogel needle tips and detachable 3M medical tape supporting substrate. As the mechanical strength of the PVA hydrogel is ionically responsive due to Hofmeister effects, the hardness of the resultant microneedle tips can be upregulated by sulfate ions to ensure skin penetration and be softened by nitrate ions after tip-substrate detachment to adapt to the surrounding tissue and release exosomes. Because the MSC-exosomes can effectively activate fibroblasts, vascular endothelial cells, and macrophages, the indwelling microneedles are demonstrated with the function of promoting tissue regeneration and diabetic wound healing in full-thickness cutaneous wounds of diabetic rat models. These features indicate that the bioinspired adaptable indwelling microneedles are with practical values and clinical prospects in tissue and wound regeneration.

SARS-CoV-2 viral protein Nsp2 stimulates translation under normal and hypoxic conditions

When viruses like SARS-CoV-2 infect cells, they reprogram the repertoire of cellular and viral transcripts that are being translated to optimize their strategy of replication, often targeting host translation initiation factors, particularly eIF4F complex consisting of eIF4E, eIF4G and eIF4A. A proteomic analysis of SARS-CoV-2/human proteins interaction revealed viral Nsp2 and initiation factor eIF4E2, but a role of Nsp2 in regulating translation is still controversial. HEK293T cells stably expressing Nsp2 were tested for protein synthesis rates of synthetic and endogenous mRNAs known to be translated via cap- or IRES-dependent mechanism under normal and hypoxic conditions. Both cap- and IRES-dependent translation were increased in Nsp2-expressing cells under normal and hypoxic conditions, especially mRNAs that require high levels of eIF4F. This could be exploited by the virus to maintain high translation rates of both viral and cellular proteins, particularly in hypoxic conditions as may arise in SARS-CoV-2 patients with poor lung functioning.

Robust Portfolio Optimization Strategies in The Serbian Stock Market

Research Question: This paper investigates the performances of six portfolios constructed using robust optimization methods in the Serbian stock market. Motivation: Motivated by the lack of research that analyses the allocation strategies based on robust optimization in the other non-US markets, this paper analyses the ability of these strategies to produce positive performance in the Serbian financial market. Idea: This paper aims to check whether robust strategies can provide positive risk-adjusted performance compared to simple strategies. Data: The analysis was performed on daily data from 2017 to 2020. Tools: We used monthly portfolio rebalancing with an estimation period of 24 months, applying budget and no-short selling constraints in portfolio construction. As a benchmark, we used two simple strategies, the strategy of market index replication and the equal weighting strategy (1/N). Consequently, the performance of the portfolios is evaluated once a month and calculated for the entire investment period. Findings: Empirical results suggest that robust optimization methods improve portfolio performance on a risk-adjusted basis. The increase in performance is affected by an increase in turnover, so the stability of weights in the portfolio depends on the compliance of the model characteristics with the conditions prevailing in the market. Contribution: To the best of our knowledge, this is the first article that analyses the performance of robust optimization portfolios for the Serbian stock markets. Analysing the performance of robust optimization strategies and comparing them to two simple strategies, this paper contributes to the existing literature by checking their possibility of obtaining a positive performance in less developed markets. Additionally, all information presented in this paper could help investors optimize their risk allocation and profitability.

Short Communication: A Primer on Perpetuals

We consider a continuous-time financial market with no arbitrage and no transactions costs. In this setting, we introduce two types of perpetual contracts, one in which the payoff to the long side is a fixed function of the underlyers and the long side pays a funding rate to the short side, the other in which the payoff to the long side is a fixed function of the underlyers times a discount factor that changes over time but no funding payments are required. Assuming asset prices are continuous and strictly positive, we derive model-free expressions for the funding rate and discount rate of these perpetual contracts as well as replication strategies for the short side. When asset prices can jump, we derive expressions for the funding and discount rates, which are semirobust in the sense that they do not depend on the dynamics of the volatility process of the underlying risky assets, but do depend on the intensity of jumps under the market’s pricing measure. When asset prices can jump and the volatility process is independent of the underlying risky assets, we derive an explicit replication strategy for the short side of a perpetual contract. Throughout the paper, we illustrate through examples how specific perpetual contracts relate to traditional financial instruments such as variance swaps and leveraged exchange traded funds.

USP1-Associated Factor 1 Modulates Japanese Encephalitis Virus Replication by Governing Autophagy and Interferon-Stimulated Genes.

Japanese encephalitis virus (JEV) is a typical mosquito-borne flavivirus that can cause central nervous system diseases in humans and animals. Host factors attempt to limit virus replication when the viruses invade the host by using various strategies for replication. It is essential to clarify the host factors that affect the life cycle of JEV and explore its underlying mechanism. Here, we found that USP1-associated factor 1 (UAF1; also known as WD repeat-containing protein 48) modulated JEV replication. We found that JEV propagation significantly increased in UAF1-depleted Huh7 cells. Moreover, we found that knockdown of UAF1 activated cell autophagic flux in further functional analysis. Subsequently, we demonstrated that autophagy can be induced by JEV, which promotes viral replication by inhibiting interferon-stimulated gene (ISG) expression in Huh7 cells. The knockdown of UAF1 reduced ISG expression during JEV infection. To explore the possible roles of autophagy in UAF1-mediated inhibition of JEV propagation, we knocked out ATG7 to generate autophagy-deficient cells and found that depletion of UAF1 failed to promote JEV replication in ATG7 knockout cells. Moreover, in ATG7-deficient Huh7 cells, interference with UAF1 expression did not lead to the induction of autophagy. Taken together, these findings indicate that UAF1 is a critical regulator of autophagy and reveal a mechanism by which UAF1 knockdown activates autophagy to promote JEV replication. IMPORTANCE Host factors play an essential role in virus replication and pathogenesis. Although UAF1 is well known to form complexes with ubiquitin-specific proteases, little is known about the function of the UAF1 protein itself. In this study, we confirmed that UAF1 is involved in JEV replication. Notably, we discovered a novel function for UAF1 in regulating autophagy. Furthermore, we demonstrated that UAF1 modulated JEV replication through its autophagy regulation. This study is the first description of the novel function of UAF1 in regulating autophagy, and it clarifies the underlying mechanism of the antiviral effect of UAF1 against JEV. These results provide a new mechanistic insight into the functional annotation of UAF1 and provide a potential target for increasing virus production during vaccine production.

Data Replication and Placement Strategies in Distributed Systems: A State of the Art Survey

Data Replication and Placement Strategies in Distributed Systems: A State of the Art Survey

Exploring the Mycovirus Universe: Identification, Diversity, and Biotechnological Applications

Viruses that infect fungi are known as mycoviruses and are characterized by the lack of an extracellular phase. In recent years, the advances on nucleic acids sequencing technologies have led to a considerable increase in the number of fungi-infecting viral species described in the literature, with a special interest in assessing potential applications as fungal biocontrol agents. In the present study, we performed a comprehensive review using Scopus, Web of Science, and PubMed databases to mine mycoviruses data to explore their molecular features and their use in biotechnology. Our results showed the existence of 267 mycovirus species, of which 189 are recognized by the International Committee on Taxonomy of Viruses (ICTV). The majority of the mycoviruses identified have a dsRNA genome (38.6%), whereas the Botourmiaviridae (ssRNA+) alone represents 14% of all mycoviruses diversity. Regarding fungal hosts, members from the Sclerotinicaeae appeared as the most common species described to be infected by mycoviruses, with 16 different viral families identified so far. It is noteworthy that such results are directly associated with the high number of studies and strategies used to investigate the presence of viruses in members of the Sclerotinicaeae family. The knowledge about replication strategy and possible impact on fungi biology is available for only a small fraction of the mycoviruses studied, which is the main limitation for considering these elements potential targets for biotechnological applications. Altogether, our investigation allowed us to summarize the general characteristics of mycoviruses and their hosts, the consequences, and the implications of this knowledge on mycovirus-fungi interactions, providing an important source of information for future studies.

Benchmarks for the benchmark approach to valuing long-term insurance liabilities: comment on Fergusson &amp; Platen (2023)

AbstractThis article comments on the paper “Less-expensive long-term annuities linked to mortality, cash and equity” by Kevin Fergusson and Eckard Platen, appearing in this issue of theAnnals of Actuarial Science. It adds two perspectives to their thought-provoking contribution. The first is a similarity to some recent work in quantitative finance on “deep hedging” that leverages machine learning models to find the cheapest replication strategy for a derivative payoff in a largely model-free setting. The second perspective engages with some of the interesting implications of their approach and draws parallels to literature in asset pricing and macro-finance. These perspectives point to the potential need for more fundamental shifts than the authors of the paper are advertising.

Effect of temperature and IRF-9 gene-knockout on dynamics of vRNA, cRNA, and mRNA of viral hemorrhagic septicemia virus (VHSV)

The replication of viral hemorrhagic septicemia virus (VHSV) in appropriate host cells depends on environmental factors and the host cell's immunity. The dynamics of each VHSV RNA strand (vRNA, cRNA, and mRNA) in different conditions can provide a clue on the viral replication strategies, which can be a base for the development of efficient control measures. As VHSV is known to be sensitive to temperature and type I interferon (IFN) responses, in this study, we analyzed the effect of temperature difference (15 °C and 20 °C) and IRF-9 gene knockout on the dynamics of the three VHSV RNA strands in Epithelioma papulosum cyprini (EPC) cells using a strand-specific RT-qPCR. The tagged primers designed in this study successfully worked to quantify the three strands of VHSV. In the results of the temperature effect, the higher speed in viral mRNA transcription and the significantly higher (more than 10 times at 12–36 h) copy number of cRNA at 20 °C compared to those at 15 °C suggested the positive effect of high temperature on VHSV replication. In the results of the IRF-9 gene knockout effect, although IRF-9 gene knockout did not bring a dramatic effect on VHSV replication compared to the temperature effect, the increase of mRNA in IRF-9 KO cells was faster than normal EPC cells, which was reflected in the copy numbers of cRNA and vRNA. The IRF-9 gene knockout effect was not dramatic even in the replication of rVHSV-ΔNV-eGFP that harbors eGFP gene ORF instead of NV gene ORF. These results suggest that VHSV may be highly susceptible to pre-activated type I IFN responses but not highly susceptible to post-infection-mediated type I IFN responses or lowered type I IFN before infection. In both experiments of temperature effect and IRF-9 gene knockout effect, the copy number of cRNA never exceeded the copy number of vRNA at all assay times, suggesting that the binding efficiency of the RNP complex to the 3′ end of cRNA might be lower than that to the 3′ end of vRNA. Further research is needed to elucidate the regulatory mechanism that limits the amount of cRNA at an appropriate level during VHSV replication.