Co-expression network analysis identifies innate immune signatures for Albizia julibrissin saponin active fraction-adjuvanted avian influenza vaccine

2021 ◽  
Vol 93 ◽  
pp. 107417
Author(s):  
Jing Du ◽  
Hongxiang Sun
Keyword(s):  
Network Analysis ◽  
Avian Influenza ◽  
Influenza Vaccine ◽  
Innate Immune ◽  
Active Fraction ◽  
Albizia Julibrissin ◽  
Immune Signatures

Effects of Ligands for Toll-Like Receptors 3, 4, and 21 as Adjuvants on the Immunogenicity of an Avian Influenza Vaccine in Chickens

2014 ◽  
Vol 27 (4) ◽  
pp. 167-173 ◽  
Author(s):  
Michael St. Paul ◽  
Neda Barjesteh ◽  
Jennifer T. Brisbin ◽  
Alexander Ian Villaneueva ◽  
Leah R. Read ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Influenza Vaccine ◽  
Toll Like Receptors

scholarly journals 1438Dynamics of inter-farm transmission of highly pathogenic avian influenza integrating vehicle movements and phylogenetic information

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Dae-sung Yoo ◽  
Chun Byung Chul
Keyword(s):  
Network Analysis ◽  
Avian Influenza ◽  
Highly Pathogenic Avian Influenza ◽  
Control Strategies ◽  
Poultry Production ◽  
Movement Restriction ◽  
Phylogenetic Information ◽  
Highly Pathogenic ◽  
Pathogenic Avian Influenza ◽  
And Control

Abstract Background Highly pathogenic avian influenza (HPAI), a zoonotic infectious disease, has been considered a severe threat to public health. The fundamental prevention and control strategy against HPAI includes minimizing the outbreaks of poultry holdings where the virus primarily spreads through animal trade and poultry production associated vehicle movement (PPVM). However, very few attempts have been made to elucidate the association between PPVM and HPAI transmission compared to studies on poultry trade. Therefore, our study aimed to elucidate the role of PPVM on HPAI transmission. Methods We performed network analysis using PPVM data based on a global positioning system (GPS), with phylogenetic information of the HPAI virus for reliable estimation. Moreover, the contribution of PPVM to HPAI infection was estimated by Bayesian inference. Results The network analysis revealed that the connection via PPVM between the same genetic group of infected premises (IPs) was more prevalent than that of different genotype IPs. Moreover, the similarity of farm poultry species and the overlapped integrators between inter-linked IPs was associated with potential transmission route formation. Additionally, the contribution of PPVM among phylogenetically clustered IPs was estimated to have 28.25% of HPAI infections in IPs on average. Conclusions HPAI control strategies including targeted movement restriction and standstill should be established against the HPAI transmission via PPVM. Key messages This is a solid and novel study depicting the need for combining epidemiological analysis with data regarding molecular epidemiology of pathogens.

scholarly journals Nasal delivery of H5N1 avian influenza vaccine formulated with GenJet™ or in vivo-jetPEI® induces enhanced serological, cellular and protective immune responses

Drug Delivery ◽  
2018 ◽  
Vol 25 (1) ◽  
pp. 773-779 ◽  
Author(s):  
Weiping Cao ◽  
Margarita Mishina ◽  
Samuel Amoah ◽  
Wadzanai P. Mboko ◽  
Caitlin Bohannon ◽  
...  
Keyword(s):  
Avian Influenza ◽  
Immune Responses ◽  
Influenza Vaccine ◽  
Nasal Delivery ◽  
H5n1 Avian Influenza

scholarly journals Identifying novel biomarkers of the pediatric influenza infection by weighted co-expression network analysis

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Mohadeseh Zarei Ghobadi ◽  
Sayed-Hamidreza Mozhgani ◽  
Mahdieh Farzanehpour ◽  
Farida Behzadian
Keyword(s):  
Immune System ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Drug Targets ◽  
Protein Targeting ◽  
Influenza Infection ◽  
Innate Immune ◽  
Differentially Expressed ◽  
Complex Interactions ◽  
Novel Biomarkers

Abstract Background Despite the high yearly prevalence of Influenza, the pathogenesis mechanism and involved genes have not been fully known. Finding the patterns and mapping the complex interactions between different genes help us to find the possible biomarkers and treatment targets. Methods Herein, weighted gene co-expression network analysis (WGCNA) was employed to construct a co-expression network among genes identified by microarray analysis of the pediatric influenza-infected samples. Results Three of the 38 modules were found as the most related modules to influenza infection. At a functional level, we found that the genes in these modules regulate the immune responses, protein targeting, and defense to virus. Moreover, the analysis of differentially expressed genes disclosed 719 DEGs between the normal and infected subjects. The comprehensive investigation of genes in the module involved in immune system and viral defense (yellow module) revealed that SP110, HERC5, SAMD9L, RTP4, C19orf66, HELZ2, EPSTI1, and PHF11 which were also identified as DEGs (except C19orf66) have the potential to be as the biomarkers and also drug targeting for the treatment of pediatric influenza. Conclusions The WGCN analysis revealed co-expressed genes which were involved in the innate immune system and defense to virus. The differentially expressed genes in the identified modules can be considered for designing drug targets. Moreover, modules can help to find pathogenesis routes in the future.

Sign in / Sign up

Export Citation Format

Share Document