IFN-alpha and IFN-beta levels in sera of patients and healthy donors were analyzed

by enzyme linked immunosorbent assay. It was found that healthy women did not show a change of gene expression levels from the second trimester until postpartum, yet some type I IFN-inducible genes were significantly upregulated in pregnant and postpartum women compared with nonpregnant individuals. In patients with RA, a pronounced upregulation of IFI35 and IFI44 at the second trimester and a peak expression of Siglec1 at the third trimester were observed. Pregnancy levels of IFI35 and IFI44 in patients with RA were higher than those of nonpregnant patients with RA. No significant association of gene expression levels with disease activity was found. In the sera of patients and healthy women, GSK3326595 IFN-beta was undetectable GS 1101 and IFN-alpha levels remained stable throughout pregnancy and postpartum. Thus, pregnancy can give rise to an increased expression of type I IFN-inducible genes, reflecting an upregulation of the innate immune system. However, an association of type I IFN-inducible genes with pregnancy induced disease amelioration seems unlikely.”
“Genetic analysis of pathogen genomes is a powerful approach to investigating the population dynamics and epidemic history of infectious diseases. However, the theoretical underpinnings of the most widely used, coalescent

methods have been questioned, casting doubt on their interpretation. The aim of this study is to develop robust population genetic inference for compartmental models in epidemiology. Using a general approach based on the theory of metapopulations, we derive coalescent models under susceptible-infectious (SI), susceptible-infectious-susceptible (SIS) and susceptible-infectious-recovered (SIR) dynamics. We show that exponential and logistic growth models are equivalent to SI and SIS models, respectively, when co-infection is negligible. Implementing

SI, SIS and SIR models in BEAST, we conduct a meta-analysis of hepatitis C epidemics, and show that we can directly estimate the basic reproductive number (R-0) and prevalence under SIR dynamics. We find that differences in genetic diversity between epidemics can be explained by differences Protein Tyrosine Kinase inhibitor in underlying epidemiology (age of the epidemic and local population density) and viral subtype. Model comparison reveals SIR dynamics in three globally restricted epidemics, but most are better fit by the simpler SI dynamics. In summary, metapopulation models provide a general and practical framework for integrating epidemiology and population genetics for the purposes of joint inference.”
“The weed flora associated with rice crop in the coastal region of Peninsular Malaysia was studied. Through this research the competitive and harmful weeds of rice were identified, which could be helpful in planning their effective control and management.