Hematopoietic tissue of Macrobrachium rosenbergii plays dual roles as a source of hemocyte hematopoiesis and as a defensive mechanism against Macrobrachium rosenbergii nodavirus infection
FISH & SHELLFISH IMMUNOLOGY
Authors: Jariyapong, Pitchanee; Pudgerd, Arnon; Cheloh, Nifareesa; Hirono, Ikuo; Kondo, Hidehiro; Vanichviriyakit, Rapeepun; Weerachatyanukul, Wattana; Chotwiwatthanakun, Charoonroj
Abstract
White tail disease caused by Macrobrachium rosenbergii nodavirus (MrNV) infection takes place only in nauplii, not adults, of M. rosenbergii prawn. Hemocyte homeostasis and immune-related functions derived from the hematopoietic tissue (Hpt) in adult prawn are presumed to play roles in resisting viral infection. To elucidate the role of the Hpt cell response to MrNV, a comparative transcriptome analysis was performed with MrNV-infected prawn at various time intervals. The results showed that there were 462 unigenes that were differentially expressed between mock and infected samples. BlastX sequence analysis revealed that two proteins, crustacean hematopoietic factor (CHF) and cell growth-regulating zinc finger protein (Lyar), are involved in hemocyte hematopoiesis and are up-regulated during MrNV infection. In fact, genes involved in cell growth regulation and immunity were highly expressed at 6 h and decreased within 24 h post-infection. Localization studies in the Hpt tissue revealed the presence of anti-lipopolysaccharide factor (ALF) and CHF mRNAs in Hpt cells. Considering these findings, we concluded that resistance to MrNV infection in adult prawn is due to an increase in humoral immune factors and the acceleration of hemocyte homeostasis by the dual roles of the Hpt organ in M. rosenbergii.
Life Years at Risk: A Population Health Measure from a Prevention Perspective
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
Authors: Zhao, Yuejen; Malyon, Rosalyn
Abstract
This paper aims to present life years at risk ( LYAR), a new measure of population health needs for primary, secondary and tertiary prevention, which classifies health outcomes by care type and distinguishes between positive and negative outcomes. It is determined by the probability of ill-health event, population size and life years lost, based on expected incidence, prevalence and mortality. The LYAR consists of two components: the observed LYAR, available using disability adjusted life years, and the avoided LYAR. Three examples are given to illustrate the calculation and application of the measure. The advantages, disadvantages and policy implications are also discussed.
COA
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