A simulation model of the Devils Hole pupfish population using monthly length-frequency distributions

The Devils Hole pupfish, Cyprinodon diabolis, is a federally-endangered fish that is endemic to Devils Hole, a discontiguous part of Death Valley National Park in Nye County, Nevada. Due to its status, Devils Hole pupfish monitoring must be non-obtrusive and thereby exclude techniques that require handling fish. Due to a recent decline in pupfish abundance, Devils Hole pupfish managers have expressed a need for a model that describes population dynamics. This population model would be used to identify vulnerable life history stage(s) and inform management actions. We constructed a set of individualbased simulation models designed to explore effects of population processes and evaluate assumptions. We developed a baseline model, whose output best resembled both observed length-frequency data and predicted intraannual abundance patterns. We then ran simulations with 5 % increases in egg-larval, juvenile, and adult survival rates to better understand Devils Hole pupfish life history, thereby helping identify vulnerable life history stages that should become the target of management actions. Simulation models with temporally constant adult, juvenile, and egg-larval survival rates were able to reproduce observed length-frequency distributions and predicted intra-annual population patterns. In particular, models with monthly adult and juvenile survival rates of 80 % and an egg-larval survival rate of 4.7 % replicated patterns in observed data. Population growth was most affected by 5 % increases in egg-larval survival, whereas adult and juvenile survival rates had similar but lesser effects on population growth. Outputs from the model were used to assess factors suspected of influencing Devils Hole pupfish population decline

An observational study on the expression levels of MDM2 and MDMX proteins, and associated effects on P53 in a series of human liposarcomas

Background: Inactivation of wild type P53 by its main cellular inhibitors (MDM2 and MDMX) is a well recognised feature of tumour formation in liposarcomas. MDM2 over-expression has been detected in approximately 80% of liposarcomas but only limited information is available about MDMX over-expression. To date, we are not aware of any study that has described the patterns of MDM2 and MDMX co-expression in liposarcomas. Such information has become more pertinent as various novel MDM2 and/or MDMX single and dual affinity antagonist compounds are emerging as an alternative approach for potential targeted therapeutic strategies. Methods. We analysed a case series of 61 fully characterized liposarcomas of various sub-types by immunohistochemistry, to assess the expression levels of P53, MDM2 and MDMX, simultaneously. P53 sequencing was performed in all cases that expressed P53 protein in 10% or more of cells to rule out mutation-related over-expression. Results: 50 cases over-expressed MDM2 and 42 of these co-expressed MDMX at varying relative levels. The relative expression levels of the two proteins with respect to each other were subtype-dependent. This apparently affected the detected levels of P53 directly in two distinct patterns. Diminished levels of P53 were observed when MDM2 was significantly higher in relation to MDMX, suggesting a dominant role for MDM2 in the degradation of P53. Higher levels of P53 were noted with increasing MDMX levels suggesting an interaction between MDM2 and MDMX that resulted in a reduced efficiency of MDM2 in degrading P53. Of the 26 cases of liposarcoma with elevated P53 expression, 5 were found to have a somatic mutation in the P53 gene. Conclusions: The results suggest that complex dynamic interactions between MDM2 and MDMX proteins may directly affect the cellular levels of P53. This therefore suggests that careful characterization of both these markers will be necessary in tumours when considering in vivo evaluation of novel blocker compounds for MDM proteins, as a therapeutic strategy to restore wild type P53 function