Isolation of Pulmonary Artery Smooth Muscle Cells from Neonatal Mice

Pulmonary hypertension is a significant cause of morbidity and mortality in infants. Historically, there has been significant study of the signaling pathways involved in vascular smooth muscle contraction in PASMC from fetal sheep. While sheep make an excellent model of term pulmonary hypertension, they are very expensive and lack the advantage of genetic manipulation found in mice. Conversely, the inability to isolate PASMC from mice was a significant limitation of that system. Here we described the isolation of primary cultures of mouse PASMC from P7, P14, and P21 mice using a variation of the previously described technique of Marshall et al.²⁶ that was previously used to isolate rat PASMC. These murine PASMC represent a novel tool for the study of signaling pathways in the neonatal period. Briefly, a slurry of 0.5% (w/v) agarose + 0.5% iron particles in M199 media is infused into the pulmonary vascular bed via the right ventricle (RV). The iron particles are 0.2 μM in diameter and cannot pass through the pulmonary capillary bed. Thus, the iron lodges in the small pulmonary arteries (PA). The lungs are inflated with agarose, removed and dissociated. The iron-containing vessels are pulled down with a magnet. After collagenase (80 U/ml) treatment and further dissociation, the vessels are put into a tissue culture dish in M199 media containing 20% fetal bovine serum (FBS), and antibiotics (M199 complete media) to allow cell migration onto the culture dish. This initial plate of cells is a 50-50 mixture of fibroblasts and PASMC. Thus, the pull down procedure is repeated multiple times to achieve a more pure PASMC population and remove any residual iron. Smooth muscle cell identity is confirmed by immunostaining for smooth muscle myosin and desmin.     

Prostaglandin D2 and its metabolites induce caspase-dependent granulocyte apoptosis that is mediated via inhibition of I kappa B alpha degradation using a peroxisome proliferator-activated receptor-gamma-independent mechanism

Many inflammatory mediators retard granulocyte apoptosis. Most natural PGs studied herein (e.g., PGE(2), PGA(2), PGA(1), PGF(2 alpha)) either delayed apoptosis or had no effect, whereas PGD(2) and its metabolite PGJ(2) selectively induced eosinophil, but not neutrophil apoptosis. This novel proapoptotic effect does not appear to be mediated via classical PG receptor ligation or by elevation of intracellular cAMP or Ca(2+). Intriguingly, the sequential metabolites Delta(12)PGJ(2) and 15-deoxy-Delta(12,) Delta(14)-PGJ(2) (15dPGJ(2)) induced caspase-dependent apoptosis in both granulocytes, an effect that did not involve de novo protein synthesis. Despite the fact that Delta(12)PGJ(2) and 15dPGJ(2) are peroxisome proliferator-activated receptor-gamma (PPAR-gamma) activators, apoptosis was not mimicked by synthetic PPAR-gamma and PPAR-alpha ligands or blocked by an irreversible PPAR-gamma antagonist. Furthermore, Delta(12)PGJ(2) and 15dPGJ(2) inhibited LPS-induced I kappa B alpha degradation and subsequent inhibition of neutrophil apoptosis, suggesting that apoptosis is mediated via PPAR-gamma-independent inhibition of NF-kappa B activation. In addition, we show that TNF-alpha-mediated loss of cytoplasmic I kappa B alpha in eosinophils is inhibited by 15dPGJ(2) in a concentration-dependent manner. The selective induction of eosinophil apoptosis by PGD(2) and PGJ(2) may help define novel therapeutic pathways in diseases in which it would be desirable to specifically remove eosinophils but retain neutrophils for antibacterial host defense. The powerful proapoptotic effects of Delta(12)PGJ(2) and 15dPGJ(2) in both granulocyte types suggest that these natural products control the longevity of key inflammatory cells and may be relevant to understanding the control and resolution of inflammation.     

Variation in insect damage and growth in Eucalyptus globulus

Abstract

• 1 Objectives of this study were to examine (i) between‐provenance variation in susceptibility to insects in Eucalyptus globulus and (ii) relationships between insect damage and tree growth. We planted seedlings of 18 provenances of E. globulus from south‐east Australia in a field trial and measured tree growth and insect damage.
• 2 Christmas beetles Anoplognathus spp. were the dominant herbivores during this experiment, and 99% of trees were affected by them. Defoliation of individual trees by Anoplognathus spp. ranged from 0% to 85%.
• 3 The main results of this study were that: (i) provenances of E. globulus from Tasmania and the Bass Strait islands, which had previously shown resistance to autumn gum moth Mnesampela privata and leaf blister sawfly Phylacteophaga froggatti tended to be resistant to Anoplognathus spp.; (ii) mean tree volume was reduced by herbivory; and (iii) the volume‐based performance ranking of provenances changed depending on the probability of insect outbreaks.
• 4 Fast‐growing provenances should be planted in optimal growing areas for E. globulus with low probability of insect outbreaks. However, in suboptimal growing areas, planting slightly slower growing but more resistant provenances is likely to result in greater output than planting fast‐growing provenances when the probability of insect outbreaks is high.

     

Collection of wind-borne haematophagous insects in the Torres Strait,Australia

Circumstantial evidence has implicated wind-borne mosquitoes (Diptera: Culicidae) in the introduction of Japanese encephalitis (JE) virus into Australia from the New Guinea mainland. A study was initiated on Saibai Island in the northern Torres Strait, during January and February 2000, to identify the potential source of insects collected in aerial (kytoon) and surface-level traps. Wind speed and direction were recorded to determine wind profiles during insect sampling. Northerly winds capable of carrying insects from New Guinea to Saibai Island were only present on three out of 18 nights sampled. Only three male mosquitoes, comprising two Verrallina funerea (Theobald) and one Ochlerotatus vigilax (Skuse), were collected in aerial samples, and were most likely of local origin. Culicoides midges were also collected in aerial nets and included gravid/parous C. bundyensis Lee and Reye, and one parous C. histrio Johannsen. Highest densities of arthropods (up to 1562/million m3) were on 30 January 2000 when NW winds, sustained for six hours, probably introduced midges from the New Guinea mainland. Adult mosquitoes (including three female Ve. funerea and a single female Ficalbia) and Culicoides (including two gravid C. bundyensis and one parous C. cordiger Macfie) were also collected in 2 m high mast nets during northerly surface winds. Although the results do not provide evidence that wind-blown mosquitoes introduced JE from New Guinea into Australia, they do not preclude that strong N winds associated with low pressure systems SW of the Torres Strait could have done so. However, results suggest that Culicoides were more likely than mosquitoes to reach high altitude and travel long distances during the light N winds experienced during the study.     

Flexible Modeling of Epidemics with an Empirical Bayes Framework

Seasonal influenza epidemics cause consistent, considerable, widespread loss annually in terms of economic burden, morbidity, and mortality. With access to accurate and reliable forecasts of a current or upcoming influenza epidemic’s behavior, policy makers can design and implement more effective countermeasures. This past year, the Centers for Disease Control and Prevention hosted the “Predict the Influenza Season Challenge”, with the task of predicting key epidemiological measures for the 2013–2014 U.S. influenza season with the help of digital surveillance data. We developed a framework for in-season forecasts of epidemics using a semiparametric Empirical Bayes framework, and applied it to predict the weekly percentage of outpatient doctors visits for influenza-like illness, and the season onset, duration, peak time, and peak height, with and without using Google Flu Trends data. Previous work on epidemic modeling has focused on developing mechanistic models of disease behavior and applying time series tools to explain historical data. However, tailoring these models to certain types of surveillance data can be challenging, and overly complex models with many parameters can compromise forecasting ability. Our approach instead produces possibilities for the epidemic curve of the season of interest using modified versions of data from previous seasons, allowing for reasonable variations in the timing, pace, and intensity of the seasonal epidemics, as well as noise in observations. Since the framework does not make strict domain-specific assumptions, it can easily be applied to some other diseases with seasonal epidemics. This method produces a complete posterior distribution over epidemic curves, rather than, for example, solely point predictions of forecasting targets. We report prospective influenza-like-illness forecasts made for the 2013–2014 U.S. influenza season, and compare the framework’s cross-validated prediction error on historical data to that of a variety of simpler baseline predictors.