Are the native giant tortoises from the Seychelles really extinct? A genetic perspective based on mtDNA and microsatellite data.

The extinction of the giant tortoises of the Seychelles Archipelago has long been suspected but is not beyond doubt. A recent morphological study of the giant tortoises of the western Indian Ocean concluded that specimens of two native Seychelles species survive in captivity today alongside giant tortoises of Aldabra, which are numerous in zoos as well as in the wild. This claim has been controversial because some of the morphological characters used to identify these species, several measures of carapace morphology, are reputed to be quite sensitive to captive conditions. Nonetheless, the potential survival of giant tortoise species previously thought extinct presents an exciting scenario for conservation. We used mitochondrial DNA sequences and nuclear microsatellites to examine the validity of the rediscovered species of Seychelles giant tortoises. Our results indicate that the morphotypes suspected to represent Seychelles species do not show levels of variation and genetic structuring consistent with long periods of reproductive isolation. We found no variation in the mitochondrial control region among 55 individuals examined and no genetic structuring in eight microsatellite loci, pointing to the survival of just a single lineage of Indian Ocean tortoises.

Cardiac beta ARK1 inhibition prolongs survival and augments beta blocker therapy in a mouse model of severe heart failure.

Chronic human heart failure is characterized by abnormalities in beta-adrenergic receptor (betaAR) signaling, including increased levels of betaAR kinase 1 (betaARK1), which seems critical to the pathogenesis of the disease. To determine whether inhibition of betaARK1 is sufficient to rescue a model of severe heart failure, we mated transgenic mice overexpressing a peptide inhibitor of betaARK1 (betaARKct) with transgenic mice overexpressing the sarcoplasmic reticulum Ca(2+)-binding protein, calsequestrin (CSQ). CSQ mice have a severe cardiomyopathy and markedly shortened survival (9 +/- 1 weeks). In contrast, CSQ/betaARKct mice exhibited a significant increase in mean survival age (15 +/- 1 weeks; P < 0.0001) and showed less cardiac dilation, and cardiac function was significantly improved (CSQ vs. CSQ/betaARKct, left ventricular end diastolic dimension 5.60 +/- 0.17 mm vs. 4.19 +/- 0.09 mm, P < 0.005; % fractional shortening, 15 +/- 2 vs. 36 +/- 2, P < 0.005). The enhancement of the survival rate in CSQ/betaARKct mice was substantially potentiated by chronic treatment with the betaAR antagonist metoprolol (CSQ/betaARKct nontreated vs. CSQ/betaARKct metoprolol treated, 15 +/- 1 weeks vs. 25 +/- 2 weeks, P < 0.0001). Thus, overexpression of the betaARKct resulted in a marked prolongation in survival and improved cardiac function in a mouse model of severe cardiomyopathy that can be potentiated with beta-blocker therapy. These data demonstrate a significant synergy between an established heart-failure treatment and the strategy of betaARK1 inhibition.

Neuronal Survival of the Fittest: The Importance of Aerobic Capacity in Exercise-Induced Neurogenesis and Cognition

It is commonly accepted that aerobic exercise increases hippocampal neurogenesis, learning and memory, as well as stress resiliency. However, human populations are widely variable in their inherent aerobic fitness as well as their capacity to show increased aerobic fitness following a period of regimented exercise. It is unclear whether these inherent or acquired components of aerobic fitness play a role in neurocognition. To isolate the potential role of inherent aerobic fitness, we exploited a rat model of high (HCR) and low (LCR) inherent aerobic capacity for running. At a baseline, HCR rats have two- to three-fold higher aerobic capacity than LCR rats. We found that HCR rats also had two- to three- fold more young neurons in the hippocampus than LCR rats as well as rats from the heterogeneous founder population. We then asked whether this enhanced neurogenesis translates to enhanced hippocampal cognition, as is typically seen in exercise-trained animals. Compared to LCR rats, HCR rats performed with high accuracy on tasks designed to test neurogenesis-dependent pattern separation ability by examining investigatory behavior between very similar objects or locations. To investigate whether an aerobic response to exercise is required for exercise-induced changes in neurogenesis and cognition, we utilized a rat model of high (HRT) and low (LRT) aerobic response to treadmill training. At a baseline, HRT and LRT rats have comparable aerobic capacity as measured by a standard treadmill fit test, yet after a standardized training regimen, HRT but not LRT rats robustly increase their aerobic capacity for running. We found that sedentary LRT and HRT rats had equivalent levels of hippocampal neurogenesis, but only HRT rats had an elevation in the number of young neurons in the hippocampus following training, which was positively correlated with accuracy on pattern separation tasks. Taken together, these data suggest that a significant elevation in aerobic capacity is necessary for exercise-induced hippocampal neurogenesis and hippocampal neurogenesis-dependent learning and memory. To investigate the potential for high aerobic capacity to be neuroprotective, doxorubicin chemotherapy was administered to LCR and HCR rats. While doxorubicin induces a progressive decrease in aerobic capacity as well as neurogenesis, HCR rats remain at higher levels on those measures compared to even saline-treated LCR rats. HCR and LCR rats that received exercise training throughout doxorubicin treatment demonstrated positive effects of exercise on aerobic capacity and neurogenesis, regardless of inherent aerobic capacity. Overall, these findings demonstrate that inherent and acquired components of aerobic fitness play a crucial role not only in the cardiorespiratory system but also the fitness of the brain.

Application of a rank-based genetic association test to age-at-onset data from the Collaborative Study on the Genetics of Alcoholism study.

Association studies of quantitative traits have often relied on methods in which a normal distribution of the trait is assumed. However, quantitative phenotypes from complex human diseases are often censored, highly skewed, or contaminated with outlying values. We recently developed a rank-based association method that takes into account censoring and makes no distributional assumptions about the trait. In this study, we applied our new method to age-at-onset data on ALDX1 and ALDX2. Both traits are highly skewed (skewness > 1.9) and often censored. We performed a whole genome association study of age at onset of the ALDX1 trait using Illumina single-nucleotide polymorphisms. Only slightly more than 5% of markers were significant. However, we identified two regions on chromosomes 14 and 15, which each have at least four significant markers clustering together. These two regions may harbor genes that regulate age at onset of ALDX1 and ALDX2. Future fine mapping of these two regions with densely spaced markers is warranted.

Simulation of mackerel (Scomber scombrus) recruitment with an individual-based model and comparison with field data

An individual-based model (IBM) for the simulation of year-to-year survival during the early life-history stages of the north-east Atlantic stock of mackerel (Scomber scombrus) was developed within the EU funded Shelf-Edge Advection, Mortality and Recruitment (SEAMAR) programme. The IBM included transport, growth and survival and was used to track the passive movement of mackerel eggs, larvae and post-larvae and determine their distribution and abundance after approximately 2 months of drift. One of the main outputs from the IBM, namely distributions and numbers of surviving post-larvae, are compared with field data as recruit (age-0/age-1 juveniles) distribution and abundance for the years 1998, 1999 and 2000. The juvenile distributions show more inter-annual and spatial variability than the modelled distributions of survivors; this may be due to the restriction of using the same initial egg distribution for all 3 yr of simulation. The IBM simulations indicate two main recruitment areas for the north-east Atlantic stock of mackerel, these being Porcupine Bank and the south-eastern Bay of Biscay. These areas correspond to areas of high juvenile catches, although the juveniles generally have a more widespread distribution than the model simulations. The best agreement between modelled data and field data for distribution (juveniles and model survivors) is for the year 1998. The juvenile catches in different representative nursery areas are totalled to give a field abundance index (FAI). This index is compared with a model survivor index (MSI) which is calculated from the total of survivors for the whole spawning season. The MSI compares favourably with the FAI for 1998 and 1999 but not for 2000; in this year, juvenile catches dropped sharply compared with the previous years but there was no equivalent drop in modelled survivors.

Failure to Achieve PSA Level ≤I ng/ml Following Neo-Adjuvant LHRHa Therapy Predicts for a Lower Biochemical Control Rate and Overall Survival in Localized Prostate Cancer Treated with Radiotherapy

PURPOSE: To investigate whether failure to suppress the prostate-specific antigen (PSA) level to /=2 months of neoadjuvant luteinizing hormone-releasing hormone agonist therapy in patients scheduled to undergo external beam radiotherapy for localized prostate carcinoma is associated with reduced biochemical failure-free survival. METHODS AND MATERIALS: A retrospective case note review of consecutive patients with intermediate- or high-risk localized prostate cancer treated between January 2001 and December 2002 with neoadjuvant hormonal deprivation therapy, followed by concurrent hormonal therapy and radiotherapy was performed. Patient data were divided for analysis according to whether the PSA level in Week 1 of radiotherapy was 1 ng/mL in 52. At a median follow-up of 49 months, the 4-year actuarial biochemical failure-free survival rate was 84% vs. 60% (p = 0.0016) in favor of the patients with a PSA level after neoadjuvant hormonal deprivation therapy of 1 ng/mL at the beginning of external beam radiotherapy after >/=2 months of neoadjuvant luteinizing hormone-releasing hormone agonist therapy have a significantly greater rate of biochemical failure and lower survival rate compared with those with a PSA level of

Simulating Coxian Phase-type Distributions for Patient Survival

Coxian phase-type distributions are a special type of Markov model that can be used to represent survival times in terms of phases through which an individual may progress until they eventually leave the system completely. Previous research has considered the Coxian phase-type distribution to be ideal in representing patient survival in hospital. However, problems exist in fitting the distributions. This paper investigates the problems that arise with the fitting process by simulating various Coxian phase-type models for the representation of patient survival and examining the estimated parameter values and eigenvalues obtained. The results indicate that numerical methods previously used for fitting the model parameters do not always converge. An alternative technique is therefore considered. All methods are influenced by the choice of initial parameter values. The investigation uses a data set of 1439 elderly patients and models their survival time, the length of time they spend in a UK hospital.

Assessment of the benefits of Discrete Conditional Survival Models in modelling ambulance response times

Many of the challenges faced in health care delivery can be informed through building models. In particular, Discrete Conditional Survival (DCS) models, recently under development, can provide policymakers with a flexible tool to assess time-to-event data. The DCS model is capable of modelling the survival curve based on various underlying distribution types and is capable of clustering or grouping observations (based on other covariate information) external to the distribution fits. The flexibility of the model comes through the choice of data mining techniques that are available in ascertaining the different subsets and also in the choice of distribution types available in modelling these informed subsets. This paper presents an illustrated example of the Discrete Conditional Survival model being deployed to represent ambulance response-times by a fully parameterised model. This model is contrasted against use of a parametric accelerated failure-time model, illustrating the strength and usefulness of Discrete Conditional Survival models.

Out-of-field cell survival following exposure to intensity-modulated radiation fields

PURPOSE:
To determine the in-field and out-of-field cell survival of cells irradiated with either primary field or scattered radiation in the presence and absence of intercellular communication.
METHODS AND MATERIALS:
Cell survival was determined by clonogenic assay in human prostate cancer (DU145) and primary fibroblast (AGO1552) cells following exposure to different field configurations delivered using a 6-MV photon beam produced with a Varian linear accelerator.
RESULTS:
Nonuniform dose distributions were delivered using a multileaf collimator (MLC) in which half of the cell population was shielded. Clonogenic survival in the shielded region was significantly lower than that predicted from the linear quadratic model. In both cell lines, the out-of-field responses appeared to saturate at 40%-50% survival at a scattered dose of 0.70 Gy in DU-145 cells and 0.24 Gy in AGO1522 cells. There was an approximately eightfold difference in the initial slopes of the out-of-field response compared with the a-component of the uniform field response. In contrast, cells in the exposed part of the field showed increased survival. These observations were abrogated by direct physical inhibition of cellular communication and by the addition of the inducible nitric oxide synthase inhibitor aminoguanidine known to inhibit intercellular bystander effects. Additional studies showed the proportion of cells irradiated and dose delivered to the shielded and exposed regions of the field to impact on response.
CONCLUSIONS:
These data demonstrate out-of-field effects as important determinants of cell survival following exposure to modulated irradiation fields with cellular communication between differentially irradiated cell populations playing an important role. Validation of these observations in additional cell models may facilitate the refinement of existing radiobiological models and the observations considered important determinants of cell survival.

Estimation of survival rate and extinction probability for stage-structured populations with overlapping life stages

The development of methods providing reliable estimates of demographic parameters (e. g., survival rates, fecundity) for wild populations is essential to better understand the ecology and conservation requirements of individual species. A number of methods exist for estimating the demographics of stage-structured populations, but inherent mathematical complexity often limits their uptake by conservation practitioners. Estimating survival rates for pond-breeding amphibians is further complicated by their complex migratory and reproductive behaviours, often resulting in nonobservable states and successive cohorts of eggs and tadpoles. Here we used comprehensive data on 11 distinct breeding toad populations (Bufo calamita) to clarify and assess the suitability of a relatively simple method [the Kiritani-Nakasuji-Manly (KNM) method] to estimate the survival rates of stage-structured populations with overlapping life stages. The study shows that the KNM method is robust and provides realistic estimates of amphibian egg and larval survival rates for species in which breeding can occur as a single pulse or over a period of several weeks. The study also provides estimates of fecundity for seven distinct toad populations and indicates that it is essential to use reliable estimates of fecundity to limit the risk of under- or overestimating the survival rates when using the KNM method. Survival and fecundity rates for B. calamita populations were then used to define population matrices and make a limited exploration of their growth and viability. The findings of the study recently led to the implementation of practical conservation measures at the sites where populations were most vulnerable to extinction. © 2010 The Society of Population Ecology and Springer.

Cell survival responses after exposure to modulated radiation fields.

In the present study survival responses were determined in cells with differing radiosensitivity, specifically primary fibroblast (AG0-1522B), human breast cancer (MDA-MB-231), human prostate cancer (DU-145) and human glioma (T98G) cells, after exposure to modulated radiation fields delivered by shielding 50% of the tissue culture flask. A significant decrease (P < 0.05) in cell survival was observed in the shielded area, outside the primary treatment field (out-of-field), that was lower than predicted when compared to uniform exposures fitted to the linear-quadratic model. Cellular radiosensitivity was demonstrated to be an important factor in the level of response for both the in- and out-of-field regions. These responses were shown to be dependent on secretion-mediated intercellular communication, because inhibition of cellular secreted factors between the in- and out-of-field regions abrogated the response. Out-of-field cell survival was shown to increase after pretreatment of cells with agents known to inhibit factors involved in mediating radiation-induced bystander signaling (aminoguanidine, DMSO or cPTIO). These data illustrate a significant decrease in survival out-of-field, dependent upon intercellular communication, in several cell lines with varying radiosensitivity after exposure to a modulated radiation field. This study provides further evidence for the importance of intercellular signaling in modulated exposures, where dose gradients are present, and may inform the refinement of established radiobiological models to facilitate the optimization of advanced radiotherapy treatment plans.

Burkholderia cenocepacia requires a periplasmic HtrA protease for growth under thermal and osmotic stress and for survival in vivo

Burkholderia cenocepacia, a member of the B. cepacia complex, is an opportunistic pathogen that causes serious infections in patients with cystic fibrosis. We identified a six-gene cluster in chromosome 1 encoding a two-component regulatory system (BCAL2831 and BCAL2830) and an HtrA protease (BCAL2829) hypothesized to play a role in the B. cenocepacia stress response. Reverse transcriptase PCR analysis of these six genes confirmed they are cotranscribed and comprise an operon. Genes in this operon, including htrA, were insertionally inactivated by recombination with a newly created suicide plasmid, pGPOmegaTp. Genetic analyses and complementation studies revealed that HtrA(BCAL2829) was required for growth of B. cenocepacia upon exposure to osmotic stress (NaCl or KCl) and thermal stress (44 degrees C). In addition, replacement of the serine residue in the active site with alanine (S245A) and deletion of the HtrA(BCAL2829) PDZ domains demonstrated that these areas are required for protein function. HtrA(BCAL2829) also localizes to the periplasmic compartment, as shown by Western blot analysis and a colicin V reporter assay. Using the rat agar bead model of chronic lung infection, we also demonstrated that inactivation of the htrA gene is associated with a bacterial survival defect in vivo. Together, our data demonstrate that HtrA(BCAL2829) is a virulence factor in B. cenocepacia.

A complete lipopolysaccharide inner core oligosaccharide is required for resistance of Burkholderia cenocepacia to antimicrobial peptides and bacterial survival in vivo

Burkholderia cenocepacia is an important opportunistic pathogen of patients with cystic fibrosis. This bacterium is inherently resistant to a wide range of antimicrobial agents, including high concentrations of antimicrobial peptides. We hypothesized that the lipopolysaccharide (LPS) of B. cenocepacia is important for both virulence and resistance to antimicrobial peptides. We identified hldA and hldD genes in B. cenocepacia strain K56-2. These two genes encode enzymes involved in the modification of heptose sugars prior to their incorporation into the LPS core oligosaccharide. We constructed a mutant, SAL1, which was defective in expression of both hldA and hldD, and by performing complementation studies we confirmed that the functions encoded by both of these B. cenocepacia genes were needed for synthesis of a complete LPS core oligosaccharide. The LPS produced by SAL1 consisted of a short lipid A-core oligosaccharide and was devoid of O antigen. SAL1 was sensitive to the antimicrobial peptides polymyxin B, melittin, and human neutrophil peptide 1. In contrast, another B. cenocepacia mutant strain that produced complete lipid A-core oligosaccharide but lacked polymeric O antigen was not sensitive to polymyxin B or melittin. As determined by the rat agar bead model of lung infection, the SAL1 mutant had a survival defect in vivo since it could not be recovered from the lungs of infected rats 14 days postinfection. Together, these data show that the B. cenocepacia LPS inner core oligosaccharide is needed for in vitro resistance to three structurally unrelated antimicrobial peptides and for in vivo survival in a rat model of chronic lung infection.

Intracellular survival of Burkholderia cepacia complex isolates in the presence of macrophage cell activation

Strains of the Burkholderia cepacia complex have emerged as a serious threat to patients with cystic fibrosis due to their ability to infect the lung and cause, in some patients, a necrotizing pneumonia that is often lethal. It has recently been shown that several strains of the B. cepacia complex can escape intracellular killing by free-living amoebae following phagocytosis. In this work, the ability of two B. cepacia complex strains to resist killing by macrophages was explored. Using fluorescence microscopy, electron microscopy and a modified version of the gentamicin-protection assay, we demonstrate that B. cepacia CEP021 (genomovar VI), and Burkholderia vietnamiensis (previously B. cepacia genomovar V) CEP040 can survive in PU5-1.8 murine macrophages for a period of at least 5 d without significant bacterial replication. Furthermore, bacterial entry into macrophages stimulated production of tumour necrosis factor and primed them to release toxic oxygen radicals following treatment with phorbol myristoyl acetate. These effects were probably caused by bacterial LPS, as they were blocked by polymyxin B. Infected macrophages primed with interferon gamma produced less nitric oxide than interferon-gamma-primed uninfected cells. We propose that the ability of B. cepacia to resist intracellular killing by phagocytic cells may play a role in the pathogenesis of cystic fibrosis lung infection. Our data are consistent with a model where repeated cycles of phagocytosis and cellular activation without bacterial killing may promote a deleterious inflammatory response causing tissue destruction and decay of lung function.

Investigating the efficiency of fitting Coxian phase-type distributions to health care data

Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.