Structural Breaks in Mortality Models and their Consequences

In recent years, the issue of life expectancy has become of upmost importance to pension providers, insurance companies and the government bodies in the developed world. Significant and consistent improvements in mortality rates and, hence, life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data in order to anticipate future life expectancy and, hence, quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age and cohort, and forecast these trends into the future using standard statistical methods. The modeling approaches used failed to capture the effects of any structural change in the trend and, thus, potentially produced incorrect forecasts of future mortality rates. In this paper, we look at a range of leading stochastic models of mortality and test for structural breaks in the trend time series.

GEP analysis validates high risk MDS and acute myeloid leukemia post MDS mice models and highlights novel dysregulated pathways

BACKGROUND: In spite of the recent discovery of genetic mutations in most myelodysplasic (MDS) patients, the pathophysiology of these disorders still remains poorly understood, and only few in vivo models are available to help unravel the disease.

METHODS: We performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS) and acute myeloid leukemia (AML) post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters MRP8NRASD12/tethBCL-2 or MRP8[NRASD12/hBCL-2], respectively.

RESULTS: Analysis of dysregulated genes that were unique to the diseased HR-MDS and AML post MDS mice and not their founder mice pointed first to pathways that had previously been reported in MDS patients, including DNA replication/damage/repair, cell cycle, apoptosis, immune responses, and canonical Wnt pathways, further validating these models at the gene expression level. Interestingly, pathways not previously reported in MDS were discovered. These included dysregulated genes of noncanonical Wnt pathways and energy and lipid metabolisms. These dysregulated genes were not only confirmed in a different independent set of BM and spleen Sca1+ cells from the MDS mice but also in MDS CD34+ BM patient samples.

CONCLUSIONS: These two MDS models may thus provide useful preclinical models to target pathways previously identified in MDS patients and to unravel novel pathways highlighted by this study.

Mucosal modulation of contractility in bladder strips from normal and overactive rat models and the effect of botulinum toxin A on overactive bladder strips

AIMS: To investigate the local, regulatory role of the mucosa on bladder strip contractility from normal and overactive bladders and to examine the effect of botulinum toxin A (BoNT-A).

METHODS: Bladder strips from spontaneously hyperactive rat (SHR) or normal rats (Sprague Dawley, SD) were dissected for myography as intact or mucosa-free preparations. Spontaneous, neurogenic and agonist-evoked contractions were investigated. SHR strips were incubated in BoNT-A (3 h) to assess effects on contractility.

RESULTS: Spontaneous contraction amplitude, force-integral or frequency were not significantly different in SHR mucosa-free strips compared with intacts. In contrast, spontaneous contraction amplitude and force-integral were smaller in SD mucosa-free strips than in intacts; frequency was not affected by the mucosa. Frequency of spontaneous contractions in SHR strips was significantly greater than in SD strips. Neurogenic contractions in mucosa-free SHR and SD strips at higher frequencies were smaller than in intact strips. The mucosa did not affect carbachol-evoked contractions in intact versus mucosa-free strips from SHR or SD bladders. BoNT-A reduced spontaneous contractions in SHR intact strips; this trend was also observed in mucosa-free strips but was not significant. Neurogenic and carbachol-evoked contractions were reduced by BoNT-A in mucosa-free but not intact strips. Depolarisation-induced contractions were smaller in BoNT-A-treated mucosa-free strips.

CONCLUSIONS: The mucosal layer positively modulates spontaneous contractions in strips from normal SD but not overactive SHR bladder strips. The novel finding of BoNT-A reduction of contractions in SHR mucosa-free strips indicates actions on the detrusor, independent of its classical action on neuronal SNARE complexes.

Comparisons, mental models, and the action effect in judgments of regret

People tend to attribute more regret to a character who has decided to take action and experienced a negative outcome than to one who has decided not to act and experienced a negative outcome. For some decisions, however, this finding is not observed in a between-participants design and thus appears to rely on comparisons between people's representations of action and their representations of inaction. In this article, we outline a mental models account that explains findings from studies that have used within- and between-participants designs, and we suggest that, for decisions with uncertain counterfactual outcomes, information about the consequences of a decision to act causes people to flesh out their representation of the counterfactual states of affairs for inaction. In three experiments, we confirm our predictions about participants' fleshing out of representations, demonstrating that an action effect occurs only when information about the consequences of action is available to participants as they rate the nonactor and when this information about action is informative with respect to judgments about inaction. It is important to note that the action effect always occurs when the decision scenario specifies certain counterfactual outcomes. These results suggest that people sometimes base their attributions of regret on comparisons among different sets of mental models.

Alternative Factor Models and Heritability of the Short Leyton Obsessional Inventory-Children's Version

An alternative models framework was used to test three confirmatory factor analytic models for the Short Leyton Obsessional Inventory-Children's Version (Short LOI-CV) in a general population sample of 517 young adolescent twins (11-16 years). A one-factor model as implicit in current classification systems of Obsessive-Compulsive Disorder (OCD), a two-factor obsessions and compulsions model, and a multidimensional model corresponding to the three proposed subscales of the Short LOI-CV (labelled Obsessions/Incompleteness, Numbers/Luck and Cleanliness) were considered. The three-factor model was the only model to provide an adequate explanation of the data. Twin analyses suggested significant quantitative sex differences in heritability for both the Obsessions/Incompleteness and Numbers/Luck dimensions with these being significantly heritable in males only (heritability of 60% and 65% respectively). The correlation between the additive genetic effects for these two dimensions in males was 0.95 suggesting they largely share the same genetic risk factors.

Detecting the effects of diversity on measures of ecosystem function: experimental design, null models and empirical observations

Here we present a novel experimental approach to examine the relationship between diversity and ecosystem Function. We develop four null predictive models, with which to differentiate between the 'sampling effect' - the chance inclusion of a highly productive species, and 'species complementarity' - the complementary use of resources by species that differ in their niche or resource use. We investigate the effects of manipulating species and functional richness on ecosystem function in marine benthic system and using empirical data from our own experiments we illustrate the application of these models.

Carotenoids and co-antioxidants in age-related maculopathy:design and methods

Age-related macular degeneration (AMD), is the leading cause of blind registration in the Western World among individuals 65 years or older. Early AMD, a clinical state without overt functional loss, is said to be present clinically when yellowish deposits known as drusen and/or alterations of fundus pigmentation are seen in the macular retina. Although the etiopathogenesis of AMD remains uncertain, there is a growing body of evidence in support of the view that cumulative oxidative damage plays a causal role. Appropriate dietary antioxidant supplementation is likely to be beneficial in maintaining visual function in patients with AMD, and preventing or delaying the progression of early AMD to late AMD. The Carotenoids in Age-Related Maculopathy (CARMA) Study is a randomized and double-masked clinical trial of antioxidant supplementation versus placebo in 433 participants with either early AMD features of sufficient severity in at least one eye or any level of AMD in one eye with late AMD (neovascular AMD or central geographic atrophy) in the fellow eye. The aim of the CARMA Study is to investigate whether lutein and zeaxanthin, in combination with co-antioxidants (vitamin C, E, and zinc), has a beneficial effect on visual function and/or prevention of progression from early to late stages of disease. The primary outcome is improved or preserved distance visual acuity at 12 months. Secondary outcomes include improved or preserved interferometric acuity, contrast sensitivity, shape discrimination ability, and change in AMD severity as monitored by fundus photography. This article outlines the CARMA Study design and methodology, including its rationale.

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.