Can we use the approaches of ecological inference to learn about the potential for dependence bias in dualsystem estimation? An application to cancer registration data

The dual-system estimator, or estimators with a similar underlying set of assumptions and structure, is a widely used approach to estimate the unknown size of a population. Within official statistics its use is linked with population census, while in health applications it is often used to estimate true levels of incidence from imperfect reporting systems; the classic example being work by Sekar and Deming exploring the estimation of births in India in the 1940s. Critical to the implementation of dual-system estimation are the assumptions that the probability of being counted in a source is homogeneous and that the event of being counted in each source is independent. When either of these assumptions fails, the two by two table will have an odds ratio different to one and the dual-system estimator will be biased. Inferential frameworks such as the aggregate association index (AAI) have been developed to allow the researcher to assess the plausibility of independence between two variables in a two by two table, when only the margins are observed. Given any appropriate measure of relationship, this strategy relies on determining the AAI, which provides an indication of the likely association structure between the variables given only the marginal information. Further advances of the AAI have also been established including its link with the odds ratio and its relationship with the size of the study being undertaken. Determining the population size from a two by two table given limited information is an alternative variation of the framework on which the AAI is built. Therefore the underlying theoretical properties of the two by two table are identical in both scenarios – it is only the nature of the unknown information that differs. In this paper we make the first steps to exploring the use of an AAI type framework (and its relatives) to assess the plausibility of an independence assumption in applications of population size estimation. We use alternative data set-ups based on real data relating to historical cancer registration (with three sources of registration) to demonstrate that the chi-square statistic behaves differently over a range of values for the missing data for differing true relationships between the two variables. We then apply the approach to the cancer registration from two of the registration systems to show that we can see evidence of potential dependence from the observed but incomplete data. The first results in this paper demonstrate the possibility of exploring the independence assumption when estimating the unknown population size from two lists. As with the AAI framework, the aim is not to directly estimate the level of the association but rather alert the analyst to the potential for an association and its direction allowing them to assess the likelihood of a biased estimate for the population size. This has important implications within a health setting where it is potentially useful to understand if the true population size, of say cancer patients, is likely to be higher or lower than the estimate constructed assuming independence. Within the official statistics setting, it can alert us to situations where it is advantageous to explore whether external data exist that would allow an adjustment for dependence in our two lists

Shaking-induced dynamics of cold atoms in magnetic traps

We describe an experiment in which cold rubidium atoms, confined in an elongated magnetic trap, are excited by transverse oscillation of the trap center. The temperature after excitation exhibits resonance as a function of the driving frequency. We measure these resonances at several different trap frequencies. In order to interpret the experiments, we develop a simple model that incorporates both collisions between atoms and the anharmonicity of the real three-dimensional trapping potential. As well as providing a precise connection between the transverse harmonic oscillation frequency and the temperature resonance frequency, this model gives insight into the heating and loss mechanisms and into the dynamics of driven clouds of cold trapped atoms

Compensation for Changing Motor Uncertainty

When movement outcome differs consistently from the intended movement, errors are used to correct subsequent movements (e.g., adaptation to displacing prisms or force fields) by updating an internal model of motor and/or sensory systems. Here, we examine changes to an internal model of the motor system under changes in the variance structure of movement errors lacking an overall bias. We introduced a horizontal visuomotor perturbation to change the statistical distribution of movement errors anisotropically, while monetary gains/losses were awarded based on movement outcomes. We derive predictions for simulated movement planners, each differing in its internal model of the motor system. We find that humans optimally respond to the overall change in error magnitude, but ignore the anisotropy of the error distribution. Through comparison with simulated movement planners, we found that aimpoints corresponded quantitatively to an ideal movement planner that updates a strictly isotropic (circular) internal model of the error distribution. Aimpoints were planned in a manner that ignored the direction-dependence of error magnitudes, despite the continuous availability of unambiguous information regarding the anisotropic distribution of actual motor errors

Sex-specific mortality forecasting for UK countries: a coherent approach

This paper introduces a gender specific model for the joint mortality projection of three countries (England and Wales combined, Scotland, and Northern Ireland) of the United Kingdom. The model, called 2-tier Augmented Common Factor model, extends the classical Lee and Carter [26] and Li and Lee [32] models, with a common time factor for the whole UK population, a sex specific period factor for males and females, and a specific time factor for each country within each gender. As death counts in each subpopulation are modelled directly, a Poisson framework is used. Our results show that the 2-tier ACF model improves the in-sample fitting compared to the use of independent LC models for each subpopulation or of independent Li and Lee models for each couple of genders within each country. Mortality projections also show that the 2-tier ACF model produces coherent forecasts for the two genders within each country and different countries within each gender, thus avoiding the divergence issues arising when independent projections are used. The 2-tier ACF is further extended to include a cohort term to take into account the faster improvements of the UK ‘golden generation’

Positive Selection within the Schizophrenia-Associated GABA(A) Receptor β(2) Gene

The gamma-aminobutyric acid type-A (GABA(A)) receptor plays a major role in inhibitory neurotransmissions. Intronic SNPs and haplotypes in GABRB2, the gene for GABA(A) receptor β(2) subunit, are associated with schizophrenia and correlated with the expression of two alternatively spliced β(2) isoforms. In the present study, using chimpanzee as an ancestral reference, high frequencies were observed for the derived (D) alleles of the four SNPs rs6556547, rs187269, rs1816071 and rs1816072 in GABRB2, suggesting the occurrence of positive selection for these derived alleles. Coalescence-based simulation showed that the population frequency spectra and the frequencies of H56, the haplotype having all four D alleles, significantly deviated from neutral-evolution expectation in various demographic models. Haplotypes containing the derived allele of rs1816072 displayed significantly less diversity compared to haplotypes containing its ancestral allele, further supporting positive selection. The variations in DD-genotype frequencies in five human populations provided a snapshot of the evolutionary history, which suggested that the positive selections of the D alleles are recent and likely ongoing. The divergence between the DD-genotype profiles of schizophrenic and control samples pointed to the schizophrenia-relevance of positive selections, with the schizophrenic samples showing weakened selections compared to the controls. These DD-genotypes were previously found to increase the expression of β(2), especially its long isoform. Electrophysiological analysis showed that this long β(2) isoform favored by the positive selections is more sensitive than the short isoform to the inhibition of GABA(A) receptor function by energy depletion. These findings represent the first demonstration of positive selection in a schizophrenia-associated gene

Monascus-Fermented Dioscorea Enhances Oxidative Stress Resistance via DAF-16/FOXO in Caenorhabditis elegans

BACKGROUND: Monascus-fermented products are mentioned in an ancient Chinese pharmacopoeia of medicinal food and herbs. Monascus-fermented products offer valuable therapeutic benefits and have been extensively used in East Asia for several centuries. Several biological activities of Monascus-fermented products were recently described, and the extract of Monascus-fermented products showed strong antioxidant activity of scavenging DPPH radicals. To evaluate whether Monascus-fermented dioscorea products have potential as nutritional supplements, Monascus-fermented dioscorea's modulation of oxidative-stress resistance and associated regulatory mechanisms in Caenorhabditis elegans were investigated. PRINCIPAL FINDINGS: We examined oxidative stress resistance of the ethanol extract of red mold dioscorea (RMDE) in C. elegans, and found that RMDE-treated wild-type C. elegans showed an increased survival during juglone-induced oxidative stress compared to untreated controls, whereas the antioxidant phenotype was absent from a daf-16 mutant. In addition, the RMDE reduced the level of intracellular reactive oxygen species in C. elegans. Finally, the RMDE affected the subcellular distribution of the FOXO transcription factor, DAF-16, in C. elegans and induced the expression of the sod-3 antioxidative gene. CONCLUSIONS: These findings suggest that the RMDE acts as an antioxidative stress agent and thus may have potential as a nutritional supplement. Further studies in C. elegans suggest that the antioxidant effect of RMDE is mediated via regulation of the DAF-16/FOXO-dependent pathway

Genome-wide fine-scale recombination rate variation in Drosophila melanogaster

Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and diversity

The genetic legacy of extreme exploitation in a polar vertebrate

Understanding the effects of human exploitation on the genetic composition of wild populations is important for predicting species persistence and adaptive potential. We therefore investigated the genetic legacy of large-scale commercial harvesting by reconstructing, on a global scale, the recent demographic history of the Antarctic fur seal (Arctocephalus gazella), a species that was hunted to the brink of extinction by 18th and 19th century sealers. Molecular genetic data from over 2,000 individuals sampled from all eight major breeding locations across the species’ circumpolar geographic distribution, show that at least four relict populations around Antarctica survived commercial hunting. Coalescent simulations suggest that all of these populations experienced severe bottlenecks down to effective population sizes of around 150–200. Nevertheless, comparably high levels of neutral genetic variability were retained as these declines are unlikely to have been strong enough to deplete allelic richness by more than around 15%. These findings suggest that even dramatic short-term declines need not necessarily result in major losses of diversity, and explain the apparent contradiction between the high genetic diversity of this species and its extreme exploitation history

Integration of Expressed Sequence Tag Data Flanking Predicted RNA Secondary Structures Facilitates Novel Non-Coding RNA Discovery

Many computational methods have been used to predict novel non-coding RNAs (ncRNAs), but none, to our knowledge, have explicitly investigated the impact of integrating existing cDNA-based Expressed Sequence Tag (EST) data that flank structural RNA predictions. To determine whether flanking EST data can assist in microRNA (miRNA) prediction, we identified genomic sites encoding putative miRNAs by combining functional RNA predictions with flanking ESTs data in a model consistent with miRNAs undergoing cleavage during maturation. In both human and mouse genomes, we observed that the inclusion of flanking ESTs adjacent to and not overlapping predicted miRNAs significantly improved the performance of various methods of miRNA prediction, including direct high-throughput sequencing of small RNA libraries. We analyzed the expression of hundreds of miRNAs predicted to be expressed during myogenic differentiation using a customized microarray and identified several known and predicted myogenic miRNA hairpins. Our results indicate that integrating ESTs flanking structural RNA predictions improves the quality of cleaved miRNA predictions and suggest that this strategy can be used to predict other non-coding RNAs undergoing cleavage during maturation