An Investigation to Validate the Grammar and Phonology Screening (GAPS) Test to Identify Children with Specific Language Impairment

The extraordinarily high incidence of grammatical language impairments in developmental disorders suggests that this uniquely human cognitive function is "fragile". Yet our understanding of the neurobiology of grammatical impairments is limited. Furthermore, there is no "gold-standard" to identify grammatical impairments and routine screening is not undertaken. An accurate screening test to identify grammatical abilities would serve the research, health and education communities, further our understanding of developmental disorders, and identify children who need remediation, many of whom are currently un-diagnosed. A potential realistic screening tool that could be widely administered is the Grammar and Phonology Screening (GAPS) test--a 10 minute test that can be administered by professionals and non-professionals alike. Here we provide a further step in evaluating the validity and accuracy (sensitivity and specificity) of the GAPS test in identifying children who have Specific Language Impairment (SLI)

Contribution of genetic effects to genetic variance components with epistasis and linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Cockerham genetic models are commonly used in quantitative trait loci (QTL) analysis with a special feature of partitioning genotypic variances into various genetic variance components, while the F_∞genetic models are widely used in genetic association studies. Over years, there have been some confusion about the relationship between these two type of models. A link between the additive, dominance and epistatic effects in an F_∞model and the additive, dominance and epistatic variance components in a Cockerham model has not been well established, especially when there are multiple QTL in presence of epistasis and linkage disequilibrium (LD).</p> <p>Results</p> <p>In this paper, we further explore the differences and links between the F_∞and Cockerham models. First, we show that the Cockerham type models are allelic based models with a special modification to correct a confounding problem. Several important moment functions, which are useful for partition of variance components in Cockerham models, are also derived. Next, we discuss properties of the F_∞models in partition of genotypic variances. Its difference from that of the Cockerham models is addressed. Finally, for a two-locus biallelic QTL model with epistasis and LD between the loci, we present detailed formulas for calculation of the genetic variance components in terms of the additive, dominant and epistatic effects in an F_∞model. A new way of linking the Cockerham and F_∞model parameters through their coding variables of genotypes is also proposed, which is especially useful when reduced F_∞models are applied.</p> <p>Conclusion</p> <p>The Cockerham type models are allele-based models with a focus on partition of genotypic variances into various genetic variance components, which are contributed by allelic effects and their interactions. By contrast, the F_∞regression models are genotype-based models focusing on modeling and testing of within-locus genotypic effects and locus-by-locus genotypic interactions. When there is no need to distinguish the paternal and maternal allelic effects, these two types of models are transferable. Transformation between an F_∞model's parameters and its corresponding Cockerham model's parameters can be established through a relationship between their coding variables of genotypes. Genetic variance components in terms of the additive, dominance and epistatic genetic effects in an F_∞model can then be calculated by translating formulas derived for the Cockerham models.</p

Population genetics of trypanosoma brucei rhodesiense: clonality and diversity within and between foci

African trypanosomes are unusual among pathogenic protozoa in that they can undergo their complete morphological life cycle in the tsetse fly vector with mating as a non-obligatory part of this development. Trypanosoma brucei rhodesiense, which infects humans and livestock in East and Southern Africa, has classically been described as a host-range variant of the non-human infective Trypanosoma brucei that occurs as stable clonal lineages. We have examined T. b. rhodesiense populations from East (Uganda) and Southern (Malawi) Africa using a panel of microsatellite markers, incorporating both spatial and temporal analyses. Our data demonstrate that Ugandan T. b. rhodesiense existed as clonal populations, with a small number of highly related genotypes and substantial linkage disequilibrium between pairs of loci. However, these populations were not stable as the dominant genotypes changed and the genetic diversity also reduced over time. Thus these populations do not conform to one of the criteria for strict clonality, namely stability of predominant genotypes over time, and our results show that, in a period in the mid 1990s, the previously predominant genotypes were not detected but were replaced by a novel clonal population with limited genetic relationship to the original population present between 1970 and 1990. In contrast, the Malawi T. b. rhodesiense population demonstrated significantly greater diversity and evidence for frequent genetic exchange. Therefore, the population genetics of T. b. rhodesiense is more complex than previously described. This has important implications for the spread of the single copy T. b. rhodesiense gene that allows human infectivity, and therefore the epidemiology of the human disease, as well as suggesting that these parasites represent an important organism to study the influence of optional recombination upon population genetic dynamics

Long-term all-sites cancer mortality time trends in Ohio, USA, 1970–2001: differences by race, gender and age

BACKGROUND: There were significant changes in cancer mortality in the USA over the last several decades, in the whole country and in particular states. However, no in depth analysis has been published so far, dealing with changes in mortality time trends in the state of Ohio. Since the state of Ohio belongs to the states of relatively high level of all-sites mortality in both males and females, it is of interest to analyze recent changes in mortality rates, as well as to compare them with the situation in the rest of the USA. The main aim of this study was to analyze, describe and interpret all-sites cancer mortality time trends in the population of the State of Ohio. METHODS: Cancer mortality data by age, sex, race and year for the period 1970–2001 were obtained from the Surveillance Research Program of the National Cancer Institute SEER*Stat software. A joinpoint regression methodology was used to provide estimated annual percentage changes (EAPCs) and to detect points in time where significant changes in the trends occurred. RESULTS: In both, males and females mortality rates were higher in blacks compared with whites. The difference was bigger in males (39.9%) than in women (23.3%). Mortality rates in Ohio are generally higher than average USA rates – an overall difference was 7.5% in men in 1997–2001, and 6.1% in women. All-sites mortality trends in Ohio and in the whole USA are similar. However, in general, mortality rates in Ohio remained elevated compared with the USA rates throughout the entire analyzed period. The exceptions are the rates in young and middle-aged African Americans. CONCLUSION: Although direction of time trends in Ohio are similar in Ohio and the whole US, Ohio still have cancer mortality rates higher than the US average. In addition, there is a significant discrepancy between white and black population of Ohio in all-sites mortality level, with disadvantage for Blacks. To diminish disparities in cancer mortality between African Americans and white inhabitants of Ohio efforts should be focused on increasing knowledge of black people regarding healthy lifestyle and behavioral risk factors, but also on diminishing socioeconomic differences, and last but not least, on better access to medical care

Analysis of oral cancer epidemiology in the US reveals state-specific trends: implications for oral cancer prevention

Background: Downward trends have been observed in oral cancer incidence and mortality in the US over the past 30 years; however, these declines are not uniform within this population. Several studies have now demonstrated an increase in the incidence and mortality from oral cancers among certain demographic groups, which may have resulted from increased risks or risk behaviors. This study examines the underlying data that comprise these trends, to identify specific populations that may be at greater risk for morbidity and mortality from oral cancers. Methods: Oral cancer incidence and mortality data analyzed for this study were generated using the National Cancer Institute\u27s Surveillance, Epidemiology and End Results (SEER) program. Results: While oral cancer incidence and mortality rates have been declining over the past thirty years, these declines have reversed in the past five years among some demographic groups, including black females and white males. Sorting of these data by state revealed that eight states exhibited increasing rates of oral cancer deaths, Nevada, North Carolina, Iowa, Ohio, Maine, Idaho, North Dakota, and Wyoming, in stark contrast to the national downward trend. Furthermore, a detailed analysis of data from these states revealed increasing rates of oral cancer among older white males, also contrary to the overall trends observed at the national level. Conclusion: These results signify that, despite the declining long-term trends in oral cancer incidence and mortality nationally, localized geographic areas exist where the incidence and mortality from oral cancers have been increasing. These areas represent sites where public health education and prevention efforts may be focused to target these specific populations in an effort to improve health outcomes and reduce disparities within these populations

Validity of sports watches when estimating energy expenditure during running

The aim of this study was to assess the accuracy of three different sport watches in estimating energy expenditure during aerobic and anaerobic running

CDCOCA: a statistical method to define complexity dependent co-occurring chromosomal aberrations

<p>Abstract</p> <p>Background</p> <p>Copy number alterations (CNA) play a key role in cancer development and progression. Since more than one CNA can be detected in most tumors, frequently co-occurring genetic CNA may point to cooperating cancer related genes. Existing methods for co-occurrence evaluation so far have not considered the overall heterogeneity of CNA per tumor, resulting in a preferential detection of frequent changes with limited specificity for each association due to the high genetic instability of many samples.</p> <p>Method</p> <p>We hypothesize that in cancer some linkage-independent CNA may display a non-random co-occurrence, and that these CNA could be of pathogenetic relevance for the respective cancer. We also hypothesize that the statistical relevance of co-occurring CNA may depend on the sample specific CNA complexity. We verify our hypotheses with a simulation based algorithm CDCOCA (complexity dependence of co-occurring chromosomal aberrations).</p> <p>Results</p> <p>Application of CDCOCA to example data sets identified co-occurring CNA from low complex background which otherwise went unnoticed. Identification of cancer associated genes in these co-occurring changes can provide insights of cooperative genes involved in oncogenesis.</p> <p>Conclusions</p> <p>We have developed a method to detect associations of regional copy number abnormalities in cancer data. Along with finding statistically relevant CNA co-occurrences, our algorithm points towards a generally low specificity for co-occurrence of regional imbalances in CNA rich samples, which may have negative impact on pathway modeling approaches relying on frequent CNA events.</p