Exact sample size needed to detect dependence in 2 x 2 x 2 tables

In the Georgia Centenarian Study (Poon et al., Exceptional Longevity, 2006), centenarian cases and young controls are classified according to three categories (age, ethnic origin, and single nucleotide polymorphisms [SNPs] of candidate longevity genes), where each factor has two possible levels. Here we provide methodologies to determine the minimum sample size needed to detect dependence in 2 x 2 x 2 tables based on Fisher's exact test evaluated exactly or by Markov chain Monte Carlo (MCMC), assuming only the case total L and the control total N are known. While our MCMC method uses serial computing, parallel computing techniques are employed to solve the exact sample size problem. These tools will allow researchers to design efficient sampling strategies and to select informative SNPs. We apply our tools to 2 x 2 x 2 tables obtained from a pilot study of the Georgia Centenarians Study, and the sample size results provided important information for the subsequent major study. A comparison between the results of an exact method and those of a MCMC method showed that the MCMC method studied needed much less computation time on average (10.16 times faster on average for situations examined with S.E. = 2.60), but its sample size results were only valid as a rule for larger sample sizes (in the hundreds).     

Nonparametric estimation of the survival function when cause of death is uncertain

A nonparametric estimator for the survival function, accommodating censored survival times and uncertainty in the assignment of cause of death, is proposed. For example, in a carcinogenicity experiment the data on each animal may consist of an observed age-at-death and some indication of the probability that the tumor type under study caused death. An estimator of the net survival function, for time-to-death due to the cause of interest, is developed. Under certain assumptions, the proposed estimator is consistent and asymptotically normally distributed. Monte Carlo simulations were used to compare this estimator with the Kaplan-Meier estimator. Forcing the cause of death to be specified with certainty, as required by the Kaplan-Meier estimator, may result in substantial biases.     

Optimal decision rules for herring gulls

A measure of fitness applicable to herring gull (Larus argentatus) life histories is introduced and related to short-term risks which depend on behaviour. This allows calculations of the relationship between fitness and behaviour if one can measure the risks an animal takes behaving in particular ways in specified situations. This method is used to evaluate the fitness of herring gulls during the incubation period at Walney Island, U.K. Two causes of egg mortality are considered, death by predation and death by exposure, and the latter is shown to be less important than the former. The chances of death by predation depend on the number of adults present on the territory and are estimated to be approximately 0·045 eggs per h if no parents are present on territory, 3·5×10^?4 eggs per h if one parent is present and 6·7×10^?4 eggs per h if two parents are present. Adult death by starvation is assumed to occur when energy reserves are exhausted; however a fitness cost is incurred if an animal maintains excess energy reserves. To restrict the number of behaviour sequences examined to manageable proportions, attention is restricted to the behaviour sequences that result from decision rules in which feeding occurs when energy reserves fall below a set point. Then optimal behaviour is characterized by (1) energy reserves maintained between 500 and 1200 kcal; (2) complementarity of mates' feeding preferences such that at least one of the pair feeds at a refuse tip; (3) parental desertion of offspring if energy reserves fall below 200 kcal; (4) parents spending the minimum possible time together on territory. These results are shown by sensitivity analysis to be insensitive to parameter errors in the model. Treating these characteristics of optimal behaviour as predictions about actual behaviour reveals that predictions 1 and 2 are correct, and prediction 4 is wrong. An experiment was designed to test prediction 3 by estimating the fat reserves of life birds and measuring how long each would continue incubation in the absence of its mate. Fatter birds did continue incubation for longer though the quantitative detail did not match prediction 3 exactly. Thus two aspects of behaviour tally with our calculation as to what is optimal, but one does not. This conclusion is discussed.     

Age-stratified QTL genome scan analyses for anthropometric measures

With the availability of longitudinal data, age-specific (stratified) or age-adjusted genetic analyses have the potential to localize different putative trait influencing loci. If age does not influence the locus-specific penetrance function within the range examined, age-stratified analyses will tend to yield comparable results for an individual trait. However, age-stratified results should vary across age strata when the locus-specific penetrance function is age dependent. In this paper, age-stratified and age-adjusted quantitative trait loci (QTL) linkage analyses were contrasted for height, weight, body mass index (BMI), and systolic blood pressure on a subset of the Framingham Heart Study. The strata comprised individuals with data present in each of three age groups: 31-49, 50-60, 61-79. Genome-wide QTL analyses were performed using SOLAR. Over all ages, a linkage signal for height was detected on chromosome 14q11.2 near marker GATA74E02A (LOD for ages 31-49 = 2.38, LOD for ages 50-60 = 1.84, LOD for ages 61-79 = 2.45). Evidence of linkage to BMI in the 31-49 age group was found on chromosome 3q22 (GATA3C02, LOD = 2.89, p = 0.0003) at the same location as the signal for weight (LOD = 3.10, p = 0.0002). Linkage was also supported on chromosome 1p22.1 for BMI (LOD = 2.21, p = 0.0014) and weight (LOD = 2.47, p = 0.0007) in the 31-49 age group. Our age-stratified results suggest that QTL that are expressed over long periods of time and affecting multiple, correlated traits may be identified using genome scan and variance-component methodology to help detect early and/or late gene expression.     

Conformation biases of amino acids based on tripeptide microenvironment from PDB database

We have constructed a bank (FTTP) of tendentious factors of three states of three-peptide units from PDB database based on conformational dihedral angle library and demonstrated that amino acid biases toward protein secondary structure are present in natural protein sequences. Our research results reveal that 20 standard amino acids fall into three groups: nine residues inclined to alpha-helix with a common character (e.g. direct side chain aliphatic residues or positive/negative charged residues) arrange in three grades, viz EA, QKRLD, and MN, in turn; seven residues are apt to beta-strand with 2'-branched side chain aliphatic residues or benzyl-included residues, namely PV, IYTC, and F, in three ranks; and four residues SHWG show a double tendency to both alpha and beta. Noticeably, proline has the strongest ability to form extended conformation, especially the Re value up to 9.5298 at position 3 (Table 3). Thus, biases of codons show an evident tendency in protein folding, where GC-rich codons are mainly in charge of forming contracted conformation, especially the codon's first letter plays a dominant role in translating the genomic GC signature into protein sequences and structures. So, biases of amino acids will play an important role in protein folding, folding codons, refining domain, structure prediction, and structural genomics/proteomics.     

An empirical assessment of saddlepoint approximations for testing a logistic regression parameter.

Saddlepoint methods provide quick and easy approximations to significance levels for conditional tests of logistic regression parameters. We evaluate the accuracies of saddlepoint approximations for three well-known conditional tests: Bartlett's test for no three-factor interaction in a 2 x 2 x 2 table, the test for trend in a series of probabilities, and the exact test of no association in stratified 2 x 2 tables with a common odds ratio. General recommendations are suggested regarding the use of saddlepoint approximations for exact conditional significance levels.     

Consequences of impediments to animal movements at different scales: A conceptual framework and review

Aim

The persistence of animal populations depends on individuals moving successfully around a landscape, but habitat fragmentation can hinder this by reducing functional connectivity. The proximate cause of population declines in fragmented habitat is dependent on the spatial and temporal scales of movement restrictions.

Location

Global.

Methods

We present a conceptual framework highlighting the relationship between spatial and temporal scales, and three mechanisms through which detrimental impacts can occur when movement is disrupted in fragmented landscapes: limited resource access, restricted demographic exchange and impeded gene flow. We then review the literature to identify the proportion of studies conducted on each mechanism and whether biases existed in how often each was studied among different geographic zones or taxa. A random selection of 250 articles was classified by the mechanism, geographic region and taxon studied in each article.

Results

Our conceptual framework highlighted that each of the three mechanisms tends to be characterized by movement restriction at progressively larger spatial and temporal scales. In our literature review, we found that the overwhelming majority (77%) of articles investigated impeded gene flow, and only 17% and 10% explored restricted demographic exchange and limited resource access, respectively. Work on limited resource access was disproportionately low for particular taxonomic groups, such as reptiles and amphibians.

Main conclusions

Distinguishing which mechanisms are disrupted in a particular system is crucial because addressing each is likely to require a distinct conservation management response. We encourage greater focus on the less‐studied mechanisms of restricted demographic exchange and limited resource access.     

Simultaneously correcting for population stratification and for genotyping error in case-control association studies

In population-based case-control association studies, the regular chi (2) test is often used to investigate association between a candidate locus and disease. However, it is well known that this test may be biased in the presence of population stratification and/or genotyping error. Unlike some other biases, this bias will not go away with increasing sample size. On the contrary, the false-positive rate will be much larger when the sample size is increased. The usual family-based designs are robust against population stratification, but they are sensitive to genotype error. In this article, we propose a novel method of simultaneously correcting for the bias arising from population stratification and/or for the genotyping error in case-control studies. The appropriate corrections depend on sample odds ratios of the standard 2x3 tables of genotype by case and control from null loci. Therefore, the test is simple to apply. The corrected test is robust against misspecification of the genetic model. If the null hypothesis of no association is rejected, the corrections can be further used to estimate the effect of the genetic factor. We considered a simulation study to investigate the performance of the new method, using parameter values similar to those found in real-data examples. The results show that the corrected test approximately maintains the expected type I error rate under various simulation conditions. It also improves the power of the association test in the presence of population stratification and/or genotyping error. The discrepancy in power between the tests with correction and those without correction tends to be more extreme as the magnitude of the bias becomes larger. Therefore, the bias-correction method proposed in this article should be useful for the genetic analysis of complex traits.     

Identifying and correcting spatial bias in opportunistic citizen science data for wild ungulates in Norway

Many publications make use of opportunistic data, such as citizen science observation data, to infer large‐scale properties of species’ distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species’ home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS‐telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species’ ecology. Models naïvely using opportunistic observations in habitat‐use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species’ RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat‐use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat‐use studies.     

Application of FTTP to alpha-helix or beta-strand motifs

Information concerning protein structure is widely dispersed and cannot easily and rapidly be processed by the biological community. We present a database of tendentious factors of three states of tripeptide units from PDB database, called a bank of tendentious factors of three states of three-peptide units (FTTP). The FTTP database was constructed based on conformational dihedral angle (varphi,psi) library of 20(3) peptide triplets by exhaustively searching through PDB databases. We introduce the FTTP database for the analysis of characteristics common to relative conformational biases of all peptide triplets, especially finding some motifs apt to alpha-helix and beta-strand. Our results show that this will provide a platform for studies of short peptide motifs, folding codons, secondary structure and three-dimensional (3D) structure of proteins. Moreover, FTTP is a unique resource that will allow a comprehensive characterization of peptide triplets and thus improve our understanding of sequence-structure relationship, refined domains, 3D structures, and their associated function. We believe the FTTP database will help biologists in increasing the efficiency of finding useful and relevant information regarding structure-function relationship of proteins. Therefore, this approach will play an important role in protein folding, protein engineering, molecular design, and proteomics.     

Assessing fear and anxiety in humans using the threat of predictable and unpredictable aversive events (the NPU-threat test)

The threat of predictable and unpredictable aversive events was developed to assess short-duration (fear) and long-duration (anxiety) aversive states in humans. A typical experiment consists of three conditions: a safe condition (neutral (N)), during which participants are safe from aversive stimuli, and two threat conditions-one in which aversive events are administered predictably (P) (i.e., signaled by a threat cue), and one in which aversive stimuli are administered unpredictably (U). During the so-called NPU-threat test, ongoing change in aversive states is measured with the startle reflex. The NPU-threat test has been validated in pharmacological and clinical studies and can be implemented in children and adults. Similar procedures have been applied in animal models, making the NPU-threat test an ideal tool for translational research. The procedure is relatively short (35 min), simple to implement and generates consistent results with large effect sizes.     

Biophysical and biochemical characterization of five animal viruses with bisegmented double-stranded RNA genomes.

Infectious pancreatic necrosis virus of fish, infectious bursal disease virus of chickens, Tellina virus and oyster virus of bivalve molluscs, and drosophila X virus of Drosophila melanogaster are naked icosahedral viruses with an electron microscopic diameter of 58 to 60 nm. The genome of each of these viruses consists of two segments of double-stranded RNA (molecular weight range between 2.6 x 10(6) and 2.2 x 10(6), and the virion, capsid proteins fall into three size class categories (large, medium, and small; ranging from 100,000 to 27,000) as determined by polyacrylamide slab gel electrophoresis. The hydrodynamic properties of the five viruses are similar as determined by analytical ultracentrifugation and laser quasi-elastic, light-scattering spectroscopy. The calculated particle weights range between 55 x 10(6) and 81 x 10(6). Tryptic peptide comparisons of 125I-labeled virion proteins showed that five viruses are different from each other, although there was considerable overlap in the peptide maps of the three aquatic viruses, indicting a degree of relatedness. Cross-neutralization tests indicated that drosophila X, infectious pancreatic necrosis, and infectious bursal disease viruses were different from each other and from oyster and Tellina viruses. The same test showed oyster and Tellina viruses to be related. The biochemical and biophysical properties of the five viruses cannt be included in the family Reoviridae or in any of the present virus genera.     

Age at Death of Creutzfeldt-Jakob Disease in Subsequent Family Generation Carrying the E200K Mutation of the Prion Protein Gene

Background

The E200K mutation of the prion protein gene (PRNP) is the most frequent amino acid substitution in genetic Creutzfeldt-Jakob disease and is the only one responsible for the appearance of clustered cases in the world. In the Israel and Slovakian clusters, age of disease onset was reduced in successive generations but the absence of a clear molecular basis raised the possibility that this event was an observational bias. The aim of the present study was to investigate possible selection biases or confounding factors related to anticipation in E200K CJD patients belonging to a cluster in Southern Italy.

Methods

Clinical and demographical data of 41 parent-offspring pairs from 19 pedigrees of the Italian cluster of E200K patients were collected. Age at death of parents was compared with age at death of E200K CJD offspring. Subgroup analyses were performed for controlling possible selection biases, confounding factors, or both.

Results

The mean age at death/last follow-up of the parent generation was 71.4 years while that of CJD offspring was 59.3 years with an estimated anticipation of 12.1 years. When the same analysis was performed including only parents with CJD or carrying the E200K mutation (n = 26), the difference between offspring and parents increased to 14.8 years.

Conclusions

These results show that early age at death occurs in offspring of families carrying the E200K PRNP mutation and that this event is not linked to observational biases. Although molecular or environmental bases for this occurrence remain unsettled, this information is important for improving the accuracy of information to give to mutated carriers.     

Interpretation of diagnostic data: 4. How to do it with a more complex table.

A more complex table is especially useful when a diagnostic test produces a wide range of results and your patient''s levels are near one of the extremes. The following guidelines will be useful: Identify the several cut-off points that could be used. Fill in a complex table along the lines of Table I, showing the numbers of patients at each level who have and do not have the target disorder. Generate a simple table for each cut-off point, as in Table II, and determine the sensitivity (TP rate) and specificity (TN rate) at each of them. Select the cut-off point that makes the most sense for your patient''s test result and proceed as in parts 2 and 3 of our series. Alternatively, construct an ROC curve by plotting the TP and FP rates that attend each cut-off point. If you keep your tables and ROC curves close at hand, you will gradually accumulate a set of very useful guides. However, if you looked very hard at what was happening, you will probably have noticed that they are not very useful for patients whose test results fall in the middle zones, or for those with just one positive result of two tests; the post-test likelihood of disease in these patients lurches back and forth past 50%, depending on where the cut-off point is. We will show you how to tackle this problem in part 5 of our series. It involves some maths, but you will find that its very powerful clinical application can be achieved with a simple nomogram or with some simple calculations.     

Experimental Chagas' disease in rhesus monkeys. I. Clinical, parasitological, hematological and anatomo-pathological studies in the acute and indeterminate phase of the disease

Rhesus monkeys (Macaca mulatta) were infected subcutaneously with 1.0 x 10(4) to 1.5 x 10(4) metacyclic trypomastigotes of Trypanosoma cruzi (Colombian strain). Parasitological and immunological parameters were evaluated in these animals for periods of 1 month to over 3 years. A chagoma was observed between the 3rd and the 13th day after infection (a.i.) and patent parasitaemia between the 13th and 59th day a.i.. Thereafter, parasites were demonstrated only by haemoculture and/or xenodiagnosis. Circulating specific IgM and IgG antibodies were observed as early as in the 2nd week a.i. IgG levels persisted until the end of the experiment, but IgM antibodies were detectable nine months a.i. Haematological alterations comprised leucocytosis and lymphocytosis. Electrocardiographic alterations were minor and transient, similar to those observed in non-lethal human acute Chagas' myocarditis. Myocarditis and myositis, characterized by multiple foci of lympho-histiocyte inflammatory infiltrate, were present in monkeys sacrificed on the 41st, 70th and 76th day but not in the animal sacrificed 3 years and 3 months a. i.. The results suggest that Chagas' disease in rhesus monkeys reproduces the acute and indeterminate phases of human Chagas' disease.     

A small molecule microarray platform to select RNA internal loop-ligand interactions.

Herein, we report the development of a microarray platform to select RNA motif-ligand interactions that allows simultaneous screening of both RNA and chemical space. We used this platform to identify the RNA internal loops that bind 6'- N-5-hexynoate kanamycin A ( 1). Selected internal loops that bind 1 were studied in detail and commonly display an adenine across from a cytosine independent of the size of the loop. Additional preferences are also observed. For 3 x 3 nucleotide loops, there is a preference for purines, and for 2 x 2 nucleotide loops there is a preference for pyrimidines neighbored by an adenine across from a cytosine. This technique has several advantageous features for selecting RNA motif-ligand interactions: (1) higher affinity RNA motif-ligand interactions are identified by harvesting bound RNAs from lower ligand loadings; (2) bound RNAs are harvested from the array via gel extraction, mitigating kinetic biases in selections; and (3) multiple selections are completed on a single array surface. To further demonstrate that multiple selections can be completed in parallel on the same array surface, we selected the RNA internal loops from a 4096-member RNA internal loop library that bound a four-member aminoglycoside library. These experiments probed 16,384 (4 aminoglycoside x 4096-member RNA library) interactions in a single experiment. These studies allow for parallel screening of both chemical and RNA space to improve our understanding of RNA-ligand interactions. This information may facilitate the rational and modular design of small molecules targeting RNA.     

Elucidating the Foundations of Statistical Inference with 2 x 2 Tables

To many, the foundations of statistical inference are cryptic and irrelevant to routine statistical practice. The analysis of 2 x 2 contingency tables, omnipresent in the scientific literature, is a case in point. Fisher''s exact test is routinely used even though it has been fraught with controversy for over 70 years. The problem, not widely acknowledged, is that several different p-values can be associated with a single table, making scientific inference inconsistent. The root cause of this controversy lies in the table''s origins and the manner in which nuisance parameters are eliminated. However, fundamental statistical principles (e.g., sufficiency, ancillarity, conditionality, and likelihood) can shed light on the controversy and guide our approach in using this test. In this paper, we use these fundamental principles to show how much information is lost when the tables origins are ignored and when various approaches are used to eliminate unknown nuisance parameters. We present novel likelihood contours to aid in the visualization of information loss and show that the information loss is often virtually non-existent. We find that problems arising from the discreteness of the sample space are exacerbated by p-value-based inference. Accordingly, methods that are less sensitive to this discreteness - likelihood ratios, posterior probabilities and mid-p-values - lead to more consistent inferences.     

Apparent diffusion coefficient in the aging mouse brain: a magnetic resonance imaging study

Novel magnetic resonance imaging sequences have and still continue to play an increasing role in neuroimaging and neuroscience. Among these techniques, diffusion-weighted imaging (DWI) has revolutionized the diagnosis and management of diseases such as stroke, neoplastic disease and inflammation. However, the effects of aging on diffusion are yet to be determined. To establish reference values for future experimental mouse studies we tested the hypothesis that absolute apparent diffusion coefficients (ADC) of the normal brain change with age. A total of 41 healthy mice were examined by T2-weighted imaging and DWI. For each animal ADC frequency histograms (i) of the whole brain were calculated on a voxel-by-voxel basis and region-of-interest (ROI) measurements (ii) performed and related to the animals' age. The mean entire brain ADC of mice <3 months was 0.715(+/-0.016) x 10(-3) mm2/s, no significant difference to mice aged 4 to 5 months (0.736(+/-0.040) x 10(-3) mm2/s) or animals older than 9 months 0.736(+/-0.020) x 10(-3) mm2/s. Mean whole brain ADCs showed a trend towards lower values with aging but both methods (i + ii) did not reveal a significant correlation with age. ROI measurements in predefined areas: 0.723(+/-0.057) x 10(-3) mm2/s in the parietal lobe, 0.659(+/-0.037) x 10(-3) mm2/s in the striatum and 0.679(+/-0.056) x 10(-3) mm2/s in the temporal lobe. With advancing age, we observed minimal diffusion changes in the whole mouse brain as well as in three ROIs by determination of ADCs. According to our data ADCs remain nearly constant during the aging process of the brain with a small but statistically non-significant trend towards a decreased diffusion in older animals.     

Modelling the Effects of Seasonality and Socioeconomic Impact on the Transmission of Rift Valley Fever Virus

Rift Valley fever (RVF) is an important mosquito-borne viral zoonosis in Africa and the Middle East that causes human deaths and significant economic losses due to huge incidences of death and abortion among infected livestock. Outbreaks of RVF are sporadic and associated with both seasonal and socioeconomic effects. Here we propose an almost periodic three-patch model to investigate the transmission dynamics of RVF virus (RVFV) among ruminants with spatial movements. Our findings indicate that, in Northeastern Africa, human activities, including those associated with the Eid al Adha feast, along with a combination of climatic factors such as rainfall level and hydrological variations, contribute to the transmission and dispersal of the disease pathogen. Moreover, sporadic outbreaks may occur when the two events occur together: 1) abundant livestock are recruited into areas at risk from RVF due to the demand for the religious festival and 2) abundant numbers of mosquitoes emerge. These two factors have been shown to have impacts on the severity of RVF outbreaks. Our numerical results present the transmission dynamics of the disease pathogen over both short and long periods of time, particularly during the festival time. Further, we investigate the impact on patterns of disease outbreaks in each patch brought by festival- and seasonal-driven factors, such as the number of livestock imported daily, the animal transportation speed from patch to patch, and the death rate induced by ceremonial sacrifices. In addition, our simulations show that when the time for festival preparation starts earlier than usual, the risk of massive disease outbreaks rises, particularly in patch 3 (the place where the religious ceremony will be held).