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PubMed2006

Models for vectors and vector-borne diseases.

The development of models for species' distributions is briefly reviewed, concentrating on logistic regression and discriminant analytical methods. Improvements in each type of modelling approach have led to increasingly accurate model predictions. This review addresses several key issues that now confront those wishing to choose the "right" sort of model for their own application. One major issue is the number of predictor variables to retain in the final model. Another is the problem of sparse datasets, or of data reported to administrative levels only, not to points. A third is the incorporation of spatial co-variance and auto-covariance in the modelling process. It is suggested that many of these problems can be resolved by adopting an information-theoretic approach whereby a group of reasonable potential models is specified in advance, and the "best" candidate model is selected among them. This approach of model selection and multi-model inference, using various derivatives of the Kullback-Leibler information or distance statistic, puts the biologist, with her or his insight, back in charge of the modelling process that is usually the domain of statisticians. Models are penalized when they contain too many variables; careful specification of the right set of candidate models may also be used to identify the importance of each predictor variable individually; and finally the degree to which the current "best" model improves on all the other models in the candidate set may be quantified. The ability definitely to exclude some models from the realm of all possible models appropriate for any particular distribution problem may be as important as the ability to identify the best current model.

Animals↗
PubMed2002

Subjective rating scales: science or art?

Subjective rating scales are widely used in almost every aspect of ergonomics research and practice for the assessment of workload, fatigue, usability, annoyance and comfort, and lesser known qualities such as urgency and presence, but are they truly scientific? This paper raises some of the key issues as a basis for debate. First, it is argued that all empirical observations, including those conventionally labelled as 'objective', are unavoidably subjective. Shared meaning between observers, or intersubjectivity, is the key criterion of scientific probity. The practical steps that can be taken to increase intersubjective agreement are discussed and the well-known sources of error and bias in human judgement reviewed. The role of conscious experience as a mechanism for appraising the environment and guiding behaviour has important implications for the interpretation of subjective reports. The view that psychometric measures do not conform to the requirements of truly 'scientific' measurement is discussed. Human judgement of subjective attributes is essentially ordinal and, unlike physical measures, can be matched to interval scales only with difficulty, but ordinal measures can be used successfully both to develop and test substantive theories using multivariate statistical techniques. Constructs such as fatigue are best understood as latent or inferred variables defined by a set of manifest or directly observed indicator variables. Both construct validity and predictive validity are viewed from this perspective and this helps to clarify several problems including the dissociation between measures of different aspects of a given construct, the question of whether physical (e.g. physiological) measures should be preferred to subjective measures and whether a single measure of constructs which are essentially multidimensional having both subjective and physical components is desirable. Finally, the fitness of subjective ratings to different purposes within the broad field of ergonomics research is discussed. For testing of competing hypotheses concerning the mechanisms underlying human performance, precise quantitative predictions are rarely needed. The same is frequently true of comparative evaluation of competing designs. In setting design standards, however, something approaching the level of measurement required for precise quantitative prediction is required, but this is difficult to achieve in practice. Although it may be possible to establish standards within restricted contexts, general standards for broadly conceived constructs such as workload are impractical owing to the requirement for representative sampling of tasks, work environments and personnel.

Ergonomics↗
PubMed2004

Dual spatial folds and different local structures of the HIV-1 immunogenic crown in various virus isolates.

Local and global structural properties of the HIV-1 principal neutralizing epitope were studied in terms of NMR spectroscopy data reported in literature for the HIV-Haiti and HIV-RF isolates. To this effect, the NMR-based method comprising a probabilistic model of protein conformation in conjunction with the molecular mechanics and quantum chemical computations was used for determining the ensembles of conformers matching the NMR requirements and energy criteria. As a matter of record, the high resolution 3D structure models were constructed for the HIV-Haiti and HIV-RF immunogenic crowns, and their geometric parameters were collated with the ones of conformers derived previously for describing the conformational features of immunogenic tip of gp120 from Thailand and MN HIV-1 strains. The HIV-1 neutralization site was demonstrated to constitute in water solution highly flexible system sensitive to its environment. This inference is completely valid for the geometric space of dihedral angles where statistically significant differences in local structures of simulated conformers have been found for all virus isolates of interest. In spite of this fact, the stretch analyzed was shown to manifest a certain conservatism in the space of atomic coordinates, building up in four HIV-1 isolates two spatial folds similar to those observed in crystal for the V3 loop peptides bound to different neutralizing Fabs. The results are discussed in the light of literature data on HIV-1 neutralizing epitope structure.

Amino Acid Sequence↗
PubMed2004

Effectiveness of mandatory license testing for older drivers in reducing crash risk among urban older Australian drivers.

Most licensing jurisdictions in Australia maintain mandatory assessment programs targeting older drivers, whereby a driver reaching a specified age is required to prove his or her fitness to drive through medical assessment and/or on-road testing. Previous studies both in Australia and elsewhere have consistently failed to demonstrate that age-based mandatory assessment results in reduced crash involvement for older drivers. However studies that have based their results upon either per-population or per-driver crash rates fail to take into account possible differences in driving activity. Because some older people maintain their driving licenses but rarely if ever drive, the proportion of inactive license-holders might be higher in jurisdictions without mandatory assessment relative to jurisdictions with periodic license assessment, where inactive drivers may more readily either surrender or lose their licenses. The failure to control for possible differences in driving activity across jurisdictions may be disguising possible safety benefits associated with mandatory assessment. The current study compared the crash rates of drivers in Melbourne, Australia, where there is no mandatory assessment and Sydney, Australia, where there is regular mandatory assessment from 80 years of age onward. The crash rate comparisons were based on four exposure measures: per population, per licensed driver, per distance driven, and per time spent driving. Poisson regression analysis incorporating an offset to control for inter-jurisdictional road safety differences indicated that there was no difference in crash risk for older drivers based on population. However drivers aged 80 years and older in the Sydney region had statistically higher rates of casualty crash involvement than their Melbourne counterparts on a per license issued basis (RR: 1.15, 1.02-1.29, p=0.02) and time spent driving basis (RR: 1.19, 1.06-1.34, p=0.03). A similar trend was apparent based on distance travelled but was of borderline statistical significance (RR: 1.11, 0.99-1.25, p=0.07). Collectively, it can be inferred from these findings that mandatory license re-testing schemes of the type evaluated have no demonstrable road safety benefits overall. Further research to resolve this on-going policy debate is discussed and recommended.

Accidents, Traffic↗
PubMed2002

A data-mining approach to spacer oligonucleotide typing of Mycobacterium tuberculosis.

MOTIVATION: The Direct Repeat (DR) locus of Mycobacterium tuberculosis is a suitable model to study (i) molecular epidemiology and (ii) the evolutionary genetics of tuberculosis. This is achieved by a DNA analysis technique (genotyping), called sp acer oligo nucleotide typing (spoligotyping ). In this paper, we investigated data analysis methods to discover intelligible knowledge rules from spoligotyping, that has not yet been applied on such representation. This processing was achieved by applying the C4.5 induction algorithm and knowledge rules were produced. Finally, a Prototype Selection (PS) procedure was applied to eliminate noisy data. This both simplified decision rules, as well as the number of spacers to be tested to solve classification tasks. In the second part of this paper, the contribution of 25 new additional spacers and the knowledge rules inferred were studied from a machine learning point of view. From a statistical point of view, the correlations between spacers were analyzed and suggested that both negative and positive ones may be related to potential structural constraints within the DR locus that may shape its evolution directly or indirectly. RESULTS: By generating knowledge rules induced from decision trees, it was shown that not only the expert knowledge may be modeled but also improved and simplified to solve automatic classification tasks on unknown patterns. A practical consequence of this study may be a simplification of the spoligotyping technique, resulting in a reduction of the experimental constraints and an increase in the number of samples processed.

Algorithms↗
PubMed2003

Optimal alphabets for an RNA world.

Experiments have shown that the canonical AUCG genetic alphabet is not the only possible nucleotide alphabet. In this work we address the question 'is the canonical alphabet optimal?' We make the assumption that the genetic alphabet was determined in the RNA world. Computational tools are used to infer the RNA secondary structure (shape) from a given RNA sequence, and statistics from RNA shapes are gathered with respect to alphabet size. Then, simulations based upon the replication and selection of fixed-sized RNA populations are used to investigate the effect of alternative alphabets upon RNA's ability to step through a fitness landscape. These results show that for a low copy fidelity the canonical alphabet is fitter than two-, six- and eight-letter alphabets. In higher copy-fidelity experiments, six-letter alphabets outperform the four-letter alphabets, suggesting that the canonical alphabet is indeed a relic of the RNA world.

Animals↗
PubMed2003

Mixtures of general linear models for functional neuroimaging.

We set out a new general framework for making inferences from neuroimaging data, which includes a standard approach to neuroimaging analysis, statistical parametric mapping (SPM), as a special case. The model offers numerous conceptual and statistical advantages that derive from analyzing data at the "cluster level" rather than the "voxel level" and from explicit modeling of the shape and position of clusters of activation. This provides a natural and principled way to pool data from nearby voxels for parameter and variance-component estimation. The model can also be viewed as performing a spatio-temporal cluster analysis. The parameters of the model are estimated using an expectation maximization (EM) algorithm.

Acoustic Stimulation↗
PubMedDate not supplied

Multimodel ranking and inference in ground water modeling.

Uncertainty of hydrogeologic conditions makes it important to consider alternative plausible models in an effort to evaluate the character of a ground water system, maintain parsimony, and make predictions with reasonable definition of their uncertainty. When multiple models are considered, data collection and analysis focus on evaluation of which model(s) is(are) most supported by the data. Generally, more than one model provides a similar acceptable fit to the observations; thus, inference should be made from multiple models. Kullback-Leibler (K-L) information provides a rigorous foundation for model inference that is simple to compute, is easy to interpret, selects parsimonious models, and provides a more realistic measure of precision than evaluation of any one model or evaluation based on other commonly referenced model selection criteria. These alternative criteria strive to identify the true (or quasi-true) model, assume it is represented by one of the models in the set, and given their preference for parsimony regardless of the available number of observations the selected model may be underfit. This is in sharp contrast to the K-L information approach, where models are considered to be approximations to reality, and it is expected that more details of the system will be revealed when more data are available. We provide a simple, computer-generated example to illustrate the procedure for multimodel inference based on K-L information and present arguments, based on statistical underpinnings that have been overlooked with time, that its theoretical basis renders it preferable to other approaches.

Evaluation Studies as Topic↗
PubMed2003

Sympatric Plasmodium falciparum isolates from Venezuela have structured var gene repertoires.

BACKGROUND: The human malaria parasite Plasmodium falciparum expresses adhesins belonging to the erythrocyte membrane protein 1 (PfEMP1) family on the surface of the infected host erythrocyte. These antigens elicit a strain-specific antibody response that is associated with protection from disease. During clonal expansion of blood-stage parasites, the surface phenotype of the infected erythrocyte changes because of transcriptional switching among the 40 to 50 members of the highly polymorphic var multi-gene family which encode PfEMP1 variants. Studies to date have compared var repertoires of natural isolates from various geographical locations but have not addressed any within-population structure that may exist among repertoires. METHODS: Distinct parasite genotypes from a single population co-circulating among a defined group of hosts were selected. PCR products encoding the DBL-alpha domain of PfEMP-1 were cloned and sequenced from each of three isolates. Repertoire similarity was statistically evaluated using combinatorial analysis. The chromosomal location of shared sequences was inferred from similarity to dbl-alpha of known location in the 3D7 genome. RESULTS: Sympatric parasites were found to share few var gene sequences, even when alleles at other polymorphic loci were shared. A number of the sequences shared by at least two of the isolates studied were found to be related to 3D7 genomic sequences with non-telomeric chromosomal locations, or atypical domain structures, which may represent globally conserved loci. CONCLUSION: The parasite population studied is structured, with minimal overlap in PfEMP1 repertoires. The var gene family accumulates diversity more rapidly than other antigen genes examined. This may be facilitated by ectopic recombination among the sub-telomeric regions of P. falciparum chromosomes.

Adolescent↗
PubMed2026

Multi-omics uncovers the pleiotropic genetic mechanisms linking MASLD and cardiometabolic syndromes.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular-kidney-metabolic (CKM) syndrome are interrelated conditions with shared pathophysiological features; however, the genetic architecture underlying their relationship has not been fully elucidated. Deciphering this shared genetic basis holds promise for advancing mechanistic insights and therapeutic discovery. METHODS: We performed an integrated genome-wide cross-trait analysis using GWAS summary statistics for MASLD and 38 CKM traits. Our analysis estimated genetic correlations, inferred causal relationships, and identified pleiotropic variants. Candidate causal genes and druggable targets were subsequently prioritized through integrating multi-omics data. RESULTS: MASLD exhibited significant genetic correlations with 16 CKM traits, especially metabolic and cardiovascular conditions. Bidirectional causal relationships were observed between MASLD and T2D, adiposity, and lipid traits. We discovered 116 pleiotropic loci, including 65 shared causal variants such as rs429358 near APOE, which exerted influence across multiple traits. Gene-based analyses prioritized 152 unique candidate pleiotropic genes, enriched in lipid and cholesterol metabolism, and highly expressed in the liver, adipose, and immune-related cell types, such as macrophages and endothelial cells. Multi-omics integration validated 131 genes using eQTL and pQTL data from multiple tissues and cohorts. Notably, FTO and APOE emerged as central pleiotropic hubs, and druggability evaluation highlighted APOE, LPL, PPARG, and GPBAR1 as established therapeutic targets for metabolic diseases. CONCLUSION: This study provides a comprehensive map of the shared genetic architecture between MASLD and CKM syndrome, reveals novel causal genes and repurposable drug targets, and offers insights into precision medicine approaches for cardiometabolic and liver diseases.

Humans↗
PubMed2026

NLCD: A method to discover nonlinear causal relations among genes.

Distinguishing correlation from causation is a fundamental challenge in many scientific fields, including biology, especially when interventions like randomized controlled trials are infeasible and only observational data are available. Methods based on statistical tests of conditional independence within the Mendelian Randomization framework can detect causality between two observed variables that are each associated with a third instrumental variable. However, these methods for detecting causal relationships between traits (e.g., two gene expression or clinical traits associated with a genetic variant, all observed in the same population) often assume a linear relationship, thereby hindering the discovery of causal gene networks from genomics data. We have developed NLCD, a method for NonLinear Causal Discovery from genomics data based on nonlinear regression modeling and conditional feature importance scoring. NLCD uses these techniques to extend the statistical tests in an existing linear causal discovery method called the Causal Inference Test (CIT). We benchmarked NLCD against current state-of-the-art methods: CIT, Findr, and MRPC. On simulated datasets, NLCD performs comparably to most methods in detecting linear relations (Average AUPRC (Area Under the Precision-Recall Curve) of NLCD = 0.94, CIT = 0.94, Findr = 0.94, and MRPC = 0.99), and outperforms them in detecting nonlinear (sine and sawtooth type) relations between two genes (Average AUPRC of NLCD = 0.76, CIT = 0.60, Findr = 0.56, and MRPC = 0.73). When tested on a nonlinear subset of a yeast genomic dataset to recover known causal relations involving transcription factors, NLCD and CIT performed comparable to each other and slightly better than Findr and MRPC (Average AUPRC of NLCD = 0.82, CIT = 0.81, Findr = 0.71, and MRPC = 0.54). On application to a human genomic dataset, NLCD revealed active causal gene pairs (IRF1 → PSME1 and HLA-C → HLA-T) in the muscle tissue, and clarified the promises and challenges in discovering causal gene networks in tissues under in vivo human settings.

Humans↗
PubMed1999

Facilitation of seizures in limbic epileptic rats by complex 1 microTesla magnetic fields.

On three separate sessions 24 male rats with histories of limbic epilepsy were exposed to 10 temporal configurations for 5 min. each of one of two patterns of magnetic fields. Their intensities averaged about 1 microTesla (microT). The numbers of Level 5 (Racine) seizures, inferred by the rat's rearing, rapid forelimb clonus, and falling, were statistically more frequent for the frequency-modulated (Thomas) pattern when its pixel duration and interstimulus presentation were 3 msec. The effectiveness of this temporal configuration was replicated in a second within-subjects experiment (n = 9) that directly compared the numbers of seizures during exposures to each of the two patterns and to a sham-field. These results suggest that brains with sensitive limbic systems might respond to weak magnetic fields, generated from multiple overlapping fields from communication and computer systems whose temporal derivatives emerge as complex sequences with pixel durations within the millisecond range.

Animals↗
PubMed2001

Population distribution of human flavin-containing monooxygenase form 3: gene polymorphisms.

The N-oxygenation of amines by the human flavin-containing monooxygenase (form 3) (FMO3) represents an important means for the conversion of lipophilic nucleophilic heteroatom-containing compounds into more polar and readily excreted products. Certain mutations of the human FMO3 gene have been linked to abnormal drug or chemical metabolism. For example, abnormal N-oxygenation of trimethylamine has been shown to segregate with mutations of human FMO3. To date, however, it is not known whether there is a pharmacogenetic basis for abnormal drug metabolism by human FMO3. The objective of this study was to estimate the allele and genotype frequencies at three variable DNA sites in the FMO3 gene in male and female blood bank donors representative of non-Hispanic Caucasians, non-Hispanic African Americans, Hispanics, and Asians sampled from the United States. The common polymorphisms at variable sites 158, 257, and 308 were experimentally determined using a high-throughput chip-based genotype variation detection method combining MassEXTEND and matrix-assisted laser desorption ionization time-of-flight mass spectrometry. We also compared the genetic variation of nonhuman primate FMO3 with the human FMO3 gene. Exon sequence analysis of the monkey FMO3 gene sequence showed that it was similar to the human gene sequence but differed from the human consensus sequence at 31 fixed positions. Compared with that of human, the chimpanzee exon sequence had one polymorphism that induced an amino acid change. The evolutionary history of the FMO3 gene was inferred from the pattern of haplotype relationships across different populations and species. Statistically significant heterogeneity in the relative frequencies of single and multiple site alleles, haplotypes, and genotypes of the human FMO3 among ethnic subdivisions suggests that population differences in the susceptibility of humans to abnormal metabolism or adverse drug reactions for chemicals metabolized by human FMO3 could exist.

Alleles↗
PubMed2001

Philosophy and phylogenetic inference: a comparison of likelihood and parsimony methods in the context of Karl Popper's writings on corroboration.

Advocates of cladistic parsimony methods have invoked the philosophy of Karl Popper in an attempt to argue for the superiority of those methods over phylogenetic methods based on Ronald Fisher's statistical principle of likelihood. We argue that the concept of likelihood in general, and its application to problems of phylogenetic inference in particular, are highly compatible with Popper's philosophy. Examination of Popper's writings reveals that his concept of corroboration is, in fact, based on likelihood. Moreover, because probabilistic assumptions are necessary for calculating the probabilities that define Popper's corroboration, likelihood methods of phylogenetic inference--with their explicit probabilistic basis--are easily reconciled with his concept. In contrast, cladistic parsimony methods, at least as described by certain advocates of those methods, are less easily reconciled with Popper's concept of corroboration. If those methods are interpreted as lacking probabilistic assumptions, then they are incompatible with corroboration. Conversely, if parsimony methods are to be considered compatible with corroboration, then they must be interpreted as carrying implicit probabilistic assumptions. Thus, the non-probabilistic interpretation of cladistic parsimony favored by some advocates of those methods is contradicted by an attempt by the same authors to justify parsimony methods in terms of Popper's concept of corroboration. In addition to being compatible with Popperian corroboration, the likelihood approach to phylogenetic inference permits researchers to test the assumptions of their analytical methods (models) in a way that is consistent with Popper's ideas about the provisional nature of background knowledge.

History, 20th Century↗
PubMed2006

A tutorial on statistical methods for population association studies.

Although genetic association studies have been with us for many years, even for the simplest analyses there is little consensus on the most appropriate statistical procedures. Here I give an overview of statistical approaches to population association studies, including preliminary analyses (Hardy-Weinberg equilibrium testing, inference of phase and missing data, and SNP tagging), and single-SNP and multipoint tests for association. My goal is to outline the key methods with a brief discussion of problems (population structure and multiple testing), avenues for solutions and some ongoing developments.

Genetics, Medical↗
PubMed1997

Statistical methods for two-sequence three-period cross-over designs with incomplete data.

In clinical trials, and in bioavailability and bioequivalence studies, one often encounters replicate cross-over designs such as a two-sequence three-period cross-over design to assess treatment and carry-over effects of two formulations of a drug product. Because of the potential dropout (or for some administrative reason), however, the observed data set from a replicate cross-over design is incomplete or unbalanced so that standard statistical methods for a cross-over design may not apply directly. For inference on the treatment and carry-over effects, we propose a method based on differences of the observations that eliminates the random subject effects and thus does not require any distributional condition on the random subject effects. When no datum is missing, this method provides the same results as the ordinary least squares method. When there are missing data, the proposed method still provides exact confidence intervals for the treatment and carry-over effects, as long as the dropout is independent of the measurement errors. We provide an example for illustration.

Clinical Trials as Topic↗
PubMedDate not supplied

Critical thinking skills and dispositions of baccalaureate nursing students--a conceptual model for evaluation.

To date, little has been written on specifically what critical thinking is and what the scores reported on critical thinking instruments actually represent. This lack of specificity provided the impetus to examine critical thinking skills and dispositions of baccalaureate nursing students, to ascertain whether or not a significant difference exists between academic levels, and to ascertain, using the California Critical Thinking Skills Test (CCTST) and the California Critical Thinking Disposition Inventory (CCTDI), whether a relationship exists between nursing students' critical thinking skills and their critical thinking dispositions. The conceptualization of critical thinking consisting of two dimensions, cognitive skills and affective dispositions, developed by a panel of experts comprised the conceptual framework for this study. A cross-sectional, descriptive, comparative, and correlational study was undertaken in which two instruments, CCTST, Form A, and the CCTDI were administered to a convenience sample of nursing students representing five academic levels. The sample in the statistical analyses comprised 328 students. Results indicated that the total critical thinking mean score for students at each level reflected percentile ranking ranging between 48 and 65 per cent. The mean score for the critical thinking subscale, inference, had the lowest percentile rankings, ranging between 37 and 55 per cent. The analysis of variance (ANOVA) statistical analysis indicated that students at the junior I level had the highest critical thinking mean scores, and students at the sophomore II level attained the lowest scores, reflecting a significant difference (P < or = .05). ANOVA also indicated a significant difference in the total critical thinking disposition mean scores between students at the junior I and senior I and II levels and those at the sophomore II level (P < or = .0000). Results indicated weak truth-seeking disposition scores among students at all levels. Pearson Product Moment Correlation Coefficient yielded a significant positive relationship between critical thinking skills and critical thinking dispositions (P < or = .01). The conceptual model, as well as its relevancy to the professional standards of Essentials for College and University Education for Professional Nursing (AACN, 1986), is presented. Recommendations are discussed in regard to nursing education, curriculum, and research.

Analysis of Variance↗
PubMed2003

A model to estimate the optimal sample size for microbiological surveys.

Estimating optimal sample size for microbiological surveys is a challenge for laboratory managers. When insufficient sampling is conducted, biased inferences are likely; however, when excessive sampling is conducted valuable laboratory resources are wasted. This report presents a statistical model for the estimation of the sample size appropriate for the accurate identification of the bacterial subtypes of interest in a specimen. This applied model for microbiology laboratory use is based on a Bayesian mode of inference, which combines two inputs: (ii) a prespecified estimate, or prior distribution statement, based on available scientific knowledge and (ii) observed data. The specific inputs for the model are a prior distribution statement of the number of strains per specimen provided by an informed microbiologist and data from a microbiological survey indicating the number of strains per specimen. The model output is an updated probability distribution of strains per specimen, which can be used to estimate the probability of observing all strains present according to the number of colonies that are sampled. In this report two scenarios that illustrate the use of the model to estimate bacterial colony sample size requirements are presented. In the first scenario, bacterial colony sample size is estimated to correctly identify Campylobacter amplified restriction fragment length polymorphism types on broiler carcasses. The second scenario estimates bacterial colony sample size to correctly identify Salmonella enterica serotype Enteritidis phage types in fecal drag swabs from egg-laying poultry flocks. An advantage of the model is that as updated inputs from ongoing surveys are incorporated into the model, increasingly precise sample size estimates are likely to be made.

Animals↗