Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Lifelong dynamics of human CD4+CD25+ regulatory T cells: insights from in vivo data and mathematical modeling.

Despite their limited proliferation capacity, regulatory T cells (T(regs)) constitute a population maintained over the entire lifetime of a human organism. The means by which T(regs) sustain a stable pool in vivo are controversial. Using a mathematical model, we address this issue by evaluating several biological scenarios of the origins and the proliferation capacity of two subsets of T(regs): precursor CD4(+)CD25(+)CD45RO(-) and mature CD4(+)CD25(+)CD45RO(+) cells. The lifelong dynamics of T(regs) are described by a set of ordinary differential equations, driven by a stochastic process representing the major immune reactions involving these cells. The model dynamics are validated using data from human donors of different ages. Analysis of the data led to the identification of two properties of the dynamics: (1) the equilibrium in the CD4(+)CD25(+)FoxP3(+)T(regs) population is maintained over both precursor and mature T(regs) pools together, and (2) the ratio between precursor and mature T(regs) is inverted in the early years of adulthood. Then, using the model, we identified three biologically relevant scenarios that have the above properties: (1) the unique source of mature T(regs) is the antigen-driven differentiation of precursors that acquire the mature profile in the periphery and the proliferation of T(regs) is essential for the development and the maintenance of the pool; there exist other sources of mature T(regs), such as (2) a homeostatic density-dependent regulation or (3) thymus- or effector-derived T(regs), and in both cases, antigen-induced proliferation is not necessary for the development of a stable pool of T(regs). This is the first time that a mathematical model built to describe the in vivo dynamics of regulatory T cells is validated using human data. The application of this model provides an invaluable tool in estimating the amount of regulatory T cells as a function of time in the blood of patients that received a solid organ transplant or are suffering from an autoimmune disease.

An interdisciplinary HIV-adherence program combining motivational interviewing and electronic antiretroviral drug monitoring.

To ensure successful treatment, HIV patients must maintain a high degree of medication adherence over time. Since August 2004, patients who are (or are at risk of) experiencing problems with their HIV antiretroviral therapy (ART) have been referred by their physicians to an interdisciplinary HIV-adherence program. The program consists of a multifactorial intervention along with electronic drug monitoring (MEMS(TM)). The pharmacists organize individualized semi-structured motivational interviews based on cognitive, emotional, behavioral, and social issues. At the end of each session, the patient brings an adherence report to the physician. This enables the physician to use the adherence results to evaluate the treatment plan. The aim of this study was to retrospectively analyze this on-going interdisciplinary HIV-adherence program. All patients who were included between August 2004 and the end of April 2008 were analyzed. One hundred and four patients were included (59% women, median age 39 (31.0, 46.0) years, 42% black ethnicity). Eighty (77%) patients were ART-experienced patients and 59% had a protease inhibitor-based treatment. The retention rate was high (92%) in the program. Patient inclusion in this HIV-adherence program was determined by patient issues for naive patients and by nonadherence or suboptimal clinical outcomes for ART-experienced patients. The median time spent by a subject at the pharmacy was 35 (25.0, 48.0) minutes, half for the medication handling and half for the interview. The adherence results showed a persistence of 87% and an execution of 88%. Proportion of undetectable subjects increased during study. In conclusion, retention and persistence rates were high in this highly selected problematic population.

A neuron-specific deletion of the microRNA-processing enzyme DICER induces severe but transient obesity in mice.

MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression post-transcriptionally. MiRNAs are implicated in various biological processes associated with obesity, including adipocyte differentiation and lipid metabolism. We used a neuronal-specific inhibition of miRNA maturation in adult mice to study the consequences of miRNA loss on obesity development. Camk2a-CreERT2 (Cre+) and floxed Dicer (Dicerlox/lox) mice were crossed to generate tamoxifen-inducible conditional Dicer knockouts (cKO). Vehicle- and/or tamoxifen-injected Cre+;Dicerlox/lox and Cre+;Dicer+/+ served as controls. Four cohorts were used to a) measure body composition, b) follow food intake and body weight dynamics, c) evaluate basal metabolism and effects of food deprivation, and d) assess the brain transcriptome consequences of miRNA loss. cKO mice developed severe obesity and gained 18 g extra weight over the 5 weeks following tamoxifen injection, mainly due to increased fat mass. This phenotype was highly reproducible and observed in all 38 cKO mice recorded and in none of the controls, excluding possible effects of tamoxifen or the non-induced transgene. Development of obesity was concomitant with hyperphagia, increased food efficiency, and decreased activity. Surprisingly, after reaching maximum body weight, obese cKO mice spontaneously started losing weight as rapidly as it was gained. Weight loss was accompanied by lowered O2-consumption and respiratory-exchange ratio. Brain transcriptome analyses in obese mice identified several obesity-related pathways (e.g. leptin, somatostatin, and nemo-like kinase signaling), as well as genes involved in feeding and appetite (e.g. Pmch, Neurotensin) and in metabolism (e.g. Bmp4, Bmp7, Ptger1, Cox7a1). A gene cluster with anti-correlated expression in the cerebral cortex of post-obese compared to obese mice was enriched for synaptic plasticity pathways. While other studies have identified a role for miRNAs in obesity, we here present a unique model that allows for the study of processes involved in reversing obesity. Moreover, our study identified the cortex as a brain area important for body weight homeostasis.

Validation and performance comparison of two carbon isotope ratio methods to control the misuse of androgens in humans.

Carbon isotope ratio of androgens in urine specimens is routinely determined to exclude an abuse of testosterone or testosterone prohormones by athletes. Increasing application of gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS) in the last years for target and systematic investigations on samples has resulted in the demand for rapid sample throughput as well as high selectivity in the extraction process particularly in the case of conspicuous samples. For that purpose, we present herein the complimentary use of an SPE-based assay and an HPLC fractionation method as a two-stage strategy for the isolation of testosterone metabolites and endogenous reference compounds prior to GC/C/IRMS analyses. Assays validation demonstrated acceptable performance in terms of intermediate precision (range: 0.1-0.4 per thousand) and Bland-Altman analyses revealed no significant bias (0.2 per thousand). For further validation of this two-stage analyses strategy, all the specimens (n=124) collected during a major sport event were processed.

Practical signal-to-noise ratio quantification for sensitivity encoding: Application to coronary MR angiography.

Purpose: To develop and evaluate a practical method for the quantification of signal-to-noise ratio (SNR) on coronary MR angiograms (MRA) acquired with parallel imaging.Materials and Methods: To quantify the spatially varying noise due to parallel imaging reconstruction, a new method has been implemented incorporating image data acquisition followed by a fast noise scan during which radio-frequency pulses, cardiac triggering and navigator gating are disabled. The performance of this method was evaluated in a phantom study where SNR measurements were compared with those of a reference standard (multiple repetitions). Subsequently, SNR of myocardium and posterior skeletal muscle was determined on in vivo human coronary MRA.Results: In a phantom, the SNR measured using the proposed method deviated less than 10.1% from the reference method for small geometry factors (<= 2). In vivo, the noise scan for a 10 min coronary MRA acquisition was acquired in 30 s. Higher signal and lower SNR, due to spatially varying noise, were found in myocardium compared with posterior skeletal muscle.Conclusion: SNR quantification based on a fast noise scan is a validated and easy-to-use method when applied to three-dimensional coronary MRA obtained with parallel imaging as long as the geometry factor remains low.

Between-year variation in population sex ratio increases with complexity of the breeding system in Hymenoptera.

While adaptive adjustment of sex ratio in the function of colony kin structure and food availability commonly occurs in social Hymenoptera, long-term studies have revealed substantial unexplained between-year variation in sex ratio at the population level. In order to identify factors that contribute to increased between-year variation in population sex ratio, we conducted a comparative analysis across 47 Hymenoptera species differing in their breeding system. We found that between-year variation in population sex ratio steadily increased as one moved from solitary species, to primitively eusocial species, to single-queen eusocial species, to multiple-queen eusocial species. Specifically, between-year variation in population sex ratio was low (6.6% of total possible variation) in solitary species, which is consistent with the view that in solitary species, sex ratio can vary only in response to fluctuations in ecological factors such as food availability. In contrast, we found significantly higher (19.5%) between-year variation in population sex ratio in multiple-queen eusocial species, which supports the view that in these species, sex ratio can also fluctuate in response to temporal changes in social factors such as queen number and queen-worker control over sex ratio, as well as factors influencing caste determination. The simultaneous adjustment of sex ratio in response to temporal fluctuations in ecological and social factors seems to preclude the existence of a single sex ratio optimum. The absence of such an optimum may reflect an additional cost associated with the evolution of complex breeding systems in Hymenoptera societies.

Genotype 3 is associated with accelerated fibrosis progression in chronic hepatitis C.

BACKGROUND/AIMS: While several risk factors for the histological progression of chronic hepatitis C have been identified, the contribution of HCV genotypes to liver fibrosis evolution remains controversial. The aim of this study was to assess independent predictors for fibrosis progression. METHODS: We identified 1189 patients from the Swiss Hepatitis C Cohort database with at least one biopsy prior to antiviral treatment and assessable date of infection. Stage-constant fibrosis progression rate was assessed using the ratio of fibrosis Metavir score to duration of infection. Stage-specific fibrosis progression rates were obtained using a Markov model. Risk factors were assessed by univariate and multivariate regression models. RESULTS: Independent risk factors for accelerated stage-constant fibrosis progression (>0.083 fibrosis units/year) included male sex (OR=1.60, [95% CI 1.21-2.12], P<0.001), age at infection (OR=1.08, [1.06-1.09], P<0.001), histological activity (OR=2.03, [1.54-2.68], P<0.001) and genotype 3 (OR=1.89, [1.37-2.61], P<0.001). Slower progression rates were observed in patients infected by blood transfusion (P=0.02) and invasive procedures or needle stick (P=0.03), compared to those infected by intravenous drug use. Maximum likelihood estimates (95% CI) of stage-specific progression rates (fibrosis units/year) for genotype 3 versus the other genotypes were: F0-->F1: 0.126 (0.106-0.145) versus 0.091 (0.083-0.100), F1-->F2: 0.099 (0.080-0.117) versus 0.065 (0.058-0.073), F2-->F3: 0.077 (0.058-0.096) versus 0.068 (0.057-0.080) and F3-->F4: 0.171 (0.106-0.236) versus 0.112 (0.083-0.142, overall P<0.001). CONCLUSIONS: This study shows a significant association of genotype 3 with accelerated fibrosis using both stage-constant and stage-specific estimates of fibrosis progression rates. This observation may have important consequences for the management of patients infected with this genotype.

Six novel susceptibility Loci for early-onset androgenetic alopecia and their unexpected association with common diseases.

Androgenetic alopecia (AGA) is a highly heritable condition and the most common form of hair loss in humans. Susceptibility loci have been described on the X chromosome and chromosome 20, but these loci explain a minority of its heritable variance. We conducted a large-scale meta-analysis of seven genome-wide association studies for early-onset AGA in 12,806 individuals of European ancestry. While replicating the two AGA loci on the X chromosome and chromosome 20, six novel susceptibility loci reached genome-wide significance (p = 2.62×10(-9)-1.01×10(-12)). Unexpectedly, we identified a risk allele at 17q21.31 that was recently associated with Parkinson's disease (PD) at a genome-wide significant level. We then tested the association between early-onset AGA and the risk of PD in a cross-sectional analysis of 568 PD cases and 7,664 controls. Early-onset AGA cases had significantly increased odds of subsequent PD (OR = 1.28, 95% confidence interval: 1.06-1.55, p = 8.9×10(-3)). Further, the AGA susceptibility alleles at the 17q21.31 locus are on the H1 haplotype, which is under negative selection in Europeans and has been linked to decreased fertility. Combining the risk alleles of six novel and two established susceptibility loci, we created a genotype risk score and tested its association with AGA in an additional sample. Individuals in the highest risk quartile of a genotype score had an approximately six-fold increased risk of early-onset AGA [odds ratio (OR) = 5.78, p = 1.4×10(-88)]. Our results highlight unexpected associations between early-onset AGA, Parkinson's disease, and decreased fertility, providing important insights into the pathophysiology of these conditions.

Adaptation to experimental alterations of the operational sex ratio in populations of Drosophila melanogaster.

Theory predicts that males adapt to sperm competition by increasing their investment in testis mass to transfer larger ejaculates. Experimental and comparative data support this prediction. Nevertheless, the relative importance of sperm competition in testis size evolution remains elusive, because experiments vary only sperm competition whereas comparative approaches confound it with other variables, in particular male mating rate. We addressed the relative importance of sperm competition and male mating rate by taking an experimental evolution approach. We subjected populations of Drosophila melanogaster to sex ratios of 1:1, 4:1, and 10:1 (female:male). Female bias decreased sperm competition but increased male mating rate and sperm depletion. After 28 generations of evolution, males from the 10:1 treatment had larger testes than males from other treatments. Thus, testis size evolved in response to mating rate and sperm depletion, not sperm competition. Furthermore, our experiment demonstrated that drift associated with sex ratio distortion limits adaptation; testis size only evolved in populations in which the effect of sex ratio bias on the effective population size had been compensated by increasing the numerical size. We discuss these results with respect to reproductive evolution, genetic drift in natural and experimental populations, and consequences of natural sex ratio distortion.

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

Subject-based steroid profiling and the determination of novel biomarkers for DHT and DHEA misuse in sports.

Doping with natural steroids can be detected by evaluating the urinary concentrations and ratios of several endogenous steroids. Since these biomarkers of steroid doping are known to present large inter-individual variations, monitoring of individual steroid profiles over time allows switching from population-based towards subject-based reference ranges for improved detection. In an Athlete Biological Passport (ABP), biomarkers data are collated throughout the athlete's sporting career and individual thresholds defined adaptively. For now, this approach has been validated on a limited number of markers of steroid doping, such as the testosterone (T) over epitestosterone (E) ratio to detect T misuse in athletes. Additional markers are required for other endogenous steroids like dihydrotestosterone (DHT) and dehydroepiandrosterone (DHEA). By combining comprehensive steroid profiles composed of 24 steroid concentrations with Bayesian inference techniques for longitudinal profiling, a selection was made for the detection of DHT and DHEA misuse. The biomarkers found were rated according to relative response, parameter stability, discriminative power, and maximal detection time. This analysis revealed DHT/E, DHT/5β-androstane-3α,17β-diol and 5α-androstane-3α,17β-diol/5β-androstane-3α,17β-diol as best biomarkers for DHT administration and DHEA/E, 16α-hydroxydehydroepiandrosterone/E, 7β-hydroxydehydroepiandrosterone/E and 5β-androstane-3α,17β-diol/5α-androstane-3α,17β-diol for DHEA. The selected biomarkers were found suitable for individual referencing. A drastic overall increase in sensitivity was obtained. The use of multiple markers as formalized in an Athlete Steroidal Passport (ASP) can provide firm evidence of doping with endogenous steroids.

Social meets molecular: Combining phylogenetic and latent class analyses to understand HIV-1 transmission in Switzerland.

Switzerland has a complex human immunodeficiency virus (HIV) epidemic involving several populations. We examined transmission of HIV type 1 (HIV-1) in a national cohort study. Latent class analysis was used to identify socioeconomic and behavioral groups among 6,027 patients enrolled in the Swiss HIV Cohort Study between 2000 and 2011. Phylogenetic analysis of sequence data, available for 4,013 patients, was used to identify transmission clusters. Concordance between sociobehavioral groups and transmission clusters was assessed in correlation and multiple correspondence analyses. A total of 2,696 patients were infected with subtype B, 203 with subtype C, 196 with subtype A, and 733 with recombinant subtypes (mainly CRF02_AG and CRF01_AE). Latent class analysis identified 8 patient groups. Most transmission clusters of subtype B were shared between groups of gay men (groups 1-3) or between the heterosexual groups "heterosexual people of lower socioeconomic position" (group 4) and "injection drug users" (group 8). Clusters linking homosexual and heterosexual groups were associated with "older heterosexual and gay people on welfare" (group 5). "Migrant women in heterosexual partnerships" (group 6) and "heterosexual migrants on welfare" (group 7) shared non-B clusters with groups 4 and 5. Combining approaches from social and molecular epidemiology can provide insights into HIV-1 transmission and inform the design of prevention strategies.