62 resultados para Compositional Rule of Inference


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Mathematical methods combined with measurements of single-cell dynamics provide a means to reconstruct intracellular processes that are only partly or indirectly accessible experimentally. To obtain reliable reconstructions, the pooling of measurements from several cells of a clonal population is mandatory. However, cell-to-cell variability originating from diverse sources poses computational challenges for such process reconstruction. We introduce a scalable Bayesian inference framework that properly accounts for population heterogeneity. The method allows inference of inaccessible molecular states and kinetic parameters; computation of Bayes factors for model selection; and dissection of intrinsic, extrinsic and technical noise. We show how additional single-cell readouts such as morphological features can be included in the analysis. We use the method to reconstruct the expression dynamics of a gene under an inducible promoter in yeast from time-lapse microscopy data.

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Adaptation to different ecological environments can promote speciation. Although numerous examples of such 'ecological speciation' now exist, the genomic basis of the process, and the role of gene flow in it, remains less understood. This is, at least in part, because systems that are well characterized in terms of their ecology often lack genomic resources. In this study, we characterize the transcriptome of Timema cristinae stick insects, a system that has been researched intensively in terms of ecological speciation, but for which genomic resources have not been previously developed. Specifically, we obtained >1 million 454 sequencing reads that assembled into 84,937 contigs representing approximately 18,282 unique genes and tens of thousands of potential molecular markers. Second, as an illustration of their utility, we used these genomic resources to assess multilocus genetic divergence within both an ecotype pair and a species pair of Timema stick insects. The results suggest variable levels of genetic divergence and gene flow among taxon pairs and genes and illustrate a first step towards future genomic work in Timema.

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Directed evolution of life through millions of years, such as increasing adult body size, is one of the most intriguing patterns displayed by fossil lineages. Processes and causes of such evolutionary trends are still poorly understood. Ammonoids (externally shelled marine cephalopods) are well known to have experienced repetitive morphological evolutionary trends of their adult size, shell geometry and ornamentation. This study analyses the evolutionary trends of the family Acrochordiceratidae Arthaber, 1911 from the Early to Middle Triassic (251228 Ma). Exceptionally large and bed-rock-controlled collections of this ammonoid family were obtained from strata of Anisian age (Middle Triassic) in north-west Nevada and north-east British Columbia. They enable quantitative and statistical analyses of its morphological evolutionary trends. This study demonstrates that the monophyletic clade Acrochordiceratidae underwent the classical evolute to involute evolutionary trend (i.e. increasing coiling of the shell), an increase in its shell adult size (conch diameter) and an increase in the indentation of its shell suture shape. These evolutionary trends are statistically robust and seem more or less gradual. Furthermore, they are nonrandom with the sustained shift in the mean, the minimum and the maximum of studied shell characters. These results can be classically interpreted as being constrained by the persistence and common selection pressure on this mostly anagenetic lineage characterized by relatively moderate evolutionary rates. Increasing involution of ammonites is traditionally interpreted by increasing adaptation mostly in terms of improved hydrodynamics. However, this trend in ammonoid geometry can also be explained as a case of Copes rule (increasing adult body size) instead of functional explanation of coiling, because both shell diameter and shell involution are two possible paths for ammonoids to accommodate size increase.

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1.1 Fundamentals Chest pain is a common complaint in primary care patients (1 to 3% of all consultations) (1) and its aetiology can be miscellaneous, from harmless to potentially life threatening conditions. In primary care practice, the most prevalent aetiologies are: chest wall syndrome (43%), coronary heart disease (12%) and anxiety (7%) (2). In up to 20% of cases, potentially serious conditions as cardiac, respiratory or neoplasic diseases underlie chest pain. In this context, a large number of laboratory tests are run (42%) and over 16% of patients are referred to a specialist or hospitalized (2).¦A cardiovascular origin to chest pain can threaten patient's life and investigations run to exclude a serious condition can be expensive and involve a large number of exams or referral to specialist -­‐ often without real clinical need. In emergency settings, up to 80% of chest pains in patients are due to cardiovascular events (3) and scoring methods have been developed to identify conditions such as coronary heart disease (HD) quickly and efficiently (4-­‐6). In primary care, a cardiovascular origin is present in only about 12% of patients with chest pain (2) and general practitioners (GPs) need to exclude as safely as possible a potential serious condition underlying chest pain. A simple clinical prediction rule (CPR) like those available in emergency settings may therefore help GPs and spare time and extra investigations in ruling out CHD in primary care patients. Such a tool may also help GPs reassure patients with more common origin to chest pain.

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γ-Hydroxybutyric acid (GHB) is an endogenous short-chain fatty acid popular as a recreational drug due to sedative and euphoric effects, but also often implicated in drug-facilitated sexual assaults owing to disinhibition and amnesic properties. Whilst discrimination between endogenous and exogenous GHB as required in intoxication cases may be achieved by the determination of the carbon isotope content, such information has not yet been exploited to answer source inference questions of forensic investigation and intelligence interests. However, potential isotopic fractionation effects occurring through the whole metabolism of GHB may be a major concern in this regard. Thus, urine specimens from six healthy male volunteers who ingested prescription GHB sodium salt, marketed as Xyrem(®), were analysed by means of gas chromatography/combustion/isotope ratio mass spectrometry to assess this particular topic. A very narrow range of δ(13)C values, spreading from -24.810/00 to -25.060/00, was observed, whilst mean δ(13)C value of Xyrem(®) corresponded to -24.990/00. Since urine samples and prescription drug could not be distinguished by means of statistical analysis, carbon isotopic effects and subsequent influence on δ(13)C values through GHB metabolism as a whole could be ruled out. Thus, a link between GHB as a raw matrix and found in a biological fluid may be established, bringing relevant information regarding source inference evaluation. Therefore, this study supports a diversified scope of exploitation for stable isotopes characterized in biological matrices from investigations on intoxication cases to drug intelligence programmes.

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Phylogenetic reconstructions are a major component of many studies in evolutionary biology, but their accuracy can be reduced under certain conditions. Recent studies showed that the convergent evolution of some phenotypes resulted from recurrent amino acid substitutions in genes belonging to distant lineages. It has been suggested that these convergent substitutions could bias phylogenetic reconstruction toward grouping convergent phenotypes together, but such an effect has never been appropriately tested. We used computer simulations to determine the effect of convergent substitutions on the accuracy of phylogenetic inference. We show that, in some realistic conditions, even a relatively small proportion of convergent codons can strongly bias phylogenetic reconstruction, especially when amino acid sequences are used as characters. The strength of this bias does not depend on the reconstruction method but varies as a function of how much divergence had occurred among the lineages prior to any episodes of convergent substitutions. While the occurrence of this bias is difficult to predict, the risk of spurious groupings is strongly decreased by considering only 3rd codon positions, which are less subject to selection, as long as saturation problems are not present. Therefore, we recommend that, whenever possible, topologies obtained with amino acid sequences and 3rd codon positions be compared to identify potential phylogenetic biases and avoid evolutionarily misleading conclusions.

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INTRODUCTION: A clinical decision rule to improve the accuracy of a diagnosis of influenza could help clinicians avoid unnecessary use of diagnostic tests and treatments. Our objective was to develop and validate a simple clinical decision rule for diagnosis of influenza. METHODS: We combined data from 2 studies of influenza diagnosis in adult outpatients with suspected influenza: one set in California and one in Switzerland. Patients in both studies underwent a structured history and physical examination and had a reference standard test for influenza (polymerase chain reaction or culture). We randomly divided the dataset into derivation and validation groups and then evaluated simple heuristics and decision rules from previous studies and 3 rules based on our own multivariate analysis. Cutpoints for stratification of risk groups in each model were determined using the derivation group before evaluating them in the validation group. For each decision rule, the positive predictive value and likelihood ratio for influenza in low-, moderate-, and high-risk groups, and the percentage of patients allocated to each risk group, were reported. RESULTS: The simple heuristics (fever and cough; fever, cough, and acute onset) were helpful when positive but not when negative. The most useful and accurate clinical rule assigned 2 points for fever plus cough, 2 points for myalgias, and 1 point each for duration <48 hours and chills or sweats. The risk of influenza was 8% for 0 to 2 points, 30% for 3 points, and 59% for 4 to 6 points; the rule performed similarly in derivation and validation groups. Approximately two-thirds of patients fell into the low- or high-risk group and would not require further diagnostic testing. CONCLUSION: A simple, valid clinical rule can be used to guide point-of-care testing and empiric therapy for patients with suspected influenza.

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Le "Chest wall syndrome" (CWS) est défini comme étant une source bénigne de douleurs thoraciques, localisées sur la paroi thoracique antérieure et provoquées par une affection musculosquelettique. Le CWS représente la cause la plus fréquente de douleurs thoraciques en médecine de premier recours. Le but de cette étude est de développer et valider un score de prédiction clinique pour le CWS. Une revue de la littérature a d'abord été effectuée, d'une part pour savoir si un tel score existait déjà, et d'autre part pour retrouver les variables décrites comme étant prédictives d'un CWS. Le travail d'analyse statistique a été effectué avec les données issues d'une cohorte clinique multicentrique de patients qui avaient consulté en médecine de premier recours en Suisse romande avec une douleur thoracique (59 cabinets, 672 patients). Un diagnostic définitif avait été posé à 12 mois de suivi. Les variables pertinentes ont été sélectionnées par analyses bivariées, et le score de prédiction clinique a été développé par régression logistique multivariée. Une validation externe de ce score a été faite en utilisant les données d'une cohorte allemande (n= 1212). Les analyses bivariées ont permis d'identifier 6 variables caractérisant le CWS : douleur thoracique (ni rétrosternale ni oppressive), douleur en lancées, douleur bien localisée, absence d'antécédent de maladie coronarienne, absence d'inquiétude du médecin et douleur reproductible à la palpation. Cette dernière variable compte pour 2 points dans le score, les autres comptent pour 1 point chacune; le score total s'étend donc de 0 à 7 points. Dans la cohorte de dérivation, l'aire sous la courbe sensibilité/spécificité (courbe ROC) est de 0.80 (95% de l'intervalle de confiance : 0.76-0.83). Avec un seuil diagnostic de > 6 points, le score présente 89% de spécificité et 45% de sensibilité. Parmi tous les patients qui présentaient un CWS (n = 284), 71% (n = 201) avaient une douleur reproductible à la palpation et 45% (n= 127) sont correctement diagnostiqués par le score. Pour une partie (n = 43) de ces patients souffrant de CWS et correctement classifiés, 65 investigations complémentaires (30 électrocardiogrammes, 16 radiographies du thorax, 10 analyses de laboratoire, 8 consultations spécialisées, et une tomodensitométrie thoracique) avaient été réalisées pour parvenir au diagnostic. Parmi les faux positifs (n = 41), on compte trois angors stables (1.8% de tous les positifs). Les résultats de la validation externe sont les suivants : une aire sous la courbe ROC de 0.76 (95% de l'intervalle de confiance : 0.73-0.79) avec une sensibilité de 22% et une spécificité de 93%. Ce score de prédiction clinique pour le CWS constitue un complément utile à son diagnostic, habituellement obtenu par exclusion. En effet, pour les 127 patients présentant un CWS et correctement classifiés par notre score, 65 investigations complémentaires auraient pu être évitées. Par ailleurs, la présence d'une douleur thoracique reproductible à la palpation, bien qu'étant sa plus importante caractéristique, n'est pas pathognomonique du CWS.

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BACKGROUND: Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. METHODS: We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). RESULTS: The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result <or= 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%). INTERPRETATION: The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care.

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The evolution of altruism is a fundamental and enduring puzzle in biology. In a seminal paper Hamilton showed that altruism can be selected for when rb - c > 0, where c is the fitness cost to the altruist, b is the fitness benefit to the beneficiary, and r is their genetic relatedness. While many studies have provided qualitative support for Hamilton's rule, quantitative tests have not yet been possible due to the difficulty of quantifying the costs and benefits of helping acts. Here we use a simulated system of foraging robots to experimentally manipulate the costs and benefits of helping and determine the conditions under which altruism evolves. By conducting experimental evolution over hundreds of generations of selection in populations with different c/b ratios, we show that Hamilton's rule always accurately predicts the minimum relatedness necessary for altruism to evolve. This high accuracy is remarkable given the presence of pleiotropic and epistatic effects as well as mutations with strong effects on behavior and fitness (effects not directly taken into account in Hamilton's original 1964 rule). In addition to providing the first quantitative test of Hamilton's rule in a system with a complex mapping between genotype and phenotype, these experiments demonstrate the wide applicability of kin selection theory.

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Sequencing of pools of individuals (Pool-Seq) represents a reliable and cost-effective approach for estimating genome-wide SNP and transposable element insertion frequencies. However, Pool-Seq does not provide direct information on haplotypes so that, for example, obtaining inversion frequencies has not been possible until now. Here, we have developed a new set of diagnostic marker SNPs for seven cosmopolitan inversions in Drosophila melanogaster that can be used to infer inversion frequencies from Pool-Seq data. We applied our novel marker set to Pool-Seq data from an experimental evolution study and from North American and Australian latitudinal clines. In the experimental evolution data, we find evidence that positive selection has driven the frequencies of In(3R)C and In(3R)Mo to increase over time. In the clinal data, we confirm the existence of frequency clines for In(2L)t, In(3L)P and In(3R)Payne in both North America and Australia and detect a previously unknown latitudinal cline for In(3R)Mo in North America. The inversion markers developed here provide a versatile and robust tool for characterizing inversion frequencies and their dynamics in Pool-Seq data from diverse D. melanogaster populations.

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PURPOSE To evaluate the prevalence of acute coronary syndrome (ACS) in patients presenting initially with atypical chest pain and suspected to have pulmonary embolism (PE) or acute aortic syndromes (AAS). To evaluate the overlap between ACS, PE and AAS in routine practice and determine how many patients could have benefit from a single CT protocol to rule out ACS at the same time as PE and AAS. METHOD AND MATERIALS Our electronic hospital database revealed 1122 consecutive patients who underwent a thoracic CT angiography for PE or AAS from 2004 to 2006 (mean age, 63±13 years). Patients without chest pain were excluded from this study. Thus, 447 patients presented with isolated atypical chest were included in the analysis. All patients who underwent a thoracic CT scan previously received standard clinical care and were initially considered as non ACS. The final diagnosis was obtained by the hospital stay report. RESULTS Among the 447 patients with atypical chest pain, 25 (5.5%) were finally found to have ACS: 19 patients (4.2%) were suspected for PE and 6 (1. 3%) were suspected for AAS. There were 90 patients diagnosed to have PE, 89 (98.8%) of them were suspected for PE while only 1 (1%) was suspected for AAS. Eleven patients diagnosed to have AAS, 9 (82%) of them were suspected for AAS while 2 (18%) were suspected for PE. CONCLUSION In clinical practice, the overlap between PE, AAS and ACS is limited which make the triple rule-out studies less recommended to be done at the time being because of the high dose radiation. A double rule-out investigation is suggested to be done for patients being evaluated for atypical chest pain and suspected of having AAS or PE because of a significant overlap between the two entities as well it doesn't implicate any increment in radiation dose. CLINICAL RELEVANCE/APPLICATION With 64-slice CT, coronary circulation and total chest can be evaluated at the same time offering new opportunitie for the evaluation of three major life-threatening conditions :ACS,PE and AAS.

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Understanding and anticipating biological invasions can focus either on traits that favour species invasiveness or on features of the receiving communities, habitats or landscapes that promote their invasibility. Here, we address invasibility at the regional scale, testing whether some habitats and landscapes are more invasible than others by fitting models that relate alien plant species richness to various environmental predictors. We use a multi-model information-theoretic approach to assess invasibility by modelling spatial and ecological patterns of alien invasion in landscape mosaics and testing competing hypotheses of environmental factors that may control invasibility. Because invasibility may be mediated by particular characteristics of invasiveness, we classified alien species according to their C-S-R plant strategies. We illustrate this approach with a set of 86 alien species in Northern Portugal. We first focus on predictors influencing species richness and expressing invasibility and then evaluate whether distinct plant strategies respond to the same or different groups of environmental predictors. We confirmed climate as a primary determinant of alien invasions and as a primary environmental gradient determining landscape invasibility. The effects of secondary gradients were detected only when the area was sub-sampled according to predictions based on the primary gradient. Then, multiple predictor types influenced patterns of alien species richness, with some types (landscape composition, topography and fire regime) prevailing over others. Alien species richness responded most strongly to extreme land management regimes, suggesting that intermediate disturbance induces biotic resistance by favouring native species richness. Land-use intensification facilitated alien invasion, whereas conservation areas hosted few invaders, highlighting the importance of ecosystem stability in preventing invasions. Plants with different strategies exhibited different responses to environmental gradients, particularly when the variations of the primary gradient were narrowed by sub-sampling. Such differential responses of plant strategies suggest using distinct control and eradication approaches for different areas and alien plant groups.