A pseudo-spectral method for simulating of poro-elastic seismic wave propagation in complex borehole environments

We present a novel numerical approach for the comprehensive, flexible, and accurate simulation of poro-elastic wave propagation in cylindrical coordinates. An important application of this method is the modeling of complex seismic wave phenomena in fluid-filled boreholes, which represents a major, and as of yet largely unresolved, computational problem in exploration geophysics. In view of this, we consider a numerical mesh consisting of three concentric domains representing the borehole fluid in the center, the borehole casing and the surrounding porous formation. The spatial discretization is based on a Chebyshev expansion in the radial direction, Fourier expansions in the other directions, and a Runge-Kutta integration scheme for the time evolution. A domain decomposition method based on the method of characteristics is used to match the boundary conditions at the fluid/porous-solid and porous-solid/porous-solid interfaces. The viability and accuracy of the proposed method has been tested and verified in 2D polar coordinates through comparisons with analytical solutions as well as with the results obtained with a corresponding, previously published, and independently benchmarked solution for 2D Cartesian coordinates. The proposed numerical solution also satisfies the reciprocity theorem, which indicates that the inherent singularity associated with the origin of the polar coordinate system is handled adequately.

Development and validation of a clinical prediction rule for chest wall syndrome in primary care

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.

Simulations in evolution. II. Relative fitness and the propagation of mutants.

In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms which propel biological evolution. Our previous article presented a histogram model [1] consisting in populations of individuals whose number changed under the influence of variation and/or fitness, the total population remaining constant. Individuals are classified into bins, and the content of each bin is calculated generation after generation by an Excel spreadsheet. Here, we apply the histogram model to a stable population with fitness F(1)=1.00 in which one or two fitter mutants emerge. In a first scenario, a single mutant emerged in the population whose fitness was greater than 1.00. The simulations ended when the original population was reduced to a single individual. The histogram model was validated by excellent agreement between its predictions and those of a classical continuous function (Eqn. 1) which predicts the number of generations needed for a favorable mutation to spread throughout a population. But in contrast to Eqn. 1, our histogram model is adaptable to more complex scenarios, as demonstrated here. In the second and third scenarios, the original population was present at time zero together with two mutants which differed from the original population by two higher and distinct fitness values. In the fourth scenario, the large original population was present at time zero together with one fitter mutant. After a number of generations, when the mutant offspring had multiplied, a second mutant was introduced whose fitness was even greater. The histogram model also allows Shannon entropy (SE) to be monitored continuously as the information content of the total population decreases or increases. The results of these simulations illustrate, in a graphically didactic manner, the influence of natural selection, operating through relative fitness, in the emergence and dominance of a fitter mutant.

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

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.

A quantitative test of Hamilton's rule for the evolution of altruism.

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.

Prevalence of Acute Coronary Syndrome in Patients Suspected for Pulmonary Embolism or Acute Aortic Syndromes: Rational for "Double" and "Triple" Rule-Out Concepts

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.

Ruling out coronary heart disease in primary care: external validation of a clinical prediction rule.

BACKGROUND: The Marburg Heart Score (MHS) aims to assist GPs in safely ruling out coronary heart disease (CHD) in patients presenting with chest pain, and to guide management decisions. AIM: To investigate the diagnostic accuracy of the MHS in an independent sample and to evaluate the generalisability to new patients. DESIGN AND SETTING: Cross-sectional diagnostic study with delayed-type reference standard in general practice in Hesse, Germany. METHOD: Fifty-six German GPs recruited 844 males and females aged ≥ 35 years, presenting between July 2009 and February 2010 with chest pain. Baseline data included the items of the MHS. Data on the subsequent course of chest pain, investigations, hospitalisations, and medication were collected over 6 months and were reviewed by an independent expert panel. CHD was the reference condition. Measures of diagnostic accuracy included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, likelihood ratios, and predictive values. RESULTS: The AUC was 0.84 (95% confidence interval [CI] = 0.80 to 0.88). For a cut-off value of 3, the MHS showed a sensitivity of 89.1% (95% CI = 81.1% to 94.0%), a specificity of 63.5% (95% CI = 60.0% to 66.9%), a positive predictive value of 23.3% (95% CI = 19.2% to 28.0%), and a negative predictive value of 97.9% (95% CI = 96.2% to 98.9%). CONCLUSION: Considering the diagnostic accuracy of the MHS, its generalisability, and ease of application, its use in clinical practice is recommended.

Propagation dans l'environnement des microorganismes et autres particules organiques issus des élevages intensifs et conséquences pour la santé des riverains

Les élevages d'animaux de rente hébergent de plus en plus de bêtes. Cette situation génère une accumulation de poussière organique, constituée de particules inertes et de microorganismes, issus de la nourriture, de la litière, des matières fécales, des pellicules de la peau, des poils, etc. L'activité des animaux et l'activité professionnelle favorisent une remise en suspension de cette poussière, qui peut se propager à l'extérieur. Ces émissions de particules organiques dans l'environnement soulèvent des inquiétudes pour la santé des riverains. Ces craintes sont légitimes, puisque les problèmes respiratoires, allergiques ou toxiques sont bien connus chez les travailleurs agricoles exposés à de fortes doses de poussières organiques. Un autre risque sanitaire lié aux élevages intensifs d'animaux est la dissémination de bactéries résistantes aux antibiotiques dans l'environnement avec, pour éventuelle conséquence, une transmission de ces souches aux personnes résidant à proximité. Cette problématique est bien connue dans les élevages de porcs fréquemment colonisés par des SARM (Staphylococcus aureus résistant à la méticilline), qui sont transmis aux éleveurs. Les deux études analysées ci-dessous ont investigué cette problématique de dissémination des particules organiques dans l'environnement et les conséquences sur la santé des riverains. La première a étudié le lien entre le fait de résider à proximité de fermes d'élevage d'animaux et la prévalence de maladies respiratoires. La deuxième a étudié le risque de colonisation nasale par des SARM dans une population de vétérans vivant à proximité d'élevages intensifs de porcs.

The pulmonary embolism rule-out criteria (PERC) rule does not safely exclude pulmonary embolism.

Background: The Pulmonary Embolism Rule-out Criteria (PERC) rule is a clinical diagnostic rule designed to exclude pulmonary embolism (PE) without further testing. We sought to externally validate the diagnostic performance of the PERC rule alone and combined with clinical probability assessment based on the revised Geneva score. Methods: The PERC rule was applied retrospectively to consecutive patients who presented with a clinical suspicion of PE to six emergency departments, and who were enrolled in a randomized trial of PE diagnosis. Patients who met all eight PERC criteria [PERC(-)] were considered to be at a very low risk for PE. We calculated the prevalence of PE among PERC(-) patients according to their clinical pretest probability of PE. We estimated the negative likelihood ratio of the PERC rule to predict PE. Results: Among 1675 patients, the prevalence of PE was 21.3%. Overall, 13.2% of patients were PERC(-). The prevalence of PE was 5.4% [95% confidence interval (CI): 3.1-9.3%] among PERC(-) patients overall and 6.4% (95% CI: 3.7-10.8%) among those PERC(-) patients with a low clinical pretest probability of PE. The PERC rule had a negative likelihood ratio of 0.70 (95% CI: 0.67-0.73) for predicting PE overall, and 0.63 (95% CI: 0.38-1.06) in low-risk patients. Conclusions: Our results suggest that the PERC rule alone or even when combined with the revised Geneva score cannot safely identify very low risk patients in whom PE can be ruled out without additional testing, at least in populations with a relatively high prevalence of PE.

A generalization of Cope's rule

For numerous shelly invertebrates, Cope's rule is shown in this paper to merely describe the particular case where volume increase is strictly coupled with diameter or length. Allometries, which are frequently observed in the evolution of the shells' geometry, mean that their size, volume and surface can vary independently. The consequences of this can be summarized as follows : 1) volume increase not coupled with an increase of diameter or length of the organisms generates increasing involution and/or lateral width in the shell of cephalopods, foraminifera and radiolarians; 2) an increase of the biomineralizing surface, not coupled with volume increase, generates increasing apparent complexity in the sutures and growth lines in ammonites, and an increase in the complexity and number of chambers in foraminifera.

Development and validation of a clinical prediction rule for chest wall syndrome in primary care.

ABSTRACT: BACKGROUND: Chest wall syndrome (CWS), the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. METHODS: Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients). A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212) for external validation. RESULTS: From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive), stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner's concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC) curve was 0.80 (95% confidence interval 0.76-0.83) in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points). Among all patients presenting CWS (n = 284), 71% (n = 201) had a pain reproducible by palpation and 45% (n = 127) were correctly diagnosed. For a subset (n = 43) of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography) had been performed to achieve diagnosis. False positives (n = 41) included three patients with stable angina (1.8% of all positives). External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79) with a sensitivity of 22% and a specificity of 93%. CONCLUSIONS: This CWS score offers a useful complement to the usual CWS exclusion diagnosing process. Indeed, for the 127 patients presenting CWS and correctly classified by our clinical prediction rule, 65 additional tests and exams could have been avoided. However, the reproduction of chest pain by palpation, the most important characteristic to diagnose CWS, is not pathognomonic.

Ubiquitin Ligases of the N-End Rule Pathway: Assessment of Mutations in UBR1 That Cause the Johanson-Blizzard Syndrome.

Background: Johanson-Blizzard syndrome (JBS; OMIM 243800) is an autosomal recessive disorder that includes congenital exocrine pancreatic insufficiency, facial dysmorphism with the characteristic nasal wing hypoplasia, multiple malformations, and frequent mental retardation. Our previous work has shown that JBS is caused by mutations in human UBR1, which encodes one of the E3 ubiquitin ligases of the N-end rule pathway. The N-end rule relates the regulation of the in vivo half-life of a protein to the identity of its N-terminal residue. One class of degradation signals (degrons) recognized by UBR1 are destabilizing N-terminal residues of protein substrates.Methodology/Principal Findings: Most JBS-causing alterations of UBR1 are nonsense, frameshift or splice-site mutations that abolish UBR1 activity. We report here missense mutations of human UBR1 in patients with milder variants of JBS. These single-residue changes, including a previously reported missense mutation, involve positions in the RING-H2 and UBR domains of UBR1 that are conserved among eukaryotes. Taking advantage of this conservation, we constructed alleles of the yeast Saccharomyces cerevisiae UBR1 that were counterparts of missense JBS-UBR1 alleles. Among these yeast Ubr1 mutants, one of them (H160R) was inactive in yeast-based activity assays, the other one (Q1224E) had a detectable but weak activity, and the third one (V146L) exhibited a decreased but significant activity, in agreement with manifestations of JBS in the corresponding JBS patients.Conclusions/Significance: These results, made possible by modeling defects of a human ubiquitin ligase in its yeast counterpart, verified and confirmed the relevance of specific missense UBR1 alleles to JBS, and suggested that a residual activity of a missense allele is causally associated with milder variants of JBS.