Multivariate contemporaneous-threshold autoregressive models

This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific innovation covariance matrix, the model can account for contemporaneous regime-specific co-movements of the variables. The stability and distributional properties of the proposed model are discussed, as well as issues of estimation, testing and forecasting. The practical usefulness of the C-MSTAR model is illustrated by examining the relationship between US stock prices and interest rates.

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (R (adj) (2) > 0.5). 2) Models including PCNM variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation of non-model species under global change.

Thymic selection generates a large T cell pool recognizing a self-peptide in humans.

The low frequency of self-peptide-specific T cells in the human preimmune repertoire has so far precluded their direct evaluation. Here, we report an unexpected high frequency of T cells specific for the self-antigen Melan-A/MART-1 in CD8 single-positive thymocytes from human histocompatibility leukocyte antigen-A2 healthy individuals, which is maintained in the peripheral blood of newborns and adults. Postthymic replicative history of Melan-A/MART-1-specific CD8 T cells was independently assessed by quantifying T cell receptor excision circles and telomere length ex vivo. We provide direct evidence that the large T cell pool specific for the self-antigen Melan-A/MART-1 is mostly generated by thymic output of a high number of precursors. This represents the only known naive self-peptide-specific T cell repertoire directly accessible in humans.

Prevalence and intensity of infections of Ascaris lumbricoides and Trichuris trichiura and associated socio-demographic variables in four rural Honduran communities

Between January and March 1998, a cross-sectional survey was carried out in four rural communities in Honduras, Central America. We examined the prevalence and intensity of Ascaris lumbricoides and Trichuris trichiura infections among 240 fecal specimens, and the association between selected socio-demographic variables and infection for 62 households. The overall prevalence of A. lumbricoides and T. trichiura was 45% (95% CI 39.0-51.9) and 38% (95% CI 31.8-44.4) respectively. The most intense infections for Ascaris and Trichuris were found in children aged 2-12 years old. By univariate analysis variables associated with infections of A. lumbricoides were: number of children 2-5 years old (p=0.001), level of formal education of respondents (p=0.01), reported site of defecation of children in households (p=0.02), households with children who had a recent history of diarrhea (p=0.002), and the location of households (p=0.03). Variables associated with both A. lumbricoides and T. trichiura infection included: number of children 6-14 years old (p=0.01, p=0.04, respectively), ownership of a latrine (p=0.04, p=0.03, respectively) and coinfection with either helminth (p=0.001, p=0.001, respectively). By multivariate analysis the number of children 2-5 years living in the household, (p=0.01, odds ratio (OR)=22.2), children with a recent history of diarrhea (p=0.0, OR=39.8), and infection of household members with T. trichiura (p=0.02, OR=16.0) were associated with A. lumbricoides infection. The number of children 6-14 years old in the household was associated with both A. lumbricoides and T. trichiura infection (p=0.04, p=0.01, OR=19.2, OR=5.2, respectively).

Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

Liver Transplantation for Neuroendocrine Tumors in Europe-Results and Trends in Patient Selection: A 213-Case European Liver Transplant Registry Study.

OBJECTIVE:: The purpose of this study was to assess outcomes and indications in a large cohort of patients who underwent liver transplantation (LT) for liver metastases (LM) from neuroendocrine tumors (NET) over a 27-year period. BACKGROUND:: LT for NET remains controversial due to the absence of clear selection criteria and the scarcity and heterogeneity of reported cases. METHODS:: This retrospective multicentric study included 213 patients who underwent LT for NET performed in 35 centers in 11 European countries between 1982 and 2009. One hundred seven patients underwent transplantation before 2000 and 106 after 2000. Mean age at the time of LT was 46 years. Half of the patients presented hormone secretion and 55% had hepatomegaly. Before LT, 83% of patients had undergone surgical treatment of the primary tumor and/or LM and 76% had received chemotherapy. The median interval between diagnosis of LM and LT was 25 months (range, 1-149 months). In addition to LT, 24 patients underwent major resection procedures and 30 patients underwent minor resection procedures. RESULTS:: Three-month postoperative mortality was 10%. At 5 years after LT, overall survival (OS) was 52% and disease-free survival was 30%. At 5 years from diagnosis of LM, OS was 73%. Multivariate analysis identified 3 predictors of poor outcome, that is, major resection in addition to LT, poor tumor differentiation, and hepatomegaly. Since 2000, 5-year OS has increased to 59% in relation with fewer patients presenting poor prognostic factors. Multivariate analysis of the 106 cases treated since 2000 identified the following predictors of poor outcome: hepatomegaly, age more than 45 years, and any amount of resection concurrent with LT. CONCLUSIONS:: LT is an effective treatment of unresectable LM from NET. Patient selection based on the aforementioned predictors can achieve a 5-year OS between 60% and 80%. However, use of overly restrictive criteria may deny LT to some patients who could benefit. Optimal timing for LT in patients with stable versus progressive disease remains unclear.

Pre-hospital antibiotic treatment and mortality caused by invasive meningococcal disease, adjusting for indication bias.

Background: Mortality from invasive meningococcal disease (IMD) has remained stable over the last thirty years and it is unclear whether pre-hospital antibiotherapy actually produces a decrease in this mortality. Our aim was to examine whether pre-hospital oral antibiotherapy reduces mortality from IMD, adjusting for indication bias. Methods: A retrospective analysis was made of clinical reports of all patients (n = 848) diagnosed with IMD from 1995 to 2000 in Andalusia and the Canary Islands, Spain, and of the relationship between the use of pre-hospital oral antibiotherapy and mortality. Indication bias was controlled for by the propensity score technique, and a multivariate analysis was performed to determine the probability of each patient receiving antibiotics, according to the symptoms identified before admission. Data on in-hospital death, use of antibiotics and demographic variables were collected. A logistic regression analysis was then carried out, using death as the dependent variable, and prehospital antibiotic use, age, time from onset of symptoms to parenteral antibiotics and the propensity score as independent variables. Results: Data were recorded on 848 patients, 49 (5.72%) of whom died. Of the total number of patients, 226 had received oral antibiotics before admission, mainly betalactams during the previous 48 hours. After adjusting the association between the use of antibiotics and death for age, time between onset of symptoms and in-hospital antibiotic treatment, pre-hospital oral antibiotherapy remained a significant protective factor (Odds Ratio for death 0.37, 95% confidence interval 0.15–0.93). Conclusion: Pre-hospital oral antibiotherapy appears to reduce IMD mortality.

Determinants of non- response to a second assessment of lifestyle factors and body weight in the EPIC-PANACEA study.

BACKGROUND This paper discusses whether baseline demographic, socio-economic, health variables, length of follow-up and method of contacting the participants predict non-response to the invitation for a second assessment of lifestyle factors and body weight in the European multi-center EPIC-PANACEA study. METHODS Over 500.000 participants from several centers in ten European countries recruited between 1992 and 2000 were contacted 2-11 years later to update data on lifestyle and body weight. Length of follow-up as well as the method of approaching differed between the collaborating study centers. Non-responders were compared with responders using multivariate logistic regression analyses. RESULTS Overall response for the second assessment was high (81.6%). Compared to postal surveys, centers where the participants completed the questionnaire by phone attained a higher response. Response was also high in centers with a short follow-up period. Non-response was higher in participants who were male (odds ratio 1.09 (confidence interval 1.07; 1.11), aged under 40 years (1.96 (1.90; 2.02), living alone (1.40 (1.37; 1.43), less educated (1.35 (1.12; 1.19), of poorer health (1.33 (1.27; 1.39), reporting an unhealthy lifestyle and who had either a low (<18.5 kg/m2, 1.16 (1.09; 1.23)) or a high BMI (>25, 1.08 (1.06; 1.10); especially ≥30 kg/m2, 1.26 (1.23; 1.29)). CONCLUSIONS Cohort studies may enhance cohort maintenance by paying particular attention to the subgroups that are most unlikely to respond and by an active recruitment strategy using telephone interviews.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Drug assessment by a Pharmacy and Therapeutics committee: from drug selection criteria to use in clinical practice.

BACKGROUND In Spain, hospital medicines are assessed and selected by local Pharmacy and Therapeutics committees (PTCs). Of all the drugs assessed, cancer drugs are particularly important because of their budgetary impact and the sometimes arguable added value with respect to existing alternatives. This study analyzed the PTC drug selection process and the main objective was to evaluate the degree of compliance of prescriptions for oncology drugs with their criteria for use. METHODS This was a retrospective observational study (May 2007 to April 2010) of PTC-assessed drugs. The variables measured to describe the committee's activity were number of drugs assessed per year and number of drugs included in any of these settings: without restrictions, with criteria for use, and not included in formulary. These drugs were also analyzed by therapeutic group. To assess the degree of compliance of prescriptions, a score was calculated to determine whether prescriptions for bevacizumab, cetuximab, trastuzumab, and bortezomib were issued in accordance with PTC drug use criteria. RESULTS The PTC received requests for inclusion of 40 drugs, of which 32 were included in the hospital formulary (80.0%). Criteria for use were established for 28 (87.5%) of the drugs included. In total, 293 patients were treated with the four cancer drugs in eight different therapeutic indications. The average prescription compliance scores were as follows: bevacizumab, 83% for metastatic colorectal cancer, 100% for metastatic breast cancer, and 82.3% for non-small-cell lung cancer; cetuximab, 62.0% for colorectal cancer and 50% for head and neck cancer; trastuzumab, 95.1% for early breast cancer and 82.4% for metastatic breast cancer; and bortezomib, 63.7% for multiple myeloma. CONCLUSION The degree of compliance with criteria for use of cancer drugs was reasonably high. PTC functions need to be changed so that they can carry out more innovative tasks, such as monitoring conditions for drug use.

Calibration and Validation of SWAT for the Upper Maquoketa River Watershed, June 2005

A validation study has been performed using the Soil and Water Assessment Tool (SWAT) model with data collected for the Upper Maquoketa River Watershed (UMRW), which drains over 16,000 ha in northeast Iowa. This validation assessment builds on a previous study with nested modeling for the UMRW that required both the Agricultural Policy EXtender (APEX) model and SWAT. In the nested modeling approach, edge-offield flows and pollutant load estimates were generated for manure application fields with APEX and were then subsequently routed to the watershed outlet in SWAT, along with flows and pollutant loadings estimated for the rest of the watershed routed to the watershed outlet. In the current study, the entire UMRW cropland area was simulated in SWAT, which required translating the APEX subareas into SWAT hydrologic response units (HRUs). Calibration and validation of the SWAT output was performed by comparing predicted flow and NO3-N loadings with corresponding in-stream measurements at the watershed outlet from 1999 to 2001. Annual stream flows measured at the watershed outlet were greatly under-predicted when precipitation data collected within the watershed during the 1999-2001 period were used to drive SWAT. Selection of alternative climate data resulted in greatly improved average annual stream predictions, and also relatively strong r2 values of 0.73 and 0.72 for the predicted average monthly flows and NO3-N loads, respectively. The impact of alternative precipitation data shows that as average annual precipitation increases 19%, the relative change in average annual streamflow is about 55%. In summary, the results of this study show that SWAT can replicate measured trends for this watershed and that climate inputs are very important for validating SWAT and other water quality models.

Asymptotic robustness in multi-sample analysis of multivariate linear relations

Standard methods for the analysis of linear latent variable models oftenrely on the assumption that the vector of observed variables is normallydistributed. This normality assumption (NA) plays a crucial role inassessingoptimality of estimates, in computing standard errors, and in designinganasymptotic chi-square goodness-of-fit test. The asymptotic validity of NAinferences when the data deviates from normality has been calledasymptoticrobustness. In the present paper we extend previous work on asymptoticrobustnessto a general context of multi-sample analysis of linear latent variablemodels,with a latent component of the model allowed to be fixed across(hypothetical)sample replications, and with the asymptotic covariance matrix of thesamplemoments not necessarily finite. We will show that, under certainconditions,the matrix $\Gamma$ of asymptotic variances of the analyzed samplemomentscan be substituted by a matrix $\Omega$ that is a function only of thecross-product moments of the observed variables. The main advantage of thisis thatinferences based on $\Omega$ are readily available in standard softwareforcovariance structure analysis, and do not require to compute samplefourth-order moments. An illustration with simulated data in the context ofregressionwith errors in variables will be presented.

1st radiometric dating of a paleontologically dated Bathonian level from Georgia (USSR) - Use of the cathodoluminescence for selection of suitable plagioclases

Jurassic volcanic formations interlayered with (ammonite-bearing) sediments are common in the Caucasus area; this situation is of interest for the numerical calibration of the poorly documented Jurassic portion of the time scale. However, following petrographic study on thin sections no whole-rocks can be considered reliable geochronometers due to subsequent alteration; from about 20 samples, two were selected for plagioclase dating; one (V134) is probably early Kimmeridgian in age; the other (V136) is probably located in the Lower Bathonian stage according to diagnostic ammonites. Cathodoluminescence (CTL) study has shown that sample V136 was similar to usual volcanic feldspars (blue to green colour); however, the lack of CTL of the V134 plagioclase is a character common to diagenetic feldspars; consequently, in spite of a good optical preservation, this geo-chronometer cannot give an age representative of the time of emplacement of the lava flow. We have combined CTL observation with microprobe analysis in order to document the poorly known CTL behaviour of volcanic feldspars; cations Ti4+ and Fe2+ play a major role in the CTL colour of plagioclases and are able to document the growing history of these feldspars ; phenocrysts are initially rich in Fe2+ (core of the crystals, green in colour), then richer in Ti toward the exterior; microcrysts are even richer in Ti (blue to bright blue). We have also observed that natural CTL colour was modified resulting from acid ``cleaning'' of the separated feldspars : the initial blue or green colour tends to change to yellow or violet, respectively, after acid treatment probably due to oxydation of Fe2+ toward Fe3+. X-ray and microprobe analyses both indicated that plagioclases from sample V134 was near the sodic end member (albite) suggesting a diagenetic origin in this andesitic basalt; In contrast, sample V136 contains a calcic plagioclase of common composition for a doleritic basalt. The K-Ar conventional technique was applied as a preliminary tool for radiometric analysis. The Kimmeridgian Na-plagioclase sample gave a ``rejuvenated'' (85 Ma) apparent age which confirms a late genesis for the separated plagioclase phase; this interpretation is based on CTL observation, X-ray analysis, and microprobe analysis ; these techniques are able to distinguish samples which have been submitted to diagenetic alteration from those which have not. An age consistent with the stratigraphic location has been obtained from sample V136. This age of 161 +/- 3 (2-sigma) Ma, is the first one available from a sample palaeontologically located with reasonable precision within the mid Jurassic time.

Nuclear well logging in soils. Calibration of slim hole nuclear tools gamma-gamma and neutron-thermal neutron.

The calculation of elasticity parameters by sonic and ultra sonic wave propagation in saturated soils using Biot's theory needs the following variables : forpiation density and porosity (p, ø), compressional and shear wave velocities (Vp, Vs), fluid density, viscosity and compressibility (Pfi Ilfi Ki), matrix density and compressibility (p" K), The first four parameters can be determined in situ using logging probes. Because fluid and matrix characteristics are not modified during core extraction, they can be obtained through laboratory measurements. All parameters necessitate precise calibrations in various environments and for specific range of values encountered in soils. The slim diameter of boreholes in shallow geophysics and the high cost of petroleum equipment demand the use of specific probes, which usually only give qualitative results. The measurement 'of density is done with a gamma-gamma probe and the measurement of hydrogen index, in relation to porosity, by a neutron probe. The first step of this work has been carried out in synthetic formations in the laboratory using homogeneous media of known density and porosity. To establish borehole corrections different casings have been used. Finally a comparison between laboratory and in situ data in cored holes of known geometry and casing has been performed.

Anàlisi factorial confirmatòria per a variables categòriques: Aplicació al qüestionari de discapacitat WHODAS-II

Objective: To describe the methodology of Confirmatory Factor Analyis for categorical items and to apply this methodology to evaluate the factor structure and invariance of the WHO-Disability Assessment Schedule (WHODAS-II) questionnaire, developed by the World HealthOrganization.Methods: Data used for the analysis come from the European Study of Mental Disorders(ESEMeD), a cross-sectional interview to a representative sample of the general population of 6 european countries (n=8796). Respondents were administered a modified version of theWHODAS-II, that measures functional disability in the previous 30 days in 6 differentdimensions: Understanding and Communicating; Self-Care, Getting Around, Getting Along withOthers, Life Activities and Participation. The questionnaire includes two types of items: 22severity items (5 points likert) and 8 frequency items (continuous). An Exploratory factoranalysis (EFA) with promax rotation was conducted on a random 50% of the sample. Theremaining half of the sample was used to perform a Confirmatory Factor Analysis (CFA) inorder to compare three different models: (a) the model suggested by the results obtained in theEFA; (b) the theoretical model suggested by the WHO with 6 dimensions; (c) a reduced modelequivalent to model b where 4 of the frequency items are excluded. Moreover, a second orderfactor was also evaluated. Finally, a CFA with covariates was estimated in order to evaluatemeasurement invariance of the items between Mediterranean and non-mediterranean countries.Results: The solution that provided better results in the EFA was that containing 7 factors. Twoof the frequency items presented high factor loadings in the same factor, and one of thempresented factor loadings smaller than 0.3 with all the factors. With regard to the CFA, thereduced model (model c) presented the best goodness of fit results (CFI=0.992,TLI=0.996,RMSEA=0.024). The second order factor structure presented adequate goodness of fit (CFI=0.987,TLI=0.991, RMSEA=0.036). Measurement non-invariance was detected for one of the items of thequestionnaire (FD20 ¿ Embarrassment due to health problems).Conclusions: AFC confirmed the initial hypothesis about the factorial structure of the WHODAS-II in 6factors. The second order factor supports the existence of a global dimension of disability. The use of 4of the frequency items is not recommended in the scoring of the corresponding dimensions.