Cognitive errors assessed by observer ratings in bipolar affective disorder: relationship with symptoms and therapeutic alliance

The construct of cognitive errors is clinically relevant for cognitive therapy of mood disorders. Beck's universality hypothesis postulates the relevance of negative cognitions in all subtypes of mood disorders, as well as positive cognitions for manic states. This hypothesis has rarely been empirically addressed for patients presenting bipolar affective disorder (BD). In-patients (n = 30) presenting with BD were interviewed, as were 30 participants of a matched control group. Valid and reliable observer-rater methodology for cognitive errors was applied to the session transcripts. Overall, patients make more cognitive errors than controls. When manic and depressive patients were compared, parts of the universality hypothesis were confirmed. Manic symptoms are related to positive and negative cognitive errors. These results are discussed with regard to the main assumptions of the cognitive model for depression; thus adding an argument for extending it to the BD diagnostic group, taking into consideration specificities in terms of cognitive errors. Clinical implications for cognitive therapy of BD are suggested.

Etudes Coût-efficacité: ce que devraient retenir les médecins [Cost-effectiveness analyses: what doctors should know]

The resources of our heath care system are limited. Choices in the attribution of resources are necessary to ensure its stability. A cost-effectiveness analysis compares the effects of one health intervention to another, taking into account the costs (including the saved costs) and the saved life years, adjusted for the quality of life (cost-utility). Cost-effectiveness analyses should take the societal perspective and the studied intervention should be compared to a relevant intervention actually in use. Physicians, at the interface between patients and payers, are in an ideal position to interpret, or even perform cost-effectiveness analysis, and to promote the interventions that are most effective and that have a reasonable cost.

Do habitat suitability models reliably predict the recovery areas of threatened species?

1. Identifying those areas suitable for recolonization by threatened species is essential to support efficient conservation policies. Habitat suitability models (HSM) predict species' potential distributions, but the quality of their predictions should be carefully assessed when the species-environment equilibrium assumption is violated.2. We studied the Eurasian otter Lutra lutra, whose numbers are recovering in southern Italy. To produce widely applicable results, we chose standard HSM procedures and looked for the models' capacities in predicting the suitability of a recolonization area. We used two fieldwork datasets: presence-only data, used in the Ecological Niche Factor Analyses (ENFA), and presence-absence data, used in a Generalized Linear Model (GLM). In addition to cross-validation, we independently evaluated the models with data from a recolonization event, providing presences on a previously unoccupied river.3. Three of the models successfully predicted the suitability of the recolonization area, but the GLM built with data before the recolonization disagreed with these predictions, missing the recolonized river's suitability and badly describing the otter's niche. Our results highlighted three points of relevance to modelling practices: (1) absences may prevent the models from correctly identifying areas suitable for a species spread; (2) the selection of variables may lead to randomness in the predictions; and (3) the Area Under Curve (AUC), a commonly used validation index, was not well suited to the evaluation of model quality, whereas the Boyce Index (CBI), based on presence data only, better highlighted the models' fit to the recolonization observations.4. For species with unstable spatial distributions, presence-only models may work better than presence-absence methods in making reliable predictions of suitable areas for expansion. An iterative modelling process, using new occurrences from each step of the species spread, may also help in progressively reducing errors.5. Synthesis and applications. Conservation plans depend on reliable models of the species' suitable habitats. In non-equilibrium situations, such as the case for threatened or invasive species, models could be affected negatively by the inclusion of absence data when predicting the areas of potential expansion. Presence-only methods will here provide a better basis for productive conservation management practices.

Fertilization response likelihood for the interpretation of leaf analyses

Leaf analysis is the chemical evaluation of the nutritional status where the nutrient concentrations found in the tissue reflect the nutritional status of the plants. Thus, a correct interpretation of the results of leaf analysis is fundamental for an effective use of this tool. The purpose of this study was to propose and compare the method of Fertilization Response Likelihood (FRL) for interpretation of leaf analysis with that of the Diagnosis and Recommendation Integrated System (DRIS). The database consisted of 157 analyses of the N, P, K, Ca, Mg, S, Cu, Fe, Mn, Zn, and B concentrations in coffee leaves, which were divided into two groups: low yield (< 30 bags ha-1) and high yield (> 30 bags ha-1). The DRIS indices were calculated using the method proposed by Jones (1981). The fertilization response likelihood was computed based on the approximation of normal distribution. It was found that the Fertilization Response Likelihood (FRL) allowed an evaluation of the nutritional status of coffee trees, coinciding with the DRIS-based diagnoses in 84.96 % of the crops.

Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity.

The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10(-8)) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.

Geometric morphometric analyses provide evidence for the adaptive character of the Tanganyikan cichlid fish radiations.

The cichlids of East Africa are renowned as one of the most spectacular examples of adaptive radiation. They provide a unique opportunity to investigate the relationships between ecology, morphological diversity, and phylogeny in producing such remarkable diversity. Nevertheless, the parameters of the adaptive radiations of these fish have not been satisfactorily quantified yet. Lake Tanganyika possesses all of the major lineages of East African cichlid fish, so by using geometric morphometrics and comparative analyses of ecology and morphology, in an explicitly phylogenetic context, we quantify the role of ecology in driving adaptive speciation. We used geometric morphometric methods to describe the body shape of over 1000 specimens of East African cichlid fish, with a focus on the Lake Tanganyika species assemblage, which is composed of more than 200 endemic species. The main differences in shape concern the length of the whole body and the relative sizes of the head and caudal peduncle. We investigated the influence of phylogeny on similarity of shape using both distance-based and variance partitioning methods, finding that phylogenetic inertia exerts little influence on overall body shape. Therefore, we quantified the relative effect of major ecological traits on shape using phylogenetic generalized least squares and disparity analyses. These analyses conclude that body shape is most strongly predicted by feeding preferences (i.e., trophic niches) and the water depths at which species occur. Furthermore, the morphological disparity within tribes indicates that even though the morphological diversification associated with explosive speciation has happened in only a few tribes of the Tanganyikan assemblage, the potential to evolve diverse morphologies exists in all tribes. Quantitative data support the existence of extensive parallelism in several independent adaptive radiations in Lake Tanganyika. Notably, Tanganyikan mouthbrooders belonging to the C-lineage and the substrate spawning Lamprologini have evolved a multitude of different shapes from elongated and Lamprologus-like hypothetical ancestors. Together, these data demonstrate strong support for the adaptive character of East African cichlid radiations.

A large-scale genetic validation study coupled with in vitro analyses reveal a role for vitamin Dsignaling in the pathogenesis and response to treatment of hepatitis C virus infection

Background and Aims: Vitamin D is an important modulatorof numerous cellular processes. Some of us recently observedan association of the 1a-hydroxylase promoter polymorphismCYP27B1-1260 rs10877012 with sustained virologic response (SVR)in a relatively small number of German patients with chronichepatitis C. In the present study, we aimed to validate thisassociation in a large and well characterized patient cohort, theSwiss Hepatitis C Cohort Study (SCCS). In addition, we examinedthe effect of vitamin D on the hepatitis C virus (HCV) life cyclein vitro.Methods: CYP27B1-1260 rs10877012 and IL28B rs12979860 singlenucleotide polymorphisms (SNPs) were genotyped in 1049 patientswith chronic hepatitis C from the SCCS, of whom 698 were treatedwith pegylated interferon-a (PEG-IFN-a) and ribavirin. In addition,112 patients with spontaneous clearance of HCV were examined.SNPs were correlated with variables reflecting the natural courseand treatment outcome of chronic hepatitis C. The effect of1,25-(OH)2D3 (calcitriol) on HCV replication and viral particleproduction was investigated in vitro using human hepatoma celllines (Huh-7.5) harbouring subgenomic replicons and cell culturederivedHCV.Results: The CYP27B1-1260 rs10877012 genotype was notassociated with SVR in patients with the good-response IL28Brs1279860 CC genotype. However, in patients with poor-responseIL28B rs1279860 genotype CT and TT, CYP27B1-1260 rs10877012was a significant independent predictor of SVR (15% difference inSVR between rs10877012 genotype AA vs. CC, p = 0.030, OR = 1.495,95% CI = 1.038-2.152). The CYPB27-1260 rs10877012 genotype wasneither associated with spontaneous clearance of HCV, nor withliver fibrosis progression rate, inflammatory activity of chronichepatitis C, or HCV viral load. Physiological doses of 1,25-(OH)2D3did not significantly affect HCVRNA replication or infectiousparticle production in vitro.Conclusions: The results of this large-scale genetic validationstudy reveal a role of vitamin D metabolism in the responseto treatment in chronic hepatitis C, but 1,25-(OH)2D3 does notexhibit a significant direct inhibitory antiviral effect. Thus, theability of vitamin D to modulate immunity against HCV shouldbe investigated.

Processes models, environmental analyses, and cognitive architectures: Quo vadis quantum probability theory? (Commentary on Pothos and Busemeyer)

A lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.

Pathological complete response after neoadjuvant chemotherapy is an independent predictive factor irrespective of simplified breast cancer intrinsic subtypes: a landmark and two-step approach analyses from the EORTC 10994/BIG 1-00 phase III trial.

BACKGROUND: Pathological complete response (pCR) following chemotherapy is strongly associated with both breast cancer subtype and long-term survival. Within a phase III neoadjuvant chemotherapy trial, we sought to determine whether the prognostic implications of pCR, TP53 status and treatment arm (taxane versus non-taxane) differed between intrinsic subtypes. PATIENTS AND METHODS: Patients were randomized to receive either six cycles of anthracycline-based chemotherapy or three cycles of docetaxel then three cycles of eprirubicin/docetaxel (T-ET). pCR was defined as no evidence of residual invasive cancer (or very few scattered tumour cells) in primary tumour and lymph nodes. We used a simplified intrinsic subtypes classification, as suggested by the 2011 St Gallen consensus. Interactions between pCR, TP53 status, treatment arm and intrinsic subtype on event-free survival (EFS), distant metastasis-free survival (DMFS) and overall survival (OS) were studied using a landmark and a two-step approach multivariate analyses. RESULTS: Sufficient data for pCR analyses were available in 1212 (65%) of 1856 patients randomized. pCR occurred in 222 of 1212 (18%) patients: 37 of 496 (7.5%) luminal A, 22 of 147 (15%) luminal B/HER2 negative, 51 of 230 (22%) luminal B/HER2 positive, 43 of 118 (36%) HER2 positive/non-luminal, 69 of 221(31%) triple negative (TN). The prognostic effect of pCR on EFS did not differ between subtypes and was an independent predictor for better EFS [hazard ratio (HR) = 0.40, P < 0.001 in favour of pCR], DMFS (HR = 0.32, P < 0.001) and OS (HR = 0.32, P < 0.001). Chemotherapy arm was an independent predictor only for EFS (HR = 0.73, P = 0.004 in favour of T-ET). The interaction between TP53, intrinsic subtypes and survival outcomes only approached statistical significance for EFS (P = 0.1). CONCLUSIONS: pCR is an independent predictor of favourable clinical outcomes in all molecular subtypes in a two-step multivariate analysis. CLINICALTRIALSGOV: EORTC 10994/BIG 1-00 Trial registration number NCT00017095.

From Empirical Bayes to Full Bayes: Methods for Analysing Traffice Safety Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this slight, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

From Empirical Bayes to Full Bayes: Methods for Analyzubg Traffic Safey Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this light, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

DnaSP, DNA polymorphism analyses by the coalescent and other methods

DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (~5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. Availability: The software package, including complete documentation and examples, is freely available to academic users from: http://www.ub.es/dnasp