High c-Met expression in stage I-II pancreatic adenocarcinoma: proposal for an immunostaining scoring method and correlation with poor prognosis.

AIMS: c-Met is an emerging biomarker in pancreatic ductal adenocarcinoma (PDAC); there is no consensus regarding the immunostaining scoring method for this marker. We aimed to assess the prognostic value of c-Met overexpression in resected PDAC, and to elaborate a robust and reproducible scoring method for c-Met immunostaining in this setting. METHODS AND RESULTS: c-Met immunostaining was graded according to the validated MetMab score, a classic visual scale combining surface and intensity (SI score), or a simplified score (high c-Met: ≥20% of tumour cells with strong membranous staining), in stage I-II PDAC. A computer-assisted classification method (Aperio software) was developed. Clinicopathological parameters were correlated with disease-free survival (DFS) and overall survival(OS). One hundred and forty-nine patients were analysed retrospectively in a two-step process. Thirty-seven samples (whole slides) were analysed as a pre-run test. Reproducibility values were optimal with the simplified score (kappa = 0.773); high c-Met expression (7/37) was associated with shorter DFS [hazard ratio (HR) 3.456, P = 0.0036] and OS (HR 4.257, P = 0.0004). c-Met expression was concordant on whole slides and tissue microarrays in 87.9% of samples, and quantifiable with a specific computer-assisted algorithm. In the whole cohort (n = 131), patients with c-Met(high) tumours (36/131) had significantly shorter DFS (9.3 versus 20.0 months, HR 2.165, P = 0.0005) and OS (18.2 versus 35.0 months, HR 1.832, P = 0.0098) in univariate and multivariate analysis. CONCLUSIONS: Simplified c-Met expression is an independent prognostic marker in stage I-II PDAC that may help to identify patients with a high risk of tumour relapse and poor survival.

Overcoming limitations of modelling rare species by using ensembles of small models

1. Species distribution models (SDMs) have become a standard tool in ecology and applied conservation biology. Modelling rare and threatened species is particularly important for conservation purposes. However, modelling rare species is difficult because the combination of few occurrences and many predictor variables easily leads to model overfitting. A new strategy using ensembles of small models was recently developed in an attempt to overcome this limitation of rare species modelling and has been tested successfully for only a single species so far. Here, we aim to test the approach more comprehensively on a large number of species including a transferability assessment. 2. For each species numerous small (here bivariate) models were calibrated, evaluated and averaged to an ensemble weighted by AUC scores. These 'ensembles of small models' (ESMs) were compared to standard Species Distribution Models (SDMs) using three commonly used modelling techniques (GLM, GBM, Maxent) and their ensemble prediction. We tested 107 rare and under-sampled plant species of conservation concern in Switzerland. 3. We show that ESMs performed significantly better than standard SDMs. The rarer the species, the more pronounced the effects were. ESMs were also superior to standard SDMs and their ensemble when they were independently evaluated using a transferability assessment. 4. By averaging simple small models to an ensemble, ESMs avoid overfitting without losing explanatory power through reducing the number of predictor variables. They further improve the reliability of species distribution models, especially for rare species, and thus help to overcome limitations of modelling rare species.

Gene Expression Profiling of Desmoid Tumors by cDNA Microarrays and Correlation with Progression-Free Survival.

PURPOSE: Because desmoid tumors exhibit an unpredictable clinical course, translational research is crucial to identify the predictive factors of progression in addition to the clinical parameters. The main issue is to detect patients who are at a higher risk of progression. The aim of this work was to identify molecular markers that can predict progression-free survival (PFS). EXPERIMENTAL DESIGN: Gene-expression screening was conducted on 115 available independent untreated primary desmoid tumors using cDNA microarray. We established a prognostic gene-expression signature composed of 36 genes. To test robustness, we randomly generated 1,000 36-gene signatures and compared their outcome association to our define 36-genes molecular signature and we calculated positive predictive value (PPV) and negative predictive value (NPV). RESULTS: Multivariate analysis showed that our molecular signature had a significant impact on PFS while no clinical factor had any prognostic value. Among the 1,000 random signatures generated, 56.7% were significant and none was more significant than our 36-gene molecular signature. PPV and NPV were high (75.58% and 81.82%, respectively). Finally, the top two genes downregulated in no-recurrence were FECH and STOML2 and the top gene upregulated in no-recurrence was TRIP6. CONCLUSIONS: By analyzing expression profiles, we have identified a gene-expression signature that is able to predict PFS. This tool may be useful for prospective clinical studies. Clin Cancer Res; 21(18); 4194-200. ©2015 AACR.

Preliminary integrated magnetostratigraphic and biostratigraphic correlation in the Miocene Lorca Basin (Murcia, SE Spain).

The Lorca basin is one of the Neogene basins OS South Eastern Spain. The infilling Tortonian-Messinian deposits are mainly composed OS marls and reach up to 1,200 m in thickness. A biostratigraphic survey OS these deposits, assisted by the determination OS the magnetic polarity reversal pattern Sor most OS these deposits (900 m), has enabled the Tortonian-Messinian chronostratigraphy to be precised. The close sampling space for biostratigraphic determination has enabled the accurate location OS Sour main biostratigraphic events than can be correlated with charactenstic events of the Mediterranean biostratigraphic Zones. In addition, the location OS the TortonianNessinian boundary has been accurately placed at some 150 m below the main gypsurn unit outcropping in the basin. The integrated bio-magnetostratigraphic data fiom the studied section allows a tentative interpretation OS the identified magnetozones. Thus, a correlation to the Geomagnetic Polarity Time Scale is presented for more than 900 m of pre-evaporite Miocene stratigraphic succession fiom the Lorca basin. Moreover, about 15' OS anticlockwise rotation has been detected. Its significance is evaluated in the basin geodynamic framework.

Spatio-temporal image correlation (STIC): nova técnica para avaliação do coração fetal

As malformações cardíacas são as mais freqüentes anomalias congênitas ao nascimento, entretanto, a sua detecção pré-natal pela ultra-sonografia convencional permanece baixa. As ultra-sonografias de terceira e quarta dimensões surgiram no início da década de 90, apresentando grandes aplicações em obstetrícia, principalmente nos casos de diagnósticos duvidosos à ultra-sonografia bidimensional. O spatio-temporal image correlation (STIC) representa grande avanço na área de ultra-som de quarta dimensão; constitui-se em um software acoplado ao aparelho Voluson 730 Expert, que permite a aquisição volumétrica do coração fetal e suas conexões vasculares. As análises volumétricas são realizadas nos modos multiplanar e de renderização, podendo-se também utilizar o Doppler. Apresenta, como grandes vantagens, a aquisição rápida e a possibilidade de análise posterior por especialistas em ecocardiografia fetal. Pode ser aplicada para a pesquisa de quaisquer cardiopatias congênitas, pois permite a aquisição de qualquer plano, diferentemente do ultra-som bidimensional. Sua principal desvantagem está relacionada aos movimentos fetais. A maior difusão do método pode permitir um aumento na detecção de malformações cardíacas, pois possibilita ao ultra-sonografista geral encaminhar, via Internet, os volumes para a análise por especialistas em ecocardiografia fetal.

Combining niche modelling and landscape genetics to study local adaptation: A novel approach illustrated using alpine plants

Understanding the factors that shape adaptive genetic variation across species niches has become of paramount importance in evolutionary ecology, especially to understand how adaptation to changing climate affects the geographic range of species. The distribution of adaptive alleles in the ecological niche is determined by the emergence of novel mutations, their fitness consequences and gene flow that connects populations across species niches. Striking demographical differences and source sink dynamics of populations between the centre and the margin of the niche can play a major role in the emergence and spread of adaptive alleles. Although some theoretical predictions have long been proposed, the origin and distribution of adaptive alleles within species niches remain untested. In this paper, we propose and discuss a novel empirical approach that combines landscape genetics with species niche modelling, to test whether alleles that confer local adaptation are more likely to occur in either marginal or central populations of species niches. We illustrate this new approach by using a published data set of 21 alpine plant species genotyped with a total of 2483 amplified fragment length polymorphisms (AFLP), distributed over more than 1733 sampling sites across the Alps. Based on the assumption that alleles that were statistically associated with environmental variables were adaptive, we found that adaptive alleles in the margin of a species niche were also present in the niche centre, which suggests that adaptation originates in the niche centre. These findings corroborate models of species range evolution, in which the centre of the niche contributes to the emergence of novel adaptive alleles, which diffuse towards niche margins and facilitate niche and range expansion through subsequent local adaptation. Although these results need to be confirmed via fitness measurements in natural populations and functionally characterised genetic sequences, this study provides a first step towards understanding how adaptive genetic variation emerges and shapes species niches and geographic ranges along environmental gradients.

Study and modelling of the effect of herbicides pulse exposure on freshwater microalgae

De plus en plus de substances chimiques sont émises et détectées dans l'environnement.Parmi ces substances, on trouve les herbicides qui sont utilisés en agriculture pour luttercontre la présence des mauvaises herbes. Après leur application sur les sols, les herbicidespeuvent être entrainés par les eaux de pluie jusque dans les ruisseaux et les rivières. Lesconcentrations de ces substances varient donc de manière importante dans les systèmesaquatiques en période de pluie ou en période de temps sec. Des pics élevés de concentrationssont suivis de période de concentrations très faibles ou nulles. Les herbicides présents dans lescours d'eau peuvent engendrer des effets toxiques sur les algues et les plantes aquatiques. Orles tests classiques d'écotoxicologie effectués en laboratoire sont réalisés en exposant lesespèces vivantes à des polluants de manière continue. Ils ne permettent donc pas d'évaluer leseffets des concentrations fluctuantes comme celles des herbicides. Le but de cette thèse estd'étudier et de modéliser les effets des concentrations fluctuantes d'herbicide sur les espècesde microalgues vertes Scenedesmus vacuolatus et Pseudokirchneriella subcapitata. Desexpériences en laboratoire ont également été effectuées dans le but de valider le modèle.Quatre herbicides ont été testés. Il s'agit de l'atrazine (utilisé jusqu'à récemment pour lemaïs), du diuron (utilisé dans la vigne), de l'isoproturon (utilisé pour les céréales) et du Smétolachlore(utilisé pour le maïs). Les résultats de ce travail de thèse indiquent que les effetsdes concentrations fluctuantes d'herbicide peuvent être modélisés sur des algues d'eau douce.Le modèle est relativement simple pour les inhibiteurs de la photosynthèse tels que l'atrazine,le diuron ou l'isoproturon. Il nécessite la connaissance de deux paramètres, le taux decroissance de l'algue sans polluant et la courbe dose-réponse pour chaque substance.Cependant, des expériences supplémentaires doivent être réalisées si la substance étudiéeinduit un délai de l'effet et du rétablissement ou si une algue est cultivée avec une autre alguedans le même milieu de croissance. Le modèle pourrait également être adapté pour tenircompte des mélanges de substances. Appliqué pour prédire les effets sur les algues descénarios réels, le modèle montre que les longs pics de concentrations jouent le rôle le plusimportant. Il est donc crucial de les mesurer lors du monitoring des cours d'eau. D'autre part,une évaluation du risque effectuée avec ce modèle montre que l'impact des pics deconcentrations sur les espèces les plus sensibles est total. Cela met en évidence, une fois deplus, l'importance de tenir compte de ces concentrations fluctuantes dans l'évaluation durisque environnemental des herbicides, mais également des autres polluants.

Subthalamic (STN) Deep Brain Stimulation (DBS) in Parkinson's Disease (PD): Correlation Between the Location of the Stimulated Contacts and the Clinical Effects in 14 Patients

Objectives: To correlate the chronic stimulated electrode position on postoperative MRI with the clinical response obtained in PD patients. Material and Method: We retrospectively reviewed 14 consecutive parkinsonian patients who were selected for STN-DBS surgery. Coordinates were determined on an IR T2 MRI coronal section per pendicular to AC-PC plane 3 mm posterior to midcommissural point (MCP) and 12 mm lateral to the midline the inferior aspect of subthalamic region. A CRW stereotactic frame was used for the surgical procedure. A 3D IR T2 MRI was performed postoperatively to determine the location of the stimulated contact in each patient. The clinical results were assessed independently by the neurological team. Results: All but 2 patients had monopolar stimulation. The mean coordinates of the stimulated contacts were: AP ^ ÿ4:23G1:4, Lat ^ 1:12G0:15, Vert ^ ÿ4:1 G2:7 to the MCP. With a mean follow-up of 8 months, all stimulated patients had a significant clinical improvement (preop/postop «ON» UPDRS: 25:8G7:0= 23:3 G8:6; preop/postop «OFF» UPDRS: 50:2G11:4=26:0 G7:8), 60% of them without any antiparkinsonian drug. Conclusion: According to the stereotactic atlas of Schaltenbrand and Warren and the 3D shape of the STN, our results show that our targetting is accurate and almost all the stimulated contacts are comprised in the STN volume. This indicates that MRI is a safe, precise and reproducible procedure for targetting the STN. The location of the stimulated contact within the STN volume is a good predictor of the clinical results.

Animal modelling for inherited central vision loss.

Disease-causing variants of a large number of genes trigger inherited retinal degeneration leading to photoreceptor loss. Because cones are essential for daylight and central vision such as reading, mobility, and face recognition, this review focuses on a variety of animal models for cone diseases. The pertinence of using these models to reveal genotype/phenotype correlations and to evaluate new therapeutic strategies is discussed. Interestingly, several large animal models recapitulate human diseases and can serve as a strong base from which to study the biology of disease and to assess the scale-up of new therapies. Examples of innovative approaches will be presented such as lentiviral-based transgenesis in pigs and adeno-associated virus (AAV)-gene transfer into the monkey eye to investigate the neural circuitry plasticity of the visual system. The models reported herein permit the exploration of common mechanisms that exist between different species and the identification and highlighting of pathways that may be specific to primates, including humans.

Modelling the consequences of a reduction in alcohol consumption among patients with alcohol dependence based on real-life observational data.

BACKGROUND: Most available pharmacotherapies for alcohol-dependent patients target abstinence; however, reduced alcohol consumption may be a more realistic goal. Using randomized clinical trial (RCT) data, a previous microsimulation model evaluated the clinical relevance of reduced consumption in terms of avoided alcohol-attributable events. Using real-life observational data, the current analysis aimed to adapt the model and confirm previous findings about the clinical relevance of reduced alcohol consumption. METHODS: Based on the prospective observational CONTROL study, evaluating daily alcohol consumption among alcohol-dependent patients, the model predicted the probability of drinking any alcohol during a given day. Predicted daily alcohol consumption was simulated in a hypothetical sample of 200,000 patients observed over a year. Individual total alcohol consumption (TAC) and number of heavy drinking days (HDD) were derived. Using published risk equations, probabilities of alcohol-attributable adverse health events (e.g., hospitalizations or death) corresponding to simulated consumptions were computed, and aggregated for categories of patients defined by HDDs and TAC (expressed per 100,000 patient-years). Sensitivity analyses tested model robustness. RESULTS: Shifting from >220 HDDs per year to 120-140 HDDs and shifting from 36,000-39,000 g TAC per year (120-130 g/day) to 15,000-18,000 g TAC per year (50-60 g/day) impacted substantially on the incidence of events (14,588 and 6148 events avoided per 100,000 patient-years, respectively). Results were robust to sensitivity analyses. CONCLUSIONS: This study corroborates the previous microsimulation modeling approach and, using real-life data, confirms RCT-based findings that reduced alcohol consumption is a relevant objective for consideration in alcohol dependence management to improve public health.

Modelling body mass index and endometrial cancer risk in a pooled-analysis of three case-control studies.

OBJECTIVE: To quantify the relation between body mass index (BMI) and endometrial cancer risk, and to describe the shape of such a relation. DESIGN: Pooled analysis of three hospital-based case-control studies. SETTING: Italy and Switzerland. POPULATION: A total of 1449 women with endometrial cancer and 3811 controls. METHODS: Multivariate odds ratios (OR) and 95% confidence intervals (95% CI) were obtained from logistic regression models. The shape of the relation was determined using a class of flexible regression models. MAIN OUTCOME MEASURE: The relation of BMI with endometrial cancer. RESULTS: Compared with women with BMI 18.5 to <25 kg/m(2) , the odds ratio was 5.73 (95% CI 4.28-7.68) for women with a BMI ≥35 kg/m(2) . The odds ratios were 1.10 (95% CI 1.09-1.12) and 1.63 (95% CI 1.52-1.75) respectively for an increment of BMI of 1 and 5 units. The relation was stronger in never-users of oral contraceptives (OR 3.35, 95% CI 2.78-4.03, for BMI ≥30 versus <25 kg/m(2) ) than in users (OR 1.22, 95% CI 0.56-2.67), and in women with diabetes (OR 8.10, 95% CI 4.10-16.01, for BMI ≥30 versus <25 kg/m(2) ) than in those without diabetes (OR 2.95, 95% CI 2.44-3.56). The relation was best fitted by a cubic model, although after the exclusion of the 5% upper and lower tails, it was best fitted by a linear model. CONCLUSIONS: The results of this study confirm a role of elevated BMI in the aetiology of endometrial cancer and suggest that the risk in obese women increases in a cubic nonlinear fashion. The relation was stronger in never-users of oral contraceptives and in women with diabetes. TWEETABLE ABSTRACT: Risk of endometrial cancer increases with elevated body weight in a cubic nonlinear fashion.