Mathématiques, Informatique et Statistique pour l'Environnement et l'Agronomie

INTRODUCTION: To investigate whether respiratory variation of inferior vena cava diameter (cIVC) predict fluid responsiveness in spontaneously breathing patients with acute circulatory failure (ACF). METHODS: Forty patients with ACF and spontaneous breathing were included. Response to fluid challenge was defined as a 15% increase of subaortic velocity time index (VTI) measured by transthoracic echocardiography. Inferior vena cava diameters were recorded by a subcostal view using M Mode. The cIVC was calculated as follows: (Dmax - Dmin/Dmax) × 100 and then receiver operating characteristic (ROC) curves were generated for cIVC, baseline VTI, E wave velocity, E/A and E/Ea ratios. RESULTS: Among 40 included patients, 20 (50%) were responders (R). The causes of ACF were sepsis (n = 24), haemorrhage (n = 11), and dehydration (n = 5). The area under the ROC curve for cIVC was 0.77 (95% CI: 0.60-0.88). The best cutoff value was 40% (Se = 70%, Sp = 80%). The AUC of the ROC curves for baseline E wave velocity, VTI, E/A ratio, E/Ea ratio were 0.83 (95% CI: 0.68-0.93), 0.78 (95% CI: 0.61-0.88), 0.76 (95% CI: 0.59-0.89), 0.58 (95% CI: 0.41-0.75), respectively. The differences between AUC the ROC curves for cIVC and baseline E wave velocity, baseline VTI, baseline E/A ratio, and baseline E/Ea ratio were not statistically different (p = 0.46, p = 0.99, p = 1.00, p = 0.26, respectively). CONCLUSION: In spontaneously breathing patients with ACF, high cIVC values (>40%) are usually associated with fluid responsiveness while low values (< 40%) do not exclude fluid responsiveness.

As biodiversity is declining at an unprecedented rate, an important current scientific challenge is to understand and predict the consequences of biodiversity loss. Here, we develop a theory that predicts the temporal variability of community biomass from the properties of individual component species in monoculture. Our theory shows that biodiversity stabilises ecosystems through three main mechanisms: (1) asynchrony in species' responses to environmental fluctuations, (2) reduced demographic stochasticity due to overyielding in species mixtures and (3) reduced observation error (including spatial and sampling variability). Parameterised with empirical data from four long-term grassland biodiversity experiments, our prediction explained 22-75% of the observed variability, and captured much of the effect of species richness. Richness stabilised communities mainly by increasing community biomass and reducing the strength of demographic stochasticity. Our approach calls for a re-evaluation of the mechanisms explaining the effects of biodiversity on ecosystem stability.

RATIONALE: Difficult intubation in the intensive care unit (ICU) is a challenging issue. OBJECTIVES: To develop and validate a simplified score for identifying patients with difficult intubation in the ICU and to report related complications. METHODS: Data collected in a prospective multicenter study from 1,000 consecutive intubations from 42 ICUs were used to develop a simplified score of difficult intubation, which was then validated externally in 400 consecutive intubation procedures from 18 other ICUs and internally by bootstrap on 1,000 iterations. MEASUREMENTS AND MAIN RESULTS: In multivariate analysis, the main predictors of difficult intubation (incidence = 11.3%) were related to patient (Mallampati score III or IV, obstructive sleep apnea syndrome, reduced mobility of cervical spine, limited mouth opening); pathology (severe hypoxia, coma); and operator (nonanesthesiologist). From the β parameter, a seven-item simplified score (MACOCHA score) was built, with an area under the curve (AUC) of 0.89 (95% confidence interval [CI], 0.85-0.94). In the validation cohort (prevalence of difficult intubation = 8%), the AUC was 0.86 (95% CI, 0.76-0.96), with a sensitivity of 73%, a specificity of 89%, a negative predictive value of 98%, and a positive predictive value of 36%. After internal validation by bootstrap, the AUC was 0.89 (95% CI, 0.86-0.93). Severe life-threatening events (severe hypoxia, collapse, cardiac arrest, or death) occurred in 38% of the 1,000 cases. Patients with difficult intubation (n = 113) had significantly higher severe life-threatening complications than those who had a nondifficult intubation (51% vs. 36%; P < 0.0001). CONCLUSIONS: Difficult intubation in the ICU is strongly associated with severe life-threatening complications. A simple score including seven clinical items discriminates difficult and nondifficult intubation in the ICU. Clinical trial registered with www.clinicaltrials.gov (NCT 01532063).

The budding yeast Saccharomyces cerevisiae can be found in the wild and is also frequently associated with human activities. Despite recent insights into the phylogeny of this species, much is still unknown about how evolutionary processes related to anthropogenic niches have shaped the genomes and phenotypes of S. cerevisiae. To address this question, we performed population-level sequencing of 82 S. cerevisiae strains from wine, flor, rum, dairy products, bakeries, and the natural environment (oak trees). These genomic data enabled us to delineate specific genetic groups corresponding to the different ecological niches and revealed high genome content variation across the groups. Most of these strains, compared with the reference genome, possessed additional genetic elements acquired by introgression or horizontal transfer, several of which were population-specific. In addition, several genomic regions in each population showed evidence of nonneutral evolution, as shown by high differentiation, or of selective sweeps including genes with key functions in these environments (e.g., amino acid transport for wine yeast). Linking genetics to lifestyle differences and metabolite traits has enabled us to elucidate the genetic basis of several niche-specific population traits, such as growth on galactose for cheese strains. These data indicate that yeast has been subjected to various divergent selective pressures depending on its niche, requiring the development of customized genomes for better survival in these environments. These striking genome dynamics associated with local adaptation and domestication reveal the remarkable plasticity of the S. cerevisiae genome, revealing this species to be an amazing complex of specialized populations.

We study a Markov process with two components: the first component evolves according to one of finitely many underlying Markovian dynamics, with a choice of dynamics that changes at the jump times of the second component. The second component is discrete and its jump rates may depend on the position of the whole process. Under regularity assumptions on the jump rates and Wasserstein contraction conditions for the underlying dynamics, we provide a concrete criterion for the convergence to equilibrium in terms of Wasserstein distance. The proof is based on a coupling argument and a weak form of the Harris Theorem. In particular, we obtain exponential ergodicity in situations which do not verify any hypoellipticity assumption, but are not uniformly contracting either. We also obtain a bound in total variation distance under a suitable regularising assumption. Some examples are given to illustrate our result, including a class of piecewise deterministic Markov processes.

In this article we propose a new framework for studying adaptive radiations in the context of diversity-dependent diversification. Diversity dependence causes diversification to decelerate at the end of an adaptive radiation but also plays a key role in the initial pulse of diversification. In particular, key innovations (which in our definition include novel traits as well as new environments) may cause decoupling of the diversity-dependent dynamics of the innovative clade from the diversity-dependent dynamics of its ancestral clade. We present a likelihood-based inference method to test for decoupling of diversity dependence using molecular phylogenies. The method, which can handle incomplete phylogenies, identifies when the decoupling took place and which diversification parameters are affected. We illustrate our approach by applying it to the molecular phylogeny of the North American clade of the legume tribe Psoraleeae (47 extant species, of which 4 are missing). Two diversification rate shifts were previously identified for this clade; our analysis shows that the first, positive shift can be associated with decoupling of two Pediomelum subgenera from the other Psoraleeae lineages, while we argue that the second, negative shift can be attributed to speciation being protracted. The latter explanation yields nonzero extinction rates, in contrast to previous findings. Our framework offers a new perspective on macroevolution: new environments and novel traits (ecological opportunity) and diversity dependence (ecological limits) cannot be considered separately.

INTRODUCTION: Pulse pressure variation (PPV) has been shown to predict fluid responsiveness in ventilated intensive care unit (ICU) patients. The present study was aimed at assessing the diagnostic accuracy of PPV for prediction of fluid responsiveness by using the grey zone approach in a large population. METHODS: The study pooled data of 556 patients from nine French ICUs. Hemodynamic (PPV, central venous pressure (CVP) and cardiac output) and ventilator variables were recorded. Responders were defined as patients increasing their stroke volume more than or equal to 15% after fluid challenge. The receiver operating characteristic (ROC) curve and grey zone were defined for PPV. The grey zone was evaluated according to the risk of fluid infusion in hypoxemic patients. RESULTS: Fluid challenge led to increased stroke volume more than or equal to 15% in 267 patients (48%). The areas under the ROC curve of PPV and CVP were 0.73 (95% confidence interval (CI): 0.68 to 0.77) and 0.64 (95% CI 0.59 to 0.70), respectively (P<0.001). A grey zone of 4 to 17% (62% of patients) was found for PPV. A tidal volume more than or equal to 8 ml.kg(-1) and a driving pressure (plateau pressure - PEEP) more than 20 cmH2O significantly improved the area under the ROC curve for PPV. When taking into account the risk of fluid infusion, the grey zone for PPV was 2 to 13%. CONCLUSIONS: In ventilated ICU patients, PPV values between 4 and 17%, encountered in 62% patients exhibiting validity prerequisites, did not predict fluid responsiveness.

MOTIVATION: Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. RESULTS: To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases. AVAILABILITY AND IMPLEMENTATION: More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.

BACKGROUND: The dual concepts of pan and core genomes have been widely adopted as means to assess the distribution of gene families within microbial species and genera. The core genome is the set of genes shared by a group of organisms; the pan genome is the set of all genes seen in any of these organisms. A variety of methods have provided drastically different estimates of the sizes of pan and core genomes from sequenced representatives of the same groups of bacteria. RESULTS: We use a combination of mathematical, statistical and computational methods to show that current predictions of pan and core genome sizes may have no correspondence to true values. Pan and core genome size estimates are problematic because they depend on the estimation of the occurrence of rare genes and genomes, respectively, which are difficult to estimate precisely because they are rare. Instead, we introduce and evaluate a robust metric - genomic fluidity - to categorize the gene-level similarity among groups of sequenced isolates. Genomic fluidity is a measure of the dissimilarity of genomes evaluated at the gene level. CONCLUSIONS: The genomic fluidity of a population can be estimated accurately given a small number of sequenced genomes. Further, the genomic fluidity of groups of organisms can be compared robustly despite variation in algorithms used to identify genes and their homologs. As such, we recommend that genomic fluidity be used in place of pan and core genome size estimates when assessing gene diversity within genomes of a species or a group of closely related organisms.

BACKGROUND: Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. RESULTS: In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. CONCLUSIONS: Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.

Integration of the priming effect (PE) in ecosystem models is crucial to better predict the consequences of global change on ecosystem carbon (C) dynamics and its feedbacks on climate. Over the last decade, many attempts have been made to model PE in soil. However, PE has not yet been incorporated into any ecosystem models. Here, we build plant/soil models to explore how PE and microbial diversity influence soil/plant interactions and ecosystem C and nitrogen (N) dynamics in response to global change (elevated CO2 and atmospheric N depositions). Our results show that plant persistence, soil organic matter (SOM) accumulation, and low N leaching in undisturbed ecosystems relies on a fine adjustment of microbial N mineralization to plant N uptake. This adjustment can be modeled in the SYMPHONY model by considering the destruction of SOM through PE, and the interactions between two microbial functional groups: SOM decomposers and SOM builders. After estimation of parameters, SYMPHONY provided realistic predictions on forage production, soil C storage and N leaching for a permanent grassland. Consistent with recent observations, SYMPHONY predicted a CO2 -induced modification of soil microbial communities leading to an intensification of SOM mineralization and a decrease in the soil C stock. SYMPHONY also indicated that atmospheric N deposition may promote SOM accumulation via changes in the structure and metabolic activities of microbial communities. Collectively, these results suggest that the PE and functional role of microbial diversity may be incorporated in ecosystem models with a few additional parameters, improving accuracy of predictions.

BACKGROUND AND OBJECTIVES: Protein-energy wasting is common in long-term haemodialysis (HD) patients with chronic kidney disease and is associated with increased morbidity and mortality. The creatinine index (CI) is a simple and useful nutritional parameter reflecting the dietary skeletal muscle protein intake and skeletal muscle mass of the patient. Because of the complexity of creatinine kinetic modeling (CKM) to derive CI, we developed a more simplified formula to estimate CI in HD patients. DESIGN, SETTING, PARTICIPANTS & MEASUREMENTS: A large database of 549 HD patients followed over more than 20 years including monthly CKM-derived CI values was used to develop a simple equation based on patient demographics, predialysis serum creatinine values and dialysis dose (spKt/V) using mixed regression models. RESULTS: The equation to estimate CI was developed based on age, gender, pre-dialysis serum creatinine concentrations and spKt/V urea. The equation-derived CI correlated strongly with the measured CI using CKM (correlation coefficient = 0.79, p-value <0.001). The mean error of CI prediction using the equation was 13.47%. Preliminary examples of few typical HD patients have been used to illustrate the clinical relevance and potential usefulness of CI. CONCLUSIONS: The elementary equation used to derive CI using demographic parameters, pre-dialysis serum creatinine concentrations and dialysis dose is a simple and accurate surrogate measure for muscle mass estimation. However, the predictive value of the simplified CI assessment method on mortality deserves further evaluation in large cohorts of HD patients.

Administration of heparin in the secondary prevention of placental vascular complications is still experimental. In women with a previous severe pre-eclampsia, we investigated the effectiveness of enoxaparin, a low-molecular-weight heparin, in preventing these complications. Between January 2000 and January 2010, 224 women from the NOHA First cohort, with previous severe pre-eclampsia but no foetal loss during their first pregnancy and negative for antiphospholipid antibodies, were randomised to either a prophylactic daily dose of enoxaparin starting from the positive pregnancy test (n=112), or no enoxaparin (n=112). The primary outcome was a composite of at least one of the following: pre-eclampsia, abruptio placentae, birthweight ≤ 5th percentile, or foetal loss after 20 weeks. Enoxaparin was associated with a lower frequency of primary outcome: 8.9% (n=10/112) vs. 25 % (28/112), p=0.004, hazard ratio = 0.32, 95% confidence interval (0.16-0.66), p=0.002. Enoxaparin was safe, with no obvious side-effect, no thrombocytopenia nor major bleeding event excess. This pilot study shows that enoxaparin given early during the second pregnancy decreases the occurrence of placental vascular complications in women with a previous severe pre-eclampsia during their first pregnancy.

PURPOSE: To retrospectively determine whether magnetic resonance (MR) volumetry of rectal cancer is a reproducible method for predicting disease-free survival (DFS) in patients with locally advanced low or midrectal tumors who undergo combined chemotherapy and radiation therapy (CRT) before total mesorectal excision. MATERIALS AND METHODS: The institutional review board does not require approval for the use of patient data obtained for an observational retrospective study. Fifty-eight patients were included in the study; 42 patients had low-lying tumors. Two radiologists independently measured tumor volumes before and after CRT with use of semiautomated software. The radiologists were blinded to the clinical information for each patient. The tumor volume reduction ratio, circumferential resection margin, T stage, and occurrence of downstaging were compared with the histopathologic response and DFS. The threshold of tumor volume reduction for predicting DFS was assessed with receiver operating characteristic curve analysis. DFS was estimated with the Kaplan-Meier method and compared between groups with the log-rank test. RESULTS: The interobserver correlation coefficient between the two radiologists was 0.87 (95% confidence interval [CI]: 0.76, 0.93) for pre-CRT volumetry and 0.81 (95% CI: 0.74, 0.90) for post-CRT volumetry. A tumor volume reduction of at least 70% was significantly associated with good histologic regression (tumor regression grade [TRG], 3 or 4) (P <.0001) compared with a volume reduction rate of less than 70%. DFS was studied in 51 patients. The mean follow-up of survivors at the time of analysis was 52 months ± 20 (standard deviation). Patients with a volume reduction ratio of at least 70% had a higher DFS (P <.0001). Tumor volume reduction was an independent prognostic parameter in multivariate analysis for DFS (P = .003; 95% CI: 0.01, 0.4). CONCLUSION: The results demonstrate that volumetric measurements are reliable markers of rectal cancer prognosis, enabling the prediction of DFS and TRG. The cutoff of 70% is an easy parameter to use as a surrogate for clinical response to predict both TRG and outcome.

BACKGROUND: The volatile metabolites produced by Saccharomyces cerevisiae during alcoholic fermentation, which are mainly esters, higher alcohols and organic acids, play a vital role in the quality and perception of fermented beverages, such as wine. Although the metabolic pathways and genes behind yeast fermentative aroma formation are well described, little is known about the genetic mechanisms underlying variations between strains in the production of these aroma compounds. To increase our knowledge about the links between genetic variation and volatile production, we performed quantitative trait locus (QTL) mapping using 130 F2-meiotic segregants from two S. cerevisiae wine strains. The segregants were individually genotyped by next-generation sequencing and separately phenotyped during wine fermentation. RESULTS: Using different QTL mapping strategies, we were able to identify 65 QTLs in the genome, including 55 that influence the formation of 30 volatile secondary metabolites, 14 with an effect on sugar consumption and central carbon metabolite production, and 7 influencing fermentation parameters. For ethyl lactate, ethyl octanoate and propanol formation, we discovered 2 interacting QTLs each. Within 9 of the detected regions, we validated the contribution of 13 genes in the observed phenotypic variation by reciprocal hemizygosity analysis. These genes are involved in nitrogen uptake and metabolism (AGP1, ALP1, ILV6, LEU9), central carbon metabolism (HXT3, MAE1), fatty acid synthesis (FAS1) and regulation (AGP2, IXR1, NRG1, RGS2, RGT1, SIR2) and explain variations in the production of characteristic sensorial esters (e.g., 2-phenylethyl acetate, 2-metyhlpropyl acetate and ethyl hexanoate), higher alcohols and fatty acids. CONCLUSIONS: The detection of QTLs and their interactions emphasizes the complexity of yeast fermentative aroma formation. The validation of underlying allelic variants increases knowledge about genetic variation impacting metabolic pathways that lead to the synthesis of sensorial important compounds. As a result, this work lays the foundation for tailoring S. cerevisiae strains with optimized volatile metabolite production for fermented beverages and other biotechnological applications.

Abstract Crop models are useful tools because they can help understand many complex processes by simulating them. They are mainly designed at a specific spatial scale, the field. But with the new spatial data being made available in modern agriculture, they are being more and more applied at multiple and changing scales. These applications range from typically at broader scales, to perform regional or national studies, or at finer scales to develop modern site-specific management approaches. These new approaches to the application of crop models raise new questions concerning the evaluation of their performance, particularly for downscaled applications. This article first reviews the reasons why practitioners decide to spatialize crop models and the main methods they have used to do this, which questions the best place of the spatialization process in the modelling framework. A strong focus is then given to the evaluation of these spatialized crop models. Evaluation metrics, including the consideration of dedicated sensitivity indices are reviewed from the published studies. Using a simple example of a spatialized crop model being used to define management zones in precision viticulture, it is shown that classical model evaluation involving aspatial indices (e.g. the RMSE) is not sufficient to characterize the model performance in this context. A focus is made at the end of the review on potentialities that a complementary evaluation could bring in a precision agriculture context.

Phenomic datasets need to be accessible to the scientific community. Their reanalysis requires tracing relevant information on thousands of plants, sensors and events. The open-source Phenotyping Hybrid Information System (PHIS) is proposed for plant phenotyping experiments in various categories of installations (field, glasshouse). It unambiguously identifies all objects and traits in an experiment and establishes their relations via ontologies and semantics that apply to both field and controlled conditions. For instance, the genotype is declared for a plant or plot and is associated with all objects related to it. Events such as successive plant positions, anomalies and annotations are associated with objects so they can be easily retrieved. Its ontology-driven architecture is a powerful tool for integrating and managing data from multiple experiments and platforms, for creating relationships between objects and enriching datasets with knowledge and metadata. It interoperates with external resources via web services, thereby allowing data integration into other systems; for example, modelling platforms or external databases. It has the potential for rapid diffusion because of its ability to integrate, manage and visualize multi-source and multi-scale data, but also because it is based on 10 yr of trial and error in our groups.

The gene composition of bacteria of the same species can differ significantly between isolates. Variability in gene composition can be summarized in terms of gene frequency distributions, in which individual genes are ranked according to the frequency of genomes in which they appear. Empirical gene frequency distributions possess a U-shape, such that there are many rare genes, some genes of intermediate occurrence, and many common genes. It would seem that U-shaped gene frequency distributions can be used to infer the essentiality and/or importance of a gene to a species. Here, we ask: can U-shaped gene frequency distributions, instead, arise generically via neutral processes of genome evolution? We introduce a neutral model of genome evolution which combines birth-death processes at the organismal level with gene uptake and loss at the genomic level. This model predicts that gene frequency distributions possess a characteristic U-shape even in the absence of selective forces driving genome and population structure. We compare the model predictions to empirical gene frequency distributions from 6 multiply sequenced species of bacterial pathogens. We fit the model with constant population size to data, matching U-shape distributions albeit without matching all quantitative features of the distribution. We find stronger model fits in the case where we consider exponentially growing populations. We also show that two alternative models which contain a "rigid" and "flexible" core component of genomes provide strong fits to gene frequency distributions. The analysis of neutral models of genome evolution suggests that U-shaped gene frequency distributions provide less information than previously suggested regarding gene essentiality. We discuss the need for additional theory and genomic level information to disentangle the roles of evolutionary mechanisms operating within and amongst individuals in driving the dynamics of gene distributions.

Although mathematical modelling has reached a degree of maturity in the last decades, microbial ecology is still developing, albeit at a rapid pace thanks to new insights provided by modern molecular tools. However, whilst microbiologists have long enjoyed the perspectives that particular mathematical frameworks can provide, there remains a reluctance to fully embrace the potential of models, which appear too complex, esoteric or distant from the 'real-world'. Nevertheless there is a strong case for pursuing the development of mathematical models to describe microbial behaviour and interactions, dynamically, spatially and across scales. Here we put forward perspectives on the current state of mathematical modelling in microbial ecology, looking back at the developments that have defined the synergies between the disciplines, and outline some of the existing challenges that motivate us to provide practical models in the hope that greater engagement with empiricists and practitioners in the microbiological domain may be achieved. We also indicate recent advances in modelling that have had impact in both the fundamental understanding of microbial ecology and its practical application in engineered biological systems. In this way, it is anticipated that interest can be garnered from across the microbiological spectrum resulting in a broader uptake of mathematical concepts in lecture theatres, laboratories and industrial systems.

Predicting whether an obese critically ill patient can be successfully extubated may be specially challenging. Several weaning tests have been described but no physiological study has evaluated the weaning test that would best reflect the post-extubation inspiratory effort. This was a physiological randomized crossover study in a medical and surgical single-center Intensive Care Unit, in patients with body mass index (BMI) >35 kg/m2 who were mechanically ventilated for more than 24 h and underwent a weaning test. After randomization, 17 patients were explored using five settings : pressure support ventilation (PSV) 7 and positive end-expiratory pressure (PEEP) 7 cmH2O; PSV 0 and PEEP 7cmH2O; PSV 7 and PEEP 0 cmH2O; PSV 0 and PEEP 0 cmH2O; and a T piece, and after extubation. To further minimize interaction between each setting, a period of baseline ventilation was performed between each step of the study. We hypothesized that the post-extubation work of breathing (WOB) would be similar to the T-tube WOB. Respiratory variables and esophageal and gastric pressure were recorded. Inspiratory muscle effort was calculated as the esophageal and trans-diaphragmatic pressure time products and WOB. Sixteen obese patients (BMI 44 kg/m2 ± 8) were included and successfully extubated. Post-extubation inspiratory effort, calculated by WOB, was 1.56 J/L ± 0.50, not statistically different from the T piece (1.57 J/L ± 0.56) or PSV 0 and PEEP 0 cmH2O (1.58 J/L ± 0.57), whatever the index of inspiratory effort. The three tests that maintained pressure support statistically underestimated post-extubation inspiratory effort (WOB 0.69 J/L ± 0.31, 1.15 J/L ± 0.39 and 1.09 J/L ± 0.49, respectively, p < 0.001). Respiratory mechanics and arterial blood gases did not differ between the five tests and the post-extubation condition. In obese patients, inspiratory effort measured during weaning tests with either a T-piece or a PSV 0 and PEEP 0 was not different to post-extubation inspiratory effort. In contrast, weaning tests with positive pressure overestimated post-extubation inspiratory effort. Clinical trial.gov (reference NCT01616901 ), 2012, June 4th