Wheat Bran Pretreatment by Room Temperature Ionic Liquid-Water Mixture: Optimization of Process Conditions by PLS-Surface Response Design

International audienceRoom Temperature Ionic Liquids (RTILs) pretreatment are well-recognized to improve the enzymatic production of platform molecules such as sugar monomers from lignocellulosic biomass (LCB). The conditions for implementing this key step requires henceforth optimization to reach a satisfactory compromise between energy saving, required RTIL amount and hydrolysis yields. Wheat bran (WB) and destarched wheat bran (DWB), which constitute relevant sugar-rich feedstocks were selected for this present study. Pretreatments of these two distinct biomasses with various 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc])-water mixtures prior to hydrolysis catalyzed by hemicellulolytic cocktail (Cellic CTec2) were finely investigated. The main operating conditions such as pretreatment temperature (25–150°C), time (40–180 min), WB and DWB loading (2–5% w/v) and concentration of [C2mim][OAc] in water [10–100% (v/v)] were screened through glucose and xylose yields and then optimized through a Partial Least Square (PLS)—Second Order Design. In an innovative way, the PLS results showed that the four factors and their interactions could be well-fitted by a second-order model (p < 0.05). The quadratic PLS models were used to predict optimal pretreatment conditions. Thus, maximum glucose (83%) and xylose (95%) yields were obtained from enzymatic hydrolysis of WB pretreated at 150°C for 40 min with 10% of [C2mim][OAc] in water and 5% of WB loading. For DWB, maximum glucose (100%) and xylose (57%) yields were achieved for pretreatment temperatures of 150°C and 25°C, respectively. The required duration was still 40 min, with 20% of [C2mim][OAc] in water and a 5% DWB loading. Then, Multiple Response Optimization (MRO) performed by Nelder-Mead Simplex Method displayed sugar yields similar to those obtained by individual PLS optimization. This complete statistical study confirmed that the established models were appropriate to predict the sugar yields achieved after different pretreatment conditions from WB and DWB biomasses. Finally, Scanning Electron microscopy (SEM) studies allowed us to establish clearer link between structural changes induced by pretreatment and the best enzymatic performances obtained

Myogenesis modelled by human pluripotent stem cells uncovers Duchenne muscular dystrophy phenotypes prior to skeletal muscle commitment

Duchenne muscular dystrophy (DMD) causes severe disability of children and death of young men, with an incidence of approximately 1/5,000 male births. Symptoms appear in early childhood, with a diagnosis made around 4 years old, a time where the amount of muscle damage is already significant, preventing early therapeutic interventions that could be more efficient at halting disease progression. In the meantime, the precise moment at which disease phenotypes arise - even asymptomatically - is still unknown. Thus, there is a critical need to better define DMD onset as well as its first manifestations, which could help identify early disease biomarkers and novel therapeutic targets. In this study, we have used human induced pluripotent stem cells (hiPSCs) from DMD patients to model skeletal myogenesis, and compared their differentiation dynamics to healthy control cells by a comprehensive multi-omics analysis. Transcriptome and miRnome comparisons combined with protein analyses at 7 time points demonstrate that hiPSC differentiation 1) mimics described DMD phenotypes at the differentiation endpoint; and 2) homogeneously and robustly recapitulates key developmental steps - mesoderm, somite, skeletal muscle - which offers the possibility to explore dystrophin functions and find earlier disease biomarkers. Starting at the somite stage, mitochondrial gene dysregulations escalate during differentiation. We also describe fibrosis as an intrinsic feature of skeletal muscle cells that starts early during myogenesis. In sum, our data strongly argue for an early developmental manifestation of DMD whose onset is triggered before the entry into the skeletal muscle compartment, data leading to a necessary reconsideration of dystrophin functions during muscle development

Myogenesis modelled by human pluripotent stem cells uncovers Duchenne muscular dystrophy phenotypes prior to skeletal muscle commitment

Duchenne muscular dystrophy (DMD) causes severe disability of children and death of young men, with an incidence of approximately 1/5,000 male births. Symptoms appear in early childhood, with a diagnosis made around 4 years old, a time where the amount of muscle damage is already significant, preventing early therapeutic interventions that could be more efficient at halting disease progression. In the meantime, the precise moment at which disease phenotypes arise - even asymptomatically - is still unknown. Thus, there is a critical need to better define DMD onset as well as its first manifestations, which could help identify early disease biomarkers and novel therapeutic targets. In this study, we have used human induced pluripotent stem cells (hiPSCs) from DMD patients to model skeletal myogenesis, and compared their differentiation dynamics to healthy control cells by a comprehensive multi-omics analysis. Transcriptome and miRnome comparisons combined with protein analyses at 7 time points demonstrate that hiPSC differentiation 1) mimics described DMD phenotypes at the differentiation endpoint; and 2) homogeneously and robustly recapitulates key developmental steps - mesoderm, somite, skeletal muscle - which offers the possibility to explore dystrophin functions and find earlier disease biomarkers. Starting at the somite stage, mitochondrial gene dysregulations escalate during differentiation. We also describe fibrosis as an intrinsic feature of skeletal muscle cells that starts early during myogenesis. In sum, our data strongly argue for an early developmental manifestation of DMD whose onset is triggered before the entry into the skeletal muscle compartment, data leading to a necessary reconsideration of dystrophin functions during muscle development

Loss of full-length dystrophin expression results in major cell-autonomous abnormalities in proliferating myoblasts

Duchenne muscular dystrophy (DMD) affects myofibers and muscle stem cells, causing progressive muscle degeneration and repair defects. It was unknown whether dystrophic myoblasts—the effector cells of muscle growth and regeneration—are affected. Using transcriptomic, genome-scale metabolic modelling and functional analyses, we demonstrate, for the first time, convergent abnormalities in primary mouse and human dystrophic myoblasts. In Dmd(mdx) myoblasts lacking full-length dystrophin, the expression of 170 genes was significantly altered. Myod1 and key genes controlled by MyoD (Myog, Mymk, Mymx, epigenetic regulators, ECM interactors, calcium signalling and fibrosis genes) were significantly downregulated. Gene ontology analysis indicated enrichment in genes involved in muscle development and function. Functionally, we found increased myoblast proliferation, reduced chemotaxis and accelerated differentiation, which are all essential for myoregeneration. The defects were caused by the loss of expression of full-length dystrophin, as similar and not exacerbated alterations were observed in dystrophin-null Dmd(mdx-βgeo) myoblasts. Corresponding abnormalities were identified in human DMD primary myoblasts and a dystrophic mouse muscle cell line, confirming the cross-species and cell-autonomous nature of these defects. The genome-scale metabolic analysis in human DMD myoblasts showed alterations in the rate of glycolysis/gluconeogenesis, leukotriene metabolism, and mitochondrial beta-oxidation of various fatty acids. These results reveal the disease continuum: DMD defects in satellite cells, the myoblast dysfunction affecting muscle regeneration, which is insufficient to counteract muscle loss due to myofiber instability. Contrary to the established belief, our data demonstrate that DMD abnormalities occur in myoblasts, making these cells a novel therapeutic target for the treatment of this lethal disease

Le FORUM, Vol. 32 Nos. 3 & 4

https://digitalcommons.library.umaine.edu/francoamericain_forum/1021/thumbnail.jp

Myogenesis modelled by human pluripotent stem cells: a multi‐omic study of Duchenne myopathy early onset

International audienceBackground Duchenne muscular dystrophy (DMD) causes severe disability of children and death of young men, with an incidence of approximately 1/5000 male births. Symptoms appear in early childhood, with a diagnosis made mostly around 4 years old, a time where the amount of muscle damage is already significant, preventing early therapeutic interventions that could be more efficient at halting disease progression. In the meantime, the precise moment at which disease phenotypes arise-even asymptomatically-is still unknown. Thus, there is a critical need to better define DMD onset as well as its first manifestations, which could help identify early disease biomarkers and novel therapeutic targets. Methods We have used both human tissue-derived myoblasts and human induced pluripotent stem cells (hiPSCs) from DMD patients to model skeletal myogenesis and compared their differentiation dynamics with that of healthy control cells by a comprehensive multi-omic analysis at seven time points. Results were strengthened with the analysis of isogenic CRISPR-edited human embryonic stem cells and through comparisons against published transcriptomic and proteomic datasets from human DMD muscles. The study was completed with DMD knockdown/rescue experiments in hiPSC-derived skeletal muscle progenitor cells and adenosine triphosphate measurement in hiPSC-derived myotubes. Results Transcriptome and miRnome comparisons combined with protein analyses demonstrated that hiPSC differentiation (i) leads to embryonic/foetal myotubes that mimic described DMD phenotypes at the differentiation endpoint and (ii) homogeneously and robustly recapitulates key developmental steps-mesoderm, somite, and skeletal muscle. Starting at the somite stage, DMD dysregulations concerned almost 10% of the transcriptome. These include mitochondrial genes whose dysregulations escalate during differentiation. We also describe fibrosis as an intrinsic feature of DMD skeletal muscle cells that begins early during myogenesis. All the omics data are available online for exploration through a graphical interface at https://muscle-dmd.omics.ovh/. Conclusions Our data argue for an early developmental manifestation of DMD whose onset is triggered before the entry into the skeletal muscle compartment, data leading to a necessary reconsideration of dystrophin roles during muscle development. This hiPSC model of skeletal muscle differentiation offers the possibility to explore these functions as well as find earlier DMD biomarkers and therapeutic targets

Biases in BCI experiments: Do we really need to balance stimulus properties across categories?

peer reviewedBrain Computer Interfaces (BCIs) consist of an interaction between humans and computers with a specific mean of communication, such as voice, gestures, or even brain signals that are usually recorded by an Electroencephalogram (EEG). To ensure an optimal interaction, the BCI algorithm typically involves the classification of the input signals into predefined task-specific categories. However, a recurrent problem is that the classifier can easily be biased by uncontrolled experimental conditions, namely covariates, that are unbalanced across the categories. This issue led to the current solution of forcing the balance of these covariates across the different categories which is time consuming and drastically decreases the dataset diversity. The purpose of this research is to evaluate the need for this forced balance in BCI experiments involving EEG data. A typical design of neural BCIs involves repeated experimental trials using visual stimuli to trigger the so-called Event-Related Potential (ERP). The classifier is expected to learn spatio-temporal patterns specific to categories rather than patterns related to uncontrolled stimulus properties, such as psycho-linguistic variables (e.g., phoneme number, familiarity, and age of acquisition) and image properties (e.g., contrast, compactness, and homogeneity). The challenges are then to know how biased the decision is, which features affect the classification the most, which part of the signal is impacted, and what is the probability to perform neural categorization per se. To address these problems, this research has two main objectives: (1) modeling and quantifying the covariate effects to identify spatio-temporal regions of the EEG allowing maximal classification performance while minimizing the biasing effect, and (2) evaluating the need to balance the covariates across categories when studying brain mechanisms. To solve the modeling problem, we propose using a linear parametric analysis applied to some observable and commonly studied covariates to them. The biasing effect is quantified by comparing the regions highly influenced by the covariates with the regions of high categorical contrast, i.e., parts of the ERP allowing a reliable classification. The need to balance the stimulus's inner properties across categories is evaluated by assessing the separability between category-related and covariate-related evoked responses. The procedure is applied to a visual priming experiment where the images represent items belonging to living or non-living entities. The observed covariates are the commonly controlled psycho-linguistic variables and some visual features of the images. As a result, we identified that the category of the stimulus mostly affects the late evoked response. The covariates, when not modeled, have a biasing effect on the classification, essentially in the early evoked response. This effect increases with the diversity of the dataset and the complexity of the algorithm used. As the effects of both psycho-linguistic variables and image features appear outside of the spatio-temporal regions of significant categorical contrast, the proper selection of the region of interest makes the classification reliable. Having proved that the covariate effects can be separated from the categorical effect, our framework can be further used to isolate the category-dependent evoked response from the rest of the EEG to study neural processes involved when seeing living vs. non-living entities

Le FORUM, Vol. 33 No. 1

https://digitalcommons.library.umaine.edu/francoamericain_forum/1022/thumbnail.jp

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Evaluation of rotavirus vaccination program effectiveness in young children living in Eastern Townships

Résumé: Introduction : Le rotavirus est la principale cause de gastro-entérite aiguë (GEA) chez les tout-petits à travers le monde. En 2011, le vaccin antirotavirus monovalent (RV1) a été introduit dans le programme de vaccination universel du Québec afin de réduire la morbidité reliée à la gastro-entérite à rotavirus (GERV). Ce mémoire avait pour objectif de décrire les taux d’hospitalisation pour GEA et GERV avant et après l’implantation du programme chez les jeunes enfants estriens (étude d’impact) ainsi que la couverture vaccinale et d’évaluer l’efficacité vaccinale (EV) du RV1 (étude d’efficacité). Méthode : Le jumelage d’une banque de données hospitalières avec le registre régional de vaccination a permis d’extraire une cohorte d’enfants nés au Centre hospitalier universitaire de Sherbrooke (CHUS), vivant en Estrie et âgés de moins de cinq ans durant la période d’étude de juin 2004 à mai 2014 (n = 37 757). Cette cohorte a été suivie de façon rétrospective afin d’examiner les taux annuels d’hospitalisation pour GEA et GERV des années pré- (2004/2005-2010/2011) et post-implantation (2011/2012-2013/2014), globalement et selon diverses caractéristiques socioéconomiques. De plus, l’EV du RV1 a été calculée à l’aide de trois cohortes d’enfants : (1) les enfants vaccinés nés en 2011-2013 (n = 5 033), (2) les enfants non vaccinés nés en 2011-2013 (n = 1 239) et (3) les enfants non vaccinés nés en 2008-2010 (n = 6 436). Résultats : Le taux d’hospitalisation pour GEA a évolué de 81/10 000 enfants de moins de cinq ans en période pré-implantation à 46/10 000 en période post-implantation (réduction relative = 43 %, p < 0,001). Suite à l’implantation du programme, la couverture vaccinale a rapidement augmenté pour atteindre 81 %. Malgré une couverture vaccinale similaire parmi les différents groupes, les plus faibles réductions relatives ont été observées chez les groupes défavorisés. L’EV ajustée pour une série complète était de 62 % (intervalle de confiance [IC] 95 % : 37-77 %) et de 94 % (IC 95 % : 52-99 %) contre les hospitalisations pour GEA et GERV, respectivement. Les enfants vivant dans des quartiers ayant une proportion élevée de familles à faible revenu avaient une EV plus faible contre les hospitalisations pour GEA (30 % contre 78 %, p = 0,027). Conclusion : Trois ans après son introduction dans le programme universel, le RV1 a réduit de façon significative les gastro-entérites sévères chez les jeunes enfants estriens. Ce vaccin est très efficace pour prévenir les hospitalisations pour GERV, particulièrement chez les groupes plus aisés. D’autres études en contexte similaire sont nécessaires pour déterminer les facteurs reliés à une plus faible EV chez les groupes vulnérables.Abstract: Introduction: Rotavirus is the main cause of acute gastroenteritis (AGE) among young children worldwide. In 2011, the monovalent rotavirus vaccine (RV1) was introduced into the Quebec universal immunization program to reduce morbidity related to rotavirus gastroenteritis (RVGE). This thesis aimed to examine AGE and RVGE hospitalization rates before and after implementation of the program in young children from the Eastern Townships (impact study) and the vaccine coverage, and to assess vaccine effectiveness (VE) of the RV1 (effectiveness study). Methods: The pairing of a tertiary hospital database with the regional immunization registry allowed to extract a cohort of children born at the Centre hospitalier universitaire de Sherbrooke (CHUS), living in Eastern Townships and aged less than five years during the study period from June 2004 to May 2014 (n= 37,757). This cohort was retrospectively followed-up to examine AGE and RVGE annual hospitalization rates of pre- (2004/2005-2010/2011) and post-program years (2011/2012-2013/2014), globally and according to several socioeconomic characteristics. Moreover, RV1 VE was calculated using three children cohorts: (1) vaccinated children born in 2011-2013 (n=5,033), (2) unvaccinated children born in 2011-2013 (n=1,239), and (3) unvaccinated children born in 2008-2010 (n=6,436). Results: AGE hospitalization rates evolved from 81/10,000 children aged less than five years in pre-program period to 46/10,000 in post-program period (relative reduction=43%, p<0.001). Following implementation of the program, vaccine coverage rapidly increased to reach 81%. Despite similar vaccine coverage among different groups, lowest relative reductions were observed in disadvantaged groups. Adjusted VE of a complete series was 62% (95% confidence interval [CI]: 37%-77%) and 94% (95% CI: 52%-99%) against AGE and RVGE hospitalizations, respectively. Children living in neighbourhoods with higher rates of low-income families had lower VE against AGE hospitalizations (30% vs. 78%, p=0.027). Conclusion: Three years following its introduction into the universal vaccination program, RV1 significantly reduced severe gastroenteritis in young children in the Eastern Townships. This vaccine was highly effective to prevent RVGE hospitalizations, particularly among the most well-off. Further studies in similar setting are needed to determine factors related to lower VE among vulnerable groups