429 research outputs found
Purification from human plasma of a tetrapeptide that potentiates insulin-like growth factor-I activity in chick embryo cartilage
AbstractHuman plasma has been shown to contain a low molecular weight factor that potentiates human IGF-I stimulation of glycosaminoglycan synthesis in chick embryo cartilage. The peptide was purified and characterized by Edman degradation and electrospray mass spectrometry. The primary structure determined was: Trp-Gly-His-Glu. A homologous synthetic peptide similarly promoted matrix biosynthesis in cartilage exposed to IGF-1
In silico evaluation of ultrafiltration and nanofiltration membrane cascades for continuous fractionation of protein hydrolysate from tuna processing byproduct
The present work proposes the design of cascades that integrate ultrafiltration (UF) and nanofiltration (NF) membranes to separate the different protein fractions from the protein hydrolysate obtained after hydrolysis of tuna byproducts. Experimental data (permeate flux and rejection of protein fractions under different applied pressures) previously obtained and published by this research group were fitted to empirical models, which were the basis for a process simulation model. High recovery rates (0.9) in the UF stages implied high process yields by reduced desired fraction losses, while similar recovery rates in the NF stages were required for high product purity. However, the applied pressures were not so influential over the performance of the system. Optimization problems were solved to identify the optimal design and operation conditions to maximize the product purity or the process yield. Maximal purity of the preferred 1-4 kDa fraction (49.3% from 19.0% in feed stream) obtained by the configuration with 3 UF stages and another 3 NF stages implied 2 and 5 bar pressures applied in the UF and NF stages, respectively, while 0.9 was the optimal recovery rate value for all the stages. These maximal purity conditions resulted in 62.6% process yield, defined as the percentage of the 1-4 kDa fraction in the feed stream recovered in the product stream. In addition, multiobjective optimization of the process was also carried out to obtain the Pareto graphs that represent the counterbalance between maximal yields and purities
Parody of political correctness or allegory of “Immaterial Labour”? A second look at Francis Veber’s Le Placard (2001)
This article questions whether readings of Francis Veber’s Le Placard (2001) as simply a parody of political correctness have tended to overlook the allegorical significance of its depiction of a middle-aged executive forced to pretend to be gay, simulating libidinal investments he does not in fact possess, in order to protect his job. It argues that the film merits re-interpretation as being not only a parody of political correctness but also a powerful allegory for the increasing demands placed on employees to invest their most personal affects and aptitudes in their work. Drawing on the work of Yann Moulier Boutang, the article interprets such demands as symptomatic of a regime of ‘cognitive capitalism’, in which ‘immaterial’ forms of labour represent the primary source of surplus value. The article thus offers an alternative reading of the film’s treatment of questions of work, gender, sexuality, family, and nation, before situating Le Placard in the context of a broader range of recent French filmic representations of the contemporary workplace
Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows
Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013
Quantifier l'effet de choix du site dans l'incertitude des jaugeages ADCP par transects
HMEM, Durham, New Hampshire, USA, 09-/07/2017 - 12/07/2017International audienceStage-discharge rating curves are used to relate streamflow discharge to continuously measured river stage readings to create a continuous record of streamflow discharge. The stage-discharge relationship is estimated and refined using discrete streamflow measurements over time, during which both the discharge and stage are measured. There is uncertainty in the resulting rating curve due to multiple factors including the curve-fitting process, assumptions on the form of the model used, fluvial geomorphology of natural channels, and the approaches used to extrapolate the rating equation beyond available observations. This rating curve uncertainty leads to uncertainty in the streamflow timeseries, and therefore to uncertainty in predictive models that use the streamflow data. Many different methods have been proposed in the literature for estimating rating curve uncertainty, differing in mathematical rigor, in the assumptions made about the component errors, and in the information required to implement the method at any given site. This study describes the results of an international experiment to test and compare streamflow uncertainty estimation methods from 7 research groups across 9 institutions. The methods range from simple LOWESS fits to more complicated Bayesian methods that consider hydraulic principles directly. We evaluate these different methods when applied to three diverse gauging stations using standardized information (channel characteristics, hydrographs, and streamflow measurements). Our results quantify the resultant spread of the stage-discharge Quantifying the uncertainty of discharge measurements (or "gaugings") is a challenge in the hydrometric community. A useful tool to empirically estimate the uncertainty of a gauging method is the field inter-laboratory experiment (Le Coz et al., 2016). Previous inter-laboratory experiments conducted in France (in 2009, 2010, 2011 and 2012) showed that the expanded uncertainty (with a probability level of 95%) of an ADCP gauging made of six successive transects is typically around 5% under optimum site conditions (straight reach, uniform and smooth streambed cross-section, homogeneous flow, etc.) and may be twice higher under poorer site conditions. In practice, the selected cross-section does not always match all quality requirements which may result in larger uncertainty. However, the uncertainty due to site selection is very difficult to estimate with predictive equations. From 9 to 10 November 2016, 50 teams from 8 different countries, using 50 ADCPs simultaneously, conducted more than 600 discharge measurements in steady flow conditions (~14 m3/s released by a dam). 26 cross-sections with various shapes and flow conditions were distributed over 500 meters along the Taurion River at Saint-Priest-de-Taurion, France. A specific experiment protocol, which consisted of circulating every team over half of the cross-sections, was implemented in order to quantify the impact of site selection on the discharge measurement uncertainty. Beyond the description of the experiments, uncertainty estimates are presented. The overall expanded uncertainty of a 6-transect ADCP gaugings (duration around 720 seconds) is estimated to be around 6%.The uncertainty of the discharge measurements varies among the cross-sections. These variations are well correlated to the expert judgment on the cross-section quality made by each team. First results seem to highlight a relation between uncertainty computed for each cross-section and criteria such as flow shallowness and measured discharge ratio. Further investigations are necessary to identify the criteria related to error sources that are possibly meaningful for categorizing measurement conditions and site selection. Moreover, experimental uncertainty and the uncertainty predicted by analytical methods such as QRev, QUant, OURSIN, RiverFlowUA or QMSys software will be compared
Cognitive and memory training in adults at risk of dementia: A Systematic Review
<p>Abstract</p> <p>Background</p> <p>Effective non-pharmacological cognitive interventions to prevent Alzheimer's dementia or slow its progression are an urgent international priority. The aim of this review was to evaluate cognitive training trials in individuals with mild cognitive impairment (MCI), and evaluate the efficacy of training in memory strategies or cognitive exercises to determine if cognitive training could benefit individuals at risk of developing dementia.</p> <p>Methods</p> <p>A systematic review of eligible trials was undertaken, followed by effect size analysis. Cognitive training was differentiated from other cognitive interventions not meeting generally accepted definitions, and included both cognitive exercises and memory strategies.</p> <p>Results</p> <p>Ten studies enrolling a total of 305 subjects met criteria for cognitive training in MCI. Only five of the studies were randomized controlled trials. Meta-analysis was not considered appropriate due to the heterogeneity of interventions. Moderate effects on memory outcomes were identified in seven trials. Cognitive exercises (relative effect sizes ranged from .10 to 1.21) may lead to greater benefits than memory strategies (.88 to -1.18) on memory.</p> <p>Conclusions</p> <p>Previous conclusions of a lack of efficacy for cognitive training in MCI may have been influenced by not clearly defining the intervention. Our systematic review found that cognitive exercises can produce moderate-to-large beneficial effects on memory-related outcomes. However, the number of high quality RCTs remains low, and so further trials must be a priority. Several suggestions for the better design of cognitive training trials are provided.</p
Salamander Hox clusters contain repetitive DNA and expanded non-coding regions: a typical Hoxstructure for non-mammalian tetrapod vertebrates?
Evidence of a relation between hippocampal volume, white matter hyperintensities, and cognition in subjective cognitive decline and mild cognitive impairment
Abtract
Objective:
The concepts of mild cognitive impairment (MCI) and subjective cognitive decline (SCD) have been proposed to identify individuals in the early stages of Alzheimer's disease (AD), or other neurodegenerative diseases. One approach to validate these concepts is to investigate the relationship between pathological brain markers and cognition in those individuals.
Method:
We included 126 participants from the Consortium for the Early Identification of Alzheimer's disease-Quebec (CIMA-Q) cohort (67 SCD, 29 MCI, and 30 cognitively healthy controls [CH]). All participants underwent a complete cognitive assessment and structural magnetic resonance imaging. Group comparisons were done using cognitive data, and then correlated with hippocampal volumes and white matter hyperintensities (WMHs).
Results:
Significant differences were found between participants with MCI and CH on episodic and executive tasks, but no differences were found when comparing SCD and CH. Scores on episodic memory tests correlated with hippocampal volumes in both MCI and SCD, whereas performance on executive tests correlated with WMH in all of our groups.
Discussion:
As expected, the SCD group was shown to be cognitively healthy on tasks where MCI participants showed impairment. However, SCD's hippocampal volume related to episodic memory performances, and WMH to executive functions. Thus, SCD represents a valid research concept and should be used, alongside MCI, to better understand the preclinical/ prodromal phase of AD
Tramadol vs dexmedetomidine for emergence agitation control in pediatric patients undergoing adenotonsillectomy with sevoflurane anesthesia: prospective randomized controlled clinical study
Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a feature selection ensemble combining stability and predictability
Background
Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are challenge to machine learning when learning prognostic models. In this context, it is paramount to pursue approaches that effectively seek for reduced sets of relevant features. Subsets of NPTs from which prognostic models can be learnt should not only be good predictors, but also stable, promoting generalizable and explainable models.
Methods
We propose a feature selection (FS) ensemble combining stability and predictability to choose the most relevant NPTs for prognostic prediction in AD. First, we combine the outcome of multiple (filter and embedded) FS methods. Then, we use a wrapper-based approach optimizing both stability and predictability to compute the number of selected features. We use two large prospective studies (ADNI and the Portuguese Cognitive Complaints Cohort, CCC) to evaluate the approach and assess the predictive value of a large number of NPTs. Results
The best subsets of features include approximately 30 and 20 (from the original 79 and 40) features, for ADNI and CCC data, respectively, yielding stability above 0.89 and 0.95, and AUC above 0.87 and 0.82. Most NPTs learnt using the proposed feature selection ensemble have been identified in the literature as strong predictors of conversion from MCI to AD.
Conclusions
The FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task.PTDC/EEI-SII/1937/2014; SFRH/BD/95846/2013; SFRH/BD/118872/2016info:eu-repo/semantics/publishedVersio
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