A coupled bulk-surface model for cell polarisation

Several cellular activities, such as directed cell migration, are coordinated by an intricate network of biochemical reactions which lead to a polarised state of the cell, in which cellular symmetry is broken, causing the cell to have a well defined front and back. Recent work on balancing biological complexity with mathematical tractability resulted in the proposal and formulation of a famous minimal model for cell polarisation, known as the wave pinning model. In this study, we present a three-dimensional generalisation of this mathematical framework through the maturing theory of coupled bulk-surface semilinear partial differential equations in which protein compartmentalisation becomes natural. We show how a local perturbation over the surface can trigger propagating reactions, eventually stopped in a stable profile by the interplay with the bulk component. We describe the behaviour of the model through asymptotic and local perturbation analysis, in which the role of the geometry is investigated. The bulk-surface finite element method is used to generate numerical simulations over simple and complex geometries, which confirm our analysis, showing pattern formation due to propagation and pinning dynamics. The generality of our mathematical and computational framework allows to study more complex biochemical reactions and biomechanical properties associated with cell polarisation in multi-dimensions

The CIRDO Corpus: Comprehensive Audio/Video Database of Domestic Falls of Elderly People

International audienceAmbient Assisted Living aims at enhancing the quality of life of older and disabled people at home thanks to Smart Homes. In particular, regarding elderly living alone at home, the detection of distress situation after a fall is very important to reassure this kind of population. However, many studies do not include tests in real settings, because data collection in this domain is very expensive and challenging and because of the few available data sets. The CIRDOcorpus is a dataset recorded in realistic conditions in DOMUS, a fully equipped Smart Home with microphones and home automation sensors, in which participants performed scenarios including real falls on a carpet and calls for help. These scenarios were elaborated thanks to a field study involving elderly persons. Experiments related in a first part to distress detection in real-time using audio and speech analysis and in a second part to fall detection using video analysis are presented. Results show the difficulty of the task. The database can be used as standardized database by researchers to evaluate and compare their systems for elderly person's assistance. Keywords: audio and video data set, multimodal corpus, natural language and multimodal interaction, Ambient Assisted Living (AAL), distress situation

Patient socioeconomic determinants for the choice of the cheapest molecule within a cluster: evidence from Belgian prescription data

Reference pricing is a common cost-sharing mechanism, with the financial penalty for the use of costly drugs shifted from the third-party payer to the patient. Unintended distributional consequences might arise, if the weakest socioeconomic groups face a relatively higher financial burden. This study analyzed for a sample of Belgian individual prescription data for 4 clusters of commonly used drugs (proton pump inhibitors, statins and two groups of antihypertensives [drugs acting on renin-angiotensin system and dihydropyridine derivatives]) whether the probability to receive the least expensive molecule within a cluster was linked to the socioeconomic status of the patient. Logistic regression models included individual demographic, working, chronic illness and financial status and small area education data for 906,543 prescriptions from 1,280 prescribing general practitioners and specialists. For the 4 clusters, results show that patients with lower socioeconomic status consistently use slightly more the least expensive drugs than other patients. Larger effects are observed for patients residing in a nursing home for the elderly, patients entitled to increased reimbursement of co-payments, unemployed, patients treated in a primary care center financed per capita (and not fee-for-service) and patients having a chronic illness. Also, patients residing in neighborhoods with low education status use more less expensive drugs. The findings of the study suggest that although equity considerations were not explicitly taken into account in the design of the reference price system, there is no real equity problem, as the costly drugs with supplement are not prescribed more often in patients from lower socioeconomic classes

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

Visualization of membrane loss during the shrinkage of giant vesicles under electropulsation

We study the effect of permeabilizing electric fields applied to two different types of giant unilamellar vesicles, the first formed from EggPC lipids and the second formed from DOPC lipids. Experiments on vesicles of both lipid types show a decrease in vesicle radius which is interpreted as being due to lipid loss during the permeabilization process. We show that the decrease in size can be qualitatively explained as a loss of lipid area which is proportional to the area of the vesicle which is permeabilized. Three possible mechanisms responsible for lipid loss were directly observed: pore formation, vesicle formation and tubule formation.Comment: Final published versio

Green Production of Anionic Surfactant Obtained from Pea Protein

A pea protein isolate was hydrolyzed by a double enzyme treatment method in order to obtain short peptide sequences used as raw materials to produce lipopeptides-based surfactants. Pea protein hydrolysates were prepared using the combination of Alcalase and Flavourzyme. The influence of the process variables was studied to optimize the proteolytic degradation to high degrees of hydrolysis. The average peptide chain lengths were obtained at 3–5 amino acid units after a hydrolysis of 30 min with the mixture of enzymes. Then, N-acylation in water, in presence of acid chloride (C12 and C16), carried out with a conversion rate of amine functions of 90%, allowed to obtain anionic surfactant mixtures (lipopeptides and sodium fatty acids). These two steps were performed in water, in continuous and did not generate any waste. This process was therefore in line with green chemistry principles. The surface activities (CMC, foaming and emulsifying properties) of these mixtures were also studied. These formulations obtained from natural renewable resources and the reactions done under environmental respect, could replace petrochemical based surfactants for some applications

Electrode surface treatment and electrochemical impedance spectroscopy study on carbon/carbon supercapacitors

Power improvement in supercapacitors is mainly related to lowering the internal impedance. The real part of the impedance at a given frequency is called ESR (equivalent series resistance). Several contributions are included in the ESR: the electrolyte resistance (including the separator), the active material resistance (with both ionic and electronic parts) and the active material/current collector interface resistance. The first two contributions have been intensively described and studied by many authors. The first part of this paper is focused on the use of surface treatments as a way to decrease the active material/current collector impedance. Al current collector foils have been treated following a two-step procedure: electrochemical etching and sol-gel coating by a highly-covering, conducting carbonaceous material. It aims to increase the Al foil/active material surface contact leading to lower resistance. In a second part, carbon-carbon supercapacitor impedance is discussed in term of complex capacitance and complex power from electrochemical impedance spectroscopy data. This representation permits extraction of a relaxation time constant that provides important information on supercapacitor behaviour. The influence of carbon nanotubes addition on electrochemical performance of carbon/carbon supercapacitors has also been studied by electrochemical impedance spectroscopy

Ultrahigh-power micrometre-sized supercapacitors based on onion-like carbon

Electrochemical capacitors, also called supercapacitors, store energy in two closely spaced layers with opposing charges, and are used to power hybrid electric vehicles, portable electronic equipment and other devices¹. By offering fast charging and discharging rates, and the ability to sustain millions of ²⁻⁵, electrochemical capacitors bridge the gap between batteries, which offer high energy densities but are slow, and conventional electrolytic capacitors, which are fast but have low energy densities. Here, we demonstrate microsupercapacitors with powers per volume that are comparable to electrolytic capacitors, capacitances that are four orders of magnitude higher, and energies per volume that are an order of magnitude higher. We also measured discharge rates of up to 200 V s⁻¹, which is three orders of magnitude higher than conventional supercapacitors. The microsupercapacitors are produced by the electrophoretic deposition of a several micrometre-thick layer of nanostructured carbon onions⁶‚⁷ with diameters of 6-7 nm. Integration of these nanoparticles in a microdevice with a high surface-to-volume ratio, without the use of organic binders and polymer separators, improves performance because of the ease with which ions can access the active material. Increasing the energy density and discharge rates of supercapacitors will enable them to compete with batteries and conventional electrolytic capacitors in a number of applications

Diffusion in low-dimensional lipid membranes

The diffusion behavior of biological components in cellular membranes is vital to the function of cells. By collapsing the complexity of planar 2D membranes down to one dimension, fundamental investigations of bimolecular behavior become possible in one dimension. Here we develop lipid nanolithography methods to produce membranes, under fluid, with widths as low as 6 nm but extending to microns in length. We find reduced lipid mobility, as the width is reduced below 50 nm, suggesting different lipid packing in the vicinity of boundaries. The insertion of a membrane protein, M2, into these systems, allowed characterization of protein diffusion using high-speed AFM to demonstrate the first membrane protein 1D random walk. These quasi-1D lipid bilayers are ideal for testing and understanding fundamental concepts about the roles of dimensionality and size on physical properties of membranes from energy transfer to lipid packing