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

Task based model for récit generation from sensor data: an early experiment

International audienceAutomatic story generation is the object of a growing research effort in Computing Sciences. However, in this domain, stories are generally produced from fictional data. In this paper, we present the general approach for automatic story generation from real data focusing on the narrative planning. The aim is to generate récit from sensor observations of skiers going for a ski sortie. The modelling of the récit as well as some preliminary experiments are introduced and suggest the interest of the approach

Self-assembled monolayers of bisphosphonates: Influence of side chain steric hindrance

Bisphosphonates form self-assembled monolayers (SAMs) spontaneously on stainless steel, silicon, and titanium oxidized surfaces. We used contact angle measurements, atomic force microscopy, and X-ray reflectivity analysis to study the formation of SAMs on a model surface of ultraflat titanium (rms=0.2 nm). The results were extended to standard materials (mechanically polished titanium, stainless steel, and silicon) and showed that water-soluble bisphosphonic perfluoropolyether can easily form SAMs, with 100% surface coverage and a layer thickness of less than 3 nm. Hydrophobic (water contact angle >110° on stainless steel or titanium) and lipophobic (methylene iodide contact angle >105° on titanium) properties are discussed in terms of industrial applications

Collision induced spatial organization of microtubules

The dynamic behavior of microtubules in solution can be strongly modified by interactions with walls or other structures. We examine here a microtubule growth model where the increase in size of the plus-end is perturbed by collisions with other microtubules. We show that such a simple mechanism of constrained growth can induce ordered structures and patterns from an initially isotropic and homogeneous suspension. First, microtubules self-organize locally in randomly oriented domains that grow and compete with each other. By imposing even a weak orientation bias, external forces like gravity or cellular boundaries may bias the domain distribution eventually leading to a macroscopic sample orientation.Comment: Submitted to Biophysical Journa

A first principle (3+1) dimensional model for microtubule polymerization

In this paper we propose a microscopic model to study the polymerization of microtubules (MTs). Starting from fundamental reactions during MT's assembly and disassembly processes, we systematically derive a nonlinear system of equations that determines the dynamics of microtubules in 3D. %coexistence with tubulin dimers in a solution. We found that the dynamics of a MT is mathematically expressed via a cubic-quintic nonlinear Schrodinger (NLS) equation. Interestingly, the generic 3D solution of the NLS equation exhibits linear growing and shortening in time as well as temporal fluctuations about a mean value which are qualitatively similar to the dynamic instability of MTs observed experimentally. By solving equations numerically, we have found spatio-temporal patterns consistent with experimental observations.Comment: 12 pages, 2 figures. Accepted in Physics Letters

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

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

Spatial distribution of cerebral white matter lesions predicts progression to mild cognitive impairment and dementia

CONTEXT White matter lesions (WML) increase the risk of dementia. The relevance of WML location is less clear. We sought to determine whether a particular WML profile, based on the density and location of lesions, could be associated with an increased risk of mild cognitive impairment (MCI) or dementia over the following 7 years. METHODS In 426 healthy subjects from a cohort of community-dwelling people aged 65 years and over (ESPRIT Project), standardized cognitive and neurological evaluations were repeated after 2, 4 and 7 years. Patterns of WML were computed with a supervised data mining approach (decision trees) using the regional WML volumes (frontal, parietal, temporal, and occipital regions) and the total WML volume estimated at baseline. Cox proportional hazard models were then constructed to study the association between WML patterns and risk of MCI/dementia. RESULTS Total WML volume and percentage of WML in the temporal region proved to be the best predictors of progression to MCI and dementia. Specifically, severe total WML load with a high proportion of lesions in the temporal region was significantly associated with the risk of developing MCI or dementia. CONCLUSIONS Above a certain threshold of damage, a pattern of WML clustering in the temporal region identifies individuals at increased risk of MCI or dementia. As this WML pattern is observed before the onset of clinical symptoms, it may facilitate the detection of patients at risk of MCI/dementia.The ESPRIT Project is financed by the regional government of Languedoc-Roussillon (http://www.laregion.fr), the Agence Nationale de la Recherche (ANR: http://www.agence-nationale-recherche.fr) and an unconditional grant from Novartis (http://www.novartis.fr). This study is also supported by France Alzheimer (http://www.francealzheimer.org/)

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

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