In silico prediction of mosquito repellents for clothing application.

Use of protective clothing is a simple and efficient way to reduce the contacts with mosquitoes and consequently the probability of transmission of diseases spread by them. This mechanical barrier can be enhanced by the application of repellents. Unfortunately the number of available repellents is limited. As a result, there is a crucial need to find new active and safer molecules repelling mosquitoes. In this context, a structure-activity relationship (SAR) model was proposed for the design of repellents active on clothing. It was computed from a dataset of 2027 chemicals for which repellent activity on clothing was measured against Aedes aegypti. Molecules were described by means of 20 molecular descriptors encoding physicochemical properties, topological information and structural features. A three-layer perceptron was used as statistical tool. An accuracy of 87% was obtained for both the training and test sets. Most of the wrong predictions can be explained. Avenues for increasing the performances of the model have been proposed.

[Diabetes and frailty in the elderly. A prospective study of an outpatient population supported by general practitioners]. / Diabète et fragilité chez la personne âgée. Etude prospective d'une population ambulatoire prise en charge en Médecine générale.

INTRODUCTION: Elderly people with diabetes represent a large and growing part of the general practitioners patient database, but their state of frailty compared to the non-diabetic population is poorly understood. OBJECTIVE: To study the relationship between diabetes and frailty in people aged 65 and over in primary care. METHOD: Frailty syndrome was assessed by the Fried Scale and compared between populations of diabetic and non-diabetic patients; 268 patients were studied, including 129 diabetic patients. RESULTS: Frailty was found in 27.9 % of older diabetic patients. The observed mean Fried score was 1.76 in people with diabetes versus 1.39 in non-diabetics, with more frail diabetic subjects (p = 0.007). In this study, HbA1c levels showed no significant association to frailty. CONCLUSION: Larger studies in several general practice clinics should be performed on subjects over 65 years of age with or without diabetes.

INTRODUCTION: Les personnes âgées diabétiques représentent une part importante et croissante de la patientèle des médecins généralistes, mais leur état de fragilité par rapport à la population non diabétique est mal connu. Objectif : Etudier les relations entre diabète et fragilité chez la personne âgée de 65 ans et plus en médecine générale. Méthode : La fragilité a été évaluée par l'échelle de Fried et comparée entre les populations de patients diabétiques et non diabétiques; 268 patients ont été inclus dont 129 patients diabétiques. Résultats : La fragilité concernait 27,9 % des diabétiques. Le score de Fried moyen observé était de 1,76 chez les personnes diabétiques versus 1,39 chez les non-diabétiques, avec des sujets diabétiques plus fragiles (p = 0,007). Dans cette étude, le taux d'HbA1c n'est pas significativement associé à la fragilité. CONCLUSION: Des études de plus grande ampleur sur plusieurs sites ambulatoires devraient être réalisées en médecine générale chez les sujets âgés de plus de 65 ans, diabétiques ou non.

[Type 2 diabetes and the elderly : a real problem]. / Diabète de type 2 et le sujet âgé : une réelle problématique.

Type 2 diabetes in the elderly remains a major concern for all healthcare professionals, this disease being considered a real global «pandemic¼. Its prevalence is high and will continue to increase in the years to come, becoming significant in the elderly and the very old. We offer you a general summary and a focus on diabetes in the elderly with the GERODIAB study.

Le diabète de type 2 chez le sujet âgé reste une préoccupation majeure pour l'ensemble des professionnels de santé, cette maladie étant elle-même considérée comme une réelle «pandémie¼ mondiale. Sa prévalence est élevée et continuera de s'accroître dans les années à venir, devenant prégnante chez le sujet âgé et très âgé. Nous proposons ici une synthèse générale et un focus sur le diabète du sujet âgé avec l'étude GERODIAB.

Evolution in geriatric syndromes and association with survival over 5 years in the GERODIAB cohort of older French diabetic patients.

PURPOSE: Although one in three patients with diabetes in Western countries is over 70 years-old, geriatric syndromes and their relationship with survival remain seldom studied. The present aim of the GERODIAB study was to examine the evolution of geriatric disorders and their relationship with survival in older type 2 patients with diabetes with initial sufficient autonomy. METHODS: We performed a prospective, observational study over 5 years in patients with diabetes aged 70 years or above. A total of 987 consecutive type 2 patients with diabetes (mean age 77 years, range 70-94 years, 65.2% were 75 years and above, 52.1% women) were included from 56 French diabetic centres. Individual characteristics, diabetes parameters and geriatric parameters (autonomy, nutrition, cognitive alteration, depression, orthostatic hypotension, falls) were annually recorded. Survival was analysed using the Kaplan-Meier method and proportional hazards regression models. RESULTS: Institutional living, impaired activity and difficulties in instrumental daily activity, cognitive disorders, malnutrition, depression, orthostatic hypotension and hypoglycaemia strongly increased during the follow-up. Institutional living, impaired activity and difficulties in instrumental daily activity, cognitive disorders and hypoglycaemia were strongly associated with reduced survival, but not falls. In hazard ratio models, living in an institution (HR = 2.39; CI = 1.77-3.24; p < 0.0001) and impaired Activity of Daily Living scale score were the most significant and independent predictors of death (HR = 1.59; CI = 1.19-2.13; p = 0.0016), associated with HbA1c ≥ 70 mmol/mol (HR = 1.62; CI = 1.12-2.36; p = 0.011). CONCLUSION: Our findings show the considerable alteration of geriatric parameters and their relationship with decreased survival after a 5-year follow-up in type 2 patients with diabetes, independent of HbA1c and age. They, therefore, confirm the prognostic interest of using yearly geriatric markers in older diabetic patient management, especially the ADL, IADL and MMSE scales. Taking into account these prognostic parameters should contribute to target appropriate HbA1c goals. TRIAL REGISTRATION: Registered at clinicaltrials.gov (21/01/2011): NCT01282060.

Floristic evidence for alternative biome states in tropical Africa.

The idea that tropical forest and savanna are alternative states is crucial to how we manage these biomes and predict their future under global change. Large-scale empirical evidence for alternative stable states is limited, however, and comes mostly from the multimodal distribution of structural aspects of vegetation. These approaches have been criticized, as structure alone cannot separate out wetter savannas from drier forests for example, and there are also technical challenges to mapping vegetation structure in unbiased ways. Here, we develop an alternative approach to delimit the climatic envelope of the two biomes in Africa using tree species lists gathered for a large number of forest and savanna sites distributed across the continent. Our analyses confirm extensive climatic overlap of forest and savanna, supporting the alternative stable states hypothesis for Africa, and this result is corroborated by paleoecological evidence. Further, we find the two biomes to have highly divergent tree species compositions and to represent alternative compositional states. This allowed us to classify tree species as forest vs. savanna specialists, with some generalist species that span both biomes. In conjunction with georeferenced herbarium records, we mapped the forest and savanna distributions across Africa and quantified their environmental limits, which are primarily related to precipitation and seasonality, with a secondary contribution of fire. These results are important for the ongoing efforts to restore African ecosystems, which depend on accurate biome maps to set appropriate targets for the restored states but also provide empirical evidence for broad-scale bistability.

Topological QSAR Modelling of Carboxamides Repellent Activity to Aedes Aegypti.

Aedes aegypti vector control is of paramount importance owing to the damages induced by the various severe diseases that these insects may transmit, and the increasing risk of important outbreaks of these pathologies. Search for new chemicals efficient against Aedes aegypti, and devoid of side-effects, which have been associated to the currently most used active substance i. e. N,N-diethyl-m-toluamide (DEET), is therefore an important issue. In this context, we developed various Quantitative Structure Activity Relationship (QSAR) models to predict the repellent activity against Aedes aegypti of 43 carboxamides, by using Multiple Linear Regression (MLR) and various machine learning approaches. The easy computation of the four topological descriptors selected in this study, compared to the CODESSA descriptors used in the literature, and the predictive ability of the here proposed MLR and machine learning models developed using the software QSARINS and R, make the here proposed QSARs attractive. As demonstrated in this study, these models can be applied at the screening level, to guide the design of new alternatives to DEET.

Haemoglobin A1c and 5-year all-cause mortality in French type 2 diabetic patients aged 70 years and older: The GERODIAB observational cohort.

AIM: The role of glycaemic control in the mortality of elderly diabetic patients remains uncertain. GERODIAB is the first multi-centre, prospective, observational study that aims to describe the link between HbA1c and 5-year mortality in French, type 2 diabetic patients aged ≥70 years. METHODS: Consecutive patients (n=987; mean age 77 years) were included from 56 diabetes centres and followed for five years. Individual histories, risk factors, standard diabetes parameters and geriatric evaluations were regularly recorded. Survival was studied using the Kaplan-Meier method. Multivariable analyses used Cox regression. RESULTS: Twenty-one percent of the patients died, 13% were lost during follow-up. Patients with a 5-year mean HbA1c in the range [40-50) mmol/mol ([5.8-6.7) %) had the highest survival (84%); those in the range [50-70) mmol/mol ([6.7-8.6) %) or <40mmol/mol (<5.8%) an intermediary survival rate (79%); patients with HbA1c ≥70mmol/mol (≥8.6%) the worst survival (71%). Patients with mean HbA1c ≥70mmol/mol (≥8.6%) had a significantly higher mortality than those with lower HbA1c (P=0.011), and HbA1c remained a significant predictor of mortality after adjusting for individual, diabetic and geriatric factors (hazards ratio [95%CI]: 1.76 [1.21 to 2.57], P=0.0033). Survival was also significantly associated with both HbA1c variability and with the frequency of HbA1c determinations. CONCLUSION: In this large sample of elderly French type 2 diabetic patients, an HbA1c level <70mmol/mol (<8.6%) was associated with lower mortality. The range [40-50) mmol/mol ([5.8-6.7) %) could be an acceptable target provided patients are not exposed to hypoglycaemia.

[Statins in primary prevention of cardiovascular disease]. / Statines en prévention primaire des événements cardiovasculaires.

Cardiovascular events are the second leading cause of death in France. The assessment of overall cardiovascular risk using a personalized assessment with weighting risk factors can predict the risk of cardiovascular events in ten years. The validated treatments to reduce cardiovascular mortality in primary prevention are few. The use of statins in primary prevention is discussed. We report in this review the updated conclusions from clinical trials regarding the treatment with statins in primary prevention.

Tunable graded cavity resonator integrated grating filters.

We demonstrated Graded Cavity Resonator Integrated Grating Filters (G-CRIGFs) that are narrowband spectral reflectors, spectrally tunable over more than 40 nm around 850 nm using a spatial gradient. A simple analytical model is introduced and validated experimentally to determine spectral performance of G-CRIGFs from the spectral properties of a standard Cavity Resonator Integrated Grating Filter (CRIGF).

QSAR models for predicting the toxicity of piperidine derivatives against Aedes aegypti.

QSAR models are proposed for predicting the toxicity of 33 piperidine derivatives against Aedes aegypti. From 2D topological descriptors, calculated with the PaDEL software, ordinary least squares multilinear regression (OLS-MLR) treatment from the QSARINS software and machine learning and related approaches including linear and radial support vector machine (SVM), projection pursuit regression (PPR), radial basis function neural network (RBFNN), general regression neural network (GRNN) and k-nearest neighbours (k-NN), led to four-variable models. Their robustness and predictive ability were evaluated through both internal and external validation. Determination coefficients (r2) greater than 0.85 on the training sets and 0.8 on the test sets were obtained with OLS-MLR and linear SVM. They slightly outperform PPR, radial SVM and RBFNN, whereas GRNN and k-NN showed lower performance. The easy availability of the involved structural descriptors and the simplicity of the MLR model make the corresponding model attractive at an exploratory level for proposing, from this limited dataset, guidelines in the design of new potentially active molecules.

Relationship between achieved personalized glycaemic targets and monitoring of clinical events in elderly diabetic patients.

AIM: Recent guidelines for the management of type 2 diabetes (T2DM) in the elderly recommend adjusting the therapeutic target (HbA1c) according to the patient's health. Our study aimed to explore the association between achieving the recommended personalized HbA1c target and the occurrence of major clinical events under real-life conditions. METHODS: The T2DM S.AGES cohort was a prospective multicentre study into which 213 general practitioners recruited 983 non-institutionalized T2DM patients aged>65 years. The recommended personalized HbA1c targets were<7%, <8% and <9% for healthy, ill and very ill patients, respectively. Major clinical events (death from any cause, major vascular events and/or hospitalization) were recorded during the 3-year follow-up. Mixed-effects logistic regression models were used for the analyses. RESULTS: Of the 747 patients analyzed at baseline, 551 (76.8%) were at their recommended personalized HbA1c target. During follow-up, 391 patients (52.3%) experienced a major clinical event. Of the patients who did not achieve their personalized HbA1c target (compared with those who did), the risk (OR) of a major clinical event was 0.95 (95% CI: 0.69-1.31; P=0.76). The risk of death, major vascular event and hospitalization were 0.88 (95% CI: 0.40-1.94; P=0.75), 1.14 (95% CI: 0.7-1.83; P=0.59) and 0.84 (95% CI: 0.60-1.18; P=0.32), respectively. CONCLUSION: Over a 3-year follow-up period, our results showed no difference in risk of a major clinical event among patients, regardless of whether or not they achieved their personalized recommended HbA1c target. These results need to be confirmed before implementing a more permissive strategy for treating T2DM in elderly patients.

Importance of air bubbles in the core of coated pellets: Synchrotron X-ray microtomography allows for new insights.

High-resolution X-ray microtomography was used to get deeper insight into the underlying mass transport mechanisms controlling drug release from coated pellets. Sugar starter cores were layered with propranolol HCl and subsequently coated with Kollicoat SR, plasticized with 10% TEC. Importantly, synchrotron X-ray computed microtomography (SR-µCT) allowed direct, non-invasive monitoring of crack formation in the film coatings upon exposure to the release medium. Propranolol HCl, as well as very small sugar particles from the pellets' core, were expulsed through these cracks into the surrounding bulk fluid. Interestingly, SR-µCT also revealed the existence of numerous tiny, air-filled pores (varying in size and shape) in the pellet cores before exposure to the release medium. Upon water penetration into the system, the contents of the pellet cores became semi-solid/liquid. Consequently, the air-pockets became mobile and fused together. They steadily increased in size (and decreased in number). Importantly, "big" air bubbles were often located in close vicinity of a crack within the film coating. Thus, they play a potentially crucial role for the control of drug release from coated pellets.

Investigation of the influence of protein corona composition on gold nanoparticle bioactivity using machine learning approaches.

The understanding of the mechanisms and interactions that occur when nanomaterials enter biological systems is important to improve their future use. The adsorption of proteins from biological fluids in a physiological environment to form a corona on the surface of nanoparticles represents a key step that influences nanoparticle behaviour. In this study, the quantitative description of the composition of the protein corona was used to study the effect on cell association induced by 84 surface-modified gold nanoparticles of different sizes. Quantitative relationships between the protein corona and the activity of the gold nanoparticles were modelled by using several machine learning-based linear and non-linear approaches. Models based on a selection of only six serum proteins had robust and predictive results. The Projection Pursuit Regression method had the best performances (r(2) = 0.91; Q(2)loo = 0.81; r(2)ext = 0.79). The present study confirmed the utility of protein corona composition to predict the bioactivity of gold nanoparticles and identified the main proteins that act as promoters or inhibitors of cell association. In addition, the comparison of several techniques showed which strategies offer the best results in prediction and could be used to support new toxicological studies on gold-based nanomaterials.

Lactic acidosis: relationship between metformin levels, lactate concentration and mortality.

AIM: The role of metformin in lactic acidosis is regularly questioned. Arguments against a causal role for metformin in lactic acidosis occurrence are the lack of correlation between plasma metformin and lactate levels, as well as between metformin plasma levels and mortality. We aim to analyse these correlations in a large series of lactic acidosis cases recorded in the French nationwide pharmacovigilance database. METHODS: All cases of lactic acidosis spontaneously reported between 1985 and October 2013 associated with metformin exposure were extracted from the pharmacovigilance database. We assessed the statistical correlations between prescribed daily doses of metformin, plasma concentrations of metformin and lactate, pH and plasma creatinine, as well as the relationship between mortality and these variables. RESULTS: Seven hundred and twenty-seven cases of lactic acidosis were reported during the period. Metformin plasma concentration was documented for 260 patients, lactate plasma concentration for 556 patients, pH for 502 patients, creatinine for 397 patients and the vital outcome for 713 patients. Metformin plasma concentration, lactate concentration, pH and plasma creatinine were all correlated (P < 0.001). There were significant differences between surviving and deceased patients in terms of metformin plasma levels (25.2 vs. 37.4 mg/l, P = 0.002) and lactate concentrations (10.8 vs. 16.3 mmol/l, P < 0.001). Thirty per cent of patients died when metformin concentration was > 5 mg/l compared with 11% for patients with concentration < 5 mg/l (P = 0.003). CONCLUSIONS: Our data suggest that metformin accumulation contributes to the pathogenesis and prognosis of lactic acidosis.

Relationships between population density, fine-scale genetic structure, mating system and pollen dispersal in a timber tree from African rainforests.

Owing to the reduction of population density and/or the environmental changes it induces, selective logging could affect the demography, reproductive biology and evolutionary potential of forest trees. This is particularly relevant in tropical forests where natural population densities can be low and isolated trees may be subject to outcross pollen limitation and/or produce low-quality selfed seeds that exhibit inbreeding depression. Comparing reproductive biology processes and genetic diversity of populations at different densities can provide indirect evidence of the potential impacts of logging. Here, we analysed patterns of genetic diversity, mating system and gene flow in three Central African populations of the self-compatible legume timber species Erythrophleum suaveolens with contrasting densities (0.11, 0.68 and 1.72 adults per ha). The comparison of inbreeding levels among cohorts suggests that selfing is detrimental as inbred individuals are eliminated between seedling and adult stages. Levels of genetic diversity, selfing rates (∼16%) and patterns of spatial genetic structure (Sp ∼0.006) were similar in all three populations. However, the extent of gene dispersal differed markedly among populations: the average distance of pollen dispersal increased with decreasing density (from 200 m in the high-density population to 1000 m in the low-density one). Overall, our results suggest that the reproductive biology and genetic diversity of the species are not affected by current logging practices. However, further investigations need to be conducted in low-density populations to evaluate (1) whether pollen limitation may reduce seed production and (2) the regeneration potential of the species.

Thin-dielectric-layer engineering for 3D nanostructure integration using an innovative planarization approach.

Three-dimensional (3D) nanostructures are emerging as promising building blocks for a large spectrum of applications. One critical issue in integration regards mastering the thin, flat, and chemically stable insulating layer that must be implemented on the nanostructure network in order to build striking nano-architectures. In this letter, we report an innovative method for nanoscale planarization on 3D nanostructures by using hydrogen silesquioxane as a spin-on-glass (SOG) dielectric material. To decouple the thickness of the final layer from the height of the nanostructure, we propose to embed the nanowire network in the insulator layer by exploiting the planarizing properties of the SOG approach. To achieve the desired dielectric thickness, the structure is chemically etched back with a highly diluted solution to control the etch rate precisely. The roughness of the top surface was less than 2 nm. There were no surface defects and the planarity was excellent, even in the vicinity of the nanowires. This newly developed process was used to realize a multilevel stack architecture with sub-deca-nanometer-range layer thickness.

Linear and non-linear modelling of the cytotoxicity of TiO2 and ZnO nanoparticles by empirical descriptors.

Titanium oxide (TiO2) and zinc oxide (ZnO) nanoparticles are among the most widely used in different applications in daily life. In this study, local regression and classification models were developed for a set of ZnO and TiO2 nanoparticles tested at different concentrations for their ability to disrupt the lipid membrane in cells. Different regression techniques were applied and compared by checking the robustness of the models and their external predictive ability. Additionally, a simple classification model was developed, which predicts the potential for disruption of the studied nanoparticles with good accuracy (overall accuracy, specificity, and sensitivity >80%) on the basis of two empirical descriptors. The present study demonstrates that empirical descriptors, such as experimentally determined size and tested concentrations, are relevant to modelling the activity of nanoparticles. This information may be useful to screen the potential for harmful effect of nanoparticles in different experimental conditions and to optimize the design of toxicological tests. Results from the present study are useful to support and refine the future application of in silico tools to nanoparticles, for research and regulatory purposes.

Seeing Central African forests through their largest trees.

Large tropical trees and a few dominant species were recently identified as the main structuring elements of tropical forests. However, such result did not translate yet into quantitative approaches which are essential to understand, predict and monitor forest functions and composition over large, often poorly accessible territories. Here we show that the above-ground biomass (AGB) of the whole forest can be predicted from a few large trees and that the relationship is proved strikingly stable in 175 1-ha plots investigated across 8 sites spanning Central Africa. We designed a generic model predicting AGB with an error of 14% when based on only 5% of the stems, which points to universality in forest structural properties. For the first time in Africa, we identified some dominant species that disproportionally contribute to forest AGB with 1.5% of recorded species accounting for over 50% of the stock of AGB. Consequently, focusing on large trees and dominant species provides precise information on the whole forest stand. This offers new perspectives for understanding the functioning of tropical forests and opens new doors for the development of innovative monitoring strategies.

Structure-activity relationship (SAR) modelling of mosquito larvicides.

An attempt was made to derive structure-activity models allowing the prediction of the larvicidal activity of structurally diverse chemicals against mosquitoes. A database of 188 chemicals with their activity on Aedes aegypti larvae was constituted from analysis of original publications. The activity values were expressed in log 1/IC50 (concentration required to produce 50% inhibition of larval development, mmol). All the chemicals were encoded by means of CODESSA and autocorrelation descriptors. Partial least squares analysis, classification and regression tree, random forest and boosting regression tree analyses, Kohonen self-organizing maps, linear artificial neural networks, three-layer perceptrons, radial basis function artificial neural networks and support vector machines with linear, polynomial, radial basis function and sigmoid kernels were tested as statistical tools. Because quantitative models did not give good results, a two-class model was designed. The three-layer perceptron significantly outperformed the other statistical approaches regardless of the threshold value used to split the data into active and inactive compounds. The most interesting configuration included eight autocorrelation descriptors as input neurons and four neurons in the hidden layer. This led to more than 96% of good predictions on both the training set and external test set of 88 and 100 chemicals, respectively. From the overall simulation results, new candidate molecules were proposed which will be shortly synthesized and tested.