Studies on Honey Bee (Apis mellifera L.) Behavior: Preferences for Ethanol Solutions and Sub-lethal Effects Of Two Insect Growth Regulators

The two studies represented in this manuscript make the following attempts: 1) to further the development of a honey bee ethanol model for human alcoholism research by way of harnessed and free-flying assays; 2) to investigate the effects of insecticides considered harmless to honey bees on their ability to learn, using classical conditioning of the proboscis extension reflex as a learning paradigm. The ethanol study determined that honey bees do not have an aversion to ethanol at 1% and 5% concentrations, do not show a preference of alcohol or sucrose in 1% ethanol trials, but do show a slight preference to sucrose in 5% ethanol trials. The insecticide study indicated that both diflubenzuron and tebufenozide influence learning, but the greatest effect was observed when diflubenzuron was administered in small amounts throughout the training session.Department of Entomology and Plant Patholog

Comment mesurer la précarité énergétique en matière de transport

National audienceSi des indicateurs existent pour quantifier la précarité énergétique dans le logement, leur simple transposition au domaine du transport n’est pas satisfaisante. Afin de mieux identifier les ménages vulnérables à une hausse des prix des carburants, un « indicateur Composite » est proposé. Il permet de mieux refléter les différents facteurs qui contraignent la mobilité des ménages et leurs possibilités d’adaptation

Investigating fuel poverty in the transport sector: toward a composite indicator of vulnerability

International audienceThis paper investigates the issue of fuel poverty and of its measurement in the transport sector. We seek to identify households who run the risk of facing difficulties if fuel prices increase. We show that fuel poverty indicators from the domestic sector are not satisfactory in this regard. They fail to take into account three specificities of the transport sector: (1) the diversity of travel needs, (2) restriction behaviours, and (3) variable capacities to adapt. We propose a composite indicator that targets factors of vulnerabilities. In contrast to the previous indicators, it does not solely focus on budgetary aspects but also reflects conditions of mobility. Three levels of exposition to rising fuel prices are considered, depending on the combinations of factors. We test this indicator on French data and find that 7,8% of French households are identified fuel poor, a further 7,4% fuel vulnerable and a further 3,7% fuel dependent

Intracellular Ca 2+ Dynamics in Astrocytes: Modeling the Underlying Spatiotemporal Diversity

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Stochastic Spatially-Extended Simulations Predict the Effect of ER Distribution on Astrocytic Microdomain Ca²⁺ Activity

Astrocytes are cells of the central nervous system that can regulate neuronal activity. Most astrocyte-neuron communication occurs at so-called tripartite synapses, where calcium signals are triggered in astrocytes by neuronal activity, resulting in the release of neuroactive molecules by the astrocyte. Most astrocytic Ca²⁺ signals occur in very thin astrocytic branchlets, containing low copy number of molecules, so that reactions are highly stochastic. As those sub-cellular compartments cannot be resolved by diffraction-limited microscopy techniques, stochastic reaction-diffusion computational approaches can give crucial insights on astrocyte activity. Here, we use our stochastic voxel-based model of IP3R-mediated Ca²⁺ signals to investigate the effect of the distance between the synapse and the closest astrocytic endoplasmic reticulum (ER) on neuronal activity-induced Ca²⁺ signals. Simulations are performed in three dimensional meshes characterized by various ER-synapse distances. Our results suggest that Ca2+ peak amplitude, duration and frequency decrease rapidly as ER-synapse distance increases. We propose that this effect mostly results from the increased cytosolic volume of branchlets that are characterized by larger ER-synapse distances. In particular, varying ER-synapse distance with constant cytosolic volume does not affect local Ca²⁺ activity. This study illustrates the insights that can be provided by three-dimensional stochastic reaction-diffusion simulations on the biophysical constraints that shape the spatio-temporal characteristics of astrocyte activity at the nanoscale

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows

Rapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60\u2005min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n\u2005=\u2005713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000\u2005cm 121 were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60\u2005min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60\u2005min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation

Control of Ca2+ signals by astrocyte nanoscale morphology at tripartite synapses

International audienceMuch of the Ca2+ activity in astrocytes is spatially restricted to microdomains and occurs in fine processes that form a complex anatomical meshwork, the so-called spongiform domain. A growing body of literature indicates that those astrocytic Ca2+ signals can influence the activity of neuronal synapses and thus tune the flow of information through neuronal circuits. Because of technical difficulties in accessing the small spatial scale involved, the role of astrocyte morphology on Ca2+ microdomain activity remains poorly understood. Here, we use computational tools and idealized 3D geometries of fine processes based on recent super-resolution microscopy data to investigate the mechanistic link between astrocytic nanoscale morphology and local Ca2+ activity. Simulations demonstrate that the nano-morphology of astrocytic processes powerfully shapes the spatio-temporal properties of Ca2+ signals and promotes local Ca2+ activity. The model predicts that this effect is attenuated upon astrocytic swelling, hallmark of brain diseases, which we confirm experimentally in hypo-osmotic conditions. Upon repeated neurotransmitter release events, the model predicts that swelling hinders astrocytic signal propagation. Overall, this study highlights the influence of the complex morphology of astrocytes at the nanoscale and its remodeling in pathological conditions on neuron-astrocyte communication at so-called tripartite synapses, where astrocytic processes come into close contact with pre- and postsynaptic structures

Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics

The aim of this study was to evaluate the effectiveness of mid-infrared spectroscopy in predicting milk protein and free amino acid (FAA) composition in bovine milk. Milk samples were collected from 7 Irish research herds and represented cows from a range of breeds, parities, and stages of lactation. Mid-infrared spectral data in the range of 900 to 5,000 cm(-1) were available for 730 milk samples; gold standard methods were used to quantify individual protein fractions and FAA of these samples with a view to predicting these gold standard protein fractions and FAA levels with available mid-infrared spectroscopy data. Separate prediction equations were developed for each trait using partial least squares regression; accuracy of prediction was assessed using both cross validation on a calibration data set (n = 400 to 591 samples) and external validation on an independent data set (n = 143 to 294 samples). The accuracy of prediction in external validation was the same irrespective of whether undertaken on the entire external validation data set or just within the Holstein-Friesian breed. The strongest coefficient of correlation obtained for protein fractions in external validation was 0.74, 0.69, and 0.67 for total casein, total beta-lactoglobulin, and beta-casein, respectively. Total proteins (i.e., total casein, total whey, and total lactoglobulin) were predicted with greater accuracy then their respective component traits; prediction accuracy using the infrared spectrum was superior to prediction using just milk protein concentration. Weak to moderate prediction accuracies were observed for FAA. The greatest coefficient of correlation in both cross validation and external validation was for Gly (0.75), indicating a moderate accuracy of prediction. Overall, the FAA prediction models overpredicted the gold standard values. Near-unity correlations existed between total casein and beta-casein irrespective of whether the traits were based on the gold standard (0.92) or mid-infrared spectroscopy predictions (0.95). Weaker correlations among FAA were observed than the correlations among the protein fractions. Pearson correlations between gold standard protein fractions and the milk processing characteristics of rennet coagulation time, curd firming time, curd firmness, heat coagulating time, pH, and casein micelle size were weak to moderate and ranged from -0.48 (protein and pH) to 0.50 (total casein and a(30)). Pearson correlations between gold standard FAA and these milk processing characteristics were also weak to moderate and ranged from -0.60 (Val and pH) to 0.49 (Val and K-20). Results from this study indicate that mid-infrared spectroscopy has the potential to predict protein fractions and some FAA in milk at a population level

Control of Ca²⁺ signals by astrocyte nanoscale morphology at tripartite synapses

Much of the Ca²⁺ activity in astrocytes is spatially restricted to microdomains and occurs in fine processes that form a complex anatomical meshwork, the so-called spongiform domain. A growing body of literature indicates that those astrocytic Ca²⁺ signals can influence the activity of neuronal synapses and thus tune the flow of information through neuronal circuits. Because of technical difficulties in accessing the small spatial scale involved, the role of astrocyte morphology on Ca²⁺ microdomain activity remains poorly understood. Here, we use computational tools and idealized 3D geometries of fine processes based on recent super-resolution microscopy data to investigate the mechanistic link between astrocytic nanoscale morphology and local Ca²⁺ activity. Simulations demonstrate that the nano-morphology of astrocytic processes powerfully shapes the spatio-temporal properties of Ca²⁺ signals and promotes local Ca²⁺ activity. The model predicts that this effect is attenuated upon astrocytic swelling, hallmark of brain diseases, which we confirm experimentally in hypo-osmotic conditions. Upon repeated neurotransmitter release events, the model predicts that swelling hinders astrocytic signal propagation. Overall, this study highlights the influence of the complex morphology of astrocytes at the nanoscale and its remodeling in pathological conditions on neuron-astrocyte communication at so-called tripartite synapses, where astrocytic processes come into close contact with pre- and postsynaptic structures

Simulation of Astrocytic Calcium Dynamics in Lattice Light Sheet Microscopy Images

International audienceAstrocytes regulate neuronal information processing through a variety of spatio-temporal calcium signals. Advances in calcium imaging started to reveal astrocytic activities, but the complexity of the recorded data strongly call for computational analysis tools. Their development is hindered by the lack of reliable annotations that are essential for their evaluation and for the design of learning-based methods. To overcome the labeling problem, we present a framework to simulate realistic astrocytic calcium signals in 3D+time lattice light sheet microscopy (LLSM) images by closely modeling calcium kinetics in real astrocytes