Pneumococcal septicemiae (Streptococcus pneumoniae) in the calves

Les auteurs décrivent un foyer de septicémie à pneumocoques ( Strepto coccus pneumoniae) chez des veaux en France. L’affection sévit chez des animaux très jeunes de 0 à 8 semaines jusqu’à 3 mois et est d’évolution très rapide (quelques heures) accompagnée d’entérite subaiguë, et de lésions pulmonaires diffuses. Cette maladie peut être confondue avec de la colibacillose ou de la salmonellose ; seuls les examens bactériologiques permettent le diagnostic. C’est une affection bien connue en Allemagne, Danemark, Suisse, présente aussi en Italie et en Angleterre. En France, la maladie existe mais l’évolution est telle que les différentes phases de son diagnostic sont difficiles. Le sérotype de Streptococcus pneumoniae trouvé dans cette étude est un 18, sérotype assez fréquent en médecine humaine.The authors describe an outbreak of pneumococcal septicemiae ( Strep tococcus pneumoniae ) in the calves in France. The disease take its course in very young animals of 0 to 8 weeks old up to 3 months. The evolution is very speedy (a few hours) with clinical signs of sub acute enteritis and diffuse pulmonary lesions ; this disease can be confused with collibacillosis and salmonellosis ; and the diagnosis can be made only by bacteriological examination. This affection is well known in Germany, Denmark and Switzerland, and exists in Italy and Great Britain. In France the disease exists but the evolution is such that the different phases of the different phases of the diagnosis are difficult. The serotye of Streptococcus pneumoniae isolated in this study is serotype 18 wich is rather frequent in human medicine

The humoral pattern recognition receptor PTX3 is stored in neutrophil granules and localizes in extracellular traps

The long pentraxin (PTX) 3 is produced by macrophages and myeloid dendritic cells in response to Toll-like receptor agonists and represents a nonredundant component of humoral innate immunity against selected pathogens. We report that, unexpectedly, PTX3 is stored in specific granules and undergoes release in response to microbial recognition and inflammatory signals. Released PTX3 can partially localize in neutrophil extracellular traps formed by extruded DNA. Eosinophils and basophils do not contain preformed PTX3. PTX3-deficient neutrophils have defective microbial recognition and phagocytosis, and PTX3 is nonredundant for neutrophil-mediated resistance against Aspergillus fumigatus. Thus, neutrophils serve as a reservoir, ready for rapid release, of the long PTX3, a key component of humoral innate immunity with opsonic activity

Element abundances in the stars of the MILES spectral library: the Mg/Fe ratio

We have obtained [Mg/Fe] measurements for 76.3 per cent of the stars in the Mid-resolution Isaac Newton Telescope Library of Empirical Spectra (MILES) spectral library used for understanding stellar atmospheres and stellar populations in galaxies and star clusters. These abundance ratios were obtained through (1) a compilation of values from the literature using abundances from high-resolution (HR) spectroscopic studies and (2) a robust spectroscopic analysis using the MILES mid-resolution (MR) optical spectra. All the [Mg/Fe] values were carefully calibrated to a single uniform scale, by using an extensive control sample with results from HR spectra. The small average uncertainties in the calibrated [Mg/Fe] values [respectively 0.09 and 0.12 dex with methods (1) and (2)] and the good coverage of the stars with [Mg/Fe] over stellar atmospheric parameter space of the library will permit the building of new simple stellar populations (SSPs) with empirical α-enhancements. These will be available for a range of [Mg/Fe], including both sub-solar and super-solar values, and for several metallicities and ages. These models will open up new prospects for testing and applications of evolutionary stellar population synthesis

Comprendre les comportements face à un risque modéré d’inondation. Etude de cas dans le périurbain toulousain (Sud-Ouest de la France)

Les espaces urbanisés soumis à des risques modérés d’inondation pour les vies humaines sont souvent peu considérés dans les études sur la vulnérabilité aux risques naturels en dépit des enjeux qu’ils représentent en termes de gestion de crise. Comment les riverains y font-ils face au danger et quelles sont leurs « bonnes raisons » d’agir? A partir de l’étude socio-géographique de deux inondations récentes (2000 et 2003) dans la périphérie toulousaine (Sud-Ouest de la France), nous montrons que les caractéristiques de l’aléa dans les vallées étudiées influencent les représentations du risque et par conséquent les motivations à se protéger. Face au risque majeur, la vulnérabilité sociale se trouve ainsi augmentée. Pour améliorer la résilience des populations, il convient d’adapter la communication sur les risques: personnaliser l’information, améliorer la compréhension de l’événement vécu et mobiliser de nouvelles formes de médiation entre gestionnaires et riverains

IL-34 and macrophage colony-stimulating factor are overexpressed in hepatitis C virus fibrosis and induce profibrotic macrophages that promote collagen synthesis by hepatic stellate cells

Chronic hepatitis C virus (HCV) infection is characterized by progressive hepatic fibrosis, a process dependent on monocyte recruitment and accumulation into the liver. The mediators expressed in chronically injured liver that control the differentiation of human monocytes into profibrotic macrophages (Mφ) remain poorly defined. We report that chronically HCV-infected patients with high fibrosis stages have higher serum levels of macrophage colony-stimulating factor (M-CSF) and interleukin (IL)−34 than HCV-infected patients with lower fibrosis stages and healthy subjects. Immunohistochemistry reveals an intense expression of IL-34 and M-CSF by hepatocytes around liver lesions. In addition, HCV infection and inflammatory cytokines enhance the in vitro production of IL-34 and M-CSF by hepatocytes. We next analyzed the acquisition of profibrotic properties by Mφ generated with M-CSF (M-CSF-Mφ) or IL-34 (IL-34-Mφ). M-CSF and IL-34 up-regulate the expression, by differentiating monocytes, of chemokine (C-C motif) ligand (CCL)2, CCL4, C-C chemokine receptor (CCR)1, and CCR5, which are involved in monocyte recruitment/Mφ accumulation in liver lesions. M-CSF-Mφ and IL-34-Mφ also express the hepatic stellate cell (HSC) activators, platelet-derived growth factor, transforming growth factor beta, and galectin-3. IL-34-Mφ and M-CSF-Mφ induce type I collagen synthesis by HSCs, the main collagen-producing cells in liver fibrosis. IL-13, whose expression correlates with the fibrosis stage in HCV-infected patients, decreases the expression of the collagenase, matrix metalloproteinase 1, by IL-34-Mφ and M-CSF-Mφ, thereby enhancing collagen synthesis. By inhibiting the production of interferon-gamma (IFN-γ) by activated natural killer cells, IL-34-Mφ and M-CSF-Mφ prevent the IFN-γ-induced killing of HSCs. Conclusion: These results identify M-CSF and IL-34 as potent profibrotic factors in HCV liver fibrosis

Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

Changes of synaptic connections between neurons are thought to be the physiological basis of learning. These changes can be gated by neuromodulators that encode the presence of reward. We study a family of reward-modulated synaptic learning rules for spiking neurons on a learning task in continuous space inspired by the Morris Water maze. The synaptic update rule modifies the release probability of synaptic transmission and depends on the timing of presynaptic spike arrival, postsynaptic action potentials, as well as the membrane potential of the postsynaptic neuron. The family of learning rules includes an optimal rule derived from policy gradient methods as well as reward modulated Hebbian learning. The synaptic update rule is implemented in a population of spiking neurons using a network architecture that combines feedforward input with lateral connections. Actions are represented by a population of hypothetical action cells with strong mexican-hat connectivity and are read out at theta frequency. We show that in this architecture, a standard policy gradient rule fails to solve the Morris watermaze task, whereas a variant with a Hebbian bias can learn the task within 20 trials, consistent with experiments. This result does not depend on implementation details such as the size of the neuronal populations. Our theoretical approach shows how learning new behaviors can be linked to reward-modulated plasticity at the level of single synapses and makes predictions about the voltage and spike-timing dependence of synaptic plasticity and the influence of neuromodulators such as dopamine. It is an important step towards connecting formal theories of reinforcement learning with neuronal and synaptic properties

An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning

An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD) learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards

Model-observations synergy in the coastal ocean

Integration of observations of the coastal ocean continuum, from regional oceans to shelf seas and estuaries/deltas with models, can substantially increase the value of observations and enable a wealth of applications. In particular, models can play a critical role at connecting sparse observations, synthesizing them, and assisting the design of observational networks; in turn, whenever available, observations can guide coastal model development. Coastal observations should sample the two-way interactions between nearshore, estuarine and shelf processes and open ocean processes, while accounting for the different pace of circulation drivers, such as the fast atmospheric, hydrological and tidal processes and the slower general ocean circulation and climate scales. Because of these challenges, high-resolution models can serve as connectors and integrators of coastal continuum observations. Data assimilation approaches can provide quantitative, validated estimates of Essential Ocean Variables in the coastal continuum, adding scientific and socioeconomic value to observations through applications (e.g., sea-level rise monitoring, coastal management under a sustainable ecosystem approach, aquaculture, dredging, transport and fate of pollutants, maritime safety, hazards under natural variability or climate change). We strongly recommend an internationally coordinated approach in support of the proper integration of global and coastal continuum scales, as well as for critical tasks such as community-agreed bathymetry and coastline products

Motor primitives in space and time via targeted gain modulation in cortical networks

Motor cortex (M1) exhibits a rich repertoire of activities to support the generation of complex movements. Recent network models capture many qualitative aspects of M1 dynamics, but they can generate only a few distinct movements (all of the same duration). We demonstrate that simple modulation of neuronal input–output gains in recurrent neuronal network models with fixed connectivity can dramatically reorganize neuronal activity and consequently downstream muscle outputs. We show that a relatively small number of modulatory control units provide sufficient flexibility to adjust high-dimensional network activity using a simple reward-based learning rule. Furthermore, novel movements can be assembled from previously-learned primitives and we can separately change movement speed while preserving movement shape. Our results provide a new perspective on the role of modulatory systems in controlling recurrent cortical activity.Our work was supported by grants from the Wellcome Trust (TPV and JPS WT100000, 246 GH 202111/Z/16/Z) and the Engineering and Physical Sciences Research Council (JPS)