Relevance of histamine and tryptase concentrations in nasal secretions after nasal challenges with phosphate buffered saline and allergen

In this prospective study, a quantitative determination of histamine and tryptase in nasal secretions after nasal phosphate buffered saline (PBS) and allergen challenge was performed in 18 atopic patients who were compared with ten non-allergic healthy volunteers. The aim of the study was to determine the normal and pathological concentrations of these important mediators in nasal secretions. The second objective was to test the relevance of these two mast cell secreted mediators after nasal challenge. Results showed that the concentrations of tryptase in almost all samples were under the minimal detection limit (< 0.5 μU/g) and only a sigrtificant increase of tryptase (median, 28 μU/g) occurred immediately after nasal allergen challenge in the patient group. Histamine concentration significantly increased after every nasal PBS challenge (median, 69 ng/g after first PBS challenge and 165 ng/g after second PBS challenge) in the control group, as well as in the patient group after both PBS (median, 69 ng/g) and allergen (median, 214 ng/g) challenge. On the other hand, a rapid onset of sneezing and increase in nasal airway resistance was experienced only in the patient group after nasal allergen challenge, but did not occur after PBS challenge even though the histamine concentrations significantly increased in both groups. This study suggests that tryptase is a more preferable marker than histamine in quantitative monitoring of mast cell activation especially during the early phase nasal allergic reaction

Utilisation des outils numériques d'aide à la décision pour la gestion de l'eau

Le succès d'une gestion des écosystèmes naturels requiert une connaissance approfondie des différents processus qui interviennent et de leurs échelles de temps et d'espace particulières. Pour cette raison, les décideurs ont besoin d'analyser une vaste gamme de données et d'informations géographiques. Les modèles mathématiques, les systèmes d'informations géographi-ques et les systèmes experts sont capables de produire cette analyse, mais seule une minorité de gestionnaires les utilise actuellement. Cet article identifie quelques unes des raisons à l'origine de l'hésitation des gestionnaires à adopter de tels outils d'aide à la décision pour la gestion des ressources naturelles et propose une structure qui pourrait faciliter leur utilisation pour le processus de prise de décision. Cet exercice est réalisé à l'intérieur du contexte de la gestion intégrée par bassin. Une revue des systèmes d'aide à la décision est également présentée.Many methods of integrated or watershed management exist which account for the necessary biophysical and socio-economic factors at the watershed level. Some of these approaches are ecosystem oriented while others are socio-economically oriented. Whatever the definition, water management at the watershed level needs to account for a plenitude of variables related to the air, water, soil, biology, and economy. The successful management of natural ecosystems requires a thorough understanding of their characteristic time and spatial scales. Because of this, decision makers need to analyze a wide range of data and geographic information. Mathematical models, geographic information systems and expert systems are capable of performing this analysis, but only a minority of managers are currently using them. This paper identifies some of the reasons why ecosystem managers have been slow to adopt such decision support tools in natural resources management and proposes a framework to facilitate their use in the decision making process. This is done in an integrated watershed management context. A review of related decision support systems is also presented.Four types of decision-support tools are introduced : mathematical models, expert-systems, geographical information systems (GIS) and decision support systems (DSS). Mathematical models have long been used for simulation, prediction, and forecasting, however, they are often task specific and were rarely developed for management uses. GIS are more and more commonly being used for decision support as they become more affordable and user-friendly and are very well-suited for managing resources at a spatial scale. There exist many kinds of software ranging from a simple viewer used for cartographic purposes to complex GIS oriented toward spatial analysis and modelling. Expert systems are also interesting for decision support when specific goals are being considered. Finally, DSS are perhaps the digital tools most applicable to management purposes, often integrating one or more models, a GIS or expert system functionalities. There are two types of DSS : 1. Environmental Information Systems (EIS), and 2. Integrated Modelling Systems (IMS) EIS can be very user- friendly, relying heavily upon GIS and statistical functions.IMS also use GIS capabilities, but integrates several mathematical models as well. The level of integration between models varies considerably and the complexity of IMS are generally high.Two questions underlie the operational use of digital technologies for decision support. The first is whether or not such technology should be used at all, while the second is why such tools take time to be adopted by government and management agencies. The use of digital technologies is often required when the problem is complex and where there are a wide range of factors involved with different spatial and temporal scales. Three major constraints towards the implementation of decision support tools can be pinpointed :1. technology, 2. data, and 3. working organization. Technological constraints include cost, lack of user friendliness, and hardware problems, among other factors. Data constraints are mostly related to availability, cost, heterogeneity and volume. Finally, organization constraints pertain mostly to the manager's perception of the tool and the structural integration of the tool within the decision process.This paper proposes a 4-step approach to optimize the use of decision-support tools. The first step requires that managers and decision-makers clearly define their project, goals and budget, as well as, decide whether to use an integrated watershed management approach or a more discrete approach. This leads directly to the second step, which consists of choosing the most appropriate digital support tool. This requires communication between managers and scientists, and at this point, data gathering and integration should begin. The third phase consists of the development of a new tool or adaptation of an existing one within the context of the agency's management structure. The final step is the operational use of the decision support tool by the agency, following an initial trial period. The successful use of a decision support tool for management purposes depends on proper planning that accounts for all factors related to management needs, budget, data, ease of use, and organization integration

First characterization of preantral follicles in the ovaries of adult alpaca

It is a fact that while even basic reproductive information on alpacas is unavailable, the normal ovarian reserve of this species in comparison to other species is also unidentified. In this study, the ovarian preantral follicles in healthy adult alpacas were characterized in order to establish a general model to in vitro studies. Ten ovaries were collected from five adult alpacas. The ovarian cortex samples were fixed with paraformaldehyde and histological analysis was done. Normal and degenerated follicles percentages were determined. The normal follicles were measured and classified in primordial, transitional, primary and secondary stages.  Most of the preantral follicles present in the ovarian cortex of alpacas were primordial and transitional stages; primary (6.10%) and secondary (0.37%) follicles were rarely found. The primary and secondary follicles were larger in diameter when compared with the primordial and transitional follicles. The largest oocyte diameter was recorded in the secondary follicles (P &lt; 0.05). This study serves to establish a biological model for future reproduction studies in Alpacas or as possible biological model for studies of folliculogenesis in humans

Inactivation of clathrin heavy chain inhibits synaptic recycling but allows bulk membrane uptake

Synaptic vesicle reformation depends on clathrin, an abundant protein that polymerizes around newly forming vesicles. However, how clathrin is involved in synaptic recycling in vivo remains unresolved. We test clathrin function during synaptic endocytosis using clathrin heavy chain (chc) mutants combined with chc photoinactivation to circumvent early embryonic lethality associated with chc mutations in multicellular organisms. Acute inactivation of chc at stimulated synapses leads to substantial membrane internalization visualized by live dye uptake and electron microscopy. However, chc-inactivated membrane cannot recycle and participate in vesicle release, resulting in a dramatic defect in neurotransmission maintenance during intense synaptic activity. Furthermore, inactivation of chc in the context of other endocytic mutations results in membrane uptake. Our data not only indicate that chc is critical for synaptic vesicle recycling but they also show that in the absence of the protein, bulk retrieval mediates massive synaptic membrane internalization