BackgroundAmbient air quality monitoring is a governmental duty that is widely carried out in order to detect non-biological (“chemical”) components in ambient air, such as particles of < 10 µm (PM10, PM2.5), ozone, sulphur dioxide, and nitrogen oxides. These monitoring networks are publicly funded and air quality data are open to the public. The situation for biological particles that have detrimental effects on health, as is the case of pollen and fungal spores, is however very different. Most pollen and spore monitoring networks are not publicly funded and data are not freely available. The information regarding which biological particle is being monitored, where and by whom, is consequently often not known, even by aerobiologists themselves. This is a considerable problem, as local pollen data are an important tool for the prevention of allergic symptoms.ObjectiveThe aim of this study was to review pollen monitoring stations throughout the world and to create an interactive visualization of their distribution.MethodsThe method employed to collect information was based on: (a) a review of the recent and historical bibliography related to pollen and fungal spore monitoring, and (b) personal surveys of the managers of national and regional monitoring networks. The interactive application was developed using the R programming language.ResultsWe have created an inventory of the active pollen and spore monitoring stations in the world. There are at least 879 active pollen monitoring stations in the world, most of which are in Europe (> 500). The prevalent monitoring method is based on the Hirst principle (> 600 stations). The inventory is visualised as an interactive and on-line map. It can be searched, its appearance can be adjusted to the users’ needs and it is updated regularly, as new stations or changes to those that already exist can be submitted online.ConclusionsThe map shows the current situation of pollen and spore monitoring and facilitates collaboration among those individuals who are interested in pollen and spore counts. It might also help to improve the monitoring of biological particles up to the current level employed for non-biological components.

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Although isolated rat islets are widely used to study in vitro insulin secretion and the underlying metabolic and ionic processes, knowledge on the properties of glucose-induced electrical activity (GIEA), a key step in glucose-response coupling, has been gathered almost exclusively from microdissected mouse islets. Using a modified intracellular recording technique, we have now compared the patterns of GIEA in collagenase-isolated rat and mouse islets. Resting membrane potentials of rat and mouse ␤-cells were approximately -50 and -60 mV, respectively. Both rat and mouse ␤-cells displayed prompt membrane depolarizations in response to glucose. However, whereas the latter exhibited a bursting pattern consisting of alternating hyperpolarized and depolarized active phases, rat ␤-cells fired action potentials from a nonoscillating membrane potential at all glucose concentrations (8.4-22.0 mmol/l). This was mirrored by changes in the intracellular Ca 2+ concentration ([Ca 2+ ] i ), which was oscillatory in mouse and nonoscillatory in rat islets. Stimulated rat ␤-cells were strongly hyperpolarized by diazoxide, an activator of ATP-dependent K + channels. Glucose evoked dosedependent depolarizations and [Ca 2+ ] i increases in both rat (EC 50 5.9-6.9 mmol/l) and mouse islets (EC 50 8.3-9.5 mmol/l), although it did not affect the burst plateau potential in the latter case. We conclude that there are important differences between ␤-cells from both species with respect to early steps in the stimulussecretion coupling cascade based on the following findings: 1) mouse ␤-cells have a larger resting K + conductance in 2 mmol/l glucose, 2) rat ␤-cells lack the compensatory mechanism responsible for generating membrane potential oscillations and holding the depolarized plateau potential in mouse ␤-cells, and 3) the electrical and [Ca 2+ ] i dose-response curves in rat ␤-cells are shifted toward lower glucose concentrations. Exploring the molecular basis of these differences may clarify several a priori assumptions on the electrophysiological properties of rat ␤-cells, which could foster the development of new working models of pancreatic ␤-cell function.