Enhanced Secretion of Amylase from Exocrine Pancreas of Connexin32-deficient Mice

To determine whether junctional communication between pancreatic acinar cells contributes to their secretory function in vivo, we have compared wild-type mice, which express the gap junctional proteins connexin32 (Cx32) and connexin26, to mice deficient for the Cx32 gene. Pancreatic acinar cells from Cx32 (−/−) mice failed to express Cx32 as evidenced by reverse transcription–PCR and immunolabeling and showed a marked reduction (4.8- and 25-fold, respectively) in the number and size of gap junctions. Dye transfer studies showed that the extent of intercellular communication was inhibited in Cx32 (−/−) acini. However, electrical coupling was detected by dual patch clamp recording in Cx32 (−/−) acinar cell pairs. Although wild-type and Cx32 (−/−) acini were similarly stimulated to release amylase by carbamylcholine, Cx32 (−/−) acini showed a twofold increase of their basal secretion. This effect was caused by an increase in the proportion of secreting acini, as detected with a reverse hemolytic plaque assay. Blood measurements further revealed that Cx32 (−/−) mice had elevated basal levels of circulating amylase. The results, which demonstrate an inverse relationship between the extent of acinar cell coupling and basal amylase secretion in vivo, support the view that the physiological recruitment of secretory acinar cells is regulated by gap junction mediated intercellular communication

Seasonal variation in Plasmodium prevalence in a population of blue tits Cyanistes caeruleus.

1. Seasonal variation in environmental conditions is ubiquitous and can affect the spread of infectious diseases. Understanding seasonal patterns of disease incidence can help to identify mechanisms, such as the demography of hosts and vectors, which influence parasite transmission dynamics. 2. We examined seasonal variation in Plasmodium infection in a blue tit Cyanistes caeruleus population over 3 years using sensitive molecular diagnostic techniques, in light of Beaudoin et al.'s (1971; Journal of Wildlife Diseases, 7, 5-13) model of seasonal variation in avian malaria prevalence in temperate areas. This model predicts a within-year bimodal pattern of spring and autumn peaks with a winter absence of infection. 3. Avian malaria infections were mostly Plasmodium (24.4%) with occasional Haemoproteus infections (0.8%). Statistical nonlinear smoothing techniques applied to longitudinal presence/absence data revealed marked temporal variation in Plasmodium prevalence, which apparently showed a within-year bimodal pattern similar to Beaudoin et al.'s model. However, of the two Plasmodium morphospecies accounting for most infections, only the seasonal pattern of Plasmodium circumflexum supported Beaudoin et al.'s model. On closer examination there was also considerable age structure in infection: Beaudoin et al.'s seasonal pattern was observed only in first year and not older birds. Plasmodium relictum prevalence was less seasonally variable. 4. For these two Plasmodium morphospecies, we reject Beaudoin et al.'s model as it does not survive closer scrutiny of the complexities of seasonal variation among Plasmodium morphospecies and host age classes. Studies of host-parasite interactions should consider seasonal variation whenever possible. We discuss the ecological and evolutionary implications of seasonal variation in disease prevalence

More things than are dreamt of in your biology: information processing in biologically-inspired robots

Animals and robots perceiving and acting in a world require an ontology that accommodates entities, processes, states of affairs, etc., in their environment. If the perceived environment includes information-processing systems, the ontology should reflect that. Scientists studying such systems need an ontology that includes the first-order ontology characterising physical phenomena, the second-order ontology characterising perceivers of physical phenomena, and a (recursive) third order ontology characterising perceivers of perceivers, including introspectors. We argue that second- and third-order ontologies refer to contents of virtual machines and examine requirements for scientific investigation of combined virtual and physical machines, such as animals and robots. We show how the CogAff architecture schema, combining reactive, deliberative, and meta-management categories, provides a first draft schematic third-order ontology for describing a wide range of natural and artificial agents. Many previously proposed architectures use only a subset of CogAff, including subsumption architectures, contention-scheduling systems, architectures with ‘executive functions’ and a variety of types of ‘Omega’ architectures. Adding a multiply-connected, fast-acting ‘alarm’ mechanism within the CogAff framework accounts for several varieties of emotions. H-CogAff, a special case of CogAff, is postulated as a minimal architecture specification for a human-like system. We illustrate use of the CogAff schema in comparing H-CogAff with Clarion, a well known architecture. One implication is that reliance on concepts tied to observation and experiment can harmfully restrict explanatory theorising, since what an information processor is doing cannot, in general, be determined by using the standard observational techniques of the physical sciences or laboratory experiments. Like theoretical physics, cognitive science needs to be highly speculative to make progress