Acute ACE inhibition causes plasma extravasation in mice that is mediated by bradykinin and substance P

The use of angiotensin-converting enzyme (ACE) has been associated with the occurrence of adverse effects, including cough and angioneurotic edema. Accumulation of kinins has been suggested to play a major role in these adverse effects of ACE inhibitor, although conclusive evidence for such a role is lacking. We investigated whether ACE inhibition increases plasma extravasation in mice (Swiss, C57Bl/6J, and J129Sv/Ev strains) via inhibition of bradykinin metabolism and stimulation of neurogenic inflammatory mechanisms. Intravenous captopril and enalapril increased the extravasation of Evans blue dye in all tissues examined (trachea, stomach, duodenum, and pancreas). This effect was evident 15 minutes after drug administration. The particulate dye Monastral blue identified the sites of captopril-induced leakage in the microvasculature. Pretreatment with the bradykinin B2 receptor antagonist Hoe 140 or with the tachykinin NK1 receptor antagonist SR 140333 inhibited captopril-evoked increase in plasma extravasation. In mice in which the gene encoding the bradykinin B2 receptor was disrupted by gene targeting, neither bradykinin nor captopril increased plasma extravasation. Pretreatment with Hoe 140 did not reduce the hypotensive response induced by captopril. The present findings suggest that ACE inhibition increases kinin levels in tissues and/or plasma. These increased kinin levels increase microvascular leakage in mouse airways and digestive tract via the release of tachykinins from terminals of primary sensory neurons. Exaggerated kinin production and the subsequent stimulation of peptide release from sensory nerves may be involved in adverse effects of ACE inhibitors.

An artificial life approach to language

The aim of the paper is to show that an Artificial Life approach to language tends to change the research agenda on language which has been shared by both the symbolic paradigm and classical connectionism. Artificial Life Neural Networks (ALNNs) are different from classical connectionist networks because they interact with an independent physical environment; are subject to evolutionary, developmental, and cultural change, and not only to learning; and are part of organisms that have a physical body, have a life (are born, develop, and die), and are members of genetic and sometimes, cultural populations. Using ALNNs to study language shifts the emphasis from research on linguistic forms and laboratory-like tasks to the investigation of the emergence and transmission of language, the use of language, its role in cognition, and language as a populational rather than as an individual phenomenon.