Development of the first marmoset-specific DNA microarray (EUMAMA): a new genetic tool for large-scale expression profiling in a non-human primate

Contains fulltext : 34911.pdf (publisher's version ) (Open Access)BACKGROUND: The common marmoset monkey (Callithrix jacchus), a small non-endangered New World primate native to eastern Brazil, is becoming increasingly used as a non-human primate model in biomedical research, drug development and safety assessment. In contrast to the growing interest for the marmoset as an animal model, the molecular tools for genetic analysis are extremely limited. RESULTS: Here we report the development of the first marmoset-specific oligonucleotide microarray (EUMAMA) containing probe sets targeting 1541 different marmoset transcripts expressed in hippocampus. These 1541 transcripts represent a wide variety of different functional gene classes. Hybridisation of the marmoset microarray with labelled RNA from hippocampus, cortex and a panel of 7 different peripheral tissues resulted in high detection rates of 85% in the neuronal tissues and on average 70% in the non-neuronal tissues. The expression profiles of the 2 neuronal tissues, hippocampus and cortex, were highly similar, as indicated by a correlation coefficient of 0.96. Several transcripts with a tissue-specific pattern of expression were identified. Besides the marmoset microarray we have generated 3215 ESTs derived from marmoset hippocampus, which have been annotated and submitted to GenBank [GenBank: EF214838-EF215447, EH380242-EH382846]. CONCLUSION: We have generated the first marmoset-specific DNA microarray and demonstrated its use to characterise large-scale gene expression profiles of hippocampus but also of other neuronal and non-neuronal tissues. In addition, we have generated a large collection of ESTs of marmoset origin, which are now available in the public domain. These new tools will facilitate molecular genetic research into this non-human primate animal model

Импортозамещение межсекционных уплотнений на примере многоступенчатого насоса "Grundfos"

Bronchoconstriction is a characteristic symptom of various chronic obstructive respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma. Precision-cut lung slices (PCLS) are a suitable ex vivo model to study physiological mechanisms of bronchoconstriction in different species. In the present study, we established an ex vivo model of bronchoconstriction in non-human primates (NHPs). PCLS prepared from common marmosets, cynomolgus macaques, rhesus macaques, and anubis baboons were stimulated with increasing concentrations of representative bronchoconstrictors: methacholine, histamine, serotonin, leukotriene D4 (LTD4), U46619, and endothelin-1. Alterations in the airway caliber were measured and compared to previously published data from rodents, guinea pigs, and humans. Methacholine induced maximal airway constriction, varying between 74 and 88% in all NHP species, whereas serotonin was ineffective. Histamine induced maximal bronchoconstriction of 77 to 90% in rhesus macaques, cynomolgus macaques, and baboons, and a lesser constriction of 53% in marmosets. LTD4 was ineffective in marmosets and rhesus macaques, but induced a maximum constriction of 44 to 49% in cynomolgus macaques and baboons. U46619 and endothelin-1 caused airway constriction in all NHP species, with maximum constrictions of 65 to 91%, and 70 to 81%, respectively. In conclusion, PCLS from NHPs represent a valuable ex vivo model for studying bronchoconstriction. All NHPs respond to mediators relevant to human airway disorders such as methacholine, histamine, U46619, endothelin-1 and are insensitive to the rodent mast cell product serotonin. Only PCLS from cynomolgus macaques and baboons, however, responded also to leukotrienes, suggesting that among all compared species, these two NHPs resemble the human airway mechanisms bes

Ein internes Vorhersagbarkeitsexperiment im Lorenz-Modell

The predictability of the atmosphere usually is quantified by the error doubling time or the limit of predictability. These measures are times when small errors double on average or reach a certain threshold value respectively. In this article we analyse the error doubling time in the Lorenz Model. We want to demonstrate, that averaged measures of predictability are not necessarily typical measures for the system. Predictability is a variable and it is an important task to identify which initial states lead to enhanced, or reduced, predictabilit