The effect of acetylcholine on adrenal function in the hypophysectomized dog

Résumé Après injection d'acétylcholine, les chiens hypophysectomisés ne secrètent pas d'hydrocortisone, mais présentent une élevation d'épinéphrine et de norépinéphrine dans le sang veineux surrénal. Aucun changement ne fut observé dans la concentration de la phényléthanolamine-N-methyl transférase dans ces glandes. Ces expériences indiquent que la relation médullaire surrénale corticale que nous avons mentionée précédemment fonctionne indépendamment de la secrétion de catécholamines, engendrée par l'Ach, de la glande surrénale.     

A gene-driven approach to the identification of ENU mutants in the mouse

The construction of parallel archives of DNA and sperm from mice mutagenized with ethylnitrosurea (ENU) represents a potentially powerful and rapid approach for identifying point mutations in any gene in the mouse genome. We provide support for this approach and report the identification of mutations in the gene (Gjb2) encoding connexin 26, using archives established from the UK ENU mutagenesis program.     

Low melting point nanocrystalline Sn–Ag solder synthesized by a refined chemical reduction method

The commercial market of Sn-Pb solder is gradually decreasing due to its toxicity, calling for Pb-free substitute materials. Sn-Ag alloy is a potential candidate in terms of good mechanical property. The major problematic issue of using Sn-Ag is their high melting temperature, consequently this study is dedicated to lowering the melt- ing temperature of Sn3.5Ag （wt%） alloy by developing nanomaterials using a chemical reduction approach. The resultant nanocrystalline Sn3.5Ag is characterized by field emission scanning electron microscope. The size dependence of the melting temperature is discussed based on differential scanning calorimetry results. We have reduced the melting temperature to 209.8 ℃ in the nanocrystalline Sn3.5Ag of （32.4± 8.0） nm, compared to ～221 ℃ of the bulk alloy. The results are consistent with the prediction made by a relevant theoretical model, and it is possible to further lower the melting temperature using the chemical reduction approach developed by this study.     

Ia binding ligands and cAMP stimulate nuclear translocation of PKC in B lymphocytes

Altered subcellular distribution and activity of protein kinase C (PKC) is associated with transmembrane signalling in a variety of systems in which receptor occupancy leads to increased hydrolysis of polyphosphoinositides. Here we report evidence that in B lymphocytes, cyclic-cAMP-generating signal transduction pathways can activate translocation of PKC from the cytosol to the nucleus. Elevated cAMP levels and translocation of PKC to the nucleus are induced by antibodies against Ia antigens in normal B lymphocytes. Further, cAMP analogues mediate the translocation of PKC to the nucleus of these cells. These findings suggest that in physiological situations, ligation of B-lymphocyte Ia molecules by helper T cells leads to increased cAMP production which in turn causes PKC translocation to the nucleus. In view of recent observations that antibodies against Ia antigens induce differentiation of B cells, we conclude that nuclear PKC may function in the regulation of gene expression.     

A Comparison of Box—Jenkins and objective methods for determining the order of a non-seasonal ARMA Model

This paper evaluates different procedures for selecting the order of a non-seasonal ARMA model. Specifically, it compares the forecasting accuracy of models developed by the personalized Box-Jenkins (BJ) methodology with models chosen by numerous automatic procedures. The study uses real series modelled by experts (textbook authors) in the BJ approach. Our results show that many objective selection criteria provide structures equal or superior to the time-consuming BJ method. For the sets of data used in this study, we also examine the influence of parsimony in time-series forecasting. Defining what models are too large or too small is sensitive to the forecast horizon. Automatic techniques that select the best models for forecasting are similar in size to BJ models although they often disagree on model order.