Multivariate analysis of the energy cycle of the South American rainy season

The South American (SA) rainy season is studied in this paper through the application of a multivariate Empirical Orthogonal Function (EOF) analysis to a SA gridded precipitation analysis and to the components of Lorenz Energy Cycle (LEC) derived from the National Centers for Environmental Prediction (NCEP) reanalysis. The EOF analysis leads to the identification of patterns of the rainy season and the associated mechanisms in terms of their energetics. The first combined EOF represents the northwest-southeast dipole of the precipitation between South and Central America, the South American Monsoon System (SAMS). The second combined EOF represents a synoptic pattern associated with the SACZ (South Atlantic convergence zone) and the third EOF is in spatial quadrature to the second EOF. The phase relationship of the EOFs, as computed from the principal components (PCs), suggests a nonlinear transition from the SACZ to the fully developed SAMS mode by November and between both components describing the SACZ by September-October (the rainy season onset). According to the LEC, the first mode is dominated by the eddy generation term at its maximum, the second by both baroclinic and eddy generation terms and the third by barotropic instability previous to the connection to the second mode by September-October. The predominance of the different LEC components at each phase of the SAMS can be used as an indicator of the onset of the rainy season in terms of physical processes, while the existence of the outstanding spectral peaks in the time dependence of the EOFs at the intraseasonal time scale could be used for monitoring purposes. Copyright (C) 2009 Royal Meteorological Society

Islet neogenesis-associated protein signaling in neonatal pancreatic rat islets: involvement of the cholinergic pathway

Islet neogenesis associated protein (INGAP) increases islet mass and insulin secretion in neonatal and adult rat islets. lit the Present Study, we measured the short- and long-term effects of INGAP-PP (a pentadecapeptide having the 104-118 amino acid sequence of INGAP) upon islet protein expression and phosphorylation of components of the PI3K, MAPK and cholinergic pathways, and on insulin secretion. Short-term exposure of neonatal islets to INGAP-PP (90 s, 5, 15, and 30 min) significantly increased Akt1(-Ser473) and MAPK3/1(-Thr202/Tyr204) phosphorylation and INGAP-PP also acutely increased insulin secretion from islets perifused with 2 and 20 mM glucose. Islets cultured for 4 days in the presence of INGAP-PP showed an increased expression of Akt1, Frap1, and Mapk1 mRNAs as well as of the muscarinic M3 receptor subtype, and phospholipase C (PLC)-beta 2 proteins. These islets also showed increased Akt1 and MAPK3/1 protein phosphorylation. Brief exposure of INGAP-P-treated islets to carbachol (Cch) significantly increased P70S6K(-Thr389) and MAPK3/1 phosphorylation and these islets released more insulin when challenged with Cch that was prevented by the M3 receptor antagonist 4-DAMP in a concentration-dependent manner. In conclusion, these data indicate that short- and long-term exposure to INGAP-PP significantly affects the expression and the phosphorylation of proteins involved in islet PI3K and MAPK signaling pathways. The observations of INGAPP-PP-stimulated up-regulation of cholinergic M3 receptors and PLC-beta 2 proteins, enhanced P70S6K and MAIIK3/1 phosphorylation and Cch-induced insulin secretion suggest a participation of the cholinergic pathway in INGAP-PP-mediated effects.

X-ray spectroscopy applied to radiation shielding calculation in mammography

The protective shielding design of a mammography facility requires the knowledge of the scattered radiation by the patient and image receptor components. The shape and intensity of secondary x-ray beams depend on the kVp applied to the x-ray tube, target/filter combination, primary x-ray field size, and scattering angle. Currently, shielding calculations for mammography facilities are performed based on scatter fraction data for Mo/Mo target/filter, even though modern mammography equipment is designed with different anode/filter combinations. In this work we present scatter fraction data evaluated based on the x-ray spectra produced by a Mo/Mo, Mo/Rh and W/Rh target/filter, for 25, 30 and 35 kV tube voltages and scattering angles between 30 and 165 degrees. Three mammography phantoms were irradiated and the scattered radiation was measured with a CdZnTe detector. The primary x-ray spectra were computed with a semiempirical model based on the air kerma and HVL measured with an ionization chamber. The results point out that the scatter fraction values are higher for W/Rh than for Mo/Mo and Mo/Rh, although the primary and scattered air kerma are lower for W/Rh than for Mo/Mo and Mo/Rh target/filter combinations. The scatter fractions computed in this work were applied in a shielding design calculation in order to evaluate shielding requirements for each of these target/filter combinations. Besides, shielding requirements have been evaluated converting the scattered air kerma from mGy/week to mSv/week adopting initially a conversion coefficient from air kerma to effective dose as 1 Sv/Gy and then a mean conversion coefficient specific for the x-ray beam considered. Results show that the thickest barrier should be provided for Mo/Mo target/filter combination. They also point out that the use of the conversion coefficient from air kerma to effective dose as 1 Sv/Gy is conservatively high in the mammography energy range and overestimate the barrier thickness. (c) 2008 American Association of Physicists in Medicine.

A neural networks study of quinone compounds with trypanocidal activity

This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.