Development neurobiology of the stress response: multilevel regulation of corticotropin-releasing hormone function.

The ability to respond to adverse environmental cues is present in the neonatal and infant rat, although in an immature form: A number of laboratories have demonstrated stress-induced elevations of plasma glucocorticoids during the first two postnatal weeks. The limbic and hypothalamic mechanisms controlling the hormonal stress-response during this period are not fully understood and are, therefore, the focus of this report. Both hypothalamic corticotropin-releasing hormone (CRH) and vasopressin contribute to the release of ACTH from the pituitary in the adult. The relative roles of these two peptides during the neonatal (first week) and infant (second week) developmental period, are controversial. Evidence is presented that argues strongly for a major role for CRH. Up-regulation of hypothalamic CRH synthesis is a major component in the mature stress response. CRH-mRNA levels in the hypothalamic PVN are increased with cold stress by ninth postnatal day, but not during the first postnatal week. Further, down-regulation of CRH gene expression by glucocorticoids (GC) constitutes a critical "shut-down" mechanism for the hormonal stress response. In vivo and in vitro experiments supporting the "immaturity" of GC feedback on CRH synthesis during the first postnatal week are described. CRH-mediated neurotransmission, in both the endocrine and neuronal effector arms of the response to stress may be modulated via alteration of receptor number. The first member of the CRH receptor family, CRF1, probably mediates the neuroendocrine effects of CRH. The developmental profile of CRF1-mRNA reveals several distinctive spatial and temporal patterns. In the hippocampal CA1, CA2, and CA3a peak (300-600% adult values) CRF1-mRNA is found on postnatal day 6. In the amygdala, CRH receptor mRNA levels are maximal on the ninth postnatal day (at 180% of adult values). In cortex, a steady decline from high postnatal day 2 levels results in adult levels by 12. These findings demonstrate distinct, regional, age-specific control of the synthesis of CRF1. Receptor expression profile may provide important information regarding modulation of the age-specific roles of CRH in different regions. For example, a high ratio of hippocampus/amygdala receptors may preferentially activate negative hippocampal input to the hypothalamus during the neonatal period. Additionally, increased CRH receptor mRNA in the infant compared with the adult provides a mechanism for enhanced excitatory effect of the peptide at this age. In conclusion, increasing evidence exists for multiple control points of the early postnatal response and adaptation to stress. CRH synthesis in hypothalamus and amygdala, its sensitivity to GC feedback, and the abundance and distribution of at least two distinct CRH receptors in the limbic central nervous system and the pituitary are developmentally regulated. All serve as control points permitting an effective endocrine, autonomic, and behavioral response to stressful environmental cues

Seasonal changes in patterns of gene expression in avian song control brain regions.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Photoperiod and hormonal cues drive dramatic seasonal changes in structure and function of the avian song control system. Little is known, however, about the patterns of gene expression associated with seasonal changes. Here we address this issue by altering the hormonal and photoperiodic conditions in seasonally-breeding Gambel's white-crowned sparrows and extracting RNA from the telencephalic song control nuclei HVC and RA across multiple time points that capture different stages of growth and regression. We chose HVC and RA because while both nuclei change in volume across seasons, the cellular mechanisms underlying these changes differ. We thus hypothesized that different genes would be expressed between HVC and RA. We tested this by using the extracted RNA to perform a cDNA microarray hybridization developed by the SoNG initiative. We then validated these results using qRT-PCR. We found that 363 genes varied by more than 1.5 fold (>log(2) 0.585) in expression in HVC and/or RA. Supporting our hypothesis, only 59 of these 363 genes were found to vary in both nuclei, while 132 gene expression changes were HVC specific and 172 were RA specific. We then assigned many of these genes to functional categories relevant to the different mechanisms underlying seasonal change in HVC and RA, including neurogenesis, apoptosis, cell growth, dendrite arborization and axonal growth, angiogenesis, endocrinology, growth factors, and electrophysiology. This revealed categorical differences in the kinds of genes regulated in HVC and RA. These results show that different molecular programs underlie seasonal changes in HVC and RA, and that gene expression is time specific across different reproductive conditions. Our results provide insights into the complex molecular pathways that underlie adult neural plasticity

GTPase regulator associated with the focal adhesion kinase (GRAF) transcript was down-regulated in patients with myeloid malignancies

<p>Abstract</p> <p>Background</p> <p>GTPase regulator associated with the focal adhesion kinase (<it>GRAF</it>), a putative tumor suppressor gene, is found inactivated in hematopoietic malignancies by either genetic or epigenetic abnormalities. However, the expression level of <it>GRAF </it>gene has not yet been studied in leukemia. The aim of this study was to investigate the expression level of <it>GRAF </it>gene in those patients with myeloid malignancies including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS) and chronic myeloid leukemia (CML).</p> <p>Methods</p> <p>The expression levels of <it>GRAF </it>transcript were determined in 94 patients using real-time quantitative PCR (RQ-PCR). Clinical and laboratory data of these patients were collected and analyzed.</p> <p>Results</p> <p>The significantly decreased level of <it>GRAF </it>transcript was observed in three myeloid malignancies compared to controls. Within AML, there was no difference in the level of <it>GRAF </it>transcript among different FAB subtypes (<it>P </it>> 0.05). Difference was not observed in the amount of <it>GRAF </it>mRNA between CML at chronic phase and controls. As CML progressed, <it>GRAF </it>transcript significantly decreased. In MDS, three cases with 5q deletion had lower <it>GRAF </it>transcript than four without 5q deletion (median 0.76 vs 2.99) (<it>P </it>> 0.05).</p> <p>Conclusion</p> <p>our results demonstrate that the <it>GRAF </it>transcript is decreased in myeloid malignancies.</p

Catecholamine Storage Vesicles: Role of Core Protein Genetic Polymorphisms in Hypertension

Hypertension is a complex trait with deranged autonomic control of the circulation. The sympathoadrenal system exerts minute-to-minute control over cardiac output and vascular tone. Catecholamine storage vesicles (or chromaffin granules) of the adrenal medulla contain remarkably high concentrations of chromogranins/secretogranins (or “granins”), catecholamines, neuropeptide Y, adenosine triphosphate (ATP), and Ca2+. Within secretory granules, granins are co-stored with catecholamine neurotransmitters and co-released upon stimulation of the regulated secretory pathway. The principal granin family members, chromogranin A (CHGA), chromogranin B (CHGB), and secretogranin II (SCG2), may have evolved from shared ancestral exons by gene duplication. This article reviews human genetic variation at loci encoding the major granins and probes the effects of such polymorphisms on blood pressure, using twin pairs to probe heritability and individuals with the most extreme blood pressure values in the population to study hypertension

Tutorial: Multivariate Classification for Vibrational Spectroscopy in Biological Samples

Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental

Variable selection for multivariate calibration using a genetic algorithm: Prediction of additive concentrations in polymer films from Fourier transform-infrared spectral data

Variable selection using a genetic algorithm is combined with partial least squares (PLS) for the prediction of additive concentrations in polymer films using Fourier transform-infrared (FT-IR) spectral data. An approach using an iterative application of the genetic algorithm is proposed. This approach allows for all variables to be considered and at the same time minimizes the risk of overfitting. We demonstrate that the variables selected by the genetic algorithm are consistent with expert knowledge. This very exciting result is a convincing application that the algorithm can select correct variables in an automated fashion. © 2002 Elsevier Science B.V. All rights reserved

Measurement of Initial Conditions at Nozzle Exit of High Speed Jets

The time averaged and unsteady density fields close to the nozzle exit (0.1 less than or = x/D less than or = 2, x: downstream distance, D: jet diameter) of unheated free jets at Mach numbers of 0.95, 1.4, and 1.8 were measured using a molecular Rayleigh scattering based technique. The initial thickness of shear layer and its linear growth rate were determined from time-averaged density survey and a modeling process, which utilized the Crocco-Busemann equation to relate density profiles to velocity profiles. The model also corrected for the smearing effect caused by a relatively long probe length in the measured density data. The calculated shear layer thickness was further verified from a limited hot-wire measurement. Density fluctuations spectra, measured using a two-Photomultiplier-tube technique, were used to determine evolution of turbulent fluctuations in various Strouhal frequency bands. For this purpose spectra were obtained from a large number of points inside the flow; and at every axial station spectral data from all radial positions were integrated. The radially-integrated fluctuation data show an exponential growth with downstream distance and an eventual saturation in all Strouhal frequency bands. The initial level of density fluctuations was calculated by extrapolation to nozzle exit