Cannabinoid CB1 receptor restrains accentuated activity of hypothalamic corticotropin-releasing factor and brainstem tyrosine hydroxylase neurons in endotoxemia-induced hypophagia in rats

It is well known that endocannabinoids play an important role in the regulation of food intake and body weight. Endocannabinoids and cannabinoid receptors are found in the hypothalamus and brainstem, which are central areas involved in the control of food intake and energy expenditure. Activation of these areas is related to hypophagia observed during inflammatory stimulus. This study investigated the effects of cannabinoid (CB1) receptor blockade on lipopolysaccharide (LPS)-induced hypophagia. Male Wistar rats were pretreated with rimonabant (10 mg/kg, by gavage) or vehicle; 30 min later they received an injection of either LPS (100 mu g/kg, intraperitoneal) or saline. Food intake, body weight, corticosterone response, CRF and CART mRNA expression, Fos-CRF and Fos-alpha-MSH immunoreactivity in the hypothalamus and Fos-tyrosine hydroxylase (TH) immunoreactivity in the brainstem were evaluated. LPS administration decreased food intake and body weight gain and increased plasma corticosterone levels and CRF mRNA expression in the PVN. We also observed an increase in Fos-CRF and Fos-TH double-labeled neurons after LPS injection in vehicle-pretreated rats, with no changes in CART mRNA or Fos-alpha-MSH immunoreactive neurons in the ARC. In saline-treated animals, rimonabant pretreatment decreased food intake and body weight gain but did not modify hormone response or Fos expression in the hypothalamus and brainstem compared with vehicle-pretreated rats. Rimonabant pretreatment potentiated LPS-induced hypophagia, body weight loss and Fos-CRF and Fos-TH expressing neurons. Rimonabant did not modify corticosterone, CRF mRNA or Fos-alpha-MSH responses in rats treated with LPS. These data suggest that the endocannabinoid system, mediated by CB1 receptors, modulates hypothalamic and brainstem circuitry underlying the hypophagic effect during endotoxemia to prevent an exaggerated food intake decrease. This article is part of a Special Issue entitled 'Central Control of Food Intake'. (C) 2011 Elsevier Ltd. All rights reserved.

Activation of the cAMP pathway by variant human MC1R alleles expressed in HEK and in melanoma cells

alpha-Melanocyte-stimulating hormone (alpha-MSH) activates the melanocortin-1 receptor (MC1R) on melanocytes to promote a switch from red/yellow pheomelanin synthesis to darker eumelanins via positive coupling to adenylate cyclase. The human MC1R locus is highly polymorphic with the specific variants associated with red hair and fair skin (RHC phenotype) postulated to be loss-of-function receptors. We have examined the ability of MC1R variants to activate the cAMP pathway in stably transfected REK293 cells. The RHC associated variants, Arg151Cys, Arg160Trp and Asp294His, demonstrated agonist-mediated increases in cAMP and phosphorylation of cAMP-responsive element-binding protein (CREB). Whereas the Asp294His variant showed severely impaired functional responses, the Arg151Cys and Arg160Trp variants retained considerable signaling capacity. Melanoma cells homozygous for either the Arg151Cys variant or consensus sequence both elicited CREB phosphorylation in response to alpha-MSH in the presence of IBMX. The common RHC alleles, Arg151Cys, Arg160Trp and Asp294His, are neither complete loss-of-function receptors nor are they functionally equivalent. (c) 2005 Elsevier Inc. All rights reserved.

Quantitative analysis of MC1R gene expression in human skin cell cultures

To address the issue of melanocortin-1 receptor (MC1R) expression in non-melanocytic cells, we have quantitatively evaluated the relative expression levels of both MC1R mRNA and protein in a subset of different cell types. Using semi-quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) at high cycle numbers, we detected MC1R mRNA in all cell types examined, including human embryonic kidney-293 (HEK 293) cells, a cell type widely used as a negative control in melanocortin expression studies. Quantitative real-time PCR revealed the highest levels of MC1R transcripts were in melanocytic cells, whereas the keratinocyte and fibroblast cell cultures examined had only a low level of expression, similar to that of HEK 293 cells. Antibody mediated detection of MC1R protein in membrane extracts demonstrated exogenous receptor in MC1R transfected cell lines, as well as endogenous MC1R in melanoma cells. However, radioligand binding procedures were required to detect MC1R protein of normal human melanocytes and no surface expression of MC1R was detected in any of the non-melanocytic cells examined. This was consistent with their low level of mRNA, and suggests that, if present, the levels of surface receptor are significantly lower than that in melanocytes. The capacity of such limited levels of MC1R protein to influence non-melanocytic skin cell biology would likely be severely compromised. Indeed, the MC1R agonist [NIe(4), D-Phe(7)] alpha-melanocyte stimulating hormone (NDP-MSH) was unable to elevate intracellular cyclic adenosine monophosphate (cAMP) levels in the keratinocyte and fibroblast cells examined, whereas a robust increase was elicited in melanocytes. Although there are a variety of cell types with detectable MC1R mRNA, the expression of physiologically significant levels of the receptor may be more restricted than the current literature indicates, and within epidermal tissue may be limited to the melanocyte

Lys-gamma3-MSH: a global regulator of hormone sensitive lipase activity?

Gamma-melanocyte stimulating hormone (gamma-MSH) is a peptide derived from the ACTH precursor, pro-opiomelanocortin (POMC), and belongs to a family of peptides called the melanocortins that also comprises alpha- and beta-MSH. Although conserved in tetrapods, the biological role of gamma-MSH remains largely undefined. It has been demonstrated previously that gamma-MSH is involved in the regulating the activity of hormone sensitive lipase (HSL) activity in the adrenal and more recently, in the adipocyte. It has been shown also to have effects on the cardiovascular and renal systems. This short review will provide a brief overview of the role of gamma-MSH in the adrenal and the more recent report that it can also regulate HSL function in the adipocyte. We also present some preliminary data purporting a direct role for Lys-gamma(3)-MSH in the regulation of HSL phosphorylation in the heart. Taken together these data suggest that gamma-MSH peptides might play a more widespread role in lipid and cholesterol utilization.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.