Retinoid-Related Receptor (ROR) alpha mRNA Expression Is Altered in the Brain of Male Mice Lacking All Ligand-Binding Thyroid Hormone Receptor (TR) Isoforms

In the vertebrate brain, the thalamus serves as a relay and integration station for diverse neuronal information en route from the periphery to the cortex. Deficiency of TH during development results in severe cerebral abnormalities similar to those seen in the mouse when the retinoic acid receptor (ROR)α gene is disrupted. To investigate the effect of the thyroid hormone recep-tors (TRs) on RORalpha gene expression, we used intact male mice, in which the genes encoding the α and beta TRs have been deleted. In situ hybridization for RORalpha mRNA revealed that this gene is expressed in specific areas of the brain including the thalamus, pons, cerebellum, cortex, and hippocampus. Our quantitative data showed differences in RORalpha mRNA expression in different subthalamic nuclei between wild-type and knock-out mice. For example, the centromedial nucleus of the thalamus, which plays a role in mediating nociceptive and visceral information from the brainstem to the basal ganglia and cortical regions, has less expression of RORalpha mRNA in the knockout mice (-37%) compared to the wild-type controls. Also, in the dorsal geniculate (+72%) and lateral posterior nuclei (+58%) we found more RORalpha mRNA in dKO as compared to dWT animals. Such differences in RORalpha mRNA expression may play a role in the behavioral alterations resulting from congenital hypothyroidism.

ROR alpha regulates the expression of genes involved in lipid homeostasis in skeletal muscle cells - Caveolin-3 and CPT-1 are direct targets of ROR

The staggerer mice carry a deletion in the RORalpha gene and have a prolonged humoral response, overproduce inflammatory cytokines, and are immunodeficient. Furthermore, the staggerer mice display lowered plasma apoA-I/-II, decreased plasma high density lipoprotein cholesterol and triglycerides, and develop hypo-alpha-lipoproteinemia and atherosclerosis. However, relatively little is known about RORalpha in the context of target tissues, target genes, and lipid homeostasis. For example, RORalpha is abundantly expressed in skeletal muscle, a major mass peripheral tissue that accounts for similar to40% of total body weight and 50% of energy expenditure. This lean tissue is a primary site of glucose disposal and fatty acid oxidation. Consequently, muscle has a significant role in insulin sensitivity, obesity, and the blood-lipid profile. In particular, the role of RORalpha in skeletal muscle metabolism has not been investigated, and the contribution of skeletal muscle to the ROR-/- phenotype has not been resolved. We utilize ectopic dominant negative RORalpha expression in skeletal muscle cells to understand the regulatory role of RORs in this major mass peripheral tissue. Exogenous dominant negative RORalpha expression in skeletal muscle cells represses the endogenous levels of RORalpha and -gamma mRNAs and ROR-dependent gene expression. Moreover, we observed attenuated expression of many genes involved in lipid homeostasis. Furthermore, we show that the muscle carnitine palmitoyltransferase-1 and caveolin-3 promoters are directly regulated by ROR and coactivated by p300 and PGC-1. This study implicates RORs in the control of lipid homeostasis in skeletal muscle. In conclusion, we speculate that ROR agonists would increase fatty acid catabolism in muscle and suggest selective activators of ROR may have therapeutic utility in the treatment of obesity and atherosclerosis.

Expression of Circadian Clock and Melatonin Receptors within Cultured Rat Cardiomyocytes

Melatonin, the pineal gland hormone, provides entrainment of many circadian rhythms to the ambient light/dark cycle. Recently, cardiovascular studies have demostrated melatonin interactions with many physiological processes and diseases, such as hypertension and cardiopathologies. Although membrane melatonin receptors (MT1, MT2) and the transcriptional factor ROR alpha have been reported to be expressed in the heart, there is no evidence of the cell-type expressing receptors as well as the possible role of melatonin on the expression of the circadian clock of cardiomyocytes, which play an important role in cardiac metabolism and function. Therefore, the aim of this study was to evaluate the mRNA and protein expressions of MT1, MT2, and ROR alpha and to determine whether melatonin directly influences expression of circadian clocks within cultured rat cardiomyocytes. Adult rat cardiomyocyte cultures were created, and the cells were stimulated with 1 nM melatonin or vehicle. Gene expressions were assayed by real-time polymerase chain reaction (PCR). The mRNA and protein expressions of membrane melatonin receptors and RORa were established within adult rat cardiomyocytes. Two hours of melatonin stimulation did not alter the expression pattern of the analyzed genes. However, given at the proper time, melatonin kept Rev-erb alpha expression chronically high, specifically 12 h after melatonin treatment, avoiding the rhythmic decline of Rev-erb alpha mRNA. The blockage of MT1 and MT2 by luzindole did not alter the observed melatonin-induced expression of Rev-erb alpha mRNA, suggesting the nonparticipation of MT1 and MT2 on the melatonin effect within cardiomyocytes. It is possible to speculate that melatonin, in adult rat cardiomyocytes, may play an important role in the light signal transduction to peripheral organs, such as the heart, modulating its intrinsic rhythmicity. (Author correspondence: cipolla@icb.usp.br)

Rev-erb beta regulates the expression of genes involved in lipid absorption in skeletal muscle cells - Evidence for cross-talk between orphan nuclear receptors and myokines

Rev-erbbeta is an orphan nuclear receptor that selectively blocks trans-activation mediated by the retinoic acid-related orphan receptor-alpha (RORalpha). RORalpha has been implicated in the regulation of high density lipoprotein cholesterol, lipid homeostasis, and inflammation. Rev-erbbeta and RORalpha are expressed in similar tissues, including skeletal muscle; however, the pathophysiological function of Rev-erbbeta has remained obscure. We hypothesize from the similar expression patterns, target genes, and overlapping cognate sequences of these nuclear receptors that Rev-erbbeta regulates lipid metabolism in skeletal muscle. This lean tissue accounts for > 30% of total body weight and 50% of energy expenditure. Moreover, this metabolically demanding tissue is a primary site of glucose disposal, fatty acid oxidation, and cholesterol efflux. Consequently, muscle has a significant role in insulin sensitivity, obesity, and the blood-lipid profile. We utilize ectopic expression in skeletal muscle cells to understand the regulatory role of Rev-erbbeta in this major mass peripheral tissue. Exogenous expression of a dominant negative version of mouse Rev-erbbeta decreases the expression of many genes involved in fatty acid/lipid absorption (including Cd36, and Fabp-3 and -4). Interestingly, we observed a robust induction (> 15-fold) in mRNA expression of interleukin-6, an exercise-induced myokine that regulates energy expenditure and inflammation. Furthermore, we observed the dramatic repression (> 20- fold) of myostatin mRNA, another myokine that is a negative regulator of muscle hypertrophy and hyperplasia that impacts on body fat accumulation. This study implicates Rev-erbbeta in the control of lipid and energy homoeostasis in skeletal muscle. In conclusion, we speculate that selective modulators of Rev-erbbeta may have therapeutic utility in the treatment of dyslipidemia and regulation of muscle growth.

International Union of Pharmacology. LXVI. Orphan nuclear receptors

Half of the members of the nuclear receptors superfamily are so-called orphan receptors because the identity of their ligand, if any, is unknown. Because of their important biological roles, the study of orphan receptors has attracted much attention recently and has resulted in rapid advances that have helped in the discovery of novel signaling pathways. In this review we present the main features of orphan receptors, discuss the structure of their ligand-binding domains and their biological functions. The paradoxical existence of a pharmacology of orphan receptors, a rapidly growing and innovative field, is highlighted.

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.