Induction of placental heme oxygenase-1 is protective against TNFα-induced cytotoxicity and promotes vessel relaxation

Background: Pregnancy is characterized by an inflammatory-like process and this may be exacerbated in preeclampsia. The heme oxygenase (HO) enzymes generate carbon monoxide (CO) that induces blood vessel relaxation and biliverdin that acts as an endogenous antioxidant. Materials and Methods: We examined the expression and localization of HO-1 and HO-2 in normal and preeclamptic placenta using reverse transcription polymerase chain reaction (RT-PCR), RNase protection assay, immunoblotting and immunohistochemistry. In addition, the effect of HO activation on tumor necrosis factor-alpha (TNF) induced placental damage and on feto-placental circulation was studied. Results: We provide the first evidence for the role of HO as an endogenous placental factor involved with cytoprotection and placental blood vessel relaxation. HO-1 was significantly higher at term, compared with first trimester placentae indicating its role in placental vascular development and regulation. HO-1 predominantly localized in the extravascular connective tissue that forms the perivascular contractile sheath around the developing blood vessels. HO-2 was localized in the capillaries, as well as the villous stroma, with weak staining of trophoblast. Induction of HO-1 caused a significant attenuation of TNF-mediated cellular damage in placental villous explants, as assessed by lactate dehydrogenase leakage (p 0.01). HO-1 protein was significantly reduced in placentae from pregnancies complicated with preeclampsia, compared with gestationally matched normal pregnancies. This suggests that the impairment of HO-1 activation may compromise the compensatory mechanism and predispose the placenta to cellular injury and subsequent maternal endothelial cell activation. Isometric contractility studies showed that hemin reduced vascular tension by 61% in U46619-preconstricted placental arteries. Hemininduced vessel relaxation and CO production was inhibited by HO inhibitor, tin protoporphyrin IX. Conclusions: Our findings establish HO-1 as an endogenous system that offers protection against cytotoxic damage in the placenta, identifies the HO-CO pathway to regulate feto-placental circulation and provides a new approach to study the disease of preeclampsia.

Does the MK2-dependent production of TNFα regulate mGluR-dependent synaptic plasticity?

The molecular mechanisms and signalling cascades that trigger the induction of group I metabotropic glutamate receptor (GI-mGluR)-dependent long-term depression (LTD) have been the subject of intensive investigation for nearly two decades. The generation of genetically modified animals has played a crucial role in elucidating the involvement of key molecules regulating the induction and maintenance of mGluR-LTD. In this review we will discuss the requirement of the newly discovered MAPKAPK-2 (MK2) and MAPKAPK-3 (MK3) signalling cascade in regulating GI-mGluR-LTD. Recently, it has been shown that the absence of MK2 impaired the induction of GI-mGluR-dependent LTD, an effect that is caused by reduced internalization of AMPA receptors (AMPAR). As the MK2 cascade directly regulates tumour necrosis factor alpha (TNFα) production, this review will examine the evidence that the release of TNFα acts to regulate glutamate receptor expression and therefore may play a functional role in the impairment of GI-mGluRdependent LTD and the cognitive deficits observed in MK2/3 double knockout animals. The strong links of increased TNFα production in both aging and neurodegenerative disease could implicate the action of MK2 in these processes.

Association of TNF-α Gene Variants With Clinical Manifestation of Cystic Fibrosis Patients of Iranian Azeri Turkish Ethnicity

Background: Cystic fibrosis (CF), a life-limiting autosomal recessive disorder, is considered a monogenic disease that is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. According to several studies, mutation analysis of the cystic fibrosis transmembrane conductance regulator (CFTR) gene alone is insufficient to predict the phenotypic manifestations observed in cystic fibrosis (CF) patients. In addition, some patients with a milder CF phenotype do not carry any pathogenic mutation. Tumor Necrosis Factor-alpha (TNF-α) contributes to the pathophysiology of CF by causing cachexia. There is a reverse association between TNF-α concentration in patient's sputum and their pulmonary function. Objectives: To assess the effect of non-CFTR genes on the clinical phenotype of CF, two polymorphic sites (-1031T/C and -308G/A) of the TNF-α gene, as a modifier, were studied. Patients and Methods: Focusing on the lung and gastrointestinal involvement as well as the poor growth, we first investigated the role of TNF-α gene in the clinical manifestation of CF. Furthermore, based on the hypothesis that the cumulative effect of specific alleles of multiple CF modifier genes, such as TNF-α, may create the final phenotype, we also investigated the potential role of TNF-α in non-classic CF patients without a known pathogenic mutation. In all, 80 CF patients and 157 healthy control subjects of Azeri Turkish ethnicity were studied by the PCR–RFLP method. The chi-square test with Yates' correction and Fisher's exact test were used for statistical analysis. Results: The allele and genotype distribution of the investigated polymorphisms, and their associated haplotypes were similar in all groups. Conclusions: There was no evidence that supported the association of TNF-α gene polymorphisms with non-classic CF disease or the clinical presentation of classic CF.

Elevated concentration of TNF-a induces trophoblast differentiation in mouse blastocyst outgrowths

Elevated expression of tumour necrosis factora (TNF-a) is associated with adverse pregnancy outcome. This study has examined the expression of TNF-a and its receptors (TNF-Rs) by mouse blastocysts and blastocyst outgrowths from day 4 to 9.5 of pregnancy and investigated the effects of elevated TNF-a on the inner cell mass (ICM) and trophoblast cells of blastocyst outgrowths. RTPCR demonstrated TNF-a mRNA expression from day 7.5 to 9.5, TNF-R1 from day 6.5 to 9.5 and TNF-R2 from day 5.5 to 7.5 of pregnancy, and in situ hybridisation revealed the trophoblast giant cells (TGCs) of the early placenta as the site of TNF-a expression. Day 4 blastocysts were cultured in a physiologically high concentration of TNF-a (100 ng/ml) for 72 h to the outgrowth stage and then compared to blastocysts cultured in media alone. TNF-a-treated blastocyst outgrowths exhibited a significant reduction in ICM cells (mean € SD 23.90€10.42 vs 9.37€7.45, t-test, P<0.0001) with no significant change in the numbers of trophoblast cells (19.97€8.14 vs 21.73€7.79, t-test, P=0.39). Within the trophoblast cell population, the TNF-a-treated outgrowths exhibited a significant increase in multinucleated cells (14.10€5.53 vs 6.37€5.80, t-test, P<0.0001) and a corresponding significant decrease in mononucleated cells (5.87€3.60 vs 15.37€5.87, t-test, P<0.0001). In summary, this study describes the expression of TNF-a and its receptors during the peri-implantation period in the mouse. It also reports that elevated TNF-a restricts ICM proliferation in the blastocyst and changes the ratio of mononucleated to multinucleated trophoblast cells. These findings suggest a mechanism by which increased

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.