N.-H. Holstein-Rathlou

The Role of L- and T-Type Calcium Channels in Local and Remote Calcium Responses in Rat Mesenteric Terminal Arterioles

Background/Aims: The roles of intercellular communication and T-type versus L-type voltage-dependent Ca2+ channels (VDCCs) in conducted vasoconstriction to local KCl-induced depolarization were investigated in mesenteric arterioles. Methods: Ratiometric Ca2+ imaging (R) using Fura-PE3 with micro-ejection of depolarizing KCl solution and VDCC blockers, and immunohistochemical and RT-PCR techniques were applied to isolated rat mesenteric terminal arterioles (n = 71 from 47 rats; intraluminal diameter: 24 ± 1 μm; length: 550–700 μm). Results: Local application of KCl (at 0 μm) led to local (ΔR = 0.54) and remote (ΔR = 0.17 at 500 μm) increases in intracellular Ca2+. Remote Ca2+ responses were inhibited by the gap junction uncouplers carbenoxolone and palmitoleic acid. CaV1.2, CaV3.1 and CaV3.2 channels were immunolocalized in vascular smooth muscle cells and CaV3.2 in adjacent endothelial cells. Local and remote Ca2+ responses were inhibited by bath application of L- and T-type blockers [nifedipine, NNC 55-0396 and R(–)-efonidipine]. Remote Ca2+ responses (500 μm) were not affected by abolishing Ca2+ entry at an intermediate position on the arterioles (at 200–300 μm) using micro-application of VDCC blockers. Conclusion: Both L- and T-type channels mediate Ca2+ entry during conducted vasoconstriction to local KCl in mesenteric arterioles. However, these channels do not participate in the conduction process per se.

Renal Albumin Excretion. Twin Studies Identify Influences of Heredity, Environment, and Adrenergic Pathway Polymorphism

Albumin excretion marks early glomerular injury in hypertension. This study investigated heritability of albumin excretion in twin pairs and its genetic determination by adrenergic pathway polymorphism. Genetic associations used single nucleotide polymorphisms at adrenergic pathway loci spanning catecholamine biosynthesis, storage, catabolism, receptor action, and postreceptor signal transduction. We studied 134 single nucleotide polymorphisms at 46 loci for a total of >51 000 genotypes. Albumin excretion heritability was 45.2±7.4% (P=2×10−7), and the phenotype aggregated significantly with adrenergic, renal, metabolic, and hemodynamic traits. In the adrenergic system, excretions of both norepinephrine and epinephrine correlated with albumin. In the kidney, albumin excretion correlated with glomerular and tubular traits (Na+ and K+ excretion; fractional excretion of Na+ and Li+). Albumin excretion shared genetic determination (genetic covariance) with epinephrine excretion, and environmental determination with glomerular filtration rate and electrolyte intake/excretion. Albumin excretion associated with polymorphisms at multiple points in the adrenergic pathway: catecholamine biosynthesis (tyrosine hydroxylase), catabolism (monoamine oxidase A), storage/release (chromogranin A), receptor target (dopamine D1 receptor), and postreceptor signal transduction (sorting nexin 13 and rho kinase). Epistasis (gene-by-gene interaction) occurred between alleles at rho kinase, tyrosine hydroxylase, chromogranin A, and sorting nexin 13. Dopamine D1 receptor polymorphism showed pleiotropic effects on both albumin and dopamine excretion. These studies establish new roles for heredity and environment in albumin excretion. Urinary excretions of albumin and catecholamines are highly heritable, and their parallel suggests adrenergic mediation of early glomerular permeability alterations. Albumin excretion is influenced by multiple adrenergic pathway genes and is, thus, polygenic. Such functional links between adrenergic activity and glomerular injury suggest novel approaches to its prediction, prevention, diagnosis, and treatment.

Application of fast orthogonal search to linear and nonlinear stochastic systems

Standard deterministic autoregressive moving average (ARMA) models consider prediction errors to be unexplain able noise sources. The accuracy of the estimated ARMA model parameters depends on producing minimum prediction errors. In this study, an accurate algorithm is developed for estimating linear and nonlinear stochastic ARMA model parameters by using a method known as fast orthogonal search, with an extended model containing prediction errors as part of the model estimation process. The extended algorithm uses fast orthogonal search in a two-step procedure in which deterministic terms in the non-linear difference equation model are first identified and then reestimated, this time in a model containing the prediction errors. Since the extended algorithm uses an orthogonal procedure, together with automatic model order selection criteria, the significant model terms are estimated efficiently and accurately. The model order selection criteria developed for the extended algorithm are also crucial in obtaining accurate parameter estimates. Several simulated examples are presented to demonstrate the efficacy of the algorithm.

Double-wavelet approach to studying the modulation properties of nonstationary multimode dynamics

On the basis of double-wavelet analysis, the paper proposes a method to study interactions in the form of frequency and amplitude modulation in nonstationary multimode data series. Special emphasis is given to the problem of quantifying the strength of modulation for a fast signal by a coexisting slower dynamics and to its physiological interpretation. Application of the approach is demonstrated for a number of model systems, including a model that generates chaotic dynamics. The approach is then applied to proximal tubular pressure data from rat nephrons in order to estimate the degree to which the myogenic dynamics of the afferent arteriole is modulated by the slower tubulo-glomerular dynamics. Our analysis reveals a significantly stronger interaction between the two mechanisms in spontaneously hypertensive rats than in normotensive rats.

Robust nonlinear autoregressive moving average model parameter estimation using stochastic recurrent artificial neural networks.

AbstractIn this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate model predictions. Furthermore, we compare the performance of the new approach to that of the deterministic recurrent neural network approach. Using this simple two-step procedure, we obtain more robust model predictions than with the deterministic recurrent neural network approach despite the presence of significant amounts of either dynamic or measurement noise in the output signal. The comparison between the deterministic and stochastic recurrent neural network approaches is furthered by applying both approaches to experimentally obtained renal blood pressure and flow signals.

Na+-independent, nifedipine-resistant rat afferent arteriolar Ca2+ responses to noradrenaline: possible role of TRPC channels.

Aim:  In rat afferent arterioles we investigated the role of Na+ entry in noradrenaline (NA)‐induced depolarization and voltage‐dependent Ca2+ entry together with the importance of the transient receptor potential channel (TRPC) subfamily for non‐voltage‐dependent Ca2+ entry.

Multinephron dynamics on the renal vascular network

Tubuloglomerular feedback (TGF) and the myogenic mechanism combine in each nephron to regulate blood flow and glomerular filtration rate. Both mechanisms are nonlinear, generate self-sustained oscillations, and interact as their signals converge on arteriolar smooth muscle, forming a regulatory ensemble. Ensembles may synchronize. Smooth muscle cells in the ensemble depolarize periodically, generating electrical signals that propagate along the vascular network. We developed a mathematical model of a nephron-vascular network, with 16 versions of a single nephron model containing representations of both mechanisms in the regulatory ensemble, to examine the effects of network structure on nephron synchronization. Symmetry, as a property of a network, facilitates synchronization. Nephrons received blood from a symmetric electrically conductive vascular tree. Symmetry was created by using identical nephron models at each of the 16 sites and symmetry breaking by varying nephron length. The symmetric model achieved synchronization of all elements in the network. As little as 1% variation in nephron length caused extensive desynchronization, although synchronization was maintained in small nephron clusters. In-phase synchronization predominated among nephrons separated by one or three vascular nodes and antiphase synchronization for five or seven nodes of separation. Nephron dynamics were irregular and contained low-frequency fluctuations. Results are consistent with simultaneous blood flow measurements in multiple nephrons. An interaction between electrical signals propagated through the network to cause synchronization; variation in vascular pressure at vessel bifurcations was a principal cause of desynchronization. The results suggest that the vasculature supplies blood to nephrons but also engages in robust information transfer.

Synchronization of tubular pressure oscillations in interacting nephrons

Abstract The pressure and flow regulation in the individual functional unit of the kidney (the nephron) tends to operate in an unstable regime. For normal rats, the regulation displays regular self-sustained oscillations, but for rats with high blood pressure the oscillations become chaotic. We explain the mechanisms responsible for this behavior and discuss the involved bifurcations. Experimental data show that neighboring nephrons adjust their pressure and flow regulation in accordance with one another. For rats with normal blood pressure, in-phase as well as anti-phase synchronization can be observed. For spontaneously hypertensive rats, indications of chaotic phase synchronization are found. Accounting for a hermodynamics as well as for a vascular coupling between nephrons that share a common interlobular artery, we present a model of the interaction of the pressure and flow regulations between adjacent nephrons. It is shown that this model, with physiologically realistic parameter values, can reproduce the different types of experimentally observed synchronization, including multistability and partial phase synchronization with respect to the slow and fast dynamics.

Norepinephrine inhibits intercellular coupling in rat cardiomyocytes by ubiquitination of connexin43 gap junctions

Abstract Gαq-stimulation reduces intercellular coupling within 10 min via a decrease in the membrane lipid phosphatidylinositol-4,5-bisphosphate (PIP2), but the mechanism is unknown. Here we show that uncoupling in rat cardiomyocytes after stimulation of α-adrenergic Gαq-coupled receptors with norepinephrine is prevented by proteasomal and lysosomal inhibitors, suggesting that internalization and possibly degradation of connexin43 (Cx43) is involved. Uncoupling was accompanied by increased Triton X-100 solubility of Cx43, which is considered a measure of the non-junctional pool of Cx43. However, inhibition of the proteasome and lysosome further increased solubility while preserving coupling, suggesting that communicating gap junctions can be part of the soluble fraction. Ubiquitination of Cx43 was also increased, and Cx43 co-immunoprecipitated with the ubiquitin ligase Nedd4. Conclusions: Norepinephrine increases ubiquitination of Cx43 in cardiomyocytes, possibly via Nedd4. We suggest that Cx43 is subsequently internalized, which is preceded by acquired solubility in Triton X-100, which does not lead to uncoupling per se.

Nonlinear analysis of renal autoregulation in rats using principal dynamic modes

AbstractThis article presents results of the use of a novel methodology employing principal dynamic modes (PDM) for modeling the nonlinear dynamics of renal autoregulation in rats. The analyzed experimental data are broadband (0–0.5 Hz) blood pressure-flow data generated by pseudorandom forcing and collected in normotensive and hypertensive rats for two levels of pressure forcing (as measured by the standard deviation of the pressure fluctuation). The PDMs are computed from first-order and second-order kernel estimates obtained from the data via the Laguerre expansion technique. The results demonstrate that two PDMs suffice for obtaining a satisfactory nonlinear dynamic model of renal autoregulation under these conditions, for both normotensive and hypertensive rats. Furthermore, the two PDMs appear to correspond to the two main autoregulatory mechanisms: the first to the myogenic and the second to the tubuloglomerular feedback (TGF) mechanism. This allows the study of the separate contributions of the two mechanisms to the autoregulatory response dynamics, as well as the effects of the level of pressure forcing and hypertension on the two distinct autoregulatory mechanisms. It is shown that the myogenic mechanism has a larger contribution and is affected only slightly, while the TGF mechanism is affected considerably by increasing pressure forcing or hypertension (the emergence of a second resonant peak and the decreased relative contribution to the response flow signal).