Novel Roles for Kv7 Channels in Shaping Histamine-Induced Contractions and Bradykinin-Dependent Relaxations in Pig Coronary Arteries.

Voltage-gated Kv7 channels are inhibited by agonists of Gq-protein-coupled receptors, such as histamine. Recent works have provided evidence that inhibition of vascular Kv7 channels may trigger vessel contractions. In this study, we investigated how Kv7 activity modulates the histamine-induced contractions in “healthy” and metabolic syndrome (MetS) pig right coronary arteries (CAs). We performed isometric tension and immunohistochemical studies with domestic, lean Ossabaw, and MetS Ossabaw pig CAs. We found that neither the Kv7.2/Kv7.4/Kv7.5 activator ML213 nor the general Kv7 inhibitor XE991 altered the tension of CA rings under preload, indicating that vascular Kv7 channels are likely inactive in the preloaded rings. Conversely, ML213 potently dilated histamine-pre-contracted CAs, suggesting that Kv7 channels are activated during histamine applications and yet partially inhibited by histamine. Immunohistochemistry analysis revealed strong Kv7.4 immunostaining in the medial and intimal layers of the CA wall, whereas Kv7.5 immunostaining intensity was strong in the intimal but weak in the medial layers. The medial Kv7 immunostaining was significantly weaker in MetS Ossabaw CAs as compared to lean Ossabaw or domestic CAs. Consistently, histamine-pre-contracted MetS Ossabaw CAs exhibited attenuated ML213-dependent dilations. In domestic pig CAs, where medial Kv7 immunostaining intensity was stronger, histamine-induced contractions spontaneously decayed to ~31% of the peak amplitude within 4 minutes. Oppositely, in Ossabaw CAs, where Kv7 immunostaining intensity was weaker, the histamine-induced contractions were more sustained. XE991 pretreatment significantly slowed the decay rate of histamine-induced contractions in domestic CAs, supporting the hypothesis that increased Kv7 activity correlates with a faster rate of histamine-induced contraction decay. Alternatively, XE991 significantly decreased the amplitude of bradykinin-dependent dilations in pre-contracted CAs. We propose that in CAs, a decreased expression or a loss of function of Kv7 channels may lead to sustained histamine-induced contractions and reduced endothelium-dependent relaxation, both risk factors for coronary spasm

Perception of Misalignment States for Sky Survey Telescopes with the Digital Twin and the Deep Neural Networks

Sky survey telescopes play a critical role in modern astronomy, but misalignment of their optical elements can introduce significant variations in point spread functions, leading to reduced data quality. To address this, we need a method to obtain misalignment states, aiding in the reconstruction of accurate point spread functions for data processing methods or facilitating adjustments of optical components for improved image quality. Since sky survey telescopes consist of many optical elements, they result in a vast array of potential misalignment states, some of which are intricately coupled, posing detection challenges. However, by continuously adjusting the misalignment states of optical elements, we can disentangle coupled states. Based on this principle, we propose a deep neural network to extract misalignment states from continuously varying point spread functions in different field of views. To ensure sufficient and diverse training data, we recommend employing a digital twin to obtain data for neural network training. Additionally, we introduce the state graph to store misalignment data and explore complex relationships between misalignment states and corresponding point spread functions, guiding the generation of training data from experiments. Once trained, the neural network estimates misalignment states from observation data, regardless of the impacts caused by atmospheric turbulence, noise, and limited spatial sampling rates in the detector. The method proposed in this paper could be used to provide prior information for the active optics system and the optical system alignment.Comment: The aforementioned submission has been accepted by Optics Express. We kindly request any feedback or comments to be directed to the corresponding author, Peng Jia ([email protected]), or the second corresponding author, Zhengyang Li ([email protected]). Please note that Zhengyang is currently stationed in the South Antarctica and will not be available until after February 1st, 202

Molecular Determinants of the Sensitivity to Gq/11-Phospholipase C-dependent Gating, Gd3+ Potentiation, and Ca2+ Permeability in the Transient Receptor Potential Canonical Type 5 (TRPC5) Channel

Transient receptor potential canonical type 5 (TRPC5) is a Ca2+-permeable cation channel that is highly expressed in the brain and is implicated in motor coordination, innate fear behavior, and seizure genesis. The channel is activated by a signal downstream of the G-protein-coupled receptor (GPCR)-Gq/11-phospholipase C (PLC) pathway. In this study we aimed to identify the molecular mechanisms involved in regulating TRPC5 activity. We report that Arg-593, a residue located in the E4 loop near the TRPC5 extracellular Gd3+ binding site, is critical for conferring the sensitivity to GPCR-Gq/11-PLC-dependent gating on TRPC5. Indeed, guanosine 5'-O-(thiotriphosphate) and GPCR agonists only weakly activate the TRPC5R593A mutant, whereas the addition of Gd3+ rescues the mutant's sensitivity to GPCR-Gq/11-PLC-dependent gating. Computer modeling suggests that Arg-593 may cross-bridge the E3 and E4 loops, forming the "molecular fulcrum." While validating the model using site-directed mutagenesis, we found that the Tyr-542 residue is critical for establishing a functional Gd3+ binding site, the Tyr-541 residue participates in fine-tuning Gd3+-sensitivity, and that the Asn-584 residue determines Ca2+ permeability of the TRPC5 channel. This is the first report providing molecular insights into the molecular mechanisms regulating the sensitivity to GPCR-Gq/11-PLC-dependent gating of a receptor-operated channel

PKC-dependent Phosphorylation of the H1 Histamine Receptor Modulates TRPC6 Activity

Transient receptor potential canonical 6 (TRPC6) is a cation selective, DAG-regulated, Ca2+-permeable channel activated by the agonists of Gq-protein-coupled heptahelical receptors. Dysfunctions of TRPC6 are implicated in the pathogenesis of various cardiovascular and kidney conditions such as vasospasm and glomerulosclerosis. When stimulated by agonists of the histamine H1 receptor (H1R), TRPC6 activity decays to the baseline despite the continuous presence of the agonist. In this study, we examined whether H1R desensitization contributes to regulating the decay rate of TRPC6 activity upon receptor stimulation. We employed the HEK expression system and a biosensor allowing us to simultaneously detect the changes in intracellular diacylglycerol (DAG) and Ca2+ concentrations. We found that the histamine-induced DAG response was biphasic, in which a transient peak was followed by maintained elevated plateau, suggesting that desensitization of H1R takes place in the presence of histamine. The application of PKC inhibitor Gö6983 slowed the decay rate of intracellular DAG concentration. Activation of the mouse H1R mutant lacking a putative PKC phosphorylation site, Ser399, responsible for the receptor desensitization, resulted in a prolonged intracellular DAG increase and greater Mn2+ influx through the TRPC6 channel. Thus, our data support the hypothesis that PKC-dependent H1R phosphorylation leads to a reduced production of intracellular DAG that contributes to TRPC6 activity regulation

Fast and Efficient Boolean Matrix Factorization by Geometric Segmentation

Boolean matrix has been used to represent digital information in many fields, including bank transaction, crime records, natural language processing, protein-protein interaction, etc. Boolean matrix factorization (BMF) aims to find an approximation of a binary matrix as the Boolean product of two low rank Boolean matrices, which could generate vast amount of information for the patterns of relationships between the features and samples. Inspired by binary matrix permutation theories and geometric segmentation, we developed a fast and efficient BMF approach, called MEBF (Median Expansion for Boolean Factorization). Overall, MEBF adopted a heuristic approach to locate binary patterns presented as submatrices that are dense in 1's. At each iteration, MEBF permutates the rows and columns such that the permutated matrix is approximately Upper Triangular-Like (UTL) with so-called Simultaneous Consecutive-ones Property (SC1P). The largest submatrix dense in 1 would lie on the upper triangular area of the permutated matrix, and its location was determined based on a geometric segmentation of a triangular. We compared MEBF with other state of the art approaches on data scenarios with different density and noise levels. MEBF demonstrated superior performances in lower reconstruction error, and higher computational efficiency, as well as more accurate density patterns than popular methods such as ASSO, PANDA and Message Passing. We demonstrated the application of MEBF on both binary and non-binary data sets, and revealed its further potential in knowledge retrieving and data denoising

Mechanisms underlying capsaicin effects in canine coronary artery: implications for coronary spasm

AIMS: The TRPV1, transient receptor potential vanilloid type 1, agonist capsaicin is considered to be beneficial for cardiovascular health because it dilates coronary arteries through an endothelial-dependent mechanism and may slow atheroma progression. However, recent reports indicate that high doses of capsaicin may constrict coronary arterioles and even provoke myocardial infarction. Thus far, the mechanisms by which TRPV1 activation modulates coronary vascular tone remain poorly understood. This investigation examined whether there is a synergistic interplay between locally acting vasoconstrictive pro-inflammatory hormones (autacoids) and capsaicin effects in the coronary circulation. METHODS AND RESULTS: Experiments were performed in canine conduit coronary artery rings and isolated smooth muscle cells (CASMCs). Isometric tension measurements revealed that 1-10 μM capsaicin alone did not affect resting tension of coronary artery rings. In contrast, in endothelium-intact rings pre-contracted with a Gq/11-coupled FP/TP (prostaglandin F/thromboxane) receptor agonist, prostaglandin F2α (PGF2α; 10 μM), capsaicin first induced transient dilation that was followed by sustained contraction. In endothelium-denuded rings pre-contracted with PGF2α or thromboxane analogue U46619 (1 μM, a TP receptor agonist), capsaicin induced only sustained contraction. Blockers of the TP receptor or TRPV1 significantly inhibited capsaicin effects, but these were still observed in the presence of 50 μM nifedipine and 70 mM KCl. Capsaicin also potentiated 20 mM KCl-induced contractions. Fluorescence imaging experiments in CASMCs revealed that the Gq/11-phospholipase C (PLC)-protein kinase C (PKC) and Ca(2+)-PLC-PKC pathways are likely involved in sensitizing CASMC TRPV1 channels. CONCLUSION: Capsaicin alone does not cause contractions in conduit canine coronary artery; however, pre-treatment with pro-inflammatory prostaglandin-thromboxane agonists may unmask capsaicin's vasoconstrictive potential

Long-term spironolactone treatment reduces coronary TRPC expression, vasoconstriction, and atherosclerosis in metabolic syndrome pigs

Coronary transient receptor potential canonical (TRPC) channel expression is elevated in metabolic syndrome (MetS). However, differential contribution of TRPCs to coronary pathology in MetS is not fully elucidated. We investigated the roles of TRPC1 and TRPC6 isoforms in coronary arteries of MetS pigs and determined whether long-term treatment with a mineralocorticoid receptor inhibitor, spironolactone, attenuates coronary TRPC expression and associated dysfunctions. MetS coronary arteries exhibited significant atherosclerosis, endothelial dysfunction, and increased histamine-induced contractions. Immunohistochemical studies revealed that TRPC6 immunostaining was significantly greater in the medial layer of MetS pig coronary arteries compared to that in Lean pigs, whereas little TRPC6 immunostaining was found in atheromas. Conversely, TRPC1 immunostaining was weak in the medial layer but strong in MetS atheromas, where it was predominantly localized to macrophages. Spironolactone treatment significantly decreased coronary TRPC expression and dysfunctions in MetS pigs. In vivo targeted delivery of the dominant-negative (DN)-TRPC6 cDNA to the coronary wall reduced histamine-induced calcium transients in the MetS coronary artery medial layer, implying a role for TRPC6 in mediating calcium influx in MetS coronary smooth muscles. Monocyte adhesion was increased in Lean pig coronary arteries cultured in the presence of aldosterone; and spironolactone antagonized this effect, suggesting that coronary mineralocorticoid receptor activation may regulate macrophage infiltration. TRPC1 expression in atheroma macrophages was associated with advanced atherosclerosis, whereas medial TRPC6 upregulation correlated with increased histamine-induced calcium transients and coronary contractility. We propose that long-term spironolactone treatment may be a therapeutic strategy to decrease TRPC expression and coronary pathology associated with MetS

Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence

In this paper, we propose a Spatial Robust Mixture Regression model to investigate the relationship between a response variable and a set of explanatory variables over the spatial domain, assuming that the relationships may exhibit complex spatially dynamic patterns that cannot be captured by constant regression coefficients. Our method integrates the robust finite mixture Gaussian regression model with spatial constraints, to simultaneously handle the spatial non-stationarity, local homogeneity, and outlier contaminations. Compared with existing spatial regression models, our proposed model assumes the existence a few distinct regression models that are estimated based on observations that exhibit similar response-predictor relationships. As such, the proposed model not only accounts for non-stationarity in the spatial trend, but also clusters observations into a few distinct and homogenous groups. This provides an advantage on interpretation with a few stationary sub-processes identified that capture the predominant relationships between response and predictor variables. Moreover, the proposed method incorporates robust procedures to handle contaminations from both regression outliers and spatial outliers. By doing so, we robustly segment the spatial domain into distinct local regions with similar regression coefficients, and sporadic locations that are purely outliers. Rigorous statistical hypothesis testing procedure has been designed to test the significance of such segmentation. Experimental results on many synthetic and real-world datasets demonstrate the robustness, accuracy, and effectiveness of our proposed method, compared with other robust finite mixture regression, spatial regression and spatial segmentation methods

Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence

In this paper, we propose a Spatial Robust Mixture Regression model to investigate the relationship between a response variable and a set of explanatory variables over the spatial domain, assuming that the relationships may exhibit complex spatially dynamic patterns that cannot be captured by constant regression coefficients. Our method integrates the robust finite mixture Gaussian regression model with spatial constraints, to simultaneously handle the spatial non-stationarity, local homogeneity, and outlier contaminations. Compared with existing spatial regression models, our proposed model assumes the existence a few distinct regression models that are estimated based on observations that exhibit similar response-predictor relationships. As such, the proposed model not only accounts for non-stationarity in the spatial trend, but also clusters observations into a few distinct and homogenous groups. This provides an advantage on interpretation with a few stationary sub-processes identified that capture the predominant relationships between response and predictor variables. Moreover, the proposed method incorporates robust procedures to handle contaminations from both regression outliers and spatial outliers. By doing so, we robustly segment the spatial domain into distinct local regions with similar regression coefficients, and sporadic locations that are purely outliers. Rigorous statistical hypothesis testing procedure has been designed to test the significance of such segmentation. Experimental results on many synthetic and real-world datasets demonstrate the robustness, accuracy, and effectiveness of our proposed method, compared with other robust finite mixture regression, spatial regression and spatial segmentation methods