Resveratrol inhibits K(v)2.2 currents through the estrogen receptor GPR30-mediated PKC pathway.

Resveratrol (REV) is a naturally occurring phytoalexin that inhibits neuronal K⁺ channels; however, the molecular mechanisms behind the effects of REV and the relevant α-subunit are not well defined. With the use of patch-clamp technique, cultured cerebellar granule cells, and HEK-293 cells transfected with the K(v)2.1 and K(v)2.2 α-subunits, we investigated the effect of REV on K(v)2.1 and K(v)2.2 α-subunits. Our data demonstrated that REV significantly suppressed Kv2.2 but not Kv2.1 currents with a fast, reversible, and mildly concentration-dependent manner and shifted the activation or inactivation curve of Kv2.2 channels. Activating or inhibiting the cAMP/PKA pathway did not abolish the inhibition of K(v)2.2 current by REV. In contrast, activation of PKC with phorbol 12-myristate 13-acetate mimicked the inhibitory effect of REV on K(v)2.2 by modifying the activation or inactivation properties of Kv2.2 channels and eliminated any further inhibition by REV. PKC and PKC-α inhibitor completely eliminated the REV-induced inhibition of K(v)2.2. Moreover, the effect of REV on K(v)2.2 was reduced by preincubation with antagonists of GPR30 receptor and shRNA for GPR30 receptor. Western blotting results indicated that the levels of PKC-α and PKC-ß were significantly increased in response to REV application. Our data reveal, for the first time, that REV inhibited K(v)2.2 currents through PKC-dependent pathways and a nongenomic action of the oestrogen receptor GPR30.

Co-training based virtual sample generation for solving the small sample size problem in process industry.

With the development of industrialization, the production scale and complexity of process industries are getting larger and larger. But, limited by the small amounts of samples and the uneven sample distribution in the process industry, it is difficult to establish accurate and efficient data-driven soft sensor models to predict some variables. To further develop the application of soft sensor models, generating new virtual samples based on the original sample distribution to extend the sample set is an ideal approach to solve this problem. In this paper, a novel virtual sample generation method based on the co-training of two K-Nearest Neighbor (KNN) models is proposed. First, according to the sparse parameter, sparse regions in each dimension of the feature space are identified. Second, the input features of virtual samples are generated in these sparse regions by performing interpolation operations. Third, the outputs of virtual samples are predicted by double KNN regressors based on co-training. The qualified virtual samples are screened and the model is updated using these virtual samples to improve the prediction accuracy of the double KNN models. To verify the effectiveness and superiority of the proposed virtual sample generation method based on the co-training (CTVSG), case studies are conducted using two standard functions and a Purified Terephthalic Acid (PTA) industrial dataset, where the effectiveness of CTVSG is confirmed.

The antidepressant citalopram inhibits delayed rectifier outward K⁺ current in mouse cortical neurons.

Citalopram, a selective serotonin (5-HT) reuptake inhibitor (SSRI) as well as an antidepressant, is thought to exert its effects by increasing synaptic 5-HT levels. However, few studies have addressed the possibility that citalopram has other molecular mechanisms of action. We examined the effects of citalopram on delayed rectifier outward K(+) current (I(K) ) in mouse cortical neurons. Extracellular citalopram reversibly inhibited I(K) in a dose-dependent manner and significantly shifted both steady-state activation and inactivation curves toward hyperpolarization. Neither 5-HT itself nor antagonists of 5-HT and dopamine receptors could abolish citalopram-induced inhibition of I(K) . In addition, intracellular application of GTPγ-S similarly failed to prevent the inhibition of I(K) by citalopram. When applied intracellularly, citalopram had no effect on I(K) and did not influence the reduction of I(K) induced by extracellular citalopram. The effect of citalopram was use dependent, but not frequency dependent, and it did not require channel opening. Electrophysiological recordings in acute cortical slice showed that citalopram significantly reduced the action potential (AP) firing frequency of cortical neurons and increased action potential duration (APD). The selective Kv2.1 subunit blocker Jingzhaotoxin-III (JZTX-III) did not abolish citalopram-induced I(K) inhibition. Transfection of HEK293 cells with Kv2.1 or Kv2.2 constructs indicated that citalopram mainly inhibited Kv2.2 current. We suggest that citalopram-induced inhibition of I(K) in mouse cortical neurons is independent of G-protein-coupled receptors and might exert its antidepressant effects by enhancing presynaptic efficiency. Our results may help to explain some of the unknown therapeutic effects of citalopram.

Enhanced virtual sample generation based on manifold features: Applications to developing soft sensor using small data.

In the process industry, it is essential to establish a data-driven soft sensor to predict the key variable that is difficult to online measure directly. The accuracy performance of data-driven soft sensors relies heavily on data. Unfortunately, it is hard to acquire sufficient and informative data from the samples with limited number, which is called as the small sample problem. For handling the small sample problem, it is a good solution to generating virtual samples according to the distribution of original data. This paper proposes an enhanced method of virtual sample generation utilizing manifold features to develop soft sensors using small data. First, T-Distribution Stochastic Neighbor Embedding (t-SNE) is utilized to extract the features of input data. The main idea of generating virtual samples is to use the interpolation algorithm to obtain virtual t-SNE input features and then the random forest algorithm is utilized to get the virtual outputs using virtual t-SNE input features. Finally, virtual samples using the proposed t-SNE based virtual sample generation (t-SNE-VSG) can be achieved. For the sake of confirming the effectiveness and feasibility of the presented t-SNE-VSG, a standard data set is first used. What is more, a small data set from an actual industrial process of Purified Terephthalic Acid is used to establish a soft sensor model. The results from simulations show that the accuracy performance of the soft sensor established with small data can be effectively improved by adding the virtual samples generated by t-SNE-VSG. In addition, t-SNE-VSG achieves superior accuracy to state-of-the-art virtual sample generation methods.

Novel double-layer bidirectional LSTM network with improved attention mechanism for predicting energy consumption.

For power generation management and power system dispatching, it is of big significance to predict the consumption of electric energy accurately. For the sake of improving the prediction accuracy of power consumption, taking the complex features of time series data into consideration, a novel neural network sandwich structure with an improved attention mechanism is inserted into the double-layer bidirectional long short-term memory network shortened as A-DBLSTM is put forward in this article. In A-DBLSTM, compared with traditional attention mechanism, the presented attention mechanism focuses on different features in each time unit and the A-DBLLSTM network extracts time information in sequence. The parameter optimization of A-DBLSTM is based on the method of particle swarm optimization (PSO). For confirming the effectiveness and feasibility of A-DBLSTM, case studies using two datasets of the hourly temperature values and power loads between 2012 and 2014 and the electric energy consumption are carried out. The experimental results indicate that the presented A-DBLSTM with the novel sandwich network structure achieves superior performance in the aspects of the mean square error, root mean square, the average absolute error and the mean absolute percentage error to other advanced methods. What is more, the factors that have the greatest impact on the prediction performance can be found through analyzing the heatmap of the attention layer.

Strain-boosted hyperoxic graphene oxide efficiently loading and improving performances of microcystinase.

Harmful Microcystis blooms (HMBs) and microcystins (MCs) that are produced by Microcystis seriously threaten water ecosystems and human health. This study demonstrates an eco-friendly strategy for simultaneous removal of MCs and HMBs by adopting unique hyperoxic graphene oxides (HGOs) as carrier and pure microcystinase A (PMlrA) as connecting bridge to form stable HGOs@MlrA composite. After oxidation, HGOs yield inherent structural strain effects for boosting the immobilization of MlrA by material characterization and density functional theory calculations. HGO5 exhibits higher loading capacities for crude MlrA (1,559 mg·g-1) and pure MlrA (1,659 mg·g-1). Moreover, the performances of HGO5@MlrA composite, including the capability of removing MCs and HMBs, the ecological and human safety compared to MlrA or HGO5 treatment alone, have been studied. These results indicate that HGO5 can be used as a promising candidate material to effectively improve the application potential of MlrA in the simultaneous removal of MCs and HMBs.

Potent Anti-SARS-CoV-2 Efficacy of COVID-19 Hyperimmune Globulin from Vaccine-Immunized Plasma.

Coronavirus disease 2019 (COVID-19) remains a global public health threat. Hence, more effective and specific antivirals are urgently needed. Here, COVID-19 hyperimmune globulin (COVID-HIG), a passive immunotherapy, is prepared from the plasma of healthy donors vaccinated with BBIBP-CorV (Sinopharm COVID-19 vaccine). COVID-HIG shows high-affinity binding to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein, the receptor-binding domain (RBD), the N-terminal domain of the S protein, and the nucleocapsid protein; and blocks RBD binding to human angiotensin-converting enzyme 2 (hACE2). Pseudotyped and authentic virus-based assays show that COVID-HIG displays broad-spectrum neutralization effects on a wide variety of SARS-CoV-2 variants, including D614G, Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Kappa (B.1.617.1), Delta (B.1.617.2), and Omicron (B.1.1.529) in vitro. However, a significant reduction in the neutralization titer is detected against Beta, Delta, and Omicron variants. Additionally, assessments of the prophylactic and treatment efficacy of COVID-HIG in an Adv5-hACE2-transduced IFNAR-/- mouse model of SARS-CoV-2 infection show significantly reduced weight loss, lung viral loads, and lung pathological injury. Moreover, COVID-HIG exhibits neutralization potency similar to that of anti-SARS-CoV-2 hyperimmune globulin from pooled convalescent plasma. Overall, the results demonstrate the potential of COVID-HIG against SARS-CoV-2 infection and provide reference for subsequent clinical trials.

Brain natriuretic peptide modulates the delayed rectifier outward K(+) current and promotes the proliferation of mouse Schwann cells.

Brain natriuretic peptide (BNP) may act as a neuromodulator via its associated receptors (natriuretic peptide receptors, NPRs) in the central nervous system (CNS), but few studies have reported its activity in the peripheral nervous system (PNS). In this study, we observed that BNP increased the tetraethylammonium chloride (TEA)-sensitive delayed rectifier outward potassium current (I(K)) in mouse Schwann cells (SCs) using whole-cell recording techniques. At concentrations of 1-100 nM, BNP reversibly activated I(K) in a dose-dependent manner, with modulating its steady-state activation and inactivation properties. The effect of BNP on I(K) was abolished by preincubation with the specific antagonist of NPR-A, and could not be mimicked by application of NPR-C agonist. These results were supported by immunocytochemical findings indicating that NPR-A was expressed in SCs. The application of 8-Br-guanosine 3',5'-monophosphate (8-Br-cGMP) mimicked the effect of BNP on I(K), but BNP was unable to further increase I(K) after the application of cyclic guanosine monophosphate (cGMP). Genistein blocked I(K) and also completely eliminated the effects of BNP and cGMP on I(K). The selective K(V)2.1 subunit blocker, Jingzhaotoxin-III (JZTX-III), reduced I(K) amplitude by 30%, but did not abolish the increase effect of BNP on I(K) amplitude. In addition, BNP significantly stimulated SCs proliferation and this effect could be partly inhibited by TEA. Together these results suggest that BNP modulated I(K) probably via cGMP- and tyrosine kinase-dependent pathways by activation of NPR-A. This effect of BNP on I(K) in SCs might partly explain its effect on cell proliferation.

Novel manifold learning based virtual sample generation for optimizing soft sensor with small data.

Due to the extremely complex mechanism and strong non-linear characteristics of industrial processes, data-driven soft sensor technologies play a key role in the intelligent measurement of process industries. However, the information of the collected process data in the steady stage is quite limited and unreliable, causing the small sample problem. As a result, it becomes an intractable challenge to catch the nature of the process and build accurate soft sensor models. To solve this problem, this paper proposes a novel manifold learning based virtual sample generation method (Isomap-VSG) to generate feasible virtual samples in the information gaps for supplementing the original small sample space. To find data sparse regions reasonably, one kind of manifold learning methods called Isomap is used to visualize process data with high dimension. Then virtual samples can be generated by the interpolation method and extreme learning machine. The simulation results on a standard dataset and a real-world application demonstrate that, compared with other advanced methods, the proposed Isomap-VSG method can achieve better performance in terms of generating feasible virtual samples and improving the accuracy of soft sensor models using limited samples.

Zhuifeng Tougu capsules improve rheumatoid arthritis symptoms in rats by regulating the toll-like receptor 2/4-nuclear factor kappa-B signaling pathway.

OBJECTIVE: To investigate the efficacy of Zhuifeng tougu capsules (, ZFTG) in the treatment of rheumatoid arthritis (RA) in rats and study its mechanism, focusing on the toll-like receptor 2/4-nuclear factor kappa-B (TLR2/4-NF-κB) signaling pathway. METHODS: Type Ⅱ collagen and an artificial climate box were used to construct the rat model of collagen-induced arthritis with wind-cold-dampness arthralgia syndrome. The rats were divided randomly into a control group, wind-cold-dampness syndrome model group, and high-, medium-, and low-dose ZFTG groups. The methotrexate (MTX) control group was treated with the corresponding drug intervention for 28 d. The joint temperature, pain threshold, joint swelling degree, and arthritis index (AI) score were measured. The production of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and rheumatoid factors (RFs) in the blood was detected by enzyme-linked immunosorbent assay. The protein expression of TLR2, TLR4, and NF-κB in synovial tissues was detected by Western blotting, and the mRNA expression of TLR2, TLR4, and NF-κB was detected by real-time polymerase chain reaction. RESULTS: Compared with the model group, the joint temperature in each treatment group, the MTX control group, and MTX group recovered, the degree of foot swelling, pain threshold, AI score decreased, serum CRP, ESR, RF level and the levels of TLR2, TLR4, and NF-κB in synovial tissue were decreased (P < 0.05). Among them, the curative effect in the medium-dose and MTX groups was more evident (P < 0.01). CONCLUSION: ZFTG has a significant effect on RA in rats, and its mechanism may involve regulating CRP levels, the ESR, and RFs via the TLR2/4-NF-κB signaling pathway.

Amoxapine inhibits the delayed rectifier outward K+ current in mouse cortical neurons via cAMP/protein kinase A pathways.

Ion channels are known to be modulated by antidepressant drugs, but the molecular mechanisms are not known. We have shown that the antidepressant drug amoxapine suppresses rectifier outward K(+) (I(K)) currents in mouse cortical neurons. At a concentration of 10 to 500 muM, amoxapine reversibly inhibited I(K) in a dose-dependent manner and modulated both steady-state activation and inactivation properties. The application of forskolin or dibutyryl cAMP mimicked the inhibitory effect of amoxapine on I(K) and abolished further inhibition by amoxapine. N-[2-(p-Bromocinnamylamino)ethyl]-5-iso-quinolinesulphonamide (H-89), a protein kinase A (PKA) inhibitor, augmented I(K) amplitudes and completely eliminated amoxapine inhibition of I(K). Amoxapine was also found to significantly increase intracellular cAMP levels. The effects of amoxapine on I(K) were abolished by preincubation with 5-hydroxytryptamine (5-HT) and the antagonists of 5-HT(2) receptor. Moreover, intracellular application of guanosine 5'-[gammathio]-triphosphate increased I(K) amplitudes and prevented amoxapine-induced inhibition. The selective Kv2.1 subunit blocker Jingzhaotoxin-III reduced I(K) amplitudes by 30% and also significantly abolished the inhibitory effect of amoxapine. Together these results suggest that amoxapine inhibits I(K) in mouse cortical neurons by cAMP/PKA-dependent pathway associated with the 5-HT receptor, and suggest that the Kv2.1 alpha-subunit may be the target for this inhibition.

Modulation of muscle rNaV1.4 Na+ channel isoform by arachidonic acid and its non-metabolized analog.

Arachidonic acid (AA) and its metabolic products are important second messengers which exert many biological actions, including modulation of various ion channels. However, the blockage of muscle Na(+) channel isoforms by AA has not been examined in detail. Here, we investigated the modulating effects of AA on muscle rNa(V)1.4 isoforms expressed in human embryonic kidney 293 cells. The results revealed that AA has both activation and inhibitory effects on rNa(V)1.4 currents depending on the depolarizing potential: AA increased the rNa(V)1.4 current evoked by a depolarization of -30 or -40 mV, but significantly decreased the rNa(V)1.4 current evoked by a depolarization of membrane potential over -10 mV. At concentrations of 1-500 microM, the inhibitory effect on the rNa(V)1.4 current induced by AA was dose-dependent and reversible. In addition to modulating the amplitude of the rNa(V)1.4 current, AA significantly modulated the steady-state activation and inactivation properties of rNa(V)1.4 channels. Furthermore, treatment with AA resulted in a fairly slow recovery of the rNa(V)1.4 channel from inactivation; however, the inhibitory effect of AA was not changed by repetitive pulses or by changing frequency. The effect of AA on rNa(V)1.4 currents was completely mimicked by ETYA, the non-metabolized analog of AA. Our data demonstrated that AA, but not the metabolic products of AA, can voltage-dependent modulate rNa(V)1.4 currents.

Cyproheptadine Regulates Pyramidal Neuron Excitability in Mouse Medial Prefrontal Cortex.

Cyproheptadine (CPH), a first-generation antihistamine, enhances the delayed rectifier outward K+ current (IK) in mouse cortical neurons through a sigma-1 receptor-mediated protein kinase A pathway. In this study, we aimed to determine the effects of CPH on neuronal excitability in current-clamped pyramidal neurons in mouse medial prefrontal cortex slices. CPH (10 µmol/L) significantly reduced the current density required to generate action potentials (APs) and increased the instantaneous frequency evoked by a depolarizing current. CPH also depolarized the resting membrane potential (RMP), decreased the delay time to elicit an AP, and reduced the spike threshold potential. This effect of CPH was mimicked by a sigma-1 receptor agonist and eliminated by an antagonist. Application of tetraethylammonium (TEA) to block IK channels hyperpolarized the RMP and reduced the instantaneous frequency of APs. TEA eliminated the effects of CPH on AP frequency and delay time, but had no effect on spike threshold or RMP. The current-voltage relationship showed that CPH increased the membrane depolarization in response to positive current pulses and hyperpolarization in response to negative current pulses, suggesting that other types of membrane ion channels might also be affected by CPH. These results suggest that CPH increases the excitability of medial prefrontal cortex neurons by regulating TEA-sensitive IK channels as well as other TEA-insensitive K+ channels, probably ID and inward-rectifier Kir channels. This effect of CPH may explain its apparent clinical efficacy as an antidepressant and antipsychotic.

Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance.

A robust hybrid model integrating enhanced inputs based extreme learning machine with PLSR (PLSR-EIELM) and its application to intelligent measurement.

In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons and the over-fitting phenomenon. First, a traditional extreme learning machine (ELM) is selected. Second, a method of randomly assigning is applied to the weights between the input layer and the hidden layer, and then the nonlinear transformation for independent variables can be obtained from the output of the hidden layer neurons. Especially, the original input variables are regarded as enhanced inputs; then the enhanced inputs and the nonlinear transformed variables are tied together as the whole independent variables. In this way, the PLSR can be carried out to identify the PLS components not only from the nonlinear transformed variables but also from the original input variables, which can remove the correlation among the whole independent variables and the expected outputs. Finally, the optimal relationship model of the whole independent variables with the expected outputs can be achieved by using PLSR. Thus, the PLSR-EIELM model is developed. Then the PLSR-EIELM model served as an intelligent measurement tool for the key variables of the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. The experimental results show that the predictive accuracy of PLSR-EIELM is stable, which indicate that PLSR-EIELM has good robust character. Moreover, compared with ELM, PLSR, hierarchical ELM (HELM), and PLSR-ELM, PLSR-EIELM can achieve much smaller predicted relative errors in these two applications.

Exposure to extremely low-frequency electromagnetic fields modulates Na+ currents in rat cerebellar granule cells through increase of AA/PGE2 and EP receptor-mediated cAMP/PKA pathway.

Although the modulation of Ca(2+) channel activity by extremely low-frequency electromagnetic fields (ELF-EMF) has been studied previously, few reports have addressed the effects of such fields on the activity of voltage-activated Na(+) channels (Na(v)). Here, we investigated the effects of ELF-EMF on Na(v) activity in rat cerebellar granule cells (GCs). Our results reveal that exposing cerebellar GCs to ELF-EMF for 10-60 min significantly increased Na(v) currents (I(Na)) by 30-125% in a time- and intensity-dependent manner. The Na(v) channel steady-state activation curve, but not the steady-state inactivation curve, was significantly shifted (by 5.2 mV) towards hyperpolarization by ELF-EMF stimulation. This phenomenon is similar to the effect of intracellular application of arachidonic acid (AA) and prostaglandin E(2) (PGE(2)) on I(Na) in cerebellar GCs. Increases in intracellular AA, PGE(2) and phosphorylated PKA levels in cerebellar GCs were observed following ELF-EMF exposure. Western blottings indicated that the Na(V) 1.2 protein on the cerebellar GCs membrane was increased, the total expression levels of Na(V) 1.2 protein were not affected after exposure to ELF-EMF. Cyclooxygenase inhibitors and PGE(2) receptor (EP) antagonists were able to eliminate this ELF-EMF-induced increase in phosphorylated PKA and I(Na). In addition, ELF-EMF exposure significantly enhanced the activity of PLA(2) in cerebellar GCs but did not affect COX-1 or COX-2 activity. Together, these data demonstrate for the first time that neuronal I(Na) is significantly increased by ELF-EMF exposure via a cPLA2 AA PGE(2) EP receptors PKA signaling pathway.

Sigma-1 receptor agonists directly inhibit Nav1.2/1.4 channels.

(+)-SKF 10047 (N-allyl-normetazocine) is a prototypic and specific sigma-1 receptor agonist that has been used extensively to study the function of sigma-1 receptors. (+)-SKF 10047 inhibits K(+), Na(+) and Ca2+ channels via sigma-1 receptor activation. We found that (+)-SKF 10047 inhibited Na(V)1.2 and Na(V)1.4 channels independently of sigma-1 receptor activation. (+)-SKF 10047 equally inhibited Na(V)1.2/1.4 channel currents in HEK293T cells with abundant sigma-1 receptor expression and in COS-7 cells, which barely express sigma-1 receptors. The sigma-1 receptor antagonists BD 1063,BD 1047 and NE-100 did not block the inhibitory effects of (+)-SKF-10047. Blocking of the PKA, PKC and G-protein pathways did not affect (+)-SKF 10047 inhibition of Na(V)1.2 channel currents. The sigma-1 receptor agonists Dextromethorphan (DM) and 1,3-di-o-tolyl-guanidine (DTG) also inhibited Na(V)1.2 currents through a sigma-1 receptor-independent pathway. The (+)-SKF 10047 inhibition of Na(V)1.2 currents was use- and frequency-dependent. Point mutations demonstrated the importance of Phe(1764) and Tyr(1771) in the IV-segment 6 domain of the Na(V)1.2 channel and Phe(1579) in the Na(V)1.4 channel for (+)-SKF 10047 inhibition. In conclusion, our results suggest that sigma-1 receptor agonists directly inhibit Na(V)1.2/1.4 channels and that these interactions should be given special attention for future sigma-1 receptor function studies.

Cyproheptadine enhances the I(K) of mouse cortical neurons through sigma-1 receptor-mediated intracellular signal pathway.

Cyproheptadine (CPH) is a histamine- and serotonin-receptor antagonist, and its effects are observed recently in the modulation of multiple intracellular signals. In this study, we used cortical neurons and HEK-293 cells transfected with Kv2.1 α-subunit to address whether CPH modify neural voltage-gated K(+) channels by a mechanism independent of its serotonergic and histaminergic properties. Our results demonstrate that intracellularly delivered CPH increased the I(K) by reducing the activity of protein kinas A (PKA). Inhibition of G(i) eliminated the CPH-induced effect on both the I(K) and PKA. Blocking of 5-HT-, M-, D(2)-, H(1)- or H(2)-type GPCR receptors with relevant antagonists did not eliminate the CPH-induced effect on the I(K). Antagonists of the sigma-1 receptor, however, blocked the effect of CPH. Moreover, the inhibition of sigma-1 by siRNA knockdown significantly reduced the CPH-induced effect on the I(K). On the contrary, sigma-1 receptor agonist mimicked the effects of CPH on the induction of I(K). A ligand-receptor binding assay indicated that CPH bound to the sigma-1 receptor. Similar effect of CPH were obtained from HEK-293 cells transfected with the α-subunit of Kv2.1. In overall, we reveal for the first time that CPH enhances the I(K) by modulating activity of PKA, and that the associated activation of the sigma-1 receptor/G(i)-protein pathway might be involved. Our findings illustrate an uncharacterized effect of CPH on neuron excitability through the I(K), which is independent of histamine H(1) and serotonin receptors.

Bradykinin inhibits the transient outward K+ current in mouse Schwann cells via the cAMP/PKA pathway.

Bradykinin (BK) is an endogenous peptide with diverse biological actions and is considered to be an important mediator of the inflammatory response in both the peripheral and the central nervous systems. BK has attracted recent interest as a potential mediator of K(+) conductance, Cl(-) channels, and Ca(2+)-activated K(+) channels. However, few reports have associated BK with the voltage-gated K(+) current. In this study, we demonstrated that BK suppressed the transient outward potassium current (I(A)) in mouse Schwann cells using whole cell recording techniques. At a concentration of 0.1 muM to 5 muM, BK reversibly inhibited I(A) in a dose-dependent manner with the modulation of steady-state activation and inactivation properties. The effect of BK on I(A) current was abolished after preincubation with a B(2) receptor antagonist but could not be eliminated by B(1) receptor antagonist. Intracellular application of GTP-gammaS induced an irreversible decrease in I(A), and the inhibition of G(s) using NF449 provoked a gradual augmentation in I(A) and eliminated the BK-induced effect on I(A,) while the G(i)/(o) antagonist NF023 did not. The application of forskolin or dibutyryl-cAMP mimicked the inhibitory effect of BK on I(A) and abolished the BK-induced effect on I(A). H-89, an inhibitor of PKA, augmented I(A) amplitude and completely eliminated the BK-induced inhibitory effect on I(A). In contrast, activation of PKC by PMA augmented I(A) amplitude. A cAMP assay revealed that BK significantly increased intracellular cAMP level. It is therefore concluded that BK inhibits the I(A) current in Schwann cells by cAMP/PKA-dependent pathways via activation of the B(2) receptor.