Channel Interaction Research Articles

Spread of activation and interaction between channels with multi-channel optogenetic stimulation in the mouse cochlea

For individuals with severe to profound hearing loss resulting from irreversibly damaged hair cells, cochlear implants can be used to restore hearing by delivering electrical stimulation directly to the spiral ganglion neurons. However, current spread lowers the spatial resolution of neural activation. Since light can be easily confined, optogenetics is a technique that has the potential to improve the precision of neural activation, whereby visible light is used to stimulate neurons that are modified with light-sensitive opsins. This study compares the spread of neural activity across the inferior colliculus of the auditory midbrain during electrical and optical stimulation in the cochlea of acutely deafened mice with opsin-modified spiral ganglion neurons (H134R variant of the channelrhodopsin-2). Monopolar electrical stimulation was delivered via each of four 0.2 mm wide platinum electrode rings at 0.6 mm centre-to-centre spacing, whereas 453 nm wavelength light was delivered via each of five 0.22 × 0.27 mm micro-light emitting diodes (LEDs) at 0.52 mm centre-to-centre spacing. Channel interactions were also quantified by threshold changes during simultaneous stimulation by pairs of electrodes or micro-LEDs at different distances between the electrodes (0.6, 1.2 and 1.8 mm) or micro-LEDs (0.52, 1.04, 1.56 and 2.08 mm). The spread of activation resulting from single channel optical stimulation was approximately half that of monopolar electrical stimulation as measured at two levels of discrimination above threshold (p<0.001), whereas there was no significant difference between optical stimulation in opsin-modified deafened mice and pure tone acoustic stimulation in normal-hearing mice. During simultaneous micro-LED stimulation, there were minimal channel interactions for all micro-LED spacings tested. For neighbouring micro-LEDs/electrodes, the relative influence on threshold was 13-fold less for optical stimulation compared electrical stimulation (p<0.05). The outcomes of this study show that the higher spatial precision of optogenetic stimulation results in reduced channel interaction compared to electrical stimulation, which could increase the number of independent channels in a cochlear implant. Increased spatial resolution and the ability to activate more than one channel simultaneously could lead to better speech perception in cochlear implant recipients.

Exploring the potential of channel interactions for image restoration

Image restoration aims to reconstruct a clear image from a degraded observation. Convolutional neural networks have achieved promising performance on this task. The usage of Transformer has recently made significant advancements in state-of-the-art performance by modeling long-range dependencies. However, these deep architectures primarily concentrate on enhancing representation learning for the spatial dimension, neglecting the significance of channel interactions. In this paper, we explore the potential of channel interactions for restoring images through our proposal of a dual-domain channel attention mechanism. To be specific, channel attention in the spatial domain allows each channel to amass valuable signals from adjacent channels under the guidance of learned dynamic weights. In order to effectively exploit the significant difference in infrequency between degraded and clean image pairs, we develop the implicit frequency domain channel attention to facilitate the integration of information from different frequencies. Extensive experiments demonstrate that the proposed network, dubbed ChaIR, achieves state-of-the-art performance on 13 benchmark datasets for five image restoration tasks, including image dehazing, image motion/defocus deblurring, image desnowing, and image deraining.

Effects of spectral smearing on speech understanding and masking release in simulated bilateral cochlear implants.

Differences in spectro-temporal degradation may explain some variability in cochlear implant users' speech outcomes. The present study employs vocoder simulations on listeners with typical hearing to evaluate how differences in degree of channel interaction across ears affects spatial speech recognition. Speech recognition thresholds and spatial release from masking were measured in 16 normal-hearing subjects listening to simulated bilateral cochlear implants. 16-channel sine-vocoded speech simulated limited, broad, or mixed channel interaction, in dichotic and diotic target-masker conditions, across ears. Thresholds were highest with broad channel interaction in both ears but improved when interaction decreased in one ear and again in both ears. Masking release was apparent across conditions. Results from this simulation study on listeners with typical hearing show that channel interaction may impact speech recognition more than masking release, and may have implications for the effects of channel interaction on cochlear implant users' speech recognition outcomes.

YOLO-SCL: a lightweight detection model for citrus psyllid based on spatial channel interaction.

Efficient and accurate detection and providing early warning for citrus psyllids is crucial as they are the primary vector of citrus huanglongbing. In this study, we created a dataset comprising images of citrus psyllids in natural environments and proposed a lightweight detection model based on the spatial channel interaction. First, the YOLO-SCL model was based on the YOLOv5s architecture, which uses an efficient channel attention module to perform local channel attention on the inputs in the recursive gated convolutional modules to achieve a combination of global spatial and local channel interactions, improving the model's ability to express the features of the critical regions of small targets. Second, the lightweight design of the 21st layer C3 module in the neck network of the YOLO-SCL model and the small target feature information were retained to the maximum extent by deleting the two convolutional layers, whereas the number of parameters was reduced to improve the detection accuracy of the model. Third, with the detection accuracy of the YOLO-SCL model as the objective function, the black widow optimization algorithm was used to optimize the hyperparameters of the YOLO-SCL model, and the iterative mechanism of swarm intelligence was used to further improve the model performance. The experimental results showed that the YOLO-SCL model achieved a mAP@0.5 of 97.07% for citrus psyllids, which was 1.18% higher than that achieved using conventional YOLOv5s model. Meanwhile, the number of parameters and computation amount of the YOLO-SCL model are 6.92 M and 15.5 GFlops, respectively, which are 14.25% and 2.52% lower than those of the conventional YOLOv5s model. In addition, after using the black widow optimization algorithm to optimize the hyperparameters, the mAP@0.5 of the YOLO-SCL model for citrus psyllid improved to 97.18%, making it more suitable for the natural environments in which citrus psyllids are to be detected. The experimental results showed that the YOLO-SCL model has good detection accuracy for citrus psyllids, and the model was ported to the Jetson AGX Xavier edge computing platform, with an average processing time of 38.8 ms for a single-frame image and a power consumption of 16.85 W. This study provides a new technological solution for the safety of citrus production.

Microfluidic Printing of Vertically-Oriented Nanosheets/MOFs Hetero-Interface for Intensive Pseudocapacitive Storage.

Efficient manufacture of electroactive vertically-oriented nanosheets with enhanced electrolyte mass diffusion and strong interfacial redox dynamics is critical for realizing high energy density of miniature supercapacitor (SC), but still challenging. Herein, microfluidic droplet printing is developed to controllably construct vertically-oriented graphene/ZIF-67 hetero-microsphere (VAGS/ZIF-67), where the ZIF-67 is coordinately grown on vertically-oriented graphene framework via Co─O─C bonds. The VAGS/ZIF-67 shows ordered porous channel, high electroactivity and strong interfacial interaction, providing rapid electrolyte diffusion dynamics and high faradaic capacitance in KOH solution (1674 F g-1 , 1004 C g-1 ), which are verified by computational fluid dynamics (CFD) and density functional theory (DFT). Moreover, the VAGS/ZIF-67 based SC exhibits large energy density (100Wh kg-1 ), excellent durability (10000 cycles and high/low temperature), and robust power-supply applications in portable electronics.

ICH S7B In Vitro Assays Do Not Address Mechanisms of QTC Prolongation for Peptides and Proteins - Data in Support of Not Needing Dedicated QTC Studies.

Current cardiac safety testing focuses on detecting drug-induced QTC prolongation as a surrogate for risk of Torsade de Pointes. The nonclinical strategy, described in International Conference on Harmonization (ICH) S7B, includes in vitro assessment of hERG block or ventricular repolarization delay and in vivo QT prolongation. Several studies have reported predictive values of ICH S7B results for clinical QTC outcomes for small molecules; none has examined peptides and proteins other than monoclonal antibodies. To address this knowledge gap, information for peptides and proteins submitted to the US Food and Drug Administration (FDA) was collected. Results of hERG assays, ventricular repolarization assays, and in vivo QT assessment were compared with clinical QTC study outcomes. The results show that 14% clinical QTC studies for approved and investigational products failed to exclude 10-ms QTC prolongation. Clinical QTC prolongation for these molecules lacked concentration-dependence which is expected for hERG block-mediated mechanism or QTC prolongation could not be excluded due to characterization in the clinical study. The hERG and ventricular repolarization assays do not identify clinical QTC prolongation potential for peptides and proteins. Lack of alignment between hERG and ventricular repolarization assay results and clinical QTC outcomes suggests that the mechanisms of QTC prolongation by some peptides and proteins are unrelated to direct cardiac ion channel block. Similar to large targeted proteins and monoclonal antibodies, peptides and proteins regardless of size have a low likelihood of direct cardiac ion channel interactions. This characteristic supports waiving the requirement for thorough QT assessment for products comprised of naturally occurring amino acids unless proarrhythmia potential is suggested by nonclinical or clinical data.

Impact Pressure Influence of Flood on Bridge Deck under Sediment Deposition Conditions: An Experimental Study

This paper investigates the impact of sediment deposition and inflow conditions on horizontal impact pressure and frequency analysis of bridge deck vibrations during flooding. Flooding-induced pressure and vibrations contribute to bridge collapse, and sediment deposition influences water flow and impact pressure. The study explores the relationship between sediment deposition height and impact pressure, revealing a significant increase as sediment approaches 50% of bridge deck clearance. Sediment amplifies impact pressure response to flow velocity changes. The dimensionless sediment deposition height has a greater influence on impact pressure compared to the inflow Froude number. Two distinct frequencies, dominant and secondary, are identified for impact pressure and water level fluctuations. Dominant frequencies positively correlate with sediment deposition height and Froude number, indicating an increasing trend. Secondary frequencies remain stable (0.31–0.58 Hz). These findings enhance understanding of flow dynamics and bridge–flow interaction in sediment-deposited channels, providing theoretical support for evaluating and managing disasters related to bridges in such environments. Overall, this research contributes to the field of bridge engineering and supports improved design and maintenance practices for bridges exposed to sediment-deposited channels.

The role of ion channels in T cell function and disease.

T lymphocytes (T cells) are an important sub-group of cells in our immune system responsible for cell-mediated adaptive responses and maintaining immune homeostasis. Abnormalities in T cell function, lead the way to the persistence of infection, impaired immunosurveillance, lack of suppression of cancer growth, and autoimmune diseases. Ion channels play a critical role in the regulation of T cell signaling and cellular function and are often overlooked and understudied. Little is known about the ion "channelome" and the interaction of ion channels in immune cells. This review aims to summarize the published data on the impact of ion channels on T cell function and disease. The importance of ion channels in health and disease plus the fact they are easily accessible by virtue of being expressed on the surface of plasma membranes makes them excellent drug targets.

GRP-YOLOv5: An Improved Bearing Defect Detection Algorithm Based on YOLOv5.

Currently, most chemical transmission equipment relies on bearings to support rotating shafts and to transmit power. However, bearing defects can lead to a series of failures in the equipment, resulting in reduced production efficiency. To prevent such occurrences, this paper proposes an improved bearing defect detection algorithm based on YOLOv5. Firstly, to mitigate the influence of the similarity between bearing defects and non-defective regions on the detection performance, gamma transformation is introduced in the preprocessing stage of the model to adjust the image's grayscale and contrast. Secondly, to better capture the details and semantic information of the defects, this approach incorporates the ResC2Net model with a residual-like structure during the feature-extraction stage, enabling more nonlinear transformations and channel interaction operations so as to enhance the model's perception and representation capabilities of the defect targets. Additionally, PConv convolution is added in the feature fusion part to increase the network depth and better capture the detailed information of defects while maintaining time complexity. The experimental results demonstrate that the GRP-YOLOv5 model achieves a mAP@0.5 of 93.5%, a mAP@0.5:0.95 of 52.7%, and has a model size of 25 MB. Compared to other experimental models, GRP-YOLOv5 exhibits excellent performance in bearing defect detection accuracy. However, the model's FPS (frames per second) performance is not satisfactory. Despite its small size of 25 MB, the processing speed is relatively slow, which may have some impact on real-time or high-throughput applications. This limitation should be considered in future research and in the optimization efforts to improve the overall performance of the model.

Neurobehavioral measures of coincidence anticipation timing.

Coincidence anticipation (CA) refers to the ability to coordinate responses to the arrival of a moving object. This study investigates the neurobehavioral processes that underlie CA through the measurement of electroencephalography (EEG) recorded during a CA task on a 17-foot plastic rail with evenly spaced LED lights. Participants responded at the anticipated moment a sequence of successively lit LEDs coincided with a stationary target. Healthy young adult participants (Mage = 21) performed six blocks with movement at 20, 30, or 40 mph and the direction either inbound or outbound relative to the participant. Behavioral results demonstrated a main effect of speed and an interaction between speed and direction, with outbound motion producing early responses and inbound motion producing delayed responses that increased at greater speeds. EEG demonstrated characteristic P1, N2, and P3-like visual evoked potentials (VEPs). VEP amplitudes revealed a significant direction by channel interaction for the P1, indicative of more medial responses for inbound motion. Significant laterality differences were present in the N2, whereas the P3 component produced significant main effects and interactions of speed and direction. This novel combination of three-dimensional CA with EEG demonstrates systematic brain responses that are tuned for motion speed and sensitive to different egocentric motion patterns thereby shedding new light on the mechanism of human visual-motor control.

Visualization and classification of Radar Emitter Pulse Sequences based on 2D feature map

With the development of modern electronic countermeasure technology, radar reconnaissance equipment receives pulse sequences of increasing density and complexity. Achieving concise as well as robust feature representation of Radar Emitter Pulse Sequences (REPS), and improving the classification and recognition performance of REPS signals have always been the focus at present. Current research did not consider the distribution information and co-information buried in REPS data. To solve this problem, we propose to visualize and classify REPS signals based on 2D feature map. First, we extract the Sequence Distribution Property (SDP) of REPS for spatial coding to obtain an encoded feature vector that is deformed into a 2D matrix. Three types of informative 2D matrices generated from REPS are combined into a color 2D feature map. Different from previous feature extraction methods, the proposed method can not only express the single sequence information concisely and accurately but also express the correlation of multiple parameter sequences synchronously in the interaction of different color channels. Second, based on the 2D feature map, we design a ‘L&FCN’ framework for classification, in which we fed the 2D feature map into a network composed of lower convolution neural layers and fully connected layers to judge the category and output recognition result. Finally, we put forward a novel strategy with integrating global and local segments’ information of REPS to train the network, making it converge with smaller classification errors. Simulation results verify the effectiveness and superiority of our method.

A Cascade Network for Pattern Recognition Based on Radar Signal Characteristics in Noisy Environments

Target recognition mainly focuses on three approaches: optical-image-based, echo-detection-based, and passive signal-analysis-based methods. Among them, the passive signal-based method is closely integrated with practical applications due to its strong environmental adaptability. Based on passive radar signal analysis, we design an “end-to-end” model that cascades a noise estimation network with a recognition network to identify working modes in noisy environments. The noise estimation network is implemented based on U-Net, which adopts a method of feature extraction and reconstruction to adaptively estimate the noise mapping level of the sample, which can help the recognition network to reduce noise interference. Focusing on the characteristics of radar signals, the recognition network is realized based on the multi-scale convolutional attention network (MSCANet). Firstly, deep group convolution is used to isolate the channel interaction in the shallow network. Then, through the multi-scale convolution module, the finer-grained features of the signal are extracted without increasing the complexity of the model. Finally, the self-attention mechanism is used to suppress the influence of low-correlation and negative-correlation channels and spaces. This method overcomes the problem of the conventional method being seriously disturbed by noise. We validated the proposed method in 81 kinds of noise environment, achieving an average accuracy of 94.65%. Additionally, we discussed the performance of six machine learning algorithms and four deep learning algorithms. Compared to these methods, the proposed MSCANet achieved an accuracy improvement of approximately 17%. Our method demonstrates better generalization and robustness.

Mechanistic understanding of KCNQ1 activating polyunsaturated fatty acid analogs.

The KCNQ1 channel is important for the repolarization phase of the cardiac action potential. Loss of function mutations in KCNQ1 can cause long QT syndrome (LQTS), which can lead to cardiac arrythmia and even sudden cardiac death. We have previously shown that polyunsaturated fatty acids (PUFAs) and PUFA analogs can activate the cardiac KCNQ1 channel, making them potential therapeutics for the treatment of LQTS. PUFAs bind to KCNQ1 at two different binding sites: one at the voltage sensor (Site I) and one at the pore (Site II). PUFA interaction at Site I shifts the voltage dependence of the channel to the left, while interaction at Site II increases maximal conductance. The PUFA analogs, linoleic-glycine and linoleic-tyrosine, are more effective than linoleic acid at Site I, but less effective at Site II. Using both simulations and experiments, we find that the larger head groups of linoleic-glycine and linoleic-tyrosine interact with more residues than the smaller linoleic acid at Site I. We propose that this will stabilize the negatively charged PUFA head group in a position to better interact electrostatically with the positively charges in the voltage sensor. In contrast, the larger head groups of linoleic-glycine and linoleic-tyrosine compared with linoleic acid prevent a close fit of these PUFA analogs in Site II, which is more confined. In addition, we identify several KCNQ1 residues as critical PUFA-analog binding residues, thereby providing molecular models of specific interactions between PUFA analogs and KCNQ1. These interactions will aid in future drug development based on PUFA-KCNQ1 channel interactions.

Intracellular Ca2+ signalling: unexpected new roles for the usual suspect.

Cytosolic Ca2+ signals are organized in complex spatial and temporal patterns that underlie their unique ability to regulate multiple cellular functions. Changes in intracellular Ca2+ concentration ([Ca2+]i) are finely tuned by the concerted interaction of membrane receptors and ion channels that introduce Ca2+ into the cytosol, Ca2+-dependent sensors and effectors that translate the elevation in [Ca2+]i into a biological output, and Ca2+-clearing mechanisms that return the [Ca2+]i to pre-stimulation levels and prevent cytotoxic Ca2+ overload. The assortment of the Ca2+ handling machinery varies among different cell types to generate intracellular Ca2+ signals that are selectively tailored to subserve specific functions. The advent of novel high-speed, 2D and 3D time-lapse imaging techniques, single-wavelength and genetic Ca2+ indicators, as well as the development of novel genetic engineering tools to manipulate single cells and whole animals, has shed novel light on the regulation of cellular activity by the Ca2+ handling machinery. A symposium organized within the framework of the 72nd Annual Meeting of the Italian Society of Physiology, held in Bari on 14-16th September 2022, has recently addressed many of the unexpected mechanisms whereby intracellular Ca2+ signalling regulates cellular fate in healthy and disease states. Herein, we present a report of this symposium, in which the following emerging topics were discussed: 1) Regulation of water reabsorption in the kidney by lysosomal Ca2+ release through Transient Receptor Potential Mucolipin 1 (TRPML1); 2) Endoplasmic reticulum-to-mitochondria Ca2+ transfer in Alzheimer's disease-related astroglial dysfunction; 3) The non-canonical role of TRP Melastatin 8 (TRPM8) as a Rap1A inhibitor in the definition of some cancer hallmarks; and 4) Non-genetic optical stimulation of Ca2+ signals in the cardiovascular system.

A detailed analysis of single-channel Nav 1.5 recordings does not reveal any cooperative gating.

Cardiac voltage-gated sodium (Na+ ) channels (Nav 1.5) are crucial for myocardial electrical excitation. Recent studies based on single-channel recordings have suggested that Na+ channels interact functionally and exhibit coupled gating. However, the analysis of such recordings frequently relies on manual interventions, which can lead to bias. Here, we developed an automated pipeline to de-trend and idealize single-channel currents, and assessed possible functional interactions in cell-attached patch clamp experiments in HEK293 cells expressing human Nav 1.5 channels as well as in adult mouse and rabbit ventricular cardiomyocytes. Our pipeline involved de-trending individual sweeps by linear optimization using a library of predefined functions, followed by digital filtering and baseline offset. Subsequently, the processed sweeps were idealized based on the idea that the ensemble average of the idealized current identified by thresholds between current levels reconstructs at best the ensemble average current from the de-trended sweeps. This reconstruction was achieved by non-linear optimization. To ascertain functional interactions, we examined the distribution of the numbers of open channels at every time point during the activation protocol and compared it to the distribution expected for independent channels. We also examined whether the channels tended to synchronize their openings and closings. However, we did not uncover any solid evidence of such interactions in our recordings. Rather, our results indicate that wild-type Nav 1.5 channels are independent entities or exhibit only very weak functional interactions that are probably irrelevant under physiological conditions. Nevertheless, our unbiased analysis will be important for further studies examining whether auxiliary proteins potentiate functional Na+ channel interactions. KEY POINTS: Nav 1.5 channels are critical for cardiac excitation. They are part of macromolecular interacting complexes, and it was previously suggested that two neighbouring channels may functionally interact and exhibit coupled gating. Manual interventions when processing single-channel recordings can lead to bias and inaccurate data interpretation. We developed an automated pipeline to de-trend and idealize single-channel currents and assessed possible functional interactions between Nav 1.5 channels in HEK293 cells and cardiomyocytes during activation protocols using the cell-attached patch clamp technique. In recordings consisting of up to 1000 sweeps from the same patch, our analysis did not reveal any evidence of functional interactions or coupled gating between wild-type Nav 1.5 channels. Our unbiased analysis may be useful in further studies examining how Na+ channel interactions are affected by mutations and auxiliary proteins.

HERG agonists pose challenges to web-based machine learning methods for prediction of drug-hERG channel interaction

Pharmacological blockade of the IKr channel (hERG) by diverse drugs in clinical use is associated with the Long QT Syndrome that can lead to life threatening arrhythmia. Various computational tools including machine learning models (MLM) for the prediction of hERG inhibition have been developed to facilitate the throughput screening of drugs in development and optimise thus the prediction of hERG liabilities. The use of MLM relies on large libraries of training compounds for the quantitative structure-activity relationship (QSAR) modelling of hERG inhibition. The focus on inhibition omits potential effects of hERG channel agonist molecules and their associated QT shortening risk. It is instructive, therefore, to consider how known hERG agonists are handled by MLM. Here, two highly developed online computational tools for the prediction of hERG liability, Pred-hERG and HergSPred were probed for their ability to detect hERG activator drug molecules as hERG interactors. In total, 73 hERG blockers were tested with both computational tools giving overall good predictions for hERG blockers with reported IC50s below Pred-hERG and HergSPred cut-off threshold for hERG inhibition. However, for compounds with reported IC50s above this threshold such as disopyramide or sotalol discrepancies were observed. HergSPred identified all 20 hERG agonists selected as interacting with the hERG channel. Further studies are warranted to improve online MLM prediction of hERG related cardiotoxicity, by explicitly taking into account channel agonism as well as inhibition.

Phosphorylation regulation of nitrogen, phosphorus, and potassium uptake systems in plants

The uptake of ammonium, nitrate, phosphorus, and potassium ions by roots is mediated by specific ion transporter or channel proteins, and protein phosphorylation regulation events occurring on these proteins and their regulators determine their ultimate activity. Elucidating the mechanism by which protein phosphorylation modification regulates nutrient uptake will advance plant breeding for high nutrient-use efficiency. In this review, it is concluded that the root nutrient absorption system is composed of several, but not all, members of a specific ion transporter or channel family. Under nutrient-starvation conditions, protein phosphorylation-based regulation of these proteins and associated transcription factors increases ion transporter- or channel-mediated nutrient uptake capacity via direct function activity enhancement, allowing more protein trafficking to the plasma membrane, by strengthening the interaction of transporters and channels with partner proteins, by increasing their protein stability, and by transcriptional activation. Under excessive nutrient conditions, protein phosphorylation-based regulation suppresses nutrient uptake by reversing these processes. Strengthening phosphorylation regulation items that increase nutrient absorption and weakening phosphorylation modification items that are not conducive to nutrient absorption show potential as strategies for increasing nutrient use efficiency.

Loss of IP3R-BKCa Coupling Is Involved in Vascular Remodeling in Spontaneously Hypertensive Rats.

Mechanisms by which BKCa (large-conductance calcium-sensitive potassium) channels are involved in vascular remodeling in hypertension are not fully understood. Vascular smooth muscle cell (VSMC) proliferation and vascular morphology were compared between hypertensive and normotensive rats. BKCa channel activity, protein expression, and interaction with IP3R (inositol 1,4,5-trisphosphate receptor) were examined using patch clamp, Western blot analysis, and coimmunoprecipitation. On inside-out patches of VSMCs, the Ca2+-sensitivity and voltage-dependence of BKCa channels were similar between hypertensive and normotensive rats. In whole-cell patch clamp configuration, treatment of cells with the IP3R agonist, Adenophostin A (AdA), significantly increased BKCa channel currents in VSMCs of both strains of rats, suggesting IP3R-BKCa coupling; however, the AdA-induced increases in BKCa currents were attenuated in VSMCs of hypertensive rats, indicating possible IP3R-BKCa decoupling, causing BKCa dysfunction. Co-immunoprecipitation and Western blot analysis demonstrated that BKCa and IP3R proteins were associated together in VSMCs; however, the association of BKCa and IP3R proteins was dramatically reduced in VSMCs of hypertensive rats. Genetic disruption of IP3R-BKCa coupling using junctophilin-2 shRNA dramatically augmented Ang II-induced proliferation in VSMCs of normotensive rats. Subcutaneous infusion of NS1619, a BKCa opener, to reverse BKCa dysfunction caused by IP3R-BKCa decoupling significantly attenuated vascular hypertrophy in hypertensive rats. In summary, the data from this study demonstrate that loss of IP3R-BKCa coupling in VSMCs induces BKCa channel dysfunction, enhances VSMC proliferation, and thus, may contribute to vascular hypertrophy in hypertension.

The cross-correlation-based analysis to digest the conformational dynamics of the mitoBK channels in terms of their modulation by flavonoids.

The activity of mitochondrial large-conductance voltage- and [Formula: see text]-activated [Formula: see text] channels (mitoBK) is regulated by a number of biochemical factors, including flavonoids. In particular, naringenin (Nar) and quercetin (Que) reached reasonable scientific attention due to their well-pronounced channel-activating effects. The open-reinforcing outcomes of Nar and Que on the mitoBK channel gating have been already reported. Nevertheless, the molecular picture of the corresponding channel-ligand interactions remains still to be revealed. In this work, we investigate the effects of the Nar and Que on the conformational dynamics of the mitoBK channel. In this aim, the cross-correlation-based analysis of the single-channel signals recorded by the patch-clamp method is performed. The obtained results in the form of phase space diagrams enable us to visually monitor the effects exerted by the considered flavonoids at the level of temporal characteristics of repetitive sequences of channel conformations. It turns out that the mitoBK channel activation by naringenin and quercetin does not lead to the change in the number of clusters within the phase space diagrams, which can be related to the constant number of available channel macroconformations regardless of the flavonoid administration. The localization and occupancy of the clusters of cross-correlated sequences suggest that mitoBK channel stimulation by flavonoids affects the relative stability of channel conformations and the kinetics of switching between them. For most clusters, greater net effects are observed in terms of quercetin administration in comparison with naringenin. It indicates stronger channel interaction with Que than Nar.

MCE-Net: polyp segmentation with multiple branch series-parallel attention and channel interaction via edge distribution guidance

Objective. Accurate polyp segmentation is vital for diagnosing colorectal cancer. However, it is still challenging for accurate polyp segmentation and several bottlenecks exist, such as incomplete boundary, localization bias and lack of micro blocks along with large fragmented boundaries in uncertain regions. Approach. To address the above issues, a novel polyp segmentation network with multiple branch series-parallel attention (MBSA) and channel interaction via edge distribution guidance is proposed. Initially, the edge distribution guidance strategy is proposed to generate the edge distribution following Cauchy distribution to capture complementary edges with sufficient details. Subsequently, a MBSA module is put forward to extract features from various receptive fields to pinpoint tiny polyps by a multiple kernel dilated convolution block, while combining semantics of different dimensions to filter out noise and refining the details of micro target. Ultimately, the channel interaction model is proposed to improve the segmentation accuracy of the polyps in uncertain area by splitting channels into groups and conducts group-wise interaction to excavate subtle clues contained in different channels. Main results. Extensive experimental results demonstrate that the proposed method is superior over the state-of-the-art methods with the mean dice of 0.8972, 0.9420, 0.8312, 0.8064 and 0.9214 on five public polyp datasets. Significance. The proposed method improves the integrity of the margins and internal details for polyp segmentation, which will provide a powerful aid for doctors to achieve accurate judgments, reducing the likelihood of colorectal cancer and improving the survival chances of patients.