Acclimatize experimental approach to adjudicate hydraulic coefficients under different bed material configurations and slopes with and without weir.

The primary purpose of this study was to evaluate the hydraulic coefficient of coarse aggregate grain size beds and hydraulic parameters under random and perpendicular bed configurations, as well as to explore the discharge coefficient for rectangular weirs. The research objectives were to compare flow resistance coefficients, evaluate the discharge coefficient for rectangular weirs, investigate the relationship between roughness coefficient and hydraulic parameters, and validate the theoretical hydraulic equation for the rectangular weir. This was achieved by analysing different bed configurations, bed slopes, and 20 and 30-mm bed materials. Sieve analysis was conducted on bed materials using American-standard sieves to determine their particle size distribution. The experiment was performed in a rectangular flume measuring 12 m in length, 0.31 m in width, and 0.45 m in depth. In a laboratory experiment, water was pumped into a flume using centrifugal pumps, and a rectangular weir was attached downstream for discharge measurement. The experiment investigated factors such as Manning roughness coefficient, bed material geometry, bed slope, and weir shapes. Approximately 1680 tests were conducted to analysed the impact of these factors on discharge and the coefficient of discharge. The average Manning's roughness coefficients for a grain size of 20 mm were 0.019 (with weir) and 0.019 (without weir) in a random bed configuration, and 0.028 (with weir) and 0.027 (without weir) in a perpendicular flow bed configuration. For a grain size of 30 mm, the coefficients were 0.023 (with weir) and 0.022 (without weir) in a random bed configuration, and 0.033 (with weir) and 0.026 (without weir) in a perpendicular flow bed configuration. The presence of a weir has affected Manning's roughness coefficients and discharge coefficients. With a weir, the roughness coefficients have generally been higher compared to without a weir, indicating increased roughness in the channel. The discharge coefficient for a rectangular weir with a grain size of 20 mm ranged from 0.39 to 0.84 (random bed) and 0.27 to 0.68 (perpendicular flow bed), while for a grain size of 30 mm it ranged from 0.31 to 0.81 (random bed) and 0.23 to 0.48 (perpendicular flow bed). The discharge coefficients have varied depending on the grain size and bed configuration, reflecting different flow efficiencies over the weir. Rough particles influenced flow and Manning's roughness coefficient value, then reduced discharge and velocity values. Under two bed configurations and slopes, beds with a grain size of 30 mm have higher roughness coefficients compared to those with a grain size of 20 mm. The models have shown that the roughness coefficient is inversely proportional to the discharge and directly proportional to the tailgate water levels. The coefficient of roughness and discharge coefficient are mainly influenced by the channel slopes, bed roughness, bed grain size, and bed configuration. A randomly configured bed with a 20 mm grain size gravel bed is preferred over a perpendicular bed configuration to handle high discharges. Using a 20 mm grain-size gravel bed in open-channel flow is more suitable than a 30 mm grain-size bed. Relying on the constant friction factor, Manning's n, is not recommended as it may result in design errors. These findings have the potential to improve hydraulic engineering design practices, enhancing the accuracy and efficiency of open-channel flow systems.

Applicability of machine learning techniques to analyze Microplastic transportation in open channels with different hydro-environmental factors.

This research utilized machine learning to analyze experiments conducted in an open channel laboratory setting to predict microplastic transport with varying discharge, velocity, water depth, vegetation pattern, and microplastic density. Four machine learning (ML) models, incorporating Random Forest (RF), Decision Tree (DT), Extreme Gradient Boost (XGB) and K-Nearest Neighbor (KNN) algorithms, were developed and compared with the Linear Regression (LR) statistical model, using 75% of the data for training and 25% for validation. The predictions of ML algorithms were more accurate than the LR, while XGB and RF provided the best predictions. To explain the ML results, Explainable artificial intelligence (XAI) was employed by using Shapley Additive Explanations (SHAP) to predict the global behavior of variables. RF was the most reliable model, with a coefficient of correlation of 0.97 and a mean absolute percentage error of 1.8% after hyperparameter tuning. Results indicated that discharge, velocity, water depth, and vegetation all influenced microplastic transport. Discharge and vegetation enhanced and reduced microplastic transport, respectively, and showed a response to different vegetation patterns. A strong linear positive correlation (R2 = 0.8) was noted between microplastic density and retention. In the absence of dedicated microplastic transport analytical models and infeasibility of using classical sediment transport models in predicting microplastic transport, ML proved to be helpful. Moreover, the use of XAI will reduce the black-box nature of ML models with effective interpretation enhancing the trust of domain experts in ML predictions. The developed model offers a promising tool for real-world open channel predictions, informing effective management strategies to mitigate microplastic pollution.

Settling velocity of microplastics in turbulent open-channel flow.

The settling behavior of microplastics (MPs) plays a pivotal role in their transport and fate in aquatic environments, but the dominant mechanisms and physics governing the settling of MPs in rivers remain poorly understood. To gain mechanistic insights into the velocity lag of MPs in an open-channel flume under different turbulent flow conditions, an experimental study was conducted using three types of MPs: polystyrene, cellulose acetate, and acrylic, of sphere-shaped particles with diameters ranging from 1 mm to 5 mm. A particle tracking technique was employed to record and analyze the MPs velocity within turbulent flows. The results showed a variation in the vertical settling velocity of MPs ωMP ranging from -26 % to +16 %, when compared to their counterparts in still water (ωs). A new formula for the drag coefficient (Cd) of MP particles was developed by introducing the suspension number (u∗/ωs). The developed Cd formula was used to calculate the resultant velocity lag VMP, with a mean relative error of 16 % compared with the measured values. Further, the study highlighted that the MPs with large Stokes numbers are mainly driven by their own inertia and turbulence has less influence on their settling behavior. This study is crucial for understanding the settling behavior of MPs in turbulent flows and developing their transport and fate models for MPs in riverine systems.

Torquetenovirus Viremia Quantification Using Real-Time PCR Developed on a Fully Automated, Random-Access Platform.

Quantification of Torquetenovirus (TTV) viremia is becoming important for evaluating the status of the immune system in solid organ transplant recipients, monitoring the appearance of post-transplant complications, and controlling the efficacy of maintenance immunosuppressive therapy. Thus, diagnostic approaches able to scale up TTV quantification are needed. Here, we report on the development and validation of a real-time PCR assay for TTV quantification on the Hologic Panther Fusion® System by utilizing its open-access channel. The manual real-time PCR previously developed in our laboratories was optimized to detect TTV DNA on the Hologic Panther Fusion® System. The assay was validated using clinical samples. The automated TTV assay has a limit of detection of 1.6 log copies per ml of serum. Using 112 samples previously tested via manual real-time PCR, the concordance in TTV detection was 93% between the assays. When the TTV levels were compared, the overall agreement between the methods, as assessed using Passing-Bablok linear regression and Bland-Altman analyses, was excellent. In summary, we validated a highly sensitive and accurate method for the diagnostic use of TTV quantification on a fully automated Hologic Panther Fusion® System. This will greatly improve the turnaround time for TTV testing and better support the laboratory diagnosis of this new viral biomarker.

Exenatide reduces atrial fibrillation susceptibility by inhibiting hKv1.5 and hNav1.5 channels.

Exenatide, a promising cardioprotective agent, protects against cardiac structural remodeling and diastolic dysfunction. Combined blockade of sodium and potassium channels is valuable for managing atrial fibrillation (AF). Here, we explored whether exenatide displayed anti-AF effects by inhibiting human Kv1.5 and Nav1.5 channels. We used the whole-cell patch-clamp technique to investigate the effects of exenatide on hKv1.5 and hNav1.5 channels expressed in human embryonic kidney 293 cells and studied the effects of exenatide on action potential (AP) and other cardiac ionic currents in rat atrial myocytes. Additionally, an electrical mapping system was used to explore the effects of exenatide on electrical properties and AF activity in isolated rat hearts. Finally, a rat AF model, established using acetylcholine and calcium chloride, was employed to evaluate the anti-AF potential of exenatide in rats. Exenatide reversibly suppressed IKv1.5 with IC50 of 3.08 µM, preferentially blocked the hKv1.5 channel in its closed state, and positively shifted the voltage-dependent activation curve. Exenatide also reversibly inhibited INav1.5 with IC50 of 3.30 µM, negatively shifted the voltage-dependent inactivation curve, and slowed its recovery from inactivation with significant use-dependency at 5 and 10 Hz. Furthermore, exenatide prolonged AP duration and suppressed the sustained K+ current (Iss) and transient outward K+ current (Ito), but without inhibition of L-type Ca2+ current (ICa,L) in rat atrial myocytes. Exenatide prevented AF incidence and duration in rat hearts and rats. These findings demonstrate that exenatide inhibits IKv1.5 and INav1.5in vitro and reduces AF susceptibility in isolated rat hearts and rats.

Failure probability analysis of high fill levee considering multiple uncertainties and correlated failure modes.

Such complex causative factors in current failure probability models are represented by simply random uncertainty and completely independent or correlation of failure modes, which can often limit the model utility. In this study, we developed a methodology to construct failure probability models for high fill levees, incorporating the identification of uncertainties and an analysis of failure modes. Based on quantification of stochastic-grey-fuzzy uncertainties, probability analysis involved with overtopping, instability and seepage failure modes was implemented combined with probability and non-probability methods. Given that the interaction among failure modes typically exhibits nonlinear behavior, rather than linear correlation or complete independence, a simple methodology for the binary Copula function was established and implemented in MATLAB. This methodology was applied to the high fill segments of a long-distance water transfer project characterized by high population density. It shows that the failure probability of a single failure mode is overestimated when uncertainties are not considered, because of the randomness and fuzziness of some parameters and the greyness of information. Meanwhile, it is found that the magnitude of failure probability related to levee breach is overestimated without respect to failure modes correlation, especially when the probabilities of seepage and instability are both significant and closely aligned.

On the dynamic contact angle of capillary-driven microflows in open channels.

The true value of the contact angle between a liquid and a solid is a thorny problem in capillary microfluidics. The Lucas-Washburn-Rideal (LWR) law assumes a constant contact angle during fluid penetration. However, recent experimental studies have shown lower liquid velocities than predicted by the LWR equation, which are attributed to a velocity-dependent dynamic contact angle that is larger than its static value. Inspection of fluid penetration in closed channels has confirmed that a dynamic angle is needed in the LWR equation. In this work, the dynamic contact angle in an open channel configuration is investigated using experimental data obtained with a range of liquids, aqueous and organic, and a PMMA substrate. We demonstrate that a dynamic contact angle must be used to explain the early stages of fluid penetration, i.e., at the start of the viscous regime, when flow velocities are sufficiently high. Moreover, the open channel configuration, with its free surface, enhances the effect of the dynamic contact angle, making its inclusion even more important. We found that for the liquids in our study, the molecular-kinetic theory (MKT) is the most accurate in predicting the effect of the dynamic contact angle on liquid penetration in open channels.

Dimensionless Groups by Entropic Similarity: II-Wave Phenomena and Information-Theoretic Flow Regimes.

The aim of this study is to explore the insights of the information-theoretic definition of similarity for a multitude of flow systems with wave propagation. This provides dimensionless groups of the form Πinfo=U/c, where U is a characteristic flow velocity and c is a signal velocity or wave celerity, to distinguish different information-theoretic flow regimes. Traditionally, dimensionless groups in science and engineering are defined by geometric similarity, based on ratios of length scales; kinematic similarity, based on ratios of velocities or accelerations; and dynamic similarity, based on ratios of forces. In Part I, an additional category of entropic similarity was proposed based on ratios of (i) entropy production terms; (ii) entropy flow rates or fluxes; or (iii) information flow rates or fluxes. In this Part II, the information-theoretic definition is applied to a number of flow systems with wave phenomena, including acoustic waves, blast waves, pressure waves, surface or internal gravity waves, capillary waves, inertial waves and electromagnetic waves. These are used to define the appropriate Mach, Euler, Froude, Rossby or other dimensionless number(s)-including new groups for internal gravity, inertial and electromagnetic waves-to classify their flow regimes. For flows with wave dispersion, the coexistence of different celerities for individual waves and wave groups-each with a distinct information-theoretic group-is shown to imply the existence of more than two information-theoretic flow regimes, including for some acoustic wave systems (subsonic/mesosonic/supersonic flow) and most systems with gravity, capillary or inertial waves (subcritical/mesocritical/supercritical flow). For electromagnetic wave systems, the additional vacuum celerity implies the existence of four regimes (subluminal/mesoluminal/transluminal/superluminal flow). In addition, entropic analyses are shown to provide a more complete understanding of frictional behavior and sharp transitions in compressible and open channel flows, as well as the transport of entropy by electromagnetic radiation. The analyses significantly extend the applications of entropic similarity for the analysis of flow systems with wave propagation.

Emerging open-channel droplet arrays for biosensing.

Open-channel droplet arrays have attracted much attention in the fields of biochemical analysis, biofluid monitoring, biomarker recognition and cell interactions, as they have advantages with regard to miniaturization, parallelization, high-throughput, simplicity and accessibility. Such droplet arrays not only improve the sensitivity and accuracy of a biosensor, but also do not require sophisticated equipment or tedious processes, showing great potential in next-generation miniaturized sensing platforms. This review summarizes typical examples of open-channel microdroplet arrays and focuses on diversified biosensing integrated with multiple signal-output approaches (fluorescence, colorimetric, surface-enhanced Raman scattering (SERS), electrochemical, etc.). The limitations and development prospects of open-channel droplet arrays in biosensing are also discussed with regard to the increasing demand for biosensors.

3D Printing of Individualized Microfluidic Chips with DLP-Based Printer.

Microfluidic chips have shown their potential for applications in fields such as chemistry and biology, and 3D printing is increasingly utilized as the fabrication method for microfluidic chips. To address key issues such as the long printing time for conventional 3D printing of a single chip and the demand for rapid response in individualized microfluidic chip customization, we have optimized the use of DLP (digital light processing) technology, which offers faster printing speeds due to its surface exposure method. In this study, we specifically focused on developing a fast-manufacturing process for directly printing microfluidic chips, addressing the high cost of traditional microfabrication processes and the lengthy production times associated with other 3D printing methods for microfluidic chips. Based on the designed three-dimensional chip model, we utilized a DLP-based printer to directly print two-dimensional and three-dimensional microfluidic chips with photosensitive resin. To overcome the challenge of clogging in printing microchannels, we proposed a printing method that combined an open-channel design with transparent adhesive tape sealing. This method enables the rapid printing of microfluidic chips with complex and intricate microstructures. This research provides a crucial foundation for the development of microfluidic chips in biomedical research.

Movement characteristics of the inclined surface flow of the open channel on the nanoscale surface.

This study investigates the water flow characteristics on a solid surface with nanoscale compared to a normal solid surface. The experiment uses a high-speed video system and Fiber-optic Laser Doppler Velocimetry to measure the flow condition of the droplet and velocity distribution profile in the inclined surface flow of the open channel, respectively. The results showed that the movement speed of water droplets on the nanoscale surface was about 2 times faster than on the normal surface. The mean error of each velocity profile was 0.6%. The results reveal that the velocity profile is not significantly influenced by whether the flume bottom is coated with nanoscale material or not in the inclined surface flow of the open channel.

Energy loss and contraction coefficients-based vertical sluice gate's discharge coefficient under submerged flow using symbolic regression.

Accurate calculation of discharge is a critical task in terms of environmental and operational regulations. In the current study, a new approach for determining vertical sluice gates' flow discharge with a minor bias is proposed. Energy-momentum equations are used to characterize the physical expression of the phenomena intended for generation of the coefficient of discharge. The coefficient of discharge is then expressed according to coefficients of energy loss and contraction. Following that, the coefficient of discharge, coefficient of contraction, and coefficient of energy loss are calculated using an optimization approach. Then, dimensional analysis is conducted and regression equations for quantifying the coefficient of energy loss is produced using symbolic regression method. The derived contraction coefficient and energy loss coefficient formulas are accordingly utilized to compute the coefficient of discharge in the vertical sluice gate and also to determine flow discharge. For computing discharge, five different scenarios are considered. The developed approaches' performance is examined against selected benchmarks from the literature. The results show that the symbolic regression method can compute discharge more accurate than its alternatives.

Laboratory and numerical investigation of the 2-array submerged vanes in meandering open channel.

In the case of flooding in rivers, river regulation structures are important since scours occur on the outer meander due to high flow velocities. In this study, 2-array submerged vane structures were investigated which is a new method in the meandering part of open channels, both laboratory and numerically with an open channel flow discharge of 20 L/s. Open channel flow experiments were carried out by using a submerged vane and without a vane. The flow velocity results of the computational fluid dynamics (CFD) models were compared to the experimental results and the results were found compatible. The flow velocities were investigated along with depth using the CFD and found that the maximum velocity was reduced by 22-27% along the depth. In the outer meander, the 2-array submerged vane with a 6-vane structure was found to affect the flow velocity by 26-29% in the region behind the vane.

Differences in the Natural Swimming Behavior of Schizothorax prenanti Individual and Schooling in Spatially Heterogeneous Turbulent Flows.

Spatially heterogeneous turbulent flow refers to nonuniform flow with coexisting multiple flow velocities, which is widely distributed in fish natural or husbandry environments, and its hydraulic parameters affect fish swimming behavior. In this study, a complex hydrodynamic environment with three flow velocity regions (low, medium, and high) coexisting in an open-channel flume was designed to explore volitional swimming ability, the spatial-temporal distribution of fish swimming trajectories, and the range of preferred hydrodynamic parameters of Schizothorax prenanti individual and schooling (three fish). The results showed that the swimming speed of individual fish during upstream migration was significantly higher than that of fish schools (p < 0.05). The swimming trajectories of fish schooling showed that they spent more time synchronously exploring the flow environment during upstream migration compared with individual fish. By superimposing the fish swimming trajectories on the environmental flow field, the range of hydrodynamic environments preferred by fish in complex flow fields was quantified. This research provides a novel approach for investigating the natural swimming behavior of fish species, and a theoretical reference for the restoration of fish natural habitats or flow enrichment of husbandry environments.

Automated and parallel microfluidic DNA extraction with integrated pneumatic microvalves/pumps and reusable open-channel columns.

A novel microfluidic DNA extraction protocol based on integrated diaphragm microvalves/pumps and silica-deposited open-channel columns was developed specifically for automated and parallel DNA solid-phase extraction (SPE). The method uses microfluidic chips with a sandwiched structure containing three layers, which are the upper fluidic layer with surface-deposited silica on glass open channels as the extraction phase, the lower actuation layer with valve actuation channels on a glass wafer, and the middle poly(dimethylsiloxane) (PDMS) membrane for reversible bonding of the two glass substrates. These two glass substrates can be reused after thoroughly cleaning and the PDMS membrane can be replaced conveniently, which could effectively decrease the time and cost of chip manufacturing. The normally closed microvalves/pumps were used to automatically control all processes of the on-chip DNA SPE without cross-contamination and leakage, enabling the processing of multiple samples in parallel without changing the microvalve control module. Using the microchip device with integrated microvalves/pumps, automated, programmable, and simultaneous λ-DNA extractions from different samples could be attained, even from complex solutions such as human blood, and the silica-deposited open-channel columns could be reused stably and reliably. Results have demonstrated that most of the eluted λ-DNA was recovered in the second 2 µL of elution buffer with high-purity suitable for successful polymerase chain reaction amplification, making it possible for further integration into microfluidic devices for fully functional and high-throughput genetic analysis.

Developing a generic relation for predicting sediment pick-up rate using symbolic soft computing techniques.

Sediment pick-up rate has been investigated using experimental and numerical approaches. However, the use of soft computing methods for its prediction has received less attention so far. In this study, genetic programming (GP), grammatical evolution (GE), and gradient boosting machine (GBM) algorithms are employed to develop a relation in dimensionless form for predicting sediment pick-up rate in open channel flow based on two experimental datasets. Dimensionless Froude number, particle diameter, and depth-averaged turbulent kinetic energy are input variables for prediction. Prediction performance is evaluated with performance indices (root mean square error, mean absolute error, and coefficient of correlation), visual comparisons (scatter, dot, and Bland-Altman plots), and uncertainty indicators (Tsallis and Renyi entropies). Three mathematical expressions for sediment pick-up rate prediction are obtained, with GE producing the most accurate results.

Derivation of new resistance principle on flow-induced morphological response of flexible vegetation.

Water flow under vegetated environments is a noteworthy research topic in environmental hydraulics and restoration ecology, and this research is particularly important for maintaining water transport and streambed stability in water ecosystems. The calculation of the resistance coefficient in vegetated water flow is the core of this research. But there are still problems such as complex expressions and low simulation accuracy in this research field. To solve this scientific problem, this research, based on the theoretical study of environmental hydraulics and genetic algorithm, selected three basic parameters of vegetation submergence, resistance length and curvature degree, and successfully constructed the formula for calculating the resistance coefficient for flexible vegetated flow by using a wide range of data sets. New quantitative relationship between the drag coefficient and the relative roughness of flexible vegetation was established in this study. The formula of drag coefficients for flexible vegetation conditions has a more concise form and can be successfully applied to both flexible and rigid vegetation. As flexible vegetation is deformed under the action of water flow, and the quantitative expressions of Vogel number and relative roughness are given quantitatively through the analysis of its physical properties. Overall, this study improves the basic theoretical study of vegetated flow in environmental fluid dynamics and provides scientific theoretical support for vegetation restoration.

Evaluation of a random displacement model for scalar mixing in ecological channels partially covered with vegetation.

The flow structure in natural rivers may change due to the disturbance of vegetation, further affecting the transport of pollutants and sediment (Liu et al. 2020). In this paper, the random displacement model (RDM) is presented to study the material transport in the emergent vegetated flow by predicting the longitudinal dispersion coefficient (LDC), which plays an important role in the longitudinal transport of pollutants in natural rivers covered by emergent vegetation. RDM can be applied for the analysis of the vegetated flow provided that the velocity distribution and the turbulent diffusion coefficient distribution remain known. According to the experimental data on velocity and Reynolds stress, the flow field was divided into four sub-zones along the cross-sectional area where the transverse distribution of the longitudinal velocity and also transverse turbulent diffusion coefficient were determined. Moreover, the simulated results of the longitudinal dispersion coefficient were verified by using the previously measured data. In addition, the sensitivity analysis of RDM parameters was carried out. In comparison with the shear layer width and the velocity difference, the impact of vegetation zone width on the longitudinal dispersion coefficient was greater, but the model was fundamentally stable, further confirming that the analytical model can be reliable for predicting the longitudinal dispersion coefficient in the vegetated open-channel flow. Accurately estimating the longitudinal dispersion coefficient is useful for understanding the transport and fate of pollutants in river channels and, thereby, for exploring the sustainable development of the river ecological environment, as well as optimizing the planning and design of river course.

Flow and turbulence in unevenly obstructed channels with rigid and flexible vegetation.

The pattern of vegetation along the cross-section of macrophyte-dominated shallow waters is generally uneven, which affects water velocity and turbulence. This study examined the velocity and turbulence in the open channel with an uneven transverse distribution of vegetation in laboratory flume experiments. Two vegetation patterns were tested: emergent vegetation which covered part of the channel, and a symmetrical combination of submerged and emergent vegetation canopies along the lateral direction of the flume. The flow was measured using a three-dimensional Acoustic Doppler Velocimeter. The velocity and turbulence characteristics were analyzed under three vegetation densities and five discharge scenarios. Results showed that the longitudinal mean velocity changed with vegetation density and flow discharge when vegetation was unevenly distributed in a lateral direction. The strong variation in shear stress at the emergent vegetation-open water intersections and submerged-emergent vegetation intersections resulted in large-scale vortices at the interfaces. The formation processes of stem-scale turbulence and shear-scale turbulence under different vegetation scenarios were discussed. A turbulent kinetic energy model within partly obstructed vegetation canopies was established, which helped to identify the development of horizontal and vertical coherent vertices.

Effects of rosiglitazone, an antidiabetic drug, on Kv3.1 channels.

Rosiglitazone is a thiazolidinedione-class antidiabetic drug that reduces blood glucose and glycated hemoglobin levels. We here investigated the interaction of rosiglitazone with Kv3.1 expressed in Chinese hamster ovary cells using the whole-cell patch-clamp technique. Rosiglitazone rapidly and reversibly inhibited Kv3.1 currents in a concentration-dependent manner (IC50 = 29.8 µM) and accelerated the decay of Kv3.1 currents without modifying the activation kinetics. The rosiglitazone-mediated inhibition of Kv3.1 channels increased steeply in a sigmoidal pattern over the voltage range of -20 to +30 mV, whereas it was voltage-independent in the voltage range above +30 mV, where the channels were fully activated. The deactivation of Kv3.1 current, measured along with tail currents, was also slowed by the drug. In addition, the steady-state inactivation curve of Kv3.1 by rosiglitazone shifts to a negative potential without significant change in the slope value. All the results with the use dependence of the rosiglitazone-mediated blockade suggest that rosiglitazone acts on Kv3.1 channels as an open channel blocker.