Optimal Estimation of Ion-Channel Kinetics from Macroscopic Currents

Markov modeling provides an effective approach for modeling ion channel kinetics. There are several search algorithms for global fitting of macroscopic or single-channel currents across different experimental conditions. Here we present a particle swarm optimization(PSO)-based approach which, when used in combination with golden section search (GSS), can fit macroscopic voltage responses with a high degree of accuracy (errors within 1%) and reasonable amount of calculation time (less than 10 hours for 20 free parameters) on a desktop computer. We also describe a method for initial value estimation of the model parameters, which appears to favor identification of global optimum and can further reduce the computational cost. The PSO-GSS algorithm is applicable for kinetic models of arbitrary topology and size and compatible with common stimulation protocols, which provides a convenient approach for establishing kinetic models at the macroscopic level

Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability

In this paper, we consider optimal linear sensor fusion for obtaining a remote state estimate of a linear process based on the sensor data transmitted over lossy channels. There is no local observability guarantee for any of the sensors. It is assumed that the state of the linear process is collectively observable. We transform the problem of finding the optimal linear sensor fusion coefficients as a convex optimization problem which can be efficiently solved. Moreover, the closed-form expression is also derived for the optimal coefficients. Simulation results are presented to illustrate the performance of the developed algorithm.The work by Y. Wu and L. Shi is supported by a Hong Kong RGC General Research Fund, Hong Kong Special Administrative Region 16204218. The work of Y. Li was supported by National Natural Science Foundation of China, China (61890924, 61991404), and Liao Ning Revitalization Talents Program (XLYC1907087)

The Design and Analysis of Split Row-Column Addressing Array for 2-D Transducer

For 3-D ultrasound imaging, the row-column addressing (RCA) with 2N connections for an N × N 2-D array makes the fabrication and interconnection simpler than the fully addressing with N2 connections. However, RCA degrades the image quality because of defocusing in signal channel direction in the transmit event. To solve this problem, a split row-column addressing scheme (SRCA) is proposed in this paper. Rather than connecting all the elements in the signal channel direction together, this scheme divides the elements in the signal channel direction into several disconnected blocks, thus enables focusing beam access in both signal channel and switch channel directions. Selecting an appropriate split scheme is the key for SRCA to maintaining a reasonable tradeoff between the image quality and the number of connections. Various split schemes for a 32 × 32 array are fully investigated with point spread function (PSF) analysis and imaging simulation. The result shows the split scheme with five blocks (4, 6, 12, 6, and 4 elements of each block) can provide similar image quality to fully addressing. The splitting schemes for different array sizes from 16 × 16 to 96 × 96 are also discussed

Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model

Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD) of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD) of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression

Fit a MWC model C₅-O₅ to the macroscopic currents of BK channels from <i>Xenopus</i> oocyte.

<p>(A) Activation traces of BK currents were recorded from an inside-out patch from a <i>Xenopus</i> oocyte injected with cRNA encoding mSlo1 α subunits. Channels were activated by voltage steps ranging from −200 to +200 mV with 10 mV increments from a holding potential of −180 mV with a cytosolic [Ca²⁺]_i as indicated. The voltage protocol is not shown here. The red lines were coming from the globally fitting the model C₅-O₅ to BK currents by PSO-GSS algorithm. The channel count N_C is 314 for 1 µM, 365 for 10 µM and 433 for 300 µM. The different Nc in the same patch is probably coming from the smaller single-channel conductance at the higher Ca²⁺, which will not change the channel kinetics. (B) Deactivation currents were obtained from the same patch as we described in (A). Currents were elicited by voltage steps ranging from −200 to +180 mV with 10 mV increments from a 20 ms-prepulse of +180 mV with a cytosolic [Ca²⁺]_i as indicated. The red lines are fits by a PSO-GSS algorithm. The channel count N_C is 301 for 1 µM, 354 for 10 µM and 387 for 300 µM. The score σ² is 41.60. All the capacitive currents of 0.15 ms were pre-substituted with straight lines before run and not counted during run. The dash line is zero current.</p