Application of association rules and simulated annealing algorithms in optimizing traditional Chinese medicine placement schemes.

Background And Aim: China has used traditional Chinese medicine (TCM) to treat diseases for more than 2000 years. Traditionally, TCMs in medicine cabinets are arranged alphabetically or on the basis of experience, but this arrangement greatly affects dispensing efficiency. However, owing to the unique properties and qualities of TCM, very few automatic approaches or systems have specifically addressed TCM dispensing problems.

Quantum State Tomography via Nonconvex Riemannian Gradient Descent.

The recovery of an unknown density matrix of large size requires huge computational resources. State-of-the-art performance has recently been achieved with the factored gradient descent (FGD) algorithm and its variants since they are able to mitigate the dimensionality barrier by utilizing some of the underlying structures of the density matrix. Despite the theoretical guarantee of a linear convergence rate, convergence in practical scenarios is still slow because the contracting factor of the FGD algorithms depends on the condition number κ of the ground truth state.

Minimum-monitor-unit optimization via a stochastic coordinate descent method.

. Deliverable proton spots are subject to the minimum monitor-unit (MMU) constraint. The MMU optimization problem with relatively large MMU threshold remains mathematically challenging due to its strong nonconvexity.

Accelerated magnetic resonance spectroscopy with Vandermonde factorization.

Multi-dimensional magnetic resonance spectroscopy is an important tool for studying molecular structures, interactions and dynamics in bio-engineering. The data acquisition time, however, is relatively long and non-uniform sampling can be applied to reduce this time. To obtain the full spectrum,a reconstruction method with Vandermonde factorization is proposed.

A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT.

Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector.

A spectral interior CT by a framelet-based reconstruction algorithm.

Reducing radiation dose is an important goal in medical computed tomography (CT), for which interior tomography is an effective approach. There have been interior reconstruction algorithms for monochromatic CT, but in reality, X-ray sources are polychromatic. Using a polychromatic acquisition model and motivated by framelet-based image processing algorithms, in this paper, we propose an interior reconstruction algorithm to obtain an image with spectral information assuming only one scan with a current energy-integrating detector.

Robust recovery of complex exponential signals from random Gaussian projections via low rank Hankel matrix reconstruction.

This paper explores robust recovery of a superposition of distinct complex exponential functions with or without damping factors from a few random Gaussian projections. We assume that the signal of interest is of 2 - 1 dimensions and < 2 - 1. This framework covers a large class of signals arising from real applications in biology, automation, imaging science, etc.

Projected Iterative Soft-Thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging.

Compressed sensing (CS) has exhibited great potential for accelerating magnetic resonance imaging (MRI). In CS-MRI, we want to reconstruct a high-quality image from very few samples in a short time. In this paper, we propose a fast algorithm, called projected iterative soft-thresholding algorithm (pISTA), and its acceleration pFISTA for CS-MRI image reconstruction.

Fast Multiclass Dictionaries Learning With Geometrical Directions in MRI Reconstruction.

Objective: Improve the reconstructed image with fast and multiclass dictionaries learning when magnetic resonance imaging is accelerated by undersampling the k-space data.

Methods: A fast orthogonal dictionary learning method is introduced into magnetic resonance image reconstruction to provide adaptive sparse representation of images. To enhance the sparsity, image is divided into classified patches according to the same geometrical direction and dictionary is trained within each class.

Balanced sparse model for tight frames in compressed sensing magnetic resonance imaging.

Compressed sensing has shown to be promising to accelerate magnetic resonance imaging. In this new technology, magnetic resonance images are usually reconstructed by enforcing its sparsity in sparse image reconstruction models, including both synthesis and analysis models. The synthesis model assumes that an image is a sparse combination of atom signals while the analysis model assumes that an image is sparse after the application of an analysis operator.

Accelerated NMR spectroscopy with low-rank reconstruction.

Accelerated multi-dimensional NMR spectroscopy is a prerequisite for high-throughput applications, studying short-lived molecular systems and monitoring chemical reactions in real time. Non-uniform sampling is a common approach to reduce the measurement time. Here, a new method for high-quality spectra reconstruction from non-uniformly sampled data is introduced, which is based on recent developments in the field of signal processing theory and uses the so far unexploited general property of the NMR signal, its low rank.

Cine cone beam CT reconstruction using low-rank matrix factorization: algorithm and a proof-of-principle study.

Respiration-correlated CBCT, commonly called 4DCBCT, provides respiratory phase-resolved CBCT images. A typical 4DCBCT represents averaged patient images over one breathing cycle and the fourth dimension is actually breathing phase instead of time. In many clinical applications, it is desirable to obtain true 4DCBCT with the fourth dimension being time, i.

Low-rank regularization for learning gene expression programs.

Learning gene expression programs directly from a set of observations is challenging due to the complexity of gene regulation, high noise of experimental measurements, and insufficient number of experimental measurements. Imposing additional constraints with strong and biologically motivated regularizations is critical in developing reliable and effective algorithms for inferring gene expression programs. Here we propose a new form of regulation that constrains the number of independent connectivity patterns between regulators and targets, motivated by the modular design of gene regulatory programs and the belief that the total number of independent regulatory modules should be small.

Assessment of left ventricular dyssynchrony and cardiac function in patients with different pacing modes using real-time three-dimensional echocardiography: Comparison with tissue Doppler imaging.

The aim of this study was to evaluate the left ventricular mechanical dyssynchrony (LVMD) and left ventricular dysfunction of patients in AAI, DDD and VVI pacing modes using real-time three-dimensional echocardiography (RT3DE) and tissue Doppler imaging (TDI). The results from the RT3DE and TDI were subsequently compared. Twenty patients with sick sinus syndrome (SSS) who had undergone the implantation of a dual-chamber pacemaker were enrolled in this study and the pacemakers were programmed to AAI, DDD and VVI modes, sequentially.

Effects of Jianpi Jiedu Recipe on reversion of P-glycoprotein-mediated multidrug resistance through COX-2 pathway in colorectal cancer.

Objective: To evaluate the underlying mechanism of Jianpi Jiedu Recipe (, JJR) in the reversion of multidrug resistance concerning colorectal cancer in vitro and in vivo.

Methods: Mice were treated orally with JJR at a daily 4.25 g/(kg·day) or injected with vinblastine (VCR) 2.

Zuo Jin Wan, a Traditional Chinese Herbal Formula, Reverses P-gp-Mediated MDR In Vitro and In Vivo.

Zuo Jin Wan (ZJW), a typical traditional Chinese medicine (TCM) formula, has been identified to have anticancer activity in recent studies. In this study, we determined the underlying mechanism of ZJW in the reversal effect of multidrug resistance on colorectal cancer in vitro and in vivo. Our results showed that ZJW significantly enhanced the sensitivity of chemotherapeutic drugs in HCT116/L-OHP, SGC7901/DDP, and Bel/Fu MDR cells.

Anti-tumor activity and apoptosis-regulation mechanisms of bufalin in various cancers: new hope for cancer patients.

The induction of apoptosis in target cells is a key mechanism for most anti-tumor therapies. Bufalin is a cardiotonic steroid that has the potential to induce differentiation and apoptosis of tumor cells. Research on bufalin has so far mainly involved leukemia, prostate cancer, gastric cancer and liver cancer, and has been confined to in vitro studies.

Role of poly(ADP-ribose) glycohydrolase in the regulation of cell fate in response to benzo(a)pyrene.

Poly(ADP-ribosyl)ation is a crucial regulator of cell fate in response to genotoxic stress. Poly(ADP-ribosyl)ation plays important roles in multiple cellular processes, including DNA repair, chromosomal stability, chromatin function, apoptosis, and transcriptional regulation. Poly(ADP-ribose) (PAR) degradation is carried out mainly by poly(ADP-ribose) glycohydrolase (PARG) enzymes.

Framelet-based blind motion deblurring from a single image.

How to recover a clear image from a single motion-blurred image has long been a challenging open problem in digital imaging. In this paper, we focus on how to recover a motion-blurred image due to camera shake. A regularization-based approach is proposed to remove motion blurring from the image by regularizing the sparsity of both the original image and the motion-blur kernel under tight wavelet frame systems.

Robust principal component analysis-based four-dimensional computed tomography.

The purpose of this paper for four-dimensional (4D) computed tomography (CT) is threefold. (1) A new spatiotemporal model is presented from the matrix perspective with the row dimension in space and the column dimension in time, namely the robust PCA (principal component analysis)-based 4D CT model. That is, instead of viewing the 4D object as a temporal collection of three-dimensional (3D) images and looking for local coherence in time or space independently, we perceive it as a mixture of low-rank matrix and sparse matrix to explore the maximum temporal coherence of the spatial structure among phases.

[Evaluation on left ventricular systolic synchronicity and cardiac function in patients with permanent cardiac pacing by real-time three-dimensional echocardiography].

Objective: To determine the feasibility on the left ventricular systolic synchronism and cardiac function evaluation in patients with permanent cardiac pacing by real-time three-dimensional echocardiography.

Methods: Fifteen patients with sick sinus syndrome post dual-chamber pacemaker implantation were enrolled in this study. Pacemakers were programmed to AAI, DDD, and VVI respectively.