Revealing the biological mechanism of acupuncture in alleviating excessive inflammatory responses and organ damage in sepsis: a systematic review.

Sepsis is a systemic inflammation caused by a maladjusted host response to infection. In severe cases, it can cause multiple organ dysfunction syndrome (MODS) and even endanger life. Acupuncture is widely accepted and applied in the treatment of sepsis, and breakthroughs have been made regarding its mechanism of action in recent years. In this review, we systematically discuss the current clinical applications of acupuncture in the treatment of sepsis and focus on the mechanisms of acupuncture in animal models of systemic inflammation. In clinical research, acupuncture can not only effectively inhibit excessive inflammatory reactions but also improve the immunosuppressive state of patients with sepsis, thus maintaining immune homeostasis. Mechanistically, a change in the acupoint microenvironment is the initial response link for acupuncture to take effect, whereas PROKR2 neurons, high-threshold thin nerve fibres, cannabinoid CB2 receptor (CB2R) activation, and Ca2+ influx are the key material bases. The cholinergic anti-inflammatory pathway of the vagus nervous system, the adrenal dopamine anti-inflammatory pathway, and the sympathetic nervous system are key to the transmission of acupuncture information and the inhibition of systemic inflammation. In MODS, acupuncture protects against septic organ damage by inhibiting excessive inflammatory reactions, resisting oxidative stress, protecting mitochondrial function, and reducing apoptosis and tissue or organ damage.

Molecular typing of Mycobacterium tuberculosis isolates circulating in Henan, central China.

The aim of this study was to characterize the genotypes of Mycobacterium tuberculosis (MT) in isolates obtained from Henan, China, and to study the distribution features of Beijing strains in Henan. A total of 443 MT strains isolated in Henan Province were tested for susceptibility to isonicotinylhydrazide (INH), rifampicin (RFP), ethambutol (EMB) and streptomycin (SM), and genotyped by spoligotyping. The clustering of genotypes revealed 4 gene clusters (Beijing and Beijing-like, T, Manu, and S and LAM3) and 24 genotypes. In total, 387 (87.4%) of the strains were Beijing strains. The frequency of multidrug-resistant (MDR) strains was significantly higher in the Beijing and Beijing-like strains than in the other strains (χ(2)=4.6564, P<0.05). However, the percentages of drug resistance and sensitivity in the Beijing strains were almost the same as those in the non-Beijing strains. The proportion of Beijing strains in the ≤60-year-old TB patients was significantly higher than in the >60-year-old TB patients (χ(2)=32.053, P<0.001). The distribution of Beijing strains deceased gradually from the east to the west in Henan Province (P<0.0001). The data demonstrate that the Beijing genotype is a major type in the area and may be related to enhanced transmissibility. The transmission of Beijing family strains has increased in Henan and its incidence is highest in the east of Henan. The MDR strains were significant in the spread of MT.

Unified reconstruction framework for multi-modal medical imaging.

Various types of advanced imaging technologies have significantly improved the quality of medical care available to patients. Corresponding medical image reconstruction algorithms, especially 3D reconstruction, play an important role in disease diagnosis and treatment assessment. However, these increasing reconstruction methods are not implemented in a unified software framework, which brings along lots of disadvantages such as breaking connection of different modalities, lack of module reuse and inconvenience to method comparison. This paper discusses reconstruction process from the viewpoint of data flow and implements a free, accelerated, extensible Unified Reconstruction Software Framework (URSF). The software framework is an abstract solution that supports multi-modal image reconstruction. The goal of this framework is to capture the common processing work flow for different modalities and different methods, make the development of reconstruction for new devices much easier, and implement a set of popular reconstruction algorithms, so that it is convenient for researchers to compare against. The overall design and certain key technologies are introduced in detail. Presented experiment examples and practical applications commendably demonstrate the validity of this framework.

Real-time visualized freehand 3D ultrasound reconstruction based on GPU.

Visualized freehand 3-D ultrasound reconstruction offers to image incremental reconstruction during acquisition and guide users to scan interactively for high-quality volumes. We originally used the graphics processing unit (GPU) to develop a visualized reconstruction algorithm that achieves real-time level. Each newly acquired image was transferred to the memory of the GPU and inserted into the reconstruction volume on the GPU. The partially reconstructed volume was then rendered using GPU-based incremental ray casting. After visualized reconstruction, hole-filling was performed on the GPU to fill remaining empty voxels in the reconstruction volume. We examine the real-time nature of the algorithm using in vitro and in vivo datasets. The algorithm can image incremental reconstruction at speed of 26-58 frames/s and complete 3-D imaging in the acquisition time for the conventional freehand 3-D ultrasound.

Fast Katsevich algorithm based on GPU for helical cone-beam computed tomography.

Katsevich reconstruction algorithm represents a breakthrough for helical cone-beam computed tomography (CT) reconstruction, because it is the first exact cone-beam reconstruction algorithm of filtered backprojection (FBP) type with 1-D shift-invariant filtering. Although FBP-type reconstruction algorithm is effective, 3-D CT reconstruction is time-consuming, and the accelerations of Katsevich algorithm on CPU or cluster have been widely studied. In this paper, Katsevich algorithm is accelerated by using graphics processing unit, including flat-detector and curved-detector geometry in the case of helical orbit. An overscan formula is derived, which helps to avoid unnecessary overscan in practical CT scanning. Based on the overscan formula, a volume-blocking method in device memory is proposed. One advantage of the blocking method is that it can reconstruct large volume with high speed.

Adaptive improved element free Galerkin method for quasi- or multi-spectral bioluminescence tomography.

Bioluminescence tomography (BLT) has become a powerful tool for whole-body small animal imaging. In this contribution, an adaptive improved element free Galerkin method (IEFGM) is presented to perform a quantitative reconstruction of the internal light source using quasi- or multi-spectral information, which not only can avoid the time-consuming mesh generation but also can reduce the ill-posedness of BLT effectively. In the algorithm, the reconstruction can be largely enhanced by an adaptive technology based on a posteriori error estimation. Finally, the numerical and physical phantom experiment results show that the bioluminescent source can be recovered accurately.

An anatomical mouse model for multimodal molecular imaging.

In order to evaluate and improve multimodal molecular imaging technology, a three-dimensional anatomical model of a BALB/c mouse was developed based on micro-CT imaging with a liver-specific contrast agent Fenestra LC. By using image processing and interactive segmentation methods, we delineated some primary organs and tissues, including the skin, skeleton, muscle, heart, lung, liver and spleen. Finally, cone-beam x-ray CT and bioluminescence tomography simulation experiments demonstrate the availability and flexibility of the proposed mouse model.

Cone beam micro-CT system for small animal imaging and performance evaluation.

A prototype cone-beam micro-CT system for small animal imaging has been developed by our group recently, which consists of a microfocus X-ray source, a three-dimensional programmable stage with object holder, and a flat-panel X-ray detector. It has a large field of view (FOV), which can acquire the whole body imaging of a normal-size mouse in a single scan which usually takes about several minutes or tens of minutes. FDK method is adopted for 3D reconstruction with Graphics Processing Unit (GPU) acceleration. In order to reconstruct images with high spatial resolution and low artifacts, raw data preprocessing and geometry calibration are implemented before reconstruction. A method which utilizes a wire phantom to estimate the residual horizontal offset of the detector is proposed, and 1D point spread function is used to assess the performance of geometric calibration quantitatively. System spatial resolution, image uniformity and noise, and low contrast resolution have been studied. Mouse images with and without contrast agent are illuminated in this paper. Experimental results show that the system is suitable for small animal imaging and is adequate to provide high-resolution anatomic information for bioluminescence tomography to build a dual modality system.

Three-dimensional bioluminescence tomography based on Bayesian approach.

Bioluminescence tomography (BLT) poses a typical ill-posed inverse problem with a large number of unknowns and a relatively limited number of boundary measurements. It is indispensable to incorporate a priori information into the inverse problem formulation in order to obtain viable solutions. In the paper, Bayesian approach has been firstly suggested to incorporate multiple types of a priori information for BLT reconstruction. Meanwhile, a generalized adaptive Gaussian Markov random field (GAGMRF) prior model for unknown source density estimation is developed to further reduce the ill-posedness of BLT on the basis of finite element analysis. Then the distribution of bioluminescent source can be acquired by maximizing the log posterior probability with respect to a noise parameter and the unknown source density. Furthermore, the use of finite element method makes the algorithm appropriate for complex heterogeneous phantom. The algorithm was validated by numerical simulation of a 3-D micro-CT mouse atlas and physical phantom experiment. The reconstructed results suggest that we are able to achieve high computational efficiency and accurate localization of bioluminescent source.

Galerkin-based meshless methods for photon transport in the biological tissue.

As an important small animal imaging technique, optical imaging has attracted increasing attention in recent years. However, the photon propagation process is extremely complicated for highly scattering property of the biological tissue. Furthermore, the light transport simulation in tissue has a significant influence on inverse source reconstruction. In this contribution, we present two Galerkin-based meshless methods (GBMM) to determine the light exitance on the surface of the diffusive tissue. The two methods are both based on moving least squares (MLS) approximation which requires only a series of nodes in the region of interest, so complicated meshing task can be avoided compared with the finite element method (FEM). Moreover, MLS shape functions are further modified to satisfy the delta function property in one method, which can simplify the processing of boundary conditions in comparison with the other. Finally, the performance of the proposed methods is demonstrated with numerical and physical phantom experiments.

An optimal permissible source region strategy for multispectral bioluminescence tomography.

Multispectral bioluminescence tomography (BLT) attracts increasing more attention in the area of small animal studies because multispectral data acquisition could help in the 3D location of bioluminescent sources. Generally, BLT problem is ill-posed and a priori information is indispensable to reconstruction bioluminescent source uniquely and quantitatively. In this paper, we propose a spectrally solved bioluminescence tomography algorithm with an optimal permissible source region strategy. Being the most different from earlier studies, an optimal permissible source region strategy which is automatically selected without human intervention is developed to reduce the ill-posedness of BLT and therefore improves the reconstruction quality. Furthermore, both numerical stability and computational efficiency benefit from the strategy. In the numerical experiments, a heterogeneous phantom is used to evaluate the proposed algorithm and the synthetic data is produced by Monte Carlo method for avoiding the inverse crime. The results demonstrate the feasibility and potential of our methodology for reconstructing the distribution of bioluminescent sources.