Synthetic high-energy computed tomography image via a Wasserstein generative adversarial network with the convolutional block attention module.

Background: Computed tomography (CT) is now universally applied into clinical practice with its non-invasive quality and reliability for lesion detection, which highly improves the diagnostic accuracy of patients with systemic diseases. Although low-dose CT reduces X-ray radiation dose and harm to the human body, it inevitably produces noise and artifacts that are detrimental to information acquisition and medical diagnosis for CT images. Methods: This paper proposes a Wasserstein generative adversarial network (WGAN) with a convolutional block attention module (CBAM) to realize a method of directly synthesizing high-energy CT (HECT) images through low-energy scanning, which greatly reduces X-ray radiation from high-energy scanning. Specifically, our proposed generator structure in WGAN consists of Visual Geometry Group Network (Vgg16), 9 residual blocks, upsampling and CBAM, a subsequent attention block. The convolutional block attention module is integrated into the generator for improving the denoising ability of the network as verified by our ablation comparison experiments. Results: Experimental results of the generator attention module ablation comparison indicate an optimization boost to the overall generator model, obtaining the synthesized high-energy CT with the best metric and denoising effect. In different methods comparison experiments, it can be clearly observed that our proposed method is superior in the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and most of the statistics (average CT value and its standard deviation) compared to other methods. Because P<0.05, the samples are significantly different. The data distribution at the pixel level between the images synthesized by the method in this paper and the high-energy CT images is also most similar. Conclusions: Experimental results indicate that CBAM is able to suppress the noise and artifacts effectively and suggest that the image synthesized by the proposed method is closest to the high-energy CT image in terms of visual perception and objective evaluation metrics.

High resolution single-shot myocardial imaging using bSSFP with wave encoding.

BACKGROUND: Single-shot balanced steady-state free precession (bSSFP) sequence is widely used in cardiac imaging. However, the limited scan time in one heartbeat greatly hinders its spatial resolution compared to the segmented acquisition mode. Therefore, a highly accelerated single-shot bSSFP imaging technology is needed for clinical use. PURPOSE: To develop and evaluate a wave-encoded bSSFP sequence with high acceleration rates for single-shot myocardial imaging. METHODS: The proposed Wave-bSSFP method is implemented by adding a sinusoidal wave gradient in the phase encoding direction during the readout of bSSFP sequence. Uniform undersampling is used for acceleration. Its performance was first validated via phantom studies by comparison with conventional bSSFP. Then it was evaluated in volunteer studies via anatomical imaging, T2 -prepared bSSFP, and T1 mapping in in-vivo cardiac imaging. All methods were compared with accelerated conventional bSSFP reconstructed using iterative SENSE and compressed sensing (CS), to demonstrate the advantage of wave encoding in suppressing the noise amplification and artifacts induced by acceleration. RESULTS: The proposed Wave-bSSFP method achieved a high acceleration factor of 4 for single-shot acquisitions. The proposed method showed lower average g-factors than bSSFP, and fewer blurring artifacts than CS reconstruction. The Wave-bSSFP with R = 4 achieved higher spatial and temporal resolutions compared with the conventional bSSFP with R = 2 in several applications such as T2 -prepared bSSFP and T1 mapping, and could be applied in systolic imaging. CONCLUSION: Wave encoding can be used to highly accelerate 2D bSSFP imaging with single-shot acquisitions. Compared with the conventional bSSFP sequence, the proposed Wave-bSSFP method can effectively reduce the g-factor and aliasing artifacts in cardiac imaging.

Diagnosis of cardiac abnormalities based on phonocardiogram using a novel fuzzy matching feature extraction method.

BACKGROUND: The diagnosis of cardiac abnormalities based on heart sound signal is a research hotspot in recent years. The early diagnosis of cardiac abnormalities has a crucial significance for the treatment of heart diseases. METHODS: For the sake of achieving more practical clinical applications of automatic recognition of cardiac abnormalities, here we proposed a novel fuzzy matching feature extraction method. First of all, a group of Gaussian wavelets are selected and then optimized based on a template signal. Convolutional features of test signal and the template signal are then computed. Matching degree and matching energy features between template signal and test signal in time domain and frequency domain are then extracted. To test performance of proposed feature extraction method, machine learning algorithms such as K-nearest neighbor, support vector machine, random forest and multilayer perceptron with grid search parameter optimization are constructed to recognize heart disease using the extracted features based on phonocardiogram signals. RESULTS: As a result, we found that the best classification accuracy of random forest reaches 96.5% under tenfold cross validation using the features extracted by the proposed method. Further, Mel-Frequency Cepstral Coefficients of phonocardiogram signals combing with features extracted by our algorithm are evaluated. Accuracy, sensitivity and specificity of integrated features reaches 99.0%, 99.4% and 99.7% respectively when using support vector machine, which achieves the best performance among all reported algorithms based on the same dataset. On several common features, we used independent sample t-tests. The results revealed that there are significant differences (p < 0.05) between 5 categories. CONCLUSION: It can be concluded that our proposed fuzzy matching feature extraction method is a practical approach to extract powerful and interpretable features from one-dimensional signals for heart sound diagnostics and other pattern recognition task.

Digital signal extraction approach for cardiotocography image.

BACKGROUND AND OBJECTIVE: Cardiotocography, commonly called CTG, has become an indispensable auxiliary examination in obstetrics. Generally, CTG is provided in the form of a report, so the fetal heart rate and uterine contraction signals have to be extracted from the CTG images. However, most studies focused on reading data for a single curve, and the influence of complex backgrounds was usually not considered. METHODS: An efficient signal extraction method was proposed for the binary CTG images with complex backgrounds. Firstly, the images' background grids and symbol noise were removed by templates. Then a morphological method was used to fill breakpoints of curves. Moreover, the projection map was utilized to localize the area and the starting and ending positions of curves. Subsequently, data of the curves were extracted by column scanning. Finally, the amplitude of the extracted signal was calibrated. RESULTS: This study had tested 552 CTG images simulated using the CTU-UHB database. The correlation coefficient between the extracted and original signals was 0.9991 ± 0.0030 for fetal heart rate and 0.9904 ± 0.0208 for uterine contraction, and the mean absolute error of fetal heart rate and uterine contraction were 2.4658 ± 1.8446 and 1.8025 ± 0.6155, and the root mean square error of fetal heart rate and uterine contraction were 4.2930 ± 2.9771 and 2.5214 ± 0.9640, respectively. After being validated using 293 clinical authentic CTG images, the extracted signals were remarkably similar to the original counterparts, and no significant differences were observed. CONCLUSIONS: The proposed method could effectively extract the fetal heart rate and uterine contraction signals from the binary CTG images with complex backgrounds.

Advances in the Progression and Prognosis Biomarkers of Chronic Kidney Disease.

Chronic kidney disease (CKD) is one of the increasingly serious public health concerns worldwide; the global burden of CKD is increasingly due to high morbidity and mortality. At present, there are three key problems in the clinical treatment and management of CKD. First, the current diagnostic indicators, such as proteinuria and serum creatinine, are greatly interfered by the physiological conditions of patients, and the changes in the indicator level are not synchronized with renal damage. Second, the established diagnosis of suspected CKD still depends on biopsy, which is not suitable for contraindication patients, is also traumatic, and is not sensitive to early progression. Finally, the prognosis of CKD is affected by many factors; hence, it is ineviatble to develop effective biomarkers to predict CKD prognosis and improve the prognosis through early intervention. Accurate progression monitoring and prognosis improvement of CKD are extremely significant for improving the clinical treatment and management of CKD and reducing the social burden. Therefore, biomarkers reported in recent years, which could play important roles in accurate progression monitoring and prognosis improvement of CKD, were concluded and highlighted in this review article that aims to provide a reference for both the construction of CKD precision therapy system and the pharmaceutical research and development.

Enhanced liver but not muscle OXPHOS in diabetes and reduced glucose output by complex I inhibition.

Mitochondrial function is critical in energy metabolism. To fully capture how the mitochondrial function changes in metabolic disorders, we investigated mitochondrial function in liver and muscle of animal models mimicking different types and stages of diabetes. Type 1 diabetic mice were induced by streptozotocin (STZ) injection. The db/db mice were used as type 2 diabetic model. High-fat diet-induced obese mice represented pre-diabetic stage of type 2 diabetes. Oxidative phosphorylation (OXPHOS) of isolated mitochondria was measured with Clark-type oxygen electrode. Both in early and late stages of type 1 diabetes, liver mitochondrial OXPHOS increased markedly with complex IV-dependent OXPHOS being the most prominent. However, ATP, ADP and AMP contents in the tissue did not change. In pre-diabetes and early stage of type 2 diabetes, liver mitochondrial complex I and II-dependent OXPHOS increased greatly then declined to almost normal at late stage of type 2 diabetes, among which alteration of complex I-dependent OXPHOS was the most significant. In contrast, muscle mitochondrial OXPHOS in HFD, early-stage type 1 and 2 diabetic mice, did not change. In vitro, among inhibitors to each complex, only complex I inhibitor rotenone decreased glucose output in primary hepatocytes without cytotoxicity both in the absence and presence of oleic acid (OA). Rotenone affected cellular energy state and had no effects on cellular and mitochondrial reactive oxygen species production. Taken together, the mitochondrial OXPHOS of liver but not muscle increased in obesity and diabetes, and only complex I inhibition may ameliorate hyperglycaemia via lowering hepatic glucose production.

Induction of apoptosis in human promyelocytic leukemia HL60 cells by panaxynol and panaxydol.

Panaxynol and panaxydol are naturally occurring polyacetylenes, isolated from the lipophilic fractions of Panax notoginseng, that exert anti-proliferative effects against malignant cells. However, to the best of our knowledge, no study concerning the inhibitory effects of the two polyacetylenes on cell growth of human promyelocytic leukemia cells has been reported. In this paper, we examined the antiproliferation and proapoptotic effects of panaxynol and panaxydol on HL60 cells and investigated their mechanism of action. Cell growth inhibition of panaxynol and panaxydol were determined by trypan blue dye exclusion assays. Apoptosis of cells was revealed by morphological observation, analysis for nuclear DNA distribution and by annexin V-FITC/ PI staining using flow cytometry. It was found that panaxynol and panaxydol markedly inhibited proliferation of HL60 cells in a time- and dose-dependent manner via an apoptotic pathway. In concern with these findings, Western blot analysis showed proteolytic activation of PKCδ, caspase-3 activation and cleavage of poly (ADP [adenosine diphosphate]-ribose) polymerase in HL60 cells treated by panaxynol and panaxydol. In conclusion, panaxynol and panaxydol have profound effects on growth and apoptosis of HL60 cells, suggesting those substances are worthy of further exploration as potential anti-cancer agents.

The moment segmentation analysis of heart sound pattern.

UNLABELLED: This paper presents two new ideas. The first one is to apply the Viola integral waveform method to analyze the heart sounds recorded by an electric stethoscope, and the multi-scale moment analysis is proposed to locate each cycle of heart sounds. A fast algorithm for calculating characteristic waveform (CW) and characteristic moment waveform (CMW) of heart sound can be expressed by the Viola integral method, and their calculation time has nothing to do with their scales. The second idea is easier to segment the heart sound based on its approximate cyclical characteristic than the ordinary methods. Each heart sound cycle can be quickly found by CMW's Local Extreme Points (LEPs). Based on the information of LEPs and CW, a high accurate search algorithm to segment S1 and S2 sounds is submitted. By numerical experiments, the important parameters of time scale delta=0.05s for CW and l=0.45s for CMW are obtained and validated for segmentation of heart sound. CONCLUSION: More exact segmentation boundaries of the heart sound signal could be located fast in an automated way, and a further performance analysis is presented. Owing to the use of the rhythm of CMW curves, the proposed method not only gives a higher success segmentation rate, but also it is actually simpler and faster than the wavelet method.

Panaxynol protects cortical neurons from ischemia-like injury by up-regulation of HIF-1alpha expression and inhibition of apoptotic cascade.

Apoptosis is one of the major characteristics of delayed neuronal degeneration in neuronal injury following cerebral ischemia. Hypoxia-induced apoptosis may be co-regulated by HIF-1alpha as well as many other factors. In recent years, numerous studies concerning panaxynol (PNN) have been reported. However, whether PNN can show anti-hypoxia properties is still unknown. In this study, the protective effects of PNN on OGD-induced neuronal apoptosis and potential mechanisms were investigated. Pretreatment of the cells with PNN for 24h following exposure to OGD resulted in a significant elevation of cell survival determined by MTT assay, LDH assay, Hoechst staining and flow cytometric assessment. In addition to enhancing the expression of HIF-1alpha, PNN also normalized the caspase-3 expression/activation and increased the Bcl-2/Bax ratio. In our study, the increased level of HIF-1alpha with decreased cellular apoptosis suggested an important role for HIF-1alpha in hypoxic neurons. These results indicated that the neuroprotective effects of PNN on hypoxic neurons were at least partly due to up-regulation of HIF-1alpha and raised the possibility that PNN might reduce neurodegenerative disorders and ischemic brain diseases.

Cytotoxic phenylpropanoids from carrot.

Carrot is widely used as a foodstuff. The active components such as beta-carotene and panaxynol have been studied by many researchers. In this investigation of nonpolar active components from carrot, a new phenylpropanoid, epilaserine oxide ( 3), was isolated along with six known compounds, laserine ( 1), 2-epilaserine ( 2), panaxynol ( 4), ginsenoyne K ( 5), (8 E)-1,8-heptadecadiene-4,6-diyne-3,10-diol ( 6), and vaginatin ( 7). Their structures were deduced on the basis of spectroscopic methods. Significant cytotoxicity of 2-epilaserine against HL-60 cells was observed, which implied that phenylpropanoids were cytotoxic compounds in carrot. Laserine and 2-epilaserine in carrots from diverse locations in China were quantified by HPLC.