[Effects of different hypoxic concentrations on biological characteristics of human dental pulp stem cells in vitro].

PURPOSE: To investigate the effects of different hypoxic concentrations on biological characteristics of human dental pulp stem cells in vitro. METHODS: Impacted mandibular third molars were extracted from healthy individuals, and the dental pulp stem cells were cultured by tissue block enzyme digestion. Cells cultured under the conditions of 3%, 5% and 21% oxygen concentration for 7 days were set as 3% hypoxia group, 5% hypoxia group, and 21% nomoxia group, respectively. Flow cytometry was used to detect cell surface markers, cell cycle and apoptosis. Cell proliferation was measured by CCK-8 method. Transwell chamber assay was used to detect migration ability. Statistical analysis was completed by SPSS 20.0 software package. RESULTS: The expression rates of CD44, CD29 and D73 of the subculture cells were 97.25%, 99.36% and 99.60%, respectively. The proliferation ability of dental pulp stem cells was the strongest in 5% hypoxia group, and weakest in 3% hypoxia group, with significant difference(P<0.05). The apoptosis rate had no significant difference among various concentrations of oxygen(P>0.05). Compared with 21% nomoxia group, the proportion of dental pulp stem cells in G1 phase was significantly lower than that in 3% hypoxia group and 5% hypoxia group(P<0.05), and cell in S phase was significantly higher than that in 3% hypoxia group and 5% hypoxia group(P<0.05). The migration ability was the strongest in 3% hypoxia group, and weakest in 21% nomoxia group, with significant difference(P<0.05). CONCLUSIONS: Different concentrations of hypoxia have great influence on the morphology, proliferation, migration and cell cycle of human dental pulp stem cells in vitro with little impact on cell apoptosis.

Quantitative analysis of non-alcoholic fatty liver in rats via combining multiple ultrasound parameters.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. The noninvasive and accurate classification of NAFLD is still a challenging problem. In this study we pro- posed a new quantitative ultrasound (QUS) technique, which combined multiple QUS parameters for distinguishing steatosis stages. NAFLD was induced in the livers of 57 rats by gavage feeding with a high fat emulsion, while 8 rats were given a standard diet to serve as controls. Ex vivo ultrasound mea- surement was conducted for capturing the radiofrequency signal. Six QUS parameters were extracted and selected for linear combination. The results show that the overall performance of the combined parameter is better than that of the single QUS parameter. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) while using our proposed method to distinguish mild steatosis (stage S1) from the steatosis under stage S0 are 90.1%, 0.93, 0.88 and 0.97 respectively. In conclusion, the proposed method in this study can make up for the deficiency of single parameter and improve the quantitative staging ability of fatty liver, and thus could play an important role in the diagnosis of NAFLD.

Correction: A new AIE multi-block polyurethane copolymer material for subcellular microfilament imaging in living cells.

Correction for 'A new AIE multi-block polyurethane copolymer material for subcellular microfilament imaging in living cells' by Yu-qing Niu et al., Chem. Commun., 2017, DOI: .

A new AIE multi-block polyurethane copolymer material for subcellular microfilament imaging in living cells.

A multi-block fluorescent amphiphilic polyurethane copolymer (TPE-PU), self-assembling into hairy, water-soluble micelles, is used as a subcellular microfilament probe in living cells.

Improved shear wave motion detection using coded excitation for transient elastography.

Transient elastography (TE) is well adapted for use in studying liver elasticity. However, because the shear wave motion signal is extracted from the ultrasound signal, the weak ultrasound signal can significantly deteriorate the shear wave motion tracking process and make it challenging to detect the shear wave motion in a severe noise environment, such as within deep tissues and within obese patients. This paper, therefore, investigated the feasibility of implementing coded excitation in TE for shear wave detection, with the hypothesis that coded ultrasound signals can provide robustness to weak ultrasound signals compared with traditional short pulse. The Barker 7, Barker 13, and short pulse were used for detecting the shear wave in the TE application. Two phantom experiments and one in vitro liver experiment were done to explore the performances of the coded excitation in TE measurement. The results show that both coded pulses outperform the short pulse by providing superior shear wave signal-to-noise ratios (SNR), robust shear wave speed measurement, and higher penetration intensity. In conclusion, this study proved the feasibility of applying coded excitation in shear wave detection for TE application. The proposed method has the potential to facilitate robust shear elasticity measurements of tissue.

Early exposure of rotating magnetic fields promotes central nervous regeneration in planarian Girardia sinensis.

Magnetic field exposure is an accepted safe and effective modality for nerve injury. However, it is clinically used only as a supplement or salvage therapy at the later stage of treatment. Here, we used a planarian Girardia sinensis decapitated model to investigate beneficial effects of early rotary non-uniform magnetic fields (RMFs) exposure on central nervous regeneration. Our results clearly indicated that magnetic stimulation induced from early RMFs exposure significantly promoted neural regeneration of planarians. This stimulating effect is frequency and intensity dependent. Optimum effects were obtained when decapitated planarians were cultured at 20 °C, starved for 3 days before head-cutting, and treated with 6 Hz 0.02 T RMFs. At early regeneration stage, RMFs exposure eliminated edema around the wound and facilitated subsequent formation of blastema. It also accelerated cell proliferation and recovery of neuron functionality. Early RMFs exposure up-regulated expression of neural regeneration related proteins, EGR4 and Netrin 2, and mature nerve cell marker proteins, NSE and NPY. These results suggest that RMFs therapy produced early and significant benefit in central nervous regeneration, and should be clinically used at the early stage of neural regeneration, with appropriate optimal frequency and intensity.

Analyzing and modeling rheological behavior of liver fibrosis in rats using shear viscoelastic moduli.

The process of liver fibrosis changes the rheological properties of liver tissue. This study characterizes and compares liver fibrosis stages from F0 to F4 in rats in terms of shear viscoelastic moduli. Here two viscoelastic models, the Zener model and Voigt model, were applied to experimental data of rheometer tests and then values of elasticity and viscosity were estimated for each fibrosis stage. The results demonstrate that moderate fibrosis (≤F2) has a good correlation with liver viscoelasticity. The mean Zener elasticity E1 increases from (0.452±0.094) kPa (F0) to (1.311±0.717) kPa (F2), while the mean Voigt elasticity E increases from (0.618±0.089) kPa (F0) to (1.701±0.844) kPa (F2). The mean Zener viscosity increases from (3.499±0.186) Pa·s (F0) to (4.947±1.811) Pa·s (F2) and the mean Voigt viscosity increases from (3.379±0.316) Pa·s (F0) to (4.625±1.296) Pa·s (F2). Compared with viscosity, the elasticity shows smaller variations at stages F1 and F2 no matter what viscoelastic model is used. Therefore, the estimated elasticity is more effective than viscosity for differentiating the fibrosis stages from F0 to F2.

Quantitative imaging of young's modulus of soft tissues from ultrasound water jet indentation: a finite element study.

Indentation testing is a widely used approach to evaluate mechanical characteristics of soft tissues quantitatively. Young's modulus of soft tissue can be calculated from the force-deformation data with known tissue thickness and Poisson's ratio using Hayes' equation. Our group previously developed a noncontact indentation system using a water jet as a soft indenter as well as the coupling medium for the propagation of high-frequency ultrasound. The novel system has shown its ability to detect the early degeneration of articular cartilage. However, there is still lack of a quantitative method to extract the intrinsic mechanical properties of soft tissue from water jet indentation. The purpose of this study is to investigate the relationship between the loading-unloading curves and the mechanical properties of soft tissues to provide an imaging technique of tissue mechanical properties. A 3D finite element model of water jet indentation was developed with consideration of finite deformation effect. An improved Hayes' equation has been derived by introducing a new scaling factor which is dependent on Poisson's ratios v, aspect ratio a/h (the radius of the indenter/the thickness of the test tissue), and deformation ratio d/h. With this model, the Young's modulus of soft tissue can be quantitatively evaluated and imaged with the error no more than 2%.

Highly sensitive computer aided diagnosis system for breast tumor based on color Doppler flow images.

A computer-aided diagnosis (CAD) system for breast tumor based on color Doppler flow images is proposed. Our system consists of automatic segmentation, feature extraction, and classification of breast tumors. First, the B-mode grayscale image containing anatomical information was separated from a color Doppler flow image (CDFI). Second, the boundary of the breast tumor was automatically defined in the B-mode image and then morphologic and gray features were extracted. Third, an optimal feature vector was created using K-means cluster algorithm. Then a back-propagation (BP) artificial neural network (ANN) was used to classify breast tumors as benign, malignant or uncertain. Finally, the blood flow feature was extracted selectively from the CDFI, and was used to classify the uncertain tumor as benign or malignant. Experiments on 500 cases show that the proposed system yields an accuracy of 100% for the malignant and 80.8% for the benign classification. Comparing with other systems, the advantage of our system is that it has a much lower percentage of malignant tumor misdiagnosis.

A fast automatic recognition and location algorithm for fetal genital organs in ultrasound images.

Severe sex ratio imbalance at birth is now becoming an important issue in several Asian countries. Its leading immediate cause is prenatal sex-selective abortion following illegal sex identification by ultrasound scanning. In this paper, a fast automatic recognition and location algorithm for fetal genital organs is proposed as an effective method to help prevent ultrasound technicians from unethically and illegally identifying the sex of the fetus. This automatic recognition algorithm can be divided into two stages. In the 'rough' stage, a few pixels in the image, which are likely to represent the genital organs, are automatically chosen as points of interest (POIs) according to certain salient characteristics of fetal genital organs. In the 'fine' stage, a specifically supervised learning framework, which fuses an effective feature data preprocessing mechanism into the multiple classifier architecture, is applied to every POI. The basic classifiers in the framework are selected from three widely used classifiers: radial basis function network, backpropagation network, and support vector machine. The classification results of all the POIs are then synthesized to determine whether the fetal genital organ is present in the image, and to locate the genital organ within the positive image. Experiments were designed and carried out based on an image dataset comprising 658 positive images (images with fetal genital organs) and 500 negative images (images without fetal genital organs). The experimental results showed true positive (TP) and true negative (TN) results from 80.5% (265 from 329) and 83.0% (415 from 500) of samples, respectively. The average computation time was 453 ms per image.

[Current research status of image-guided neurosurgery].

Image-guided neurosurgery is playing a more and more important role in modern neurosurgical therapy. The current trend is to construct an open platform for image-guided neurosurgery, to make applied researches of various new therapeutic techniques, and finally to integrate them into the clinical image-guided neurosurgery system.