Biomedical Engineering: Applications, Basis and Communications

The NKX2.1 gene is considered as a proto-onco gene to promote the development of early lung adenocarcinoma. In this study, three kinds of specific siRNAs aiming to NKX2.1 gene were designed to down-regulate the expression of NKX2.1 gene, and constructed into rAAV vectors, respectively. NCI-H1975 cells were infected with the rAAV virus. RT-PCR results showed that all the three siRNAs decreased the expression of NKX2.1 mRNA. WB results show that the expression of NKX2.1 protein was decreased too. It is concluded that the siRNA constructed in rAAV could significantly down-regulate the expression of NKX2.1 gene. Meanwhile, it is proven that the rAAV-NKX2.1-siRNA could inhibit the proliferation and induce apoptosis occurrence in NCI-H1975 cells. In this study, we have expected that the rAAV-NKX2.1-siRNA could be developed into a potential genetic engineering therapeutic virus to suppress the lung AC development and metastasis. The current experiment thus makes a foundation for further research on in vivo gene therapy.

According to a research report by the World Health Organization (WHO), breast cancer is the most common type of cancer in women, while the mortality rate of breast cancer of females over 40 years old is extremely high. If detected early, it can be treated early, and the mortality rate of breast cancer can be reduced. Meanwhile, the image processing and pattern recognition technology has been adopted to select suspicious regions, provides alerts to assist in doctors' diagnosis, and reduces misdiagnosis rates due to fatigue of doctors, and improves diagnostic accuracy. Hence, this paper proposed an intelligent breast tumor detection system with texture and contrast features. This system consists of three parts: preprocessing, feature extraction, and learning algorithm. The goal of preprocessing is to obtain a good image quality and a real breast area. In the feature extraction, we extract the two features to describe the breast tumor. These features include Laws' Mask features which are the representation of the texture and modification average distance (MAD) feature which is the representation of the contrast. Each region of interest (ROI) image block will be extracted by these two features. And we will extract useful feature from all extracted features. We hope that a small quantity of feature can be used in our proposed system. Next, we use neural network as learning algorithm to detect the tumor with extracted features. Finally, in the experimental results, we use three databases to verify our proposed system, and two radiologists participated in that process and designed final verification study. Thus, we understand from the experimental results that a detection rate as high as 98% can be achieved by using only a few features and the simplest artificial neural network rather than a large number of features and a complex classifier. The success of the system will improve the accuracy of the existing detection methods, assist medical diagnosis, and decrease the time of the judgment effective by doctors.

Mammography is the most reliable, effective, low cost and highly sensitive method for early detection of breast cancer. Mammogram analysis usually refers to the processing of mammograms with the goal of finding abnormality presented in the mammogram. Mammogram enhancement is one of the most critical tasks in automatic mammogram image analysis. Main purpose of mammogram enhancement is to enhance the contrast of details and subtle features while suppressing the background heavily. In this paper, a hybrid approach is proposed to enhance the contrast of microcalcifications while suppressing the background heavily, using fuzzy logic and mathematical morphology. First, mammogram is fuzzified using Gaussian fuzzy membership function whose bandwidth is computed using Kapur measure of entropy. After this, mathematical morphology is applied on fuzzified mammogram. Mathematical morphology provides tools for the extraction of microcalcifications even if the microcalcifications are located on a nonuniform background. Main advantage of Kapur measure of entropy over Shannon entropy is that Kapur measure of entropy has α and β parameters that can be used as adjustable values. These parameters can play an important role as tuning parameters in the image processing chain for the same class of images. Experiments have been conducted on images of mini-Mammogram Image Analysis Society (MIAS) database (UK). Experiment results of the proposed approach are compared with histogram equalization (HE), contrast limited adaptive histogram equalization (CLAHE) and fuzzy histogram hyperbolization (FHH) which are well-established image enhancement techniques. In order to validate the results, several different kinds of standard test images (fatty, fatty-glandular and dense-glandular) of mini-MIAS database are considered. Objective image quality assessment parameters: Target-to-background contrast enhancement measurement based on standard deviation (TBC_SD), target-to-background contrast enhancement measurement based on entropy (TBC_E), contrast improvement index (CII), peak signal-to-noise ratio (PSNR) and average signal-to-noise ratio (ASNR) are used to evaluate the performance of proposed approach. The experimental results show that the proposed approach performs well. This study can be a part of developing a computer-aided diagnosis (CAD) system for early detection of breast cancer.

Identification of individuals who are at risk for sudden cardiac death (SCD) remains a formidable challenge. T-wave alternans (TWA) evaluation is emerging as an important tool for risk stratification in patients with heart diseases. Several methods have been developed in recent years to detect and quantify TWA. One such method is known as the correlation method (CM). This method performs well for different levels of TWA and phase shifts in the time domain, but it is sensitive to noise and requires higher quality of electrocardiogram (ECG) signal for test. In this paper, we propose a modified correlation method (MCM) to ensure a robust and accuracy detection of TWA. Compared with CM, MCM add a stage of T-wave curve fitting before media T-wave template, and the TWA magnitude is obtained by meaning the maximum absolute difference between even and odd T-wave. Our assessment study demonstrates the improved performance of the proposed algorithm.

This study presents the design and implementation of a high-performance oxygen concentrator (OC) system that can continuously monitor its own operating parameters and report information about the status of the system and patients off-line. In the designed system, the functions related to oxygen production, monitoring facilities, and reporting facilities are performed by its two basic sections: hardware and software. Hardware section is an apparatus supplying oxygen at the required purity, informing patients about the operating parameters of device through a visual display, and periodically saving these parameters to a memory card. In this section, in order to achieve a high-purity oxygen from the system output, a new structure based on the principle of equal pressure application to the surface of molecular sieves is used in the absorption columns of OC apparatus. Software section is an interface program that saves the patient and device information in the memory card into the database, and also allows doctors and technical services to make an assessment and report by using this information. Experimental results show that the proposed system produces oxygen at high purity for flow rates of 1–5 l/min.

The controlling method for high-voltage pulse form or pulse parameter is extremely important in high speed switching technique. Function generation can repeatedly make various forms and widths of pulse waves such as low-voltage sine wave, square wave, and sawtooth wave. Waveform control is not easy when voltage exceeds a certain amount of kVs. Pulse forming network (PFN) or pulse forming line (PFL) has been used so far along with trigger gap, rail gap, semiconductor switch, ignitron, cyratron, and autocompression switch, which are used as switching device. For PFN, multistep LC circuit is introduced to widen the pulse width, and for PFL, a method to lengthen the charging line is adopted. These methods are difficult to control because a large number of devices are used, and the devices are getting bigger in terms of size. In order to compensate this weakness, the researchers of this study made self-stimulating pulse forms with various pulse widths by actively engrafting the low-voltage two-step or four-step circuits with the AVR one-chip microprocessor technology, which is widely used for two-step or four-step electric network recently with low price.

The volume of the skull defect should be one of the most important quantitative measures for decompressive craniectomy. However, there has been no study focusing on automated estimation of the volume from postoperative computed tomography (CT). This study develops and validates three methods that can automatically locate, recover and measure the missing skull region based on symmetry without preoperative images. The low resolution estimate (LRE) method involves downsizing CT images, finding the axis of symmetry for each slice, and estimating the location and size of the missing skull regions. The intact mid-sagittal plane (iMSP) can be defined either by dimension-by-dimension (DBD) method as a global symmetry plane or by Liu's method as a regression from each slices. The skull defect volume can then be calculated by skull volume difference (SVD) with respect to each iMSP. During a 48-month period between July 2006 and June 2010 at a regional hospital in northern Taiwan, we collected 30 sets of nonvolumetric CT images after craniectomies. Three board-certified neurosurgeons perform computer-assisted volumetric analysis of skull defect volume V_Man as the gold standard for evaluating the performance of our algorithm. We compare the error of the three volumetry methods. The error of V_LRE is smaller than that of V_Liu(p < 0.0001) and V_DBD(p = 0.034). The error of V_DBD is significant smaller than that of V_Liu(p = 0.001). The correlation coefficients between V_Man and V_LRE, V_Liu, V_DBD are 0.98, 0.88 and 0.95, respectively. In conclusion, these methods can help to define the skull defect volume in postoperative images and provide information of the immediate volume gain after decompressive craniectomies. The iMSP of the postoperative skull can be reliably identified using the DBD method.

A new wearable assistive device (WAD) was developed to decrease required force on the lumbar spine in static holding tasks. In order to obtain moments on lumbar spine in two conditions, with and without WAD, a biomechanical static model was used for estimation of external moments on lumbar spine. The results of biomechanical models indicated that there was a reduction in the lumbar moment ranging from 20% to 43% using WAD depending on the load and flexion angle. A total of 15 male healthy subjects were tested to experimentally verify the predicted reduction of external moments on the spine by wearing WAD. Normalized electromyography (EMG) of the right and left lumbar and thoracic erector spinae (LES, TES), latissimus dorsi (LD), external oblique (EO), internal oblique (IO) and rectus abdominus (RA) muscles were monitored at three lumbar flexion positions (0°, 30° and 60°) in symmetric posture with three different loads (0, 5 and 15 kg) in two conditions of with and without WAD. The effects of WAD and load were significant for all muscles but the interaction effects were only significant for extensor muscles groups (p < 0.016). Results of statistical analysis (ANOVA) on the normalized EMG while wearing WAD indicated that the muscle activity of right and left LES, TES and LD muscles significantly decreased (p < 0.001). This reduction for right LES, TES, LD muscles at 15 kg load and 60° trunk flexion were 23.2%, 30% and 27.8%, respectively which were in good agreement with the biomechanical model results.

Cervical cancer is a common cancer amongst women, accounting for 9% of female cancer death. There are certain risk factors for the development of cervical cancer, in which human papilloma virus (HPV) infection is believed to be a significant cause. This study aimed at evaluating the inhibitory activity of active compounds derived from Chinese herbs against HPV and the underlying mechanism. First, conventional screening platform which uses HeLa cell line in conjunction with MTT assay was used to evaluate the cytotoxicity of these natural compounds. Then, a novel screening platform, in which the HeLa cells were infected by HPV 16 pseudoviruses expressing green fluorescent protein, was employed to screen for active compounds capable of inhibiting the HPV 16 pseudovirus infection. Two compounds, baicalein and gallic acid, was found to exhibit significant inhibitory activity against HPV 16 pseudovirus with IC₅₀ values of 8.2 and 8.9 μg/ml, respectively. In addition, these two compounds showed insignificant cytotoxicity on HeLa cell line. Screening experiments using a novel dosage form consisting of a hydrophilic PU foam and aquagel indicated that the aquagel also inhibited the HPV 16 pseudovirus infection. In sum, the natural active compounds and novel dosage form proposed by the present study imply a potential treatment for vaginal administration to prevent HPV infection and the diseases it caused.

Separation of rare cells such as circulating cancer and fetal cells from blood has potential importance in disease monitoring and prevention. In this paper, we report a new method of cancer cells separation from patient blood by inertial focusing technique. A design and simulation of ascending and descending curvilinear microchannels for separation of particles resembling cancer cells have been presented. In simulation, polystyrene particles have been used which represent the size of red blood cell (RBC), white blood cell (WBC) and cancer cells. Computational fluid dynamics (CFD) design and simulation of ascending and descending microchannels is used for cell separation. The simulation was carried out in two stages including focusing and separation. The ascending curvilinear channel design demonstrated favorable focusing and separation. Separation with 100% purity and efficiency of the unwanted particle was achieved at Reynolds number (R_e) = 8.50 and velocity 0.105 m/s. In case of descending curvilinear channel, cell separation was not good. Considering cancer cells size about 15 μm, our proposed ascending microchannel is a good candidate for cancer cells separation from blood.

In this work, we used multiphoton microscopic system for characterizing three-dimensional microstructure of collagen/chitosan polymeric scaffolds in a noninvasive fashion. Nonlinear optical signals including multiphoton autofluorescence (MAF) and second harmonic generation (SHG) derived from collagen/chitosan scaffolds were collected and analyzed. The three-dimensional porous microstructures of collagen/chitosan scaffolds were visualized by co-localized and evenly distributed MAF and SHG signals. The distribution of collagen and chitosan compositions within miscible collagen/chitosan blends cannot be either localized or differentiated simply using these nonlinear optical signals. However, the intensity of MAF signals in scaffolds was found to be markedly decreased in correlation to the supplementation of chitosan within blends, regardless of collagen/chitosan weight ratios. It therefore implied that the MAF-generating molecules within collagen being altered in miscible collagen/chitosan blends. And the SHG signals also decreased significantly in collagen/chitosan scaffolds with the supplementation of chitosan, regardless of different weight ratios. This finding supported the hypothesis regarding the miscibility of collagen/chitosan blends that triple helix structure of collagen, a proven SHG-generating microstructure, was altered in miscible collagen/chitosan blends. In conclusion, our work demonstrated that multiphoton imaging modality can be versatile for investigating three-dimensional microstructure of miscible polymeric scaffolds in a minimal invasive fashion, and may potentially be applicable in the field of tissue engineering.

This paper presents modified equations for a nonlinear electrical–thermal model of the skin, and optimizes the parameters of the model by a genetic algorithm. In publications, an electrical–thermal model for the skin has been presented. Although, the model is sophisticated and includes the most of physical phenomena occurring in the skin; however, mathematical equations used in this model for the capacitance and dissipated power are incompletely stated so that they sometimes cause instability in solving the equations. In this paper, the equations given previously for the capacitance current and the dissipated power are first modified. We have considered different inward and outward current in the model, since there are different ions which make this two currents in the skin. Then, a special kind of genetic algorithm is applied to estimate the parameters of the model. The used algorithm is a powerful optimization tool against high-dimensional problems and can overcome the curse of dimensionality. In each iteration, it divides variable sets into two groups: a small set still variable and a large set frozen on their best values. Finally, modeling results are compared with experimental results. The comparison shows there is a good agreement between the modeling and experimental results especially in the steady state regime.

This paper reports a novel design of a surface plasmon resonance (SPR) device that can be developed into a high-performance biosensor. The design utilizes wurtzite crystal structure semiconductor (zinc oxide, ZnO) layers to enhance the SPR signal quality and to improve the full width at half maximum (FWHM) of the SPR reflectivity curve. There exists a new mechanism when the excitation in the plasmon energy is in resonance with the ZnO band-gap (BG) energy transfer process. The excitation energy between Au and ZnO causes an interactive, coupled phenomenon with the ZnO BG (λ_BG = 360–430 nm, 3.1–3.4 eV) when it matches the ZnO–Au interface surface plasmon (400 nm). We have optimized the design of the ZnO and Au thin films thicknesses through analytical comparisons with conventional SPR structures. Upon exposure to ethanol, the ZnO–Au device showed a 2-times decrease in the FWHM and a 4.5-times larger shift in intensity interrogation. The ZnO–Au device exhibits a wider linearity range and very higher sensitivity. This characteristic of the ZnO–Au device is the basis for realizing accurate and specific biomolecular detection.