Synergistic integration of metal nanoclusters and biomolecules as hybrid systems for therapeutic applications

Therapeutic nanoparticles are designed to enhance efficacy, real-time monitoring, targeting accuracy, biocompatibility, biodegradability, safety, and the synergy of diagnosis and treatment of diseases by leveraging the unique physicochemical and biological properties of well-developed bio-nanomaterials. Recently, bio-inspired metal nanoclusters (NCs) consisting of several to roughly dozens of atoms (<2 nm) have attracted increasing research interest, owing to their ultrafine size, tunable fluorescent capability, good biocompatibility, variable metallic composition, and extensive surface bio-functionalization. Hybrid core-shell nanostructures that effectively incorporate unique fluorescent inorganic moieties with various biomolecules, such as proteins (enzymes, antigens, and antibodies), DNA, and specific cells, create fluorescently visualized molecular nanoparticle. The resultant nanoparticles possess combinatorial properties and synergistic efficacy, such as simplicity, active bio-responsiveness, improved applicability, and low cost, for combination therapy, such as accurate targeting, bioimaging, and enhanced therapeutic and biocatalytic effects. In contrast to larger nanoparticles, bio-inspired metal NCs allow rapid renal clearance and better pharmacokinetics in biological systems. Notably, advances in nanoscience, interfacial chemistry, and biotechnologies have further spurred researchers to explore bio-inspired metal NCs for therapeutic purposes. The current review presents a comprehensive and timely overview of various metal NCs for various therapeutic applications, with a special emphasis on the design rationale behind the use of biomolecules/cells as the main scaffolds. In the different hybrid platform, we summarize the current challenges and emerging perspectives, which are expected to offer in-depth insight into the rational design of bio-inspired metal NCs for personalized treatment and clinical translation.

A review of automatic liver tumor segmentation based on computed tomography / 生物医学工程学杂志

Liver cancer is a common type of malignant tumor in digestive system. At present, computed tomography (CT) plays an important role in the diagnosis and treatment of liver cancer. Segmentation of tumor lesions based on CT is thus critical in clinical diagnosis and treatment. Due to the limitations of manual segmentation, such as inefficiency and subjectivity, the automatic and accurate segmentation based on advanced computational techniques is becoming more and more popular. In this review, we summarize the research progress of automatic segmentation of liver cancer lesions based on CT scans. By comparing and analyzing the results of experiments, this review evaluate various methods objectively, so that researchers in related fields can better understand the current research progress of liver cancer segmentation based on CT scans.

Value of acoustic radiation force impulse elastography in evaluation of nonalcoholic fatty liver disease and hepatic fibrosis in rats / 中国医学影像技术

Objective To evaluate the value of acoustic radiation force impulse (ARFI) elastography in assessment of nonalcoholic fatty liver disease (NAFLD) and hepatic fibrosis in rats.Methods Models with various degrees of NAFLD severity were conducted in 110 rats by feeding high fat emulsion.The right liver lobe of rat models were processed and embedded in a fabricated gelatin solution to measure the shear wave velocity (SWV) by ARFI.And the other liver lobes were used for histologic assessment.Based on NAFLD activity score (NAS),the final pathologic NAFLD diagnosis were considered as normal group (NAS=0),simple steatosis (SS) group (1≤NAS≤2),borderline (3≤NAS≤4) group and nonalcoholic steatohepatitis (NASH) group (NAS≥5).The diagnostic accuracy of the SWV parameters in evaluating NAFLD severity and fibrosis stages was studied using ROC curves.Results The difference of SWV values among normal group,SS group,borderline group and NASH group was statistically significant (F=31.53,P＜0.001).Taking SWV≥ 2.54 m/s as the diagnostic standard to differentiate normal rats from rats with SS,and SWV≥2.90 m/s to differentiate SS from NASH in rats,the area under ROC curve (AUC) was 0.922 (95％CI [0.871,0.973],P＜0.001) and 0.882 (95％ CI [0.807,0.956],P＜0.001) respectively.The sensitivity and specificity were 93.5 ％ and 100 ％ for differentiating normal and SS groups,83.3 ％ and 84.2 ％ for differentiating SS and NASH groups.Taking SWV≥3.48 m/s as cutoff to predict fibrosis (≥F2 stage),the AUC was 0.963 (95％CI [0.909,1.000],P＜0.001),the sensitivity was 92.9％ and the specificity was 97.6％.Taking SWV≥3.61 m/s as cutoff to predict severe fibrosis (≥F3 stage),the AUC was 0.997 (95％CI [0.990,1.000],P＜0.001),sensitivity was 100％ and specificity was 98.9％.The same high validity was maintained as in the prediction of cirrhosis (F4 stage) with the cutoff as SWV≥4.50 m/s,and the AUC was 0.993 (95％CI [0.982,1.000],P＜0.001),the sensitivity was 100 ％ and the specificity was 96.8％.Conclusion ARFI elastography is a promising method for differentiating the different severity of NAFLD and staging the degree of hepatic fibrosis with NAFLD in rat models.

The computer-aided diagnosis of attention-deficit hyperactivity disorder and autism spectrum disorder based on structural magnetic resonance imaging / 中华行为医学与脑科学杂志

Child and adolescent mental disorders are common disorders with various symptoms,and attracting more attention due to the increasing prevalence.Mental disorders,especially the attention-deficit hyperactivity disorder (ADHD) and the autism spectrum disorder (ASD),have great influence on the development of children and adolescents.Nowadays,the biomarkers from neuroimaging such as magnetic resonance imaging (MRI) have a great importance on the diagnosis of mental disorders,and machine learning has been proved to be very powerful in the processing for neuroimages.Nowadays,many researchers are focusing on the studies of computer-aided diagnosis (CAD) based on machine learning and neuroimaging.In this review,the technical details of machine learning based CAD of child and adolescent mental disorders are briefly introduced,and the research progress in CAD of ADHD and ASD based on machine learning and structural MRI are summarized.These studies showed that many machine learning methods have been used in the diagnosis of child and adolescent mental disorders,but the relevant methods cannot be applied to clinical diagnosis.Further studies should be conducted to improve the diagnostic ability of machine learning methods from multiple perspectives,and provide an objective and reliable tool for the clinical diagnosis of child and adolescent mental disorders.

Analysis of diagnosis and treatment of 18 patients with primary presacral tumor / 中国医师进修杂志

Objective To investigate the diagnosis and treatment of primary presacral tumor. Methods The clinical data of 18 patients with primary presacral tumor were retrospectively analyzed. Results Preoperative diagnosis of primary presacral tumor depended on digital rectal examination, endorectal ultrasound, CT, MRI, et al. The surgical approaches of 18 cases included posterior approach (14 cases) and abdominoperineal approach (4 cases). All tumors were completely resected. Postoperative complications were rectal injury (1 case) and wound infection (2 cases), which were cured by symptomatic treatment. Postoperative pathological results showed that 15 cases had benign lesions and 3 cases had malignant lesions. Sixteen patients were followed up from 0.5 to 5.0 years, with recurrence in 2 cases and death in 2 cases. Conclusions Primary presacral tumor should be treated with operation. Sufficient preoperative examination, personalized operative planning, subtle manipulation operative procedures with an experienced multidisciplinary team, are the important points in preventing or reducing recurrence. Endorectal ultrasound plays an important role in the diagnosis and treatment of primary presacral tumor.

Design and Application of Portable Micro Sleep Monitoring System / 中国医疗器械杂志

Through the study of the pathology of sleep apnea-hypopnea syndrome, evaluation indexes, diagnosis requirements and so on, a portable sleep monitoring system was designed, which had the characteristics of convenience, wireless transmission and no disturbance. The system can be assessed by respiration monitoring and pulse oximetry, which is based on the pressure variation in miniature air-bag and spectral absorption method. It provides the value of the apnea-hypopnea index (AHI), which is used to evaluate OSAHS severity. The experiment of the system's stability and accuracy is done, which exhibits good performance, it can diagnose OSAHS effectively and provide convenience for home monitoring.

Research Progress of Medical Ultrasound Assessment of Placental Function / 生物医学工程学杂志

Our country has been using maturity grading method, which was proposed by Grammum in 1979, to evaluate the placental function. However, this method is subjective to consequence because it totally depends on the observation and experiences of clinicians. With the development of ultrasound technology, therefore, we reviewed more novel applications in other aspects of placenta (such as blood flow, vascularization, etc). Over the past years, scholars in the world have done a lot of research around these topics. In this review we introduce placental maturity grading with B-mode ultrasound, placental vascularization qualitative and quantitative analysis with three-dimensional Doppler ultrasound and placental volume measurement, respectively.

Design of acoustic radiation force module for ultrasound elastography / 中国医疗器械杂志

Developing an acoustic radiation force excitation module including 64 channels based in FPGA for ultrasound elastography. The circuit of the module was derived in bipolar, and the parameters such as excitation frequency, pulse repetition frequency, pulse number, element number and focus depth were adjustable. The acoustic field for special parameter was experimented with OptiSon laser acoustic field system with a result which reflects the width of focal spot is about 3 mm. The acoustic power was experimented with RFB2000 radiation force balance with a result which reflects acoustic power is increasing linearly with the number of pulses and the number of elements, and is increasing squarely with the peak-to-peak value of excitation voltage. The module is promising in factual application which can be triggered externally in synchronously, and can be combined with B-mode ultrasound system for ultrasound elastography.

The development and transplantation of LCD module-based interface for medical diagnosis instrument / 中国医疗器械杂志

Based on LCD Module and Visual C++ development environment, this paper proposes a new method which can quickly develop the human-machine interface .We define a LCD module programming interface by designing Serial Communication Class(SCS). On this basis,we achieve the transplantation on an Embedded ARM Platform to fulfil the requirements of Medical Diagnostic Instruments (MDI). Experimental results show that this method has advantages of short development cycle and high level transplantation which has broad application prospects in the field of Medical Diagnosis Instrument.

Instruction of clinical testing method for medical devices / 中国医疗器械杂志

The article introduces the clinical testing method for the product of patient monitor, the definition of direct measurement and indirect measurement method, and the different testing methods. The clinical testing methods for none invasive blood pressure, pulse oxygen saturation and ECG analysis have significant value, which are important solutions to test the safety and effectiveness of medical devices by using the equivalent analysis method. These methods above are also provided as reference for other medical devices' clinical testing.

Finite element analysis of the dynamic behaviour of a microbubble within a rigid micro-tube / 生物医学工程学杂志

The dynamic behaviour of a microbubble confined within a rigid micro-tube was studied using finite element method. The results indicated that the microbubble oscillation was limited when constrained within the micro-tube. Both the expansion ratio of its effective radius and natural frequency decreased with the decrease of the tube radius. Meanwhile, the deformation of the microbubble was non-spherical and became more significant when the ultrasound pressure amplitude increased. The dynamic behaviour in micro-tube was different from that in infinite liquid.

An investigation on the in vitro release behavior of TCM components in different pressure sensitive adhesives / 中成药

AIM: To examine the effect of acrylic ester and thermosol respectively as pressure sensitive adhesive matrix of zhitong huoxue extract ( Rhizoma Corydalis,Radix aconiti,Radix Paeoniae alba,Radix et notoginseng ginseng,etc) on the dissolution of effective constituent from zhitong huoxue extract.METHODS: The in vitro release experiment was carried out on Permcell diffusion cell,HPLC method was applied to determining the cumulative elease rate of tetrahydropalmatine,aconitine,paeoniflorin and ginsenoside Rg_1 from zhitong huoxue pressure sensitive adhensive.RESULTS: The acrylic ester matrix had sound controlled release profile in vitro of alkaloid components.In KT-A thermosol matrix,the in vitro release rate proved to be inversely proportional to the molecular weight (R = 0.91 ) of the effective constituents,while the 2501 s matrix presented a steadily cumulative release rate over 12 h (30% -43% ).CONCLUSION: Good release rates are observed with effective constituent with small molecular weight,adhesive composition of matrix has an obvious effect on the in vitro release behavior of zhitong huoxue extract.

Recognition of liver steatosis degree based on multi-fractal spectrum of type-B ultrasonic image / 中国医学影像技术

Objective To develop a recognition method of liver steatosis degree on type-B ultrasonic images based on multi-fractal spectrum texture analysis method and pattern recognition. Methods Features of singularity strength width and multi-spectrum area were extracted from the curve of multi-fractal spectrum of each liver ultrasonic images. These two features and the feature of mean intensity ratio comprised a three-dimensional feature vector, which would be classified by BP neural network. Results The classification accuracy was 96.00% for normal liver, 80.00% for mild fatty liver, 88.00% for moderate fatty liver and 92.00% for severe fatty liver. Conclusion Feature vector combined with BP neural network can identify the steatosis degree of liver on the ultrasonic images and can be used as an assistant diagnostic method.

A water-fat separation imaging method for the brain on low field magnetic resonance imaging / 药物分析学报

Water-fat separation is a particularly important problem for magnetic resonance imaging. Although many methods have been proposed, the reliability is still challenging. In this work, we have presented a method based on the combination of the branch-cut method and multigrid algorithm to get a more robust performance of water-fat separation. First, the branch-cut method is applied to identify residues, which violates the requirement that the interacting phase gradient around a closed path be zero. Residues and branches are marked to be zeros and filled to the weighting factor array. Then, the unwrapped phase array can be given by the multigrid algorithm. Finally, the Dixon method for water-fat separation is applied to the unwrapped phase array. Experiments for brain scanning on the 0.3T low field MRI system demonstrate the successful application of the proposed method.

Facial expression recognition based on feature selection by quadratic mutual information / 生物医学工程学杂志

To solve the problem of imprecise positioning of feature point and of the feature data redundancy in facial expression recognition by active appearance models (AAM), the automatic adjustment of initial model for AAM fitting is proposed in this paper. The specific aims are to improve the precision of positioning and to more effectively reflect the variation of expressions by acquired features. The problem of feature selection is resolved by adopting quadratic mutual information and reducing the feature dimension. The support vector machine (SVM) classifier is used for expression recognition. The experimental results on CAS-PEAL facial expression database show that the proposed method effectively improves the performance of facial expression recognition, the maximum recognition rate being 83.33%.

Segmentation of ultrasonic medical image based on a symmetric region growing algorithm / 生物医学工程学杂志

A method based on a symmetric region growing algorithm is presented for the segmentation of ultrasonic medical image. The method divides into three steps. First, according to the characteristic of the ultrasonic medical images, an adaptive weighted median filter is used to suppress speckle noise. Then, scan the digital image from the first row and grow regions from each scanned point by applying the growth criteria and combination criteria until all image pixels have been scanned. Examine the resulting regions using the seed criteria. If any point of a region satisfies the criteria for the region of interest region, assign the region to the resulting segmented image. The effectiveness of this method and a group of growth criteria as well as combination criteria applicable to ultrasonic medical image have been obtained by cardiac ultrasound image segmentation experiments. The experiment result shows that this method is good in the performance of the segmention of cardiac ultrasonic medical image.

A medical ultrasonic image filtering method based on morphological reconstruction / 生物医学工程学杂志

Speckle is the main reason which declines the quality of medical ultrasonic images. In this paper, the initial condition for the Downhill filter, a morphological reconstruction algorithm, is modified and applied in the speckle reduction. Firstly, the initial area and start position as the mark image was determined in the marker image. Then the modified Downhill filter was used in the ultrasonic marker image. The results showed that, in comparison with the other three filters, this modified Downhill filter, while maintaining the integrity of the contour,could reduce the speckle in the regions of cavity efficiently and rapidly.

Filtering and contrast enhancement of medical ultrasonic image / 生物医学工程学杂志

Lower contrast and speckle noise are the main reasons which decline the quality of medical ultrasonic images. In this paper, a new method is proposed to filter the speckle noises and enhance the contrast simultaneously. Anisotropic diffusion filtering method was firstly applied to filter images. Then the loss of information, which the contrast function of contrast enhancement model lies on, was obtained. Finally, the contrast can be enhanced by using enhancement model. Experimental results show that the proposed method not only removes the speckle noises effectively, but also enhances the contrast obviously. This method supplies an effective approach for improving the quality of medical ultrasonic images.

Fast edge extraction for ultrasound image of breast tumor based on fuzzy number / 生物医学工程学杂志

An accurate edge extraction method for the ultrasound breast tumor image is useful for classifying tumors as benign or malignant. This paper refers to a fast technique to extract edge of breast tumor from ultrasound image. This method uses the triangular fuzzy number to build up a fuzzy number plane whose basic unit is the marching square. It is possible to visualize at once the results obtained using different presumption levels. Experiments of benign and malignant breast tumor in ultrasound images have shown that our method can extract the breast tumor edge faster than many conventional methods can do separately, and the results are reliable and credible. Our experiments demonstrate that it can be efficiently used to extract the edge of breast tumor from the ultrasound image.

The recognition of breast tumor based on ultrasonic image contour features / 生物医学工程学杂志

The purpose of this article is to evaluate the role of quantitative margin features in the computer-aided diagnosis of malignant and benign solid breast masses using sonographic imaging. The tumour was seperated by the expert. Three contour features circurity (C), area ratio (A) and length width ratio (LWR) was caculated from the tumour contour. Then back-propagation (BP) neural network with contour features was used to classify tumors into benign and malignant. Results from 119 ultrasonic images have been applied in this experiment. BP neural network yielded the following results: 89.7% and 73.5% respectively. The methods applied in this paper are helpful to raise the correctance of breast cancer diagnosis.