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Objective This study aimed to investigate whether ultrasound parameters during non-painful episodes could indicate impaired differential renal function (DRF) in patients with ureteropelvic junction obstruction (UPJO) and intermittent abdominal pain. Methods We conducted a retrospective review of all cases of unilateral UPJO with intermittent abdominal pain undergoing their first pyeloplasty between March 2019 and October 2021. Clinical characteristics, such as gender, affected side, age at the first onset of pain, waiting time for pyeloplasty, age, and concurrent symptoms, were collected. Ultrasound examination (US) was used to measure the anteroposterior diameter (APD) and renal parenchyma thickness (PT) during intermittent pain episodes and dynamic renal scintigraphy (RDS) was used to assess DRF. Results This study investigated the characteristics and demographics of 109 patients with UPJO. Of the patients, 28.4% had baseline DRF less than 40%, and factors affecting baseline DRF were analyzed. Patients diagnosed with hydronephrosis before the onset of pain had a lower risk of DRF impairment compared to those diagnosed after the onset of pain (p = 0.021). Patients with impaired renal function had larger APD and thinner PT values on ultrasound (p = 0.002, p༜0.001). Abdominal pain accompanying symptoms were found to be associated with DRF impairment (p = 0.044). Multifactorial analysis identified that right UPJO, diagnosis of UPJO after pain onset, large APD, and thin PT were risk factors for baseline DRF damage in patients with intermittent abdominal pain (p༜0.05). Conclusion Patients with right-sided UPJO, UPJO diagnosed after a pain episode, and those with larger APD and thinner PT on ultrasound during pain-free intervals were more likely to have DRF impairment.

Numerous lung nodule candidates can be produced through an automated lung nodule detection system. Classifying these candidates to reduce false positives is an important step in the detection process. The objective during this paper is to predict real nodules from a large number of pulmonary nodule candidates. Facing the challenge of the classification task, we propose a novel 3D convolution neural network (CNN) to reduce false positives in lung nodule detection. The novel 3D CNN includes embedded multiple branches in its structure. Each branch processes a feature map from a layer with different depths. All of these branches are cascaded at their ends; thus, features from different depth layers are combined to predict the categories of candidates. The proposed method obtains a competitive score in lung nodule candidate classification on LUNA16 dataset with an accuracy of 0.9783, a sensitivity of 0.8771, a precision of 0.9426, and a specificity of 0.9925. Moreover, a good performance on the competition performance metric (CPM) is also obtained with a score of 0.830. As a 3D CNN, the proposed model can learn complete and three-dimensional discriminative information about nodules and non-nodules to avoid some misidentification problems caused due to lack of spatial correlation information extracted from traditional methods or 2D networks. As an embedded multi-branch structure, the model is also more effective in recognizing the nodules of various shapes and sizes. As a result, the proposed method gains a competitive score on the false positive reduction in lung nodule detection and can be used as a reference for classifying nodule candidates.

Objective To analyze the imaging and clinical features of fetal cardiac tumors, and to explore the relationship between tuberous sclerosis complex (TSC) and cardiac rhabdomyoma in the fetus. Methods Fifty-three women pregnant with a fetus affected by cardiac tumor(s) were examined by standardized fetal echocardiography (FE), and fetuses, mothers and fathers, including other relevant family members if necessary, underwent familial TSC genetic testing. Relevant pathological features, including pathological findings at clinical examination of liveborn infants and autopsy findings in terminated cases, were noted. Results Of the 53 fetuses, 37 had multiple cardiac tumors and 16 had a single cardiac tumor detected by FE. In all 53 fetuses and their families, TSC genetic testing was successful, showing that 37 of the fetuses had a TSC1 (n = 6) or TSC2 (n = 31) pathogenic or suspected pathogenic mutation, of which 25 were spontaneous and 12 were familial mutations. The proportion of single and multiple cardiac tumors at FE was significantly different between the group of fetuses with positive genetic test results and that with negative results for TSC (31% and 86%, respectively), although the presence of multiple or single tumors was not associated with the type of TSC mutation. The decision to terminate the pregnancy was made by 45 women and their families, and eight fetuses were liveborn. Autopsy was performed in 38 fetuses, which revealed 36 cases with pathologically confirmed cardiac rhabdomyoma, one case of hemangioma and one case of fibroma. 93% of fetuses with multiple rhabdomyomas at autopsy and 71% of those with a single cardiac rhabdomyoma harbored a TSC1 or TSC2 mutation. Conclusion Cardiac rhabdomyoma is the most common cardiac tumor in the fetus. The correlation between cardiac rhabdomyoma and TSC is strong regardless of the presence of single or multiple tumors. For fetuses with suspected cardiac rhabdomyoma identified by FE, prenatal genetic testing for TSC of both fetus and family members is recommended. A positive genetic diagnosis can help in counseling and planning for neonatal treatment. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

Aims We assessed the viable myocardium status and investigated the relationship between collaterals with the ischemia burden and myocardial viability utilizing cardiac magnetic resonance imaging (CMR) and adenosine stress single-photon emission computed tomography (SPECT). Methods and results 150 consecutive patients with at least one native CTO artery, as confirmed by coronary arteriography or coronary CT angiography, were prospectively recruited. SPECT examination was accepted by only 50 patients while declined by the other 100 patients for reasons such as financial problems. Of all segments in the 173 CTO artery territories, only 10.4% exhibited transmural myocardial infarction and 60.2% showed no late gadolinium enhancement. Among 50 patients who completed SPECT examination, 36 patients showed inducible perfusion defect in CTO territory, and the proportion of the ischemic area of 42% patients was over 10%. Conclusion Most patients with CTO had different degrees of myocardial infarction detected by CMR, but only a minority of them showed transmural infarction and cardiac function in patients with transmural infarction declined compared to those without transmural infarction. Approximately half of CTO patients exhibited inducible ischemia in CTO territory. Based on this, a large proportion of patients potentially benefit from CTO-PCI. Figure 1. Relationship between WMSI, LVE Funding Acknowledgement Type of funding source: Other. Main funding source(s): Beijing Municipal Education Commission Science and Technology Plan for 2020, Capital Health Development Research Project (no. 2018-2-2063)

Photodynamic therapy (PDT) is generally safer and less invasive than conventional strategies for head and neck cancer treatment. However, currently available photosensitizers have low selectivity for tumor cells, and the burden and side effects are so great that research is needed to develop safe photosensitizers. In this study, it was confirmed that the Buddleja officinalis (BO) extract, used in the treatment of inflammation and vascular diseases, shows fluorescence when activated by LED light, and, based on this, we aimed to develop a new photosensitive agent suitable for PDT. MTT, Diff-Quick® staining, and DCF-DA were performed to measure the effects of treating head and neck cancer cells with BO extract and 625 nm LED light (BO-PDT). Cell cycle, TUNEL, and western blot assays, as well as acridine orange staining, were performed to explore the mechanism of BO-PDT-induced cell death. We found that when the BO extract was irradiated with 625 nm LED light, it showed sufficient fluorescence and stronger intracellular toxicity and ROS effect than the currently commercially available hematoporphyrin. BO-PDT resulted in a decrease of mTOR activity that was correlated with an increase in the levels of ATG5, beclin-1, and LC3-II, which interfere with the formation of autophagosomes. In addition, BO-PDT induced the activation of PARP and led to an increase in the expression of proapoptotic protein Bax and a decrease in the expression of the antiapoptotic protein Bcl-2. Moreover, BO-PDT has been shown to induce the autophagy pathway 4 h after treatment, while apoptosis was induced 16 h after treatment. Finally, we confirmed that BO-PDT caused cell death of head and neck cancer cells via the intrinsic pathway. Therefore, we suggest that BO extract can be used as a new photosensitizer in PDT of head and neck cancer.

The flower pollination algorithm (FPA) is a novel optimization technique derived from the pollination behavior of flowers. However, the shortcomings of the FPA, such as a tendency towards premature convergence and poor exploitation ability, confine its application in engineering problems. To further strengthen FPA optimization performance, an orthogonal learning (OL) strategy based on orthogonal experiment design (OED) is embedded into the local pollination operator. OED can predict the optimal factor level combination by constructing a smaller but representative test set based on an orthogonal array. Using this characteristic of OED, the OL strategy can extract a promising solution from various sources of experience information, which leads the population to a potentially reasonable search direction. Moreover, the catfish effect mechanism is introduced to focus on the worst individuals during the iteration process. This mechanism explores new valuable information and maintains superior population diversity. The experimental results on benchmark functions show that our proposed algorithm significantly enhances the performance of the basic FPA and offers stronger competitiveness than several state-of-the-art algorithms.

Osteoporosis is the most common bone metabolic disease, characterized by bone mass loss and bone microstructure changes due to unbalanced bone conversion, which increases bone fragility and fracture risk. Glucocorticoids are clinically used to treat a variety of diseases, including inflammation, cancer and autoimmune diseases. However, excess glucocorticoids can cause osteoporosis. Herein we performed an integrated analysis of two glucocorticoid-related microarray datasets. The WGCNA analysis identified 3 and 4 glucocorticoid-related gene modules, respectively. Differential expression analysis revealed 1047 and 844 differentially expressed genes in the two datasets. After integrating differentially expressed glucocorticoid-related genes, we found that most of the robust differentially expressed genes were up-regulated. Through protein-protein interaction analysis, we obtained 158 glucocorticoid-related candidate genes. Enrichment analysis showed that these genes are significantly enriched in the osteoporosis related pathways. Our results provided new insights into glucocorticoid-induced osteoporosis and potential candidate markers of osteoporosis.

Accumulating evidence showed that Interleukin (IL) level is associated with Osteoporosis. Whereas, most of these associations are based on observational studies. Thus, their causality was still unclear. Mendelian randomization (MR) is a widely used statistical framework that uses genetic instrumental variables (IVs) to explore the causality of intermediate phenotype with disease. To classify their causality, we conducted a MR analysis to investigate the effect of IL-18 level on the risk of Osteoporosis. First, based on summarized genome-wide association study (GWAS) data, 8 independent IL-18 SNPs reaching genome-wide significance were deemed as IVs. Next, Simple median method was used to calculate the pooled odds ratio (OR) of these 8 SNPs for the assessment of IL-8 on the risk of Osteoporosis. Then, MR-Egger regression was utilized to detect potential bias due to the horizontal pleiotropy of these IVs. As a result of simple median method, we get the SE (−0.001; 95% CI−0.002 to 0; P = 0.042), which means low IL-18 level could increases the risk of the development of Osteoporosis. The low intercept (0; 95% CI −0.001 to 0; P = 0.59) shows there is no bias due to the horizontal pleiotropy of the IVs.

The repair of infective bone defects is a great challenge in clinical work. It is of vital importance to develop a kind of bone scaffold with good osteogenic properties and long-term antibacterial activity for local anti-infection and bone regeneration. A porous mineralized collagen (MC) scaffold containing poly(d,l-lactide-co-glycolic acid) (PLGA) microspheres loaded with two antibacterial synthetic peptides, Pac-525 or KSL-W was developed and characterized via scanning electron microscopy (SEM), porosity measurement, swelling and mechanical tests. The results showed that the MC scaffold embedded with smooth and compact PLGA microspheres had a positive effect on cell growth and also had antibacterial properties. Through toxicity analysis, cell morphology and proliferation analysis and alkaline phosphatase evaluation, the antibacterial scaffolds showed excellent biocompatibility and osteogenic activity. The antibacterial property evaluated with Staphylococcus aureus and Escherichia coli suggested that the sustained release of Pac-525 or KSL-W from the scaffolds could inhibit the bacterial growth aforementioned in the long term. Our results suggest that the antimicrobial peptides-loaded MC bone scaffold has good antibacterial and osteogenic activities, thus providing a great promise for the treatment of infective bone defects.

Background Heterotaxy (Htx) syndrome is an congenital disorders resulting from incorrectly establishment of left-right patterning during embryogenesis. Over 96% of patients with Htx exhibit some form of congenital heart disease (CHD),and has relatively poor survival. Multiple lines of evidence support genetic contributions to the etiology of Htx. As a specific genetic etiology is currently identifiable in only a minority of patients, there remains enormous potential for novel gene and pathway discovery. Purpose The aim of this study was to investigate the diagnostic yield of whole-exome sequencing (WES) and whole-genome sequencing (WGS) in fetuses with the pathogenesis of Htx, to explore candidate genes for Htx and to expand the clinical phenotype of known genetic conditions. Method WES and WGS were performed on specimens from 46 fetuses diagnosed with Htx and their parents. The single-nucleotide variants (SNVs) and copy-number variants (CNVs) were filtered and annotated by standard analysis process. All reported variants were classified according to he American College of Medical Genetics and Genomics guidelines. Results In the 46 fetuses, the detection rates of pathogenic and likely pathogenic variations were21.7% (10/46) and 10.9% (5/46) respectively. Ten pathogenic variations were identified on genes of CCDC114, DNAH11, ARMC4, STRA6, PQBP1 (hemizygote), HYDIN, RAI1 (Alagille Syndrome), ZFMP2 and Del(22q11.2) Syndrome. Five likely pathogenic variation were on DNAAF1 (Holshner syndrome), NF1, NEXN, NOTCH3 and FOXC1. Of 30 fetuses with prenatally diagnosed right atrial isomerism (RAI), the main intracardiac anomalies were atrioventricular canal (AV canal), isomerism of right atrial appendages, pulmonary stenosis or atresia (PS & PA) and right aortic arch. In 16 fetuses diagnosed left atrial isomerism (LAI) the main intracardiac anomalies were isomerism of left atrial appendages, interrupted IVC and azygos vein continuation. Of the 10 positive cases, 8 fetus were diagnosed of RAI and 2 were diagnosed of LAI by prenatal ultrasonic examination or fetal autopsy. The detection rate was 8/30 (26.7%) for RAI and 2/16 (12.5%) for LAI. Conclusion This study outlines the way for a substantial improvement in the diagnostic yield of prenatal genetic disorders in Htx through WES and WGS. Our experience also expanded the knowledge of the clinical phenotype of known genetic conditions. Our results indicate that the proportion of SNV in Htx of prenatal cases was significantly higher than that in patients with other congenital heart abnormalities, and the recessive inheritance occurred in a higher proportion in Htx. Our results have important implications for clinical management and genetic counseling of Htx. Acknowledgement/Funding Ministry of Science and Technology of the People's Republic of China

Background No data is available for the contribution of single gene disorders (SGDs) to left-sided congenital heart defects (LSCHDs) in the fetal population. Purpose The aim of this study was to explore the entire genetic architecture of LSCHDs, especially the contribution of SGDs in a cohort of fetal LSCHDs. Methods Low-pass whole genome sequencing (WGS) and whole exome sequencing (WES) were performed on specimens from 83 deceased fetuses with lSCHDs, including 48 HLHS, 22 CoA, 5 AS, 3 AAH, 2 AS+CoA and 1 case of AA, AS+MS, MA. Sequencing was predominantly performed in fetus-parent trios (n=63, 75.9%), or in fetus only (n=20, 24.1%). Results 34.9% (n=29) of the 83 fetal left-sided CHDs were identified with related genetic abnormalities. WGS analysis identified 14 (16.9%) with chromosomal abnormalities, including 6 (7.2%) aneuploidies and 8 (9.6%) pathogenic copy number variants (CNVs). WES analysis of the remaining 69 cases without chromosomal abnormalities identified 15 (15/69, 21.7%) with pathogenic/likely pathogenic variants. Of these 15 cases, KMT2D was the most frequently mutated gene (7/69, 10.1%), followed by NOTCH1 (4/69, 2.5%). Compound heterozygosity was identified in 3 genes (DNAH11, POFUT1, CRB2) that are not yet well established as CHD genes. Finally, we also observed a LOF variant in NONO (X-linked) that was maternally transmitted to an affected male case. The genetic results of this cohort Aneuploidies Trisomy 18 4 Turner syndrome 2 CNVs 11q terminal deletion 3 1p36 deletion 1 15q terminal deletion 1 7q11.23 deletion 1 4p terminal deletion 1 12q complex internal duplication 1 SGDs AD (KMT2D = 7; NOTCH1 = 4) 11 AR (DNAH11, POFUT1, CRB2) 3 X-recessive (NONO) 1 AD: autosomal dominant; AR: autosomal recessive. Conclusions Our experience supports that SGDs contribute a significant part to the pathogenesis of fetal CHDs, WES has the potential to provide molecular diagnoses in fetal left-sided CHDs without chromosomal abnormalities. KMT2D mutations accounted for a large fraction of left-sided CHDs in fetal population. If the KMT2D mutation is detected, further diagnosis of Kabuki syndrome should be considered.

Template matching is the process of accurately extracting the interesting regions in a source image according to reference templates. In this paper, the gravitational search algorithm (GSA) is employed as a novel search strategy for template matching. However, the basic GSA is easily trapped in a local optimum and has a poor exploitation ability. In this paper, to enhance the optimization performance of GSA, a novel cross-search strategy based on chaotic global search (CGS) and cloud local search (CLS) is incorporated into GSA. The new variant is named chaotic cloud GSA (CCGSA). CGS makes full use of the ergodicity of chaos theory to improve global search ability and to avoid premature convergence. Inspired by the randomness and stable tendency of the normal cloud model, CLS was formed to realize a refined exploitation in the neighborhood of the current best solution; therefore, it can enhance optimization efficiency. Comparative experiments on six composite benchmark functions indicate that CCGSA convergence performance is superior to that of two advanced variants of GSA. Moreover, when applied to template matching, CCGSA performs better than the other selected intelligent optimization algorithms.

This paper proposes a new decision tree approach for analog circuit fault diagnosis using binary support vector machines (BSVMs) that are trained by using different data sets. To evaluate the performance of those different BSVMs, a new criterion is defined by considering the weighted number of fault-pairs that can be separated by one BSVM. Specifically, the weight of each fault-pair is inversely proportional to the number of BSVMs that can separate it. Simulation results by using two example circuits demonstrate that the proposed approach achieves better performance in terms of accuracy and efficiency than existing approaches.

A novel modified binary bat algorithm (MBBA) with chaos and Doppler effect in echoes is presented in this paper to deal with the fault diagnosis problem of analog circuits with tolerance. The proposed method focuses on further mimicking the bats' behaviors and improving the binary bat algorithm (BBA) in view of biology. The proposed algorithm utilizes the bats' self-adaptive compensation for Doppler effect in echoes and the chaotic optimization method to improve the BBA. The elitist strategy is also used to store all the possible global best solutions, which will provide us with more possible choices in practice. Since single feature extraction method has limitations during fault diagnosis of analog circuits with tolerance, several kinds of feature extraction methods are used together to build a big feature set firstly in our method, and then, the new proposed MBBA is used to select the optimal feature subset simultaneously optimize the classifier parameters for the analog fault diagnosis. Three analog circuits' examples are given to demonstrate the effectiveness and generalization ability of our method, and other methods are also used to do comparisons. The results indicate that combining different kinds of feature extraction method together to optimally select the feature subset simultaneously optimize the classifier parameters by MBBA can obtain better performance in dealing with analog fault diagnosis problems, and our proposed method provides a better tradeoff between fault diagnosis accuracy and total cost, which is superior to other methods. Therefore, it is an effective method for analog fault diagnosis and has broad application prospects in practice.

Feature extraction plays an important role in the field of fault diagnosis of analog circuits. How to effectively extract fault features is crucial to diagnostic accuracy. The components tolerance and circuit nonlinearities of analog circuits can cause some part overlapping of primal signal among different component faults in time domain and frequency domain. Currently, the existing method aims at wavelet features, statistical property features, conventional frequency features and conventional time-domain features. There is no decoupling ability for the feature extraction methods mentioned above. To solve the problem, a new fault features extraction method is proposed. The diagnostic results are compared with those from other methods. Firstly, it is proposed to use the statistical property features of transformed signals by the fractional Fourier transform in the optimal fractional order domain as fault features, such as range, mean, standard deviation, skewness, kurtosis, entropy, median, the third central moment, and centroid. And then, KPCA is used to reduce the dimensionality of candidate features so as to obtain the optimal features. Next, normalization is applied to rescale input features. Finally, extracted features are trained by SVM to diagnose faulty components in analog circuits. The simulation results show that compared with traditional methods, the proposed method is quite efficient to improve diagnostic accuracy.

With the development of both hardware and software technologies in camera and computer, automated visual inspection system is being used more and more in intelligent transportation system for its high efficiency. For the safety operation, it is necessary to perform fault inspection for train mechanical components. As one of the most widely used small mechanical components in freight trains, bogie block key (BBK) is used to keep wheel sets from separating out of bogies, and its fault is likely to cause terrible accidents. This study proposes a vision-based system to inspect the missing of BBK automatically. To ensure accurate and rapid fault inspection, a hierarchical detection framework consisting of fault area extraction and object detection is proposed. The purpose of fault area extraction is to divide image regions which contain the inspected component from the complex background. Subsequently, a component detector based on the sparse histograms of oriented gradients and support vector machine is proposed to verify the candidate image regions to check whether the BBK is missing or not. The experiments show that the proposed system realises the status inspection of BBK with high accuracy and high speed and can meet the need of actual applications.

Tumor Necrosis Factor-alpha (TNF-α) was reported to increase autophagy in rheumatoid arthritis human fibroblast-like synovial cell (RA-HFLS). We investigated different levels of TNF-α exposed to RA-HFLS by focusing on the relationship of autophagy and apoptosis. RA-HFLS and normal human fibroblast-like synovial cell (HFLS) were stimulated by TNF-α in the presence or the absence of 3-methyladenine (3-MA) or chloroquine (CQ). Cell apoptosis was detected by flow cytometry. Autophagy was determined through the expression levels of LC3, Beclin1, and P62 measured by Western Blot analysis as well as Confocal Laser Scanning Microscopy. The basal autophagy level was significantly higher in RA-HFLS than in HFLS. Autophagy was enhanced both in RA-HFLS and HFLS when they were treated with TNF-α. With the treatment of TNF-α, a slightly higher autophagy level was found in RA-HFLS than in HFLS, without a dose dependent effect. When autophagy was inhibited by 3-MA or CQ, apoptosis increased in both groups. With the stimulation of different doses TNF-α, apoptosis was much higher in HFLS group than in RA-HFLS. Autophagy is a protection mechanism when treated by TNF-α in RA-HFLS.

With the development of hardware and software in camera and computing units, visual inspection system (VIS) plays an increasing significant role in fault inspection task. This paper proposes a VIS to inspect the missing of bogie block key (BBK) used on freight trains. BBK is an important component to keep wheel sets from separating out of bogies. The missing of BBK is one of the most common faults threatening the running safety. VIS first acquires a bogie image by the image acquisition system, and then a hierarchical inspection framework containing bearing cap (BC) detection, fault region localization, and BBK classification is proposed. Specifically, a cascaded detector trained by the AdaBoost approach combined with the gradient coded co-occurrence matrix (GCCM) features is used to achieve fast and accurate BC detection. Then, a fault region is located on the basis of the relationship between the BC and BBK. Finally, a BBK classifier based on the GCCM features and a support vector machine is used to process the fault region to identify the missing of BBK. The proposed system has been applied on a long sequence of real images showing high inspection speed and accuracy.

A set of novel methods are proposed to optimize analog test point selection in this paper. We have introduced chaos and elitist strategy into the binary bat algorithm so as to increase its global search mobility and effectiveness for robust global optimization. In the present study, nine well known chaotic maps are introduced and used to construct the chaotic binary bat algorithm (CBBA) respectively. As a result, we have developed nine different CBBAs and for the first time applied them to deal with the analog test point selection problem. The attractiveness of our proposed CBBA mainly lies in two aspects: the utilization of chaotic maps to tune the BBA parameter and the application of elitist strategy to store all the possible global best solutions. These improvements obviously enhance the performance of BBA and make our new algorithms (CBBAs) get all the best solutions (usually more than one) easily and effectively, which will give us more possible choices in practice. Analog circuits' examples and a group of statistical experiments are given to demonstrate the feasibility and effectiveness of the proposed algorithms. The other reported algorithms are also used to do the comparison. The results indicate that the proposed algorithms have excellent performance in finding the optimum test point sets. Therefore, they are good solutions and applicable to actual circuits and engineering practice.

Photodynamic therapy (PDT) is generally safer and less invasive than conventional strategies for head and neck cancer treatment. However, currently available photosensitizers have low selectivity for tumor cells, and the burden and side effects are so great that research is needed to develop safe photosensitizers. In this study, it was confirmed that the Buddleja officinalis (BO) extract, used in the treatment of inflammation and vascular diseases, shows fluorescence when activated by LED light, and, based on this, we aimed to develop a new photosensitive agent suitable for PDT. MTT, Diff-Quick® staining, and DCF-DA were performed to measure the effects of treating head and neck cancer cells with BO extract and 625 nm LED light (BO-PDT). Cell cycle, TUNEL, and western blot assays, as well as acridine orange staining, were performed to explore the mechanism of BO-PDT-induced cell death. We found that when the BO extract was irradiated with 625 nm LED light, it showed sufficient fluorescence and stronger intracellular toxicity and ROS effect than the currently commercially available hematoporphyrin. BO-PDT resulted in a decrease of mTOR activity that was correlated with an increase in the levels of ATG5, beclin-1, and LC3-II, which interfere with the formation of autophagosomes. In addition, BO-PDT induced the activation of PARP and led to an increase in the expression of proapoptotic protein Bax and a decrease in the expression of the antiapoptotic protein Bcl-2. Moreover, BO-PDT has been shown to induce the autophagy pathway 4 h after treatment, while apoptosis was induced 16 h after treatment. Finally, we confirmed that BO-PDT caused cell death of head and neck cancer cells via the intrinsic pathway. Therefore, we suggest that BO extract can be used as a new photosensitizer in PDT of head and neck cancer.

The demand for testability analysis has increased with the integration densities and complexity of circuits. As an important part of testability analysis, the test point selection method needs to be researched in depth. A new similarity coefficient criterion is proposed to determine the fault isolation degree because output responses of a circuit with component tolerance are approximately subject to the normal distribution. Then, a new test point selection method is proposed based on the fault-pair similarity coefficient criterion information table. Simulation experiments are used to validate the accuracy of the proposed method in terms of the optimum test point set and fault isolation degree. The results show that the proposed method improves the performance of test point selection by comparing with the other reported methods.

A new method to select an optimum test point set in analog fault diagnosis is proposed in this paper. As the probability density of the circuit output approximately satisfies the normal distribution, an accurate way for determining the fault ambiguity gap is used to calculate the isolation probability of the faults. The proposed fault-pair isolation table derived from the mean and standard deviation values of node voltage can exactly represent the fault-pair isolation capability of the test points. The special test points that can uniquely isolate some particular fault pairs are selected first. This step can help to save the total cost of the computation time and even find the final solution directly. After removing the isolated fault pairs (rows) and the selected test points (columns), the size of the fault-pair isolation table could reduce dramatically. If more optimum test points are needed, the normalized fault-pair isolation probability values in the table are used to select the right test point that has the largest fault-pair isolation capability among all the candidate test points. Analog circuits' examples and the statistical experiments are given to demonstrate the feasibility and effectiveness of the proposed algorithm. The other reported algorithms are also used to do the comparison. The results indicate that the proposed algorithm has excellent performance in minimizing the size of the test point set. Therefore, it is a good solution and applicable to actual circuits and engineering practice.

Fuzzy support vector machines (FSVMs) are known for their excellent antinoise performance, but there is no general rule when the fuzzy membership function (FMF) is set up. A novel FSVM based on hyperbolas optimized by the quantum-inspired gravitational search algorithm (QGSH-FSVM) is proposed to handle this question. In the proposed QGSH-FSVM, the FMF is defined by two disparate hyperbolas, whose eccentricities are optimized by the quantum-inspired gravitational search algorithm. A variable called diversity, revealing the percentage of a sample in different classes, is proposed to distinguish outliers or noises from valid samples. Experimental results confirm that the QGSH-FSVM is able to provide the best solutions to different situations by optimizing its eccentricities. The traditional support vector machine and the FSVM based on affinity or the distance between a sample and its cluster center, however, can only succeed in some particular problems while failing in others.

A new efficient method to select an optimum or near optimum set of test points for fault dictionary techniques in analog fault diagnosis is proposed. This is done by constructing a fault-isolated table firstly according to the integer-coded fault dictionary, and picking the special test points with particular fault isolate abilities out from the candidate test points set. This step can help us save the total cost of computation and even find the global minimum test-point set directly. After this step, the selected test points might isolate most of the defined faults together, and these isolated faults (rows) and the chosen test points (columns) are deleted from the fault dictionary, the dimension of which will reduce quite a lot. And then the inclusive and exclusive approach are combined together to choose other optimum test points from the candidate test points set to solve the problem. Three analog circuits' examples and the statistical experiments are given to demonstrate the feasibility and effectiveness of the proposed algorithm, the existing classical algorithms are also used to do the comparison. The results indicate that the proposed method has a better tradeoff between the solution accuracy and the computational cost, and it is superior to other methods in its computational efficiency and quality of final solution. Therefore, it is a good solution to minimize the size of the test-point set, and practical for medium and large scale systems.