Search

Aim. To explore the mechanism of resveratrol in reducing the soft tissue damage of osteoarthritis (OA) based on network pharmacology. Methods. Pharmmapper was used to predict the target of resveratrol, OMIM and Genecards were used to collect OA-related disease genes, and David ver 6.8 was used for enrichment analysis. Then, animal experiments were carried out for verification. The rat OA model was established and the rats were randomly divided into 4 groups: model group, resveratrol low-dose group, resveratrol high-dose group, and blank control group for follow-up experiments. Hematoxylin-eosin (HE) staining was used to detect the degree of pathological damage of rat bones and joints. Enzyme-linked immunosorbent assay (ELISA) was used for the content of inflammatory factors. Western blot was used to detect the expression of Toll-like receptor 4 (TLR4), Myeloid differentiation factor 88 (MyD88), nuclear factor kappa B protein (NF-κB), cysteine protease-9 (CASP-9), Bcl-2 protein, and Bax protein. Results. Through network pharmacological analysis, this study found that resveratrol may regulate the TLR4 signaling pathway, PI3K-Akt signaling pathway, FoxO signaling pathway, Osteoclast differentiation, Rheumatoid arthritis, etc. Animal experiments showed that compared with the model group, the pathological damage of bone and joint in the resveratrol low-dose and high-dose groups was significantly improved. Compared with the model group, the serum levels of IL-1beta, IL-6, IL-17, TNF-α, and MCP-1 in the resveratrol low-dose and high-dose groups were significantly reduced ( P P P P

Grain storage plays a vital part in social stability as well as people’s daily lives. By virtue of its unique storage advantages, wheat has become one of the most important grain reserves in the world. Wheat kernels continue consuming their own energy to maintain lives during the whole process of storage, which will lead to deterioration of their edible qualities as well as may be infected by certain mold provided that the surrounding conditions are suitable. Thus, establishing an efficient and accurate method to assess wheat kernel’s storage status is necessary for the sake of shaping a shelter to human beings as well as animals. For that reason, various wheat aging and wheat moldy detection methods have been summarized in this chapter. Up to now, study of aging and mold detection in wheat kernels can be divided into conventional chemical techniques and newly proposed physical detection methods. This review has analyzed in detail the limitations of conventional technologies, and then probes into some promising physical technologies for better detecting stored status of wheat kernels.

Background Inguinal lymphadenectomy (iLAD) is effective for penile carcinoma treatment, but usually results in many complications. This study aims to clinically evaluate the feasibility and clinical significance of a laparoscopic radical iLAD approach partly preserving great saphenous vein branches for penile carcinoma patients. Methods A total of 48 patients with penile cancer who underwent laparoscopic radical iLAD with retention of the great saphenous vein in Henan Cancer Hospital from 2012 Jan to 2020 Dec were included in this study. Sixteen penile carcinoma patients who underwent laparoscopic radical iLAD preserving parts of superficial branches of the great saphenous vein were identified as the sparing group, and the matched 32 patients who incised those branches were identified as control group. This new procedure was performed by laparoscopy, preserving parts of superficial branches of the great saphenous vein, superficial lateral and medial femoral veins. Clinicopathological features and perioperative variables were recorded. Postoperative complications, including skin flap necrosis, lymphorrhagia, and lower extremity edema were analyzed retrospectively. Results We found that the operative time of the sparing group is significantly longer than the control group (p = 0.011). There was no statistical difference in intraoperative blood loss, the lymph node number per side, average time to remove the drainage tube and postoperative hospital stay between the two groups. Compared to the control group, the sparing group showed a significantly decreased incidence of lower extremity edema (p = 0.018). The preservation of parts of superficial branches of the great saphenous vein was mainly decreased the incidence of edema below ankle (p = 0.034). Conclusions This study demonstrated that the iLAD with preserving parts of superficial branches of the great saphenous vein, with a decreased incidence of postoperative complications, is a safe and feasible approach for penile cancer.

Background: Bladder cancer (BLCA) ranks 10th in incidence among malignant tumors and 6th in incidence among malignant tumors in males. With the application of immune therapy, the overall survival (OS) rate of BLCA patients has greatly improved, but the 5-year survival rate of BLCA patients is still low. Furthermore, not every BLCA patient benefits from immunotherapy, and there are a limited number of biomarkers for predicting the immunotherapy response. Therefore, novel biomarkers for predicting the immunotherapy response and prognosis of BLCA are urgently needed.Methods: The RNA sequencing (RNA-seq) data, clinical data and gene annotation files for The Cancer Genome Atlas (TCGA) BLCA cohort were extracted from the University of California, Santa Cruz (UCSC) Xena Browser. The BLCA datasets GSE31684 and GSE32894 from the Gene Expression Omnibus (GEO) database were extracted for external validation. Immune-related genes were extracted from InnateDB. Significant differentially expressed genes (DEGs) were identified using the R package “limma,” and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for the DEGs were performed using R package “clusterProfiler.” Least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the signature model. The infiltration level of each immune cell type was estimated using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The performance of the model was evaluated with receiver operating characteristic (ROC) curves and calibration curves.Results: In total, 1,040 immune-related DEGs were identified, and eight signature genes were selected to construct a model using LASSO regression analysis. The risk score of BLCA patients based on the signature model was negatively correlated with OS and the immunotherapy response. The ROC curve for OS revealed that the model had good accuracy. The calibration curve showed good agreement between the predictions and actual observations.Conclusions: Herein, we constructed an immune-related eight-gene signature that could be a potential biomarker to predict the immunotherapy response and prognosis of BLCA patients.

Background: Bladder cancer (BLCA) is a common malignant tumor of the genitourinary system, and there is a lack of specific, reliable, and non-invasive tumor biomarker tests for diagnosis and prognosis evaluation. Homeobox genes play a vital role in BLCA tumorigenesis and development, but few studies have focused on the prognostic value of homeobox genes in BLCA. In this study, we aim to develop a prognostic signature associated with the homeobox gene family for BLCA.Methods: The RNA sequencing data, clinical data, and probe annotation files of BLCA patients were downloaded from the Gene Expression Omnibus database and the University of California, Santa Cruz (UCSC), Xena Browser. First, differentially expressed homeobox gene screening between tumor and normal samples was performed using the “limma” and robust rank aggregation (RRA) methods. The mutation data were obtained with the “TCGAmutation” package and visualized with the “maftools” package. Kaplan–Meier curves were plotted with the “survminer” package. Then, a signature was constructed by logistic regression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using “clusterProfiler.” Furthermore, the infiltration level of each immune cell type was estimated using the single-sample gene set enrichment analysis (ssGSEA) algorithm. Finally, the performance of the signature was evaluated by receiver-operating characteristic (ROC) curve and calibration curve analyses.Results: Six genes were selected to construct this prognostic model: TSHZ3, ZFHX4, ZEB2, MEIS1, ISL1, and HOXC4. We divided the BLCA cohort into high- and low-risk groups based on the median risk score calculated with the novel signature. The overall survival (OS) rate of the high-risk group was significantly lower than that of the low-risk group. The infiltration levels of almost all immune cells were significantly higher in the high-risk group than in the low-risk group. The average risk score for the group that responded to immunotherapy was significantly lower than that of the group that did not.Conclusion: We constructed a risk prediction signature with six homeobox genes, which showed good accuracy and consistency in predicting the patient’s prognosis and response to immunotherapy. Therefore, this signature can be a potential biomarker and treatment target for BLCA patients.

The prognosis of patients with advanced urothelial carcinoma is dismal. Platinum-based chemotherapy is still the main first-line treatment for advanced urothelial carcinoma, while immunotherapy can be used as a first-line treatment option for people who cannot tolerate platinum. Immunotherapy is preferred in the second-line treatment of bladder urothelial carcinoma. PD-1 inhibitors (Pembrolizumab, nivolumab and atezolizumab) and PD-L1 inhibitors (Ddurvalumab and avelumab) have not been approved for the treatment of advanced urothelial cancer in China. We describe a patient with advanced urothelial carcinoma experienced disease progression after gemcitabine chemotherapy. Following a treatment of domestic PD-1 inhibitor (sintilimab), the patient achieved a durable complete response with mild toxicity. This case indicates that PD-1 inhibitor sintilimab might be a second-line treatment choice for advanced urothelial carcinoma.

When exposed to high levels of noise, earmuffs are often used to avoid hearing loss. However, active noise control earmuffs may exhibit nonlinearities under excessive levels of noise, due to their low-power characteristics of the loudspeakers, and thus nonlinear control algorithms are required to improve the control performance. In this paper, an analytical model of a nonlinear active noise control earmuff is investigated. Based on this model, a robust state feedback control law is designed in the framework of linear matrix inequalities with respect to the parametric uncertainties of the loudspeaker and the limitation of control input. Then the backstepping approach is adopted to force the nonlinear part of the loudspeaker to track the derived state feedback signal and estimate the unknown parameters. Both recorded vehicle noise and multi-frequency noise are used to test the effectiveness of the proposed controller and the control performance is compared with that of a widely accepted nonlinear generalized functional link artificial neural network algorithm. Simulation results demonstrate that the proposed controller is capable of attenuating the interior noise and reducing harmonic and intermodulation distortions significantly.

The segmentation of brain tumors in magnetic resonance imaging (MRI) images plays an important role in early diagnosis, treatment planning and outcome evaluation. However, due to gliomas’ significant diversity in structure, the segmentation accuracy is low. In this paper, an automatic segmentation method integrating the small kernels two-path convolutional neural network (SK-TPCNN) and random forests (RF) is proposed, the feature extraction ability of SK-TPCNN and the joint optimization capability of model are presented respectively. The SK-TPCNN structure combining the small convolutional kernels and large convolutional kernels can enhance the nonlinear mapping ability and avoid over-fitting, the multiformity of features is also increased. The learned features from SK-TPCNN are then applied to the RF classifier to implement the joint optimization. RF classifier effectively integrates redundancy features and classify each MRI image voxel into normal brain tissues and different parts of tumor. The proposed algorithm is validated and evaluated in the Brain Tumor Segmentation Challenge (Brats) 2015 challenge Training dataset and the better performance is achieved.

Background Renal cell carcinoma (RCC) is a common malignant tumour of the genitourinary system. We aimed to analyse the potential value of metastasis-related biomarkers, circulating tumour cells (CTCs) and the proliferative marker Ki-67 in the diagnosis of RCC. Methods Data from 24 laparoscopic radical nephrectomies (RNs) and 17 laparoscopic partial nephrectomies (PNs) were collected in 2018. The numbers and positive rates of CTCs and circulating tumour microemboli (CTM) in the peripheral blood were obtained at three different time points: just before surgery, immediately after surgery and 1 week after surgery. Ki-67 protein expression was evaluated in the RCC tissue by immunohistochemistry. Results Except for the statistically significant association between the preoperative CTC counts and tumour size, no association between the number and positive rate of perioperative CTCs and clinicopathological features was found. The CTC counts gradually decreased during the perioperative period, and at 1 week after surgery, they were significantly lower than those before surgery. High Ki-67 expression was significantly positively correlated with preoperative CTC counts. In addition, Ki-67 expression was higher in the high CTC group (≥ 5 CTCs). Conclusion Our results suggest that surgical nephrectomy is associated with a decrease in CTC counts in RCC patients. CTCs can act as a potential biomarker for the diagnosis and prognosis of RCC. A careful and sufficient long-term follow-up is needed for patients with high preoperative CTC counts.

Background Brain tumor segmentation plays an important role in assisting diagnosis of disease, treatment plan planning, and surgical navigation. Objective This study aims to improve the accuracy of tumor boundary segmentation using the multi-scale U-Net network. Methods In this study, a novel U-Net with dilated convolution (DCU-Net) structure is proposed for brain tumor segmentation based on the classic U-Net structure. First, the MR brain tumor images are pre-processed to alleviate the class imbalance problem by reducing the input of the background pixels. Then, the multi-scale spatial pyramid pooling is used to replace the max pooling at the end of the down-sampling path. It can expand the feature receptive field while maintaining image resolution. Finally, a dilated convolution residual block is combined to improve the skip connections in the training networks to improve the network's ability to recognize the tumor details. Results The proposed model has been evaluated using the Brain Tumor Segmentation (BRATS) 2018 Challenge training dataset and achieved the dice similarity coefficients (DSC) score of 0.91, 0.78 and 0.83 for whole tumor, core tumor and enhancing tumor segmentation, respectively. Conclusions The experiment results indicate that the proposed model yields a promising performance in automated brain tumor segmentation.

Background: Regarding the outbreak of highly contagious the 2019 Novel Coronavirus (2019-nCoV) in various countries and regions, data have been needed on the early chest CT images and clinical characteristics of the affected patients. Objectives: To explore the early clinical and computed tomography (CT) characteristics of the 2019 Novel Coronavirus Disease (COVID-19) patients to improve the diagnostic level of this contagious respiratory disease. Methods: An analysis retrospectively was implemented on the radiological features and clinical characteristics of 12 patients with COVID-19 who had undergone chest CT scanning in the designated hospital from Jan 23, 2020, to Feb 18, 2020. The clinical data on general information, epidemiological, cardinal symptoms, blood test, and CT imaging characteristics were obtained. Results: According to the relevant diagnostic criteria, the patients were divided into two groups: mild (2 cases), and ordinary type (10 cases). The main symptoms of 2019-nCoV pneumonia were fever (9/12) and cough (8/12) with or without respiratory and other systemic symptoms. The blood test of the patients showed that most of the white blood cell count was normal (10/12), decreased lymphocyte count (6/12), and increased hypersensitive C reactive protein (hs-CRP) (5/12). In the early stage of COVID-19, the chest CT images showed patchy mixed ground-glass opacity (GGO) (8/12), mainly distributed in the periphery and posterior part of both lungs. The internal density of image lesion area was uneven, and lesions primarily manifested as “crazy-paving pattern” (8/12), with grid-like, interlobular septal thickening, thickened bronchovascular bundle and air bronchus sign and multiple fibrosis. A few cases showed pulmonary atelectasis (1/12), bilateral pleural effusion (1/12), no mediastinal or bilateral hilar lymph node enlargement. Conclusions: The clinical characteristics of 2019-nCoV pneumonia are similar to those of common viral pneumonia. The chest CT images may be helpful for the early detection of novel coronavirus pneumonia.

BACKGROUNDAccurate segmentation of brain tumor depicting on magnetic resonance imaging (MRI) is an important step for doctors to determine optimal treatment plan of Gliomas, which are the common malignant brain tumors that seriously damage patients' health and life.OBJECTThis study aims to improve accuracy and efficiency of brain tumor segmentation on MRI using the advanced deep learning model.METHODIn this study, an improved model based on the U-net for accurate segmentation of brain tumor MRI images, called Deeper ResU-net, is proposed. First, a deep Deeper U-net is built, which has deeper network depth compared with U-net, uses Squeeze Operator to control network parameters and attempts to enhance the feature extraction ability. Then, Deeper ResU-net is formed to eliminate degradation phenomenon of the deep network, in which residual unit is designed and integrated into the Deeper U-net to keep the number of parameters unchanged.RESULTDeeper ResU-net makes the deep network conduct stable training without degrading. Evaluation result shows that the Deeper ResU-net has achieved competitive result with average DSC metrics of 0.9, 0.82, 0.88 for Complete tumor region, Core tumor region and Enhanced tumor region, respectively.CONCLUSIONBy extending the U-net model to a deeper layer and adding the residual structure to ensure effective and stable training of the model, the experiment results demonstrate that applying the improved Deeper ResU-net can effectively eliminate the degradation phenomenon of deep network and improve segmentation performance.

Brain tumor images segmentation plays a crucial role in the auxiliary diagnosis of disease, treatment planning and surgical navigation. In order to accurately segment brain tumor images, this paper proposes an automatic brain tumor Magnetic Resonance Imaging (MRI) image segmentation algorithm based on the U-net model. Firstly, based on samples preprocessing, loss function and optimization algorithm, a U-net baseline model with optimal parameters structure which is suitable for segmentation task is constructed. Secondly, a feature recombination layer, i.e. a 1×1 convolutional layer, is added to the baseline model to linearly recombine the upper layer features, enrich extracted features, reduce network parameters, and improve the segmentation results. The algorithm is validated and evaluated on the Brain Tumor Segmentation Challenge (Brats) 2015 challenge training dataset. The experimental results show that the proposed algorithm has strong competitiveness compared with the existing brain tumor MRI image segmentation algorithm.

Background Advanced pancreatic cancer (PC) has very poor prognosis with present treatments, thus necessitating continued efforts to find improved therapeutic approaches. Both preclinical and preliminary clinical data indicate that cytokine-induced killer (CIK) cells are an effective tool against various types of solid tumors. Here, we conducted a study to determine whether CIK cell-based therapy (CBT) can improve the outcomes of advanced PC. Methods Eighty-two patients with advanced PC, whose predicted survival time was longer than 3 months, were analyzed retrospectively. Of all the patients, 57 individuals were receiving chemotherapy, while the remaining 25 individuals were treated with CBT. Results The overall survival analysis was based on 48 deaths in the 57 patients in the chemotherapy group (84.2 %) and 18 deaths in the 25 patients in the CBT group (72.0 %). In the CBT group, the median overall survival time was 13.5 months, as compared to 6.6 months in the chemotherapy group (hazard ratio for death, 0.39; 95 % confidence interval, 0.23 to 0.65; p

Background Elongation factor for RNA polymerase 2 (ELL2) and ELL associated factor 2 (EAF2) have been reported to have tumor suppressive properties in prostate epithelial cells. Aims We investigated ELL2 expression in human prostate cancer specimens, and ELL2 protein stability and ubiquitination in prostate cancer cells. Materials and methods Immunostaining analysis of human prostate cancer specimens was used to determine ELL2 expression in tumor and normal tissues. ELL2 knockdown in prostate cancer cell lines LNCaP and C4-2 was used to compare proliferation and motility. Deletion and site-directed mutagenesis was used to identify amino acid residues in ELL2 that were important for degradation. Results ELL2 protein was downregulated in prostate cancer specimens and was up-regulated by androgens in prostate cancer cell lines LNCaP and C4-2. ELL2 knockdown enhanced prostate cancer cell proliferation and motility. ELL2 protein has a short half-life and was stabilized by proteasome inhibitor MG132. Amino acid residues K584 and K599 in ELL2 were important for ELL2 degradation. EAF2 could stabilize ELL2 and inhibited its polyubiquitination. Conclusion Our findings provide further evidence that ELL2 is a potential tumor suppressor frequently down-regulated in clinical prostate cancer specimens and provides new insights into regulation of ELL2 protein level by polyubiquitination and EAF2 binding.

In this paper, the free and forced in-plane vibration analysis of rectangular plates are performed for the first time using an improved Fourier series method, in which the boundary restraining spring stiffness can vary in any functional pattern along each edge. Two-dimensional improved Fourier series displacement forms are constructed with four supplementary polynomials introduced into the standard 2-D Fourier series to make the field functions sufficiently smooth in the whole solving domain. Energy formulations are employed to describe the in-plane dynamics of plate system, in which the in-plane concentrated point force is taken into account in the form of work term. All the unknown Fourier series coefficients are then solved through the Rayleigh-Ritz procedure. Several numerical examples are given to demonstrate the correctness and effectiveness of the proposed model through the comparison with those calculated via finite element analysis (FEA). The results show that these two results can agree very well with each other for various non-uniform boundary conditions. Based on the established model, the in-plane vibration response is also studied. Some curves and contours are obtained to illustrate how the boundary restraining stiffnesses affect the in-plane point and transfer mobility of rectangular plate structure.

Elongation factor, RNA polymerase II, 2 (ELL2) is an RNA Pol II elongation factor with functional properties similar to ELL that can interact with the prostate tumor suppressor EAF2. In the prostate, ELL2 is an androgen response gene that is upregulated in benign prostatic hyperplasia (BPH). We recently showed that ELL2 loss could enhance prostate cancer cell proliferation and migration, and that ELL2 gene expression was downregulated in high Gleason score prostate cancer specimens. Here, prostate-specific deletion of ELL2 in a mouse model revealed a potential role for ELL2 as a prostate tumor suppressor in vivo. Ell2-knockout mice exhibited prostatic defects including increased epithelial proliferation, vascularity and PIN lesions similar to the previously determined prostate phenotype in Eaf2-knockout mice. Microarray analysis of prostates from Ell2-knockout and wild-type mice on a C57BL/6J background at age 3 months and qPCR validation at 17 months of age revealed a number of differentially expressed genes associated with proliferation, cellular motility and epithelial and neural differentiation. OncoPrint analysis identified combined downregulation or deletion in prostate adenocarcinoma cases from the Cancer Genome Atlas (TCGA) data portal. These results suggest that ELL2 and its pathway genes likely play an important role in the development and progression of prostate cancer.

BackgroundRheumatoid arthritis (RA) is a chronic auto-inflammatory disorder of joints. The present study aimed to identify the key genes in RA for better understanding the underlying mechanisms of RA.MethodsThe integrated analysis of expression profiling was conducted to identify differentially expressed genes (DEGs) in RA. Moreover, functional annotation, protein–protein interaction (PPI) network and transcription factor (TF) regulatory network construction were applied for exploring the potential biological roles of DEGs in RA. In addition, the expression level of identified candidate DEGs was preliminarily detected in peripheral blood cells of RA patients in theGSE17755dataset. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to validate the expression levels of identified DEGs in RA.ResultsA total of 378 DEGs, including 202 up- and 176 down-regulated genes, were identified in synovial tissues of RA patients compared with healthy controls. DEGs were significantly enriched in axon guidance, RNA transport and MAPK signaling pathway. RBFOX2, LCK and SERBP1 were the hub proteins in the PPI network. In the TF-target gene network, RBFOX2, POU6F1, WIPF1 and PFKFB3 had the high connectivity with TFs. The expression status of 11 candidate DEGs was detected inGSE17755, the expression levels of MAT2A and NSA2 were significantly down-regulated and CD47 had the up-regulated tendency in peripheral blood cells of patients with RA compared with healthy individuals. qRT-PCR results of MAT2A, NSA2, CD47 were compatible with our bioinformatics analyses.DiscussionOur study might provide valuable information for exploring the pathogenesis mechanism of RA and identifying the potential biomarkers for RA diagnosis.

Aim: To investigate the correlation between the related variables of prostate-specific antigen (PSA) and risk factors in patients with prostate carcinoma. Methods: The clinical records of 187 cases with prostate carcinoma, diagnosed by biopsy, were retrospectively analyzed to assess the correlation of PSA density (PSAD), free PSA (FPSA), and FPSA/total PSA (TPSA) with risk factors in prostate carcinoma. Results: The results from "Spearman rank correlation analysis" and "rank sum test" revealed that TPSA and FPSA were positively correlated with risk factors for prostate cancer patients, whereas there was no correlation between F/TPSA and risk factors. Conclusion: PSAD, FPSA, and the related variables of PSA may serve as valuable tools to guide the treatment of prostate cancer.

This paper investigates the most desirable configuration of a two-stage nonlinear vibration isolation system, in which the isolators contain hardening geometric stiffness nonlinearity and linear viscous damping. The force transmissibility of the system is used as the measure of the effectiveness of the isolation system. The hardening nonlinearity is achieved by placing horizontal springs onto the suspended and intermediate masses, which are supported by vertical springs. It is found that nonlinearity in the upper stage has very little effect and thus serves little purpose. The nonlinearity in the lower stage, however, has a profound effect, and can significantly improve the effectiveness of the isolation system. Further, it is found that it is desirable to have high damping in the upper stage and very low damping in the lower stage.

Background Pulmonary fibrosis (PF) is a destructive pulmonary disease and the molecular mechanisms underlying PF are unclear. This study investigated differentially expressed proteins associated with the occurrence and development of PF in rat lung tissue with bleomycin-induced PF. Methods Sixteen Sprague-Dawley rats were randomly divided into 2 groups: the PF model group ( n = 8) and the control group ( n = 8). After successfully establishing the rat PF model induced by bleomycin, the differentially expressed proteins in the 2 groups were identified through isobaric tag for relative and absolute quantitation coupled with liquid chromatography-mass spectrometry and bioinformatics analysis. Results A total of 146 differentially expressed proteins were identified; 88 of which displayed increased abundance and 58 were downregulated in the PF rat model group. Most functional proteins were associated with extracellular matrix, inflammation, damage response, vitamin A synthesis and metabolism. Critical proteins related to PF development and progression was identified, such as type V collagen-3, arachidonic acid 12-lipoxygenase, arachidonic acid 15-lipoxygenase and cytochrome P4501A1. Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that these differentially expressed proteins were enriched in extracellular matrix receptor interaction pathway, renin-angiotensin system and metabolic pathway of retinol. Conclusions The proteins expressed in bleomycin-induced PF rat model provide important data for further functional analysis of proteins involved in PF.

Automated detection of blood vessel structures is becoming a crucial interest for better management of vascular disease. In this paper, we propose an algorithm for vessel segmentation in digital retinal images based on integral channel features and random forests. In the first stage, preprocessing is performed to obtain the candidate pixels of vessels, then a host of simple features are extracted for each candidate pixels based on integral channels. Furthermore random forests is used to classify the candidate pixels as vessels or not. Finally, postprocessing is applied to fill pixel gaps in classified blood vessels. The proposed algorithm achieves an average accuracy of 0.9614, 0.9588, sensitivity of 0.7191, 0.6996 and specificity of 0.9849, 0.9787 on two public databases DRIVE and STARE respectively.

This paper presents an analytical study on the influence of edge restraining stiffness on the transverse vibrations of rectangular plate structure. An improved Fourier series method was employed to analyze the transverse vibration of plate structure with general elastically restrained boundary conditions. A linear combination of a double Fourier series and eight auxiliary terms was sought as the admissible function of the flexural displacement of the plate, each term being a combination of a polynomial function and a single cosine series expansion. The auxiliary terms were introduced to ensure and improve the smoothness of the original displacement function and its derivatives at the boundaries. Several numerical examples were given to demonstrate the validity and accuracy of the current solution. The influences of translational and rotational stiffness on the natural frequencies and mode shapes of plate were analyzed by numerical results. The results show that the translational stiffness has bigger influence on the natural frequencies than the rotational stiffness. It is generally well known that little change of the rotational stiffness has little influence on the mode shapes of plate. However, the current work shows that a very little change of rotational stiffness value may lead to a large change of the mode shapes of a square plate structure.

Human epidermal growth factor receptor 2 (HER2) has become a well-established target for the treatment of HER2-positive lung cancer. However, a frequently observed in-frame mutation that inserts amino acid quadruplex Tyr776-Val777-Met778-Ala779 at G776 (G776(YVMA)) in HER2 kinase domain can cause drug resistance and sensitivity, largely limiting the application of reversible tyrosine kinase inhibitors in lung cancer therapy. A systematic investigation of the intermolecular interactions between the HER2(YVMA) mutant and clinical small-molecule inhibitors would help to establish a complete picture of drug response to HER2 G776(YVMA) insertion in lung cancer, and to design new tyrosine kinase inhibitors with high potency and selectivity to target the lung cancer-related HER2(YVMA) mutant. Here, we combined homology modeling, ligand grafting, structure minimization, molecular simulation and binding affinity analysis to profile a number of tyrosine kinase inhibitors against the G776(YVMA) insertion in HER2. It is found that the insertion is far away from HER2 active pocket and thus cannot contact inhibitor ligand directly. However, the insertion is expected to induce marked allosteric effect on some regions around the pocket, including A-loop and hinges connecting between the N- and C-lobes of HER2 kinase domain, which may exert indirect influence to inhibitor binding. Most investigated inhibitors exhibit weak binding strength to both wild-type and mutant HER2, which can be attributed to steric hindrance that impairs ligand compatibility with HER2 active pocket. However, the cognate inhibitor lapatinib and the non-cognate inhibitor bosutinib were predicted to have low affinity for wild-type HER2 but high affinity for HER2(YVMA) mutant, which was confirmed by subsequent kinase assay experiments; the inhibitory potencies of bosutinib against wild-type and mutant HER2 were determined to be IC(50) > 1000 and =27 nM, respectively, suggesting that the bosutinib might be exploited as a selective inhibitor for mutant over wild-type HER2. Structural examination revealed that formation of additional non-bonded interactions such as hydrogen bonds and hydrophobic contacts with HER2 A-loop region due to G776(YVMA) insertion is the primary factor to improve bosutinib affinity upon the mutation.

Objective. Osteoarthritis (OA) is a complex arthritic condition in which the genetic factor plays a major role. One of the candidate genes of is the ADAM12 gene, but no consistency has been reached till now. This study aims to investigate the potential role of four single nucleotide polymorphisms (SNPs) of the ADAM12 gene in susceptibility to knee OA and its progression in Chinese Han population.Methods. The rs1278279, rs3740199, rs1044122, and rs1871054 polymorphisms were genotyped and compared in a population based cohort consisting of 164 OA subjects and 200 age- and gender-matched controls.Results. The SNP rs1871054 was found with increased risk of OA susceptibility in comparing the genotype frequencies between the case and control groups no matter for which model of comparison (allele level, dominant model, recessive model, and extreme genotype model). Additionally, the SNP rs1871054 was found associated with increased OA severity according to the K/L grade.Conclusion. In summary, we have identified that the rs1871054 variant within the ADAM12 gene is a risk factor for increased osteoarthritis susceptibility and severity.

Made available in DSpace on 2018-12-11T16:56:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-01-01 Motivated by the need for improving the isolation performance, many research studies have been performed on isolators with nonlinear characteristics. Based on the shape of their phase portrait, such devices can be configured as either a mono- or bi-stable isolator. This paper focuses on investigating the relative performance of these two classes under the same excitations. Force transmissibility is used to measure the isolation performance, which is defined in terms of the RMS of the ratio of the transmitted force to the excitation force. When the system is subjected to harmonic excitation, it is found that the maximum reduction of the force transmissibility in the isolation range using Quasi-Zero stiffness is achieved. When the system is subjected to random excitation, it has the same effect of Quasi-Zero stiffness. Further, optimum damping can be changed with stiffness and has minimum value. © 2014 Harbin Engineering University and Springer-Verlag Berlin Heidelberg. College of Power and Energy Engineering, Harbin Engineering University, Harbin, 150001 Departamento de Engenharia Mecânica, UNESP, Ilha Solteira, 03001-000 Departamento de Engenharia Mecânica, UNESP, Ilha Solteira, 03001-000

BTG3 is identified as a tumor suppressor gene in some malignancies. Btg3-deficient mice display a higher incidence of lung cancer. These results suggest that BTG3 plays an important role in lung tumorigenesis, although the underlying mechanisms are unknown. The BTG3 expression was detected using immunohistochemical staining and our results showed that the expression of BTG3 was reduced in lung cancer compared to benign lung tissues. We identified two BTG3 isoforms present in lung cancer: Full-length BTG3 and BTG3b lacking the 44 amino acids. BTG3 was predominantly expressed in benign lung tissues, whereas its expression was generally undetectable in lung cancer and cancer cell lines. Functional analysis revealed that BTG3 but not BTG3b inhibited lung cancer growth. Our results disclosed an important role of BTG3 in lung tumorigenesis.

An analytical method is derived for the vibration analysis of doubly curved shallow shells with arbitrary elastic supports alone its edges, a class of problems which are rarely attempted in the literature. Under this framework, all the classical homogeneous boundary conditions for both in-plane and out-of-plane displacements can be universally treated as the special cases when the stiffness for each of restraining springs is equal to either zero or infinity. Regardless of the boundary conditions, the displacement functions are invariably expanded as an improved trigonometric series which converges uniformly and polynomially over the entire solution domain. All the unknown expansion coefficients are treated as the generalized coordinates and solved using the Rayleigh–Ritz technique. Unlike most of the existing solution techniques, the current method offers a unified solution to a wide spectrum of shell problems involving, such as different boundary conditions, varying material and geometric properties with no need of modifying or adapting the solution schemes and implementing procedures. A numerical example is presented to demonstrate the accuracy and reliability of the current method.

Accurate lung CT image segmentation is of great clinical value, especially when it comes to delineate pathological regions including lung tumor. In this paper, we present a novel framework that jointly segments multiple lung computed tomography (CT) images via hierarchical Dirichlet process (HDP). In specifics, based on the assumption that lung CT images from different patients share similar image structure (organ sets and relative positioning), we derive a mathematical model to segment them simultaneously so that shared information across patients could be utilized to regularize each individual segmentation. Moreover, compared to many conventional models, the algorithm requires little manual involvement due to the nonparametric nature of Dirichlet process (DP). We validated proposed model upon clinical data consisting of healthy and abnormal (lung cancer) patients. We demonstrate that, because of the joint segmentation fashion, more accurate and consistent segmentations could be obtained.