Biomedical image segmentation algorithm based on dense atrous convolution.

Biomedical images have complex tissue structures, and there are great differences between images of the same part of different individuals. Although deep learning methods have made some progress in automatic segmentation of biomedical images, the segmentation accuracy is relatively low for biomedical images with significant changes in segmentation targets, and there are also problems of missegmentation and missed segmentation. To address these challenges, we proposed a biomedical image segmentation method based on dense atrous convolution. First, we added a dense atrous convolution module (DAC) between the encoding and decoding paths of the U-Net network. This module was based on the inception structure and atrous convolution design, which can effectively capture multi-scale features of images. Second, we introduced a dense residual pooling module to detect multi-scale features in images by connecting residual pooling blocks of different sizes. Finally, in the decoding part of the network, we adopted an attention mechanism to suppress background interference by enhancing the weight of the target area. These modules work together to improve the accuracy and robustness of biomedical image segmentation. The experimental results showed that compared to mainstream segmentation networks, our segmentation model exhibited stronger segmentation ability when processing biomedical images with multiple-shaped targets. At the same time, this model can significantly reduce the phenomenon of missed segmentation and missegmentation, improve segmentation accuracy, and make the segmentation results closer to the real situation.

A global optimization generation method of stitching dental panorama with anti-perspective transformation.

To address the limitation of narrow field-of-view in local oral cavity images that fail to capture large-area targets at once, this paper designs a method for generating natural dental panoramas based on oral endoscopic imaging that consists of two main stages: the anti-perspective transformation feature extraction and the coarse-to-fine global optimization matching. In the first stage, we increase the number of matched pairs and improve the robustness of the algorithm to viewpoint transformation by normalizing the anti-affine transformation region extracted from the Gaussian scale space and using log-polar coordinates to compute the gradient histogram of the octagonal region to obtain the set of perspective transformation resistant feature points. In the second stage, we design a coarse-to-fine global optimization matching strategy. Initially, we incorporate motion smoothing constraints and improve the Fast Library for Approximate Nearest Neighbors (FLANN) algorithm by utilizing neighborhood information for coarse matching. Then, we eliminate mismatches via homography-guided Random Sample Consensus (RANSAC) and further refine the matching using the Levenberg-Marquardt (L-M) algorithm to reduce cumulative errors and achieve global optimization. Finally, multi-band blending is used to eliminate the ghosting due to unalignment and make the image transition more natural. Experiments show that the visual effect of dental panoramas generated by the proposed method is significantly better than that of other methods, addressing the problems of sparse splicing discontinuities caused by sparse keypoints, ghosting due to parallax, and distortion caused by the accumulation of errors in multi-image splicing in oral endoscopic image stitching.

Intelligent crowd sensing pickpocketing group identification using remote sensing data for secure smart cities.

As a public infrastructure service, remote sensing data provided by smart cities will go deep into the safety field and realize the comprehensive improvement of urban management and services. However, it is challenging to detect criminal individuals with abnormal features from massive sensing data and identify groups composed of criminal individuals with similar behavioral characteristics. To address this issue, we study two research aspects: pickpocketing individual detection and pickpocketing group identification. First, we propose an IForest-FD pickpocketing individual detection algorithm. The IForest algorithm filters the abnormal individuals of each feature extracted from ticketing and geographic information data. Through the filtered results, the factorization machines (FM) and deep neural network (DNN) (FD) algorithm learns the combination relationship between low-order and high-order features to improve the accuracy of identifying pickpockets composed of factorization machines and deep neural networks. Second, we propose a community relationship strength (CRS)-Louvain pickpocketing group identification algorithm. Based on crowdsensing, we measure the similarity of temporal, spatial, social and identity features among pickpocketing individuals. We then use the weighted combination similarity as an edge weight to construct the pickpocketing association graph. Furthermore, the CRS-Louvain algorithm improves the modularity of the Louvain algorithm to overcome the limitation that small-scale communities cannot be identified. The experimental results indicate that the IForest-FD algorithm has better detection results in Precision, Recall and F1score than similar algorithms. In addition, the normalized mutual information results of the group division effect obtained by the CRS-Louvain pickpocketing group identification algorithm are better than those of other representative methods.

Research on user recruitment algorithms based on user trajectory prediction with sparse mobile crowd sensing.

Sparse mobile crowd sensing saves perception cost by recruiting a small number of users to perceive data from a small number of sub-regions, and then inferring data from the remaining sub-regions. The data collected by different people on their respective trajectories have different values, and we can select participants who can collect high-value data based on their trajectory predictions. In this paper, we study two aspects of user trajectory prediction and user recruitment. First, we propose an STGCN-GRU user trajectory prediction algorithm, which uses the STGCN algorithm to extract features related to temporal and spatial information from the trajectory map, and then inputs the feature sequences into GRU for trajectory prediction, and this algorithm improves the accuracy of user trajectory prediction. Second, an ADQN (action DQN) user recruitment algorithm is proposed.The ADQN algorithm improves the objective function in DQN on the idea of reinforcement learning. The action with the maximum input value is found from the Q network, and then the output value of the objective function of the corresponding action Q network is found. This reduces the overestimation problem that occurs in Q networks and improves the accuracy of user recruitment. The experimental results show that the evaluation metrics FDE and ADE of the STGCN-GRU algorithm proposed in this paper are better than other representative algorithms. And the experiments on two real datasets verify the effectiveness of the ADQN user selection algorithm, which can effectively improve the accuracy of data inference under budget constraints.

Research on rainy day traffic sign recognition algorithm based on PMRNet.

The recognition of traffic signs is of great significance to intelligent driving and traffic systems. Most current traffic sign recognition algorithms do not consider the impact of rainy weather. The rain marks will obscure the recognition target in the image, which will lead to the performance degradation of the algorithm, a problem that has yet to be solved. In order to improve the accuracy of traffic sign recognition in rainy weather, we propose a rainy traffic sign recognition algorithm. The algorithm in this paper includes two modules. First, we propose an image deraining algorithm based on the Progressive multi-scale residual network (PMRNet), which uses a multi-scale residual structure to extract features of different scales, so as to improve the utilization rate of the algorithm for information, combined with the Convolutional long-short term memory (ConvLSTM) network to enhance the algorithm's ability to extract rain mark features. Second, we use the CoT-YOLOv5 algorithm to recognize traffic signs on the recovered images. In this paper, in order to improve the performance of YOLOv5 (You-Only-Look-Once, YOLO), the 3 × 3 convolution in the feature extraction module is replaced by the Contextual Transformer (CoT) module to make up for the lack of global modeling capability of Convolutional Neural Network (CNN), thus improving the recognition accuracy. The experimental results show that the deraining algorithm based on PMRNet can effectively remove rain marks, and the evaluation indicators Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) are better than the other representative algorithms. The mean Average Precision (mAP) of the CoT-YOLOv5 algorithm on the TT100k datasets reaches 92.1%, which is 5% higher than the original YOLOv5.

An improved pix2pix model based on Gabor filter for robust color image rendering.

In recent years, with the development of deep learning, image color rendering method has become a research hotspot once again. To overcome the detail problems of color overstepping and boundary blurring in the robust image color rendering method, as well as the problems of unstable training based on generative adversarial networks, we propose an color rendering method using Gabor filter based improved pix2pix for robust image. Firstly, the multi-direction/multi-scale selection characteristic of Gabor filter is used to preprocess the image to be rendered, which can retain the detailed features of the image while preprocessing to avoid the loss of features. Moreover, among the Gabor texture feature maps with 6 scales and 4 directions, the texture map with the scale of 7 and the direction of 0° has the comparable rendering performance. Finally, by improving the loss function of pix2pix model and adding the penalty term, not only the training can be stabilized, but also the ideal color image can be obtained. To reflect image color rendering quality of different models more objectively, PSNR and SSIM indexes are adopted to evaluate the rendered images. The experimental results of the proposed method show that the robust image rendered by this method has better visual performance and reduces the influence of light and noise on the image to a certain extent.

[Detection and clinical significance of Notch1 methylation in breast cancer and intraductal proliferative breast lesions].

OBJECTIVE: To explore the relevance between the promoter methylation status of Notch1 gene and the invasive ductal carcinoma and ductal hyperplastic lesions of the breast. METHODS: Methylation status of Notch1 gene in human breast invasive ductal carcinoma (IDC, n = 89), ductal carcinoma in situ (DCIS, n = 20), atypical ductal hyperplasia (ADH, n = 11) and usual ductal hyperplasia (UDH, n = 20) were quantitatively evaluated by MALDI-TOF MS. The expression of Notch1 protein was detected by immunohistochemical stain (SP method). RESULTS: Positive expression rates of Notch1 protein in IDC and DCIS were 91.0% (81/89) and 75.0% (15/20), respectively, which were significantly higher than those of ADH (4/11) and UDH (30.0%, 6/20;P < 0.05). Notch1 protein expression was correlated significantly with lymph node metastasis, pathological grades and TNM stages of IDC. The mean methylation levels of Notch1 gene at CpG_3, CpG_4.5 and CpG_8 significantly decreased in IDC group compared with those of DCIS, ADH and UDH groups (P < 0.0083). In breast carcinomas, the mean methylation rates of Notch1 gene at CpG_4.5, CpG_10.11, and CpG_14.15.16 loci in cases with axillary node metastasis were significantly lower than those without axillary node metastasis (P < 0.05); and the methylation rates at CpG_14.15.16 and CpG_18 loci in stage Iwere lower than that in stage II, further lower than that in stage III (P < 0.05); and that in CpG_1.2, CpG_12.13 loci in grade I (highly-differentiated group) were higher than that in grade II (moderate-differentiated group) and grade III (poorly-differentiated group) (P < 0.05); and the methylation rates at CpG_3, CpG_8 and CpG_14.15.16 loci in ER(+) PR(+) HER2(-) group were lower than that in ER(-) PR(-) HER2(+) group (P < 0.05). CONCLUSIONS: There is an overall hypomethylation of Notch1 gene in breast invasive ductal carcinomas with corresponding over-expression of Notch1 protein. This inverse correlation show that the alteration of protein expression result from hypomethylation oncogene Notch1, and this change may have important significance in breast tumorigenesis and the development. Specific hypomethylation at CpG_3, CpG_ 4.5 and CpG_8 loci of Notch1 gene may play a role in the pathogenesis of breast carcinoma, suggesting the progression and/or malignant transformation from benign glandular lesions of the breast.

Neural Network-Based Mapping Mining of Image Style Transfer in Big Data Systems.

Image style transfer can realize the mutual transfer between different styles of images and is an essential application for big data systems. The use of neural network-based image data mining technology can effectively mine the useful information in the image and improve the utilization rate of information. However, when using the deep learning method to transform the image style, the content information is often lost. To address this problem, this paper introduces L1 loss on the basis of the VGG-19 network to reduce the difference between image style and content and adds perceptual loss to calculate the semantic information of the feature map to improve the model's perceptual ability. Experiments show that the proposal in this paper improves the ability of style transfer, while maintaining image content information. The stylization of the improved model can better meet people's requirements for stylization, and the evaluation indexes of structural similarity, cosine similarity, and mutual information value have increased by 0.323%, 0.094%, and 3.591%, respectively.

PAX--FKHR fusion genes and AChR-gamma in Chinese patients with rhabdomyosarcoma: diagnosis using formalin-fixed archival tissues.

The majority of alveolar RMSs have t(2;13)(q35;q14) or (1:13)(p36;q14),which generate PAX3/7 -FKHR fusion genes. Here, the authors detected the PAX3/7-FKHR fusion transcripts in 17 formalin-fixed, paraffin-embedded RMSs and 26 other SRCTs using one-step RT-PCR. PAX3 -FKHR and PAX7-FKHR transcripts were positive in 4/8 and 2/8 cases of ARMS, respectively. 9 ERMSs and 26 other SRCTs were negative for PAX3/7-FKHR. In addition, AChR-gamma and AChR-alpha mRNA were detected by semiquantitative duplex PCR in above cases and 3 normal muscles. 17 RMSs were found to have overexpression of AChR-gamma, with an AChR-gamma/-alpha ratio of > or =1; 3 cases of normal muscle had very weak AChR-gamma expression, with an AChR- gamma/-alpha ratio of <1. AChR-gamma transcripts were not detectable in all 26 other SCRTs. The results demonstrated that detection of PAX3/7-FKHR fusion gene by one-step RT-PCR is useful in the diagnosis of RMS and that AChR-gamma is overexpressed in Chinese RMS patients.

[Notch1 mRNA and protein expression in human breast cancer and normal mammary gland tissues].

OBJECTIVE: To explore the Notch1 mRNA and protein expression in human breast cancers and normal mammary tissues, and their relationship with the clinical indicators of breast cancers were analyzed. METHODS: Notch1 gene of human breast invasive ductal carcinoma (IDC) and normal mammary gland tissues were amplified by RT-PCR, and the expression of Notch1 protein was detected by immunohistochemical Streptavidin-Biotin Complex (SP) stain in 60 IDC, 30 ductal carcinoma in situ (DCIS) and 60 normal mammary tissues. RESULTS: Notch1 gene of human IDC and normal mammary tissues both could express in a transcription level; the positive rates of Notch1 protein expression in normal mammary tissues and DCIS were 55% and 70%. Respectively, which did not differ statistically (P > 0.05), while the positive rate in IDC was 90%, significantly higher than that of the normal mammary tissues and DCIS (P < 0.05). The high expression of Notch1 protein in IDC correlate significantly with lymph node metastasis, pathological grades and TNM stages. CONCLUSIONS: Notch1 protein was over expressed in breast IDC. A high Notch1 protein expression is considered associating with the evolution and malignant transformation of the breast tumor. The expression of Notch1 gene maybe impact the effect of on the progression of breast cancers.

[Correlation between HLA-DRB1*0901 and 1501, HLA-DQB1*0301 and 0602 alleles and esophageal squamous cell carcinoma of Kazakh in Xinjiang, China].

OBJECTIVE: To investigate the polymorphism of HLA-DRB1 and DQB1 allele in esophageal squamous cell carcinomas of Kazakh in Xinjiang, and to characterize susceptible genes for the family of Kazakh esophageal squamous cell carcinoma. METHODS: HLA-DRB1*0901, DRB1*1501, DQB1*0301, DQB1*0602 alleles were genotyped by sequence specific primers using polymerase chain reaction (PCR-SSP) in 200 Kazakh esophageal squamous cell carcinoma and 177 normal esophageal mucosa. RESULTS: The frequency of HLA-DRB1*1501, HLA-DQB1*0301, HLA-DQB1*0602 alleles in 200 Kazakh esophageal squamous cell carcinoma (0.455, 0.760 and 0.690) were significantly higher than that of 177 normal esophageal mucosa (0.232, 0.520, 0.554; OR = 2.78, 2.93, 1.80; P < 0.05). The frequency of HLA-DRB1*0901 between the carcinoma (0.105) and control groups (0.102) had no association (OR = 1.036, P > 0.05); The frequency of HLA-DQB1*0602 was higher in poor-differentiated squamous cell carcinomas (0.742) than that of well-differentiated tumors (0.597, P < 0.05). CONCLUSIONS: HLA-DRB1*1501, HLA-DQB1*0301, HLA-DQB1* 0602 may be susceptible to Kazakh esophageal squamous cell carcinoma. HLA-DQB1*0602 correlates with well-differentiated esophageal squamous cell carcinoma.

[Comparative genomic hybridization: the profile of chromosomal imbalances in rhabdomyosarcoma].

OBJECTIVE: To characterize the profile of chromosomal imbalances of rhabdomyosarcoma(RMS). METHODS: Comparative genomic hybridization (CGH) was used to investigate genomic imbalances in 25 cases of primary RMS including 10 cases of alveolar rhabdomyosarcoma (ARM), 12 cases of embryonic rhabdomyosarcoma (ERMS), 3 cases of polymorphic rhabdomyosarcoma (PRMS) and 2 RMS cell lines (A240 originated from ARMS and RD from PRMS), with correlation to histological type, pathologic grading, clinical staging, gender and age, respectively. RESULTS: All twenty-five rhabdomyosarcomas showed evidence of increased or decreased DNA sequence copy numbers involving one or more regions of the genome. (1) The frequently gained chromosome regions in RMS were 2p, 12q, 6p, 9q, 10q, 1p, 2q, 6q, 8q, 15q, 18q, and the frequently lost chromosome regions were 3p, 11p, 6p. (2) The frequently gained chromosome arms in ARMS were 12q, 2p, 6, 2q, 4q, 10q, 15q. The frequently lost chromosome arms were 3p, 6p, 1q, 5q. The frequently gained chromosome regions in ERMS were 7p, 9q, 2p, 18q, 1p, 8q. The frequently lost chromosome arms in ERMS were 11p. (3) The frequently gained chromosome arms in translocation associated RMS were 12q, 2, 6, 10q, 4q and 15q (> 30%), 3p, 6p, 5q (> 30%) were the frequently loss chromosome arms. The frequently gained chromosome regions in non-translocation associated RMS were 2p, 9q, 18q (> 30%), and 11p, 14q (> 30%) were the frequently loss chromosome regions. Gain of 12q was significantly correlated with the translocation-associated tumors (P < 0.05). (4) Gains of 9q was significantly correlated with clinical staging (P < 0.05). CONCLUSIONS: Gain of 2p, 12q, 6p, 9q, 10q, 1p, 2q, 6q, 8q, 15q, 18q and loss of 3p, 11p, 6p may be involved in the tumorigenesis of RMS. Gains of 12q may be correlated with gene fusion/chromosomal translocation in ARMS. Gains of 9q may be correlated with an early tumor stage of RMS.

[Study on clinicopathologic features and immunophenotype of 114 cases of renal cell carcinoma].

OBJECTIVE: To study the clinicopathologic features and immunophenotype of renal cell carcinomas, and to discuss their diagnostic value. METHODS: The clinicopathologic features of 114 cases of renal cell carcinoma were reviewed and categorized on the basis of 2004 WHO classification. Immunohistochemical study for a panel of antibodies (including CK, CD10, vimentin, CD117, AMACR, CK7 and TFE3) was carried out. The follow-up data, if available, were also analyzed. RESULTS: The cases were reclassified into 5 subtypes, including 77 cases (67.5%) of clear cell carcinoma (CCRCC), 11 cases (9.6%) of papillary renal cell carcinoma (PRCC), 14 cases (12.3%) of chromophobe renal cell carcinoma (chrRCC), 10 cases (8.8%) of renal carcinoma associated with Xp11.2 translocations/TFE3 gene fusions (Xp11.2RCC) and 2 cases (1.8%) of unclassified renal cell carcinoma (unRCC). Immunohistochemical study showed that the expression rates of CK, CD10 and vimentin in CCRCC were 93.5% (72/77), 93.5% (72/77) and 75.3% (58/77), respectively. On the other hand, all the 11 cases of PRCC studied were positive for AMACR. The expression rate of CD117 in chrRCC was 78.5% (11/14). In the 10 cases of Xp11.2 RCC studied, the expression rates of TFE3, AMACR, CD10 and CK were 100% (10/10), 100% (10/10), 90% (9/10) and 70% (7/10), respectively. CONCLUSIONS: The various subtypes of renal cell carcinomas are heterogeneous in histologic appearance and demonstrate distinctive immunophenotype. The expressions of CD10, vimentin, CD117, AMACR, CK7 and TFE3 are helpful in the differential diagnosis.

[Analysis of the mutation of BRCA1 gene in 70 Uigur women breast cancer patients in Xinjiang].

OBJECTIVE: To analyze the mutations of BRCA1 in breast cancer patients of Uigur women in Xinjiang. METHODS: By using single strand conformation polymorphism (SSCP) and DNA sequencing, BRCA1 mutations were detected in 70 Uigur women breast cancer cases and 32 cases of benign breast diseases and non-tumor tissue next to carcinoma. RESULTS: (1) 12 new loci of BRCA1 gene mutation were detected firstly in 70 Uigur women breast cancer patients. (2)The frequency of BRCA1 mutation in 70 Uigur women breast cancer cases was 12.86% (9/70). The frequency of BRCA1 mutation in Uigur women early onset breast cancer was 31.82% (7/22), which was significantly higher than that in late onset group (2/48, 4.16%) (chi(2) =10.295, P<0.01). (3) There were BRCA1 gene polymorphisms in 9 of 70 Uigur women breast cancer patients. The loci of polymorphisms in 8 of 9 cases were 3232A>G. (4)In the research group two cases of bilateral breast cancer were found with BRCA1 gene mutation. CONCLUSION: The mutation of BRCA1 gene may be related to Uigur women breast cancer and bilateral breast cancer.

[Relationship between p53 Arg72Pro polymorphism and cervical carcinoma in Uigur and Han women in Xinjiang].

OBJECTIVE: To investigate the association between p53 Arg72Pro polymorphism and cervical carcinomas HPV-associated cervical carcinoma in Uigur and Han women. METHODS: The distribution and frequencies of p53 Arg72Pro genotypes were determined by PCR-RFLP in 152 cases of cervical carcinoma in ethnic Uigur women with 110 cases of normal control and 120 cases of cervical carcinoma in Han women with 122 cases of normal control. RESULTS: The omni-constituent ratio of p53 genotype was statistically different between cervical carcinoma and normal control groups in the Uigur (chi(2) = 7.196, P < 0.05) group. The proportion of Arg/Arg was higher in cervical carcinomas than that in control. The omni-constituent ratio of p53 genotype was statistically different between cervical carcinoma and normal control groups in Han (chi(2) = 8.231, P < 0.025). The proportion of Pro/Pro was higher in cervical carcinoma than that in normal control. The omni-constituent ratio was statistically different between HPV 16 positive and negative groups of cervical carcinoma in the Uigur group (chi(2) = 7.177, P < 0.05). The proportion of Arg/Arg was higher in HPV 16 positive group than that in HPV 16 negative group. CONCLUSIONS: p53 Arg72Pro polymorphism may be associated with the development of cervical carcinoma in Uigur and Han women in Xinjiang. p53 Arg/Arg genotype may be a genetically susceptible factor to HPV-associated cervical carcinoma in Uigur. p53 Pro/Pro genotype may be a genetically susceptible factor to cervical carcinoma in Han. There may be different susceptibilities to cervical cancer between Uigur and Han women in Xinjiang.

A Multiscale Constraints Method Localization of 3D Facial Feature Points.

It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative angle histogram of each vertex in a 3D point distribution model is calculated; then the cluster set of the facial feature points is determined using the cluster algorithm. Finally, the feature points are located precisely according to multiscale integral features. The experimental results show that the feature point localization accuracy of this algorithm is better than that of the localization method using the relative angle histograms.

Chromosomal imbalances revealed in primary renal cell carcinomas by comparative genomic hybridization.

Renal cell carcinoma (RCC) accounts for approximately 3% of all new cancer cases. Although the classification of RCC is based mainly on histology, this method is not always accurate. We applied comparative genomic hybridization (CGH) to determine genomic alterations in 46 cases of different RCC histological subtypes [10 cases of clear cell RCC (CCRCC), 13 cases of papillary RCC (PRCC), 12 cases of chromophobe RCC (CRCC), 9 cases of Xp11.2 translocation RCC (Xp11.2RCC), 2 cases of undifferentiated RCC (unRCC)], and investigated the relationships between clinical parameters and genomic aberrations. Changes involving one or more regions of the genome were seen in all RCC patients; DNA sequence gains were most frequently (>30%) seen in chromosomes 7q, 16p, and 20q; losses from 1p, 3p, 13q, 14q, and 8p. We conclude CGH is a useful complementary method for differential diagnosis of RCC. Loss of 3p21-25, 15q, and gain of 16p11-13 are relatively particular to CCRCC vs. other types of RCC. Gain of 7p13-22, 8q21-24, and loss of 18q12-ter, 14q13-24, and Xp11-q13/Y are more apparent in PRCC, and gain of 8q21-24 is characteristic of type 2 PRCC vs. type 1 PRCC. Loss of 2q12-32, 10p12-15, and 11p11-15, 13p are characteristic of CRCC, and gain of 3p and loss of 11p11-15 and 13p are significant differentiators between common CRCC and CRCC accompanied by sarcomatous change groups. Gain of Xp11-12 is characteristic of the Xp11.2RCC group. Based on Multivariate Cox regression analysis, aberration in 5 chromosome regions were poor prognostic markers of RCC, and include the gain of chromosome 12p12-ter (P = 0.034, RR = 3.502, 95% CI 1.097-11.182), 12q14-ter (P = 0.002, RR = 5.115, 95% CI 1.847-14.170), 16q21-24 (P = 0.044, RR = 2.629, 95% CI 1.027-6.731), 17p12-ter (P = 0.017, RR = 3.643, 95% CI 1.262-10.512) and the loss of 18q12-23 (P = 0.049, RR = 2.911, 95% CI 1.006-8.425), which may provide clues of new genes involved in RCC tumorigenesis.

[Diagnostic significance and clinical application of specific chimeric genes in soft tissue sarcomas by RT-PCR using paraffin-embedded tissues: a study of 103 specimens].

OBJECTIVE: To investigate the expression of the chimeric genes resulting from the specific chromosomal translocations in soft tissue sarcomas (STS) and its diagnostic significance for STS. METHODS: The variety of fusion transcripts were detected in 103 cases of STS, including 30 cases of synovial sarcoma (SS), 15 cases of rhabdomyosarcoma (RMS), 25 cases of Ewing's sarcoma/peripheral primitive neuroectodermal tumors (ES/pPNET), 12 cases of dermatofibrosarcoma protuberans (DFSP), 14 cases of aveolar soft part sarcoma (ASPS), 3 cases of leiomyosarcoma (LMS), 2 cases of malignant fibrous histocytoma (MFH), and 2 cases of fibrosarcoma (FS); and 20 cases of control tumors by reverse transcription-polymerase chain reaction (RT-PCR) using formalin fixed, paraffin embedded specimens. RESULTS: Of the 34 cases of SS 28 (93.3%) expressed SSX-SYT chimeric transcripts (14 were positive for SYT-SSX1, 9 for SYT-SSX2). Four of the six cases of alveolar RMS had a PAX3/PAX7-FKHR fusion transcript. None of the 9 cases of embryonic and polymorphic RMS expressed PAX3/PAX7-FKHR. Of the 25 cases of ES/pPNET, 19 were positive for EWS-FLI1 fusion transcript and 1 for EWS-ERG fusion transcript. COL1A1-PDGFB fusion transcript was expressed in 8 of the 12 cases (66.7%) of DFSP. Of the fourteen cases of ASPS, ten expressed ASPL-TFE3 fusion transcript. None of the 3 cases of LMS, 2 cases of MFH, 2 cases of FS, and 20 control cases contained any of the fusion transcript. CONCLUSION: Chimeric gene transcript resulting from specific chromosomal translocations is a reliable index for the molecular diagnosis of STS and RT-PCR assay for detection of specific fusion gene provides a useful tool for confirmation of the diagnosis of STS in diagnostically difficult cases and in retrospective studies.

[Detection of COL1A1/PDGFB fusion transcripts in dermatofibroscoma protuberans by revers transcriptase-polymerase chain reaction using paraffin-embedded tissues].

OBJECTIVE: To detect the COL1A1/PDGFB fusion transcripts and discuss its clinicopathological significance in dermatofibroscoma protuberans. METHODS: Formalin fixed, paraffin-embedded tumor specimens from 12 patients with DFSP were reviewed by light microscope and the expression of COL1A1/PDGFB mRNA resulting from the reciprocal translocation t(17;22) (q22;q13.1) was detected by one-step revers transcriptase-polymerase chain reaction. The following tumor specimens were included as controls: 2 fibrosarcoma, 2 malignant fibrous histocytoma, 3 leiomyosarcoma, 1 dermarofibroma and 1 nerve shealth tumor. RESULTS: The COL1A1/PDGFB fusion transcripts were detected in 8 (67%) of 12 samples from patients with DFSP. Nucleotide sequence analysis using the PCR products confirmed that different regions of the COL1A1 gene, respectively, were fused with of PDGFB gene. No COL1A1/PDGFB fusion transcripts were detected in the control tumors. CONCLUSION: Detection of specific COL1A1/PDGFB fusion transcripts in DFSP will help to diagnose the nature of DFSP and research the mechanism of its molecular histogenesis.

[Study on the diagnostic significance of detecting the expression of AChR-gamma mRNA in rhabdomyosarcoma tissues].

OBJECTIVE: To detect over-expression of AChR-gamma mRNA in rhabdomyosarcoma tissues by duplex RT-PCR and discuss its potential in diagnosis of rhabdomyosarcoma. METHODS: Duplex RT-PCR was applied to the simultaneous detection of AChR-alpha and gamma subunit messenger RNA in 17 cases of rhabdomyosarcoma (9 ERMS, 6 ARMS, 2 PRMS). 20 cases of non-rhabdomyosarcomous small round cell tumors (6 poorly differentiated synovial sarcomas, 6 ES/PNET, 6 lymphomas, 2 neuroblastomas) and three normal muscle samples were also detected for AChR-alpha and gamma mRNA by the same method. RESULTS: AChR-alpha and AChR-gamma mRNA were expressed in all the cases of rhabdomyosarcoma. The rate of quantity in both transcripts was AChR-gamma/AChR-alpha >or= 1, but the rate for three normal muscle samples was < 1. Cases of non-rhabdomyosarcomous small round cell tumors were all negative for AChR-gamma. CONCLUSION: AChR-gamma mRNA expression detected by molecular genetic methods is useful in diagnosis and differential diagnosis of rhabdomyosarcoma.