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.

Treatment response of a two-dose regimen of dose-adjusted inotuzumab ozogamicin in relapsed/refractory B-cell acute lymphoblastic leukemia / 中华血液学杂志

Objective: To observe the treatment response of a two-dose regimen of inotuzumab ozogamicin (inotuzumab), a monoclonal antibody targeting CD22, for patients with heavily treated relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL), including those failed or relapsed after chimeric antigen receptor (CAR) -T-cell therapy. Methods: Pediatric and adult patients who received two doses of inotuzumab and who were evaluated after inotuzumab treatment were included. Antibody infusions were performed between March 2020 and September 2022. All patients expressed CD22 antigen as detected by flow cytometry (>80% leukemic cells displaying CD22) before treatment. For adults, the maximum dosage per administration was 1 mg (with a total of two administrations). For children, the maximum dosage per administration was 0.85 mg/m(2) (no more than 1 mg/dose; total of two administrations). The total dosage administered to each patient was less than the standard dosage of 1.8 mg/m(2). Results: Twenty-one patients with R/R B-ALL were included, including five children (<18 years old) and sixteen adults. Seventeen patients presented with 5.0% -99.0% leukemic blasts in the bone marrow/peripheral blood or with extramedullary disease, and four patients were minimal residual disease (MRD) -positive. Fourteen patients underwent both CD19 and CD22 CAR-T-cell therapy, four underwent CD19 CAR-T-cell therapy, and three underwent blinatumomab therapy. Eleven patients underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT). After inotuzumab treatment, 14 of 21 patients (66.7% ) achieved a complete response (CR, one was MRD-positive CR), and all four MRD-positive patients turned MRD-negative. Four of six patients who failed recent CD22 CAR-T-cell therapy achieved a CR after subsequent inotuzumab treatment. Seven patients (33.3% ) demonstrated no response. Grade 1-3 hepatotoxicity occurred in five patients (23.8% ), one child with no response experienced hepatic veno-occlusive disease (HVOD) during salvage transplantation and recovered completely. Conclusion: For patients with heavily treated R/R B-ALL, including those who had undergone allo-HSCT and CD19/CD22 CAR-T-cell therapy, the two-dose regimen of inotuzumab resulted in a CR rate of 66.7%, and the frequency of hepatotoxicity and HVOD was low.

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.

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.

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.

Unclassified renal cell carcinoma: a clinicopathological, comparative genomic hybridization, and whole-genome exon sequencing study.

Unclassified renal cell carcinoma (URCC) is a rare variant of RCC, accounting for only 3-5% of all cases. Studies on the molecular genetics of URCC are limited, and hence, we report on 2 cases of URCC analyzed using comparative genome hybridization (CGH) and the genome-wide human exon GeneChip technique to identify the genomic alterations of URCC. Both URCC patients (mean age, 72 years) presented at an advanced stage and died within 30 months post-surgery. Histologically, the URCCs were composed of undifferentiated, multinucleated, giant cells with eosinophilic cytoplasm. Immunostaining revealed that both URCC cases had strong p53 protein expression and partial expression of cluster of differentiation-10 and cytokeratin. The CGH profiles showed chromosomal imbalances in both URCC cases: gains were observed in chromosomes 1p11-12, 1q12-13, 2q20-23, 3q22-23, 8p12, and 16q11-15, whereas losses were detected on chromosomes 1q22-23, 3p12-22, 5p30-ter, 6p, 11q, 16q18-22, 17p12-14, and 20p. Compared with 18 normal renal tissues, 40 mutated genes were detected in the URCC tissues, including 32 missense and 8 silent mutations. Functional enrichment analysis revealed that the missense mutation genes were involved in 11 different biological processes and pathways, including cell cycle regulation, lipid localization and transport, neuropeptide signaling, organic ether metabolism, and ATP-binding cassette transporter signaling. Our findings indicate that URCC may be a highly aggressive cancer, and the genetic alterations identified herein may provide clues regarding the tumorigenesis of URCC and serve as a basis for the development of targeted therapies against URCC in the future.

Analysis of PTEN methylation patterns in soft tissue sarcomas by MassARRAY spectrometry.

Soft tissue sarcomas (STSs) are a rare and fascinating group of diseases that can be subdivided into specific reciprocal translocations in STSs (SRTSs) and nonspecific reciprocal translocations in STSs (NRTSs). PTEN mutations are rare in STSs, suggesting that PTEN expression may be lost by alternative mechanisms such as methylation. In order to reveal whether aberrant PTEN methylation occurs in STSs, MassARRAY Spectrometry was carried to detect methylation patterns of PTEN in STSs. We evaluated methylation levels in 41 CpG sites from -2,515 to -2,186 bp (amplicon A) and -1,786 to -1,416 bp (amplicon B) relative to the translation initiation site in 110 different cases (46 cases of SRTSs, 40 cases of NRTSs, and 24 cases of normal controls). In addition, immunohistochemistry (IHC) was used to detect the loss of PTEN to determine whether PTEN alterations were responsible for decreased PTEN expression. Our data showed that expression of PTEN was diminished in 49 (57%) STSs, whereas the remaining cases (43%) were classified as high expression. Our previous results found that only 2 of 86 cases (2.3%) had a PTEN mutation suggesting that PTEN may be mainly downregulated in STSs by methylation, but not by mutation of PTEN itself. We observed that amplicon A was hypermethylated in STSs with low PTEN expression, whereas normal controls had low methylation levels (P<0.0001), which was not present in amplicon B (P>0.05), nor were there significant differences in the methylation levels in PTEN between SRTS and NRTS cases. The majority of individual CpG units within two amplicons was demonstrated to be hypermethylated. These findings indicate that PTEN hypermethylation is a common event in STSs suggesting that the inactivation of PTEN may be due to hypermethylation in the promoter of PTEN. The aberrant methylation of the CpG sites within PTEN promoter may serve as a potential candidate biomarker for STSs.

Mutational analysis of p53 and PTEN in soft tissue sarcoma.

p53 and PTEN are the two most frequently mutated tumor suppressors in human cancer. However, literature on the effect of the joint inactivation of tumor-suppressor genes in soft tissue sarcoma (STS) is lacking. The purpose of this study was to investigate whether p53 and PTEN mutations play a role in the carcinogenesis of STS, as well as to evaluate their mutual role in STS pathogenesis. We screened mutations of p53 and PTEN in 86 human STSs using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) and DNA sequencing, respectively. p53 mutations were detected in 25.6% (22 out of 86) of STSs: 6 cases of p53 mutations were detected in 46 cases of specific reciprocal translocations in STSs (13.0%), 16 cases were detected in 40 cases of nonspecific reciprocal translocations in STSs (40.0%); the majority of the mutations were point mutations in exon 6-7. Furthermore, PTEN mutations were observed in 2 out of 86 STSs (2.3%). Two out of 86 cases revealed a 130th codon G>A missense mutation in exon 8 of PTEN which resulted in an Arg change to Gln in the PTEN protein structure; and a 334th codon A>T missense mutation in exon 8 of PTEN, which resulted in an Asn change to Lys in the PTEN protein structure. All subjects were examined for p53 exon 5-9 mutations and for PTEN exon 5-9 mutations. However, no tumors contained an alteration of the two genes. The findings indicate that p53 mutations may be involved in the oncogenesis of STS and also suggest that p53 may function as a potential molecular marker for distinguishing between STSs with specific reciprocal translocations and nonspecific reciprocal translocations. Although the existence of PTEN mutations in STS was detected, the PTEN mutation frequency was quite low. We conclude that PTEN may have played a less prognostic role than p53 in the development and malignant transformation of STS in the patients examined.

Shengjing tablets for semen non-liquefaction: a clinical study of 100 cases / 中华男科学杂志

<p><b>OBJECTIVE</b>To investigate the efficacy and action mechanism of Shengjing Tablets in the treatment liquefaction.</p><p><b>METHODS</b>We randomly assigned 150 patients with semen non-liquefaction to receive Shengjing Tablets group, n = 100) and vitamin E capsules (control group, n = 50) for 2 courses of 45 days each, followed by observation liquefaction time and other semen parameters.</p><p><b>RESULTS</b>After the first course, 68 of the patients in the treatment group 20 responded and 12 failed to respond; and after the second course, 84 were cured, 9 responded and 7 failed to respond, effective rate of 93.0%. In comparison, only 8 of the controls were cured, 8 responded and 34 failed to respond after medication. There were statistically significant differences between the two groups (P < 0.01). Meanwhile, the treatment showed obvious improvement in sperm motility and concentration.</p><p><b>CONCLUSION</b>Shengjing Tablets may shorten the time liquefaction, and can be used as a safe and effective therapy for semen non-liquefaction.</p>

[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.

Phenotypic changes of human cells in human-rat liver during partial hepatectomy-induced regeneration.

AIM: To examine the human hepatic parenchymal and stromal components in rat liver and the phenotypic changes of human cells in liver of human-rat chimera (HRC) generated by in utero transplantation of human cells during partial hepatectomy (PHx)-induced liver regeneration. METHODS: Human hepatic parenchymal and stromal components and phenotypic changes of human cells during liver regeneration were examined by flow cytometry, in situ hybridization and immunohistochemistry. RESULTS: ISH analysis demonstrated human Alu-positive cells in hepatic parenchyma and stroma of recipient liver. Functional human hepatocytes generated in this model potentially constituted human hepatic functional units with the presence of donor-derived human endothelial and biliary duct cells in host liver. Alpha fetoprotein (AFP)(+), CD34(+) and CD45(+) cells were observed in the chimeric liver on day 10 after PHx-induced liver regeneration and then disappeared in PHx group, but not in non-PHx group, suggesting that dynamic phenotypic changes of human cells expressing AFP, CD34 and CD45 cells may occur during the chimeric liver regeneration. Additionally, immunostaining for human proliferating cell nuclear antigen (PCNA) showed that the number of PCNA-positive cells in the chimeric liver of PHx group was markedly increased, as compared to that of control group, indicating that donor-derived human cells are actively proliferated during PHx-induced regeneration of HRC liver. CONCLUSION: HRC liver provides a tool for investigating human liver regeneration in a humanized animal model.

Chromosomal imbalances revealed in primary rhabdomyo-sarcomas by comparative genomic hybridization.

BACKGROUND: Previous cytogenetic studies revealed aberrations varied among the three subtypes of rhabdomyosarcoma. We profiled chromosomal imbalances in the different subtypes and investigated the relationships between clinical parameters and genomic aberrations. METHODS: Comparative genomic hybridization was used to investigate genomic imbalances in 25 cases of primary rhabdomyosarcomas and two rhabdomyosarcoma cell lines. Specimens were reviewed to determine histological type, pathological grading and clinical staging. RESULTS: Changes involving one or more regions of the genome were seen in all rhabdomyosarcomal patients. For rhabdomyosarcoma, DNA sequence gains were most frequently (> 30%) seen in chromosomes 2p, 12q, 6p, 9q, 10q, 1p, 2q, 6q, 8q, 15q and 18q; losses from 3p, 11p and 6p. In aggressive alveolar rhabdomyosarcoma, frequent gains were seen on chromosomes 12q, 2p, 6p, 2q, 4q, 10q and 15q; losses from 3p, 6p, 1q and 5q. For embryonic rhabdomyosarcoma, frequent gains were on 7p, 9q, 2p, 18q, 1p and 8q; losses only from 11p. Frequently gained chromosome arms of translocation associated with rhabdomyosarcoma were 12q, 2, 6, 10q, 4q and 15q; losses from 3p, 6p and 5q. The frequently gained chromosome arms of nontranslocation associated with rhabdomyosarcoma were 2p, 9q and 18q, while 11p and 14q were the frequently lost chromosome arms. Gains on chromosome 12q were significantly correlated with translocation type. Gains on chromosome 9q were significantly correlated with clinical staging. CONCLUSIONS: Gains on chromosomes 2p, 12q, 6p, 9q, 10q, 1p, 2q, 6q, 8q, 15q and 18q and losses on chromosomes 3p, 11p and 6p may be related to rhabdomyosarcomal carcinogenesis. Furthermore, gains on chromosome 12q may be correlated with translocation and gains on chromosome 9q with the early stages of rhabdomyosarcoma.

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.

[The effect of formalin-induced pain on CCK in rat spinal cord neurons].

AIM: CCK is one of the strongest endogenous anti-opioid substances and suppresses morphine tolerance which results from long term use of morphine. This study explores the modulatory effect of CCK on pain formalin-induced. METHODS: The effect of formalin-induced pain on CCK immunoreactivity in rat sensory neurons was observed through immunohistochemistry technique. RESULTS: After 1 h of subcutaneous injection of formalin in one paw of rats, the number of positive neurons of CCK immunoreactivity in spinal cord neurons was obviously increased and greater than that of non-injection side (P <0.01). The semi-quantitative optical density average values of CCK immunoreactivity neurons were 0.397 +/- 0.014 and 0.295 +/- 0.007 in injection side and non-injection side respectively, the difference was obvious (P < 0.01). After 3 h of subcutaneous injection of formalin in one paw of rats, the semi-quantitative optical density average values of CCK immunoreactivity neurons were 0.366 +/- 0.009 and 0.303 +/- 0.005 in injection side and noninjection side respectively, the difference was significant (P < 0.01). CONCLUSION: Formalin-induced pain can significantly change semi-quantitative optical density average value of CCK immunoractivity in spinal cord neurons, this indicates CCK participates in modulation of pain.

[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.