Medical image diagnosis of prostate tumor based on PSP-Net+VGG16 deep learning network.

BACKGROUND AND OBJECTIVE: Prostate cancer is the most common cancer of the male reproductive system. With the development of medical imaging technology, magnetic resonance images (MRI) have been used in the diagnosis and treatment of prostate cancer because of its clarity and non-invasiveness. Prostate MRI segmentation and diagnosis experience problems such as low tissue boundary contrast. The traditional segmentation method of manually drawing the contour boundary of the tissue cannot meet the clinical real-time requirements. How to quickly and accurately segment the prostate tumor has become an important research topic. METHODS: This paper proposes a prostate tumor diagnosis based on the deep learning network PSP-Net+VGG16. The deep convolutional neural network segmentation method based on the PSP-Net constructs a atrous convolution residual structure model extraction network. First, the three-dimensional prostate MRI is converted to two-dimensional image slices, and then the slice input of the two-dimensional image is trained based on the PSP-Net neural network; and the VGG16 network is used to analyze the region of interest and classify prostate cancer and normal prostate. RESULTS: According to the experimental results, the segmentation method based on the deep learning network PSP-Net is used to identify the data set samples. The segmentation accuracy is close to the Dice similarity coefficient and Hausdorff distance, and even exceeds the traditional prostate image segmentation method. The Dice index reached 91.3%, and the technique is superior in speed of processing. The predicted tumor markers are very close to the actual markers manually by clinicians; the classification accuracy and recognition rates of prostate MRI based on VGG16 are as high as 87.95% and 87.33%, and the accuracy rate and recall rate of the network model are relatively balanced. The area under curve index is also higher than other models, with good generalization ability. CONCLUSION: Experiments show that prostate cancer diagnosis based on the deep learning network PSP-Net+VGG16 is superior in accuracy and processing time compared to other algorithms, and can be well applied to clinical prostate tumor diagnosis.

Image Enhancement Model Based on Deep Learning Applied to the Ureteroscopic Diagnosis of Ureteral Stones during Pregnancy.

OBJECTIVE: To explore the image enhancement model based on deep learning on the effect of ureteroscopy with double J tube placement and drainage on ureteral stones during pregnancy. We compare the clinical effect of ureteroscopy with double J tube placement on pregnancy complicated with ureteral stones and use medical imaging to diagnose the patient's condition and design a treatment plan. METHODS: The image enhancement model is constructed using deep learning and implemented for quality improvement in terms of image clarity. In the way, the relationship of the media transmittance and the image with blurring artifacts was established, and the model can estimate the ureteral stone predicted map of each region. Firstly, we proposed the evolution-based detail enhancement method. Then, the feature extraction network is used to capture blurring artifact-related features. Finally, the regression subnetwork is used to predict the media transmittance in the local area. Eighty pregnant patients with ureteral calculi treated in our hospital were selected as the research object and were divided into a test group and a control group according to the random number table method, 40 cases in each group. The test group underwent ureteroscopy double J tube placement, and the control group underwent ureteroscopy lithotripsy. Combined with the ultrasound scan results of the patients before and after the operation, the operation time, time to get out of bed, and hospitalization time of the two groups of patients were compared. The operation success rate and the incidence of complications within 1 month after surgery were counted in the two groups of patients. RESULTS: We are able to improve the quality of the images prior to medical diagnosis. The total effective rate of the observation group was 100.0%, which is higher than that of the control group (90.0%). The difference between the two groups was statistically significant (P < 0.05). The adverse reaction rate in the observation group was 5.0%, which was lower than 17.5% in the control group. The difference between the two groups was statistically significant (P < 0.05). The comparison results are then prepared. CONCLUSIONS: The image enhancement model based on deep learning is able to improve medical diagnosis which can assist radiologists to better locate the ureteral stones. Based on our method, double J tube placement under ureteroscopy has a significant effect on the treatment of ureteral stones during pregnancy, and it has good safety and is worthy of widespread application.

Underdogs make an alliance: The co-experience of rejection promotes cooperation.

Social rejection research has largely focused on the consequences of rejection when individuals experience rejection alone. Yet little is known about the reaction of those co-experiencing rejection. We tested the hypothesis that the co-experience of rejection increases cooperation between the co-experiencers. Three experiments provided supporting evidence for the hypothesis. The participants cooperated more when they co-experienced rejection than when they experienced rejection alone. The need to belong mediated the relationship between those co-experiencing rejection and cooperation. These findings shed light on the factors that initiate the formation of small groups, especially deviant ones.

Severe traumatic hemorrhagic shock induces compromised immune barrier function of the mesenteric lymph node leading to an increase in intestinal bacterial translocation.

Critically ill patients have increased susceptibility to translocation of gut bacteria. However, the mechanisms are complicated and remain unclear, and the aim of this study was to explore these mechanisms. Rats exposed to different levels of shock were orally administrated with bioluminescent Citrobacter. We found that severe shock caused an increase in bacterial translocation to the visceral organs, such as liver, spleen and blood, compared with mild shock. Surprisingly, bacterial translocation to mesenteric lymph node (MLN) was unchanged between the two shock groups. Various methods, including flow cytometry, a co-culture model and western blots, were used to evaluate MLN-associated immune function. Specifically, we focused on mesenteric lymph node dendritic cells (MLN-DCs), the critical antigen presenting cells involved in the construction of the immune barrier in MLN. We also found that severe shock impaired the phenotypic maturation of MLN-DCs and induced a tolerogenic phenotype. Furthermore, co-culture assays of DCs with naive CD4+ T cells showed that DCs subject to severe shock were more inclined to polarize native CD4+ T cells into Th2 and Treg cells. This study successfully reproduced the clinical phenomenon of severe shock resulting in increased bacterial translocation to extraintestinal tissues, and this may be related to the compromised immune barrier function of MLN, as maturation and function of MLN-DC's were badly impaired.

Molecular cloning and characterization of Babesia orientalis rhoptry-associated protein 1.

The rhoptry-associated protein 1 (RAP-1) gene of Babesia orientalis was obtained from a cDNA expression library by immunoscreening with B. orientalis-infected water buffalo sera. The nucleotide sequence of the cDNA was 1732 bp with an open reading frame (ORF) of 1434 bp, encoding a polypeptide of 478 amino acid residues with a predicted size of 52.5 kDa. The ORF was cloned into a pGEX-KG plasmid and subsequently expressed as a GST-fusion protein. The recombinant RAP-1 of B. orientalis (rBoRAP-1) was purified and evaluated as an antigen using Western blotting. The native BoRAP-1 was recognized by the antibodies raised in rabbits against rBoRAP-1. Strong immunofluorescence signals were observed in erythrocytes infected with B. orientalis. Phylogentic analysis revealed that B. orientalis fell into a Babesia clade and most closely related to Babesia bovis and Babesia ovis, which was similar to the previous reported trees based on 18S rRNA and HSP70 genes. The present study suggests that the BoRAP-1 might be a potential diagnostic antigen, and the RAP-1 genes can aid in the classification of Babesia and Theileria species.

Molecular cloning and characterization of a novel heat shock protein 20 of Babesia orientalis.

The heat shock protein 20 (HSP20) gene of Babesia orientalis (BoHSP20) was identified from both genomic DNA and cDNA. The full-length BoHSP20 gene was 690bp with one intron from position 88-243bp. The amplicon obtained from cDNA corresponded to a full-length open reading frame (ORF) with a length of 534bp, encoding a polypeptide of 178 amino acid residues with a predicted size of 20kDa. The ORF was cloned into a pET-28a plasmid and subsequently expressed as a His-fusion protein. The recombinant HSP20 of B. orientalis (rBoHSP20) was purified and evaluated as an antigen using Western blotting. Anti-B. orientalis water buffalo serum reacted with rBoHSP20, indicating that this protein was an immunodominant antigen and could be a useful diagnostic reagent to detect antibodies against B. orientalis in water buffalo. The native BoHSP20 was recognized by polyclonal antibody from the serum of rabbit immunized with rBoHSP20. Strong immunofluorescence signals were observed from B. orientalis in blood smears by fluorescence microscopy. Bacterial survival experiments indicated that HSP20 can significantly increase the viability of bacteria when the culture is exposed to thermal stress. The results suggest that BoHSP20 might play an important role during B. orientalis transmission from tick to host animal, given the sudden shifts in temperature involved. Phylogenetic analysis revealed that B. orientalis is in the Babesia clade and most closely related to Babesia bovis. Similar topologies were obtained from trees based on 18S rRNA and the HSP70 gene. The present study suggests that BoHSP20 might be a potential diagnostic antigen and that the HSP20 genes can aid in the classification of Babesia and Theileria species.

[Increasing the content of active constituents in Polygonum cuspidatum hairy root by gene transformation technology].

To increase the content of active constituent--RE and PD of Polygonum cuspidatum hairy root, through Ri-mediated gene transformation technology, modified high salt low pH method was used to distill genome DNA of grapevine (Vitis raparia). Primer was designed according to sequence of Genebank (AF128861). Through PCR amplification obtain RS gene sequence was obtained. Binary vector pCAMBIA1300-35S-RS was constructed. Frost thawing method was used to transform Agrobacterium rhizogenes ATCC11325. Scratched aseptic seedling leaf of Polygonum cuspidatum was contaminated subsequently. DNA conformity and mRNA expression of RS gene were investigated by PCR and RT-PCR respectively. RE and PD in transgenic hairy root were determined by HPLC. For the first time successfully inducement acquires transformed RS gene hairy root of Polygonum cuspidatum. Content of active constituents--RE and PD were 17 - 187 microg x g(-1) DW and 836 - 1 970 microg x g(-1) DW, respectively, the non-transgenic hairy root was 0 - 130 microg x g(-1) DW and 190 - 320 microg x g(-1) DW. In the different root selected, the content of PD was much higher than that in non-transformed hairy roots of Polygonum cuspidatum, the highest content is 5 times, but the content of RE has not increased apparently.

[Expression of T cell markers in hematological diseases and solid tumor].

To explore the relationship between T cell markers in hematological diseases and T cell markers in solid tumor, CD3, CD4, CD8 in hematological diseases, malignant and benign tumors were detected by flow cytometry and results were analyzed statistically. The results showed that CD3, CD4, CD8 and CD4/CD8 in chronic leukemia decreased significantly while these markers in acute leukemia and MDS decreased obviously in comparison with normal persons and other hematological diseases (P < 0.0l). Hemolytic anemia markers increased significantly (P < 0.05). CD3, CD4, CD4/CD8 in idiopathic thrombocytopenic purpura decreased and CD8 increased (P < 0.0l). CD3, CD4, CD8 in iron-deficiency anemia, anemia from chronic diseases, benign tumor and other hematological diseases were lower than those in normal persons and hemolytic anemia, but higher than those in acute and chronic leukemia, malignant tumor, granulocytopenia, and MDS (P > 0.05). It is notable that the above markers correlated with the development and prognosis of diseases. In conclusion, expression of CD3, CD4, CD8, CD4/CD8 contributes to diagnosis of hematological diseases and benign or malignant tumors, and is an important indicator for therapeutic strategy.