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Backgroud: This study was aimed to develop and internally validate a nomogram for risk of upgrade of ISUP (International Society of Urology Pathology) grade group from biopsy tissue to RP (radical prostatectomy) final histology.Methods: 166 patients with prostate cancer were retrospectively analyzed and divided into two groups based on ISUP upgrade status from needle biopsy to radical prostatectomy specimen, these being the 'ISUP upgrade' group and the 'no ISUP upgrade' group. Logistic regression analysis was used to predict the significant independent factors for ISUP upgrade. A nonogram was then developed based on these independent factors, which would predict risk of ISUP upgrade. The C-index, calibration plot, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the predicting model. Internal validation was evaluated by using the bootstrapping validation. Results: There were 47 patients in the ISUP upgrade group and 119 patients in the no ISUP upgrade group respectively. Patients in the ISUP upgrade group tended to be of younger age, smaller PV (prostate volume), lower GS (Gleason score) of PB (prostate biopsy) tissue than the no ISUP upgrade group (p=0.043, p=0.041, p < 0.001, p =0.04, respectively). Multivariate logistic regression analysis showed that GS ≤6 (OR=14.236, P=0.001), prostate biopsy approach (TB-SB (transperineal prostate systematic biopsy) VS TR-SB (transrectal prostate systematic biopsy), OR=0.361, P=0.03) and number of positive cores < 10 (OR=0.396, P=0.04) were the independent risk factors for ISUP upgrade. A prediction nomogram model of ISUP upgrade was built based on these significant factors above, the area under the receiver operating characteristic (AUC) curve of which was 0.802. The C-index for the prediction nomogram was 0.798 (95%CI: 0.655–0.941) and the nomogram showed good calibration. High C-index value of 0.772 could still be reached in the interval validation. Decision curve analysis also demonstrated that the threshold value of RP-ISUP upgrade risk was 3% to 67%. Conclusion: A novel nomogram incorporating PSA, GS of PCa, ways of prostate biopsy and number of positive cores was built with a relatively good accuracy to assist clinicians to evaluate the risk of ISUP upgrade in the RP specimen, especially for the low-risk prostate cancer diagnosed by TR-SB.

Backgroud: This study was aimed to develop and internally validate an ISUP (International Society of Urology Pathology) upgrade risk nomogram from the biopsy tissue to the specimen of radical prostatectomy. Methods: The clinical characteristics of 166 patients with prostate cancer were retrospectively analyzed, who were divided into two groups based on the upgrade of ISUP between the biopsy tissue and radical prostatectomy specimen. Logistic regression analysis was used to predict the significant independent factors of ISUP upgrade, a nomogram was established to predict ISUP upgrade of prostatectomy specimen based on the significant factors. The C-index, calibration plot, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the predicting model. Internal validation was evaluated by using the bootstrapping validation. Results: There were 47 patients in the ISUP upgrade group and 119 patients in the no ISUP upgrade group respectively. Patients in the ISUP upgrade group inclined to be younger age, smaller PV, lower GS scores and PB-ISUP than the no ISUP upgrade group (p=0.043, p=0.041, p < 0.001, p =0.04, respectively), Multivariate logistic regression analysis showed that PSA≥20 ng/ml (OR=8.558, P=0.024), Gleason score of PCa≤6 (OR=9.026, P=0.004), PB-ISUP=3,4vs5 (OR=23.232, P=0.000417; OR=26.72, P=0.000241), ways of prostate biopsy (TP-SB+COG-TB (transperineal prostate biopsy + cognitive fusion targeted biopsy) VS TR-SB (transrectal prostate system biopsy), OR=033, P=0.036) and number of positive cores < 10 (OR=0.21, P=0.002) were the independent risk factors for ISUP upgrade. A prediction nomogram model of ISUP upgrade was built based on these significant factors above, the area under the receiver operating characteristic (AUC) curve of which was 0.843. The C-index for the prediction nomogram was 0.871 (95% CI: 0.817–0.925) and the nomogram showed good calibration. Decision curve analysis also demonstrated that the threshold value of RP-ISUP upgrade risk was 1% to 89%. Conclusion: A novel nomogram incorporating PSA, Gleason score of PCa, PB-ISUP, ways of prostate biopsy and number of positive cores was built with a relatively good accuracy to assist clinicians to evaluate the risk of ISUP upgrade in the radical prostatectomy specimen, especially for the low-risk prostate cancer diagnosed by TR-SB.

Background. In recent years, immune-associated genes (IAGs) have been documented as having critical roles in the occurrence and progression of muscle-invasive bladder cancer (MIBC). Novel immune-related biomarkers and a robust prognostic signature for MIBC patients are still limited. The study is aimed at developing an IAG-based signature to predict the prognosis of MIBC patients. Methods. In the present study, we identified differentially expressed IAGs in MIBC by using transcriptomics data from The Cancer Genome Atlas (TCGA) database and proteomics data from our samples. We further constructed an IAG-based signature and evaluated its prognostic and predictive value by survival analysis and nomogram. Tumor Immune Estimation Resource (TIMER) was applied to explore the correlation between the IAG-based signature and immune cell infiltration in the microenvironment of MIBC. Results. A total of 22 differentially expressed IAGs were identified, and 2 IAGs (NR2F6 and AHNAK) were used to establish a prognostic signature. Subsequently, survival analysis showed that high-risk scores were significantly correlated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of MIBC patients. A prognostic nomogram was constructed by integrating clinical factors with the IAG-based signature risk score. In addition, the IAG-based signature risk score was positively associated with the infiltration of macrophages and dendritic cells in MIBC. Conclusions. We constructed and verified a novel IAG-based signature, which could predict the prognosis of MIBC and might reflect the status of the immune microenvironment of MIBC. Further studies in more independent clinical cohorts and further experimental exploration of the prognostic IAG-based signature are still needed.

In this paper, we investigate synchronization and its DSP implementation of fractional-order simplified Lorenz hyperchaotic systems by employing the Adomian decomposition method. The active controller and linear feedback controller are designed. Numerical simulation of the synchronized systems is carried out, and it is found that the synchronization phenomenon can be observed in both state variables and intermediate variables. Moreover, the synchronized systems are implemented in two TMS320F2-8335 DSP boards which are connected by a serial port and the output signals are exhibited by an oscilloscope. The experiment results show that the proposed implementation method works well on DSP.

For most containers drop during transportation, it may be due to bad weather conditions, bad channel conditions, a cluster of vessel traffic flow distribution, and the operation of ship’s personnel container water, causing water pollution, such as floats the water pollution situation, design a kind of container transportation of container water pollution prevention plan. The first is to modify the original container, and install GSP positioning device and transmission module for data transmission in the container. In addition, a mesh air bag is arranged on the outside of the container and a self-starting device is installed on the outside of the container. When the container accidentally falls into the water, the self-starting device in the water contact with the water to start, and open the air valve mesh air bag to inflate to provide buoyancy, collision protection and content leakage for the falling water container. After all devices are started, the GSP positioning device locates every 10 minutes and sends location information to the fishing center through the transmission module of data transmission. In the fishing center, the distribution map of the falling container in the target water area can be formed to facilitate the salvage of the falling container.