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Using a combination of CT findings may increase our ability to distinguish PC from DMPM.

As the proportion of wind power in the world's electricity generation increases, improving wind power prediction accuracy is vital for making full use of wind energy and ensuring the safe and stable operation of the power grid. Given the uncertainty and volatility of wind power and the weak generalization ability of the current wind power prediction models, we propose a wind power prediction model that combines Adaboost algorithm with extreme learning machine optimized by particle swarm optimization (PSO-ELM). First, particle swarm optimization is used to optimize the initial thresholds and input weights of the ELM to obtain the PSO-ELM basic prediction model. Then, combined with the Adaboost algorithm, a series of PSO-ELM weak predictors with input weights and thresholds optimized by PSO and containing different hidden layer nodes are composed. Finally, each weak predictor is weighted and fused into a strong prediction model of wind power, and the final prediction results are output. In this paper, the Adaboost-PSO-ELM model is verified by a wind turbine's measured data in Turkey. The prediction indicators are compared with the current wind power prediction methods including optimized neural networks and ensemble learning models. The results show that the Adaboost-PSO-ELM wind power prediction model has higher accuracy and better generalization ability.

BackgroundThe study aims to find out independent prognostic factors for patients with malignant peritoneal mesothelioma (MPeM).MethodsPatients with pathologically proven MPeM were retrospectively reviewed. Potential prognostic factors were analyzed, including age, gender, asbestos exposure, body mass index (BMI), treatment, and laboratory results, such as blood routine examination and liver functions. The influences of various risk factors on the prognoses were analyzed by univariate analysis. A Cox regression model analysis established independent factors for the survival prognosis of the patients.ResultsSeventy MPeM patients, including 33 patients who received intraperitoneal chemotherapy with cisplatin, 14 patients who received systemic chemotherapy with cisplatin + pemetrexed, and 21 untreated patients were included in this study. The 1-year survival was 32.9%, the 2-year survival was 10%, and the 3-year survival was 2.9%. The median age of MPeM was 62 years, and the female-to-male ratio was 1:0.56. The univariate and multivariate analyses showed that treatment, albumin (ALB), and blood neutrophil-to-lymphocyte ratio (NLR) were independent factors that affected the overall survival (OS) of MPeM patients.ConclusionHigh blood NLR and hypoalbuminemia are adverse prognostic factors for MPeM patients. Systemic chemotherapy and intraperitoneal chemotherapy can prolong the survival period.

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Background/Aims: To investigate differences in blood routine indexes and the expression of cyclooxygenase-2 (COX-2) and nuclear factor-kappa B (NF-κB) in malignant peritoneal mesothelioma (MPeM) and their relationship with clinical prognosis. Methods: We investigated changes in blood routine indexes between the MPeM patients and healthy subjects and detected the expression of COX-2 and NF-κB in peritoneal tissues by a streptavidin-peroxidase immunohistochemistry method. Potential prognostic factors were analyzed including age, gender, white blood cell count (WBC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), absolute platelet count (APC), absolute monocyte count (AMC), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), COX-2, and NF-κB. Cox regression model analysis established independent factors for the survival prognosis of the patients. Results: Compared with the control group, AMC, MXD%, ANC, neutrophilic granulocyte percentage (NEUT%), APC, NLR, MLR, and PLR were markedly increased (p < 0.05) in the MPeM group. The positivity rates for COX-2 and NF-κB expression were 59.4 and 44.9%, respectively. Single factor analyses indicated that PLR, NLR, MLR, COX-2, and NF-κB were factors that affected the overall survival of MPeM patients, but multivariate analyses identified MLR and COX-2 as independent prognostic factors. Conclusions: High blood levels of MLR and COX-2 are adverse prognostic factors for patients with MPeM.

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Objective. The aim of our study was to investigate the expression of EGFR and PTEN in tissues and measure the serum platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) to evaluate the prognostic factors of patients with epithelioid malignant peritoneal mesothelioma (MPeM). Methods. 33 patients of pathologically diagnosed epithelioid MPeM tissues were analyzed using immunohistochemistry to detect EGFR and PTEN; the PLR and NLR were determined by using a routine blood test. We analyzed the relationships of these markers to age, sex, asbestos exposure, elevated platelet count, ascites, and clinical stage. Results. EGFR and PTEN expressions were positive in 22 (66.67%) and 7 (21.21%) epithelioid MPeM patients, respectively. However, these two markers as well as PLR and NLR were not significantly associated with age, sex, asbestos exposure, elevated platelet counts, ascites, and clinical stage (P>0.05). The correlation between EGFR and PTEN was negative (r=−0.577, P<0.001), but the correlation between NLR and PLR was positive (r=0.456, P=0.008). The median survival of all patients was 6 months. In univariate analysis, PTEN (P<0.001), PLR (P=0.014), and NLR (P=0.015) affected the overall survival. Multivariate analysis revealed that PTEN and PLR were validated as predictive for overall survival of epithelioid MPeM (HR=0.070, P=0.001, and HR=3.379, P=0.007, respectively). Conclusion. On the basis of these results, it is suggested that PTEN and PLR are risk factors for the prognosis of epithelioid MPeM, which may be targets for selective therapies and improve the outcomes of patients with epithelioid MPeM.