Release characteristics and risk assessment of volatile sulfur compounds in municipal wastewater treatment plants.

In recent years, the malodorous gases generated by sewage treatment plants have gradually received widespread attention due to their sensory stimulation and health hazards. The emission concentration, sensory evaluation and health risk assessment of volatile sulfur compounds (VSCs) were all explored in two municipal wastewater treatment plants (WWTPs) with oxidation ditch and anaerobic/oxic treatment process, respectively. The VSCs concentration showed the highest amount in the primary treatment unit in both the two WWTPs (73.3% in Plant A and 93.0% in Plant B), while the H2S took the main role in the composition of VSCs. However, H2S took a larger percentage in Plant A (84.5% âˆ¼ 87.0%) rather than Plant B (61.2% âˆ¼ 83.5%), which may be due to the different operating conditions and sludge properties in different treatment process. Besides, H2S also gained the first rank in the sensory evaluation and health risk assessment, which may cause considerable sensory irritation and health risk to workers and surrounding residents. Furthermore, the influencing factor analyses of VSCs emission showed that the temperature of water and air, ORP of sludge made the greatest effect on VSCs release. This study provides theoretical and data support for the research of VSCs emission control in WWTPs.

Release characteristics and risk assessment of volatile sulfur compounds in a municipal wastewater treatment plant with odor collection device.

Due to the malodorous effects and health risks of volatile sulfur compounds (VSCs) emitted from wastewater treatment plants (WWTPs), odor collection devices have been extensively utilized; however, their effectiveness has rarely been tested. In the present investigation, the characteristics of VSCs released in a WWTP equipped with gas collection hoods are methodically examined by gas chromatography. The obtained results indicate that the concentration of VSCs in the ambient air can be substantially reduced, and the primary treatment unit still achieves the highest concentration of VSCs. Compared to WWTPs without odor collection devices, the concentration of H2S in this WWTP is not dominant, but its sensory effects and health risks are still not negligible. Additionally, research on the emission of VSCs from sludge reveals that the total VSCs emitted from dewatering sludge reaches the highest level. Volatile organic sulfur compounds play a dominant role in the component and sensory effects of VSCs released by sludge. This study provides both data and theoretical support for analyzing the effectiveness of odor collection devices in WWTPs, as well as reducing the source of VSCs. The findings can be effectively employed to optimize these devices and improve their performance.

Multi-dimension analysis of volatile sulfur compound emissions from an urban wastewater treatment plant.

Long-term monitoring of volatile sulfur compounds (VSCs) released at the water-air interface from different treatment units of an anaerobic/oxic (A/O) wastewater treatment plant (WWTP) was carried out to assess the temporal and spatial emission characteristics of VSCs, to explore relationships between wastewater quality and VSC release. The VSC from non-aerated and aerated units were collected using dynamic and static chambers, respectively, and determined using gas chromatography. The VSC emission fluxes diminished in the order of primary sedimentation tank (PST) > anaerobic areas (ANA) > oxic section 1 (OX1). VSCs were not detected in the oxic section 2 (OX2), the oxic areas section 3 (OX3), and the final setting basin (FSB). Release capacities of VSCs descended in the order of summer > fall > spring > winter, with July, August, and September being the months with the highest VSC release capacities. VSC emission fluxes correlated well with wastewater temperatures, sulfate concentrations, and COD. VSC emission flux empirical equations based on wastewater temperature, sulfate concentrations, and COD were established. Based on the established VSC emission empirical equation, a control strategy to reduce the operating costs of deodorization facilities was proposed. This strategy is economically efficient and reduces the consumption of electrical energy.

Construction and validation of a survival prognostic model for stage III hepatocellular carcinoma: a real-world, multicenter clinical study.

OBJECTIVE: To construct a survival prediction model for patients with TNM stage III hepatocellular carcinoma (HCC) to guide the clinical diagnosis and treatment of HCC patients and improve prognosis. METHODS: Based on data from patients with stage III (AJCC 7th TNM stage) recorded by the American Institute of Cancer Research from 2010 to 2013, risk factors affecting the prognosis were screened by Cox univariate and multivariate regression, line plots was constructed, and the credibility of the model was verified by Boostrap method. ROC operating curves, calibration curves and DCA clinical decision curves were used to evaluate the model, and Kaplan-Meier was used for survival analysis was used to evaluate the efficacy of the model. External survival data from patients newly diagnosed with stage III hepatocellular carcinoma during 2014-2015 were used to validate and fit the model and to optimize the model. RESULTS: Age > 75 years vs.18-53 years [HR = 1.502; 95%CI(1.134-1.990)], stage IIIC vs. Stage IIIA [HR = 1.930; 95%CI(1.509-2.470)], lobotomy vs. non-surgery [HR = 0.295; 95%CI(0.228-0.383)], radiotherapy vs. non-radiotherapy [HR = 0.481; 95%CI(0.373-0.619)], chemotherapy vs. Non-chemotherapy [HR = 0.443; 95%CI(0.381-0.515)], positive serum AFP before treatment vs. negative [HR = 1.667; 95%CI(1.356-2.049)], the above indicators are independent prognostic factors for patients with stage III hepatocellular carcinoma, and the P values for the above results were less than 0.05. A joint prediction model was constructed based on age, TNM stage, whether and how to operate, whether to receive radiotherapy, whether to receive chemotherapy, pre-treatment serum AFP status and liver fibrosis score. The consistency index of the improved prognosis model was 0.725. CONCLUSIONS: The traditional TNM staging has limitations for clinical diagnosis and treatment, while the Nomogram model modified by TNM staging has good predictive efficacy and clinical significance.

Construction and validation of a nomogram for non small cell lung cancer patients with liver metastases based on a population analysis.

Lung cancer is one of the most common malignancies in the United States, and the common metastatic sites in advanced non-small cell lung cancer (NSCLC) are bone, brain, adrenal gland, and liver, respectively, among which patients with liver metastases have the worst prognosis. We retrospectively analyzed 1963 patients diagnosed with NSCLC combined with liver metastases between 2010 and 2015. Independent prognostic factors for patients with liver metastases from NSCLC were identified by univariate and multivariate Cox regression analysis. Based on this, we developed a nomogram model via R software and evaluated the performance and clinical utility of the model by calibration curve, receiver operating characteristic curves, and decision curve analysis (DCA). The independent prognostic factors for NSCLC patients with liver metastases included age, race, gender, grade, T stage, N stage, brain metastases, bone metastases, surgery, chemotherapy, and tumor size. The area under the curve predicting OS at 6, 9, and 12 months was 0.793, 0.787, and 0.784 in the training cohort, and 0.767, 0.771, and 0.773 in the validation cohort, respectively. Calibration curves of the nomogram showed high agreement between the outcomes predicted by the nomogram and the actual observed outcomes, and the DCA further demonstrated the value of the clinical application of the nomogram. By analyzing the Surveillance, Epidemiology, and End Results database, we established and verified a prognostic nomogram for NSCLC patients with liver metastases, to personalize the prognosis of patients. At the same time, the prognostic nomogram has a satisfactory accuracy and the results are a guide for the development of patient treatment plans.

Diagnostic and prognostic factors, and two nomograms for endometrial cancer patients with bone metastasis: A large cohort retrospective study.

ABSTRACT: Patients with endometrial cancer (EC) who develop bone metastasis (BM) always imply a poorer prognosis. However, reliable predictive models associated with BM from EC are currently limited.We retrospectively analyzed data on 54,077 patients diagnosed with primary EC in the Surveillance, Epidemiology, and End Results database. Multivariate logistic regression analysis was used to determine independent predictors of BM from EC. Univariate and multivariate Cox regression analyses were used to determine independent prognostic factors for EC with BM. Based on independent predictors and prognostic factors, we constructed a diagnostic nomogram and prognostic nomogram separately. Besides, calibration curves, receiver operating characteristic curves, and decision curve analysis were used to evaluate the models.A total of 54,077 patients with EC from the Surveillance, Epidemiology, and End Results database were included in this study, 364 of whom had BM. Multivariate analysis in the logistic model showed that lung metastasis, liver metastasis, brain metastasis, N stage, T stage, histologic grade, and race were risk factors for BM from EC. Multivariate analysis in the Cox model showed that liver metastasis, brain metastasis, chemotherapy, surgery, and histologic type had a significant effect on overall survival. Moreover, the receiver operating characteristic curve, calibration curve, and decision curve analysis indicated the good performance of both diagnostic and prognostic nomograms.Two clinical prediction model was constructed and validated to predict individual risk and overall survival for EC with BM, respectively. Diagnostic nomogram and prognostic nomogram are complementary, improving the clinician's ability to assess the patient's prognosis and enhancing prognosis-based decision making.

EGFR tyrosine kinase inhibitors alone or in combination with chemotherapy for non-small-cell lung cancer with EGFR mutations: A meta-analysis of randomized controlled trials.

OBJECTIVE: The objective of this study was to perform a meta-analysis comparing the efficiency of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) with chemotherapy to EGFR TKI treatment alone in patients with EGFR mutation-positive non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: Following keyword queries in databases and identification of randomized control trials for inclusion, hazard ratios (HRs), relative risks (RRs), and associated 95% confidence intervals (95% CIs) were determined. RESULTS: Ten randomized controlled trials involving 1354 participants with NSCLC were evaluated. We found that a combined approach of chemotherapy with EGFR TKIs significantly improved overall survival (OS) compared with EGFR TKI alone in our patient cohort (HR = 0.47, 95% CI = 0.31-0.72). In addition, a higher overall response rate (ORR) was found for patients who received combined treatment compared to chemotherapy alone (RR = 2.17, 95% CI = 1.51-3.12). Furthermore, concomitant use of chemotherapy with TKIs significantly improved the progression-free survival (PFS) when compared to the use of TKIs alone (HR = 0.68, 95% CI = 0.49-0.95). Moreover, there was a higher ORR among patients who received combined treatment as compared to those who were managed using TKIs only (RR=1.17, 95%CI=1.09-1.25). CONCLUSION: Our meta-analysis shows that EGFR TKIs with chemotherapy confer better OS and ORR compared to either treatment alone, similarly, the combined treatment showed better PFS and ORR profiles than the use of TKI alone.

Surgery for primary tumor benefits survival for breast cancer patients with bone metastases: a large cohort retrospective study.

BACKGROUND: The role of surgery for the primary tumor in breast cancer patients with bone metastases (BM) remains unclear. The purpose of this study was to determine the impact of surgery for the primary tumor in breast cancer patients with BM and to develop prognostic nomograms to predict the overall survival (OS) of breast cancer patients with BM. METHODS: A total of 3956 breast cancer patients with BM from the Surveillance, Epidemiology, and End Results database between 2010 and 2016 were included. Propensity score matching (PSM) was used to eliminate the bias between the surgery and non-surgery groups. The Kaplan-Meier analysis and the log-rank test were performed to compare the OS between two groups. Cox proportional risk regression models were used to identify independent prognostic factors. Two nomograms were constructed for predicting the OS of patients in the surgery and non-surgery groups, respectively. In addition, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to evaluate the performance of nomograms. RESULT: The survival analysis showed that the surgery of the primary tumor significantly improved the OS for breast cancer patients with BM. Based on independent prognostic factors, separate nomograms were constructed for the surgery and non-surgery groups. The calibration and ROC curves of these nomograms indicated that both two models have high predictive accuracy, with the area under the curve values ≥0.700 on both the training and validation cohorts. Moreover, DCA showed that nomograms have strong clinical utility. Based on the results of the X-tile analysis, all patients were classified in the low-risk-of-death subgroup had a better prognosis. CONCLUSION: The surgery of the primary tumor may provide survival benefits for breast cancer patients with BM. Furthermore, these prognostic nomograms we constructed may be used as a tool to accurately assess the long-term prognosis of patients and help clinicians to develop individualized treatment strategies.