Response of Acid and Alkaline Phosphatase Activities to Copper Exposure and Recovery in Freshwater Fish Carassius auratus gibelio var

Abstract: Phosphatase is known to be sensitive to metal exposures and can be used to predict metal toxicity. In this study, freshwater fish Carassius auratus gibelio var were exposed to different concentrations (0.1, 0.2, 0.5, 1.0 and 2.0mg/L) of copper for 96 h, and the group of 2.0 mg/L exposure was then transferred to clean water for different days (1, 4, 8 and 12d) to assess recovery profile. Responses of acid phosphatase (ACP) and alkaline phosphatase (ALP) activities from kidney, liver, gill, spleen, muscle and brain to copper exposure and recovery were investigated. As shown from the results, after a 96-h copper exposure, ACP and ALP activities in different organs/tissues appeared to be different. At the highest copper concentration (2.0 mg/L), compared with the control, ACP activity decreased significantly in kidney, liver, gill and spleen, but increased significantly in muscle and brain. ALP activity decreased significantly in kidney, liver, gill, spleen and brain. However, after removing 2.0 mg/L copper exposure, ACP and ALP activities in different organs/tissues all normalized within 12 days. The observed data suggest that ACP and ALP in spleen of Carassius auratus gibelio var are most sensitive to copper stress and might be used as suitable biomarkers for copper contamination in aquatic environment

Development, assessment and validation of a novel prediction nomogram model for risk identification of tracheobronchial tuberculosis in patients with pulmonary tuberculosis

Objective Tracheobronchial tuberculosis (TBTB), a specific subtype of pulmonary tuberculosis (PTB), can lead to bronchial stenosis or bronchial occlusion if not identified early. However, there is currently no available means for predicting the risk of associated TBTB in PTB patients. The objective of this study was to establish a risk prediction nomogram model for estimating the associated TBTB risk in every PTB patient.Methods A retrospective cohort study was conducted with 2153 PTB patients. Optimised characteristics were selected using least absolute shrinkage and selection operator regression. Multivariate logistic regression was applied to build a predictive nomogram model. Discrimination, calibration and clinical usefulness of the prediction model were assessed using C-statistics, receiver operator characteristic curves, calibration plots and decision analysis. The developed model was validated both internally and externally.Results Among all PTB patients who underwent bronchoscopies (n=2153), 40.36% (n=869) were diagnosed with TBTB. A nomogram model incorporating 11 predictors was developed and displayed good discrimination with a C-statistics of 0.782, a sensitivity of 0.661 and a specificity of 0.762 and good calibration with a calibration-in-the-large of 0.052 and a calibration slope of 0.957. Model’s discrimination was favourable in both internal (C-statistics, 0.782) and external (C-statistics, 0.806) validation. External validation showed satisfactory accuracy (sensitivity, 0.690; specificity, 0.804) in independent cohort. Decision curve analysis showed that the model was clinically useful when intervention was decided on at the exacerbation possibility threshold of 2.3%–99.2%. A clinical impact curve demonstrated that our model predicted high-risk estimates and true positives.Conclusion We developed a novel and convenient risk prediction nomogram model that enhances the risk assessment of associated TBTB in PTB patients. This nomogram can help identify high-risk PTB patients who may benefit from early bronchoscopy and aggressive treatment to prevent disease progression