The inter-species differences of estradiol metabolism were investigated in human, Beagle dog and rat liver microsomes by comparing enzyme kinetics of parent drug and the formation of its major metabolites. The incubation systems of estradiol with liver microsomes of the three species were optimized in terms of estradiol concentration, microsomal protein content and incubation time. The concentrations of estradiol and its metabolites were measured by LC-MS/MS method. The t1/2, CLint, CLh, Km and Vmax of estradiol incubated with male human liver microsomes were 40.02 +/- 8.32 min, 41.39 +/- 6.57 mL x min(-1) x kg(-1), 13.81 +/- 12.36 mL x min(-1) x kg(-1), 26.8 +/- 6.99 micromol x L(-1) and 0.75 +/- 0.92 micromol x L(-1) x min(-1), respectively. The corresponding parameters of female human were 44.71 +/- 10.21 min, 29.85 +/- 8.97 mL x min(-1) x kg(-1), 0.01 +/- 0.68 mL x min(-1) x kg(-1), 44.2 +/- 7.73 micromol x L(-1) and 1.27 +/- 4.41 micromol x L(-1) x min(-1), that of male dog were 21 +/- 7.33 min, 165.53 +/- 29.33 mL x min(-1) xkg(-1), 26.01 +/- 8.39 mL x min(-1) x kg(-1), 19.5 +/- 7.34 micromol x L(-1) and 1.6 +/- 0.65 micromol x L(-1) x min(-1), that of female dog were 25.5 +/- 5.32 min, 135.11 +/- 42.34 mL x min(-1) x kg(-1), 0.24 +/- 3.18 mL x min(-1) x kg(-1), 8.33 +/- 6.32 micromol x L(-1) and 0.51 +/- 2.15 micromol x L(-1) x min(-1), that of male rat were 5.11 +/- 3.84 min, 485.63 +/- 36.52 mL x min(-1) x kg(-1), 49.57 +/- 15.29 mL x min(-1) x kg(-1), 62 +/- 13.74 micromol x L(-1) and 19.16 +/- 9.67 micromol x L(-1) x min(-1), and that of female rat were 7.0 +/- 3.69 min, 354.82 +/- 33.33 mL x min(-1) x kg(-1), 8.04 +/- 3.23 mL x min(-1) x kg(-1), 35.38 +/- 7.65 micromol x L(-1) and 8.39 +/- 4.91 micromol x L(-1) min(-1), respectively. There were nine metabolites detected from all the three species, but the relative amounts of the metabolites generated were different in three species. The results indicted that the major phase I metabolic pathway of estradiol was similar in the liver microsomes from all the three species. However, the inter-species differences were found in the view of relative amounts of the metabolites as well as the metabolic characteristics of estradiol in liver microsomal incubation.

Waterborne viruses that can be harmful to human health pose significant challenges globally,affecting health care systems and the economy.Identifying these waterborne pathogens is essential for preventing diseases and protecting public health.However,handling complex samples such as human and waste-water can be challenging due to their dynamic and complex composition and the ultralow concentration of target analytes.This review presents a comprehensive overview of the latest breakthroughs in waterborne virus biosensors.It begins by highlighting several promising strategies that enhance the sensing performance of optical and electrochemical biosensors in human samples.These strategies include optimizing bioreceptor selection,transduction elements,signal amplification,and integrated sensing systems.Furthermore,the insights gained from biosensing waterborne viruses in human sam-ples are applied to improve biosensing in wastewater,with a particular focus on sampling and sample pretreatment due to the dispersion characteristics of waterborne viruses in wastewater.This review suggests that implementing a comprehensive system that integrates the entire waterborne virus detection process with high-accuracy analysis could enhance virus monitoring.These findings provide valuable insights for improving the effectiveness of waterborne virus detection,which could have sig-nificant implications for public health and environmental management.

Objective:To explore the accuracy of artificial intelligence (AI) system based on deep learning in evaluating bone age of children with abnormal growth and development.Methods:The positive X-ray films of the left wrist of children with abnormal growth and development who were treated at the Affiliated Hospital of Guizhou Medical University from January 2020 to December 2021 were collected retrospectively. A total of 717 children were collected, including 266 males and 451 females, aged 2-18 (11±3) years. Based on Tanner Whitehouse 3 (TW 3)-RUS (radius, ulna, short bone) and TW3-Carpal (carpal bone) method, bone age was measured by 3 senior radiologists, and the mean value was taken as reference standard. The bone ages were independently evaluated by the AI system (Dr.Wise bone age prediction software) and two junior radiologists (physicians 1 and 2). The accuracy within 0.5 year, the accuracy within 1 year, the mean absolute error (MAE) and the root mean square error (RMSE) between the evaluation results and the reference standard were analyzed. Paired sample t-test was used to compare MAE between AI system and junior physicians. Intraclass correlation coefficient (ICC) was used to evaluate the consistency between AI system, junior physician and reference standard. The Bland-Altman diagram was drawn and the 95% consistency limit was calculated between AI system and reference standard. Results:For TW3-RUS bone age, compared with the reference standard, the accuracy within 0.5 year of AI system, physician 1 and physician 2 was 75.3% (540/717), 62.1% (445/717) and 66.2% (475/717), respectively. The accuracy within 1 year was 96.9% (695/717), 86.3% (619/717) and 89.1% (639/717), respectively. MAE was 0.360, 0.565 and 0.496 years, and RMSE was 0.469, 0.634 and 0.572 years, respectively. For TW3-Carpal bone age, compared with the reference standard, the accuracy within 0.5 year of AI system, physician 1 and physician 2 was 80.9% (580/717), 65.1% (467/717) and 71.7% (514/717), respectively. The accuracy within 1 year was 96.0% (688/717), 87.3% (626/717) and 90.4% (648/717), respectively. MAE was 0.330, 0.527 and 0.455 years, and RMSE was 0.458, 0.612, 0.538 years, respectively. Based on TW3-RUS and TW3-Carpal bone age, the MAE of AI system were lower than those of physician 1 and physician 2, and the differences were statistically significant ( P all<0.001). The evaluation results of AI, physician 1 and physician 2 were in good agreement with the reference standard (ICC all>0.950). The Bland-Altman analysis showed that the 95% agreement limits of AI system for assessing TW3-RUS and TW3-Carpal bone age were -0.75-1.02 years and-0.86-0.91 years, respectively. Conclusion:The accuracy of AI system in evaluating the bone age of children with abnormal growth and development is close to that of senior doctors, better than that of junior doctors, and in good agreement with senior doctors.

A novel method for the simultaneous determination of 3-nitrotyrosine (NT) and 3-chlorotyrosine (CT) in human plasma has been developed based on direct analysis in real time-tandem mass spectrometry (DART-MS/MS). Analysis was performed in the positive ionization mode using multiple reaction monitoring (MRM) of the ion transitions at m/z 216.2/170.1 for CT, m/z 227.2/181.1 for NT and m/z 230.2/184.2 for the internal standard, d (3)-NT. The assay was linear in the ranges 0.5-100 μg/mL for CT and 4-100 μg/mL for NT with corresponding limits of detection of 0.2 and 2 μg/mL. Intra- and inter-day precisions and accuracies were respectively <15% and ±15%. Matrix effects were also evaluated. The method is potentially useful for high throughput analysis although sensitivity needs to be improved before it can be applied in clinical research.