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Objective Residue risk assessment of pesticides in celery was conducted to provide a scientific basis for agricultural regulation policies and working procedures. Methods Three hundred samples from eight main growing regions in China were collected and pesticide residue analyses were performed using GC–MS/MS and LC-MS/MS methods. Both chronic and acute intake risk of pesticides were assessed. Furthermore, intake risk of each detected pesticide was ranked according to a predefined ranking matrix. Results (1) Out of these 300 samples, 175 were revealed to contain one or more pesticide residues. Twenty-five pesticides were identified in total, out of which, carbofuran was found to exceed the maximum residue limit. (2) Chronic and acute intake risks were evaluated and lie in between 0 and 1.80 and between 0.05 and 28.0 for these twenty-five pesticides, respectively. (3) Intake risk of individual pesticide was ranked; five pesticides, including avermectin, triazophos, chlorpyrifos, dimethoate oxygen, and carbofuran posed the highest risks. Conclusion Pesticide residues were detected in more than 58% celery samples in our study. Most pesticides have a residue level lower than their maximum residue limit and pose low chronic and acute dietary intake risk. However, usage of some pesticides like carbofuran should be closely monitored and regulated in the future. [ABSTRACT FROM AUTHOR]

Background: The clinical utility of warfarin dose prediction algorithms remains controversial, our purpose is to evaluate the performance of warfarin dose prediction algorithms and the effects of clinical factors on warfarin dose in Chinese patients., Methods: Clinical data of 217 patients who received warfarin treatment were used to assess 6 warfarin dose prediction algorithms (OHNO, IWPC [International Warfarin Pharmacogenetics Consortium], HUANG, KIM, BRESS, and MIAO). The predicted dose (PD) was compared with the warfarin optimal dose (WOD, defined as the dose that maintains the international normalized ratio within the target range of 2.0-3.0). A multiple regression analysis with WOD as the dependent variable was performed to evaluate the effects of clinical factors on warfarin dose., Results: The mean absolute error analysis ranked the predictive accuracies of the algorithms as OHNO > IWPC > HUANG > KIM > BRESS > MIAO. Stratified analysis indicated that HUANG most accurately predicted that patients required lower WODs (≤3 mg/d), whereas OHNO was the most effective in predicting medium WODs (3-5 mg/d). KIM was effective in predicting high WODs (>5 mg/d). Multiple linear regression analysis showed that VKORC1 (rs9923231) and body mass index were significantly positively correlated with WOD, whereas concurrent atrial fibrillation status, CYP2C9*3 (rs1057910), and sex were significantly negatively correlated with WOD., Conclusions: In Chinese patients, OHNO should be given priority during the prediction and selection of warfarin dose. When using OHNO to predict warfarin dose (≤3 mg/d or >5 mg/d), HUANG or KIM algorithms can provide precise predictions. At the same time, physicians should pay close attention to clinical factors, such as VKORC1 (rs9923231), concurrent atrial fibrillation status, CYP2C9*3 (rs1057910), body mass index, and sex, to improve warfarin dose adjustment strategies in Chinese patients., Competing Interests: The authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)