Background Imidacloprid is a neonicotinoid insecticide that is widely used in agricultural production, with a high detection rate in human biological samples. Previous studies have shown a high correlation between imidacloprid exposure and liver injury, but the specific mechanism is still unknown. Objective To observe potential toxic effects of HepG2 cells and its perturbation of non-targeted metabolic profile after imidacloprid exposure, and to explore possible molecular mechanisms of hepatotoxicity of imidacloprid by analyzing invovlved biological processes and signaling pathways. Methods HepG2 cell suspension was prepared and seeded in a 96-well plate, which was divided into blank control group, dimethyl sulfoxide (DMSO) solvent control group and imidacloprid exposure groups with multiple concentrations. Each group was set with 5 parallel samples. The viability of HepG2 cells viability were determined after 8 h of exposure to different concentrationsof imidacloprid (1, 2.5, 5, 7.5, 10 mmol·L⁻¹), and the dose-effect relationship was analyzed. A proper concentration (3 mmol·L⁻¹ with 80% viability) was chosen for imidacloprid exposure, non-targeted metabolomic analysis was applied to the cultivated HepG2 cells using UHPLC-Q-TOF/MS technology, the differential metabolites between groups were screened, and the bioprocess and related signaling pathways of their enrichment were annotated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Results Compared to the other two groups, the survival rates of HepG2 cells in the imidacloprid exposure groups decreased. A survival rate of about 86% of HepG2 cells was found in HepG2 cells exposed to 2.5 mmol·L⁻¹ imidacloprid exposure. The non-targeted metabolomics studies showed that 61 metabolites were significantly affected in HepG2 cells after 3 mmol·L⁻¹ imidacloprid exposure, including creatine (variable importance in projection VIP=1.11, P<0.001), arginine (VIP=1.47, P=0.048), taurine (VIP=4.28, P=0.001), and α-D-glucose (VIP=1.90, P=0.006). The differential metabolites enriched in bioprocess and related signaling pathways were mainly directed to mTOR signaling pathways (P<0.001), arginine and proline metabolism (P=0.002), and galactose metabolism (P=0.015). Conclusion Imidacloprid exposure can significantly inhibit the survival rate of HepG2 cells, and interfere with the mTOR signaling pathway, arginine and proline metabolism, galactose metabolism, and so on.

Objective: To investigate the effect of perioperative fluid therapy on early postoperative pulmonary complication (PPC) after orthotopic liver transplantation (OLT). Methods: The clinical data of 132 patients who underwent OLT in the First Affiliated Hospital of Xi′an Jiaotong University from April 2016 to December 2017 were analyzed retrospectively. These patients included 96 males and 36 females, aged (47.3±9.6) years (range: 24-69 years). Based on the clinical manifestations, laboratory and imaging findings of patients in ICU and PPC occurrence within 7 days after OLT surgery, the patients were divided into 2 groups: non-PPC group and PPC group. Univariate and multivariate logistic regression analyses were used to evaluate the association between perioperative variables and PPC. The Kaplan-Meier method was used to estimate cumulative survival of recipients with or without PPC within 2-years. Results: During the follow-up, 11 patients (8.3%) died and 72 patients (54.5%) developed PPC after operation. There were 34 cases, 6 cases, 3 cases, 4 cases, 15 cases, 6 cases and 4 cases of only pleural effusion, only pulmonary edema, only pneumonia, pleural effusion with pneumonia, pleural effusion with pulmonary edema, pleural effusion with atelectasis, and pleural effusion with pneumonia and pneumonia in PPC, respectively. Univariate analysis showed that the preoperative factors (model for end-stage liver disease score), the intra-operative factors (duration of surgery, total infusion volume, total blood products) and the postoperative cumulative fluid balance within the first 24 h, 48 h, and 72 h were the prognosis factors of PPC (P<0.05). At least two out of the first three postoperative days with a fluid balance of ≤-500 ml was a protective factor. Using multivariate analysis by Logistic regression, only the red blood units >10 U (OR=3.55, 95% CI: 1.35-9.26, P=0.010) and the cumulative fluid intake >12 L (OR=2.98, 95% CI: 1.14-7.80, P=0.026) within the first 72 h after operation were independent prognosis factors of PPC after OLT. Kaplan-Meier analysis showed that the cumulative survival rate was lower in PPC group than that in non-PPC group (χ²=6.590, P=0.01). Conclusion Massive red blood cell transfusion and the cumulative fluid volume >12 L during perioperative 72 hours are independent prognosis factors of PPC after OLT.