Background Arsenic is an environmentally harmful substance that causes hepatic insulin resistance and liver damage, increasing the risk of type 2 diabetes mellitus. Objective To explore whether the insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) is involved in insulin resistance in HepG2 cells after arsenic exposure through the peroxisome-proliferator-activated receptor γ (PPAR-γ) / glucose transporter 4 (GLUT4) pathway. Methods Cell viability was determined using cell counting kit 8 (CCK8) and an appropriate NaAsO₂ infection dose was determined. A cellular arsenic exposure model of HepG2 cells was established by four concentrations of NaAsO₂ solution for 24 h (the experiment was divided into four groups: 0, 2, 4, and 8 μmol·L⁻¹); HepG2 cells were firstly treated with pcDNA3.1-IGF2BP2 and pcDNA3.1-NC respectively for 6 h, then with 8 μmol·L⁻¹ NaAsO₂ for 24 h to establish a IGF2BP2 overexpression cell model (the experiment was divided into 4 groups: control, NaAsO₂, NaAsO₂+pcDNA3.1-IGF2BP2, and NaAsO₂+pcDNA3.1-NC); finally the cells were subject to 100 nmol·L⁻¹ insulin stimulation for 30 min. Glycogen and glucose in HepG2 cells were determined by glycogen and glucose assay kits; mRNA expression levels of IGF2BP2 were measured by quantitative real-time PCR; protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in HepG2 were detected by Western blot (WB); and the binding of IGF2BP2 to PPAR-γ and PPAR-γ to GLUT4 was verified by co-immunoprecipitation (CO-IP) experiment. Results The results of CCK8 experiment showed a dose-effect relationship between NaAsO₂ concentration and cell viability. When the concentration of NaAsO₂ was ≥4 μmol·L⁻¹ , the cell viabilities were lower than that of the control group (P <0.05). With the increasing dose of NaAsO₂ infection, reduced glucose consumption and glycogen levels in HepG2 cells were found in the 2, 4, and 8 μmol·L⁻¹ NaAsO₂ treatment groups compared to the control group (P <0.05). The difference between the mRNA expression level of IGF2BP2 in the HepG2 cells treated with 4 or 8 μmol L⁻¹ NaAsO₂ and the control group was significant (P <0.05). In the IGF2BP2 overexpression cell model, compared with the control group, glucose consumption and glycogen levels were lowered in the NaAsO₂ group (P <0.05), the mRNA expression level of IGF2BP2 and the protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in the cell membrane were all decreased (P <0.05). Compared with the NaAsO₂ group, the glucose consumption and glycogen levels were increased in the NaAsO₂+pcDNA3.1-IGF2BP2 group (P <0.05), and the mRNA expression level of IGF2BP2 and the protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in the cell membrane were all increased (P <0.05). The results of CO-IP experiments showed that IGF2BP2 interacted with PPAR-γ as well as PPAR-γ with GLUT4 protein. Conclusion IGF2BP2 is involved in arsenic exposure-induced insulin resistance in HepG2 cells by acting on the PPAR-γ/GLUT4 pathway.

Objective: To screen and identify the key active molecules, signaling pathways, and therapeutic targets of Shuxuening (SXN) injection for treating liver cirrhosis (LC) and to evaluate its therapeutic potential using a mouse model. Methods: Target genes of SXN and LC were retrieved from public databases, and enrichment analysis was performed. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and hub genes were identified using Molecular Complex Detection (MCODE). LC was induced in rats and mice via intraperitoneal injections of diethylnitrosamine and carbon tetrachloride (CCl4) for 12 weeks. Starting at week 7, SXN was administered intraperitoneally to the mice in the treatment group. Serum and liver tissues of the mice were collected for the detection of indicators, pathological staining, and expression analysis of hub targets using quantitative real-time polymerase chain reaction (qRT-PCR). Results: We identified 368 overlapping genes (OLGs) between SXN and LC targets. These OLGs were subsequently used to build a PPI network and to screen for hub genes. Enrichment analysis showed that these genes were associated with cancer-related pathways, including phosphoinositide-3-kinase/Akt and mitogen-activated protein kinase signaling and various cellular processes, such as responses to chemicals and metabolic regulation. In vivo experiments demonstrated that SXN treatment significantly improved liver function and pathology in CCl4-induced LC mice by reducing inflammation and collagen deposition. Furthermore, qRT-PCR demonstrated that SXN regulated the expression of MAPK8, AR and CASP3 in the livers of LC mice. Conclusion This study highlighted the therapeutic effects of SXN in alleviating LC using both bioinformatics and experimental methods. The observed effect was associated with modulation of hub gene expression, particularly MAPK8, and CASP3.

Background Arsenic exposure is a common and important environmental and occupational hazardous factor in China, and arsenic-induced insulin resistance (IR) has attracted widespread attention as a negative health outcome to the population. Objective To explore part of the mechanism of hepatic IR induced by arsenic exposure based on the peroxisome proliferators-activated receptors γ (PPARγ)/ glucose transporter 4 (GLUT4) pathway, and to investigate potential effects of Ginkgo biloba extract (GBE) on hepatic IR induced by arsenic exposure and associated mechanism of action. Methods The target of drug action was predicted by network pharmacology and verified by in vivo and in vitro experiments. In vivo experiments: 48 SPF C57BL/6J male mice were divided into 4 groups, including control group, 50 mg·L⁻¹ NaAsO₂ model group (NaAsO₂), 50 mg·L⁻¹ NaAsO₂+10 mg·kg⁻¹ GBE intervene group (NaAsO₂+GBE), and 10 mg·kg⁻¹ GBE group (GBE), 12 mice in each group. The animals were given free access to purified water containing 50 mg·L⁻¹ NaAsO₂, or given intraperitoneal injection of normal saline containing 10 mg·kg⁻¹ GBE once per week. After 6 months of exposure, blood glucose detection, intraperitoneal glucose tolerance test (IPGTT), and insulin tolerance test (ITT) were performed. Serum and liver tissues were collected after the mice were neutralized, liver histopathological sections were obtained, serum insulin levels, liver tissue glycogen content, glucose content were detected by enzyme linked immunosorbent assay (ELISA), and the expression of PPARγ and GLUT4 proteins was detected by Western blot (WB). In vitro experiments: HepG2 cells were divided into 4 groups, including control group, 8 μmol·L⁻¹ NaAsO₂ group (NaAsO₂), 8 μmol·L⁻¹ NaAsO₂ + 200 mg·L⁻¹ GBE intervene group (NaAsO₂+GBE), and 200 mg·L⁻¹ GBE group (GBE). The levels of glycogen and glucose were detected by ELISA, and the expression of PPARγ and GLUT4 proteins was detected by WB. Results A strong binding effect between GBE and PPARγ was revealed by network pharmacology. In in vivo experiments, the NaAsO₂ group exhibited an elevated blood glucose compared to the control group, and the NaAsO₂+GBE group showed a decreased blood glucose compared to the NaAsO₂ group (P<0.01). The histopathological sections indicated severe liver structural damage in the arsenic exposure groups (NaAsO₂ group and NaAsO₂+GBE group), with varying staining intensity, partial liver cell necrosis, and diffuse red blood cell appearance. Both results of in vitro and in vivo experiments showed a decrease in glycogen synthesis and glucose uptake in the NaAsO₂ groups compared to the control groups, which was alleviated in the NaAsO₂+GBE group (P<0.01). The results of WB revealed inhibited PPARγ expression and reduced GLUT4 levels on the cell membrane, and all these changes were alleviated in the NaAsO₂+GBE group (P<0.01). Conclusion This study findings suggest that GBE antagonizes arsenic exposure-induced hepatic IR by regulating the PPARγ/GLUT4 pathway, indicating that GBE has a protective effect on arsenic exposure-induced hepatic IR, and PPARγ may be a potential therapeutic target for arsenic exposure-induced hepatic IR.

Objective To analyze adverse drug event(ADE)signals associated with exenatide based on data from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS),and to provide insights for rational medication use in clinical settings.Methods ADE reports of exenatide as the primary suspected drug were obtained by collecting the data of FAERS database from the first quarter 2014 to the second quarter 2024.ADE signals were analyzed by joint reporting odds ratio(ROR)method,proportional reporting odds ratio(PRR)method,Bayesian confidence interval progressive neural network(BCPNN)method and multi-item gamma Poisson shrinker(MGPS)method.Results After data cleaning,118 745 reports of exenatide-related ADEs were collected.These ADEs spanned 14 system-organ classes and involved 185 preferred terms.Commonly reported ADEs included reactions at the injection site,hypoglycemia,reduced appetite,and cholelithiasis.Severe ADEs were primarily cases of acute pancreatitis,in consistent with the drug's labeling.Moreover,the instructions did not record ADE signals of pancreatic cancer,thyroiditis,and reduced frustration tolerance.Conclusion Prescription of the exenatide should be vigilant about the signals not listed on the product labeling,such as pancreatic cancer,thyroid cancer,and decreased frustration tolerance,to improve the safety of medication use in patients.

Objective To mine adverse drug event(ADE)signals of pioglitazone,and to provide references for the safe clinical use of the medication.Methods The reporting odds ratio(ROR)method and the Bayesian confidence propagation neural network(BCPNN)method were utilized to analyze pioglitazone ADE reports from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)database,spanning from the first quarter of 2013 to the second quarter of 2024.Results After data cleaning,a total of 16 904 pioglitazone ADE reports were retrieved.The ADE reports primarily involved individuals over the age of 45,with a male predominance,and were mainly reported from the United States.After screening,180 ADE signals were identified,affecting 27 system-organ classes(SOC).Out of these,34 ADE signals were classified as medium to high risk,with 9 ADE signals not mentioned in the product labeling,including ureteral cancer,urethral cancer,gallbladder tumors,malignant tumors of the renal pelvis,pericardial tamponade,left ventricular dysfunction,pulmonary edema,cystitis,and somniloquy.Conclusion In addition to closely monitoring weight gain,systemic edema,and heart failure,clinical attention should be given to left ventricular dysfunction,pulmonary edema,cystitis,and pericardial tamponade ADEs that are not mentioned in the instructions,to ensure the safety of pioglitazone use in clinical practice.

Objective To analyze adverse drug event(ADE)signals associated with exenatide based on data from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS),and to provide insights for rational medication use in clinical settings.Methods ADE reports of exenatide as the primary suspected drug were obtained by collecting the data of FAERS database from the first quarter 2014 to the second quarter 2024.ADE signals were analyzed by joint reporting odds ratio(ROR)method,proportional reporting odds ratio(PRR)method,Bayesian confidence interval progressive neural network(BCPNN)method and multi-item gamma Poisson shrinker(MGPS)method.Results After data cleaning,118 745 reports of exenatide-related ADEs were collected.These ADEs spanned 14 system-organ classes and involved 185 preferred terms.Commonly reported ADEs included reactions at the injection site,hypoglycemia,reduced appetite,and cholelithiasis.Severe ADEs were primarily cases of acute pancreatitis,in consistent with the drug's labeling.Moreover,the instructions did not record ADE signals of pancreatic cancer,thyroiditis,and reduced frustration tolerance.Conclusion Prescription of the exenatide should be vigilant about the signals not listed on the product labeling,such as pancreatic cancer,thyroid cancer,and decreased frustration tolerance,to improve the safety of medication use in patients.

Objective To mine adverse drug event(ADE)signals of pioglitazone,and to provide references for the safe clinical use of the medication.Methods The reporting odds ratio(ROR)method and the Bayesian confidence propagation neural network(BCPNN)method were utilized to analyze pioglitazone ADE reports from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)database,spanning from the first quarter of 2013 to the second quarter of 2024.Results After data cleaning,a total of 16 904 pioglitazone ADE reports were retrieved.The ADE reports primarily involved individuals over the age of 45,with a male predominance,and were mainly reported from the United States.After screening,180 ADE signals were identified,affecting 27 system-organ classes(SOC).Out of these,34 ADE signals were classified as medium to high risk,with 9 ADE signals not mentioned in the product labeling,including ureteral cancer,urethral cancer,gallbladder tumors,malignant tumors of the renal pelvis,pericardial tamponade,left ventricular dysfunction,pulmonary edema,cystitis,and somniloquy.Conclusion In addition to closely monitoring weight gain,systemic edema,and heart failure,clinical attention should be given to left ventricular dysfunction,pulmonary edema,cystitis,and pericardial tamponade ADEs that are not mentioned in the instructions,to ensure the safety of pioglitazone use in clinical practice.

Objective To investigate post-marketing adverse drug event(ADE)signals associated with lixisenatide,and to provide guidance for safe clinical use.Methods The ADE reporting data of lixisenatide ADE were mined and the signals were detected from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)database from the first quarter 2013 to the second quarter 2024 using the reporting odds ratio(ROR)method and Bayesian confidence propagation neural network(BCPNN)method.Results After data cleaning,a total of 5 162 ADE reports with lixisenatide as the primary suspected drug were collected.The 85 ADE signals identified by the two statistical analysis methods,affected 14 system-organ classes(SOC).They were primarily concentrated in injuries,poisonings,and procedural complications(25.88％),various examinations(14.12％),systemic diseases and reactions at administration sites(14.12％),gastrointestinal diseases(9.41％),and various neurological diseases(5.88％).There were 28 ADE signals such as pancreatitis,visual impairment,and color blindness,that were not included in the drug instructions.Conclusion In addition to monitoring for common ADE associated with GLP-1 receptor agonists such as hypoglycemia,gastrointestinal,and neurological effects,clinicians should also be vigilant for underlying ADE like pancreatic-related diseases,eye toxicity reaction when using lixisenatide to ensure safe and rational medication use.

bjective To mine signals of post-marketing adverse drug events(ADEs)associated with dapagliflozin,and to provide insights for safe medication in clinical settings.Methods Data on ADEs related to dapagliflozin from U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)were collected from the first quarter of 2013 to the third quarter of 2024.The analyses involved data mining and signal monitoring using disproportionality analysis techniques including the reporting odds ratio(ROR)method,Medicines and Healthcare Products Regulatory Agency(MHRA)method,Bayesian confidence propagation neural network(BCPNN)method,and multi-item gamma Poisson shrinker(MGPS)method.Results After data cleaning,a total of 55 832 qualified dapagliflozin case reports were obtained,involving 25 090 patients,with a slightly higher percentage of males(44.99％)than females(41.18％).The predominant age group was 45 to 64 years(20.78％).A total of 379 ADE signals were detected across 22 system-organ classes(SOC).The ADEs of dapagliflozin were mainly concentrated in the SOC such as infections and infestations,general disorders and administration sites conditions,and metabolism and nutrition disorders,aligning with information provided in the drug instructions.Additionally,the ADE signals were not documented in drug inserts such as scrotal gangrene,periperineal cellulitis,scrotal abscess,hyperglycemia,ketonuria,and pancreatitis.Conclusion When clinically using dapagliflozin,it is essential to conduct a thorough medication assessment.In addition to closely monitoring diabetes ketoacidosis,fungal infection,and acute renal injury.The latent ADEs that are not mentioned in the instructions to should be noticed ensure safe medication.

Objective To mine the real-world risk signals associated with saxagliptin-related adverse drug event(ADE),and to provide insights for evidence-based use of the drug in clinical practice.Methods Data on ADE related to saxagliptin from U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)were collected from the first quarter of 2013 to the third quarter of 2024,and analyzed using the reporting odds ratio(ROR)and Bayesian confidence propagation neural network(BCPNN)techniques.Results After data cleaning,the study analyzed 2 036 qualified case reports from patients who were using saxagliptin,uncovering 4 497 adverse events and identifying 131 adverse event signals across 19 system-organ classes(SOCs),including cardiac organ system diseases(20.61％),various types of investigations(10.69％),and gastrointestinal tract diseases(13.74％).Among them,heart failure,pancreatitis,pancreatic cancer,and hypoglycaemic coma were high-intensity signals.Conclusion In clinical practice,the indications for saxagliptin should be strictly managed.It is advisable to avoid using saxagliptin as monotherapy in patients with a history of heart failure or in patients at elevated risk for arteriosclerotic cardiovascular disease.Continuous monitoring of essential organ functions,especially cardiac and pancreatic,is essential throughout the course of treatment to ensure the safety of the medication.