Additional file 1 of An area under the concentration–time curve threshold as a predictor of efficacy and nephrotoxicity for individualizing polymyxin B dosing in patients with carbapenem-resistant gram-negative bacteria

Additional file 1: Figure S1. Scatterplot of polymyxin B AUCss,24h versus dosage. AUCss,24h, the area under the plasma concentration-time curve across 24 hours at steady state. Figure S2. Scatterplot of polymyxin B AUCss,24h (a) and C0h (b) stratified for different stages of acute kidney injury. AUCss,24h, the area under the plasma concentration-time curve across 24 hours at steady state; C0h, trough concentration. Figure S3. Kaplan-Meier estimates of survival to 30 days after administration of polymyxin B. Stratified by AUCss,24h (a) and C0h (b). AUCss,24h, the area under the plasma concentration-time curve across 24 hours at steady state; C0h, trough concentration

Data_Sheet_1_Evaluation of polymyxin B AUC/MIC ratio for dose optimization in patients with carbapenem-resistant Klebsiella pneumoniae infection.docx

Polymyxin B has been used as a last-line therapy for the treatment of carbapenem-resistant gram-negative bacterial infection. The pharmacokinetic/pharmacodynamic index (AUC/MIC) of polymyxin B has not been clinically evaluated, given that the broth microdilution method for polymyxin susceptibility testing is rarely used in hospitals. This study analyzed data from 77 patients with carbapenem-resistant Klebsiella pneumoniae infections. Among the samples, 63 K. pneumoniae isolates had MIC values of 1.0 mg/L as measured by broth microdilution but 0.5 mg/L as measured using the Vitek 2 system. Polymyxin B AUC/MIC was significantly associated with clinical response (p = 0.002) but not with 30-day all-cause mortality (p = 0.054). With a target AUC/MIC value of 50, Monte Carlo simulations showed that a fixed dose of 100 mg/12 h and three weight-based regimens (1.25 mg/kg/12 h for 80 kg and 1.5 mg/kg/12 h for 70 kg/80 kg) achieved a cumulative fraction of response >90% regardless of renal function, but the risk of nephrotoxicity was high. For patients with carbapenem-resistant K. pneumoniae infections, the underestimation of polymyxin resistance in automated systems need to be taken into account when optimizing polymyxin B dosing based on pharmacokinetic/pharmacodynamic principles.</p

DataSheet3_Tetramethylpyrazine nitrone activates hypoxia-inducible factor and regulates iron homeostasis to improve renal anemia.PDF

Renal anemia is one of the most common complications of chronic kidney disease and diabetic kidney disease. Despite the progress made in recent years, there is still an urgent unmet clinical need for renal anemia treatment. In this research, we investigated the efficacy and mechanism of action of the novel tetramethylpyrazine nitrone (TBN). Animal models of anemia including the streptozotocin (STZ)-induced spontaneously hypertensive rats (SHR) and the cisplatin (CDDP)-induced C57BL/6J mice are established to study the TBN’s effects on expression of hypoxia-inducible factor and erythropoietin. To explore the mechanism of TBN’s therapeutic effect on renal anemia, cobalt chloride (CoCl2) is used in Hep3B/HepG2 cells to simulate a hypoxic environment. TBN is found to increase the expression of hypoxia-inducible factor HIF-1α and HIF-2α under hypoxic conditions and reverse the reduction of HIFs expression caused by saccharate ferric oxide (SFO). TBN also positively regulates the AMPK pathway. TBN stimulates nuclear transcription and translation of erythropoietin by enhancing the stability of HIF-1α expression. TBN has a significant regulatory effect on several major biomarkers of iron homeostasis, including ferritin, ferroportin (FPN), and divalent metal transporter-1 (DMT1). In conclusion, TBN regulates the AMPK/mTOR/4E-BP1/HIFs pathway, and activates the hypoxia-inducible factor and regulates iron homeostasis to improve renal anemia.</p

DataSheet1_Tetramethylpyrazine nitrone activates hypoxia-inducible factor and regulates iron homeostasis to improve renal anemia.PDF

Renal anemia is one of the most common complications of chronic kidney disease and diabetic kidney disease. Despite the progress made in recent years, there is still an urgent unmet clinical need for renal anemia treatment. In this research, we investigated the efficacy and mechanism of action of the novel tetramethylpyrazine nitrone (TBN). Animal models of anemia including the streptozotocin (STZ)-induced spontaneously hypertensive rats (SHR) and the cisplatin (CDDP)-induced C57BL/6J mice are established to study the TBN’s effects on expression of hypoxia-inducible factor and erythropoietin. To explore the mechanism of TBN’s therapeutic effect on renal anemia, cobalt chloride (CoCl2) is used in Hep3B/HepG2 cells to simulate a hypoxic environment. TBN is found to increase the expression of hypoxia-inducible factor HIF-1α and HIF-2α under hypoxic conditions and reverse the reduction of HIFs expression caused by saccharate ferric oxide (SFO). TBN also positively regulates the AMPK pathway. TBN stimulates nuclear transcription and translation of erythropoietin by enhancing the stability of HIF-1α expression. TBN has a significant regulatory effect on several major biomarkers of iron homeostasis, including ferritin, ferroportin (FPN), and divalent metal transporter-1 (DMT1). In conclusion, TBN regulates the AMPK/mTOR/4E-BP1/HIFs pathway, and activates the hypoxia-inducible factor and regulates iron homeostasis to improve renal anemia.</p

DataSheet2_Tetramethylpyrazine nitrone activates hypoxia-inducible factor and regulates iron homeostasis to improve renal anemia.PDF

Renal anemia is one of the most common complications of chronic kidney disease and diabetic kidney disease. Despite the progress made in recent years, there is still an urgent unmet clinical need for renal anemia treatment. In this research, we investigated the efficacy and mechanism of action of the novel tetramethylpyrazine nitrone (TBN). Animal models of anemia including the streptozotocin (STZ)-induced spontaneously hypertensive rats (SHR) and the cisplatin (CDDP)-induced C57BL/6J mice are established to study the TBN’s effects on expression of hypoxia-inducible factor and erythropoietin. To explore the mechanism of TBN’s therapeutic effect on renal anemia, cobalt chloride (CoCl2) is used in Hep3B/HepG2 cells to simulate a hypoxic environment. TBN is found to increase the expression of hypoxia-inducible factor HIF-1α and HIF-2α under hypoxic conditions and reverse the reduction of HIFs expression caused by saccharate ferric oxide (SFO). TBN also positively regulates the AMPK pathway. TBN stimulates nuclear transcription and translation of erythropoietin by enhancing the stability of HIF-1α expression. TBN has a significant regulatory effect on several major biomarkers of iron homeostasis, including ferritin, ferroportin (FPN), and divalent metal transporter-1 (DMT1). In conclusion, TBN regulates the AMPK/mTOR/4E-BP1/HIFs pathway, and activates the hypoxia-inducible factor and regulates iron homeostasis to improve renal anemia.</p

DataSheet1_Population Pharmacokinetics of Mycophenolic Acid in Renal Transplant Patients: A Comparison of the Early and Stable Posttransplant Stages.docx

Mycophenolic acid (MPA) is an antimetabolic immunosuppressive drug widely used in solid organ transplantation and autoimmune diseases. Pharmacokinetics (PK) of MPA demonstrates high inter- and intra-variability. The aim of this study was to compare the population PK properties of MPA in adult renal transplant patients in the early and stable post-transplant stages and to simulate an optimal dosing regimen for patients at different stages. A total of 51 patients in the early post-transplant period (1 week after surgery) and 48 patients in the stable state (5.5–10 years after surgery) were included in the study. In the two-compartment population PK model, CL/F (23.36 L/h vs. 10.25 L/h) and V/F (78.07 vs. 16.24 L) were significantly different between the two stages. The dose-adjusted area under the concentration time curve (AUCss,12h/dose) for patients in the early stage were significantly lower than those for patients in the stable state (40.83 ± 22.26 mg h/L vs. 77.86 ± 21.34 mg h/L; p ss,12h of 30–60 mg h/L. In addition, limited sampling strategies showed that two 4-point models (C0-C1-C2-C4 and C1-C2-C3-C6) performed well in predicting MPA exposure by both Bayesian estimate and regression equation and could be applied in clinical practice to assist therapeutic drug monitoring of MPA.</p

Table_1_A Prediction Model for Tacrolimus Daily Dose in Kidney Transplant Recipients With Machine Learning and Deep Learning Techniques.DOCX

Tacrolimus is a major immunosuppressor against post-transplant rejection in kidney transplant recipients. However, the narrow therapeutic index of tacrolimus and considerable variability among individuals are challenges for therapeutic outcomes. The aim of this study was to compare different machine learning and deep learning algorithms and establish individualized dose prediction models by using the best performing algorithm. Therefore, among the 10 commonly used algorithms we compared, the TabNet algorithm outperformed other algorithms with the highest R2 (0.824), the lowest prediction error [mean absolute error (MAE) 0.468, mean square error (MSE) 0.558, and root mean square error (RMSE) 0.745], and good performance of overestimated (5.29%) or underestimated dose percentage (8.52%). In the final prediction model, the last tacrolimus daily dose, the last tacrolimus therapeutic drug monitoring value, time after transplantation, hematocrit, serum creatinine, aspartate aminotransferase, weight, CYP3A5, body mass index, and uric acid were the most influential variables on tacrolimus daily dose. Our study provides a reference for the application of deep learning technique in tacrolimus dose estimation, and the TabNet model with desirable predictive performance is expected to be expanded and applied in future clinical practice.</p