Population pharmacokinetics of cyclosporine in Chinese children receiving hematopoietic stem cell transplantation.

Cyclosporine (CsA) is characterized by a narrow therapeutic window and high interindividual pharmacokinetic variability, particularly in juvenile patients. The aims of this study were to build a population pharmacokinetic model of CsA in Chinese children with hematopathy who received allogeneic hematopoietic stem cell transplantation (allo-HSCT) and to identify covariates affecting CsA pharmacokinetics. A total of 86 Chinese children aged 8.4 ± 3.8 years (range 1.1-16.8 years) who received allo-HSCT were enrolled. Whole blood samples were collected before allo-HSCT. Genotyping was performed using an Agena MassARRAY system. A total of 1010 trough plasma concentration values of CsA and clinical data were collected. The population pharmacokinetic model of CsA was constructed using nonlinear mixed-effects modeling (NONMEM) software. The stability and performance of the final model were validated using bootstrapping and normalized prediction distribution errors. We showed that a one-compartment model with first-order elimination adequately described the pharmacokinetics of CsA. The typical values for clearance (CL) and volume of distribution (V) were 42.3 L/h and 3100 L, respectively. Body weight, postoperative days, CYP3A4*1 G genotype, estimated glomerular filtration rate and coadministration of triazole antifungal drugs were identified as significant covariates for CL. Weight and postoperative days were significant covariates for the V of CsA. Our model can be adopted to optimize the CsA dosing regimen for Chinese children with hematopathy receiving allo-HSCT.

Accuracy of iohexol plasma clearance for GFR-determination: a comparison between single and dual sampling.

BACKGROUND: Current guidelines regarding plasma-sampling techniques for glomerular filtration rate (GFR) determination are inconsistent. Single-sample methods are commonly believed not to be precise enough to meet clinical demands. The present study compared the agreement between single- and dual- plasma sampling methods with a three-point plasma clearance of iohexol. METHODS: A total of 46 healthy volunteers and 124 chronic kidney disease (CKD) patients with varying degrees of renal dysfunction received 5 ml iohexol (300 mgI/ml) i.v. and plasma samples were drawn at 2-, 3- and 4-h post-injection. Plasma-iodine concentrations were detected by high-performance liquid chromatography (HPLC). RESULTS: Bias was similar among single-plasma sampling methods (SPSM) and dual-plasma sampling methods (DPSM). The best correlation was obtained from the 2- and 4-h DPSM (concordance correlation coefficient [CCC]: 0.9988) with none of the estimates differed by more than 30% from the reference GFR and only one (0.06%) estimate differed by more than 10% (P30, 100%; P10, 99.4%). SPSM using samples around 3- or 4-h demonstrated acceptable accuracy at a GFR level of ≥60 ml/min/1.73m2 (P30 = 100% and P10 > 75% for both measurements). CONCLUSION: 4-h SPSM is advantageous in clinical practice in subjects with GFR ≥ 60 ml/min/1.73m2. For patients with an expected GFR < 60 ml/min/1.73m2, a prolonged sampling time is more reliable.

Enzymatic synthesis of novel phloretin glucosides.

A UDP-glycosyltransferase from Bacillus licheniformis was exploited for the glycosylation of phloretin. The in vitro glycosylation reaction confirmed the production of five phloretin glucosides, including three novel glucosides. Consequently, we demonstrated the application of the same glycosyltransferase for the efficient whole-cell biocatalysis of phloretin in engineered Escherichia coli.

Improving Dental Implant Outcomes: CNN-Based System Accurately Measures Degree of Peri-Implantitis Damage on Periapical Film.

As the popularity of dental implants continues to grow at a rate of about 14% per year, so do the risks associated with the procedure. Complications such as sinusitis and nerve damage are not uncommon, and inadequate cleaning can lead to peri-implantitis around the implant, jeopardizing its stability and potentially necessitating retreatment. To address this issue, this research proposes a new system for evaluating the degree of periodontal damage around implants using Periapical film (PA). The system utilizes two Convolutional Neural Networks (CNN) models to accurately detect the location of the implant and assess the extent of damage caused by peri-implantitis. One of the CNN models is designed to determine the location of the implant in the PA with an accuracy of up to 89.31%, while the other model is responsible for assessing the degree of Peri-implantitis damage around the implant, achieving an accuracy of 90.45%. The system combines image cropping based on position information obtained from the first CNN with image enhancement techniques such as Histogram Equalization and Adaptive Histogram Equalization (AHE) to improve the visibility of the implant and gums. The result is a more accurate assessment of whether peri-implantitis has eroded to the first thread, a critical indicator of implant stability. To ensure the ethical and regulatory standards of our research, this proposal has been certified by the Institutional Review Board (IRB) under number 202102023B0C503. With no existing technology to evaluate Peri-implantitis damage around dental implants, this CNN-based system has the potential to revolutionize implant dentistry and improve patient outcomes.