Matrix Vesicle–Mediated Mineralization and Potential Applications

Hard tissues, including the bones and teeth, are a fundamental part of the body, and their formation and homeostasis are critically regulated by matrix vesicle–mediated mineralization. Matrix vesicles have been studied for 50 y since they were first observed using electron microscopy. However, research progress has been hampered by various technical barriers. Recently, there have been great advancements in our understanding of the intracellular biosynthesis of matrix vesicles. Mitochondria and lysosomes are now considered key players in matrix vesicle formation. The involvement of mitophagy, mitochondrial-derived vesicles, and mitochondria–lysosome interaction have been suggested as potential detailed mechanisms of the intracellular pathway of matrix vesicles. Their main secretion pathway may be exocytosis, in addition to the traditionally understood mechanism of budding from the outer plasma membrane. This basic knowledge of matrix vesicles should be strengthened by novel nano-level microscopic technologies, together with basic cell biologies, such as autophagy and interorganelle interactions. In the field of tissue regeneration, extracellular vesicles such as exosomes are gaining interest as promising tools in cell-free bone and periodontal regenerative therapy. Matrix vesicles, which are recognized as a special type of extracellular vesicles, could be another potential alternative. In this review, we outline the recent significant progress in the process of matrix vesicle–mediated mineralization and the potential clinical applications of matrix vesicles for tissue regeneration.Iwayama T., Bhongsatiern P., Takedachi M., et al., Matrix Vesicle–Mediated Mineralization and Potential Applications, Journal of Dental Research 2022;220345221103145. Copyright © 2022 International Association for Dental Research and American Association for Dental, Oral, and Craniofacial Research. DOI:10.1177/00220345221103145

Neonatal Population Pharmacokinetics and Pharmacodynamics Modeling of Vancomycin to Simulate Target Exposure Attainment

ACKGROUND Vancomycin is bactericidal against gram-positive organisms, including coagulase (+) and coagulase (-) Staphylococci. Several professional societies have recommended a ratio of area under the curve to minimum inhibitory concentration (AUC:MIC) \u3e400, which has been associated with optimal adult outcomes. The objectives of this neonatal study were: 1) to construct a population PK/PD model for vancomycin serum concentrations and 2) to simulate the proportion who achieved an AUC:MIC \u3e400. METHODS Population PK/PD modeling using NONMEM was conducted. Neonatal data (1 vancomycin serum concentration(s) from 2006-2011 were obtained from electronic medical records. These data were not complete before October 1, 2012. RESULTS A one compartment, first order elimination model evaluated 1081 vancomycin concentrations from 222 neonates. Estimated CL was 0.107 L/hr/kg and Vd was 1.10 L/kg. Coagulase (+) Staphylococci MIC values ranged from 0.5-2 mg/L and coagulase (-) Staphylococci MIC values ranged from 0.5-4 mg/L. Doses of 40 and 60 mg/kg/day infrequently achieved the AUC:MIC target of \u3e400. CONCLUSION Conventional neonatal vancomycin dosing regimens infrequently achieve an adult PK/PD target associated with optimal bactericidal activity. Further research is needed to evaluate the clinical efficacy of this target in neonates

Neonatal Population Pharmacokinetics and Pharmacodynamics Modeling of Vancomycin to Simulate Target Exposure Attainment

ACKGROUND Vancomycin is bactericidal against gram-positive organisms, including coagulase (+) and coagulase (-) Staphylococci. Several professional societies have recommended a ratio of area under the curve to minimum inhibitory concentration (AUC:MIC) \u3e400, which has been associated with optimal adult outcomes. The objectives of this neonatal study were: 1) to construct a population PK/PD model for vancomycin serum concentrations and 2) to simulate the proportion who achieved an AUC:MIC \u3e400. METHODS Population PK/PD modeling using NONMEM was conducted. Neonatal data (1 vancomycin serum concentration(s) from 2006-2011 were obtained from electronic medical records. These data were not complete before October 1, 2012. RESULTS A one compartment, first order elimination model evaluated 1081 vancomycin concentrations from 222 neonates. Estimated CL was 0.107 L/hr/kg and Vd was 1.10 L/kg. Coagulase (+) Staphylococci MIC values ranged from 0.5-2 mg/L and coagulase (-) Staphylococci MIC values ranged from 0.5-4 mg/L. Doses of 40 and 60 mg/kg/day infrequently achieved the AUC:MIC target of \u3e400. CONCLUSION Conventional neonatal vancomycin dosing regimens infrequently achieve an adult PK/PD target associated with optimal bactericidal activity. Further research is needed to evaluate the clinical efficacy of this target in neonates

Predictive Performance of a Vancomycin Population Pharmacokinetic Model in Neonates

Introduction The pharmacokinetics of vancomycin are highly variable among neonates, which makes dosing challenging in this population. However, adequate drug exposure is critical, especially when treating methicillin-resistant Staphylococcus aureus (MRSA) infections. Utilization of population pharmacokinetic models and Bayesian methods offers the potential for developing individualized therapeutic approaches. To meet this need, a neonatal vancomycin population pharmacokinetic model was recently published. The current study sought to externally evaluate the predictive performance and generalizability of this model. Methods A retrospective chart review of neonates who received vancomycin and had ≥1 peak and ≥1 trough concentrations at five Intermountain Healthcare neonatal intensive care units from 2006 to 2013 was performed and served as the external validation cohort. The published population pharmacokinetic model was implemented in NONMEM 7.2 with the structural and variance parameter values set equal to the estimates reported previously. The model was then used to predict the first peak and trough concentration for each neonate in the validation cohort and the model prediction error and absolute prediction error were calculated. Normalized prediction distribution errors (NPDE) were also evaluated. Results A total of 243 neonates were studied with a median postmenstrual age of 33 (range: 23–54) weeks and a median weight of 1.6 (range: 0.4–6.8) kg. The model predicted the observed vancomycin concentrations with reasonable precision. For all vancomycin concentrations, the median prediction error was −0.8 (95% CI: −1.4 to −0.4) mg/L and the median absolute prediction error was 3.0 (95% CI: 2.7–3.5) mg/L. No trends in NPDE across weight, postmenstrual age, serum creatinine, or time after dose were observed. Conclusion An evaluation of a recently published neonatal vancomycin population pharmacokinetic model in a large external dataset supported the predictive performance and generalizability of the model. This model may be useful in evaluating neonatal vancomycin dosing regimens and estimating the extent of drug exposure

Genetics of Clusterin Isoform Expression and Alzheimer’s Disease Risk

The minor allele of rs11136000 within CLU is strongly associated with reduced Alzheimer’s disease (AD) risk. The mechanism underlying this association is unclear. Here, we report that CLU1 and CLU2 are the two primary CLU isoforms in human brain; CLU1 and CLU2 share exons 2–9 but differ in exon 1 and proximal promoters. The expression of both CLU1 and CLU2 was increased in individuals with significant AD neuropathology. However, only CLU1 was associated with the rs11136000 genotype, with the minor ‘‘protective’ ’ rs11136000T allele being associated with increased CLU1 expression. Since CLU1 and CLU2 are predicted to encode intracellular and secreted proteins, respectively, we compared their expression; for both CLU1 and CLU2 transfected cells, clusterin is present in the secretory pathway, accumulates in the extracellular media, and is similar in size to clusterin in human brain. Overall, we interpret these results as indicating that the AD-protective minor rs11136000T allele is associated with increased CLU1 expression. Since CLU1 and CLU2 appear to produce similar proteins and are increased in AD, the AD-protection afforded by the rs11136000T allele may reflect increased soluble clusterin throughout life

An Improved Vancomycin Dosing Strategy in Neonates Using Population Pharmacokinetics and Simulations to Achieve Pharmacodynamic Target Attainment

BACKGROUND Vancomycin is a first-line therapy for neonatal MRSA. Two dosing strategies, postmenstrual age (PMA)-based and serum creatinine (SCR)-based are currently used. This study aimed to evaluate pharmacodynamic (PD) target attainment rates using current dosing regimens, and derive an optimal vancomycin dosing strategy for neonates. METHODS Data were collected for neonates with ≥1 vancomycin serum concentrations. Completed data were not available before September 19, 2013. A population PK model was constructed using NONMEM 7.2. Dosing simulations were performed in MATLAB R2010a. The PD target that best predicts clinical success was defined as a ratio of the area under the curve to the minimum inhibitory concentration (AUC/MIC) ≥ 400. RESULTS A one-compartment model with first-order elimination was developed. Overall, 1,458 serum concentrations were obtained from 515 patients. The final model established clearance (CL) = 0.042 • (CWT/1.5)^0.72 • (1/ SCR) • (PMA/33) and volume of distribution (V) = 1.04 • (CWT/1.5)^1.06. In simulations, \u3e90% of patients achieved the AUC/MIC target for both current dosing regimens at an MIC 0.5 mg/L. At MICs of 1 and 2, 72% and 12% of the simulated SCR-based dosing profiles achieved the AUC/ MIC target, which was higher than the rates achieved with PMA-based dosing. An improved dosing strategy was developed that featured increased SCR-based doses and dosing intervals from 7.5-30 to 10-40 mg/kg/day. This strategy achieved the AUC/MIC target in 98%, 86%, and 25% of simulations at MICs of 0.5, 1, and 2, respectively. CONCLUSION For neonates, a dosing strategy that incorporates weight and SCR is predicted to achieve the PD target that is predictive of successful therapy in \u3e80% of patients at MICs ≤1 mg/L. Vancomycin is not recommended for isolates with MICs≥2 mg/L

An Improved Vancomycin Dosing Strategy in Neonates Using Population Pharmacokinetics and Simulations to Achieve Pharmacodynamic Target Attainment

BACKGROUND Vancomycin is a first-line therapy for neonatal MRSA. Two dosing strategies, postmenstrual age (PMA)-based and serum creatinine (SCR)-based are currently used. This study aimed to evaluate pharmacodynamic (PD) target attainment rates using current dosing regimens, and derive an optimal vancomycin dosing strategy for neonates. METHODS Data were collected for neonates with ≥1 vancomycin serum concentrations. Completed data were not available before September 19, 2013. A population PK model was constructed using NONMEM 7.2. Dosing simulations were performed in MATLAB R2010a. The PD target that best predicts clinical success was defined as a ratio of the area under the curve to the minimum inhibitory concentration (AUC/MIC) ≥ 400. RESULTS A one-compartment model with first-order elimination was developed. Overall, 1,458 serum concentrations were obtained from 515 patients. The final model established clearance (CL) = 0.042 • (CWT/1.5)^0.72 • (1/ SCR) • (PMA/33) and volume of distribution (V) = 1.04 • (CWT/1.5)^1.06. In simulations, \u3e90% of patients achieved the AUC/MIC target for both current dosing regimens at an MIC 0.5 mg/L. At MICs of 1 and 2, 72% and 12% of the simulated SCR-based dosing profiles achieved the AUC/ MIC target, which was higher than the rates achieved with PMA-based dosing. An improved dosing strategy was developed that featured increased SCR-based doses and dosing intervals from 7.5-30 to 10-40 mg/kg/day. This strategy achieved the AUC/MIC target in 98%, 86%, and 25% of simulations at MICs of 0.5, 1, and 2, respectively. CONCLUSION For neonates, a dosing strategy that incorporates weight and SCR is predicted to achieve the PD target that is predictive of successful therapy in \u3e80% of patients at MICs ≤1 mg/L. Vancomycin is not recommended for isolates with MICs≥2 mg/L

Renal Function Descriptors in Neonates: Which Creatinine‐Based Equation Best Describes Vancomycin Clearance?

BACKGROUND: Glomerular function develops rapidly in the first month of life. Several estimated glomerular filtration rate (eGFR) equations have been applied to estimate the rate of clearance (CL) of renally-excreted drugs. This study aimed to compare eGFR with reference values and analyze their influence on vancomycin CL. Data were collected for neonates (3-30 days postnatal age; PNA) with ≥ 1 vancomycin serum concentration(s). Complete data could not be analyzed before September 8, 2014. A population PK model was constructed using NONMEM 7.2. eGFR was calculated using creatinine (Cr)-based equations from modified Schwartz (1), Leger (2), Pottel (3), and British Columbia’s Children’s Hospital (4) equations. Reference eGFR values were derived from Cr. RESULTS: A total of 528 neonates contributed vancomycin 6121 concentrations. The median gestational age (GA) was 29 (IQR 25-36) weeks. Schwartz equation provided comparable results with reference values in preterm neonates, i.e. 24.4 (20.6-26.6) mL/min/1.73 m2 at 14 days PNA in 29 weeks GA infants. In contrast, elevated eGFR were obtained: 46.7+/- 18.2 (2) 52.8 +/- (3), and 44.9 +/-17.6 (4) mL/min/1.7 m2. Theser were close to the values using equations based on cystatin C. Vancomycin PK was analyzed using a one-compartment model with first-order elimination. Weight, postmenstrual age, and eGFR were significant covariated for CL. Between-subject variability decreased by 38.3% with the inclusion of eGRF alone. Although Schwartz equation contributed the best fit, estimated CL (0.13 =/- 0.1 L/hr/kg) across eGRF equations were in reasonable agreement with literature values. Conclusion: Inclusion of eGFR can be used to estimate vancomycin C. The modified Schwartz equation was the best predictor of vancomycin CL in this neonatal population