Emissions of electric vehicle charging in future scenarios: The effects of time of charging

Electrification of transport is an important option to reduce greenhouse gas emissions. Although many studies have analyzed emission implications of electric vehicle charging, time-specific emission effects of charging are inadequately understood. Here, we combine climate protection scenarios for Europe for the year 2050, detailed power system simulation at hourly time steps, and life cycle assessment of electricity in order to explore the influence of time on the greenhouse gas emissions associated with electric vehicle charging for representative days. We consider both average and short-term marginal emissions. We find that the mix of electricity generation technologies, and thus, also the emissions of charging, vary appreciably across the 24-h day. In our estimates for Europe for 2050, an assumed day-charging regime yields one-third-to-one-half lower average emissions than an assumed night-charging regime. This is owing to high fractions of solar PV in the electricity mix during daytime and more reliance on natural gas electricity in the late evening and night. The effect is stronger during summer months than during winter months, with day charging causing one-half-to-two-thirds lower emissions than night charging during summer. Also, when short-term marginal electricity is assumed, emissions tend to be lower with day charging because of contributions from nuclear electricity during the day. However, the results for short-term marginal electricity have high uncertainty. Overall, our results suggest a need for electric vehicle charging policies and emission assessments to take into consideration variations in electricity mixes and time profiles of vehicle charging over the 24-h day

Pre- and postnatal maturation are important for fentanyl exposure in preterm and term newborns: a pooled population pharmacokinetic study

Fentanyl is an opioid commonly used to prevent and treat severe pain in neonates; however, its use is off label and mostly based on bodyweight. Given the limited pharmacokinetic information across the entire neonatal age range, we characterized the pharmacokinetics of fentanyl across preterm and term neonates to individualize dosing. We pooled data from two previous studies on 164 newborns with a median gestational age of 29.0 weeks (range 23.9-42.3), birthweight of 1055 g (range 390-4245), and postnatal age (PNA) of 1 day (range 0-68). In total, 673 plasma samples upon bolus dosing (69 patients; median dose 2.1 μg/kg, median 2 boluses per patient) or continuous infusions (95 patients; median dose 1.1 μg/kg/h for 30 h) with and without boluses were used for population pharmacokinetic modeling in NONMEM® 7.4. Clearance in neonates with birthweight of 2000 and 3000 g was 2.8- and 5.0-fold the clearance in a neonate with birthweight of 1000 g, respectively. Fentanyl clearance at PNA of 7, 14, and 21 days was 2.7-fold, 3.8-fold, and 4.6-fold the clearance at 1 day, respectively. Bodyweight-based dosing resulted in large differences in fentanyl concentrations. Depending on PNA and birthweight, fentanyl concentrations increased slowly after the start of therapy for both intermittent boluses and continuous infusion and reached a maximum concentration at 12-48 h. As both prenatal and postnatal maturation are important for fentanyl exposure, we propose a birthweight- and PNA-based dosage regimen. To provide rapid analgesia in the first 24 h of treatment, additional loading doses need to be considered.Pharmacolog

Prediction of glomerular filtration rate maturation across preterm and term neonates and young infants using inulin as marker

Describing glomerular filtration rate (GFR) maturation across the heterogeneous population of preterm and term neonates and infants is important to predict the clearance of renally cleared drugs. This study aims to describe the GFR maturation in (pre)term neonates and young infants (PNA < 90 days) using individual inulin clearance data (CLinulin). To this end, published GFR maturation models were evaluated by comparing their predicted GFR with CLinulin retrieved from literature. The best model was subsequently optimized in NONMEM V7.43 to better fit the CLinulin values. Our study evaluated seven models and collected 381 individual CLinulin values from 333 subjects with median (range) birthweight (BWb) 1880 g (580-4950), gestational age (GA) 34 weeks (25-43), current weight (CW) 1890 g (480-6200), postnatal age (PNA) 3 days (0-75), and CLinulin 2.20 ml/min (0.43-17.90). The De Cock 2014 model (covariates: BWb and PNA) performed the best in predicting CLinulin followed by the Rhodin 2009 model (covariates: CW and postmenstrual age). The final optimized model shows that GFR at birth is determined by BWb, thereafter the maturation rate of GFR is dependent on PNA and GA, with a higher GA showing an overall faster maturation. To conclude, using individual CLinulin data, we found that a model for neonatal GFR requires a distinction between prenatal maturation quantified by BWb and postnatal maturation. To capture postnatal GFR maturation in (pre)term neonates and young infants, we developed an optimized model in which PNA-related maturation was dependent on GA.Pharmacolog

Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research

Late-onset neonatal sepsis (LONS) remains an important threat to the health of preterm neonates in the neonatal intensive care unit. Strategies to optimize care for preterm neonates with LONS are likely to improve survival and long-term neurocognitive outcomes. However, many important questions on how to improve the prevention, early detection, and therapy for LONS in preterm neonates remain unanswered. This review identifies important knowledge gaps in the management of LONS and describe possible methods and technologies that can be used to resolve these knowledge gaps. The availability of computational medicine and hypothesis-free-omics approaches give way to building bedside feedback tools to guide clinicians in personalized management of LONS. Despite advances in technology, implementation in clinical practice is largely lacking although such tools would help clinicians to optimize many aspects of the management of LONS. We outline which steps are needed to get possible research findings implemented on the neonatal intensive care unit and provide a roadmap for future research initiatives. Impact This review identifies knowledge gaps in prevention, early detection, antibiotic, and additional therapy of late-onset neonatal sepsis in preterm neonates and provides a roadmap for future research efforts. Research opportunities are addressed, which could provide the means to fill knowledge gaps and the steps that need to be made before possible clinical use. Methods to personalize medicine and technologies feasible for bedside clinical use are described.Pharmacolog

Biomarker-guided individualization of antibiotic therapy

Treatment failure of antibiotic therapy due to insufficient efficacy or occurrence of toxicity is a major clinical challenge, and is expected to become even more urgent with the global rise of antibiotic resistance. Strategies to optimize treatment in individual patients are therefore of crucial importance. Currently, therapeutic drug monitoring plays an important role in optimizing antibiotic exposure to reduce treatment failure and toxicity. Biomarker-based strategies may be a powerful tool to further quantify and monitor antibiotic treatment response, and reduce variation in treatment response between patients. Host response biomarkers, such as CRP, procalcitonin, IL-6, and presepsin, could potentially carry significant information to be utilized for treatment individualization. To achieve this, the complex interactions among immune system, pathogen, drug, and biomarker need to be better understood and characterized. The purpose of this tutorial is to discuss the use and evidence of currently available biomarker-based approaches to inform antibiotic treatment. To this end, we also included a discussion on how treatment response biomarker data from preclinical, healthy volunteer, and patient-based studies can be further characterized using pharmacometric and system pharmacology based modeling approaches. As an illustrative example of how such modeling strategies can be used, we describe a case study in which we quantitatively characterize procalcitonin dynamics in relation to antibiotic treatments in patients with sepsis.Pharmacolog

Optimisation of fluconazole therapy for the treatment of invasive candidiasis in preterm infants

Introduction: Fluconazole is an important antifungal in the prevention and treatment of invasive Candida infections in neonates, even though its use in preterm infants is still off-label. Here, we performed a population pharmacokinetic study on fluconazole in preterm neonates in order to optimise dosing through the identified predictive patient characteristics.Methods: Fluconazole concentrations obtained from preterm infants from two studies were pooled and analysed using NONMEM V.7.3. The developed model was used to evaluate current dosing practice. A therapeutic dosing strategy aiming to reach a minimum target exposure of 400 and 200 mgxhour/L per 24 hours for fluconazole-susceptible C. albicans meningitis and other systemic infections, respectively, was developed.Results: In 41 preterm neonates with median (range) gestational age 25.3 (24.0-35.1) weeks and median postnatal age (PNA) at treatment initiation 1.4 (0.2-32.5) days, 146 plasma samples were collected. A one-compartment model described the data best, with an estimated clearance of 0.0147 L/hour for a typical infant of 0.87 kg with a serum creatinine concentration of 60 mu mol/L and volume of distribution of 0.844 L. Clearance was found to increase with 16% per 100 g increase in actual body weight, and to decrease with 12% per 10 mu mol/L increase in creatinine concentration once PNA was above 1 week. Dose adjustments based on serum creatinine and daily dosing are required for therapeutic target attainment.Conclusion: In preterm neonates, fluconazole clearance is best predicted by actual body weight and serum creatinine concentration. Therefore, fluconazole dosing should not only be based on body weight but also on creatinine concentration to achieve optimal exposure in all infants.Pharmacolog

Use of Continuous Physiological Monitor Data to Evaluate Doxapram Therapy in Preterm Infants

Introduction: Evaluation of pharmacotherapy during intensive care treatment is commonly based on subjective, intermittent interpretations of physiological parameters. Realtime visualization and analysis may improve drug effect evaluation. We aimed to evaluate the effects of the respiratory stimulant doxapram objectively in preterm infants using continuous physiological parameters. Methods: In this longitudinal observational study, preterm infants who receiv

Enantiomer specific pharmacokinetics of ibuprofen in preterm neonates with patent ductus arteriosus

Aims: Racemic ibuprofen is widely used for the treatment of preterm neonates with patent ductus arteriosus. Currently used bodyweight-based dosing guidelines are based on total ibuprofen, while only the S-enantiomer of ibuprofen is pharmacologically active. We aimed to optimize ibuprofen dosing for preterm neonates of different ages based on an enantiomer-specific population pharmacokinetic model. Methods: We prospectively collected 210 plasma samples of 67 preterm neonates treated with ibuprofen for patent ductus arteriosus (median gestational age [GA] 26 [range 24–30] weeks, median body weight 0.83 [0.45–1.59] kg, median postnatal age [PNA] 3 [1–12] days), and developed a population pharmacokinetic model for S- and R-ibuprofen. Results: We found that S-ibuprofen clearance (CLS, 3.98 mL/h [relative standard error {RSE} 8%]) increases with PNA and GA, with exponents of 2.25 (RSE 6%) and 5.81 (RSE 15%), respectively. Additionally, a 3.11-fold higher CLS was estimated for preterm neonates born small for GA (RSE 34%). Clearance of R-ibuprofen was found to be high compared to CLS (18 mL/h [RSE 24%]), resulting in a low contribution of R-ibuprofen to total ibuprofen exposure. Current body weight was identified as covariate on both volume of distribution of S-ibuprofen and R-ibuprofen. Conclusion: S-ibuprofen clearance shows important maturation, especially with PNA, resulting in an up to 3-fold increase in CLS during a 3-day treatment regimen. This rapid increase in clearance needs to be incorporated in dosing guidelines by adjusting the dose for every day after birth to achieve equal ibuprofen exposure

The bioavailability and maturing clearance of doxapram in preterm infants

Background Doxapram is used for the treatment of apnea of prematurity in dosing regimens only based on bodyweight, as pharmacokinetic data are limited. This study describes the pharmacokinetics of doxapram and keto-doxapram in preterm infants. Methods Data (302 samples) from 75 neonates were included with a median (range) gestational age (GA) 25.9 (23.9-29.4) weeks, bodyweight 0.95 (0.48-1.61) kg, and postnatal age (PNA) 17 (1-52) days at the start of continuous treatment. A population pharmacokinetic model was developed using non-linear mixed-effects modelling (NONMEM (R)). Results A two-compartment model best described the pharmacokinetics of doxapram and keto-doxapram. PNA and GA affected the formation clearance of keto-doxapram (CLFORMATION KETO-DOXAPRAM) and clearance of doxapram via other routes (CLDOXAPRAM OTHER ROUTES). For a median individual of 0.95 kg, GA 25.6 weeks, and PNA 29 days, CL(FORMATION KETO-DOXAPRAM)was 0.115 L/h (relative standard error (RSE) 12%) and CL(DOXAPRAM OTHER ROUTES)was 0.645 L/h (RSE 9%). Oral bioavailability was estimated at 74% (RSE 10%). Conclusions Dosing of doxapram only based on bodyweight results in the highest exposure in preterm infants with the lowest PNA and GA. Therefore, dosing may need to be adjusted for GA and PNA to minimize the risk of accumulation and adverse events. For switching to oral therapy, a 33% dose increase is required to maintain exposure. ImpactCurrent dosing regimens of doxapram in preterm infants only based on bodyweight result in the highest exposure in infants with the lowest PNA and GA. Dosing of doxapram may need to be adjusted for GA and PNA to minimize the risk of accumulation and adverse events. Describing the pharmacokinetics of doxapram and its active metabolite keto-doxapram following intravenous and gastroenteral administration enables to include drug exposure to the evaluation of treatment of AOP. The oral bioavailability of doxapram in preterm neonates is 74%, requiring a 33% higher dose via oral than intravenous administration to maintain exposure.Pharmacolog

The Hydrophobic Core of Twin-Arginine Signal Sequences Orchestrates Specific Binding to Tat-Pathway Related Chaperones

Redox enzyme maturation proteins (REMPs) bind pre-proteins destined for translocation across the bacterial cytoplasmic membrane via the twin-arginine translocation system and enable the enzymatic incorporation of complex cofactors. Most REMPs recognize one specific pre-protein. The recognition site usually resides in the N-terminal signal sequence. REMP binding protects signal peptides against degradation by proteases. REMPs are also believed to prevent binding of immature pre-proteins to the translocon. The main aim of this work was to better understand the interaction between REMPs and substrate signal sequences. Two REMPs were investigated: DmsD (specific for dimethylsulfoxide reductase, DmsA) and TorD (specific for trimethylamine N-oxide reductase, TorA). Green fluorescent protein (GFP) was genetically fused behind the signal sequences of TorA and DmsA. This ensures native behavior of the respective signal sequence and excludes any effects mediated by the mature domain of the pre-protein. Surface plasmon resonance analysis revealed that these chimeric pre-proteins specifically bind to the cognate REMP. Furthermore, the region of the signal sequence that is responsible for specific binding to the corresponding REMP was identified by creating region-swapped chimeric signal sequences, containing parts of both the TorA and DmsA signal sequences. Surprisingly, specificity is not encoded in the highly variable positively charged N-terminal region of the signal sequence, but in the more similar hydrophobic C-terminal parts. Interestingly, binding of DmsD to its model substrate reduced membrane binding of the pre-protein. This property could link REMP-signal peptide binding to its reported proofreading function