TY - JOUR A1 - Minichmayr, Iris K. A1 - Roberts, Jason A. A1 - Frey, Otto R. A1 - Roehr, Anka C. A1 - Kloft, Charlotte A1 - Brinkmann, Alexander T1 - Development of a dosing nomogram for continuous-infusion meropenem in critically ill patients based on a validated population pharmacokinetic model JF - Journal of Antimicrobial Chemotherapy N2 - Background: Optimal antibiotic exposure is a vital but challenging prerequisite for achieving clinical success in ICU patients. Objectives: To develop and externally validate a population pharmacokinetic model for continuous-infusion meropenem in critically ill patients and to establish a nomogram based on a routinely available marker of renal function. Methods: A population pharmacokinetic model was developed in NONMEM (R) 7.3 based on steady-state meropenem concentrations (C-ss) collected during therapeutic drug monitoring. Different serum creatinine-based markers of renal function were compared for their influence on meropenem clearance (the Cockcroft-Gault creatinine clearance CLCRcG, the CLCR bedside estimate according to Jelliffe, the Chronic Kidney Disease Epidemiology Collaboration equation and the four-variable Modification of Diet in Renal Disease equation). After validation of the pharmacokinetic model with independent data, a dosing nomogram was developed, relating renal function to the daily doses required to achieve selected target concentrations (4/8/16 mg/L) in 90% of the patients. Probability of target attainment was determined for efficacy (C-ss >= 8 mg/L) and potentially increased likelihood of adverse drug reactions (C-ss >32 mg/L). Results: In total, 433 plasma concentrations (3.20-48.0 mg/L) from 195 patients (median/P-0.05 - P-0.95 at baseline: weight 77.0/55.0-114 kg, CLCRCG 63.0/19.6-168 mL/min) were used for model building. We found that CLCRCG best described meropenem clearance (CL = 7.71 L/h, CLCRCG = 80 mL/min). The developed model was successfully validated with external data (n = 171, 73 patients). According to the nomogram, daily doses of 910/1480/2050/2800/ 3940 mg were required to reach a target C-ss = 8 mg/L in 90% of patients with CLCRCG = 20/50/80/120/180 mL/min, respectively. A low probability of adverse drug reactions (<0.5%) was associated with these doses. Conclusions: A dosing nomogram was developed for continuous-infusion meropenem based on renal function in a critically ill population. Y1 - 2018 U6 - https://doi.org/10.1093/jac/dkx526 SN - 0305-7453 SN - 1460-2091 VL - 73 IS - 5 SP - 1330 EP - 1339 PB - Oxford Univ. Press CY - Oxford ER - TY - GEN A1 - Riebe, Daniel A1 - Erler, Alexander A1 - Brinkmann, Pia A1 - Beitz, Toralf A1 - Löhmannsröben, Hans-Gerd A1 - Gebbers, Robin T1 - Comparison of Calibration Approaches in Laser-Induced Breakdown Spectroscopy for Proximal Soil Sensing in Precision Agriculture T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 786 KW - laser-induced breakdown spectroscopy KW - LIBS KW - proximal soil sensing KW - soil nutrients KW - elemental composition Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-440079 SN - 1866-8372 IS - 786 ER - TY - JOUR A1 - Riebe, Daniel A1 - Erler, Alexander A1 - Brinkmann, Pia A1 - Beitz, Toralf A1 - Löhmannsröben, Hans-Gerd A1 - Gebbers, Robin T1 - Comparison of Calibration Approaches in Laser-Induced Breakdown Spectroscopy for Proximal Soil Sensing in Precision Agriculture JF - Sensors N2 - The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method. KW - laser-induced breakdown spectroscopy KW - LIBS KW - proximal soil sensing KW - soil nutrients KW - elemental composition Y1 - 2019 U6 - https://doi.org/10.3390/s19235244 SN - 1424-8220 VL - 19 IS - 23 PB - MDPI CY - Basel ER - TY - JOUR A1 - Brinkmann, Kai Oliver A1 - Becker, Tim A1 - Zimmermann, Florian A1 - Kreusel, Cedric A1 - Gahlmann, Tobias A1 - Theisen, Manuel A1 - Haeger, Tobias A1 - Olthof, Selina A1 - Tückmantel, Christian A1 - Günster, M. A1 - Maschwitz, Timo A1 - Göbelsmann, Fabian A1 - Koch, Christine A1 - Hertel, Dirk A1 - Caprioglio, Pietro A1 - Peña-Camargo, Francisco A1 - Perdigón-Toro, Lorena A1 - Al-Ashouri, Amran A1 - Merten, Lena A1 - Hinderhofer, Alexander A1 - Gomell, Leonie A1 - Zhang, Siyuan A1 - Schreiber, Frank A1 - Albrecht, Steve A1 - Meerholz, Klaus A1 - Neher, Dieter A1 - Stolterfoht, Martin A1 - Riedl, Thomas T1 - Perovskite-organic tandem solar cells with indium oxide interconnect JF - Nature N2 - Multijunction solar cells can overcome the fundamental efficiency limits of single-junction devices. The bandgap tunability of metal halide perovskite solar cells renders them attractive for multijunction architectures(1). Combinations with silicon and copper indium gallium selenide (CIGS), as well as all-perovskite tandem cells, have been reported(2-5). Meanwhile, narrow-gap non-fullerene acceptors have unlocked skyrocketing efficiencies for organic solar cells(6,7). Organic and perovskite semiconductors are an attractive combination, sharing similar processing technologies. Currently, perovskite-organic tandems show subpar efficiencies and are limited by the low open-circuit voltage (V-oc) of wide-gap perovskite cells(8) and losses introduced by the interconnect between the subcells(9,10). Here we demonstrate perovskite-organic tandem cells with an efficiency of 24.0 per cent (certified 23.1 per cent) and a high V-oc of 2.15 volts. Optimized charge extraction layers afford perovskite subcells with an outstanding combination of high V-oc and fill factor. The organic subcells provide a high external quantum efficiency in the near-infrared and, in contrast to paradigmatic concerns about limited photostability of non-fullerene cells(11), show an outstanding operational stability if excitons are predominantly generated on the non-fullerene acceptor, which is the case in our tandems. The subcells are connected by an ultrathin (approximately 1.5 nanometres) metal-like indium oxide layer with unprecedented low optical/electrical losses. This work sets a milestone for perovskite-organic tandems, which outperform the best p-i-n perovskite single junctions(12) and are on a par with perovskite-CIGS and all-perovskite multijunctions(13). Y1 - 2022 U6 - https://doi.org/10.1038/s41586-022-04455-0 SN - 0028-0836 SN - 1476-4687 VL - 604 IS - 7905 SP - 280 EP - 286 PB - Nature Research CY - Berlin ER -