Model selection for time-activity curves: the corrected Akaike information criterion and the F-test

MIRD Pamphlet No. 30: MIRDfit-A Tool for Fitting of Biodistribution Time-Activity Data for Internal Dosimetry

In nuclear medicine, estimating the number of radioactive decays that occur in a source organ per unit administered activity of a radiopharmaceutical (i.e., the time-integrated activity coefficient [TIAC]) is an essential task within the internal dosimetry workflow. TIAC estimation is commonly derived by least-squares fitting of various exponential models to organ time-activity data (radiopharmaceutical biodistribution). Rarely, however, are methods used to objectively determine the model that best characterizes the data. Additionally, the uncertainty associated with the resultant TIAC is generally not evaluated. As part of the MIRDsoft initiative, MIRDfit has been developed to offer a biodistribution fitting software solution that provides the following essential features and advantages for internal dose assessment: nuclear medicine-appropriate fit functions; objective metrics for guiding best-fit selection; TIAC uncertainty calculation; quality control and data archiving; integration with MIRDcalc software for dose calculation; and a user-friendly Excel-based interface. For demonstration and comparative validation of MIRDfit's performance, TIACs were derived from serial imaging studies involving 18F-FDG and 177Lu-DOTATATE using MIRDfit. These TIACs were then compared with TIAC estimates obtained using other software. In most cases, the TIACs agreed within approximately 10% between MIRDfit and the other software. MIRDfit has been endorsed by the MIRD Committee of the Society of Nuclear Medicine and Molecular Imaging and has been integrated into the MIRDsoft suite of free dosimetry software; it is available for download at no user cost (https://mirdsoft.org/).

Population-based model selection for an accurate estimation of time-integrated activity using non-linear mixed-effects modelling

PURPOSE

Personalized treatment planning in Molecular Radiotherapy (MRT) with accurately determining the absorbed dose is highly desirable. The absorbed dose is calculated based on the Time-Integrated Activity (TIA) and the dose conversion factor. A crucial unresolved issue in MRT dosimetry is which fit function to use for the TIA calculation. A data-driven population-based fitting function selection could help solve this problem. Therefore, this project aims to develop and evaluate a method for accurately determining TIAs in MRT, which performs a Population-Based Model Selection within the framework of the Non-Linear Mixed-Effects (NLME-PBMS) model.

METHODS

Biokinetic data of a radioligand for the Prostate-Specific Membrane Antigen (PSMA) for cancer treatment were used. Eleven fit functions were derived from various parameterisations of mono-, bi-, and tri-exponential functions. The functions' fixed and random effects parameters were fitted (in the NLME framework) to the biokinetic data of all patients. The goodness of fit was assumed acceptable based on the visual inspection of the fitted curves and the coefficients of variation of the fitted fixed effects. The Akaike weight, the probability that the model is the best among the whole set of considered models, was used to select the fit function most supported by the data from the set of functions with acceptable goodness of fit. NLME-PBMS Model Averaging (MA) was performed with all functions having acceptable goodness of fit. The Root-Mean-Square Error (RMSE) of the calculated TIAs from individual-based model selection (IBMS), a shared-parameter population-based model selection (SP-PBMS) reported in the literature, and the functions from NLME-PBMS method to the TIAs from MA were calculated and analysed. The NLME-PBMS (MA) model was used as the reference as this model considers all relevant functions with corresponding Akaike weights.

RESULTS

The function [Formula: see text] was selected as the function most supported by the data with an Akaike weight of (54 ± 11) %. Visual inspection of the fitted graphs and the RMSE values show that the NLME model selection method has a relatively better or equivalent performance than the IBMS or SP-PBMS methods. The RMSEs of the IBMS, SP-PBMS, and NLME-PBMS (f3a) methods are 7.4%, 8.8%, and 2.4%, respectively.

CONCLUSION

A procedure including fitting function selection in a population-based method was developed to determine the best fit function for calculating TIAs in MRT for a given radiopharmaceutical, organ and set of biokinetic data. The technique combines standard practice approaches in pharmacokinetics, i.e. an Akaike-weight-based model selection and the NLME model framework.

Modeling Chromatography Binding through Molecular Dynamics Simulations with Resin Fragments

Accurate atomistic modeling of the interactions of a chromatography resin with a solute can inform the selection of purification conditions for a product, an important problem in the biotech and pharmaceutical industries. We present a molecular dynamics simulation-based approach for the qualitative prediction of interaction sites (specificity) and retention times (affinity) of a protein for a given chromatography resin. We mimicked the resin with an unrestrained ligand composed of the resin headgroup coupled with successively larger fragments of the agarose backbone. The interactions of the ligand with the protein are simulated in an explicit solvent using the Replica Exchange Molecular Dynamics enhanced sampling approach in conjunction with Hydrogen Mass Repartitioning (REMD-HMR). We computed the ligand interaction surface from the simulation trajectories and correlated the features of the interaction surface with experimentally determined retention times. The simulation and analysis protocol were first applied to a series of ubiquitin mutants for which retention times on Capto MMC resin are available. The ubiquitin simulations helped identify the optimal ligand that was used in subsequent simulations on six proteins for which Capto MMC elution times are available. For each of the six proteins, we computed the interaction surface and characterized it in terms of a range of simulation-averaged residue-level physicochemical descriptors. Modeling of the salt concentrations required for elution with respect to the descriptors resulted in a linear fit in terms of aromaphilicity and Kyte-Doolittle hydrophobicity that was robust to outliers, showed high correlation, and correctly ranked the protein elution order. The physics-based model building approach described here does not require a large experimental data set and can be readily applied to different resins and diverse biomolecules.

Single-Time-Point Renal Dosimetry Using Nonlinear Mixed-Effects Modeling and Population-Based Model Selection in [177Lu]Lu-PSMA-617 Therapy

The aim of this study was to investigate the accuracy of single-time-point (STP) renal dosimetry imaging using SPECT/CT data, a nonlinear mixed-effects (NLME) model, and a population-based model selection (PBMS) in a large population for 177Lu-labeled prostate-specific membrane antigen therapy. Methods: Biokinetic data (mean ± SD) of [177Lu]Lu-PSMA-617 in kidneys at time points 1 (1.8 ± 0.8 h), 2 (18.7 ± 0.9 h), 3 (42.6 ± 1.0 h), 4 (66.3 ± 0.9 h), and 5 (160.3 ± 24.2 h) after injection were obtained from 63 patients with metastatic castration-resistant prostate cancer using SPECT/CT. Thirteen functions were derived from various parameterizations of 1- to 5-exponential functions. The function's parameters were fitted in the NLME framework to the all-time-point (ATP) data. The PBMS NLME method was performed using the goodness-of-fit test and Akaike weight to select the best function fitting the data. The best function from ATP fitting was used to calculate the reference time-integrated activity and absorbed doses. In STP dosimetry, the parameters of a particular patient with STP data were fitted simultaneously to the STP data at different time points of that patient with ATP data of all other patients. The parameters from STP fitting were used to calculate the STP time-integrated activity and absorbed doses. Relative deviations (RDs) and root-mean-square errors (RMSEs) were used to analyze the accuracy of the calculated STP absorbed dose compared with the reference absorbed dose obtained from the best-fit ATP function. The performance of STP dosimetry using PBMS NLME modeling was compared with the Hänscheid and Madsen methods. Results: The function [Formula: see text] was selected as the best-fit ATP function, with an Akaike weight of 100%. For STP dosimetry, the STP measurement by SPECT/CT at time point 3 (42.6 ± 1.0 h) showed a relatively low mean RD of -4.4% ± 9.4% and median RD of -0.7%. Time point 3 had the lowest RMSE value compared with those at the other 4 time points. The RMSEs of the absorbed dose RDs for time points 1-5 were 23%, 16%, 10%, 20%, and 53%, respectively. The STP dosimetry using the PBMS NLME method outperformed the Hänscheid and Madsen methods for all investigated time points. Conclusion: Our results show that a single measurement of SPECT/CT at 2 d after injection might be used to calculate accurate kidney-absorbed doses using the NLME method and PBMS.

Optimizing hepatocellular carcinoma disease staging systems by incorporating tumor micronecrosis: A multi-institutional retrospective study

Tumor micronecrosis is a pathological feature that reflects malignant biological behavior in hepatocellular carcinoma (HCC). However, whether micronecrosis can optimize HCC staging systems remains unilluminated. A total of 1632 HCC patients who underwent curative hepatectomy in four institutions from January 2014 to December 2021 were enrolled in this study. Independent prognostic factors were identified, and optimized staging models were established using a training cohort (n = 934). The performance of optimized staging models was validated using an external cohort consisting of cases from three other institutions (n = 232). In addition, patients from our prospectively collected database (n = 379) tested the application effectiveness of the models. Harrel's c-statistics and the corrected Akaike information criterion (AICc) were used to assess the performance of staging models. In most of Barcelona Clinic Liver Cancer (BCLC) and tumor (T) stages, HCC patients with tumor micronecrosis showed poorer prognosis than those without. Tumor micronecrosis, microvascular invasion, multiple tumors and tumor size >2 cm were independent prognostic-related factors. The BCLC and T staging models incorporating tumor micronecrosis showed better performance than the original systems (c-statistic, 0.712 and 0.711 vs. 0.664 and 0.679; AICc, 2314.8 and 2322.3 vs. 2338.2 and 2338.1; respectively). Furthermore, the external validation cohort confirmed that the optimized staging models had improved efficiency compared with the original ones. Moreover, the prospective cohort demonstrated the applicability of the optimized staging systems. Tumor micronecrosis plays a stage-ascending role in HCC patients. The BCLC and T staging systems incorporating tumor micronecrosis can improve the prognosis stratification efficiency of patients.

Pharmacokinetics of doxycycline hyclate in pigs with a new feed premix formulation

This study aimed to evaluate the administration of doxycycline hyclate in a long-acting pharmaceutical preparation in pigs when administered either ad libitum as a feed medication or an oral bolus dose. In all instances, the studied dose was 20 mg/kg b.w. A total of 48 healthy crossbred, castrated male pigs (Landrace-Yorkshire) weighing 23 ± 4.3 kg were included in this trial. They were randomly assigned to six groups as follows: two groups for the experimental prototype 1 of doxycycline hyclate administering it ad libitum (Fad-lib) or as forced bolus (Fbolus); two groups for the experimental prototype 2 of doxycycline hyclate as for the former groups (FCad-lib and FCbolus), and two control groups receiving the same dose of doxycycline hyclate, but of a commercial premix, also as previously explained (Cbolus and Cad-lib). Statistical analysis of the mean pharmacokinetic values was carried out with Kruskal-Wallis and Dunn's tests. The relative bioavailability (Fr) of the best prototype, when administered ad libitum (FCad-lib), was five times larger than the reference group (Cadlib). These results allow the proposal that the referred differences achieved in the presented prototypes can mark a notable clinical difference, particularly in pathogens with some resistance.

Fit of biokinetic data in molecular radiotherapy: a machine learning approach

BACKGROUND

In literature are reported different analytical methods (AM) to choose the proper fit model and to fit data of the time-activity curve (TAC). On the other hand, Machine Learning algorithms (ML) are increasingly used for both classification and regression tasks. The aim of this work was to investigate the possibility of employing ML both to classify the most appropriate fit model and to predict the area under the curve (τ).

METHODS

Two different ML systems have been developed for classifying the fit model and to predict the biokinetic parameters. The two systems were trained and tested with synthetic TACs simulating a whole-body Fraction Injected Activity for patients affected by metastatic Differentiated Thyroid Carcinoma, administered with [131I]I-NaI. Test performances, defined as classification accuracy (CA) and percentage difference between the actual and the estimated area under the curve (Δτ), were compared with those obtained using AM varying the number of points (N) of the TACs. A comparison between AM and ML were performed using data of 20 real patients.

RESULTS

As N varies, CA remains constant for ML (about 98%), while it improves for F-test (from 62 to 92%) and AICc (from 50 to 92%), as N increases. With AM, [Formula: see text] can reach down to - 67%, while using ML [Formula: see text] ranges within ± 25%. Using real TACs, there is a good agreement between τ obtained with ML system and AM.

CONCLUSIONS

The employing of ML systems may be feasible, having both a better classification and a better estimation of biokinetic parameters.

Studies on solubility measurement of codeine phosphate (pain reliever drug) in supercritical carbon dioxide and modeling

In this study, the solubilities of codeine phosphate, a widely used pain reliever, in supercritical carbon dioxide (SC-CO2) were measured under various pressures and temperature conditions. The lowest determined mole fraction of codeine phosphate in SC-CO2 was 1.297 × 10-5 at 308 K and 12 MPa, while the highest was 6.502 × 10-5 at 338 K and 27 MPa. These measured solubilities were then modeled using the equation of state model, specifically the Peng-Robinson model. A selection of density models, including the Chrastil model, Mendez-Santiago and Teja model, Bartle et al. model, Sodeifian et al. model, and Reddy-Garlapati model, were also employed. Additionally, three forms of solid-liquid equilibrium models, commonly called expanded liquid models (ELMs), were used. The average solvation enthalpy associated with the solubility of codeine phosphate in SC-CO2 was calculated to be - 16.97 kJ/mol. The three forms of the ELMs provided a satisfactory correlation to the solubility data, with the corresponding average absolute relative deviation percent (AARD%) under 12.63%. The most accurate ELM model recorded AARD% and AICc values of 8.89% and - 589.79, respectively.

Solubility measurement and modeling of hydroxychloroquine sulfate (antimalarial medication) in supercritical carbon dioxide

A supercritical fluid, such as supercritical carbon dioxide (scCO₂) is increasingly used for the micronization of pharmaceuticals in the recent past. The role of scCO₂ as a green solvent in supercritical fluid (SCF) process is decided by the solubility information of the pharmaceutical compound in scCO₂. The commonly used SCF processes are the rapid expansion of supercritical solution (RESS) and supercritical antisolvent precipitation (SAS). To implement micronization process, solubility of pharmaceuticals in scCO₂ is required. Present study is aimed at both measuring and modeling of solubilities of hydroxychloroquine sulfate (HCQS) in scCO₂. Experiments were conducted at various conditions (P = 12 to 27 MPa and T = 308 to 338 K), for the first time. The measured solubilities were found to be ranging between (0.0304 × 10^-4 and 0.1459 × 10^-4) at 308 K, (0.0627 × 10^-4 and 0.3158 × 10^-4) at 318 K, (0.0982 × 10^-4 and 0.4351 × 10^-4) at 328 K, (0.1398 × 10^-4 and 0.5515 × 10^-4) at 338 K. To expand the usage of the data, various models were tested. For the modelling task existing models (Chrastil, reformulated Chrastil, Méndez-Santiago and Teja (MST), Bartle et al., Reddy-Garlapati, Sodeifian et al., models) and new set of solvate complex models were considered. Among the all models investigated Reddy-Garlapati and new solvate complex models are able to fit the data with the least error. Finally, the total and solvation enthalpies of HCQS in scCO₂ were calculated with the help of model constants obtained from Chrastil, reformulated Chrastil and Bartle et al., models.

Boost dynamic protocols for producing mammalian biopharmaceuticals with intensified DoE—a practical guide to analyses with OLS and hybrid modeling

Introduction: For the implementation of robust bioprocesses, understanding of temporal cell behavior with respect to relevant inputs is crucial. Intensified Design of Experiments (iDoE) is an efficient tool to assess the joint influence of input parameters by including intra-experimental changes.

Methods: We applied iDoE to the production phase of a monoclonal antibody in a mammalian bioprocess. The multidimensional design space spanned by temperature, dissolved oxygen (DO), timing of change, and growth category was investigated in 12 cultivations. We built ordinary least squares (OLS) and hybrid models (HM) on the iDoE-data, validated them with classical DoE (cDoE)-derived data, and used the models as in silico representation for process optimization.

Results: If the complexity of interactions between changing setpoints of inputs is sufficiently captured during planning and modeling, iDoE proved to be valid for characterizing the mammalian biopharmaceutical production phase. For local behavior and flexible composition of optimization goals, OLS regressions can easily be implemented. To predict global and interconnected dynamics while incorporating mass balances, HM holds potential.

Discussion: iDoE will boost protocols that optimize inputs for different bioprocess phases. The described key aspects of OLS- and HM-based analyses of iDoE-data shall guide future applications during manufacturing.

Experimental solubility and modeling of Crizotinib (anti-cancer medication) in supercritical carbon dioxide

Measurement of saturation solubility of drugs in a supercritical fluid is an important parameter for the implementation of supercritical technology in pharmaceutical industry. CO₂ is the most sorted substance as a supercritical fluid since it has attractive properties like easily achievable critical temperature, moderate pressure. Cancer is increasingly affecting the mankind, a proper dosage while treating would help in minimizing the drug usage. The bioavailability of the drug is mainly influenced by the drug particle size. An appropriate technology is always useful in making suitable drug particles; thus, supercritical fluid technology (SFT) is considered as promising technique for the production of micro and nanoparticles. Since, particle production process through SFT needs solubility information, appropriate solubility information is necessary. In the present work, Crizotinib (anti-cancer drug) solubility in supercritical carbon dioxide (scCO₂) is measured and reported, for the first time. The obtained solubilities are at temperatures 308, 318, 328,338 K and pressures 12, 15, 18, 21, 24 to 27 MPa. The measured solubilities are ranged in terms of mole fraction from (0.483 × 10^-5 to 0.791 × 10^-5) at 308 K, (0.315 × 10^-5 to 0.958 × 10^-5) at 318 K, (0.26 × 10^-5 to 1.057 × 10^-5) at 328 K, (0.156 × 10^-5 to 1.219 × 10^-5) at 338 K. The cross over region is observed at 14.5 MPa. To expand the application of the solubility data, few important solubility models and three cubic equations of sate (cubic EoS) models along with Kwak and Mansoori mixing rules are investigated. Sublimation and salvation enthalpies of Crizotinib dissolution in scCO₂ are calculated.

Spatial Characterisation of Vegetation Diversity in Groundwater-Dependent Ecosystems Using In-Situ and Sentinel-2 MSI Satellite Data

Groundwater-Dependent Ecosystems (GDEs) are under threat from groundwater over-abstraction, which significantly impacts their conservation and sustainable management. Although the socio-economic significance of GDEs is understood, their ecosystem services and ecological significance (e.g., biodiversity hotspots) in arid environments remains understudied. Therefore, under the United Nations Sustainable Development Goal (SDG) 15, characterizing or identifying biodiversity hotspots in GDEs improves their management and conservation. In this study, we present the first attempt towards the spatial characterization of vegetation diversity in GDEs within the Khakea-Bray Transboundary Aquifer. Following the Spectral Variation Hypothesis (SVH), we used multispectral remotely sensed data (i.e., Sentinel-2 MSI) to characterize the vegetation diversity. This involved the use of the Rao’s Q to measure spectral diversity from several measures of spectral variation and validating the Rao’s Q using field-measured data on vegetation diversity (i.e., effective number of species). We observed that the Rao’s Q has the potential of spatially characterizing vegetation diversity of GDEs in the Khakea-Bray Transboundary Aquifer. Specifically, we discovered that the Rao’s Q was related to field-measured vegetation diversity (R2 = 0.61 and p = 0.00), and the coefficient of variation (CV) was the best measure to derive the Rao’s Q. Vegetation diversity was also used as a proxy for identifying priority conservation areas and biodiversity hotspots. Vegetation diversity was more concentrated around natural pans and along roads, fence lines, and rivers. In addition, vegetation diversity was observed to decrease with an increasing distance (>35 m) from natural pans and simulated an inverse piosphere (i.e., minimal utilization around the natural water pans). We provide baseline information necessary for identifying priority conservation areas within the Khakea-Bray Transboundary Aquifer. Furthermore, this work provides a pathway for resource managers to achieve SDG 15 as well as national and regional Aichi biodiversity targets.

Experimental solubility and thermodynamic modeling of empagliflozin in supercritical carbon dioxide

The solubility of empagliflozin in supercritical carbon dioxide was measured at temperatures (308 to 338 K) and pressures (12 to 27 MPa), for the first time. The measured solubility in terms of mole faction ranged from 5.14 × 10^–6 to 25.9 × 10^–6. The cross over region was observed at 16.5 MPa. A new solubility model was derived to correlate the solubility data using solid–liquid equilibrium criteria combined with Wilson activity coefficient model at infinite dilution for the activity coefficient. The proposed model correlated the data with average absolute relative deviation (AARD) and Akaike’s information criterion (AIC_c), 7.22% and − 637.24, respectively. Further, the measured data was also correlated with 11 existing (three, five and six parameters empirical and semi-empirical) models and also with Redlich-Kwong equation of state (RKEoS) along with Kwak-Mansoori mixing rules (KMmr) model. Among density-based models, Bian et al., model was the best and corresponding AARD% was calculated 5.1. The RKEoS + KMmr was observed to correlate the data with 8.07% (correspond AIC_c is − 635.79). Finally, total, sublimation and solvation enthalpies of empagliflozin were calculated.

Prevalence and time-course of diaphragmatic dysfunction following lung resection: A repeated ultrasonic assessment

PURPOSE

Ultrasound (US) allows non-invasive repeated assessments of diaphragmatic excursion (DE) and thickening fraction (DTF) at the bedside, reflecting diaphragmatic dysfunction (DD). We aimed at determining the prevalence and time-course of DD following elective thoracic surgery and the association with postoperative complications.

MATERIAL AND METHODS

Prospective, single-centre, observational study with consecutive patients undergoing thoracic surgery. DE/DTF were measured by two observers blinded to each other at 3 different time-points: prior to surgery, immediately after extubation and on postoperative day 3. The changes in DE/DTF of both hemi-diaphragms over time were compared according to the side (operated/non-operated) using a two-way-ANOVA. The association with postoperative complications was assessed using logistic regression.

RESULTS

Fifty patients, 60% males, aged 60 ± 15 years were included. Surgical procedures included lobectomy (n = 30), wedge-resection (n = 17) or pneumonectomy (n = 3). On the operated side, we observed a decrease in DE/DTF at D0 (-0.71 ± 0.12 mm, P < 0.05; -44 ± 30%, P < 0.05) and D3 (-0.82 ± 0.19 mm, P < 0.05; -39 ± 19%, P < 0.05) with respect to preoperative and non-operated side values over the study period. Persistent DD on the operated side was associated with an increased risk of lung infection (OR: 9.0, 95%CI [1.92-65.93], P = 0.001), ICU-admission (OR: 3.9, 95%CI [1.10-15.53], P = 0.04) according to univariate analysis and a prolonged length in hospital (OR: 1.3, 95%CI [1.1-1.7], P = 0.016) according to multivariate analysis.

CONCLUSIONS

Thoracic surgery generates DD mainly observed on the operated side, which persists at least up to postoperative D3 and is associated with an increase in hospital stay.

Measurement and modeling of clemastine fumarate (antihistamine drug) solubility in supercritical carbon dioxide

The solubilities of clemastine fumarate in supercritical carbon dioxide (ScCO₂) were measured for the first time at temperature (308 to 338 K) and pressure (12 to 27 MPa). The measured solubilities were reported in terms of mole faction (mol/mol total) and it had a range from 1.61 × 10^–6 to 9.41 × 10^–6. Various models were used to correlate the data. The efficacy of the models was quantified with corrected Akaike’s information criterion (AICc). A new cluster salvation model was derived to correlate the solubility data. The new model was able to correlate the data and deviation was 10.3% in terms of average absolute relative deviation (AARD). Furthermore, the measured solubilities were also correlated with existing K.-W. Chen et al., model, equation of state model and a few other density models. Among density models, Reddy and Garlapati model was observed to be the best model and corresponding AARD was 7.57% (corresponding AIC_c was − 678.88). The temperature independent Peng–Robinson equation of state was able to correlate the data and AARD was 8.25% (corresponding AIC_c was − 674.88). Thermodynamic parameters like heats of reaction, sublimation and solvation of clemastine fumarate were calculated and reported.

Changes in alcohol consumption during pregnancy and over the transition towards parenthood

OBJECTIVE

To examine pre- to postnatal changes in drinking for women and men and assess the role of education level in these changes.

BACKGROUND

The transition towards parenthood can contribute to significant shifts in alcohol consumption for women and men. Research has generally focused on pregnancy and short-term changes following childbirth, usually for mothers only. Socio-economic variation in the impact of childbirth and return to drinking postnatally is similarly understudied.

METHOD

Longitudinal alcohol consumption data for 2470 individuals (1248 female) who were pregnant, or the partner of a pregnant woman, were obtained from a representative, Australian survey for three years prior and following birth. Piecewise regression models, including an education-x-time interaction, assessed changes in drinking quantity and frequency.

RESULTS

Female usual quantity and frequency significantly declined during pregnancy, followed by significant postnatal increases in quantity, approaching pre-pregnancy levels, with similar trends across education levels. Male usual quantity increased following childbirth, save for those men with a high-school education. Having an undergraduate degree was associated with a significant postnatal increase in drinking frequency.

CONCLUSION

Further awareness of the risks associated with male-partner drinking could provide substantial public health benefits. Successful facilitation and implementation of interventions and harm reduction strategies for harmful drinking over the pre- to postnatal period could benefit from further consideration of socioeconomic status and education level, particularly for men.

Oral bioavailability and pharmacokinetics of esculetin following intravenous and oral administration in rats

Esculetin is the main active ingredient isolated from Artemisia montana (Nakai) Pamp. and Euphorbia lathyris L. The present study investigated the oral bioavailability and pharmacokinetics of esculetin in rats, following intravenous and oral administration.Twenty Sprague-Dawley rats were randomly assigned to receive 10 mg/kg of esculetin either by the intravenous or oral route. Plasma concentrations of esculetin were measured using liquid chromatography-tandem mass spectrometry. Pharmacokinetic parameters were estimated using non-compartmental analysis as well as a compartmental modelling approach using WinNonlin^TM and ADAPT 5 software, respectively.According to non-compartmental analysis, the mean oral bioavailability of esculetin was 19%. Mean ± standard deviation values of esculetin half-life, steady-state volume of distribution and clearance, following intravenous dosing, were 2.08 ± 0.46 h, 1.81 ± 0.52 L/kg and 1.27 ± 0.26 L/h/kg, respectively. As indicated by compartmental modelling, a two-compartment pharmacokinetic model with first-order absorption and elimination rate constants of 0.98 ± 0.18 h^-1 and 2.47 ± 0.28 h^-1, respectively, sufficiently described the plasma concentration-time curve of esculetin.Improving our understanding of the pharmacokinetic properties of esculetin could help with future development of herbal medicine products with appropriate bioactivity.

Kinetic modeling of malondialdehyde reactivity in oil to simulate actual malondialdehyde formation upon lipid oxidation

The reactivity of malondialdehyde in saturated glycerol triheptanoate oil was studied over a wide temperature range (298.15-453.15 K). With respect to the non-ideal character of a lipid medium, a kinetic model was proposed that described the experimental malondialdehyde data by a reversible hydrolytic cleavage and an irreversible aldol self-condensation reaction. Significant parameter estimates were obtained by using a global one-step non-linear regression procedure. The aldol self-condensation of malondialdehyde showed to be the main degradation route of malondialdehyde in oils. Simulation of the malondialdehyde formation during lipid oxidation of sunflower oil demonstrated that, depending on the heating time, the experimentally obtained malondialdehyde concentrations can substantially underestimate the ongoing lipid oxidation.

Altered RNA Splicing by Mutant p53 Activates Oncogenic RAS Signaling in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is driven by co-existing mutations in KRAS and TP53. However, how these mutations collaborate to promote this cancer is unknown. Here, we uncover sequence-specific changes in RNA splicing enforced by mutant p53 which enhance KRAS activity. Mutant p53 increases expression of splicing regulator hnRNPK to promote inclusion of cytosine-rich exons within GTPase-activating proteins (GAPs), negative regulators of RAS family members. Mutant p53-enforced GAP isoforms lose cell membrane association, leading to heightened KRAS activity. Preventing cytosine-rich exon inclusion in mutant KRAS/p53 PDACs decreases tumor growth. Moreover, mutant p53 PDACs are sensitized to inhibition of splicing via spliceosome inhibitors. These data provide insight into co-enrichment of KRAS and p53 mutations and therapeutics targeting this mechanism in PDAC.

Comparison of commercial dosimetric software platforms in patients treated with 177 Lu-DOTATATE for peptide receptor radionuclide therapy

Purpose

The aim of this study was to quantitatively compare five commercial dosimetric software platforms based on the analysis of clinical datasets of patients who benefited from peptide receptor radionuclide therapy (PRRT) with ¹⁷⁷Lu‐DOTATATE (LUTATHERA^®).

Methods

The dosimetric analysis was performed on two patients during two cycles of PRRT with ¹⁷⁷Lu. Single photon emission computed tomography/computed tomography images were acquired at 4, 24, 72, and 192 h post injection. Reconstructed images were generated using Dosimetry Toolkit^® (DTK) from Xeleris™ and HybridRecon‐Oncology version_1.3_Dicom (HROD) from HERMES. Reconstructed images using DTK were analyzed using the same software to calculate time‐integrated activity coefficients (TIAC), and mean absorbed doses were estimated using OLINDA/EXM V1.0 with mass correction. Reconstructed images from HROD were uploaded into PLANET® OncoDose from DOSIsoft, STRATOS from Phillips, Hybrid Dosimetry Module™ from HERMES, and SurePlan™ MRT from MIM. Organ masses, TIACs, and mean absorbed doses were calculated from each application using their recommendations.

Results

The majority of organ mass estimates varied by <9.5% between all platforms. The highest variability for TIAC results between platforms was seen for the kidneys (28.2%) for the two patients and the two treatment cycles. Relative standard deviations in mean absorbed doses were slightly higher compared with those observed for TIAC, but remained of the same order of magnitude between all platforms.

Conclusions

When applying a similar processing approach, results obtained were of the same order of magnitude regardless of the platforms used. However, the comparison of the performances of currently available platforms is still difficult as they do not all address the same parts of the dosimetric analysis workflow. In addition, the way in which data are handled in each part of the chain from data acquisition to absorbed doses may be different, which complicates the comparison exercise. Therefore, the dissemination of commercial solutions for absorbed dose calculation calls for the development of tools and standards allowing for the comparison of the performances between dosimetric software platforms.

Plasticity of haemoglobin concentration and thermoregulation in a mountain lizard

The plastic capability of species to cope with the new conditions created by climate change is poorly understood. This is particularly relevant for organisms restricted to high elevations because they are adapted to cold temperatures and low oxygen availability. Therefore, evaluating trait plasticity of mountain specialists is fundamental to understand their vulnerability to environmental change. We transplanted mountain lizards, Iberolacerta cyreni, 800 m downhill to evaluate the plastic response in body condition, thermoregulation traits, haemoglobin level, and haemoparasite load. Initial measurements of body mass, total haemoglobin concentration ([Hb]), hematic parasite intensities, dorsal luminance, and thermoregulatory behaviour were resampled after two and four weeks of acclimation. We also tested whether an anti-parasitic drug reduced haemoparasite intensity. After only two weeks of acclimation to a lower elevation, lizards decreased 42% in [Hb], had 17% less parasite intensities, increased body condition by 25%, and raised by ~3% their mean preferred temperatures and their voluntary thermal maximum. The anti-parasitic treatment had no significant effect on the intensity of hematic parasites, but our results suggest that negative effects of haemoparasites on [Hb] are relaxed at lower elevation. The rapid plastic changes observed in thermal preferences, body condition, [Hb], and parasite intensity of I. cyreni demonstrate a potential plastic response of a mountain specialist. This may be adaptive under the climatic extremes typical of mountain habitats. However, there is uncertainty in whether the observed plasticity can also help overcome long term environmental changes.

Pharmacokinetic analysis of mosapride following intravenous and oral administration in beagle dogs

The aim of this study was to investigate the pharmacokinetic properties of mosapride after intravenous and oral administration to beagle dogs. To obtain the advanced pharmacokinetic parameters of mosapride, both noncompartmental analysis and pharmacokinetic modeling were performed. Twenty beagle dogs were randomly sorted into intravenous (1 mg single administration of mosapride) and oral (5 mg once a day administration of mosapride) groups. Blood samples were collected according to the reported schedule for pharmacokinetics. The plasma concentration of mosapride was analyzed using liquid chromatography-tandem mass spectrometry. According to the pharmacokinetic analysis, the absorption rate of mosapride was 3.14 ± 1.14 hr^-1 and oral bioavailability of mosapride was approximately 1%. The one-compartment model well described the pharmacokinetics of mosapride after both intravenous and oral administration to dogs. These findings will help facilitate the determination of the optimal dose regimen of mosapride for dogs with gastrointestinal disorder.

Particle filter de-noising of voxel-specific time-activity-curves in personalized 177Lu therapy

BACKGROUND

Currently, there is a high interest in ¹⁷⁷Lu targeted radionuclide therapies, which could be attributed to favorable results obtained from ¹⁷⁷Lu compounds targeting neuro-endocrine and prostate tumors. SPECT based dosimetry could be used for deriving dose values for individual voxels, as is the standard in external-beam radiation-therapy (EBRT). For this a time-activity-curve (TAC) at voxel resolution and also a voxel-wise modeling of radiation energy deposition are necessary. But a voxel-wise determination of TACs is problematic, since several confounding factors exist, such as e.g. poor count-statistics or registration inaccuracies, which add noise to the observed activity states. A particle filter (PF) is a class of methods which applies regularization based on a model of the temporal evolution of activity states. The aim of this study is to introduce the application of PFs for de-noising of per-voxel time-activity curves.

METHODS

We applied a PF for de-noising the TACs of 26 patients, who underwent ¹⁷⁷Lu-DOTATOC or -PSMA therapy. The TACs were obtained from fully-quantitative, serial SPECT(/CT) data, acquired at 4h, 24h, 48h, 72h p.i. The model used in the PF was a mono-exponential decay and its free parameters were determined based on objective criteria. The time-integrated activities (TIA) resulting from the PF (PFF) were compared to the results of a mono-exponential fit (SF) of individual voxels in several volumes of interest (kidneys, spleen, tumors). Additionally, an organ-averaged TIA was derived from whole-organ VOIs and subsequent curve-fitting. This whole-organ TIA was also compared to the whole-organ TIAs obtained from summation of the voxel-wise TIAs from PFF and SF.

RESULTS

The number of particles was set to 1000. Optimal values for noise of observations and noise of the model were 0.25 and 0.5, respectively. The deviation of whole-organ TIAs from conventional organ-based dosimetry and the summation of the voxel-wise TIAs was substantial for SF (kidneys -22.3%, spleen -49.6%, tumor -60.0%), as well as for PFF (kidneys -37.1%, spleen -57.9%, tumor -70.9%). The distribution of voxel-wise half-lives resulting from the PFF method was considerably closer to the organ-averaged value, and the number of implausibly long half-lives (>physical HL) was reduced.

CONCLUSION

The PFF leads to voxel-wise half-lives, which are more plausible than those resulting from SF. However, one has to admit that voxel-wise fitting generally leads to considerable deviations from the organ-averaged TIA as obtained by conventional whole-organ evaluation. Unfortunately, we did not have ground-truth TIA of our patient data and proper ground-truth could even be impossible to obtain. Nevertheless, there are strong indicators that particle filtering can be used for reducing voxel-wise TAC noise.

Extracorporeal Membrane Oxygenation for Severe Adenoviral Pneumonia in Neonatal, Pediatric, and Adult Patients

OBJECTIVES

We examined data on patients with severe adenoviral pneumonia from the international registry of the Extracorporeal Life Support Organization to identify risk factors for mortality in patients receiving extracorporeal membrane oxygenation.

DESIGN

Retrospective analysis.

SETTING

International Registry of Extracorporeal Life Support Organization.

PATIENTS

We collected de-identified data on all patients with adenoviral pneumonia who needed extracorporeal membrane oxygenation from 1992 to 2016 using International Classification of Diseases, 9th Edition, criteria.

INTERVENTIONS

Our primary outcome measure was in-hospital mortality. We also collected data on demographics, preextracorporeal membrane oxygenation ventilator settings, biochemical variables, extracorporeal membrane oxygenation mode, duration, and complications. Initial bivariate analysis assessed potential associations between mortality and various preextracorporeal membrane oxygenation variables as well as extracorporeal membrane oxygenation factors. Variables with p values of less than 0.1 were considered for logistic regression analysis that identified predictors of mortality.

MEASUREMENTS AND RESULTS

There were 542 patients with adenoviral pneumonia who were supported with extracorporeal membrane oxygenation. Overall mortality was 58% (307/529 patients) (neonates 86.4% [108/125 patients], children 49% [158/327 patients], and adults 49% [41/83 patients]). Multivariate regression identified hypercapnia (PCO2 > 45.7; odds ratio > 3.2; p < 0.001), immunosuppression (odds ratio, 4.44; 95% CI, 1.69-11.61; p = 0.002] and lack of pharmacologic paralysis (odds ratio, 0.30; 95% CI, 0.16-0.57; p < 0.001] as significant preextracorporeal membrane oxygenation factors for mortality. Neonatal patients had significantly higher mortality than pediatric or adult patients (odds ratio, 10.9; 95% CI, 3.2-37.3; p < 0.001). The presence of renal (odds ratio, 4.4; 95% CI, 2.5-7.7; p < 0.001), neurologic (odds ratio, 2.5; 95% CI, 1.2-5.1; p = 0.014), hemorrhagic (odds ratio, 2.2; 95% CI, 1.2-4.0; p = 0.014), or cardiovascular complications (odds ratio, 2.4; 95% CI, 1.3-4.6; p = 0.006) was associated with higher mortality on extracorporeal membrane oxygenation.

CONCLUSIONS

Patients with adenoviral pneumonia supported on extracorporeal membrane oxygenation had mortality of 58% over a 25-year-old period. We identified risk factors both before and during extracorporeal membrane oxygenation which were associated with higher mortality. Mortality in neonatal patients was particularly high.

Modelling the internalisation process of prostate cancer cells for PSMA-specific ligands

INTRODUCTION

In prostate-specific membrane antigen (PSMA)-targeting radioligand therapy, small molecules are regularly internalised by the tumour cells. To determine the effectiveness of these ligands, the internalised fraction over time is derived from cell studies. Parameters, such as the ligand concentration and the number of cells, are experiment-specific and therefore a comparison between ligands is difficult. A more objective approach that allows better comparison is desirable. Therefore, the aim of this work was to develop a compartmental model that fully describes all relevant pharmacokinetic interactions of PSMA-specific ligands with prostate cancer cells.

METHODS

Internalisation studies were performed using the lymph node carcinoma of the prostate cell line LNCaP C4-2 and the prostatic carcinoma cell line PC-3. A new protocol was established for the determination of the PSMA-binding specificity by surface plasmon resonance (SPR). The experimental data in combination with parameters from literature were used for the modelling approach.

RESULTS

A compartmental model which includes the relevant physiological mechanisms was developed. The basic model structure and some parameters originate from the literature. The PSMA-specific association and dissociation rates of Ga-PSMA-11 were measured using surface plasmon resonance technology. The ligand-induced internalisation and PSMA synthesis rates were estimated by fitting the developed model to experimental data obtained using LNCaP C4-2 cells. For all [⁶⁸Ga]Ga-PSMA-11 concentrations and including four various incubation times, the ligand-induced internalisation was determined to be (3.6 ± 0.1) % min^-1.

CONCLUSIONS

The presented approach is a prerequisite for better estimation and thus comparison of important ligand-cell interaction parameters, by combining SPR measurements, cell experiments and mathematical modelling.

ADVANCES IN KNOWLEDGE AND IMPLICATIONS FOR PATIENT

A compartmental model was developed for evaluation and comparison of PSMA-binding small molecules. A SPR protocol was established for the determination of PSMA-binding specificity.

Economic and Technological Analysis of Commercial LNG Production in the EU

There is a global need to increase the production of alternative sources of energy due to many issues related to conventional sources, such as environmental degradation or energy security. In this paper, decentralized liquefied natural gas production is analyzed. Liquefied natural gas, according to the analysis, can be considered a viable alternative even for decentralized applications Design and economic analysis of a small-scale biogas LNG plan together with the necessary technology and economic evaluation are presented in the paper. The results show that a project of the proposed size (EUR 3 million) offers a relatively good profitability level. Specifically, the net present value of the project is mostly positive (around EUR 0.1 million up to EUR 0.8 million). Therefore, based on the research, small LNG plants operating across the continent can be recommended for the processing of local sources of biogas.

An LC-MS/MS method for the quantification of diclofenac sodium in dairy cow plasma and its application in pharmacokinetics studies

An LC-MS/MS method with internal standard tolfenamic acid for determining diclofenac sodium (DCF) in dairy cow plasma was developed and validated. Samples were processed with protein precipitation by cold formic acid-acetonitrile. Determination of DCF was performed using LC-ESI⁺ -MS/MS with the matrix-matched calibration curve. The results showed that the method was sensitive (LOD 2 ng mL^-1 , LOQ 5 ng mL^-1 ), accurate (97.60 ± 5.64%), precise (<10%) and linear in the range of 5-10,000 ng mL^-1 . A single intravenous (i.v.) or intramuscular (i.m.) administration of 5% diclofenac sodium injection at a dose of 2.2 mg kg^-1 was performed in six healthy dairy cows according to a two-period crossover design. The main pharmacokinetic (PK) parameters after a single i.v. administration were as follows: t_1/2β , 4.52 ± 1.71 h; AUC, 77.79 ± 16.76 h μg mL^-1 ; mean residence time, 5.16 ± 1.11 h. The main PK parameters after a single i.m. administration were as follows: T_max , 2.38 ± 1.19 h; C_max , 7.46 ± 1.85 μg mL^-1 ; t_1/2β , 9.46 ± 2.86 h; AUC 67.57 ± 13.07 h μg mL^-1 . The absolute bioavailability was 87.37 ± 5.96%. The results showed that the diclofenac sodium injection had PK characteristics of rapid absorption and slow elimination, and high peak concentration and bioavailability in dairy cows, and that the recommended clinical dosage of diclofenac sodium injection is 2.2 mg kg^-1 .

A simulation-based method to determine optimal sampling schedules for dosimetry in radioligand therapy

AIM

For dosimetry in radioligand therapy, the time-integrated activity coefficients (TIACs) for organs at risk and for tumour lesions have to be determined. The used sampling scheme affects the TIACs and therefore the calculated absorbed doses. The aim of this work was to develop a general and flexible method, which analyses numerous clinically applicable sampling schedules using true time-activity curves (TACs) of virtual patients.

METHOD

Nine virtual patients with true TACs of the tumours were created using a physiologically-based pharmacokinetic (PBPK) model and individual biokinetic data of five patients with neuroendocrine tumours and four with meningioma. ¹¹¹In-DOTATATE was used for pre-therapeutic dosimetry. In total, 15,120 sampling schemes, each consisting of 4 time points, were investigated. Gaussian noise of different levels was added to the corresponding true time-activity points. A bi-exponential function was used to fit the simulated time-activity data. For each investigated sampling schedule, 1000 replications were performed. Patient-specific and population-specific optimal sampling schedules were determined using the relative root-mean-square error (rRMSE). Furthermore, the fractions of TIACs a˜ deviating >5% (f_Δa˜>5%) and >10% (f_Δa˜>10%) from the true TIAC a˜_true were used for additional evaluations e.g. to investigate the effect of varying single time points.

RESULTS

Almost all patient-specific and all population-specific optimal sampling schedules have t₄≥96h for all noise levels. Changing the latest time point from the population-specific optimal time to e.g. 48h leads to a median increase of f_Δa˜>10% from 0.1% to 88% for the lowest investigated noise level. Using the determined population-specific optimal schedules, results in more accurate and precise results than established schedules from the literature.

CONCLUSION

A method of determining the optimal sampling schedule for dosimetry, which considers clinical working hours and measurement uncertainties, has been developed and applied. The simulation study shows that optimised sampling schedules result in high accuracy and precision of the determined TIACs.

EANM practical guidance on uncertainty analysis for molecular radiotherapy absorbed dose calculations

A framework is proposed for modelling the uncertainty in the measurement processes constituting the dosimetry chain that are involved in internal absorbed dose calculations. The starting point is the basic model for absorbed dose in a site of interest as the product of the cumulated activity and a dose factor. In turn, the cumulated activity is given by the area under a time-activity curve derived from a time sequence of activity values. Each activity value is obtained in terms of a count rate, a calibration factor and a recovery coefficient (a correction for partial volume effects). The method to determine the recovery coefficient and the dose factor, both of which are dependent on the size of the volume of interest (VOI), are described. Consideration is given to propagating estimates of the quantities concerned and their associated uncertainties through the dosimetry chain to obtain an estimate of mean absorbed dose in the VOI and its associated uncertainty. This approach is demonstrated in a clinical example.

Enhanced Bioavailability of Tadalafil after Intranasal Administration in Beagle Dogs

Tadalafil is an oral selective phosphodiesterase type-5 inhibitor with demonstrated efficacy and safety that is used to treat erectile dysfunction. The purpose of this study is to compare the pharmacokinetic properties of tadalafil after conventional oral tablet administration and novel intranasal administration in beagle dogs. Fourteen 13-month-old male beagle dogs were randomly divided into two groups, and were given 5 mg tadalafil orally or intranasally in a parallel design. Blood samples were collected before and 0.5, 1, 1.5, 2, 4, 6, 8, 12, 24, and 36 h after administration. The plasma concentration of tadalafil was determined via liquid chromatography-tandem mass spectrometry (LC-MS/MS). The systemic exposure and absorption rate of tadalafil were significantly greater in the intranasal administration group than in the oral administration group. A one-compartment model with first-order absorption and elimination was sufficient to explain the pharmacokinetic characteristics observed after both oral and intranasal administration. This study indicates that the development of tadalafil nasal delivery systems is feasible and may lead to better results than the conventional oral route.

Model selection criteria for dynamic brain PET studies

Background

 Several criteria exist to identify the optimal model for quantification of tracer kinetics. The purpose of this study was to evaluate the correspondence in kinetic model preference identification for brain PET studies among five model selection criteria: Akaike Information Criterion (AIC), AIC unbiased (AIC_C), model selection criterion (MSC), Schwartz Criterion (SC), and F-test.

Materials and Methods

Six tracers were evaluated: [¹¹C]FMZ, [¹¹C]GMOM, [¹¹C]PK11195, [¹¹C]Raclopride, [¹⁸F]FDG, and [¹¹C]PHT, including data from five subjects per tracer. Time activity curves (TACs) were analysed using six plasma input models: reversible single-tissue model (1T2k), irreversible two-tissue model (2T3k), and reversible two-tissue model (2T4k), all with and without blood volume fraction parameter (V_B). For each tracer and criterion, the percentage of TACs preferring a certain model was calculated.

Results

For all radiotracers, strong agreement was seen across the model selection criteria. The F-test was considered as the reference, as it is a frequently used hypothesis test. The F-test confirmed the AIC preferred model in 87% of all cases. The strongest (but minimal) disagreement across regional TACs was found when comparing AIC with AIC_C. Despite these regional discrepancies, same preferred kinetic model was obtained using all criteria, with an exception of one FMZ subject.

Conclusion

In conclusion, all five model selection criteria resulted in similar conclusions with only minor differences that did not affect overall model selection.

Electronic supplementary material

The online version of this article (10.1186/s40658-017-0197-0) contains supplementary material, which is available to authorized users.

Effect of dronedarone on the pharmacokinetics of carvedilol following oral administration to rats

Dronedarone is a CYP2D6 inhibitor; therefore, it is prudent to exercise caution when concurrently administering CYP2D6-metabolized β-blockers because of a lack of published data on potential drug interactions. The aim of this study was to investigate the effect of dronedarone on the pharmacokinetics of orally administered carvedilol in rats. Twenty male Sprague-Dawley rats were randomly divided into two groups and 10mg/kg carvedilol was administered to the rat with or without dronedarone pretreatment in a parallel design. Blood samples were collected before and after 0.25, 0.5, 0.75, 1, 2, 4, 6, 8, 12, and 24h of drug administration. The plasma concentration of carvedilol was determined using LC-MS/MS. The systemic exposure to carvedilol was significantly increased and elimination of carvedilol was significantly decreased in the dronedarone-pretreated rats than in the vehicle-pretreated rats. The one-compartment model with first-order absorption and elimination was sufficient to explain the pharmacokinetic characters after single oral administration of carvedilol to both vehicle-pretreated and dronedarone-pretreated rats. This study suggests that dronedarone inhibits CYP2D6-mediated carvedilol metabolism, and dose adjustment is needed in carvedilol and dronedarone combination therapy. Further studies are needed to clarify the effect of dronedarone on carvedilol and CYP2D6 substrates in clinical use.

Extracorporeal Membrane Oxygenation for Adult Community-Acquired Pneumonia: Outcomes and Predictors of Mortality

OBJECTIVES

Extracorporeal membrane oxygenation is a rescue therapy used to support severe cardiorespiratory failure. Data on outcomes from severe community-acquired pneumonia in adults receiving rescue extracorporeal membrane oxygenation are mainly confined to single-center experiences or specific pathogens. We examined data from the Extracorporeal Life Support Organisation registry to identify risk factors for poor outcomes in adult patients with community-acquired pneumonia.

DESIGN

Retrospective data analysis.

SETTING

Extracorporeal Life Support Organization Registry database.

PATIENTS

We collected deidentified data on adult patients (> 18 yr) receiving extracorporeal membrane oxygenation for community-acquired pneumonia between 2002 and 2012. Patients with incomplete data or brain death were excluded. The primary outcome measure was in-hospital mortality. Other measurements included demographic information, pre-extracorporeal membrane oxygenation mechanical ventilation and biochemical variables, inotrope requirements, extracorporeal membrane oxygenation mode, duration, and complications. Initial univariate analysis assessed potential associations between survival and various pre-extracorporeal membrane oxygenation and extracorporeal membrane oxygenation factors. Variables with p values of less than 0.1 were considered for logistic regression analysis to identify predictors of mortality.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN FINDINGS

One thousand fifty-five patients, who satisfied inclusion criteria, were included in the final analysis. There was an increase in the number of patients cannulated per annum over the 10-year period studied. Univariate analysis identified pre-extracorporeal membrane oxygenation and extracorporeal membrane oxygenation variables associated with high mortality. Further multiple regression analysis identified certain pre-extracorporeal membrane oxygenation factors as predictors of mortality, including duration of mechanical ventilation prior to extracorporeal membrane oxygenation, lower arterial pressure, fungal pneumonia, and advancing age. Type and duration of extracorporeal membrane oxygenation, neurologic complications, and presence of more than three complications on extracorporeal membrane oxygenation were also associated with higher mortality.

CONCLUSIONS

The majority (66%) of adults with community-acquired pneumonia supported on extracorporeal membrane oxygenation survived. Certain potentially modifiable risk factors were associated with increased mortality.

Subnanosecond Emission Dynamics of AT DNA Oligonucleotides

UV radiation creates excited electronic states in DNA that can decay to mutagenic photoproducts. When excited states return to the electronic ground state, photochemical injury is avoided. Understanding of the available relaxation pathways has advanced rapidly during the past decade, but there has been persistent uncertainty, and even controversy, over how to compare results from transient absorption and time-resolved emission experiments. Here, emission from single- and double-stranded AT DNA compounds excited at 265 nm was studied in aqueous solution using the time-correlated single photon counting technique. There is quantitative agreement between the emission lifetimes ranging from 50 to 200 ps and ones measured in transient absorption experiments, demonstrating that both techniques probe the same excited states. The results indicate that excitations with lifetimes of more than a few picoseconds are weakly emissive excimer and charge transfer states. Only a minute fraction of excitations persist beyond 1 ns in AT DNA strands at room temperature.

Investigating the Effect of Ligand Amount and Injected Therapeutic Activity: A Simulation Study for 177Lu-Labeled PSMA-Targeting Peptides

In molecular radiotherapy with ¹⁷⁷Lu-labeled prostate specific membrane antigen (PSMA) peptides, kidney and/or salivary glands doses limit the activity which can be administered. The aim of this work was to investigate the effect of the ligand amount and injected activity on the tumor-to-normal tissue biologically effective dose (BED) ratio for ¹⁷⁷Lu-labeled PSMA peptides. For this retrospective study, a recently developed physiologically based pharmacokinetic model was adapted for PSMA targeting peptides. General physiological parameters were taken from the literature. Individual parameters were fitted to planar gamma camera measurements (¹⁷⁷Lu-PSMA I&T) of five patients with metastasizing prostate cancer. Based on the estimated parameters, the pharmacokinetics of tumor, salivary glands, kidneys, total body and red marrow was simulated and time-integrated activity coefficients were calculated for different peptide amounts. Based on these simulations, the absorbed doses and BEDs for normal tissue and tumor were calculated for all activities leading to a maximal tolerable kidney BED of 10 Gy_2.5/cycle, a maximal salivary gland absorbed dose of 7.5 Gy/cycle and a maximal red marrow BED of 0.25 Gy₁₅/cycle. The fits yielded coefficients of determination > 0.85, acceptable relative standard errors and low parameter correlations. All estimated parameters were in a physiologically reasonable range. The amounts (for 2⁵−2⁹ nmol) and pertaining activities leading to a maximal tumor dose, considering the defined maximal tolerable doses to organs of risk, were calculated to be 272±253 nmol (452±420 μg) and 7.3±5.1 GBq. Using the actually injected amount (235±155 μg) and the same maximal tolerable doses, the potential improvement for the tumor BED was 1–3 fold. The results suggest that currently given amounts for therapy are in the appropriate order of magnitude for many lesions. However, for lesions with high binding site density or lower perfusion, optimizing the peptide amount and activity might improve the tumor-to-kidney and tumor-to-salivary glands BED ratio considerably.

Significance of the zero sum principle for circadian, homeostatic and allostatic regulation of sleep-wake state in the rat

Sleep-wake behavior exhibits diurnal rhythmicity, rebound responses to acute total sleep deprivation (TSD), and attenuated rebounds following chronic sleep restriction (CSR). We investigated how these long-term patterns of behavior emerge from stochastic short-term dynamics of state transition. Male Sprague-Dawley rats were subjected to TSD (1day×24h, N=9), or CSR (10days×18h TSD, N=7) using a rodent walking-wheel apparatus. One baseline day and one recovery day following TSD and CSR were analyzed. The implications of the zero sum principle were evaluated using a Markov model of sleep-wake state transition. Wake bout duration (a combined function of the probability of wake maintenance and proportional representations of brief and long wake) was a key variable mediating the baseline diurnal rhythms and post-TSD responses of all three states, and the attenuation of the post-CSR rebounds. Post-NREM state transition trajectory was an important factor in REM rebounds. The zero sum constraint ensures that a change in any transition probability always affects bout frequency and cumulative time of at least two, and usually all three, of wakefulness, NREM and REM. Neural mechanisms controlling wake maintenance may play a pivotal role in regulation and dysregulation of all three states.