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Nielsen, Elisabet I.
Alternative names
Publications (10 of 35) Show all publications
Thorsted, A., Bouchene, S., Tano, E., Castegren, M., Lipcsey, M., Sjölin, J., . . . Nielsen, E. I. (2019). A non-linear mixed effect model for innate immune response: In vivo kinetics of endotoxin and its induction of the cytokines tumor necrosis factor alpha and interleukin-6. PLoS ONE, 14(2), Article ID e0211981.
Open this publication in new window or tab >>A non-linear mixed effect model for innate immune response: In vivo kinetics of endotoxin and its induction of the cytokines tumor necrosis factor alpha and interleukin-6
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2019 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 14, no 2, article id e0211981Article in journal (Refereed) Published
Abstract [en]

Endotoxin, a component of the outer membrane of Gram-negative bacteria, has been extensively studied as a stimulator of the innate immune response. However, the temporal aspects and exposure-response relationship of endotoxin and resulting cytokine induction and tolerance development is less well defined. The aim of this work was to establish an in silico model that simultaneously captures and connects the in vivo time-courses of endotoxin, tumor necrosis factor alpha (TNF-alpha), interleukin-6 (IL-6), and associated tolerance development. Data from six studies of porcine endotoxemia in anesthetized piglets (n = 116) were combined and used in the analysis, with purified endotoxin (Escherichia coli O111: B4) being infused intravenously for 1-30 h in rates of 0.063-16.0 mu g/kg/h across studies. All data were modelled simultaneously by means of importance sampling in the non-linear mixed effects modelling software NONMEM. The infused endotoxin followed one-compartment disposition and non-linear elimination, and stimulated the production of TNF-alpha to describe the rapid increase in plasma concentration. Tolerance development, observed as declining TNF-alpha concentration with continued infusion of endotoxin, was also driven by endotoxin as a concentration-dependent increase in the potency parameter related to TNF-alpha production (EC50). Production of IL-6 was stimulated by both endotoxin and TNF-a, and four consecutive transit compartments described delayed increase in plasma IL-6. A model which simultaneously account for the time-courses of endotoxin and two immune response markers, the cytokines TNF-alpha and IL-6, as well as the development of endotoxin tolerance, was successfully established. This model-based approach is unique in its description of the time-courses and their interrelation and may be applied within research on immune response to bacterial endotoxin, or in pre-clinical pharmaceutical research when dealing with study design or translational aspects.

National Category
Physiology
Identifiers
urn:nbn:se:uu:diva-379038 (URN)10.1371/journal.pone.0211981 (DOI)000459330800014 ()30789941 (PubMedID)
Funder
Swedish Foundation for Strategic Research
Available from: 2019-03-11 Created: 2019-03-11 Last updated: 2019-03-11Bibliographically approved
Ungphakorn, W. (2018). Automated time-lapse microscopy a novel method for screening of antibiotic combination effects against multidrug-resistant Gram-negative bacteria. Clinical Microbiology and Infection, 24(7), Article ID 778.e7.
Open this publication in new window or tab >>Automated time-lapse microscopy a novel method for screening of antibiotic combination effects against multidrug-resistant Gram-negative bacteria
2018 (English)In: Clinical Microbiology and Infection, ISSN 1198-743X, E-ISSN 1469-0691, Vol. 24, no 7, article id 778.e7Article in journal (Refereed) Published
Abstract [en]

Objectives

Antibiotic combinations are often used for carbapenemase-producing Enterobacteriaceae (CPE) but more data are needed on the optimal selection of drugs. This study aimed to evaluate the feasibility of a novel automated method based on time-lapse microscopy (the oCelloScope, Philips BioCell A/S, Allerød, Denmark) to determine in vitro combination effects against CPE and to discuss advantages and limitations of the oCelloScope in relation to standard methods.

Methods

Four Klebsiella pneumoniae and two Escherichia coli were exposed to colistin, meropenem, rifampin and tigecycline, alone and in combination. In the oCelloScope experiments, a background corrected absorption (BCA) value of ≤8 at 24 h was used as a primary cut-off indicating inhibition of bacterial growth. A new approach was used to determine synergy, indifference and antagonism based on the number of objects (bacteria) in the images. Static time–kill experiments were performed for comparison.

Results

The time–kill experiments showed synergy with 12 of 36 regimens, most frequently with colistin plus rifampin. BCA values ≤8 consistently correlated with 24-h bacterial concentrations ≤6 log10 CFU/mL. The classification of combination effects agreed with the time–kill results for 33 of 36 regimens. In three cases, the interactions could not be classified with the microscopy method because of low object counts.

Conclusions

Automated time-lapse microscopy can accurately determine the effects of antibiotic combinations. The novel method is highly efficient compared with time–kill experiments, more informative than checkerboards and can be useful to accelerate the screening for combinations active against multidrug-resistant Gram-negative bacteria.

Keywords
Antibiotic combinations, Carbapenemases, Escherichia coli, Image analysis, Klebsiella pneumoniae, oCelloScope, Synergy, Time–kill experiments
National Category
Infectious Medicine
Identifiers
urn:nbn:se:uu:diva-343647 (URN)10.1016/j.cmi.2017.10.029 (DOI)000436640800021 ()29108951 (PubMedID)
Funder
Swedish Research CouncilAFA InsurancePublic Health Agency of Sweden
Available from: 2018-02-28 Created: 2018-02-28 Last updated: 2018-09-18Bibliographically approved
Senek, M., Nyholm, D. & Nielsen, E. I. (2018). Population pharmacokinetics of levodopa/carbidopa microtablets in healthy subjects and Parkinson’s disease patients. European Journal of Clinical Pharmacology, 74(10), 1299-1307
Open this publication in new window or tab >>Population pharmacokinetics of levodopa/carbidopa microtablets in healthy subjects and Parkinson’s disease patients
2018 (English)In: European Journal of Clinical Pharmacology, ISSN 0031-6970, E-ISSN 1432-1041, Vol. 74, no 10, p. 1299-1307Article in journal (Refereed) Published
Abstract [en]

Objectives: Low dose, dispersible, levodopa/carbidopa microtablets with an automatic dose dispenser have been developed to facilitate individualized levodopa treatment. The aim of this study was to characterize the pharmacokinetics (PK) of levodopa and carbidopa after microtablet administration, and evaluate the impact of potential covariates.

Methods: The population PK analysis involved data from 18 healthy subjects and 18 Parkinson's disease patients included in two single-dose, open-label levodopa/carbidopa microtablet studies. The analysis was carried out using non-linear mixed effects modeling. Bodyweight was included on all disposition parameters according to allometric scaling. Potential influence of additional covariates was investigated using graphical evaluation and adjusted adaptive least absolute shrinkage and selection operator.

Results: Dispositions of levodopa and carbidopa were best described by a two- and one-compartment model respectively. Double-peak profiles were described using two parallel absorption compartments. Levodopa apparent clearance was found to decrease with increasing carbidopa dose (15% lower with 75 compared to 50mg of carbidopa) and disease stage (by 18% for Hoehn and Yahr 1 to 4). Carbidopa apparent clearance was found to decrease with age (28% between the age of 60 and 80years). An external evaluation showed the model to be able to reasonably well predict levodopa concentrations following multiple-dose microtablet administration in healthy subjects.

Conclusions: The presented models adequately described the PK of levodopa and carbidopa, following microtablet administration. The developed model may in the future be combined with a pharmacokinetic-pharmacodynamic target and used for individualized dose selection, utilizing the flexibility offered by the microtablets.

National Category
Neurology
Identifiers
urn:nbn:se:uu:diva-343034 (URN)10.1007/s00228-018-2497-2 (DOI)000444387700009 ()29882153 (PubMedID)
Funder
VINNOVA
Available from: 2018-02-25 Created: 2018-02-25 Last updated: 2018-11-13Bibliographically approved
Khan, D., Lagerbäck, P., Malmberg, C., Kristoffersson, A., Gullberg, E., Cao, S., . . . Friberg, L. E. (2018). Predicting mutant selection in competition experiments with ciprofloxacin-exposed Escherichia coli. International Journal of Antimicrobial Agents, 51(3), 399-406, Article ID S0924-8579(17)30392-8.
Open this publication in new window or tab >>Predicting mutant selection in competition experiments with ciprofloxacin-exposed Escherichia coli
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2018 (English)In: International Journal of Antimicrobial Agents, ISSN 0924-8579, E-ISSN 1872-7913, Vol. 51, no 3, p. 399-406, article id S0924-8579(17)30392-8Article in journal (Refereed) Published
Abstract [en]

Predicting competition between antibiotic-susceptible wild-type (WT) and less susceptible mutant (MT) bacteria is valuable for understanding how drug concentrations influence the emergence of resistance. Pharmacokinetic/pharmacodynamic (PK/PD) models predicting the rate and extent of takeover of resistant bacteria during different antibiotic pressures can thus be a valuable tool in improving treatment regimens. The aim of this study was to evaluate a previously developed mechanism-based PK/PD model for its ability to predict in vitro mixed-population experiments with competition between Escherichia coli (E. coli) WT and three well-defined E. coli resistant MTs when exposed to ciprofloxacin. Model predictions for each bacterial strain and ciprofloxacin concentration were made for in vitro static and dynamic time–kill experiments measuring CFU (colony forming units)/mL up to 24 h with concentrations close to or below the minimum inhibitory concentration (MIC), as well as for serial passage experiments with concentrations well below the MIC measuring ratios between the two strains with flow cytometry. The model was found to reasonably well predict the initial bacterial growth and killing of most static and dynamic time–kill competition experiments without need for parameter re-estimation. With parameter re-estimation of growth rates, an adequate fit was also obtained for the 6-day serial passage competition experiments. No bacterial interaction in growth was observed. This study demonstrates the predictive capacity of a PK/PD model and further supports the application of PK/PD modelling for prediction of bacterial kill in different settings, including resistance selection.

Keywords
Ciprofloxacin, Escherichia coli, PK/PD modelling, PK/PD predictions, Pharmacokinetics/Pharmacodynamics, Time–kill experiments
National Category
Pharmaceutical Sciences Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-343607 (URN)10.1016/j.ijantimicag.2017.10.019 (DOI)000427582000016 ()29127049 (PubMedID)
Funder
Swedish Research CouncilSwedish Foundation for Strategic Research EU, FP7, Seventh Framework Programme, FP7/2007-2013
Available from: 2018-02-28 Created: 2018-02-28 Last updated: 2018-05-18Bibliographically approved
Mangles, S., Rea, C., Madan, B., Nielsen, E. I., Jönsson, S., Needham, J., . . . Rangarajanl, S. (2018). Real life experiences of a PK dosing study: Challenges and lessons learned [Letter to the editor]. Haemophilia, 24(3), E145-E148
Open this publication in new window or tab >>Real life experiences of a PK dosing study: Challenges and lessons learned
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2018 (English)In: Haemophilia, ISSN 1351-8216, E-ISSN 1365-2516, Vol. 24, no 3, p. E145-E148Article in journal, Letter (Other academic) Published
Place, publisher, year, edition, pages
John Wiley & Sons, 2018
National Category
Hematology
Identifiers
urn:nbn:se:uu:diva-366682 (URN)10.1111/hae.13470 (DOI)000434111800017 ()29626381 (PubMedID)
Available from: 2018-11-23 Created: 2018-11-23 Last updated: 2018-11-23Bibliographically approved
Brill, M. J. E., Kristoffersson, A., Zhao, C., Nielsen, E. I. & Friberg, L. E. (2018). Semi-mechanistic pharmacokinetic-pharmacodynamic modelling of antibiotic drug combinations. Clinical Microbiology and Infection, 24(7), 697-706
Open this publication in new window or tab >>Semi-mechanistic pharmacokinetic-pharmacodynamic modelling of antibiotic drug combinations
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2018 (English)In: Clinical Microbiology and Infection, ISSN 1198-743X, E-ISSN 1469-0691, Vol. 24, no 7, p. 697-706Article, review/survey (Refereed) Published
Abstract [en]

Background: Deriving suitable dosing regimens for antibiotic combination therapy poses several challenges as the drug interaction can be highly complex, the traditional pharmacokinetic-pharmacodynamic (PKPD) index methodology cannot be applied straightforwardly, and exploring all possible dose combinations is unfeasible. Therefore, semi-mechanistic PKPD models developed based on in vitro single and combination experiments can be valuable to suggest suitable combination dosing regimens. Aims: To outline how the interaction between two antibiotics has been characterized in semi-mechanistic PKPD models. We also explain how such models can be applied to support dosing regimens and design future studies. Sources: PubMed search for published semi-mechanistic PKPD models of antibiotic drug combinations. Content: Thirteen publications were identified where ten had applied subpopulation synergy to characterize the combined effect, i.e. independent killing rates for each drug and bacterial subpopulation. We report the various types of interaction functions that have been used to describe the combined drug effects and that characterized potential deviations from additivity under the PKPD model. Simulations from the models had commonly been performed to compare single versus combined dosing regimens and/or to propose improved dosing regimens.

Keywords
Antibiotics, Drug combinations, Interaction, Semi-mechanistic pharmacokinetic-pharmacodynamic modelling, Simulations
National Category
Infectious Medicine
Identifiers
urn:nbn:se:uu:diva-366616 (URN)10.1016/j.cmi.2017.11.023 (DOI)000436640800008 ()29229429 (PubMedID)
Funder
Swedish Research Council, 2015-06826EU, FP7, Seventh Framework Programme, Health-F3-2011-278348
Available from: 2018-11-26 Created: 2018-11-26 Last updated: 2018-11-26Bibliographically approved
Netterberg, I., Karlsson, M. O., Nielsen, E. I., Quartino, A. L., Lindman, H. & Friberg, L. E. (2018). The risk of febrile neutropenia in breast cancer patients following adjuvant chemotherapy is predicted by the time course of interleukin-6 and C-reactive protein by modelling.. British Journal of Clinical Pharmacology, 84(3), 490-500
Open this publication in new window or tab >>The risk of febrile neutropenia in breast cancer patients following adjuvant chemotherapy is predicted by the time course of interleukin-6 and C-reactive protein by modelling.
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2018 (English)In: British Journal of Clinical Pharmacology, ISSN 0306-5251, E-ISSN 1365-2125, Vol. 84, no 3, p. 490-500Article in journal (Refereed) Published
Abstract [en]

AIMS: Early identification of patients with febrile neutropenia (FN) is desirable for initiation of preventive treatment, such as with antibiotics. In this study, the time courses of two inflammation biomarkers, interleukin (IL)-6 and C-reactive protein (CRP), following adjuvant chemotherapy of breast cancer, were characterized. The potential to predict development of FN by IL-6 and CRP, and other model-derived and clinical variables, was explored.

METHODS: The IL-6 and CRP time courses in cycles 1 and 4 of breast cancer treatment were described by turnover models where the probability for an elevated production following initiation of chemotherapy was estimated. Parametric time-to-event models were developed to describe FN occurrence to assess: (i) predictors available before chemotherapy is initiated; (ii) predictors available before FN occurs; and (iii) predictors available when FN occurs.

RESULTS: The IL-6 and CRP time courses were successfully characterized with peak IL-6 typically occurring 2 days prior to CRP peak. Of all evaluated variables the CRP time course was most closely associated with the occurrence of FN. Since the CRP peak typically occurred at the time of FN diagnosis it will, however, have limited value for identifying the need for preventive treatment. The time course of IL-6 was the predictor that could best forecast FN events. Of the variables available at baseline, age was the best, although in comparison a relatively weak, predictor.

CONCLUSIONS: The developed models add quantitative knowledge about IL-6 and CRP and their relationship to the development of FN. The study suggests that IL-6 may have potential as a clinical predictor of FN if monitored during myelosuppressive chemotherapy.

Keywords
C-reactive protein, NONMEM, adjuvant chemotherapy, febrile neutropenia, interleukin-6
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:uu:diva-343812 (URN)10.1111/bcp.13477 (DOI)000424877400009 ()29178353 (PubMedID)
Funder
Swedish Cancer Society
Available from: 2018-03-01 Created: 2018-03-01 Last updated: 2018-04-09Bibliographically approved
Johansson, A., Lindstedt, D., Roman, M., Thelander, G., Nielsen, E. I., Lennborn, U., . . . Kugelberg, F. C. (2017). A non-fatal intoxication and seven deaths involving the dissociative drug 3-MeO-PCP. Forensic Science International, 275, 76-82
Open this publication in new window or tab >>A non-fatal intoxication and seven deaths involving the dissociative drug 3-MeO-PCP
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2017 (English)In: Forensic Science International, ISSN 0379-0738, E-ISSN 1872-6283, Vol. 275, p. 76-82Article in journal (Refereed) Published
Abstract [en]

Introduction: 3-methoxyphencyclidine (3-MeO-PCP) appeared on the illicit drug market in 2011 and is an analogue of phencyclidine, which exhibits anesthetic, analgesic and hallucinogenic properties. In this paper, we report data from a non-fatal intoxication and seven deaths involving 3-MeO-PCP in Sweden during the period March 2014 until June 2016. Case descriptions: The non-fatal intoxication case, a 19-year-old male with drug problems and a medical history of depression, was found awake but tachycardic, hypertensive, tachypnoeic and catatonic at home. After being hospitalized, his condition worsened as he developed a fever and lactic acidosis concomitant with psychomotor agitation and hallucinations. After 22 h of intensive care, the patient had made a complete recovery. During his hospitalization, a total of four blood samples were collected at different time points. The seven autopsy cases, six males and one female, were all in their twenties to thirties with psychiatric problems and/or an ongoing drug abuse. Methods: 3-MeO-PCP was identified with liquid chromatography (LC)/time-of-flight technology and quantified using LC-tandem mass spectrometry. Results: In the clinical case, the concentration of 3-MeO-PCP was 0.14 mu g/g at admission, 0.08 mu g/g 2.5 h after admission, 0.06 mu g/g 5 h after admission and 0.04 mu g/g 17 h after admission. The half-life of 3-MeO-PCP was estimated to 11 h. In the autopsy cases, femoral blood concentrations ranged from 0.05 mu g/g to 0.38 mu g/g. 3-MeO-PCP was the sole finding in the case with the highest concentration and the cause of death was established as intoxication with 3-MeO-PCP. In the remaining six autopsy cases, other medications and drugs of abuse were present as well. Conclusion: Despite being scheduled in January 2015, 3-MeO-PCP continues to be abused in Sweden. Exposure to 3-MeO-PCP may cause severe adverse events and even death, especially if the user does not receive life-supporting treatment.

Place, publisher, year, edition, pages
ELSEVIER IRELAND LTD, 2017
Keywords
Dissociative drugs, Phencyclidine, 3-MeO-PCP, Intoxication, Postmortem blood concentrations
National Category
Forensic Science
Identifiers
urn:nbn:se:uu:diva-330757 (URN)10.1016/j.forsciint.2017.02.034 (DOI)000404011100011 ()28324770 (PubMedID)
Available from: 2017-10-03 Created: 2017-10-03 Last updated: 2017-10-03Bibliographically approved
Sadiq, M. W., Nielsen, E. I., Khachman, D., Conil, J.-M., Georges, B., Houin, G., . . . Friberg, L. E. (2017). A whole-body physiologically based pharmacokinetic (WB-PBPK) model of ciprofloxacin: a step towards predicting bacterial killing at sites of infection.. Journal of Pharmacokinetics and Pharmacodynamics, 44(2), 69-79
Open this publication in new window or tab >>A whole-body physiologically based pharmacokinetic (WB-PBPK) model of ciprofloxacin: a step towards predicting bacterial killing at sites of infection.
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2017 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 44, no 2, p. 69-79Article in journal (Refereed) Published
Abstract [en]

The purpose of this study was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model for ciprofloxacin for ICU patients, based on only plasma concentration data. In a next step, tissue and organ concentration time profiles in patients were predicted using the developed model. The WB-PBPK model was built using a non-linear mixed effects approach based on data from 102 adult intensive care unit patients. Tissue to plasma distribution coefficients (Kp) were available from the literature and used as informative priors. The developed WB-PBPK model successfully characterized both the typical trends and variability of the available ciprofloxacin plasma concentration data. The WB-PBPK model was thereafter combined with a pharmacokinetic-pharmacodynamic (PKPD) model, developed based on in vitro time-kill data of ciprofloxacin and Escherichia coli to illustrate the potential of this type of approach to predict the time-course of bacterial killing at different sites of infection. The predicted unbound concentration-time profile in extracellular tissue was driving the bacterial killing in the PKPD model and the rate and extent of take-over of mutant bacteria in different tissues were explored. The bacterial killing was predicted to be most efficient in lung and kidney, which correspond well to ciprofloxacin's indications pneumonia and urinary tract infections. Furthermore, a function based on available information on bacterial killing by the immune system in vivo was incorporated. This work demonstrates the development and application of a WB-PBPK-PD model to compare killing of bacteria with different antibiotic susceptibility, of value for drug development and the optimal use of antibiotics.

National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-318715 (URN)10.1007/s10928-016-9486-9 (DOI)000399036400002 ()27578330 (PubMedID)
Funder
Swedish Foundation for Strategic Research EU, FP7, Seventh Framework Programme, 115156
Available from: 2017-03-28 Created: 2017-03-28 Last updated: 2018-01-13Bibliographically approved
Nielsen, E. I., Khan, D. D., Cao, S., Lustig, U., Hughes, D., Andersson, D. I. & Friberg, L. E. (2017). Can a pharmacokinetic/pharmacodynamic (PKPD) model be predictive across bacterial densities and strains?: External evaluation of a PKPD model describing longitudinal in vitro data. Journal of Antimicrobial Chemotherapy, 72(11), 3108-3116
Open this publication in new window or tab >>Can a pharmacokinetic/pharmacodynamic (PKPD) model be predictive across bacterial densities and strains?: External evaluation of a PKPD model describing longitudinal in vitro data
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2017 (English)In: Journal of Antimicrobial Chemotherapy, ISSN 0305-7453, E-ISSN 1460-2091, Vol. 72, no 11, p. 3108-3116Article in journal (Refereed) Published
Abstract [en]

Background: Pharmacokinetic/pharmacodynamic (PKPD) models developed based on data from in vitro time-kill experiments have been suggested to contribute to more efficient drug development programmes and better dosing strategies for antibiotics. However, for satisfactory predictions such models would have to show good extrapolation properties. Objectives: To evaluate if a previously described mechanism-based PKPD model was able also to predict drug efficacy for higher bacterial densities and across bacterial strains. Methods: A PKPD model describing the efficacy of ciprofloxacin on Escherichia coli was evaluated. The predictive performance of the model was evaluated across several experimental conditions with respect to: (i) bacterial start inoculum ranging from the standard of similar to 10(6) cfu/mL up to late stationary-phase cultures; and (ii) efficacy for seven additional strains (three laboratory and four clinical strains), not included during the model development process, based only on information regarding their MIC. Model predictions were performed according to the intended experimental protocol and later compared with observed bacterial counts. Results: The mechanism-based PKPD model structure developed based on data from standard start inoculum experiments was able to accurately describe the inoculum effect. The model successfully predicted the time course of drug efficacy for additional laboratory and clinical strains based on only the MIC values. The model structure was further developed to better describe the stationary phase data. Conclusions: This study supports the use of mechanism-based PKPD models based on preclinical data for predictions of untested scenarios.

Place, publisher, year, edition, pages
OXFORD UNIV PRESS, 2017
National Category
Pharmaceutical Sciences Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:uu:diva-340705 (URN)10.1093/jac/dkx269 (DOI)000413464200019 ()28961946 (PubMedID)
Funder
Swedish Foundation for Strategic Research
Available from: 2018-02-21 Created: 2018-02-21 Last updated: 2018-02-21Bibliographically approved
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