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Nilsson, David
Publikasjoner (10 av 26) Visa alla publikasjoner
Machleid, R., Hoehse, M., Scholze, S., Mazarakis, K., Nilsson, D., Johansson, E., . . . Surowiec, I. (2024). Feasibility and performance of cross-clone Raman calibration models in CHO cultivation. Biotechnology Journal, 19(1), Article ID 2300289.
Åpne denne publikasjonen i ny fane eller vindu >>Feasibility and performance of cross-clone Raman calibration models in CHO cultivation
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2024 (engelsk)Inngår i: Biotechnology Journal, ISSN 1860-6768, E-ISSN 1860-7314, Vol. 19, nr 1, artikkel-id 2300289Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Raman spectroscopy is widely used in monitoring and controlling cell cultivations for biopharmaceutical drug manufacturing. However, its implementation for culture monitoring in the cell line development stage has received little attention. Therefore, the impact of clonal differences, such as productivity and growth, on the prediction accuracy and transferability of Raman calibration models is not yet well described. Raman OPLS models were developed for predicting titer, glucose and lactate using eleven CHO clones from a single cell line. These clones exhibited diverse productivity and growth rates. The calibration models were evaluated for clone-related biases using clone-wise linear regression analysis on cross validated predictions. The results revealed that clonal differences did not affect the prediction of glucose and lactate, but titer models showed a significant clone-related bias, which remained even after applying variable selection methods. The bias was associated with clonal productivity and lead to increased prediction errors when titer models were transferred to cultivations with productivity levels outside the range of their training data. The findings demonstrate the feasibility of Raman-based monitoring of glucose and lactate in cell line development with high accuracy. However, accurate titer prediction requires careful consideration of clonal characteristics during model development.

sted, utgiver, år, opplag, sider
John Wiley & Sons, 2024
Emneord
bioprocess development, bioprocess engineering, bioprocess monitoring, CHO cells
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-218135 (URN)10.1002/biot.202300289 (DOI)38015079 (PubMedID)2-s2.0-85178957570 (Scopus ID)
Tilgjengelig fra: 2023-12-18 Laget: 2023-12-18 Sist oppdatert: 2024-04-30bibliografisk kontrollert
Alinaghi, M., Nilsson, D., Singh, N., Höjer, A., Saedén, K. H. & Trygg, J. (2023). Near-infrared hyperspectral image analysis for monitoring the cheese-ripening process. Journal of Dairy Science, 106(11), 7407-7418
Åpne denne publikasjonen i ny fane eller vindu >>Near-infrared hyperspectral image analysis for monitoring the cheese-ripening process
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2023 (engelsk)Inngår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 106, nr 11, s. 7407-7418Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Ripening is the most crucial process step in cheese manufacturing and constitutes multiple biochemical alterations that describe the final cheese quality and its perceived sensory attributes. The assessment of the cheese-ripening process is challenging and requires the effective analysis of a multitude of biochemical changes occurring during the process. This study monitored the biochemical and sensory attribute changes of paraffin wax-covered long-ripening hard cheeses (n = 79) during ripening by collecting samples at different stages of ripening. Near-infrared hyperspectral (NIR-HS) imaging, together with free amino acid, chemical composition, and sensory attributes, was studied to monitor the biochemical changes during the ripening process. Orthogonal projection-based multivariate calibration methods were used to characterize ripening-related and orthogonal components as well as the distribution map of chemical components. The results approve the NIR-HS imaging as a rapid tool for monitoring cheese maturity during ripening. Moreover, the pixelwise evaluation of images shows the homogeneity of cheese maturation at different stages of ripening. Among the chemical compositions, fat content and moisture are the most important variables correlating to NIR-HS images during the ripening process.

sted, utgiver, år, opplag, sider
Elsevier, 2023
Emneord
cheese maturation, free amino acids, homogeneity distribution, near-infrared hyperspectral imaging, sensory analysis
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-215833 (URN)10.3168/jds.2023-23377 (DOI)37641350 (PubMedID)2-s2.0-85174425331 (Scopus ID)
Tilgjengelig fra: 2023-11-03 Laget: 2023-11-03 Sist oppdatert: 2023-11-03bibliografisk kontrollert
Sun, L., Lundh, Å., Höjer, A., Bernes, G., Nilsson, D., Johansson, M., . . . Dicksved, J. (2022). Milking system and premilking routines have strong effect on the microbial community in bulk tank milk. Journal of Dairy Science, 105(1), 123-139
Åpne denne publikasjonen i ny fane eller vindu >>Milking system and premilking routines have strong effect on the microbial community in bulk tank milk
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2022 (engelsk)Inngår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 105, nr 1, s. 123-139Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In this study, we investigated the variation in the microbial community present in bulk tank milk samples and the potential effect of different farm management factors. Bulk tank milk samples were collected repeatedly over one year from 42 farms located in northern Sweden. Total and thermoresistant bacteria counts and 16S rRNA gene-based amplicon sequencing were used to characterize microbial community composition. The microbial community was in general heterogeneous both within and between different farms and the community composition in the bulk tank milk was commonly dominated by Pseudomonas, Acinetobacter, Streptococcus, unclassified Peptostreptococcaceae, and Staphylococcus. Principal component analysis including farm factor variables and microbial taxa data revealed that the microbial community in milk was affected by type of milking system. Milk from farms using an automatic (robot) milking system (AMS) and loose housing showed different microbial community composition compared with milk from tiestall farms. A discriminant analysis model revealed that this difference was dependent on several microbial taxa. Among farms using an automatic milking system, there were further differences in the microbial community composition depending on the brand of the milking robot used. On tiestall farms, routines for teat preparation and cleaning of the milking equipment affected the microbial community composition in milk. Total bacteria count (TBC) in milk differed between the farm types, and TBC were higher on AMS than tiestall farms (log 4.05 vs. log 3.79 TBC/mL for AMS and tiestalls, respectively). Among tiestall farms, milk from farms using a chemical agent in connection to teat preparation and a more frequent use of acid to clean the milking equipment had lower TBC in milk, than milk from farms using water for teat preparation and a less frequent use of acid to clean the milking equipment (log 3.68 vs. 4.02 TBC/mL). There were no significant differences in the number of thermoresistant bacteria between farm types. The evaluated factors explained only a small proportion of total variation in the microbiota data, however, despite this, the study highlights the effect of routines associated with teat preparation and cleaning of the milking equipment on raw milk microbiota, irrespective of type of milking system used.

sted, utgiver, år, opplag, sider
Elsevier, 2022
Emneord
bulk tank milk microbiota, microbial community composition, milking system, premilking routines
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-191308 (URN)10.3168/jds.2021-20661 (DOI)000734351700011 ()34696914 (PubMedID)2-s2.0-85117776726 (Scopus ID)
Forskningsfinansiär
The Kamprad Family Foundation
Tilgjengelig fra: 2022-01-13 Laget: 2022-01-13 Sist oppdatert: 2022-07-14bibliografisk kontrollert
Norman, M., Nilsson, D., Trygg, J. & Håkansson, S. (2022). Perinatal risk factors for mortality in very preterm infants: A nationwide, population-based discriminant analysis. Acta Paediatrica, 111(8), 1526-1535
Åpne denne publikasjonen i ny fane eller vindu >>Perinatal risk factors for mortality in very preterm infants: A nationwide, population-based discriminant analysis
2022 (engelsk)Inngår i: Acta Paediatrica, ISSN 0803-5253, E-ISSN 1651-2227, Vol. 111, nr 8, s. 1526-1535Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Aim: To assess the strength of associations between interrelated perinatal risk factors and mortality in very preterm infants.

Methods: Information on all live-born infants delivered in Sweden at 22–31 weeks of gestational age (GA) from 2011 to 2019 was gathered from the Swedish Neonatal Quality Register, excluding infants with major malformations or not resuscitated because of anticipated poor prognosis. Twenty-seven perinatal risk factors available at birth were exposures and in-hospital mortality outcome. Orthogonal partial least squares discriminant analysis was applied to assess proximity between individual risk factors and mortality, and receiver operating characteristic (ROC) curves were used to estimate discriminant ability.

Results: In total, 638 of 8,396 (7.6%) infants died. Thirteen risk factors discriminated reduced mortality; the most important were higher Apgar scores at 5 and 10 min, GA and birthweight. Restricting the analysis to preterm infants <28 weeks’ GA (n = 2939, 16.9% mortality) added antenatal corticosteroid therapy as significantly associated with lower mortality. The area under the ROC curve (the C-statistic) using all risk factors was 0.86, as determined after both internal and external validation.

Conclusion: Apgar scores, gestational age and birthweight show stronger associations with mortality in very preterm infants than several other perinatal risk factors available at birth.

sted, utgiver, år, opplag, sider
John Wiley & Sons, 2022
Emneord
infant mortality, orthogonal partial least squares discriminant analysis, preterm infant
HSV kategori
Forskningsprogram
pediatrik
Identifikatorer
urn:nbn:se:umu:diva-193971 (URN)10.1111/apa.16356 (DOI)000782490500001 ()35397189 (PubMedID)2-s2.0-85128063703 (Scopus ID)
Tilgjengelig fra: 2022-05-03 Laget: 2022-05-03 Sist oppdatert: 2022-11-30bibliografisk kontrollert
Priyashantha, H., Lundh, Å., Höjer, A., Bernes, G., Nilsson, D., Hetta, M., . . . Johansson, M. (2021). Composition and properties of bovine milk: A study from dairy farms in northern Sweden; Part I. Effect of dairy farming system. Journal of Dairy Science, 104(8), 8582-8594
Åpne denne publikasjonen i ny fane eller vindu >>Composition and properties of bovine milk: A study from dairy farms in northern Sweden; Part I. Effect of dairy farming system
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2021 (engelsk)Inngår i: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 104, nr 8, s. 8582-8594Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This study was part of a larger project that aimed to understand the causes for increasing variation in cheese ripening in a cheese-producing region in northern Sweden. The influence of different on-farm factors on raw milk composition and properties was investigated and is described in this paper, whereas the monthly variation in the milk quality traits during 1 yr is described in our companion paper. The dairy farming systems on a total of 42 dairy farms were characterized through a questionnaire and farm visits. Milk from farm tanks was sampled monthly over 1 yr and analyzed for quality attributes important for cheese making. On applying principal component analyses to evaluate the variation in on-farm factors, different types of farms were distinguished. Farms with loose housing and automatic milking system (AMS) or milking parlor had a higher number of lactating cows, and predominantly Swedish Holstein (SH) breed. Farms associated with tiestalls had a lower number of lactating cows and breeds other than SH. Applying principal component analyses to study the variation in composition and properties of tank milk samples from farms revealed a tendency for the formation of 2 clusters: milk from farms with AMS or a milking parlor, and milk from farms with tiestall milking. The interaction between the milking system, housing system, and breed probably contributed to this grouping. Other factors that were used in the characterization of the farming systems only showed a minor influence on raw milk quality. Despite the interaction, milk from tiestall farms with various cow breeds had higher concentrations (g/100 g of milk) of fat (4.74) and protein (3.63), and lower lactose concentrations (4.67) than milk from farms with predominantly SH cows and AMS (4.32, 3.47, and 4.74 g/100 g of milk, respectively) or a milking parlor (4.47, 3.54, and 4.79 g/100 g of milk, respectively). Higher somatic cell count (195 × 103/mL) and lower free fatty acid concentration (0.75 mmol/100 g of fat) were observed in milk from farms with AMS than in milk from tiestall systems (150 × 103/mL and 0.83 mmol/100 g of fat, respectively). Type of farm influenced milk gel strength, with milk from farms with predominantly SH cows showing the lowest gel strength (65.0 Pa), but not a longer rennet coagulation time. Effects of dairy farming system (e.g., dominant breed, milking system, housing, and herd size) on milk quality attributes indicate a need for further studies to evaluate the in-depth effects of farm-related factors on milk quality attributes.

sted, utgiver, år, opplag, sider
Elsevier, 2021
Emneord
dominant breed, farm management factor, milk coagulation property, milking system, raw milk quality
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-186183 (URN)10.3168/jds.2020-19650 (DOI)000672155100017 ()2-s2.0-85109355528 (Scopus ID)
Forskningsfinansiär
The Kamprad Family Foundation, 20160098
Tilgjengelig fra: 2021-07-16 Laget: 2021-07-16 Sist oppdatert: 2023-09-05bibliografisk kontrollert
Skotare, T., Sjögren, R., Surowiec, I., Nilsson, D. & Trygg, J. (2020). Visualization of descriptive multiblock analysis. Journal of Chemometrics, 34(1), Article ID e3071.
Åpne denne publikasjonen i ny fane eller vindu >>Visualization of descriptive multiblock analysis
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2020 (engelsk)Inngår i: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 34, nr 1, artikkel-id e3071Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Understanding and making the most of complex data collected from multiple sources is a challenging task. Data integration is the procedure of describing the main features in multiple data blocks, and several methods for multiblock analysis have been previously developed, including OnPLS and JIVE. One of the main challenges is how to visualize and interpret the results of multiblock analyses because of the increased model complexity and sheer size of data. In this paper, we present novel visualization tools that simplify interpretation and overview of multiblock analysis. We introduce a correlation matrix plot that provides an overview of the relationships between blocks found by multiblock models. We also present a multiblock scatter plot, a metadata correlation plot, and a variation distribution plot, that simplify the interpretation of multiblock models. We demonstrate our visualizations on an industrial case study in vibration spectroscopy (NIR, UV, and Raman datasets) as well as a multiomics integration study (transcript, metabolite, and protein datasets). We conclude that our visualizations provide useful tools to harness the complexity of multiblock analysis and enable better understanding of the investigated system.

sted, utgiver, år, opplag, sider
John Wiley & Sons, 2020
Emneord
data fusion, descriptive analytics, multiblock analysis, OnPLS, visualization
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-152512 (URN)10.1002/cem.3071 (DOI)000509318600006 ()2-s2.0-85051048496 (Scopus ID)
Forskningsfinansiär
eSSENCE - An eScience CollaborationSwedish Research Council, 2016‐04376
Tilgjengelig fra: 2018-10-09 Laget: 2018-10-09 Sist oppdatert: 2020-03-12bibliografisk kontrollert
Skotare, T., Nilsson, D., Xiong, S., Geladi, P. & Trygg, J. (2019). Joint and unique multiblock analysis for integration and calibration transfer of NIR instruments. Analytical Chemistry, 91(5), 3516-3524
Åpne denne publikasjonen i ny fane eller vindu >>Joint and unique multiblock analysis for integration and calibration transfer of NIR instruments
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2019 (engelsk)Inngår i: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 91, nr 5, s. 3516-3524Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In the present paper, we introduce an end-to-end workflow called joint and unique multiblock analysis (JUMBA), which allows multiple sources of data to be analyzed simultaneously to better understand how they complement each other. In near-infrared (NIR) spectroscopy, calibration models between NIR spectra and responses are used to replace wet-chemistry methods, and the models tend to be instrument-specific. Calibration-transfer techniques are used for standardization of NIR-instrumentation, enabling the use of one model on several instruments. The current paper investigates both the similarities and differences among a variety of NIR instruments using JUMBA. We demonstrate JUMBA on both a previously unpublished data set in which five NIR instruments measured mushroom substrate and a publicly available data set measured on corn samples. We found that NIR spectra from different instrumentation largely shared the same underlying structures, an insight we took advantage of to perform calibration transfer. The proposed JUMBA transfer displayed excellent calibration-transfer performance across the two analyzed data sets and outperformed existing methods in terms of both prediction accuracy and stability. When applied to a multi-instrument environment, JUMBA transfer can integrate all instruments in the same model and will ensure higher consistency among them compared with existing calibration-transfer methods.

sted, utgiver, år, opplag, sider
Washington: American Chemical Society (ACS), 2019
Emneord
near-infrared spectroscopy, spent mushroom compost, multivariate calibration, water-content, standardization, regression, vegetation, models, ONPLS
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-156707 (URN)10.1021/acs.analchem.8b05188 (DOI)000460709200047 ()30758178 (PubMedID)2-s2.0-85062418105 (Scopus ID)
Prosjekter
Bio4Energy
Forskningsfinansiär
Bio4Energy
Tilgjengelig fra: 2019-02-25 Laget: 2019-02-25 Sist oppdatert: 2020-07-01bibliografisk kontrollert
Peterson, G., O'Leary, S., Nilsson, D., Moodie, K., Tucker, K., Trygg, J. & Peolsson, A. (2019). Ultrasound imaging of dorsal neck muscles with speckle tracking analyses: the relationship between muscle deformation and force. Scientific Reports, 9, Article ID 13688.
Åpne denne publikasjonen i ny fane eller vindu >>Ultrasound imaging of dorsal neck muscles with speckle tracking analyses: the relationship between muscle deformation and force
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2019 (engelsk)Inngår i: Scientific Reports, E-ISSN 2045-2322, Vol. 9, artikkel-id 13688Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The development of methods of non-invasive measurement of neck muscle function remains a priority in the clinical sciences. In this study, dorsal neck muscle deformation vs time curves (deformation area) were evaluated against incremental force, recorded from non-invasive real-time ultrasound measurement. The results revealed subject-specific moderate to strong linear or non-linear relationships between deformation and force. Test-retest variability showed strong reliability for all five neck muscles summed together and fair to good reliability for the five muscles evaluated separately. Multivariate statistics were used to analyse the interactions between the dorsal neck muscles during different percentages of maximal voluntary contraction (MVC). Low force (10-20% MVC) was related to muscle shortening; higher force (40-80% MVC) showed combination of shortening and elongation deformation in the muscle interactions. The muscle interactions during isometric MVC test were subject-specific, with different combinations and deformations of the five neck muscles. Force >= 40% MVC were associated with a forward movement of the cervical spine that affected the ultrasound measurement of the dorsal neck muscles. Ultrasound with speckle-tracking analyses may be best used to detect low levels (<40% MVC) of neck muscle activity.

sted, utgiver, år, opplag, sider
Nature Publishing Group, 2019
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-164049 (URN)10.1038/s41598-019-49916-1 (DOI)000487216300008 ()31548564 (PubMedID)2-s2.0-85072551115 (Scopus ID)
Tilgjengelig fra: 2019-10-15 Laget: 2019-10-15 Sist oppdatert: 2023-03-24bibliografisk kontrollert
Peterson, G., Nilsson, D., Trygg, J. & Peolsson, A. (2018). Neck-specific exercise improves impaired interactions between ventral neck muscles in chronic whiplash: A randomized controlled ultrasound study. Scientific Reports, 8, Article ID 9649.
Åpne denne publikasjonen i ny fane eller vindu >>Neck-specific exercise improves impaired interactions between ventral neck muscles in chronic whiplash: A randomized controlled ultrasound study
2018 (engelsk)Inngår i: Scientific Reports, E-ISSN 2045-2322, Vol. 8, artikkel-id 9649Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Chronic pain and disability is common in whiplash-associated disorders (WAD), leading to personal suffering, sick leave, and social cost. The cervical spine is heavily dependent on muscular support and whiplash injury can cause damage to the neck muscles, but diagnostic tools to measure neck muscle impairment and evaluate exercise interventions are lacking. Therefore, the present study investigated ventral neck muscle interactions in 26 individuals with chronic WAD randomized to neck-specific exercise (NSE) or remaining on a waiting list (WL) in 3 months. We performed real-time, non-invasive ultrasound measurements with speckle tracking analysis and calculated the deformation area and deformation rate in three ventral neck muscles. Multivariate statistics were used to analyse interactions between the muscles. After 3 months of NSE, significant improvements were observed in neck muscle interactions and pain intensity in the NSE group compared to the WL group. Thus, this study demonstrates that non-invasive ultrasound can be a diagnostic tool for muscle impairment and used to evaluate exercise interventions in WAD and stands to make a breakthrough for better management in chronic WAD.

sted, utgiver, år, opplag, sider
Nature Publishing Group, 2018
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-150773 (URN)10.1038/s41598-018-27685-7 (DOI)000436078500012 ()29941911 (PubMedID)2-s2.0-85049198473 (Scopus ID)
Tilgjengelig fra: 2018-08-31 Laget: 2018-08-31 Sist oppdatert: 2023-03-24bibliografisk kontrollert
Kuess, P., Andrzejewski, P., Nilsson, D., Georg, P., Knoth, J., Susani, M., . . . Nyholm, T. (2017). Association between pathology and texture features of multi parametric MRI of the prostate. Physics in Medicine and Biology, 62(19), 7833-7854
Åpne denne publikasjonen i ny fane eller vindu >>Association between pathology and texture features of multi parametric MRI of the prostate
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2017 (engelsk)Inngår i: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 62, nr 19, s. 7833-7854Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The role of multi-parametric (mp)MRI in the diagnosis and treatment of prostate cancer has increased considerably. An alternative to visual inspection of mpMRI is the evaluation using histogram-based (first order statistics) parameters and textural features (second order statistics). The aims of the present work were to investigate the relationship between benign and malignant sub-volumes of the prostate and textures obtained from mpMR images. The performance of tumor prediction was investigated based on the combination of histogram-based and textural parameters. Subsequently, the relative importance of mpMR images was assessed and the benefit of additional imaging analyzed. Finally, sub-structures based on the PI-RADS classification were investigated as potential regions to automatically detect maligned lesions. Twenty-five patients who received mpMRI prior to radical prostatectomy were included in the study. The imaging protocol included T2, DWI, and DCE. Delineation of tumor regions was performed based on pathological information. First and second order statistics were derived from each structure and for all image modalities. The resulting data were processed with multivariate analysis, using PCA (principal component analysis) and OPLS-DA (orthogonal partial least squares discriminant analysis) for separation of malignant and healthy tissue. PCA showed a clear difference between tumor and healthy regions in the peripheral zone for all investigated images. The predictive ability of the OPLS-DA models increased for all image modalities when first and second order statistics were combined. The predictive value reached a plateau after adding ADC and T2, and did not increase further with the addition of other image information. The present study indicates a distinct difference in the signatures between malign and benign prostate tissue. This is an absolute prerequisite for automatic tumor segmentation, but only the first step in that direction. For the specific identified signature, DCE did not add complementary information to T2 and ADC maps.

Emneord
textural features, mpMRI, prostate cancer, haralick texture features
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-142316 (URN)10.1088/1361-6560/aa884d (DOI)000425829000002 ()28837046 (PubMedID)2-s2.0-85029886940 (Scopus ID)
Tilgjengelig fra: 2017-11-27 Laget: 2017-11-27 Sist oppdatert: 2023-03-23bibliografisk kontrollert
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