| 1. |
- Locke, Adam E, et al.
(författare)
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Genetic studies of body mass index yield new insights for obesity biology.
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 197-401
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Tidskriftsartikel (refereegranskat)abstract
- Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
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| 2. |
- Abramian, David, 1992-, et al.
(författare)
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Evaluation of inverse treatment planning for gamma knife radiosurgery using fMRI brain activation maps as organs at risk
- 2023
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Ingår i: Medical physics (Lancaster). - : WILEY. - 0094-2405. ; 50:9, s. 5297-5311
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Tidskriftsartikel (refereegranskat)abstract
- Background: Stereotactic radiosurgery (SRS) can be an effective primary or adjuvant treatment option for intracranial tumors. However, it carries risks of various radiation toxicities, which can lead to functional deficits for the patients. Current inverse planning algorithms for SRS provide an efficient way for sparing organs at risk (OARs) by setting maximum radiation dose constraints in the treatment planning process.Purpose: We propose using activation maps from functional MRI (fMRI) to map the eloquent regions of the brain and define functional OARs (fOARs) for Gamma Knife SRS treatment planning.Methods: We implemented a pipeline for analyzing patient fMRI data, generating fOARs from the resulting activation maps, and loading them onto the GammaPlan treatment planning software. We used the Lightning inverse planner to generate multiple treatment plans from open MRI data of five subjects, and evaluated the effects of incorporating the proposed fOARs.Results: The Lightning optimizer designs treatment plans with high conformity to the specified parameters. Setting maximum dose constraints on fOARs successfully limits the radiation dose incident on them, but can have a negative impact on treatment plan quality metrics. By masking out fOAR voxels surrounding the tumor target it is possible to achieve high quality treatment plans while controlling the radiation dose on fOARs.Conclusions: The proposed method can effectively reduce the radiation dose incident on the eloquent brain areas during Gamma Knife SRS of brain tumors.
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| 3. |
- Abramian, David, 1992-
(författare)
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Modern multimodal methods in brain MRI
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Magnetic resonance imaging (MRI) is one of the pillars of modern medical imaging, providing a non-invasive means to generate 3D images of the body with high soft-tissue contrast. Furthermore, the possibilities afforded by the design of MRI sequences enable the signal to be sensitized to a multitude of physiological tissue properties, resulting in a wide variety of distinct MRI modalities for clinical and research use. This thesis presents a number of advanced brain MRI applications, which fulfill, to differing extents, two complementary aims. On the one hand, they explore the benefits of a multimodal approach to MRI, combining structural, functional and diffusion MRI, in a variety of contexts. On the other, they emphasize the use of advanced mathematical and computational tools in the analysis of MRI data, such as deep learning, Bayesian statistics, and graph signal processing. Paper I introduces an anatomically-adapted extension to previous work in Bayesian spatial priors for functional MRI data, where anatomical information is introduced from a T1-weighted image to compensate for the low anatomical contrast of functional MRI data. It has been observed that the spatial correlation structure of the BOLD signal in brain white matter follows the orientation of the underlying axonal fibers. Paper II argues about the implications of this fact on the ideal shape of spatial filters for the analysis of white matter functional MRI data. By using axonal orientation information extracted from diffusion MRI, and leveraging the possibilities afforded by graph signal processing, a graph-based description of the white matter structure is introduced, which, in turn, enables the definition of spatial filters whose shape is adapted to the underlying axonal structure, and demonstrates the increased detection power resulting from their use. One of the main clinical applications of functional MRI is functional localization of the eloquent areas of the brain prior to brain surgery. This practice is widespread for various invasive surgeries, but is less common for stereotactic radiosurgery (SRS), a non-invasive surgical procedure wherein tissue is ablated by concentrating several beams of high-energy radiation. Paper III describes an analysis and processing pipeline for functional MRI data that enables its use for functional localization and delineation of organs-at-risk for Elekta GammaKnife SRS procedures. Paper IV presents a deep learning model for super-resolution of diffusion MRI fiber ODFs, which outperforms standard interpolation methods in estimating local axonal fiber orientations in white matter. Finally, Paper V demonstrates that some popular methods for anonymizing facial data in structural MRI volumes can be partially reversed by applying generative deep learning models, highlighting one way in which the enormous power of deep learning models can potentially be put to use for harmful purposes.
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| 4. |
- Akbar, Muhammad Usman, 1990-, et al.
(författare)
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Brain tumor segmentation using synthetic MR images - A comparison of GANs and diffusion models
- 2024
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Ingår i: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Large annotated datasets are required for training deep learning models, but in medical imaging data sharing is often complicated due to ethics, anonymization and data protection legislation. Generative AI models, such as generative adversarial networks (GANs) and diffusion models, can today produce very realistic synthetic images, and can potentially facilitate data sharing. However, in order to share synthetic medical images it must first be demonstrated that they can be used for training different networks with acceptable performance. Here, we therefore comprehensively evaluate four GANs (progressive GAN, StyleGAN 1–3) and a diffusion model for the task of brain tumor segmentation (using two segmentation networks, U-Net and a Swin transformer). Our results show that segmentation networks trained on synthetic images reach Dice scores that are 80%–90% of Dice scores when training with real images, but that memorization of the training images can be a problem for diffusion models if the original dataset is too small. Our conclusion is that sharing synthetic medical images is a viable option to sharing real images, but that further work is required. The trained generative models and the generated synthetic images are shared on AIDA data hub.
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| 5. |
- Berndt, Sonja I., et al.
(författare)
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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
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Tidskriftsartikel (refereegranskat)abstract
- Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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| 6. |
- Boito, Deneb, 1993-
(författare)
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Diffusion MRI with generalised gradient waveforms : methods, models, and neuroimaging applications
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The incessant, random motion of water molecules within biological tissues reveals unique information about the tissues’ structural and functional characteristics. Diffusion magnetic resonance imaging is sensitive to this random motion, and since the mid-1990s it has been extensively employed for studying the human brain. Most notably, measurements of water diffusion allow for the early detection of ischaemic stroke and for the unveiling of the brain’s wiring via reconstruction of the neuronal connections. Ultimately, the goal is to employ this imaging technique to perform non-invasive, in vivo virtual histology to directly characterise both healthy and diseased tissue. Recent developments in the field have introduced new ways to measure the diffusion process in clinically feasible settings. These new measurements, performed by employing generalised magnetic field gradient waveforms, grant access to specific features of the cellular composition and structural organisation of the tissue. Methods based on them have already proven beneficial for the assessment of different brain diseases, sparking interest in translating such techniques into clinical practice. This thesis focuses on improving the methods currently employed for the analysis of such diffusion MRI data, with the aim of facilitating their clinical adoption. The first two publications introduce constrained frameworks for the estimation of parameters from diffusion MRI data acquired with generalised gradient waveforms. The constraints are dictated by mathematical and physical properties of a multi-compartment model used to represent the brain tissue, and can be efficiently enforced by employing a relatively new optimisation scheme called semidefinite programming. The developed routines are demonstrated to improve robustness to noise and imperfect data collection. Moreover, constraining the fit is shown to relax the requirements on the number of points needed for the estimation, thus allowing for faster data acquisition. In the third paper, the developed frameworks are employed to study the brain’s white matter in patients previously hospitalised for COVID-19 and who still suffer from neurological symptoms months after discharge. The results show widespread alterations to the structural integrity of their brain, with the metrics available through the advanced diffusion measurements providing new insights into the damage to the white matter. The fourth paper revisits the modelling paradigm currently adopted for the analysis of diffusion MRI data acquired with generalised gradient waveforms. Hitherto, the assumption of free diffusion has been employed to represent each domain in a multi-compartmental picture of the brain tissue. In this work, a model for restricted diffusion is considered instead to alleviate the paradoxical assumption of free but compartmentalised diffusion. The model is shown to perfectly capture restricted diffusion as measured with the generalised diffusion gradient waveforms, thus endorsing its use for representing each domain in the multi-compartmental model of the tissue.
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| 7. |
- Boito, Deneb, 1993-, et al.
(författare)
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MRI with generalized diffusion encoding reveals damaged white matter in patients previously hospitalized for COVID-19 and with persisting symptoms at follow-up
- 2023
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Ingår i: Brain Communications. - : Oxford University Press. - 2632-1297. ; 5:6
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Tidskriftsartikel (refereegranskat)abstract
- There is mounting evidence of the long-term effects of COVID-19 on the central nervous system, with patients experiencing diverse symptoms, often suggesting brain involvement. Conventional brain MRI of these patients shows unspecific patterns, with no clear connection of the symptomatology to brain tissue abnormalities, whereas diffusion tensor studies and volumetric analyses detect measurable changes in the brain after COVID-19. Diffusion MRI exploits the random motion of water molecules to achieve unique sensitivity to structures at the microscopic level, and new sequences employing generalized diffusion encoding provide structural information which are sensitive to intravoxel features. In this observational study, a total of 32 persons were investigated: 16 patients previously hospitalized for COVID-19 with persisting symptoms of post-COVID condition (mean age 60 years: range 41–79, all male) at 7-month follow-up and 16 matched controls, not previously hospitalized for COVID-19, with no post-COVID symptoms (mean age 58 years, range 46–69, 11 males). Standard MRI and generalized diffusion encoding MRI were employed to examine the brain white matter of the subjects. To detect possible group differences, several tissue microstructure descriptors obtainable with the employed diffusion sequence, the fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, microscopic anisotropy, orientational coherence (Cc) and variance in compartment’s size (CMD) were analysed using the tract-based spatial statistics framework. The tract-based spatial statistics analysis showed widespread statistically significant differences (P < 0.05, corrected for multiple comparisons using the familywise error rate) in all the considered metrics in the white matter of the patients compared to the controls. Fractional anisotropy, microscopic anisotropy and Cc were lower in the patient group, while axial diffusivity, radial diffusivity, mean diffusivity and CMD were higher. Significant changes in fractional anisotropy, microscopic anisotropy and CMD affected approximately half of the analysed white matter voxels located across all brain lobes, while changes in Cc were mainly found in the occipital parts of the brain. Given the predominant alteration in microscopic anisotropy compared to Cc, the observed changes in diffusion anisotropy are mostly due to loss of local anisotropy, possibly connected to axonal damage, rather than white matter fibre coherence disruption. The increase in radial diffusivity is indicative of demyelination, while the changes in mean diffusivity and CMD are compatible with vasogenic oedema. In summary, these widespread alterations of white matter microstructure are indicative of vasogenic oedema, demyelination and axonal damage. These changes might be a contributing factor to the diversity of central nervous system symptoms that many patients experience after COVID-19.
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| 8. |
- Egeblad, Louise, et al.
(författare)
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Structural and functional studies of the human phosphoribosyltransferase domain containing protein 1
- 2010
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Ingår i: The FEBS Journal. - : Wiley. - 1742-464X .- 1742-4658. ; 277:23, s. 4920-30
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Tidskriftsartikel (refereegranskat)abstract
- Human hypoxanthine-guanine phosphoribosyltransferase (HPRT) (EC 2.4.2.8) catalyzes the conversion of hypoxanthine and guanine to their respective nucleoside monophosphates. Human HPRT deficiency as a result of genetic mutations is linked to both Lesch-Nyhan disease and gout. In the present study, we have characterized phosphoribosyltransferase domain containing protein 1 (PRTFDC1), a human HPRT homolog of unknown function. The PRTFDC1 structure has been determined at 1.7 Å resolution with bound GMP. The overall structure and GMP binding mode are very similar to that observed for HPRT. Using a thermal-melt assay, a nucleotide metabolome library was screened against PRTFDC1 and revealed that hypoxanthine and guanine specifically interacted with the enzyme. It was subsequently confirmed that PRTFDC1 could convert these two bases into their corresponding nucleoside monophosphate. However, the catalytic efficiency (k(cat)/K(m)) of PRTFDC1 towards hypoxanthine and guanine was only 0.26% and 0.09%, respectively, of that of HPRT. This low activity could be explained by the fact that PRTFDC1 has a Gly in the position of the proposed catalytic Asp of HPRT. In PRTFDC1, a water molecule at the position of the aspartic acid side chain position in HPRT might be responsible for the low activity observed by acting as a weak base. The data obtained in the present study indicate that PRTFDC1 does not have a direct catalytic role in the nucleotide salvage pathway.
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| 9. |
- Eklund, Ida, et al.
(författare)
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Patients' Experiences of Pain and Postoperative Nausea and Vomiting in the Early Postoperative Period After an Elective Knee Arthroplasty
- 2020
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Ingår i: Journal of Perianesthesia Nursing. - : Elsevier. - 1089-9472 .- 1532-8473. ; 35:4, s. 382-388
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Tidskriftsartikel (refereegranskat)abstract
- PurposeThe aim of this study is to explore patients' experience of pain and postoperative nausea and vomiting (PONV) in the early postoperative period after knee arthroplasties.DesignThis is a retrospective cohort study with a quantitative approach. Data from patients registered in the Swedish Perioperative Registry were used. We used the Strenghtening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies.MethodsData were collected from patients (N = 439) undergoing knee arthroplasties. The analysis was performed with descriptive and analytic statistics.FindingsThe findings indicate that women experienced significantly higher levels of pain than men and suffered significantly more often from PONV. However, the relationship of postoperative pain and PONV was not significant. There was also no significance for the relationship among postoperative pain, PONV, and age.ConclusionsCare needs to be sensitive to differences in experiencing pain and PONV depending on sex or gender bias, with a goal of increasing the equality in care.
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| 10. |
- Eklund, Rakel, 1986-, et al.
(författare)
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Daily uplifts during the COVID-19 pandemic : what is considered helpful in everyday life?
- 2022
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Ingår i: BMC Public Health. - : Springer Nature. - 1471-2458. ; 22:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundKnowledge of what is uplifting and helpful during pandemics could inform the design of sustainable pandemic recommendations in the future. We have explored individuals’ views on helpful and uplifting aspects of everyday life during the coronavirus disease 2019 (COVID-19) pandemic.MethodsParticipants answered a brief, daily survey via text messages during 14 consecutive days in July–August, 2020. The survey included the question: “During the past 24 hours, is there anything that has made you feel good or helped you in your life?” We used content analysis to compile responses from 693 participants, who provided 4,490 free-text answers, which resulted in 24 categories subsumed under 7 themes.ResultsPositive aspects during the COVID-19 pandemic primarily related to social interactions, in real life or digitally, with family, friends and others. Other important aspects concerning work, colleagues and maintaining everyday life routines. One theme concerning vacations, going on excursions and being in nature. Leisure and recreation activities, such as hobbies and physical exercise, also emerged as important, as did health-related factors. Bodily sensations, thoughts, feelings and activities that benefited well-being were mentioned frequently. Lastly, people commented on the government strategies for containing COVID-19, and whether to comply with restrictions.ConclusionsTo summarize, daily uplifts and helpful aspects of everyday life centered around social relationships. To comply with recommendations on physical distancing, people found creative ways to maintain social connections both digitally and face-to-face. Social interaction, maintenance of everyday life routines, hobbies and physical activity appeared to be important for well-being.
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