| 1. |
- Boström, Magnus, 1972-, et al.
(författare)
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Conditions for Transformative Learning for Sustainable Development : A Theoretical Review and Approach
- 2018
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 10:12
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Tidskriftsartikel (refereegranskat)abstract
- Continued unsustainability and surpassed planetary boundaries require not only scientific and technological advances, but deep and enduring social and cultural changes. The purpose of this article is to contribute a theoretical approach to understand conditions and constraints for societal change towards sustainable development. In order to break with unsustainable norms, habits, practices, and structures, there is a need for learning for transformation, not only adaption. Based on a critical literature review within the field of learning for sustainable development, our approach is a development of the concept of transformative learning, by integrating three additional dimensions—Institutional Structures, Social Practices, and Conflict Perspectives. This approach acknowledges conflicts on macro, meso, and micro levels, as well as structural and cultural constraints. It contends that transformative learning is processual, interactional, long-term, and cumbersome. It takes place within existing institutions and social practices, while also transcending them. The article adopts an interdisciplinary social science perspective that acknowledges the importance of transformative learning in order for communities, organizations, and individuals to be able to deal with global sustainability problems, acknowledging the societal and personal conflicts involved in such transformation.
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| 2. |
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| 3. |
- Gawel, Danuta R., 1988-
(författare)
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Identification of genes and regulators that are shared across T cell associated diseases
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Genome-wide association studies (GWASs) of hundreds of diseases and millions of patients have led to the identification of genes that are associated with more than one disease. The aims of this PhD thesis were to a) identify a group of genes important in multiple diseases (shared disease genes), b) identify shared up-stream disease regulators, and c) determine how the same genes can be involved in the pathogenesis of different diseases. These aims have been tested on CD4+ T cells because they express the T helper cell differentiation pathway, which was the most enriched pathway in analyses of all disease associated genes identified with GWASs.Combining information about known gene-gene interactions from the protein-protein interaction (PPI) network with gene expression changes in multiple T cell associated diseases led to the identification of a group of highly interconnected genes that were miss-expressed in many of those diseases – hereafter called ‘shared disease genes’. Those genes were further enriched for inflammatory, metabolic and proliferative pathways, genetic variants identified by all GWASs, as well as mutations in cancer studies and known diagnostic and therapeutic targets. Taken together, these findings supported the relevance of the shared disease genes.Identification of the shared upstream disease regulators was addressed in the second project of this PhD thesis. The underlying hypothesis assumed that the determination of the shared upstream disease regulators is possible through a network model showing in which order genes activate each other. For that reason a transcription factor–gene regulatory network (TF-GRN) was created. The TF-GRN was based on the time-series gene expression profiling of the T helper cell type 1 (Th1), and T helper cell type 2 (Th2) differentiation from Native T-cells. Transcription factors (TFs) whose expression changed early during polarization and had many downstream predicted targets (hubs) that were enriched for disease associated single nucleotide polymorphisms (SNPs) were prioritised as the putative early disease regulators. These analyses identified three transcription factors: GATA3, MAF and MYB. Their predicted targets were validated by ChIP-Seq and siRNA mediated knockdown in primary human T-cells. CD4+ T cells isolated from seasonal allergic rhinitis (SAR) and multiple sclerosis (MS) patients in their non-symptomatic stages were analysed in order to demonstrate predictive potential of those three TFs. We found that those three TFs were differentially expressed in symptom-free stages of the two diseases, while their TF-GRN{predicted targets were differentially expressed during symptomatic disease stages. Moreover, using RNA-Seq data we identified a disease associated SNP that correlated with differential splicing of GATA3.A limitation of the above study is that it concentrated on TFs as main regulators in cells, excluding other potential regulators such as microRNAs. To this end, a microRNA{gene regulatory network (mGRN) of human CD4+ T cell differentiation was constructed. Within this network, we defined regulatory clusters (groups of microRNAs that are regulating groups of mRNAs). One regulatory cluster was differentially expressed in all of the tested diseases, and was highly enriched for GWAS SNPs. Although the microRNA processing machinery was dynamically upregulated during early T-cell activation, the majority of microRNA modules showed specialisation in later time-points.In summary this PhD thesis shows the relevance of shared genes and up-stream disease regulators. Putative mechanisms of why shared genes can be involved in pathogenesis of different diseases have also been demonstrated: a) differential gene expression in different diseases; b) alternative transcription factor splicing variants may affect different downstream gene target group; and c) SNPs might cause alternative splicing.
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| 4. |
- Gustafsson, Erik, 1977-, et al.
(författare)
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Causes and consequences of acidification in the Baltic Sea : implications for monitoring and management
- 2023
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Ingår i: Scientific Reports. - 2045-2322. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Increasing atmospheric CO2 drives ocean acidification globally. In coastal seas, acidification trends can however be either counteracted or enhanced by other processes. Ecosystem effects of acidification are so far small in the Baltic Sea, but changes should be anticipated unless CO2 emissions are curbed. Possible future acidification trends in the Baltic Sea, conditional on CO2 emissions, climate change, and changes in productivity, can be assessed by means of model simulations. There are uncertainties regarding potential consequences for marine organisms, partly because of difficulties to assign critical thresholds, but also because of knowledge gaps regarding species’ capacity to adapt. Increased temporal and spatial monitoring of inorganic carbon system parameters would allow a better understanding of current acidification trends and also improve the capacity to predict possible future changes. An additional benefit is that such measurements also provide quantitative estimates of productivity. The technology required for precise measurements of the inorganic carbon system is readily available today. Regularly updated status evaluations of acidification, and the inorganic carbon system in general, would support management when assessing climate change effects, eutrophication or characteristics of the pelagic habitats. This would, however, have to be based on a spatially and temporally sufficient monitoring program.
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| 5. |
- Gustafsson, Erik, 1977, et al.
(författare)
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The air-water CO2 exchange of a coastal sea— A sensitivity study on factors that influence the absorption and outgassing of CO2 in the Baltic Sea
- 2015
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Ingår i: Journal of Geophysical Research - Oceans. - 0148-0227 .- 2156-2202 .- 2169-9275 .- 2169-9291. ; 120:8, s. 5342-5357
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Tidskriftsartikel (refereegranskat)abstract
- In this study, the BALTSEM model is used to estimate how air-water CO2 fluxes in the Baltic Sea respond to parameterizations of organic alkalinity (Aorg), gas transfer, and phytoplankton growth, and further to changes in river loads. The forcing data include the most complete compilation of Baltic river loads for dissolved inorganic and organic carbon (DIC and DOC) and total alkalinity (TA). In addition, we apply the most recent estimates of internal TA generation in the system. Our results clearly demonstrate how airwater CO2 fluxes of a coastal sea depend on river loads of carbon, TA, and nutrients as well the freshwater import itself. Long-term changes in DIC loads are shown to be compensated by corresponding changes in air-water CO2 exchange. By adding Aorg, a discrepancy in the carbonate system calculations was removed, and the simulated net CO2 absorption of the system decreased by 11%. A new parameterization for cyanobacteria growth significantly improved the seasonal development of pCO2 in the central Baltic Sea, although the net effect on CO2 fluxes was below 5%. By applying either a linear, quadratic, or cubic wind speed dependence for gas transfer, the long-term net CO2 exchange was adjusted by less than 5%. There is no clear indication that any one of these parameterizations provides a more accurate estimate of CO2 fluxes than the other two. Our findings are applicable in other coastal areas that are heavily influenced by river loads of TA, DIC, and DOC.
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| 6. |
- Gustafsson, Stefan, et al.
(författare)
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Development and validation of deep learning ECG-based prediction of myocardial infarction in emergency department patients
- 2022
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Ingår i: Scientific Reports. - : Springer Nature. - 2045-2322. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Myocardial infarction diagnosis is a common challenge in the emergency department. In managed settings, deep learning-based models and especially convolutional deep models have shown promise in electrocardiogram (ECG) classification, but there is a lack of high-performing models for the diagnosis of myocardial infarction in real-world scenarios. We aimed to train and validate a deep learning model using ECGs to predict myocardial infarction in real-world emergency department patients. We studied emergency department patients in the Stockholm region between 2007 and 2016 that had an ECG obtained because of their presenting complaint. We developed a deep neural network based on convolutional layers similar to a residual network. Inputs to the model were ECG tracing, age, and sex; and outputs were the probabilities of three mutually exclusive classes: non-ST-elevation myocardial infarction (NSTEMI), ST-elevation myocardial infarction (STEMI), and control status, as registered in the SWEDEHEART and other registries. We used an ensemble of five models. Among 492,226 ECGs in 214,250 patients, 5,416 were recorded with an NSTEMI, 1,818 a STEMI, and 485,207 without a myocardial infarction. In a random test set, our model could discriminate STEMIs/NSTEMIs from controls with a C-statistic of 0.991/0.832 and had a Brier score of 0.001/0.008. The model obtained a similar performance in a temporally separated test set of the study sample, and achieved a C-statistic of 0.985 and a Brier score of 0.002 in discriminating STEMIs from controls in an external test set. We developed and validated a deep learning model with excellent performance in discriminating between control, STEMI, and NSTEMI on the presenting ECG of a real-world sample of the important population of all-comers to the emergency department. Hence, deep learning models for ECG decision support could be valuable in the emergency department.
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| 7. |
- Gustafsson, Sofia, et al.
(författare)
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Heterogeneous drug tissue binding in brain regions of rats, Alzheimer’s patients and controls : impact on translational drug development
- 2019
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- For preclinical and clinical assessment of therapeutically relevant unbound, free, brain concentrations, the pharmacokinetic parameter fraction of unbound drug in brain (fu,brain) is commonly used to compensate total drug concentrations for nonspecific brain tissue binding (BTB). As, homogenous BTB is assumed between species and in health and disease, rat BTB is routinely used. The impact of Alzheimer’s disease (AD) on drug BTB in brain regions of interest (ROI), i.e., fu,brain,ROI, is yet unclear. This study for the first time provides insight into regional drug BTB and the validity of employing rat fu,brain,ROI as a surrogate of human BTB, by investigating five marketed drugs in post-mortem tissue from AD patients (n = 6) and age-matched controls (n = 6). Heterogeneous drug BTB was observed in all within group comparisons independent of disease and species. The findings oppose the assumption of uniform BTB, highlighting the need of case-by-case evaluation of fu,brain,ROI in translational CNS research.
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| 8. |
- Gustafsson, Stefan, et al.
(författare)
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Markers of imminent myocardial infarction
- 2024
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Ingår i: Nature Cardiovascular Research. - : Springer Nature. - 2731-0590.
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Tidskriftsartikel (refereegranskat)abstract
- Myocardial infarction is a leading cause of death globally but is notoriously difficult to predict. We aimed to identify biomarkers of an imminent first myocardial infarction and design relevant prediction models. Here, we constructed a new case–cohort consortium of 2,018 persons without prior cardiovascular disease from six European cohorts, among whom 420 developed a first myocardial infarction within 6 months after the baseline blood draw. We analyzed 817 proteins and 1,025 metabolites in biobanked blood and 16 clinical variables. Forty-eight proteins, 43 metabolites, age, sex and systolic blood pressure were associated with the risk of an imminent first myocardial infarction. Brain natriuretic peptide was most consistently associated with the risk of imminent myocardial infarction. Using clinically readily available variables, we devised a prediction model for an imminent first myocardial infarction for clinical use in the general population, with good discriminatory performance and potential for motivating primary prevention efforts.
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| 9. |
- Christersson, Malin, et al.
(författare)
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Usefulness of Heart Failure Categories Based on Left Ventricular Ejection Fraction
- 2024
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Ingår i: Journal of the American Heart Association. - : John Wiley & Sons. - 2047-9980. ; 13:8
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Heart failure guidelines have recently introduced a narrow category with mildly reduced left ventricular ejection fraction (LVEF) (heart failure with mildly reduced ejection fraction; LVEF 41%-49%) between the previous categories of reduced (heart failure with reduced ejection fraction; LVEF <= 40%) and preserved (heart failure with preserved ejection fraction; LVEF >= 50%) ejection fraction. Grouping of continuous measurements into narrow categories can be questioned if their variability is high. METHODS AND RESULTS: We constructed a cohort of all 9716 new cases of chronic heart failure with an available LVEF in Stockholm, Sweden, from January 1, 2015, until December 31, 2020. All values of LVEF were collected over time, and patients were followed up until death, moving out of Stockholm, or end of study. Mixed models were used to quantify within-person variance in LVEF, and multistate Markov models, with death as an absorbing state, to quantify the stability of LVEF categories. LVEF values followed a normal distribution. The SD of the within-person variance in LVEF over time was 7.4%. The mean time spent in any LVEF category before transition to another category was on average <1 year for heart failure with mildly reduced ejection fraction. Probabilities of transitioning between categories during the first year were substantial; patients with heart failure with mildly reduced ejection fraction had a probability of <25% of remaining in that category 1 year later. CONCLUSIONS: LVEF follows a normal distribution and has considerable variability over time, which may impose a risk for under-use of efficient treatment. The heart failure with mildly reduced ejection fraction category is especially inconstant. Assumptions of a patient's current LVEF should take this variability and the normal distribution of LVEF into account.
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