| 1. |
- Eriksson, Jens, 1980-, et al.
(författare)
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Difference in twitching motility between Neisseria meningitidis and Neisseria gonorrhoeae and its relation to pilus dynamics
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Type IV pili of pathogenic Neisseria, i. e. Neisseria gonorrhoeae and Neisseria meningitidis, are essential for initial attachment to host cells, induction of signal transduction cascades and disease development. A characteristic feature of type IV pili is their ability to retract, which generates forces that move bacteria over surfaces. However, the relation between bacterial motility and pilus dynamics remains poorly understood. In this work we analyzed bacterial motility and monitored movement of fluorescently labeled pili by live cell imaging. We found that movement of N. meningitidis occurred at higher speed and with a larger number of retracting pili than for N. gonorrhoeae. Analysis of time-lapse images suggested that N. gonorrhoeae most often moved using one retracting pilus, whereas N. meningitidis most often used four pili. There were no differences in the membrane distribution of PilT among strains. However, we found significantly higher levels of PilT in N. gonorrhoeae than in N. meningitidis. This produces a higher retraction probability, which could contribute to explaining the lower number of pili observed in N. gonorrhoeae. Finally, we propose a mechanism for how the speed of bacterial movement on a surface depends on the number of retracting pili.
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| 2. |
- 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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| 3. |
- Shungin, Dmitry, et al.
(författare)
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New genetic loci link adipose and insulin biology to body fat distribution.
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 518:7538, s. 187-378
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Tidskriftsartikel (refereegranskat)abstract
- Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.
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| 4. |
- Spreco, Armin, et al.
(författare)
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Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020
- 2022
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Ingår i: Emerging Infectious Diseases. - : Centers for Disease Control and Prevention (CDC). - 1080-6040 .- 1080-6059. ; 28:3, s. 564-571
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Tidskriftsartikel (refereegranskat)abstract
- We report on local nowcasting (short-term forecasting) of coronavirus disease (COVID-19) hospitalizations based on syndromic (symptom) data recorded in regular healthcare routines in Östergötland County (population ≈465,000), Sweden, early in the pandemic, when broad laboratory testing was unavailable. Daily nowcasts were supplied to the local healthcare management based on analyses of the time lag between telenursing calls with the chief complaints (cough by adult or fever by adult) and COVID-19 hospitalization. The complaint cough by adult showed satisfactory performance (Pearson correlation coefficient r>0.80; mean absolute percentage error <20%) in nowcasting the incidence of daily COVID-19 hospitalizations 14 days in advance until the incidence decreased to <1.5/100,000 population, whereas the corresponding performance for fever by adult was unsatisfactory. Our results support local nowcasting of hospitalizations on the basis of symptom data recorded in routine healthcare during the initial stage of a pandemic. © 2022 Centers for Disease Control and Prevention (CDC). All rights reserved.
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| 5. |
- Abdalmoaty, Mohamed R. H., 1986-, et al.
(författare)
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Identification of Non-Linear Differential-Algebraic Equation Models with Process Disturbances
- 2021
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Ingår i: 2021 60th IEEE Conference on Decision and Control (CDC). - : IEEE. - 9781665436595 - 9781665436588 - 9781665436601 ; , s. 2300-2305
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Konferensbidrag (refereegranskat)abstract
- Differential-algebraic equations (DAEs) arise naturally as a result of equation-based object-oriented modeling. In many cases, these models contain unknown parameters that have to be estimated using experimental data. However, often the system is subject to unknown disturbances which, if not taken into account in the estimation, can severely affect the model's accuracy. For non-linear state-space models, particle filter methods have been developed to tackle this issue. Unfortunately, applying such methods to non-linear DAEs requires a transformation into a state-space form, which is particularly difficult to obtain for models with process disturbances. In this paper, we propose a simulation-based prediction error method that can be used for non-linear DAEs where disturbances are modeled as continuous-time stochastic processes. To the authors' best knowledge, there are no general methods successfully dealing with parameter estimation for this type of model. One of the challenges in particle filtering methods are random variations in the minimized cost function due to the nature of the algorithm. In our approach, a similar phenomenon occurs and we explicitly consider how to sample the underlying continuous process to mitigate this problem. The method is illustrated numerically on a pendulum example. The results suggest that the method is able to deliver consistent estimates.
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| 6. |
- Abedi Dunia, Oscar, et al.
(författare)
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Visibilising hidden realities and uncertainties : the ‘post-covid’ move towards decolonized and ethical field research practices
- 2023
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Ingår i: International Journal of Social Research Methodology. - : Routledge. - 1364-5579 .- 1464-5300. ; 26:5, s. 549-564
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Tidskriftsartikel (refereegranskat)abstract
- This article seeks to move beyond the Euro/North-centrism recurrent in methodological discussions on what we may learn from the COVID-19 pandemic. Such debates often centre on uncertainty and involuntary immobility – aspects which are hardly new for many researchers. In this article, we argue that the pandemic offers an opportunity to rethink research relations between what we term ‘contracting researchers’ in the Global North and ‘facilitating researchers’ in the Global South. Such relations are often marked by rampant inequalities in remuneration, working conditions, and visibility/authorship. Drawing upon experiences in DR Congo, Sierra Leone, and India, we argue that the pandemic increased the dependence on – and highlighted the invaluable contributions and skills of – facilitating researchers, in part slightly refiguring bargaining power. We also propose pathways for change, arguing for a strong collaborative approach and the need for institutional change, without discarding the responsibilities of individual researchers.
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| 7. |
- Abedi, Oscar, et al.
(författare)
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The Covid-19 Opportunity: Creating More Ethical and Sustainable Research Practices
- 2020
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Contributing to the “Covid-19 and the Social Sciences” essay series, Oscar Abedi, Maria Eriksson Baaz, David Mwambari, Swati Parashar, Anju Oseema Maria Toppo, and James Vincent outline various paths toward reducing field research’s potential for exploitation, especially that of Global South collaborators. The pandemic has highlighted inequalities and immobility that differently affect facilitating researchers and contracting researchers. In response, the authors identify key issues that institutions, publishers, and individual researchers must reflect on in order to counteract these imbalances—and take advantage of an opportunity to fundamentally transform field research into collaborative knowledge production.
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| 10. |
- Bereza-Jarocinski, Robert, et al.
(författare)
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Stochastic Approximation for Identification of Non-Linear Differential-Algebraic Equations with Process Disturbances
- 2022
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Ingår i: 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665467612 - 9781665467605 - 9781665467629 ; , s. 6712-6717
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Konferensbidrag (refereegranskat)abstract
- Differential-algebraic equations, commonly used to model physical systems, are the basis for many equation-based object-oriented modeling languages. When systems described by such equations are influenced by unknown process disturbances, estimating unknown parameters from experimental data becomes difficult. This is because of problems with the existence of well-defined solutions and the computational tractability of estimators. In this paper, we propose a way to minimize a cost function-whose minimizer is a consistent estimator of the true parameters-using stochastic gradient descent. This approach scales significantly better with the number of unknown parameters than other currently available methods for the same type of problem. The performance of the method is demonstrated through a simulation study with three unknown parameters. The experiments show a significantly reduced variance of the estimator, compared to an output error method neglecting the influence of process disturbances, as well as an ability to reduce the estimation bias of parameters that the output error method particularly struggles with.
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