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| 2. |
- Rajalahti, Tarja, et al.
(författare)
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Proteins in different Synechocystis compartments have distinguishing N-terminal features : a combined proteomics and multivariate sequence analysis
- 2007
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 6:7, s. 2420-2434
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Tidskriftsartikel (refereegranskat)abstract
- Cyanobacteria have a cell envelope consisting of a plasma membrane, a periplasmic space with a peptidoglycan layer, and an outer membrane. A third, separate membrane system, the intracellular thylakoid membranes, is the site for both photosynthesis and respiration. All membranes and luminal spaces have unique protein compositions, which impose an intriguing mechanism for protein sorting of extracytoplasmic proteins due to single sets of translocation protein genes. It is shown here by multivariate sequence analyses of many experimentally identified proteins in Synechocystis, that proteins routed for the different extracytosolic compartments have correspondingly different physicochemical properties in their signal peptide and mature N-terminal segments. The full-length mature sequences contain less significant information. From these multivariate, N-terminal property-profile models for proteins with single experimental localization, proteins with ambiguous localization could, to a large extent, be predicted to a defined compartment. The sequence properties involve amino acids varying especially in volume and polarizability and at certain positions in the sequence segments, in a manner typical for the various compartment classes. Potential means of the cell to recognize the property features are discussed, involving the translocation channels and two Type I signal peptidases with different cellular localization, and charge features at their membrane interfaces.
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| 4. |
- Rosén, Maria L, et al.
(författare)
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Recognition of Fold and Sugar Linkage for Glycosyltransferases by Multivariate Sequence Analysis
- 2004
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Ingår i: Journal of Biological Chemistry. ; 279, s. 38683-92
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Tidskriftsartikel (refereegranskat)abstract
- Glycosyltransferases (GTs) are among the largest groups of enzymes found and are usually classified on the basis of sequence comparisons into many families of varying similarity (CAZy systematics). Only two different Rossman-like folds have been detected (GT-A and GT-B) within the small number of established crystal structures. A third uncharacterized fold has been indicated with transmembrane organization (GT-C). We here use a method based on multivariate data analyses (MVDAs) of property patterns in amino acid sequences and can with high accuracy recognize the correct fold in a large data set of GTs. Likewise, a retaining or inverting enzymatic mechanism for attachment of the donor sugar could be properly revealed in the GT-A and GT-B fold group sequences by such analyses. Sequence alignments could be correlated to important variables in MVDA, and the separating amino acid positions could be mapped over the active sites. These seem to be localized to similar positions in space for the // binding motifs in the GT-B fold group structures. Analogous, active-site sequence positions were found for the GT-A fold group. Multivariate property patterns could also easily group most GTs annotated in the genomes of Escherichia coli and Synechocystis to proper fold or organization group, according to benchmarking comparisons at the MetaServer. We conclude that the sequence property patterns revealed by the multivariate analyses seem more conserved than amino acid types for these GT groups, and these patterns are also conserved in the structures. Such patterns may also potentially define substrate preferences.
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| 6. |
- Aarseth, Espen, et al.
(författare)
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Scholars' open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal
- 2017
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Ingår i: Journal of Behavioral Addictions. - : AKADEMIAI KIADO RT. - 2062-5871 .- 2063-5303. ; 6:3, s. 267-270
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Concerns about problematic gaming behaviors deserve our full attention. However, we claim that it is far from clear that these problems can or should be attributed to a new disorder. The empirical basis for a Gaming Disorder proposal, such as in the new ICD-11, suffers from fundamental issues. Our main concerns are the low quality of the research base, the fact that the current operationalization leans too heavily on substance use and gambling criteria, and the lack of consensus on symptomatology and assessment of problematic gaming. The act of formalizing this disorder, even as a proposal, has negative medical, scientific, public-health, societal, and human rights fallout that should be considered. Of particular concern are moral panics around the harm of video gaming. They might result in premature application of diagnosis in the medical community and the treatment of abundant false-positive cases, especially for children and adolescents. Second, research will be locked into a confirmatory approach, rather than an exploration of the boundaries of normal versus pathological. Third, the healthy majority of gamers will be affected negatively. We expect that the premature inclusion of Gaming Disorder as a diagnosis in ICD-11 will cause significant stigma to the millions of children who play video games as a part of a normal, healthy life. At this point, suggesting formal diagnoses and categories is premature: the ICD-11 proposal for Gaming Disorder should be removed to avoid a waste of public health resources as well as to avoid causing harm to healthy video gamers around the world.
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| 7. |
- Ahlgren, Serina, et al.
(författare)
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Description of the Agrosfär model – a tool for climate impact assessment of crop and animal production systems in Sweden : Version 1: Crops, milk and beef
- 2022
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The agricultural sector in Sweden needs to cut GHG emissions and contribute to the climate goal of net-zero emissions by 2045. The GHG reduction goal for agricultural emissions is not quantified, but the Swedish climate policy framework states that ‘the Swedish food production shall increase as much as possible with as little climate impact as possible’ and multiple key actors within the sector of food and agriculture have developed roadmaps or industry specific goals for reducing GHG emissions from the sector. Consequently, requirements of transparent GHG accounting and reporting are increasing within the agricultural sector, both at national and international level. The purpose of the Agrosfär tool is to establish an automatic data driven climate calculator used to calculate GHG emissions from agricultural products and on farm enterprise level. The automation and automatic data collection will save time, increase accuracy of the calculations, and simplify updates of the tool to keep it aligned with the most recent climate data and climate reporting methodology. It will make it possible to continuously carry out follow-ups on climate performance indicators and measure improvements from climate measures taken. A working group consisting of Swedish agricultural life cycle assessment experts have developed the framework of the tool, e.g. setting system boundaries, selecting methodologies and input data. A technical team has developed algorithms, a digital interface and coupled the tool to other existing agricultural databases providing farm specific information on crop and animal production data, soil characteristics, carbon footprints and amounts of purchased inputs etc. The tool and user interface have been developed based on input from farmers through prototyping and in-depth interviews. For general guidelines on methodology the calculation model follows the Product Environmental Footprint Category Rules (PEFCR), the International Dairy Federation (IDF)’s approach for carbon footprint for the dairy sector and FAO Livestock Environmental Assessment and Performance guidelines (FAO LEAP). Where standards have diverged or where assumptions have been required the working group has made expert judgements on which method/guideline to follow or what assumptions to make. A first version of the tool, a so called minimal viable product (MVP) has been developed which will be the basis for further development. The MVP contains an animal and crop module and can calculate the carbon footprint of crops, milk and beef. Future development possibilities of the tool and calculation model is described in chapter 7, such as enabling climate calculations on enterprise level, develop modules for more animal production types, deepen the integration between the crop and animal modules, expand sources for automatic data collection, develop a carbon sequestration module and other technical and methodological improvements to ensure alignment with important climate reporting standards. The report will be repeatedly updated as the tool develops, and new versions of the tool are released.
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| 8. |
- Ahlgren, Serina, et al.
(författare)
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Description of the Agrosfär model – a tool for the climate impact assessment of farms, crop and animal production systems in Sweden
- 2024
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The agricultural sector in Sweden needs to cut GHG emissions and contribute to the climate goal of net-zero emissions by 2045. The GHG reduction goal for agricultural emissions is not quantified, but the Swedish climate policy framework states that ‘Swedish food production shall increase as much as possible with as little climate impact as possible’. Multiple key actors within the sector of food and agriculture have developed roadmaps or industry specific goals for reducing GHG emissions from the sector. Consequently, requirements for transparent GHG accounting and reporting are increasing within the agricultural sector, both on a national and international level. The purpose of the Agrosfär tool is to establish an automatic data driven climate calculator used to calculate GHG emissions from agricultural products and on a farm enterprise level. Automation and automatic data collection will save time, increase the accuracy of the calculations, and simplify updates of the tool to keep it aligned with the most recent climate data and climate reporting methodology. It will make it possible to continuously carry out follow-ups on climate performance indicators and measure improvements from climate measures taken. A working group consisting of agricultural life cycle assessment experts has developed the framework of the tool (e.g., setting system boundaries, selecting methodologies and input data). A technical team has developed algorithms, a digital interface and coupled the tool to other existing agricultural databases, providing farm specific information on crop and animal production data, soil characteristics, carbon footprints and amounts of purchased inputs etc. The tool and user interface have been developed based on input from farmers through prototyping and in-depth interviews. The priority guidelines on which the calculation model is based are the Product Environmental Footprint Category Rules (PEFCR), the International Dairy Federation (IDF)’s approach for carbon footprint for the dairy sector, and FAO Livestock Environmental Assessment and Performance guidelines (FAO LEAP). From the farm perspective, the Greenhouse Gas Protocol (GHG Protocol) Corporate Standard, GHG Protocol Agricultural Guidance (Scope 1 & 2) and GHG Protocol Corporate value chain (Scope 3) Accounting and Reporting Standard are guiding standards. Where standards have diverged or where assumptions have been required, the working group has made expert judgements on which method/guideline to follow or what assumptions to make. A first version of the tool, first described in report version 1, was developed as the basis for further development. The first version contains an animal and a crop module, and can calculate the carbon footprint of crops, milk and beef. This report (version 1.1) has been updated to include the most recent developments of the tool. The main change is that the tool can now also be used to calculate farm climate impact on a yearly basis. Future possibilities to develop the tool and calculation model are described in chapter 7, including suggestions for developing modules for more animal production types, deepening the integration between the crop and animal modules, expanding sources for automatic data collection, developing a carbon sequestration module, and other technical and methodological improvements to ensure alignment with important climate reporting standards. The report will be repeatedly updated as the tool develops, and new versions of the tool are released.
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| 9. |
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| 10. |
- Bejerot, Susanne, 1955-, et al.
(författare)
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The Brief Obsessive-Compulsive Scale (BOCS) : a self-report scale for OCD and obsessive-compulsive related disorders
- 2014
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Ingår i: Nordic Journal of Psychiatry. - : Informa Healthcare. - 0803-9488 .- 1502-4725. ; 68:8, s. 549-559
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Tidskriftsartikel (refereegranskat)abstract
- Background: The Brief Obsessive Compulsive Scale (BOCS), derived from the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and the children's version (CY-BOCS), is a short self-report tool used to aid in the assessment of obsessive-compulsive symptoms and diagnosis of obsessive-compulsive disorder (OCD). It is widely used throughout child, adolescent and adult psychiatry settings in Sweden but has not been validated up to date.Aim: The aim of the current study was to examine the psychometric properties of the BOCS amongst a psychiatric outpatient population.Method: The BOCS consists of a 15-item Symptom Checklist including three items (hoarding, dysmorphophobia and self-harm) related to the DSM-5 category "Obsessive-compulsive related disorders", accompanied by a single six-item Severity Scale for obsessions and compulsions combined. It encompasses the revisions made in the Y-BOCS-II severity scale by including obsessive-compulsive free intervals, extent of avoidance and excluding the resistance item. 402 adult psychiatric outpatients with OCD, attention-deficit/hyperactivity disorder, autism spectrum disorder and other psychiatric disorders completed the BOCS.Results: Principal component factor analysis produced five subscales titled "Symmetry", "Forbidden thoughts", "Contamination", "Magical thoughts" and "Dysmorphic thoughts". The OCD group scored higher than the other diagnostic groups in all subscales (P < 0.001). Sensitivities, specificities and internal consistency for both the Symptom Checklist and the Severity Scale emerged high (Symptom Checklist: sensitivity = 85%, specificities = 62-70% Cronbach's alpha = 0.81; Severity Scale: sensitivity = 72%, specificities = 75-84%, Cronbach's alpha = 0.94).Conclusions: The BOCS has the ability to discriminate OCD from other non-OCD related psychiatric disorders. The current study provides strong support for the utility of the BOCS in the assessment of obsessive-compulsive symptoms in clinical psychiatry.
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