| 1. |
- Moberg, Christina, et al.
(författare)
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De unga gör helt rätt när de stämmer staten
- 2022
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Ingår i: Aftonbladet. - 1103-9000.
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Tidskriftsartikel (populärvet., debatt m.m.)abstract
- 1 620 forskare och lärare i forskarvärlden: Vi ställer oss bakom Auroras klimatkrav
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| 2. |
- Alijagic, Andi, 1992-, et al.
(författare)
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Particle Safety Assessment in Additive Manufacturing : From Exposure Risks to Advanced Toxicology Testing.
- 2022
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Ingår i: Frontiers in Toxicology. - : Frontiers Media S.A.. - 2673-3080. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- Additive manufacturing (AM) or industrial three-dimensional (3D) printing drives a new spectrum of design and production possibilities; pushing the boundaries both in the application by production of sophisticated products as well as the development of next-generation materials. AM technologies apply a diversity of feedstocks, including plastic, metallic, and ceramic particle powders with distinct size, shape, and surface chemistry. In addition, powders are often reused, which may change the particles' physicochemical properties and by that alter their toxic potential. The AM production technology commonly relies on a laser or electron beam to selectively melt or sinter particle powders. Large energy input on feedstock powders generates several byproducts, including varying amounts of virgin microparticles, nanoparticles, spatter, and volatile chemicals that are emitted in the working environment; throughout the production and processing phases. The micro and nanoscale size may enable particles to interact with and to cross biological barriers, which could, in turn, give rise to unexpected adverse outcomes, including inflammation, oxidative stress, activation of signaling pathways, genotoxicity, and carcinogenicity. Another important aspect of AM-associated risks is emission/leakage of mono- and oligomers due to polymer breakdown and high temperature transformation of chemicals from polymeric particles, both during production, use, and in vivo, including in target cells. These chemicals are potential inducers of direct toxicity, genotoxicity, and endocrine disruption. Nevertheless, understanding whether AM particle powders and their byproducts may exert adverse effects in humans is largely lacking and urges comprehensive safety assessment across the entire AM lifecycle-spanning from virgin and reused to airborne particles. Therefore, this review will detail: 1) brief overview of the AM feedstock powders, impact of reuse on particle physicochemical properties, main exposure pathways and protective measures in AM industry, 2) role of particle biological identity and key toxicological endpoints in the particle safety assessment, and 3) next-generation toxicology approaches in nanosafety for safety assessment in AM. Altogether, the proposed testing approach will enable a deeper understanding of existing and emerging particle and chemical safety challenges and provide a strategy for the development of cutting-edge methodologies for hazard identification and risk assessment in the AM industry.
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| 3. |
- Alijagic, Andi, 1992-, et al.
(författare)
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A Novel Nanosafety Approach Using Cell Painting, Metabolomics, and Lipidomics Captures the Cellular and Molecular Phenotypes Induced by the Unintentionally Formed Metal-Based (Nano)Particles
- 2023
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Ingår i: Cells. - : MDPI. - 2073-4409. ; 12:2
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Tidskriftsartikel (refereegranskat)abstract
- Additive manufacturing (AM) or industrial 3D printing uses cutting-edge technologies and materials to produce a variety of complex products. However, the effects of the unintentionally emitted AM (nano)particles (AMPs) on human cells following inhalation, require further investigations. The physicochemical characterization of the AMPs, extracted from the filter of a Laser Powder Bed Fusion (L-PBF) 3D printer of iron-based materials, disclosed their complexity, in terms of size, shape, and chemistry. Cell Painting, a high-content screening (HCS) assay, was used to detect the subtle morphological changes elicited by the AMPs at the single cell resolution. The profiling of the cell morphological phenotypes, disclosed prominent concentration-dependent effects on the cytoskeleton, mitochondria, and the membranous structures of the cell. Furthermore, lipidomics confirmed that the AMPs induced the extensive membrane remodeling in the lung epithelial and macrophage co-culture cell model. To further elucidate the biological mechanisms of action, the targeted metabolomics unveiled several inflammation-related metabolites regulating the cell response to the AMP exposure. Overall, the AMP exposure led to the internalization, oxidative stress, cytoskeleton disruption, mitochondrial activation, membrane remodeling, and metabolic reprogramming of the lung epithelial cells and macrophages. We propose the approach of integrating Cell Painting with metabolomics and lipidomics, as an advanced nanosafety methodology, increasing the ability to capture the cellular and molecular phenotypes and the relevant biological mechanisms to the (nano)particle exposure.
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| 4. |
- Alijagic, Andi, 1992-, et al.
(författare)
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Immunotoxic, genotoxic, and endocrine disrupting impacts of polyamide microplastic particles and chemicals
- 2024
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Ingår i: Environment International. - : Elsevier. - 0160-4120 .- 1873-6750. ; 183
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Tidskriftsartikel (refereegranskat)abstract
- Due to their exceptional properties and cost effectiveness, polyamides or nylons have emerged as widely used materials, revolutionizing diverse industries, including industrial 3D printing or additive manufacturing (AM). Powder-based AM technologies employ tonnes of polyamide microplastics to produce complex components every year. However, the lack of comprehensive toxicity assessment of particulate polyamides and polyamide-associated chemicals, especially in the light of the global microplastics crisis, calls for urgent action. This study investigated the physicochemical properties of polyamide-12 microplastics used in AM, and assessed a number of toxicity endpoints focusing on inflammation, immunometabolism, genotoxicity, aryl hydrocarbon receptor (AhR) activation, endocrine disruption, and cell morphology. Specifically, microplastics examination by means of field emission scanning electron microscopy revealed that work flow reuse of material created a fraction of smaller particles with an average size of 1-5 µm, a size range readily available for uptake by human cells. Moreover, chemical analysis by means of gas chromatography high-resolution mass spectrometry detected several polyamide-associated chemicals including starting material, plasticizer, thermal stabilizer/antioxidant, and migrating slip additive. Even if polyamide particles and chemicals did not induce an acute inflammatory response, repeated and prolonged exposure of human primary macrophages disclosed a steady increase in the levels of proinflammatory chemokine Interleukin-8 (IL-8/CXCL-8). Moreover, targeted metabolomics disclosed that polyamide particles modulated the kynurenine pathway and some of its key metabolites. The p53-responsive luciferase reporter gene assay showed that particles per se were able to activate p53, being indicative of a genotoxic stress. Polyamide-associated chemicals triggered moderate activation of AhR and elicited anti-androgenic activity. Finally, a high-throughput and non-targeted morphological profiling by Cell Painting assay outlined major sites of bioactivity of polyamide-associated chemicals and indicated putative mechanisms of toxicity in the cells. These findings reveal that the increasing use of polyamide microplastics may pose a potential health risk for the exposed individuals, and it merits more attention.
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| 5. |
- Bethlehem, RAI, et al.
(författare)
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Brain charts for the human lifespan
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 604:79057906, s. 525-
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Tidskriftsartikel (refereegranskat)abstract
- Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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| 8. |
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| 9. |
- Huhnstock, Nikolas Alexander, 1988-, et al.
(författare)
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An Infinite Replicated Softmax Model for Topic Modeling
- 2019
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Ingår i: Modeling Decisions for Artificial Intelligence. - Cham : Springer. - 9783030267728 - 9783030267735 ; , s. 307-318
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Konferensbidrag (refereegranskat)abstract
- In this paper, we describe the infinite replicated Softmax model (iRSM) as an adaptive topic model, utilizing the combination of the infinite restricted Boltzmann machine (iRBM) and the replicated Softmax model (RSM). In our approach, the iRBM extends the RBM by enabling its hidden layer to adapt to the data at hand, while the RSM allows for modeling low-dimensional latent semantic representation from a corpus. The combination of the two results is a method that is able to self-adapt to the number of topics within the document corpus and hence, renders manual identification of the correct number of topics superfluous. We propose a hybrid training approach to effectively improve the performance of the iRSM. An empirical evaluation is performed on a standard data set and the results are compared to the results of a baseline topic model. The results show that the iRSM adapts its hidden layer size to the data and when trained in the proposed hybrid manner outperforms the base RSM model.
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| 10. |
- Huhnstock, Nikolas Alexander, 1988-, et al.
(författare)
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On the behavior of the infinite restricted boltzmann machine for clustering
- 2018
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Ingår i: SAC '18 Proceedings of the 33rd Annual ACM Symposium on Applied Computing. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450351911 ; , s. 461-470
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Konferensbidrag (refereegranskat)abstract
- Clustering is a core problem within a wide range of research disciplines ranging from machine learning and data mining to classical statistics. A group of clustering approaches so-called nonparametric methods, aims to cluster a set of entities into a beforehand unspecified and unknown number of clusters, making potentially expensive pre-analysis of data obsolete. In this paper, the recently, by Cote and Larochelle introduced infinite Restricted Boltzmann Machine that has the ability to self-regulate its number of hidden parameters is adapted to the problem of clustering by the introduction of two basic cluster membership assumptions. A descriptive study of the influence of several regularization and sparsity settings on the clustering behavior is presented and results are discussed. The results show that sparsity is a key adaption when using the iRBM for clustering that improves both the clustering performances as well as the number of identified clusters.
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