Degrowth wächst an Geschlechterperspektiven: Genderaspekte in Degrowth-Konzeptionen und -Praxis

Trotz zunehmender Anstrengungen finden Genderaspekte der Gestaltung gesellschaftlicher Naturverhältnisse in deutschsprachigen Debatten um Postwachstum und Degrowth wenig Beachtung. In diesem Artikel werden diesbezügliche Leerstellen sowohl auf konzeptioneller Ebene am Beispiel der Postwachstumsökonomik und -ökonomie Niko Peachs als auch in der Praxis der Degrowthbewegung anhand empirischer Forschungsergebnisse in Deutschland aufgezeigt. Ihnen werden Potentiale feministischer Forschung und Praxis für Degrowthkonzepte und -bewegung gegenübergestellt, um die Forderung nach einer emanzipatorischen sozial-ökologischen Transformation, die auch notwendig auf die Überwindung patriarchaler Geschlechterverhältnisse zielen muss, zu Zeiten gesellschaftlicher Regressionstendenzen zu bestärken

Interpreting Cancer Genomes Using Systematic Host Perturbations by Tumour Virus Proteins

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer

Animal models for cystic fibrosis: a systematic search and mapping review of the literature. Part 2: nongenetic models

Various animal models are available to study cystic fibrosis (CF). These models may help to enhance our understanding of the pathology and contribute to the development of new treatments. We systematically searched all publications on CF animal models. Because of the large number of models retrieved, we split this mapping review into two parts. Previously, we presented the genetic CF animal models. In this paper we present the nongenetic CF animal models. While genetic animal models may, in theory, be preferable for genetic diseases, the phenotype of a genetic model does not automatically resemble human disease. Depending on the research question, other animal models may thus be more informative.We searched Pubmed and Embase and identified 12,303 unique publications (after duplicate removal). All references were screened for inclusion by two independent reviewers. The genetic animal models for CF (from 636 publications) were previously described. The non-genetic CF models (from 189 publications) are described in this paper, grouped by model type: infection-based, pharmacological, administration of human materials, xenografts and other. As before for the genetic models, an overview of basic model characteristics and outcome measures is provided. This CF animal model overview can be the basis for an objective, evidence-based model choice for specific research questions. Besides, it can help to retrieve relevant background literature on outcome measures of interest

Acute acinar pancreatitis blocks vesicle-associated membrane protein 8 (VAMP8)-dependent secretion, resulting in intracellular trypsin accumulation

Zymogen secretory granules in pancreatic acinar cells express two vesicle-associated membrane proteins (VAMP), VAMP2 and -8, each controlling 50% of stimulated secretion. Analysis of secretion kinetics identified a first phase (0-2 min) mediated by VAMP2 and second (2-10 min) and third phases (10-30 min) mediated by VAMP8. Induction of acinar pancreatitis by supramaximal cholecystokinin (CCK-8) stimulation inhibits VAMP8-mediated mid- and late-phase but not VAMP2-mediated early-phase secretion. Elevation of cAMP during supramaximal CCK-8 mitigates third-phase secretory inhibition and acinar damage caused by the accumulation of prematurely activated trypsin. VAMP8-/- acini are resistant to secretory inhibition by supramaximal CCK-8, and despite a 4.5-fold increase in total cellular trypsinogen levels, are fully protected from intracellular trypsin accumulation and acinar damage. VAMP8-mediated secretion is dependent on expression of the early endosomal proteins Rab5, D52, and EEA1. Supramaximal CCK-8 (60 min) caused a 60% reduction in the expression of D52 followed by Rab5 and EEA1 in isolated acini and in in vivo The loss of D52 occurred as a consequence of its entry into autophagic vacuoles and was blocked by lysosomal cathepsin B and L inhibition. Accordingly, adenoviral overexpression of Rab5 or D52 enhanced secretion in response to supramaximal CCK-8 and prevented accumulation of activated trypsin. These data support that acute inhibition of VAMP8-mediated secretion during pancreatitis triggers intracellular trypsin accumulation and loss of the early endosomal compartment. Maintaining anterograde endosomal trafficking during pancreatitis maintains VAMP8-dependent secretion, thereby preventing accumulation of activated trypsin

Animal models for cystic fibrosis: a systematic search and mapping review of the literature. Part 2: nongenetic models

Various animal models are available to study cystic fibrosis (CF). These models may help to enhance our understanding of the pathology and contribute to the development of new treatments. We systematically searched all publications on CF animal models. Because of the large number of models retrieved, we split this mapping review into two parts. Previously, we presented the genetic CF animal models. In this paper we present the nongenetic CF animal models. While genetic animal models may, in theory, be preferable for genetic diseases, the phenotype of a genetic model does not automatically resemble human disease. Depending on the research question, other animal models may thus be more informative. We searched Pubmed and Embase and identified 12,303 unique publications (after duplicate removal). All references were screened for inclusion by two independent reviewers. The genetic animal models for CF (from 636 publications) were previously described. The non-genetic CF models (from 189 publications) are described in this paper, grouped by model type: infection-based, pharmacological, administration of human materials, xenografts and other. As before for the genetic models, an overview of basic model characteristics and outcome measures is provided. This CF animal model overview can be the basis for an objective, evidence-based model choice for specific research questions. Besides, it can help to retrieve relevant background literature on outcome measures of interest

Animal models for cystic fibrosis: a systematic search and mapping review of the literature. Part 2: nongenetic models

Various animal models are available to study cystic fibrosis (CF). These models may help to enhance our understanding of the pathology and contribute to the development of new treatments. We systematically searched all publications on CF animal models. Because of the large number of models retrieved, we split this mapping review into two parts. Previously, we presented the genetic CF animal models. In this paper we present the nongenetic CF animal models. While genetic animal models may, in theory, be preferable for genetic diseases, the phenotype of a genetic model does not automatically resemble human disease. Depending on the research question, other animal models may thus be more informative. We searched Pubmed and Embase and identified 12,303 unique publications (after duplicate removal). All references were screened for inclusion by two independent reviewers. The genetic animal models for CF (from 636 publications) were previously described. The non-genetic CF models (from 189 publications) are described in this paper, grouped by model type: infection-based, pharmacological, administration of human materials, xenografts and other. As before for the genetic models, an overview of basic model characteristics and outcome measures is provided. This CF animal model overview can be the basis for an objective, evidence-based model choice for specific research questions. Besides, it can help to retrieve relevant background literature on outcome measures of interest

Animal models for cystic fibrosis: a systematic search and mapping review of the literature. Part 2: nongenetic models

Various animal models are available to study cystic fibrosis (CF). These models may help to enhance our understanding of the pathology and contribute to the development of new treatments. We systematically searched all publications on CF animal models. Because of the large number of models retrieved, we split this mapping review into two parts. Previously, we presented the genetic CF animal models. In this paper we present the nongenetic CF animal models. While genetic animal models may, in theory, be preferable for genetic diseases, the phenotype of a genetic model does not automatically resemble human disease. Depending on the research question, other animal models may thus be more informative. We searched Pubmed and Embase and identified 12,303 unique publications (after duplicate removal). All references were screened for inclusion by two independent reviewers. The genetic animal models for CF (from 636 publications) were previously described. The non-genetic CF models (from 189 publications) are described in this paper, grouped by model type: infection-based, pharmacological, administration of human materials, xenografts and other. As before for the genetic models, an overview of basic model characteristics and outcome measures is provided. This CF animal model overview can be the basis for an objective, evidence-based model choice for specific research questions. Besides, it can help to retrieve relevant background literature on outcome measures of interest

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer