1. |
- Dixon-Suen, Suzanne C, et al.
(author)
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Physical activity, sedentary time and breast cancer risk : a Mendelian randomisation study
- 2022
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In: British Journal of Sports Medicine. - : BMJ Publishing Group Ltd. - 0306-3674 .- 1473-0480. ; 56:20, s. 1157-1170
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Journal article (peer-reviewed)abstract
- OBJECTIVES: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.METHODS: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity.RESULTS: Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger).CONCLUSION: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.
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2. |
- Fazey, Ioan, et al.
(author)
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Transforming knowledge systems for life on Earth : Visions of future systems and how to get there
- 2020
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In: Energy Research & Social Science. - : Elsevier. - 2214-6296 .- 2214-6326. ; 70
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Journal article (peer-reviewed)abstract
- Formalised knowledge systems, including universities and research institutes, are important for contemporary societies. They are, however, also arguably failing humanity when their impact is measured against the level of progress being made in stimulating the societal changes needed to address challenges like climate change. In this research we used a novel futures-oriented and participatory approach that asked what future envisioned knowledge systems might need to look like and how we might get there. Findings suggest that envisioned future systems will need to be much more collaborative, open, diverse, egalitarian, and able to work with values and systemic issues. They will also need to go beyond producing knowledge about our world to generating wisdom about how to act within it. To get to envisioned systems we will need to rapidly scale methodological innovations, connect innovators, and creatively accelerate learning about working with intractable challenges. We will also need to create new funding schemes, a global knowledge commons, and challenge deeply held assumptions. To genuinely be a creative force in supporting longevity of human and non-human life on our planet, the shift in knowledge systems will probably need to be at the scale of the enlightenment and speed of the scientific and technological revolution accompanying the second World War. This will require bold and strategic action from governments, scientists, civic society and sustained transformational intent.
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3. |
- Middha, Pooja K., et al.
(author)
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A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
- 2023
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In: Breast Cancer Research. - : BioMed Central (BMC). - 1465-5411 .- 1465-542X. ; 25:1
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Journal article (peer-reviewed)abstract
- Background Genome-wide studies of gene-environment interactions (GxE) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide GxE analysis of similar to 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. Methods Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. Results Assuming a 1 x 10(-5) prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). Conclusions Overall, the contribution of GxE interactions to the heritability of breast cancer is very small. At the population level, multiplicative GxE interactions do not make an important contribution to risk prediction in breast cancer.
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4. |
- Mueller, Stefanie H., et al.
(author)
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Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry
- 2023
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In: Genome Medicine. - : BioMed Central (BMC). - 1756-994X. ; 15
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Journal article (peer-reviewed)abstract
- Background: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.Methods: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.Results: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 x 10(-6)) and AC058822.1 (P = 1.47 x 10(-4)), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C.Conclusions: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 x 10(-5)), demonstrating the importance of diversifying study cohorts.
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5. |
- Nilsson, Kelly Dimovska, et al.
(author)
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TOF-SIMS imaging reveals tumor heterogeneity and inflammatory response markers in the microenvironment of basal cell carcinoma
- 2020
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In: Biointerphases. - : American Vacuum Society. - 1559-4106 .- 1934-8630. ; 15:4
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Journal article (peer-reviewed)abstract
- Basal cell carcinoma (BCC) is the most common skin malignancy. In fact, it is as common as the sum of all other skin malignancies combined and the incidence is rising. In this focused and histology-guided study, tissue from a patient diagnosed with aggressive BCC was analyzed by imaging mass spectrometry in order to probe the chemistry of the complex tumor environment. Time-of-flight secondary ion mass spectrometry using a (CO2)(6 k)(+)gas cluster ion beam allowed a wide range of lipid species to be detected. Their distributions were then imaged in the tissue that contained small tumor islands that were histologically classified as more/less aggressive. Maximum autocorrelation factor (MAF) analysis highlighted chemical differences between the tumors and the surrounding stroma. A closer inspection of the distribution of individual ions, selected based on the MAF loadings, showed heterogeneity in signal between different microtumors, suggesting the potential of chemically grading the aggressiveness of each individual tumor island. Sphingomyelin lipids were found to be located in stroma containing inflammatory cells.
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6. |
- Rhodes, Olin E., et al.
(author)
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Integration of ecosystem science into radioecology : A consensus perspective
- 2020
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In: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 740
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Journal article (peer-reviewed)abstract
- In the Fall of 2016 a workshop was held which brought together over 50 scientists from the ecological and radiological fields to discuss feasibility and challenges of reintegrating ecosystem science into radioecology. There is a growing desire to incorporate attributes of ecosystem science into radiological risk assessment and radioecological research more generally, fueled by recent advances in quantification of emergent ecosystem attributes and the desire to accurately reflect impacts of radiological stressors upon ecosystem function. This paper is a synthesis of the discussions and consensus of the workshop participant's responses to three primary questions, which were: 1) How can ecosystem science support radiological risk assessment? 2) What ecosystem level endpoints potentially could be used for radiological risk assessment? and 3) What inference strategies and associated methods would be most appropriate to assess the effects of radionuclides on ecosystem structure and function? The consensus of the participants was that ecosystem science can and should support radiological risk assessment through the incorporation of quantitative metrics that reflect ecosystem functions which are sensitive to radiological contaminants. The participants also agreed that many such endpoints exit or are thought to exit and while many are used in ecological risk assessment currently, additional data need to be collected that link the causal mechanisms of radiological exposure to these endpoints. Finally, the participants agreed that radiological risk assessments must be designed and informed by rigorous statistical frameworks capable of revealing the causal inference tying radiological exposure to the endpoints selected for measurement.
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7. |
- Serge, M. A., et al.
(author)
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Testing the Effect of Relative Pollen Productivity on the REVEALS Model : A Validated Reconstruction of Europe-Wide Holocene Vegetation
- 2023
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In: Land. - : MDPI. - 2073-445X. ; 12:5
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Journal article (peer-reviewed)abstract
- Reliable quantitative vegetation reconstructions for Europe during the Holocene are crucial to improving our understanding of landscape dynamics, making it possible to assess the past effects of environmental variables and land-use change on ecosystems and biodiversity, and mitigating their effects in the future. We present here the most spatially extensive and temporally continuous pollen-based reconstructions of plant cover in Europe (at a spatial resolution of 1 degrees x 1 degrees) over the Holocene (last 11.7 ka BP) using the 'Regional Estimates of VEgetation Abundance from Large Sites' (REVEALS) model. This study has three main aims. First, to present the most accurate and reliable generation of REVEALS reconstructions across Europe so far. This has been achieved by including a larger number of pollen records compared to former analyses, in particular from the Mediterranean area. Second, to discuss methodological issues in the quantification of past land cover by using alternative datasets of relative pollen productivities (RPPs), one of the key input parameters of REVEALS, to test model sensitivity. Finally, to validate our reconstructions with the global forest change dataset. The results suggest that the RPPs.st1 (31 taxa) dataset is best suited to producing regional vegetation cover estimates for Europe. These reconstructions offer a long-term perspective providing unique possibilities to explore spatial-temporal changes in past land cover and biodiversity.
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8. |
- Glasbey, JC, et al.
(author)
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- 2021
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swepub:Mat__t
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9. |
- Barut, Inci, et al.
(author)
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Cell and tissue imaging by secondary ion mass spectrometry
- 2023
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In: Biointerphases. - 1934-8630 .- 1559-4106. ; 18:6
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Journal article (peer-reviewed)abstract
- This Tutorial focuses on the use of secondary ion mass spectrometry for the analysis of cellular and tissue samples. The Tutorial aims to cover the considerations in sample preparation analytical set up and some specific aspects of data interpretation associated with such analysis.
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10. |
- Barut, Inci, 1984, et al.
(author)
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Correlative Cellular Mass Spectrometry Imaging and Amperometry Show Dose Dependent Changes in Lipid Composition and Exocytosis
- 2023
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In: Angewandte Chemie - International Edition. - : Wiley. - 1433-7851 .- 1521-3773. ; 62:15
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Journal article (peer-reviewed)abstract
- Aberrant functioning of the proteasome has been associated with crucial pathologic conditions including neurodegeneration. Yet, the complex underlying causes at the cellular level remain unclear and there are conflicting reports of neuroprotective to neurodegenerative effects of proteasomal inhibitors such as lactacystin that are utilised as models for neurodegenerative diseases. The conflicting results may be associated with different dose regimes of lactacystin and hence we have performed a dose dependent study of the effects of lactacystin to identify concurrent changes in the cell membrane lipid profile and the dynamics of exocytosis using a combination of surface sensitive mass spectrometry and single cell amperometry. Significant changes of negatively charged lipids were associated with different lactacystin doses that showed a weak correlation with exocytosis while changes in PE and PE−O lipids showed dose dependent changes correlated with initial pore formation and total release of vesicle content respectively.
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