| 1. |
- Almstedt, Elin, 1988-, et al.
(författare)
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Integrative discovery of treatments for high-risk neuroblastoma
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Despite advances in the molecular exploration of paediatric cancers, approximately 50% of children with high-risk neuroblastoma lack effective treatment. To identify therapeutic options for this group of high-risk patients, we combine predictive data mining with experimental evaluation in patient-derived xenograft cells. Our proposed algorithm, TargetTranslator, integrates data from tumour biobanks, pharmacological databases, and cellular networks to predict how targeted interventions affect mRNA signatures associated with high patient risk or disease processes. We find more than 80 targets to be associated with neuroblastoma risk and differentiation signatures. Selected targets are evaluated in cell lines derived from high-risk patients to demonstrate reversal of risk signatures and malignant phenotypes. Using neuroblastoma xenograft models, we establish CNR2 and MAPK8 as promising candidates for the treatment of high-risk neuroblastoma. We expect that our method, available as a public tool (targettranslator.org), will enhance and expedite the discovery of risk-associated targets for paediatric and adult cancers.
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| 2. |
- Biggs, Reinette, et al.
(författare)
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Social-ecological change : insights from the Southern African Program on Ecosystem Change and Society
- 2022
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Ingår i: Ecosystems and People. - : Informa UK Limited. - 2639-5908 .- 2639-5916. ; 18:1, s. 447-468
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Tidskriftsartikel (refereegranskat)abstract
- Social-ecological systems (SES) research has emerged as an important area of sustainability science, informing and supporting pressing issues of transformation towards more sustainable, just and equitable futures. To date, much SES research has been done in or from the Global North, where the challenges and contexts for supporting sustainability transformations are substantially different from the Global South. This paper synthesises emerging insights on SES dynamics that can inform actions and advance research to support sustainability transformations specifically in the southern African context. The paper draws on work linked to members of the Southern African Program on Ecosystem Change and Society (SAPECS), a leading SES research network in the region, synthesizing key insights with respect to the five core themes of SAPECS: (i) transdisciplinary and engaged research, (ii) ecosystem services and human well-being, (iii) governance institutions and management practices, (iv) spatial relationships and cross-scale connections, and (v) regime shifts, traps and transformations. For each theme, we focus on insights that are particularly novel, interesting or important in the southern African context, and reflect on key research gaps and emerging frontiers for SES research in the region going forward. Such place-based insights are important for understanding the variation in SES dynamics around the world, and are crucial for informing a context-sensitive global agenda to foster sustainability transformations at local to global scales.
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| 3. |
- Biggs, Reinette, et al.
(författare)
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The Southern African Program on Ecosystem Change and Society : an emergent community of practice
- 2023
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Ingår i: Ecosystems and People. - : Informa UK Limited. - 2639-5908 .- 2639-5916. ; 19:1
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Tidskriftsartikel (refereegranskat)abstract
- Sustainability-focused research networks and communities of practice have emerged as a key response and strategy to build capacity and knowledge to support transformation towards more sustainable, just and equitable futures. This paper synthesises insights from the development of a community of practice on social-ecological systems (SES) research in southern Africa over the past decade, linked to the international Programme on Ecosystem Change and Society (PECS). This community consists of a network of researchers who carry out place-based SES research in the southern African region. They interact through various cross-cutting working groups and also host a variety of public colloquia and student and practitioner training events. Known as the Southern African Program on Ecosystem Change and Society (SAPECS), its core objectives are to: (1) derive new approaches and empirical insights on SES dynamics in the southern African context; (2) have a tangible impact by mainstreaming knowledge into policy and practice; and (3) grow the community of practice engaged in SES research and governance, including researchers, students and practitioners. This paper reflects on experiences in building the SAPECS community, with the aim of supporting the development of similar networks elsewhere in the world, particularly in the Global South.
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| 4. |
- Verberk, Janneke D. M., et al.
(författare)
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The augmented value of using clinical notes in semi-automated surveillance of deep surgical site infections after colorectal surgery
- 2023
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Ingår i: Antimicrobial Resistance and Infection Control. - 2047-2994. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundIn patients who underwent colorectal surgery, an existing semi-automated surveillance algorithm based on structured data achieves high sensitivity in detecting deep surgical site infections (SSI), however, generates a significant number of false positives. The inclusion of unstructured, clinical narratives to the algorithm may decrease the number of patients requiring manual chart review. The aim of this study was to investigate the performance of this semi-automated surveillance algorithm augmented with a natural language processing (NLP) component to improve positive predictive value (PPV) and thus workload reduction (WR).MethodsRetrospective, observational cohort study in patients who underwent colorectal surgery from January 1, 2015, through September 30, 2020. NLP was used to detect keyword counts in clinical notes. Several NLP-algorithms were developed with different count input types and classifiers, and added as component to the original semi-automated algorithm. Traditional manual surveillance was compared with the NLP-augmented surveillance algorithms and sensitivity, specificity, PPV and WR were calculated.ResultsFrom the NLP-augmented models, the decision tree models with discretized counts or binary counts had the best performance (sensitivity 95.1% (95%CI 83.5-99.4%), WR 60.9%) and improved PPV and WR by only 2.6% and 3.6%, respectively, compared to the original algorithm.ConclusionsThe addition of an NLP component to the existing algorithm had modest effect on WR (decrease of 1.4-12.5%), at the cost of sensitivity. For future implementation it will be a trade-off between optimal case-finding techniques versus practical considerations such as acceptability and availability of resources.
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