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- Sherratt, K., et al.
(författare)
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Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
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Ingår i: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.
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| 2. |
- Boddaert, S., et al.
(författare)
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Fire safety of BIPV : International mapping of accredited and R&D facilities in the context of codes and standards 2023
- 2023
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The objective of Task 15 of the IEA Photovoltaic Power Systems Programme is to create an enabling framework to accelerate the penetration of BIPV products in the global market of renewables, resulting in an equal playing field for BIPV products, BAPV products and regular building envelope components, respecting mandatory issues, aesthetic issues, reliability issues, and financial issues.Subtask E of Task 15 is focused on pre-normative international research on BIPV characterisation methods and activity E.3 is dedicated to fire safety of BIPV modules and installations.
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| 3. |
- Codenotti, S, et al.
(författare)
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Hyperactive Akt1 Signaling Increases Tumor Progression and DNA Repair in Embryonal Rhabdomyosarcoma RD Line and Confers Susceptibility to Glycolysis and Mevalonate Pathway Inhibitors
- 2022
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Ingår i: Cells. - : MDPI AG. - 2073-4409. ; 11:18
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Tidskriftsartikel (refereegranskat)abstract
- In pediatric rhabdomyosarcoma (RMS), elevated Akt signaling is associated with increased malignancy. Here, we report that expression of a constitutively active, myristoylated form of Akt1 (myrAkt1) in human RMS RD cells led to hyperactivation of the mammalian target of rapamycin (mTOR)/70-kDa ribosomal protein S6 kinase (p70S6K) pathway, resulting in the loss of both MyoD and myogenic capacity, and an increase of Ki67 expression due to high cell mitosis. MyrAkt1 signaling increased migratory and invasive cell traits, as detected by wound healing, zymography, and xenograft zebrafish assays, and promoted repair of DNA damage after radiotherapy and doxorubicin treatments, as revealed by nuclear detection of phosphorylated H2A histone family member X (γH2AX) through activation of DNA-dependent protein kinase (DNA-PK). Treatment with synthetic inhibitors of phosphatidylinositol-3-kinase (PI3K) and Akt was sufficient to completely revert the aggressive cell phenotype, while the mTOR inhibitor rapamycin failed to block cell dissemination. Furthermore, we found that pronounced Akt1 signaling increased the susceptibility to cell apoptosis after treatments with 2-deoxy-D-glucose (2-DG) and lovastatin, enzymatic inhibitors of hexokinase, and 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR), especially in combination with radiotherapy and doxorubicin. In conclusion, these data suggest that restriction of glucose metabolism and the mevalonate pathway, in combination with standard therapy, may increase therapy success in RMS tumors characterized by a dysregulated Akt signaling.
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