| 1. |
- Giubilato, E, et al.
(författare)
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Risk Management Framework for Nano-Biomaterials Used in Medical Devices and Advanced Therapy Medicinal Products
- 2020
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Ingår i: Materials (Basel, Switzerland). - : MDPI AG. - 1996-1944. ; 13:20
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Tidskriftsartikel (refereegranskat)abstract
- The convergence of nanotechnology and biotechnology has led to substantial advancements in nano-biomaterials (NBMs) used in medical devices (MD) and advanced therapy medicinal products (ATMP). However, there are concerns that applications of NBMs for medical diagnostics, therapeutics and regenerative medicine could also pose health and/or environmental risks since the current understanding of their safety is incomplete. A scientific strategy is therefore needed to assess all risks emerging along the life cycles of these products. To address this need, an overarching risk management framework (RMF) for NBMs used in MD and ATMP is presented in this paper, as a result of a collaborative effort of a team of experts within the EU Project BIORIMA and with relevant inputs from external stakeholders. The framework, in line with current regulatory requirements, is designed according to state-of-the-art approaches to risk assessment and management of both nanomaterials and biomaterials. The collection/generation of data for NBMs safety assessment is based on innovative integrated approaches to testing and assessment (IATA). The framework can support stakeholders (e.g., manufacturers, regulators, consultants) in systematically assessing not only patient safety but also occupational (including healthcare workers) and environmental risks along the life cycle of MD and ATMP. The outputs of the framework enable the user to identify suitable safe(r)-by-design alternatives and/or risk management measures and to compare the risks of NBMs to their (clinical) benefits, based on efficacy, quality and cost criteria, in order to inform robust risk management decision-making.
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| 2. |
- Gerhards, R, et al.
(författare)
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Oligodendrocyte myelin glycoprotein as a novel target for pathogenic autoimmunity in the CNS
- 2020
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Ingår i: Acta neuropathologica communications. - : Springer Science and Business Media LLC. - 2051-5960. ; 8:1, s. 207-
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Tidskriftsartikel (refereegranskat)abstract
- Autoimmune disorders of the central nervous system (CNS) comprise a broad spectrum of clinical entities. The stratification of patients based on the recognized autoantigen is of great importance for therapy optimization and for concepts of pathogenicity, but for most of these patients, the actual target of their autoimmune response is unknown. Here we investigated oligodendrocyte myelin glycoprotein (OMGP) as autoimmune target, because OMGP is expressed specifically in the CNS and there on oligodendrocytes and neurons. Using a stringent cell-based assay, we detected autoantibodies to OMGP in serum of 8/352 patients with multiple sclerosis, 1/28 children with acute disseminated encephalomyelitis and unexpectedly, also in one patient with psychosis, but in none of 114 healthy controls. Since OMGP is GPI-anchored, we validated its recognition also in GPI-anchored form. The autoantibodies to OMGP were largely IgG1 with a contribution of IgG4, indicating cognate T cell help. We found high levels of soluble OMGP in human spinal fluid, presumably due to shedding of the GPI-linked OMGP. Analyzing the pathogenic relevance of autoimmunity to OMGP in an animal model, we found that OMGP-specific T cells induce a novel type of experimental autoimmune encephalomyelitis dominated by meningitis above the cortical convexities. This unusual localization may be directed by intrathecal uptake and presentation of OMGP by meningeal phagocytes. Together, OMGP-directed autoimmunity provides a new element of heterogeneity, helping to improve the stratification of patients for diagnostic and therapeutic purposes.
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| 3. |
- Bakris, George L, et al.
(författare)
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Effect of Finerenone on Chronic Kidney Disease Outcomes in Type 2 Diabetes
- 2020
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Ingår i: New England Journal of Medicine. - 0028-4793 .- 1533-4406. ; 383:23, s. 2219-2229
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Finerenone, a nonsteroidal, selective mineralocorticoid receptor antagonist, reduced albuminuria in short-term trials involving patients with chronic kidney disease (CKD) and type 2 diabetes. However, its long-term effects on kidney and cardiovascular outcomes are unknown.METHODS: In this double-blind trial, we randomly assigned 5734 patients with CKD and type 2 diabetes in a 1:1 ratio to receive finerenone or placebo. Eligible patients had a urinary albumin-to-creatinine ratio (with albumin measured in milligrams and creatinine measured in grams) of 30 to less than 300, an estimated glomerular filtration rate (eGFR) of 25 to less than 60 ml per minute per 1.73 m2 of body-surface area, and diabetic retinopathy, or they had a urinary albumin-to-creatinine ratio of 300 to 5000 and an eGFR of 25 to less than 75 ml per minute per 1.73 m2. All the patients were treated with renin-angiotensin system blockade that had been adjusted before randomization to the maximum dose on the manufacturer's label that did not cause unacceptable side effects. The primary composite outcome, assessed in a time-to-event analysis, was kidney failure, a sustained decrease of at least 40% in the eGFR from baseline, or death from renal causes. The key secondary composite outcome, also assessed in a time-to-event analysis, was death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure.RESULTS: During a median follow-up of 2.6 years, a primary outcome event occurred in 504 of 2833 patients (17.8%) in the finerenone group and 600 of 2841 patients (21.1%) in the placebo group (hazard ratio, 0.82; 95% confidence interval [CI], 0.73 to 0.93; P = 0.001). A key secondary outcome event occurred in 367 patients (13.0%) and 420 patients (14.8%) in the respective groups (hazard ratio, 0.86; 95% CI, 0.75 to 0.99; P = 0.03). Overall, the frequency of adverse events was similar in the two groups. The incidence of hyperkalemia-related discontinuation of the trial regimen was higher with finerenone than with placebo (2.3% and 0.9%, respectively).CONCLUSIONS: In patients with CKD and type 2 diabetes, treatment with finerenone resulted in lower risks of CKD progression and cardiovascular events than placebo. (Funded by Bayer; FIDELIO-DKD ClinicalTrials.gov number, NCT02540993.).
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| 4. |
- Watson-Parris, D., et al.
(författare)
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ClimateBench v1.0 : A Benchmark for Data-Driven Climate Projections
- 2022
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Ingår i: Journal of Advances in Modeling Earth Systems. - 1942-2466. ; 14:10
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Tidskriftsartikel (refereegranskat)abstract
- Many different emission pathways exist that are compatible with the Paris climate agreement, and many more are possible that miss that target. While some of the most complex Earth System Models have simulated a small selection of Shared Socioeconomic Pathways, it is impractical to use these expensive models to fully explore the space of possibilities. Such explorations therefore mostly rely on one-dimensional impulse response models, or simple pattern scaling approaches to approximate the physical climate response to a given scenario. Here we present ClimateBench-the first benchmarking framework based on a suite of Coupled Model Intercomparison Project, AerChemMIP and Detection-Attribution Model Intercomparison Project simulations performed by a full complexity Earth System Model, and a set of baseline machine learning models that emulate its response to a variety of forcers. These emulators can predict annual mean global distributions of temperature, diurnal temperature range and precipitation (including extreme precipitation) given a wide range of emissions and concentrations of carbon dioxide, methane and aerosols, allowing them to efficiently probe previously unexplored scenarios. We discuss the accuracy and interpretability of these emulators and consider their robustness to physical constraints such as total energy conservation. Future opportunities incorporating such physical constraints directly in the machine learning models and using the emulators for detection and attribution studies are also discussed. This opens a wide range of opportunities to improve prediction, robustness and mathematical tractability. We hope that by laying out the principles of climate model emulation with clear examples and metrics we encourage engagement from statisticians and machine learning specialists keen to tackle this important and demanding challenge.
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