Uusitalo, L. | bioRxiv Science

bioRxiv2023

Quantifying stem cell derived islet graft volume and composition with FDOPA positron emission tomography

Stem cell derived islets (SC-islets) are being developed as a novel source of beta cells that would enable large scale cell replacement therapy for insulin dependent diabetes. Therapeutic use of SC-islets carries an inherent risk of unwanted growth; and multiple strategies are being explored for optimizing long-term SC-islet graft effectiveness. However, a method for noninvasive in vivo monitoring for SC-islet graft safety and efficacy is lacking, as current insulin secretion measurements are inadequate. Here, we demonstrate the potential of positron emission tomography (PET) for monitoring SC-islet grafts using two tracers: GLP1-receptor binding [18F]F-DBCO-exendin and dopamine precursor [18F]FDOPA. We could detect and longitudinally monitor human SC-islet grafts in calf muscles of immunocompromised mice. Importantly, graft volume quantified with PET strongly correlated with actual graft volume (r2=0.91 for [18F]F-DBCO-exendin). PET using [18F]F-DBCO-exendin allowed delineation of cystic structures and its uptake correlated with graft beta cell proportion, enabling study of SC-islet graft purity noninvasively. [18F]FDOPA performed similarly to [18F]F-DBCO-exendin, but with slightly weaker sensitivity. Uptake of neither tracer was biased in SC-islet grafts genetically rendered hyper- or hypoactive. Insulin secretion measurements under fasted, glucose-stimulated or hypoglycemic conditions did not correlate with graft volume. In conclusion, [18F]F-DBCO-exendin and [18F]FDOPA PET constitute powerful approaches to noninvasively assess SC-islet graft volume and composition regardless of their functionality. PET imaging could therefore be leveraged for optimizing safety and effectiveness of SC-islet grafts in patients with insulin dependent diabetes.

cell biology↗

bioRxiv2021

Causal approach to environmental risks of seabed mining

Seabed mining is approaching the commercial mining phase across the worlds oceans. This rapid industrialization of seabed resource use is introducing new pressures to marine environments. The environmental impacts of such pressures should be carefully evaluated prior to permitting new activities, yet observational data is mostly missing. Here, we examine the environmental risks of seabed mining using a causal, probabilistic network approach. Drawing on a series of interviews with a multidisciplinary group of experts, we outline the cause-effect pathways related to seabed mining activities to inform quantitative risk assessments. The approach consists of (1) iterative model building with experts to identify the causal connections between seabed mining activities and the affected ecosystem components, and (2) quantitative probabilistic modelling to provide estimates of mortality of benthic fauna in the Baltic Sea. The model is used to evaluate alternative mining scenarios, offering a quantitative means to highlight the uncertainties around the impacts of mining. We further outline requirements for operationalizing quantitative risk assessments, highlighting the importance of a cross-disciplinary approach to risk identification. The model can be used to support permitting processes by providing a more comprehensive description of the potential environmental impacts of seabed resource use, allowing iterative updating of the model as new information becomes available.

ecology↗