GM1 Oligosaccharide Crosses the Human Blood–Brain Barrier In Vitro by a Paracellular Route

Ganglioside GM1 (GM1) has been reported to functionally recover degenerated nervous system in vitro and in vivo, but the possibility to translate GM1′s potential in clinical settings is counteracted by its low ability to overcome the blood–brain barrier (BBB) due to its amphiphilic nature. Interestingly, the soluble and hydrophilic GM1-oligosaccharide (OligoGM1) is able to punctually replace GM1 neurotrophic functions alone, both in vitro and in vivo. In order to take advantage of OligoGM1 properties, which overcome GM1′s pharmacological limitations, here we characterize the OligoGM1 brain transport by using a human in vitro BBB model. OligoGM1 showed a 20-fold higher crossing rate than GM1 and time–concentration-dependent transport. Additionally, OligoGM1 crossed the barrier at 4 °C and in inverse transport experiments, allowing consideration of the passive paracellular route. This was confirmed by the exclusion of a direct interaction with the active ATP-binding cassette (ABC) transporters using the “pump out” system. Finally, after barrier crossing, OligoGM1 remained intact and able to induce Neuro2a cell neuritogenesis by activating the TrkA pathway. Importantly, these in vitro data demonstrated that OligoGM1, lacking the hydrophobic ceramide, can advantageously cross the BBB in comparison with GM1, while maintaining its neuroproperties. This study has improved the knowledge about OligoGM1′s pharmacological potential, offering a tangible therapeutic strategy.

Anthropogenic CO2 emission uncertainties

<p>The CO2 Human Emissions (CHE) project has been tasked by the European Commission to prepare the development of a European capacity to monitor anthropogenic CO2 emissions. The monitoring of fossil fuel CO2 emissions has to come with a sufficiently low uncertainty in order to be useful for policymakers. In this context, the main approaches to estimate fossil fuel emissions, apart from bottom-up inventories, are based on inverse transport<br>modeling either on its own or within a coupled carbon cycle fossil fuel data assimilation system. Both approaches make use of atmospheric CO2 and other tracers (e.g., CO and NOx) and rely on the availability of prior fossil fuel CO2 emission estimates and uncertainties (as well as biogenic fluxes for the transport inverse modeling). For a robust estimate of the uncertainty, information from different sources needs to be brought together.<br>A methodology to calculate yearly and monthly anthropogenic CO2 emission uncertainties based on IPCC guidelines (2006 IPCC Guidelines for National Greenhouse Gas Inventories + its 2019 Refinements) has been developed. Emission uncertainties are calculated for all world countries, under the assumption of two categories of world countries, depending on whether the country’s statistical infrastructure is well or less developed. For well-developed statistical infrastructure, emission uncertainties are lower, while less developed statistical infrastructure countries have higher emission uncertainties. A sensitivity analysis is investigating the impact of the well or less developed infrastructure assumption for several countries on the global emission uncertainty. Sensitivity experiments with different anthropogenic CO2 sources distributions, as well as the first results on using these prior anthropogenic CO2 uncertainties in ensemble perturbation runs will be presented.</p>

Evaluation of model-data mismatch errors in the CarboScope-Regional Inversion System

<p>With an increasing network of atmospheric stations that produce a constant data stream, top-down inverse transport modelling of GHGs in a quasi-operational way becomes feasible. The CarboScope-Regional inversion system embeds the regional inversion, within a global inversion using the two-step approach. The regional inversion consists of Lagrangian mesoscale transport from STILT, prior fluxes from the diagnostic VPRM biosphere model, and anthropogenic emissions from a combination of EDGAR v4.3 with the annually updated BP statistical report. Regional ocean fluxes were derived from the CarboScope ocean flux product based on SOCATv2019 data. The inversion uses atmospheric observations from 44 stations to infer biosphere-atmosphere exchange. The regional domain covers most of Europe (33 – 73N, 15W – 35E) with a spatial resolution of 0.25 degree for fluxes and 0.5 degree for flux corrections inferred by the inversion (i.e. the state space).<br>One of the critical parameters is the assumed uncertainty of the observations, and the major contribution to this is the model-data mismatch error, or representation error. Within CarboScope-Regional, this model-data mismatch error is specified differently for different station types, such as tall towers, mountain or coastal stations, etc. To evaluate the validity and appropriateness of these assumed uncertainties, a leave-one-out cross-validation is applied for a single year, using all stations except one for the inversion, and comparing posterior concentrations predicted for the omitted station with the observed concentrations. Results of this cross-validation will be presented separately for the different station types, and will be used to evaluate the magnitude of the assumed model-data mismatch errors.</p>