Core Ideas: Cosmic‐ray neutron data are used to inversely estimate soil hydraulic properties. The forward neutron operator COSMIC is coupled with the vadose zone model HYDRUS‐1D. Bayesian analyses confirm the information content of cosmic‐ray neutron data. Observations of soil moisture content from remote sensing platforms can be used in conjunction with hydrological models to inversely estimate soil hydraulic properties (SHPs). In recent years, cosmic‐ray neutron sensing (CRNS) has proven to be a reliable method for the estimation of area‐average soil moisture at field scales. However, its use in the inverse estimation of the effective SHPs is largely unexplored. Thus, the main objective of this study was to assess the information content of aboveground fast‐neutron counts to estimate SHPs using both a synthetic modeling study and actual experimental data from the Rollesbroich catchment in Germany. For this, the forward neutron operator COSMIC was externally coupled with the hydrological model HYDRUS‐1D. The coupled model was combined with the Affine Invariant Ensemble Sampler to calculate the posterior distributions of effective soil hydraulic parameters as well as the model‐predictive uncertainty for different synthetic and experimental scenarios. Measured water contents at different depths were used to assess estimated SHPs. The analysis of both synthetic and actual CRNS data from homogenous and heterogeneous soil profiles, respectively, led to confident estimations of the shape parameters α and n , while higher uncertainty was observed for the saturated hydraulic conductivity. Furthermore, results demonstrated that neutron data are less influenced by local sources of uncertainty compared with near‐surface point measurements. The simultaneous use of CRNS and water content data further reduced the overall uncertainty, opening up new perspectives for the combination of CRNS with other remote sensing techniques for the inverse estimation of the effective SHPs.

The FGF2/FGFR1 paracrine loop is involved in the cross-talk between breast cancer cells and components of the tumor stroma as cancer-associated fibroblasts (CAFs). By quantitative PCR (qPCR), western blot, immunofluorescence analysis, ELISA and ChIP assays, we demonstrated that 17β-estradiol (E2) and the G protein estrogen receptor (GPER) agonist G-1 induce the up-regulation and secretion of FGF2 via GPER together with the EGFR/ERK/c-fos/AP-1 signaling cascade in (ER)-negative primary CAFs. Evaluating the genetic alterations from METABRIC and TCGA datasets, we then assessed that FGFR1 is the most frequently amplified FGFRs family member and its amplification/expression associates with shorter survival rates in breast cancer patients. Therefore, in order to assess the functional FGF2/FGFR1 interplay between CAFs and breast cancer cells, we generated the FGFR1-knockout MDA-MB-231 cells using CRISPR/Cas9 genome editing strategy. Using conditioned medium from estrogen-stimulated CAFs, we established that the activation of FGF2/FGFR1 paracrine signaling triggers the expression of the connective tissue growth factor (CTGF), leading to the migration and invasion of MDA-MB-231 cells. Our findings shed new light on the role elicited by estrogens through GPER in the activation of the FGF2/FGFR1 signaling. Moreover, our findings may identify further biological targets that could be considered in innovative combination strategies halting breast cancer progression.