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Monitoring vegetation moisture conditions is paramount to better understand and assess drought impacts on vegetation, enhance crop yield predictions, and improve ecosystem models. Passive microwave remote sensing allows retrievals of the vegetation optical depth (VOD; [unitless]), which is directly proportional to the vegetation water content (VWC; in units of water mass per unit area [kg/m2]). However, VWC is largely dependent on the dry biomass and structure imprints on the VOD signal. Previously, statistical models have been used to isolate the water component from the biomass and structure components. Physically-based approaches have not yet been proposed for this goal. In this study, we present a multi-sensor semi-physical approach to retrieve the vegetation moisture from the VOD and express it as Live Fuel Moisture Content (LFMC [%]; the percentage of water mass per dry biomass unit). The study is performed in the western United States for the period April 2015 – December 2018. There, in situ LFMC samples are available for assessment. We rely on a VOD model based on vegetation height data from GEDI/Sentinel-2 and radar backscatter from Sentinel-1, which account for the biomass and structure components. Vegetation moisture is retrieved at L-, X- and Ku-bands by minimizing the difference between the modeled VOD and the VOD estimates from SMAP (L-band) and AMSR-2 (X- and Ku-band) satellites. Results show that the LFMC retrievals are independent of canopy height, land cover, and radar backscatter, demonstrating the capability of the proposed algorithm to separate water dynamics from the biomass/structure component in VOD. LFMC estimates at X- and Ku-bands reproduce well the expected spatio-temporal dynamics of in situ LFMC. Results show good agreement with in situ at a regional scale, with Pearson's correlations (r) between in situ LFMC samples and LFMC estimates of 0.64 (Ku-band), 0.60 (X-band) and 0.47 (L-band). Similar results are obtained independently for shr, The work of D. Chaparro was supported by the XXXIII Ramón Areces Postdoctoral Fellowship and by MIT and the “la Caixa” Foundation (ID 100010434) under Grant LCF/ PR/MIT19/51840001 (MIT-Spain Seed Fund; D. Entekhabi, D. Chaparro). M. Piles thanks the support of Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital through the project AI4CS CIPROM/2021/56. M. Vall-llossera acknowledges funding from the Grant PID2020-114623RB-C32, funded by MCIN/AEI/10.13039/ 501100011033, and from the ERDF under Grant RTI2018-096765-A- 100. Also, the authors are grateful to MIT for supporting this research with the MIT-Germany Seed Fund (D. Entekhabi, T. Jagdhuber) and with the MIT-Belgium Seed Fund (D. Entekhabi, F. Jonard). A.F. Feldman was supported by both the ECOSTRESS science team and by a NASA Terrestrial Ecology scoping study for a dryland field campaign., Peer Reviewed, Postprint (author's final draft)

Vegetation optical depth (VOD) depends on the water, structure, and biomass of vegetation. Here, we propose a multi-sensor approach to isolate the water component from the VOD and to retrieve gravimetric vegetation moisture (m g ) in the western United States. The approach estimates VOD from radar and LiDAR data and minimizes the differences between these estimates and SMAP/AMSR2 VOD observations. This minimization allows to obtain the best fitting value of m g with help of a dielectric model. Results are consistent both in space (drier vegetation in arid areas) and time (drier vegetation in drier months). The mg estimates are in the same range than in situ mg data, with some underestimation (bias ~ -0.07 kg/kg). Statistical results are reasonable (r ~ 0.45, RMSE =0.10 kg/kg), yet the different spatial and temporal representation of in situ and remote measurements have an impact in the direct comparisons. Our results highlight the potential for developing new vegetation moisture datasets based on VOD decomposition., The work of D. Chaparro was supported by the XXXIII Ramón Areces Postdoctoral Fellowship, and by “la Caixa” Foundation (ID 100010434) under Grant LCF/PR/MIT19/51840001 (MIT-Spain Seed Fund). This research was supported also by the Spanish Ministry of Science and Innovation (MCIN/AEI /10.13039/501100011 033), through the coordinated project INTERACT PID2020-114623RB-C32. M. Piles thanks the support of Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital through the project AI4CS CIPROM/2021/56., Peer Reviewed, Postprint (author's final draft)

The vegetation optical depth (VOD) variable contains information on plant water content and biomass. It can be estimated alongside soil moisture from currently operating satellite radiometer missions, such as SMOS (ESA) and SMAP (NASA). The estimation of water fluxes, such as plant water uptake (PWU) and transpiration rate (TR), from these earth system parameters (VOD, soil moisture) requires assessing water potential gradients and flow resistances in the soil, the vegetation and the atmosphere. Yet water flux estimation remains an elusive challenge especially on a global scale. In this concept study, we conduct a field-scale experiment to test mechanistic models for the estimation of seasonal water fluxes (PWU and TR) of a winter wheat stand using measurements of soil moisture, VOD, and relative air humidity (RH) in a controlled environment. We utilize microwave L-band observations from a tower-based radiometer to estimate VOD of a wheat stand during the 2017 growing season at the Selhausen test site in Germany. From VOD, we first extract the gravimetric moisture of vegetation and then determine the relative water content (RWC) and vegetation water potential (VWP) of the wheat field. Although the relative water content could be directly estimated from VOD, our results indicate this may be challenging for the phenological phases, when rapid biomass and plant structure development take place within the wheat canopy. We estimate water uptake from the soil to the wheat plants from the difference between the soil and vegetation potentials divided by the flow resistance from soil into wheat plants. The TR from the wheat plants into the atmosphere was obtained from the difference between the vegetation and atmosphere water potentials divided by the flow resistances from plants to the atmosphere. For this, the required soil matric potential (SMP), the vapor pressure deficit (VPD), and the flow resistances were obtained from on-site observations of soil, plant, and atmosphe, David Chaparro has received funding by “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/MIT19/51840001, by the MIT-MISTI, by the XXXIII Ramón Areces Postdoctoral Fellowship, and by grants PID2020-114623RB-C32 and MDM-2016-0600 funded by MCIN/AEI/10.13039/501100011033 and by the European Regional Development Fund (ERDF, EU). María Piles was supported by grant RTI2018-096765-A-100 funded by MCIN/AEI/10.13039/501100011033 and by the European Regional Development Fund (ERDF, EU). The article processing charges for this open-access publication were covered by the German Aerospace Center (DLR)., Peer Reviewed, Postprint (published version)

In this article, we present a multipolarimetric estimation approach for two model-based vegetation structure parameters (shape A and orientation distribution ψ of the main canopy elements). The approach is based on a reduced observation set of three incoherent (no phase information) polarimetric backscatter intensities (|S HH | 2 , |S HV | 2 , and |S VV | 2 ) combined with a two-parameter (A P and ψ) discrete scatterer model of vegetation. The objective is to understand whether this confined set of observations contains enough information to estimate the two vegetation structure parameters from the L-band radar signals. In order to disentangle soil and vegetation scattering influences on these signals and ultimately perform a vegetation only retrieval of vegetation shape A and orientation distribution ψ, we use the subpixel spatial heterogeneity expressed by the covariation of co- and cross-polarized backscatter Γ PP-PQ of the neighboring cells and assume it is indicative for the amount of a vegetation-only co-to-cross-polarized backscatter ratio μ PP-PQ . The ratio-based retrieval approach enables a relative (no absolute backscatter) estimation of the vegetation structure parameters which is more robust compared to retrievals with absolute terms. The application of the developed algorithm on global L-band Soil Moisture Active Passive (SMAP) radar data acquired from April to July 2015 indicates the potential and limitations of estimating these two parameters when no fully polarimetric data are available. A focus study on six different regions of interest, spanning land cover from barren land to tropical rainforest, shows a steady increase in orientation distribution toward randomly oriented volumes and a continuous decrease in shape arriving at dipoles for tropical vegetation. A comparison with independent data sets of vegetation height and above-ground biomass confirms this consistent and meaningful retrieval of A P and ψ. The retrieved shapes and orientation distr, This work was supported with the MIT-Germany Seed Fund “Global Water Cycle and Environmental Monitoring using Active and Passive Satellite-based Microwave Instruments” and with the MIT-Belgium UCL Seed Fund “Early Detection of Plant Water Stress Using Remote Sensing”. C. Montzka is supported by the European Commission Horizon 2020 Program that funded the ERA-PLANET/GEOEssential (Grant Agreement no. 689443) project. M. Piles received partial funding through project RTI2018-096765-A-100 (MCIU/AEI/FEDER, UE)., Peer Reviewed, Postprint (author's final draft)

Purpose: The Swiss Federal Office of Public Health demanded a nationwide HTA registry for lumbar total disc arthroplasty (TDA), to decide about its reimbursement. The goal of the SWISS spine registry is to generate evidence about the safety and efficiency of lumbar TDA. Methods: Two hundred forty-eight cases treated between 3-2005 and 6-2006, who were eligible for the 5-year follow-up were included in the study. Follow-up rates for 3-6months, 1, 2 and 5years were 85.9, 77.0, 44.0 and 51.2%, respectively. Outcome measures were back and leg pain, medication consumption, quality of life, intraoperative and postoperative complication and revision rates. Additionally, segmental mobility, ossification, adjacent and distant segment degeneration were analysed at the 5-year follow-up. Results: There was a significant, clinically relevant and lasting reduction of back (preop/postop 73/29 VAS points) and leg pain (preop/postop VAS 55/22) and a consequently decreased analgesics consumption and quality of life improvement (preop/postop 0.30/0.76 EQ-5D score points) until 5years after surgery. The rates for intraoperative and early postoperative complications were 4.4 and 3.2%, respectively. The overall complication rate during five postoperative years was 23.4%, and the adjacent segment degeneration rate was 10.7%. In 4.4 % of patients, a revision surgery was performed. Cumulative survivorship probability for a revision/re-intervention-free 5-year postoperative course was 90.4%. At the 5-year follow-up, the average range of motion of the mobile segments (86.8%) was 9.7°. In 43.9% of patients, osteophytes at least potentially affecting the range of motion were seen. Conclusions: Lumbar TDA appeared as efficient in long-term pain alleviation, consequent reduction of pain medication consumption and improvement of quality of life. The procedure also appeared sufficiently safe, but surgeons have to be aware of a list of potential adverse events. The outcome is stable over the 5-year

Introduction: Cell-based therapies for regeneration of the degenerated intervertebral disc (IVD) are an alternative to current surgical intervention. Mesenchymal stem cells (MSCs), in combination with a scaffold, might be ideal candidates for regenerating nucleus pulposus (NP), the pressure-distributing part of the IVD. While the use of growth factors for MSCs differentiation currently receives major attention, in this study we compare the performance of sponge-like matrixes in supporting cell differentiation into NP-like cells. Materials and methods: Four types matrixes approved as medical devices for other applications were tested as scaffolds for MSCs: two made of equine or porcine collagen, one of gelatin and one of chitosan. Bone marrow-derived human MSCs were seeded in these scaffolds or embedded in alginate, as a three-dimensional control. After five weeks in culture, NP-like differentiation of the cell-scaffold constructs was analyzed by qRT-PCR, histology, total DNA quantification, proteoglycan accumulation and immunohistochemistry. Results: MSCs in collagen matrixes and gelatin produced more mRNA and proteins of the chondrogenic markers collagen type I, collagen type II (COL2) and aggrecan (ACAN), when compared with cells embedded in alginate or chitosan. Proteoglycan accumulation and cell survival were also higher in collagen and gelatin matrixes. Gene expression results were also confirmed by histological and immunohistochemical staining. In contrast to alginate control, the gene expression of the undesired bone marker osteopontin was lower in all tested groups. In porcine collagen supports, MSC expression ratio between COL2/ACAN closely resembled the expression of nucleus pulposus cells, but gene expression of recently described NP markers keratin19, PAX1 and FOXF1 was lower. Conclusions: Collagen supports provide a readily available, medically approved and effective scaffold for chondrogenic differentiation in vitro, but the phenotype of differentiated

The Radar Vegetation Index (RVI) is a well-established microwave metric of vegetation cover. The index utilizes measured linear scattering intensities from co- and cross-polarization and is normalized to ideally range from 0 to 1, increasing with vegetation cover. At long wavelengths (L-band) microwave scattering does not only contain information coming from vegetation scattering, but also from soil scattering (moisture & roughness) and therefore the standard formulation of RVI needs to be revised. Using global level SMAP L-band radar data, we illustrate that RVI runs up to 1.2, due to the pre-factor in the standard formulation not being adjusted to the scattering mechanisms at these low frequencies. Improvements on the RVI are subsequently proposed to obtain a normalized value range, to remove soil scattering influences as well as to mask out regions with dominant soil scattering at L-band (sparse or no vegetation cover). Two purely vegetation-based RVIs (called RVII and RVIII), are obtained by subtracting a forward modeled, attenuated soil scattering contribution from the measured backscattering intensities. Active and passive microwave information is used jointly to obtain the scattering contribution of the soil, using a physics-based multi-sensor approach; simulations from a particle model for polarimetric vegetation backscattering are utilized to calculate vegetation-based RVI-values without any soil scattering contribution. Results show that, due to the pre-factor in the standard formulation of RVI the index runs up to 1.2, atypical for an index normally ranging between zero and one. Correlation analysis between the improved radar vegetation indices (standard RVI and the indices with potential improvements RVII and RVIII) are used to evaluate the degree of independence of the indices from surface roughness and soil moisture contributions. The improved indices RVII and RVIII show reduced dependence on soil roughness and soil moisture. All RVI-indices examin