Abstract To date, there are no efficacious translational solutions for end-stage urinary bladder dysfunction. Current surgical strategies, including urinary diversion and bladder augmentation enterocystoplasty (BAE), utilize autologous intestinal segments (e.g. ileum) to increase bladder capacity to protect renal function. Considered the standard of care, BAE is fraught with numerous short- and long-term clinical complications. Previous clinical trials employing tissue engineering approaches for bladder tissue regeneration have also been unable to translate bench-top findings into clinical practice. Major obstacles still persist that need to be overcome in order to advance tissue-engineered products into the clinical arena. These include scaffold/bladder incongruencies, the acquisition and utility of appropriate cells for anatomic and physiologic tissue recapitulation, and the choice of an appropriate animal model for testing. In this study, we demonstrate that the elastomeric, bladder biomechanocompatible poly(1,8-octamethylene-citrate-co-octanol) (PRS; synthetic) scaffold coseeded with autologous bone marrow-derived mesenchymal stem cells and CD34+ hematopoietic stem/progenitor cells support robust long-term, functional bladder tissue regeneration within the context of a clinically relevant baboon bladder augmentation model simulating bladder trauma. Partially cystectomized baboons were independently augmented with either autologous ileum or stem-cell-seeded small-intestinal submucosa (SIS; a commercially available biological scaffold) or PRS grafts. Stem-cell synergism promoted functional trilayer bladder tissue regeneration, including whole-graft neurovascularization, in both cell-seeded grafts. However, PRS-augmented animals demonstrated fewer clinical complications and more advantageous tissue characterization metrics compared to ileum and SIS-augmented animals. Two-year study data demonstrate that PRS/stem-cell-seeded grafts drive bladder tissue regeneration and are a suitable alternative to BAE.
Special Feature: The Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC).-- 42 pages, 16 figures, 3 tables, supplemental files https://doi.org/10.1525/elementa.2021.000046.-- Data accessibility statement: All data in this manuscript are publicly available from online repositories. Note that most data sets contain raw or preliminary data, while advanced versions will become available in future. The data may be found under the following references: drift track data (Figure 1, Nicolaus et al., doi:10.1594/PANGAEA.937204), observational dates (Figure 4, Nicolaus et al., doi:10.5281/zenodo.5898517), panorama photographs (Figure 5, Nicolaus et al., doi:10.1594/PANGAEA.938534), TLS data (Figure 6, Clemens-Sewall et al., doi:10.18739/A27S7HT3B), ROV radiation data (Figure 7, Nicolaus et al., doi:10.1594/PANGAEA.935688), surface albedo data on ground (Figure 8, Smith et al., broadband data under doi:10.18739/A2KK94D36 and spectral data under doi:10.18739/A2FT8DK8Z) and from the HELiX drone (Figure 8, Calmer et al., doi:10.18739/A2GH9BB0Q), on-ice RS data (Figure 10, Spreen et al., doi:10.5281/zenodo.5725870), surface images from thermal infrared and true color (Figure 11, Thielke et al, doi:10.1594/PANGAEA.934666), drift speed data from Polarstern (Figure 12, Nicolaus et al., doi:10.1594/PANGAEA.937204), deformation data from SAR (Figure 13, von Albedyll et al, doi:10.5281/zenodo.5195366), sea ice thickness and snow depth distribution (Figure 14, Hendricks et al., doi:10.5281/zenodo.5155244), sea ice physical properties (Figure 15, in Tables S2 and S3) with a sea ice core overview (Granskog et al., doi:10.5281/zenodo.4719905), snow pack properties (Figure 16, Macfarlane et al., doi:10.1594/PANGAEA.935934), and ship radar video sequence (Jäkel et al., doi:10.5446/52953) ; Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice ; This work was funded by the following: – the German Federal Ministry of Education and Research (BMBF) through financing the Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) and the Polarstern expedition PS122 under the grant N-2014-H-060_Dethloff, – the AWI through its projects: AWI_ROV, AWI_ICE, AWI_SNOW, AWI_ECO. The AWI buoy program and ROV work were funded by the Helmholtz strategic investment Frontiers in Arctic Marine Monitoring (FRAM), – the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through the Transregional Collaborative Research Centre TRR-172 "ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3" (grant 268020496), the International Research Training Group 1904 ArcTrain (grant 221211316), the MOSAiCmicrowaveRS project (grant 420499875), the HELiPOD grant (LA 2907/11-1), and the SCASI (NI 1096/5-1 and KA 2694/7-1) and SnowCast (AR1236/1) projects, – the BMBF through the projects Diatom-ARCTIC (03F0810A), IceSense (BMBF 03F0866A and 03F0866B), MOSAiC3-IceScan (BMBF 03F0916A), NiceLABpro (BMBF 03F0867A), SSIP (01LN1701A), and SIDFExplore (03F0868A), – the German Federal Ministry for Economic Affairs and Energy through the project ArcticSense (BMWi 50EE1917A), – the US National Science Foundation (NSF) through the project PROMIS (OPP-1724467, OPP-1724540, and OPP-1724748), the buoy work (OPP-1723400), the MiSNOW (OPP-1820927), the snow transect work (OPP-1820927), the sea ice coring work (OPP-1735862), the HELiX drone operations (OPP-1805569), surface energy fluxes (OPP-1724551), Climate Active Trace Gases (OPP-1807496), and Reactive Gas Chemistry (OPP-1914781). The last 4 of these were also supported by the NOAA Physical Sciences Laboratory, – the European Union's Horizon 2020 research and innovation program projects ARICE (grant 730965) for berth fees associated with the participation of the DEARice team and INTAROS (grant 727890) supporting the drone and albedo measurements, – the US Department of Energy Atmospheric Radiation Measurement (ARM) and Atmospheric System Research (ASR) programs (DE-SC0019251, DE-SC0021341), – the National Aeronautics and Space Administration (NASA) project 80NSSC20K0658, – the European Space Agency (ESA) MOSAiC microwave radiometer (EMIRAD2, ELBARA, HUTRAD), (EMIRAD2, ELBARA, HUTRAD), CIMRex (contract 4000125503/18/NL/FF/gp) and GNSS-R (P.O. 5001025474, C.N. 4000128320/19/NL/FF/ab) GNSS-R (contracts P.O. 5001025474 and C.N. 4000128320/19/NL/FF/ab) projects, – the Canadian Space Agency FAST project (grant no. 19FACALB08), – EUMETSAT support for microwave scatterometer measurements, – the Research Council of Norway through the projects HAVOC (grant no. 280292), SIDRiFT (grant no. 287871), and CAATEX (grant no. 280531), – the Fram Centre (Tromsø, Norway), from its flagship program on Arctic Ocean through the PHOTA project, – the UKRI Natural Environment Research Council (NERC) and BMBF, who jointly funded the Changing Arctic Ocean program (project Diatom Arctic, NE/R012849/1 and 03F0810A), – the UK Natural Environment Research Council (project SSAASI-CLIM grant NE/S00257X/1), – the Agencia Estatal de Investigación AEI of Spain (grant no. PCI2019-111844-2, RTI2018-099008-B-C22), – the Swedish Research Council (VR, grant no. 2018-03859), – the Swedish Polar Research Secretariat for berth fees for MOSAiC, – the Swiss Polar Institute project SnowMOSAiC, – the Werner-Petersen-Foundation for the development of a remotely operated floating platform (grant no. FKZ 2019/610). ; Peer reviewed
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1714977115/-/DCSupplemental. ; Knowledge about the biogeographic affinities of the world's tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world's tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests. ; European Union's Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie Grant Agreement 660020, Instituto Bem Ambiental (IBAM), Myr Projetos Sustentáveis, IEF, and CNPq, CAPES FAPEMIG, German Research Foundation (DFG; Grants CRC 552, CU127/3-1, HO 3296/2-2, HO3296/4-1, and RU 816), UNAM-PAPIIT IN218416 and Semarnat-CONACYT 128136, Conselho Nacional de Desenvolvimento Científico e Tecnoloógico (CNPq, Brazil), Fundação Grupo Boticário de Proteção à Natureza/Brazil, PAPIIT-DGAPA-UNAM (Project IN-204215), National Geographic Society, National Foundation for Scientific and Technology Development Vietnam (Grant 106.11-2010.68), Operation Wallacea, and core funding for Crown Research Institutes from the New Zealand Ministry of Business, Innovation and Employment's Science and Innovation Group. ; Peer-reviewed ; Publisher Version
