Water sources for root water uptake : Using stable isotopes of hydrogen and oxygen as a research tool in agricultural and agroforestry systems

DP was supported by the autonomous Province of Bozen-Bolzano and Free University of Bozen-Bolzano, Italy [grant number B83G13000420003]; JG was supported by the Carnegie Trust for the Universities of Scotland [grant reference: RIG008284] and the UK Natural Environment Research Council [grant numbers: NE/N007611/1 and NE/S009167/1].Peer reviewedPostprin

How can we model subsurface stormflow at the catchment scale if we cannot measure it?

Subsurface stormflow (SSF) can be a dominant run‐off generation process in humid mountainous catchments (e.g., Bachmair & Weiler, 2011; Blume & van Meerveld, 2015; Chifflard, Didszun, & Zepp, 2008). Generally, SSF develops in structured soils where bedrock or a less permeable soil layer is overlaid by a more permeable soil layer and vertically percolating water is deflected, at least partially, in a lateral downslope direction due to the slope inclination. SSF can also occur when groundwater levels rise into more permeable soil layers and water flows laterally through the more permeable layers to the stream (“transmissivity feedback mechanism”; Bishop, Grip, & O'Neill, 1990). The different existing terms for SSF in the hydrological literature such as shallow subsurface run‐off, interflow, lateral flow, or soil water flow reflects the different underlying process concepts developed in various experimental studies in different environments by using different experimental approaches at different spatial and temporal scales (Weiler, McDonnell, Tromp‐van Meerveld, & Uchida, 2005). Intersite comparisons and the extraction of general rules for SSF generation and its controlling factors are still lacking, which hampers the development of appropriate approaches for modelling SSF. But appropriate prediction of SSF is essential due to its clear influence on run‐off generation at the catchment scale (e.g., Chifflard et al., 2010; Zillgens, Merz, Kirnbauer, & Tilch, 2005), on the formation of floods (e.g., Markart et al., 2013, 2015) and on the transport of nutrients or pollutants from the hillslopes into surface water bodies (Zhao, Tang, Zhao, Wang, & Tang, 2013). However, a precise simulation of SSF in models requires an accurate process understanding including, knowledge about water pathways, residence times, magnitude of water fluxes, or the spatial origin of SSF within a given catchment because such factors determine the transport of subsurface water and solutes to the stream. But due to its occurrence in the subsurface and its spatial and temporal variability, determining and quantifying the processes generating SSF is a challenging task as they cannot be observed directly. Therefore, it is logical to ask whether we can really model SSF correctly if we cannot measure it well enough on the scale of interest (Figure 1). This commentary reflects critically on whether current experimental concepts and modelling approaches are sufficient to predict the contribution of SSF to the run‐off at the catchment scale. This applies in particular to the underlying processes, controlling factors, modelling approaches, research gaps, and innovative strategies to trace SSF across different scales

Arsenic and chromium partitioning in a podzolic soil contaminated by chromated copper arsenate

This research combined the use of selective extractions and x-ray spectroscopy to examine the fate of As and Cr in a podzolic soil contaminated by chromated copper arsenate (CCA). Iron was enriched in the upper 30 cm due to a previous one-time treatment of the soil with Fe(II). High oxalate-soluble Al concentrations in the Bs horizon of the soil and micro-XRD data indicated the presence of short-range ordered aluminosilicates (i.e. proto-imogolite allophane, PIA). In the surface layers, Cr, as Cr(III), was partitioned between a mixed Fe(III)/Cr(III) solid phase that formed upon the Fe(II) application (25-50%) and a recalcitrant phase (50-75%) likely consisting of organic material such as residual CCA-treated wood. Deeper in the profile Cr appeared to be largely in the form of extractable (hydr)oxides. Throughout the soil, As was present as As(V). In the surface layers a considerable fraction of As was also associated with a recalcitrant phase, probably CCA-treated woody debris, and the remainder was associated with (hydr)oxide-like solid phases. In the Bs horizon, however, XAS and XRF findings strongly pointed to the presence of PIA acting as an effective adsorbent for As. This research shows for the first time the relevance of PIA for the adsorption of As in natural soils

Entrevistas a los ex integrantes de los Consejos de Redacción de Lecciones y Ensayos (1956-2016)

Fil: Ortiz, Tulio. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Teoría del Estado-Profesor Emérito. Buenos Aires, ArgentinaFil: Díaz de Vivar, Elisa Matilde. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Derecho Civil I. Buenos Aires, ArgentinaFil: Dulitzky, Ariel. Universidad de Buenos Aires. Facultad de Derecho.Cátedra Derechos Humanos. Buenos Aires, ArgentinaFil: Dulitzky, Ariel. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Derecho Constitucional. Buenos Aires, ArgentinaFil: Ferrante, Marcelo. Universidad de Buenos Aires. Facultad de Derecho. Buenos Aires, ArgentinaFil: Bloch, Ivana Verónica. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Elementos de Derecho Penal y Procesal Penal. Buenos Aires, ArgentinaFil: Bergallo, Paola. CONICET-Universidad de Buenos Aires. Facultad de Derecho. Buenos Aires, ArgentinaFil: Filippini, Leonardo G. Universidad de Buenos Aires. Facultad de Derecho. Centro de Estudios de Ejecución Penal (CEEP). Buenos Aires, ArgentinaFil: Sigal, Martín. Universidad de Buenos Aires. Facultad de Derecho. Centro de Derechos Humanos (CDH). Buenos Aires, ArgentinaFil: Bloch, Demise. Universidad de Buenos Aires. Facultad de Derecho. Buenos Aires, ArgentinaFil: Freedman, Diego. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Finanzas Públicas y Derecho Tributario. Buenos Aires, ArgentinaFil: Pezzot, Romina. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Derecho Internacional Público. Buenos Aires, ArgentinaFil: Hopp, Cecilia. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Derecho Administrativo. Buenos Aires, ArgentinaFil: Rojas, Mishkila. Universidad de Buenos Aires. Facultad de Derecho. Proyectos DeCyT. Buenos Aires, ArgentinaFil: Garaventa, Carlos A. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Derecho Público II. Buenos Aires, ArgentinaFil: Kenny, Patricio Enrique. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Teoría General del Derecho. Buenos Aires, ArgentinaFil: Ramallo, María de los Ángeles. Universidad de Buenos Aires. Facultad de Derecho. Centro de Derechos Humanos (CDH). Buenos Aires, ArgentinaFil: Furfaro, Lautaro. Universidad de Buenos Aires. Facultad de Derecho; ArgentinaFil: Piqué, María Luisa. Universidad de Buenos Aires. Facutad de Derecho. Cátedra Elementos de Derecho Constitucional. Buenos Aires, ArgentinaFil: Benente, Mauro. Universidad de Buenos Aires. Facultad de Derecho. Instituto de Investigaciones Jurídicas y Sociales Ambrosio L. Gioja. Buenos Aires, ArgentinaFil: Etchegorry, María Alejandra. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Derecho Internacional Privado. Buenos Aires, ArgentinaFil: Monti, Ezequiel. Universidad de Buenos Aires. Facultad de Derecho. Teoría General y Filosofía del Derecho. Buenos Aires, ArgentinaFil: Green Martínez, Sebastián. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Derecho Internacional Público. Buenos Aires, ArgentinaFil: Bulit Goñi, Magdalena. Universidad de Buenos Aires. Facultad de Derecho. Buenos Aires, ArgentinaFil: Brodsky, Jonathan Matías. Universidad de Buenos Aires. Facultad de Derecho. Cátedra Obligaciones Civiles y Comerciales. Buenos Aires, ArgentinaFil: Olivera, Federico Eduardo. Universidad de Buenos Aires. Facultad de Derecho. Proyecto UBACyT. Buenos Aires, Argentin

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing

The genomic and transcriptional landscape of primary central nervous system lymphoma

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations