Classification of finite dimensional uniserial representations of conformal Galilei algebras

With the aid of the $6j$-symbol, we classify all uniserial modules of $\mathfrak{sl}(2)\ltimes \mathfrak{h}_{n}$, where $\mathfrak{h}_{n}$ is the Heisenberg Lie algebra of dimension $2n+1$.Comment: Some references added, introduction expanded, title change

Study of the Genetic Variants in BRCA1/2 and Non-BRCA Genes in a Population-Based Cohort of 2155 Breast/Ovary Cancer Patients, Including 443 Triple-Negative Breast Cancer Patients, in Argentina

Gene/s sequencing in hereditary breast/ovary cancer (HBOC) in routine diagnosis is challenged by the analysis of panels. We aim to report a retrospective analysis of BRCA1/2 and non-BRCA gene sequencing in patients with breast/ovary cancer (BOC), including triple-negative breast cancer (TNBC), in our population. In total 2155 BOC patients (1900 analyzed in BRCA1/2 and 255 by multigenic panels) gave 372 (17.2.6%) and 107 (24.1%) likely pathogenic/pathogenic variants (LPVs/PVs), including BRCA and non-BRCA genes, for the total and TNBC patients, respectively. When BOC was present in the same proband, a 51.3% rate was found for LPVs/PVs in BRCA1/2. Most of the LPVs/PVs in the panels were in BRCA1/2; non-BRCA gene LPVs/PVs were in CDH1, CHEK2, CDKN2A, MUTYH, NBN, RAD51D, and TP53. TNBC is associated with BRCA1/2 at a higher rate than the rest of the breast cancer types. The more prevalent PVs in BRCA1/2 genes (mostly in BRCA1) do not rule out the importance to panels of genes, although they are certainly far from shedding light on the gap of the 85% predicted linkage association of BOC with BRCA1/2 and are still not elucidated.Fil: Solano, Angela Rosario. Centro de Educaciones Médicas e Investigación Clínica "Norberto Quirno"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas; ArgentinaFil: Mele, Pablo Gustavo. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana. Cátedra de Química Biologica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas; ArgentinaFil: Jalil, Fernanda S.. Centro de Educaciones Médicas e Investigación Clínica "Norberto Quirno"; ArgentinaFil: Liria, Natalia C.. Centro de Educaciones Médicas e Investigación Clínica "Norberto Quirno"; ArgentinaFil: Podesta, Ernesto Jorge. Universidad de Buenos Aires. Facultad de Medicina. Departamento de Bioquímica Humana. Cátedra de Química Biologica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas; ArgentinaFil: Gutiérrez, Leandro G.. Centro de Educaciones Médicas e Investigación Clínica "Norberto Quirno"; Argentin

A New Highly Selective Chromogenic and Fluorogenic Chemosensor for Copper (II)

[EN] A new fluorogenic and chromogenic probe (L) for the selective, sensitive and naked-eye detection of Cu2+ is reported. Complexation constant, complex stoichiometry and quantum chemical (DFT) calculation for Cu2+ complex has been determined. Also, detection limits and the selectivity in front of other divalent and trivalent cations have been evaluated.This research was supported by the Agencia Nacional de Ciencia y Tecnologia (ANCyT) of Argentina-PICT 2014 No. 1587 and by the Universidad Nacional del Litoral, Santa Fe, Argentina.Quindt, MI.; Gutiérrez, LG.; Kneeteman, MN.; Mancini, P.; Parra Alvarez, M.; Gil Grau, S.; Costero, AM. (2018). A New Highly Selective Chromogenic and Fluorogenic Chemosensor for Copper (II). Letters in Organic Chemistry. 15(8):659-664. https://doi.org/10.2174/1570178615666180102155804S65966415

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

La renovación de la palabra en el bicentenario de la Argentina : los colores de la mirada lingüística

El libro reúne trabajos en los que se exponen resultados de investigaciones presentadas por investigadores de Argentina, Chile, Brasil, España, Italia y Alemania en el XII Congreso de la Sociedad Argentina de Lingüística (SAL), Bicentenario: la renovación de la palabra, realizado en Mendoza, Argentina, entre el 6 y el 9 de abril de 2010. Las temáticas abordadas en los 167 capítulos muestran las grandes líneas de investigación que se desarrollan fundamentalmente en nuestro país, pero también en los otros países mencionados arriba, y señalan además las áreas que recién se inician, con poca tradición en nuestro país y que deberían fomentarse. Los trabajos aquí publicados se enmarcan dentro de las siguientes disciplinas y/o campos de investigación: Fonología, Sintaxis, Semántica y Pragmática, Lingüística Cognitiva, Análisis del Discurso, Psicolingüística, Adquisición de la Lengua, Sociolingüística y Dialectología, Didáctica de la lengua, Lingüística Aplicada, Lingüística Computacional, Historia de la Lengua y la Lingüística, Lenguas Aborígenes, Filosofía del Lenguaje, Lexicología y Terminología

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries