2,238 research outputs found
Exercising power in software ecosystems
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Companies in a software ecosystem must understand which power capabilities drive cooperation or generate conflicts. In this article, we analyze how power influences the relationships among companies in ecosystems formed by small-to-medium enterprises as well as in platform ecosystems governed by large keystones.Postprint (author's final draft
Tissue-specific control of brain-enriched miR-7 biogenesis
MicroRNA (miRNA) biogenesis is a highly regulated process in eukaryotic cells. Several mature miRNAs exhibit a tissue-specific pattern of expression without an apparent tissue-specific pattern for their corresponding primary transcripts. This discrepancy is suggestive of post-transcriptional regulation of miRNA abundance. Here, we demonstrate that the brain-enriched expression of miR-7, which is processed from the ubiquitous hnRNP K pre-mRNA transcript, is achieved by inhibition of its biogenesis in nonbrain cells in both human and mouse systems. Using stable isotope labeling by amino acids in cell culture (SILAC) mass spectrometry combined with RNase-assisted RNA pull-down, we identified Musashi homolog 2 (MSI2) and Hu antigen R (HuR) proteins as inhibitors of miR-7 processing in nonneural cells. This is achieved through HuR-mediated binding of MSI2 to the conserved terminal loop of pri-miR-7. Footprinting and electrophoretic gel mobility shift analysis (EMSA) provide further evidence for a direct interaction between pri-miR-7-1 and the HuR/MSI2 complex, resulting in stabilization of the pri-miR-7-1 structure. We also confirmed the physiological relevance of this inhibitory mechanism in a neuronal differentiation system using human SH-SY5Y cells. Finally, we show elevated levels of miR-7 in selected tissues from MSI2 knockout (KO) mice without apparent changes in the abundance of the pri-miR-7 transcript. Altogether, our data provide the first insight into the regulation of brain-enriched miRNA processing by defined tissue-specific factors
Integrando aspectos de sustentabilidade à engenharia de sistemas
Sustentabilidade é uma das principais forças motoras de nossa sociedade. Entre as muitas iniciativas para alcançar esta meta estão as de TI, que se preocupam principalmente com o consumo responsável de recursos durante o desenvolvimento e a operação de sistemas de software. Software, no entanto, é parte de um contexto mais amplo, sistemas sócio-técnicos, cujo projeto tem uma grande influência no consumo de recursos. Uma maior compreensão do papel da sustentabilidade e a incorporação deste aspecto à engenharia de sistemas sócio-técnicos pode representar uma importante contribuição para vencer este desafio. Este artigo descreve a proposta de uma pesquisa para compreender o estado-da-prática e desenvolver métodos e técnicas que deem suporte aos diferentes aspectos de sustentabilidade durante a engenharia de sistemas.Peer ReviewedPostprint (published version
Simultaneous inhibition of pan-phosphatidylinositol-3-kinases and MEK as a potential therapeutic strategy in peripheral T-cell lymphomas
Obtained from Haematologica/the Hematology Journal website http://www.haematologica.orgPeripheral T-cell lymphomas are very aggressive hematologic malignancies for which there is no targeted therapy.
New, rational approaches are necessary to improve the very poor outcome in these patients. Phosphatidylinositol-
3-kinase is one of the most important pathways in cell survival and proliferation. We hypothesized that phosphatidylinositol-
3-kinase inhibitors could be rationally selected drugs for treating peripheral T-cell lymphomas.
Several phosphatidylinositol-3-kinase isoforms were inhibited genetically (using small interfering RNA) and pharmacologically
(with CAL-101 and GDC-0941 compounds) in a panel of six peripheral and cutaneous T-cell lymphoma
cell lines. Cell viability was measured by intracellular ATP content; apoptosis and cell cycle changes were
checked by flow cytometry. Pharmacodynamic biomarkers were assessed by western blot. The PIK3CD gene,
which encodes the δ isoform of phosphatidylinositol-3-kinase, was overexpressed in cell lines and primary samples,
and correlated with survival pathways. However, neither genetic nor specific pharmacological inhibition of
phosphatidylinositol-3-kinase δ affected cell survival. In contrast, the pan-phosphatidylinositol-3-kinase inhibitor
GDC-0941 arrested all T-cell lymphoma cell lines in the G1 phase and induced apoptosis in a subset of them. We
identified phospho-GSK3b and phospho-p70S6K as potential biomarkers of phosphatidylinositol-3-kinase
inhibitors. Interestingly, an increase in ERK phosphorylation was observed in some GDC-0941-treated T-cell lymphoma
cell lines, suggesting the presence of a combination of phosphatidylinositol-3-kinase and MEK inhibitors.
A highly synergistic effect was found between the two inhibitors, with the combination enhancing cell cycle arrest
at G0/G1 in all T-cell lymphoma cell lines, and reducing cell viability in primary tumor T cells ex vivo. These results
suggest that the combined treatment of pan-phosphatidylinositol-3-kinase + MEK inhibitors could be more effective
than single phosphatidylinositol-3-kinase inhibitor treatment, and therefore, that this combination could be
of therapeutic value for treating peripheral and cutaneous T-cell lymphomas.This work was supported by grants from the Asociación Española
Contra el Cáncer, Fondo de Investigaciones Sanitarias (PI051623,
PI052800 and PI080856), RTICC (RD06/0020/0107) and
Ministerio de Ciencia e Innovación (SAF2008-0387-1). EMS is
supported by a grant from the Department of Education,
Universities and Research of the Basque Government (BFI08.207).
MSB is supported by a Contract Miguel Servet from Fondo de
Investigaciones Sanitarias (CP11/00018
Towards sugar derivatives as toxin-blocking pharmaceuticals: STD NMR spectroscopy as versatile tool for affinity assessment in drug development
Using a 3-tier Training Model for Effective Exchange of Good Practices in as ERASMUS+ Project
VISIR+ is an Erasmus+ project that aims to develop educational modules for electric and electronic circuits theory and practice following an enquiry-based teaching and learning methodology. The project has installed five new VISIR remote labs in Higher Education Institutions located in Argentina and Brazil, to allow students doing more experiments and hence acquire better experimental skills, through a combination of traditional (hands-on), remote and virtual laboratories. A key aspect for the success of this project was to motivate and train teachers in the underpinning educational methodology. As such, VISIR+ adopted a 3-tier training process to effectively support the use of VISIR in the Institutions that received it. This process is based on the “train the trainer” approach, which required the participating partner institutions to identify and engage a number of associated partners, interested in using their newly installed remote lab. To measure the quality of the training process, the same satisfaction questionnaire was used in all training actions. This paper presents a detailed description of the training actions along with the analysis of the satisfaction questionnaire results. Major conclusions are that the quality level of the training process remained practically the same across all training actions and that trainees sometimes considered the practical use of the VISIR remote lab as difficult, irrespectively of where and when the training action took place.info:eu-repo/semantics/publishedVersio
Transient Changes in Bacterioplankton Communities Induced by the Submarine Volcanic Eruption of El Hierro (Canary Islands)
Postprint4,411
High-Throughput Sequencing, Characterization and Detection of New and Conserved Cucumber miRNAs
Micro RNAS (miRNAs) are a class of endogenous small non coding RNAs involved in the post-transcriptional regulation of gene expression. In plants, a great number of conserved and specific miRNAs, mainly arising from model species, have been identified to date. However less is known about the diversity of these regulatory RNAs in vegetal species with agricultural and/or horticultural importance
Co-limitation towards lower latitudes shapes global forest diversity gradients
Funding Information: The team collaboration and manuscript development are supported by the web-based team science platform: science-i.org, with the project number 202205GFB2. We thank the following initiatives, agencies, teams and individuals for data collection and other technical support: the Global Forest Biodiversity Initiative (GFBI) for establishing the data standards and collaborative framework; United States Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program; University of Alaska Fairbanks; the SODEFOR, Ivory Coast; University Félix Houphouët-Boigny (UFHB, Ivory Coast); the Queensland Herbarium and past Queensland Government Forestry and Natural Resource Management departments and staff for data collection for over seven decades; and the National Forestry Commission of Mexico (CONAFOR). We thank M. Baker (Carbon Tanzania), together with a team of field assistants (Valentine and Lawrence); all persons who made the Third Spanish Forest Inventory possible, especially the main coordinator, J. A. Villanueva (IFN3); the French National Forest Inventory (NFI campaigns (raw data 2005 and following annual surveys, were downloaded by GFBI at https://inventaire-forestier.ign.fr/spip.php?rubrique159 ; site accessed on 1 January 2015)); the Italian Forest Inventory (NFI campaigns raw data 2005 and following surveys were downloaded by GFBI at https://inventarioforestale.org/ ; site accessed on 27 April 2019); Swiss National Forest Inventory, Swiss Federal Institute for Forest, Snow and Landscape Research WSL and Federal Office for the Environment FOEN, Switzerland; the Swedish NFI, Department of Forest Resource Management, Swedish University of Agricultural Sciences SLU; the National Research Foundation (NRF) of South Africa (89967 and 109244) and the South African Research Chair Initiative; the Danish National Forestry, Department of Geosciences and Natural Resource Management, UCPH; Coordination for the Improvement of Higher Education Personnel of Brazil (CAPES, grant number 88881.064976/2014-01); R. Ávila and S. van Tuylen, Instituto Nacional de Bosques (INAB), Guatemala, for facilitating Guatemalan data; the National Focal Center for Forest condition monitoring of Serbia (NFC), Institute of Forestry, Belgrade, Serbia; the Thünen Institute of Forest Ecosystems (Germany) for providing National Forest Inventory data; the FAO and the United Nations High Commissioner for Refugees (UNHCR) for undertaking the SAFE (Safe Access to Fuel and Energy) and CBIT-Forest projects; and the Amazon Forest Inventory Network (RAINFOR), the African Tropical Rainforest Observation Network (AfriTRON) and the ForestPlots.net initiative for their contributions from Amazonian and African forests. The Natural Forest plot data collected between January 2009 and March 2014 by the LUCAS programme for the New Zealand Ministry for the Environment are provided by the New Zealand National Vegetation Survey Databank https://nvs.landcareresearch.co.nz/. We thank the International Boreal Forest Research Association (IBFRA); the Forestry Corporation of New South Wales, Australia; the National Forest Directory of the Ministry of Environment and Sustainable Development of the Argentine Republic (MAyDS) for the plot data of the Second National Forest Inventory (INBN2); the National Forestry Authority and Ministry of Water and Environment of Uganda for their National Biomass Survey (NBS) dataset; and the Sabah Biodiversity Council and the staff from Sabah Forest Research Centre. All TEAM data are provided by the Tropical Ecology Assessment and Monitoring (TEAM) Network, a collaboration between Conservation International, the Missouri Botanical Garden, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors, with thanks to all current and previous TEAM site manager and other collaborators that helped collect data. We thank the people of the Redidoti, Pierrekondre and Cassipora village who were instrumental in assisting with the collection of data and sharing local knowledge of their forest and the dedicated members of the field crew of Kabo 2012 census. We are also thankful to FAPESC, SFB, FAO and IMA/SC for supporting the IFFSC. This research was supported in part through computational resources provided by Information Technology at Purdue, West Lafayette, Indiana.This work is supported in part by the NASA grant number 12000401 ‘Multi-sensor biodiversity framework developed from bioacoustic and space based sensor platforms’ (J. Liang, B.P.); the USDA National Institute of Food and Agriculture McIntire Stennis projects 1017711 (J. Liang) and 1016676 (M.Z.); the US National Science Foundation Biological Integration Institutes grant NSF‐DBI‐2021898 (P.B.R.); the funding by H2020 VERIFY (contract 776810) and H2020 Resonate (contract 101000574) (G.-J.N.); the TEAM project in Uganda supported by the Moore foundation and Buffett Foundation through Conservation International (CI) and Wildlife Conservation Society (WCS); the Danish Council for Independent Research | Natural Sciences (TREECHANGE, grant 6108-00078B) and VILLUM FONDEN grant number 16549 (J.-C.S.); the Natural Environment Research Council of the UK (NERC) project NE/T011084/1 awarded to J.A.-G. and NE/ S011811/1; ERC Advanced Grant 291585 (‘T-FORCES’) and a Royal Society-Wolfson Research Merit Award (O.L.P.); RAINFOR plots supported by the Gordon and Betty Moore Foundation and the UK Natural Environment Research Council, notably NERC Consortium Grants ‘AMAZONICA’ (NE/F005806/1), ‘TROBIT’ (NE/D005590/1) and ‘BIO-RED’ (NE/N012542/1); CIFOR’s Global Comparative Study on REDD+ funded by the Norwegian Agency for Development Cooperation, the Australian Department of Foreign Affairs and Trade, the European Union, the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) and donors to the CGIAR Fund; AfriTRON network plots funded by the local communities and NERC, ERC, European Union, Royal Society and Leverhume Trust; a grant from the Royal Society and the Natural Environment Research Council, UK (S.L.L.); National Science Foundation CIF21 DIBBs: EI: number 1724728 (A.C.C.); National Natural Science Foundation of China (31800374) and Shandong Provincial Natural Science Foundation (ZR2019BC083) (H.L.). UK NERC Independent Research Fellowship (grant code: NE/S01537X/1) (T.J.); a Serra-Húnter Fellowship provided by the Government of Catalonia (Spain) (S.d.-M.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.A.S.); a grant from the Franklinia Foundation (D.A.C.); Russian Science Foundation project number 19-77-300-12 (R.V.); the Takenaka Scholarship Foundation (A.O.A.); the German Research Foundation (DFG), grant number Am 149/16-4 (C.A.); the Romania National Council for Higher Education Funding, CNFIS, project number CNFIS-FDI-2022-0259 (O.B.); Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-05109 and STPGP506284) and the Canadian Foundation for Innovation (36014) (H.Y.H.C.); the project SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/0000797) (E.C.); Consejo de Ciencia y Tecnología del estado de Durango (2019-01-155) (J.J.C.-R.); Science and Engineering Research Board (SERB), New Delhi, Government of India (file number PDF/2015/000447)—‘Assessing the carbon sequestration potential of different forest types in Central India in response to climate change ’ (J.A.D.); Investissement d’avenir grant of the ANR (CEBA: ANR-10-LABEX-0025) (G.D.); National Foundation for Science & Technology Development of Vietnam, 106-NN.06-2013.01 (T.V.D.); Queensland government, Department of Environment and Science (T.J.E.); a Czech Science Foundation Standard grant (19-14620S) (T.M.F.); European Union Seventh Framework Program (FP7/2007–2013) under grant agreement number 265171 (L. Finer, M. Pollastrini, F. Selvi); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (J.F.); CNPq productivity grant number 311303/2020-0 (A.L.d.G.); DFG grant HE 2719/11-1,2,3; HE 2719/14-1 (A. Hemp); European Union’s Horizon Europe research project OpenEarthMonitor grant number 101059548, CGIAR Fund INIT-32-MItigation and Transformation Initiative for GHG reductions of Agrifood systems RelaTed Emissions (MITIGATE+) (M.H.); General Directorate of the State Forests, Poland (1/07; OR-2717/3/11; OR.271.3.3.2017) and the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (A.M.J.); Czech Science Foundation 18-10781 S (S.J.); Danish of Ministry of Environment, the Danish Environmental Protection Agency, Integrated Forest Monitoring Program—NFI (V.K.J.); State of São Paulo Research Foundation/FAPESP as part of the BIOTA/FAPESP Program Project Functional Gradient-PELD/BIOTA-ECOFOR 2003/12595-7 & 2012/51872-5 (C.A.J.); Danish Council for Independent Research—social sciences—grant DFF 6109–00296 (G.A.K.); Russian Science Foundation project 21-46-07002 for the plot data collected in the Krasnoyarsk region (V.K.); BOLFOR (D.K.K.); Department of Biotechnology, New Delhi, Government of India (grant number BT/PR7928/NDB/52/9/2006, dated 29 September 2006) (M.L.K.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (J.N.K.); Korea Forest Service (2018113A00-1820-BB01, 2013069A00-1819-AA03, and 2020185D10-2022-AA02) and Seoul National University Big Data Institute through the Data Science Research Project 2016 (H.S.K.); the Brazilian National Council for Scientific and Technological Development (CNPq, grant 442640/2018-8, CNPq/Prevfogo-Ibama number 33/2018) (C.K.); CSIR, New Delhi, government of India (grant number 38(1318)12/EMR-II, dated: 3 April 2012) (S.K.); Department of Biotechnology, New Delhi, government of India (grant number BT/ PR12899/ NDB/39/506/2015 dated 20 June 2017) (A.K.); Coordination for the Improvement of Higher Education Personnel (CAPES) #88887.463733/2019-00 (R.V.L.); National Natural Science Foundation of China (31800374) (H.L.); project of CEPF RAS ‘Methodological approaches to assessing the structural organization and functioning of forest ecosystems’ (AAAA-A18-118052590019-7) funded by the Ministry of Science and Higher Education of Russia (N.V.L.); Leverhulme Trust grant to Andrew Balmford, Simon Lewis and Jon Lovett (A.R.M.); Russian Science Foundation, project 19-77-30015 for European Russia data processing (O.M.); grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (M.T.E.M.); the National Centre for Research and Development, Poland (BIOSTRATEG1/267755/4/NCBR/2015) (S.M.); the Secretariat for Universities and of the Ministry of Business and Knowledge of the Government of Catalonia and the European Social Fund (A. Morera); Queensland government, Department of Environment and Science (V.J.N.); Pinnacle Group Cameroon PLC (L.N.N.); Queensland government, Department of Environment and Science (M.R.N.); the Natural Sciences and Engineering Research Council of Canada (RGPIN-2018-05201) (A.P.); the Russian Foundation for Basic Research, project number 20-05-00540 (E.I.P.); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 778322 (H.P.); Science and Engineering Research Board, New Delhi, government of India (grant number YSS/2015/000479, dated 12 January 2016) (P.S.); the Chilean Government research grants Fondecyt number 1191816 and FONDEF number ID19 10421 (C.S.-E.); the Deutsche Forschungsgemeinschaft (DFG) Priority Program 1374 Biodiversity Exploratories (P.S.); European Space Agency projects IFBN (4000114425/15/NL/FF/gp) and CCI Biomass (4000123662/18/I-NB) (D. Schepaschenko); FunDivEUROPE, European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 265171 (M.S.-L.); APVV 20-0168 from the Slovak Research and Development Agency (V.S.); Manchester Metropolitan University’s Environmental Science Research Centre (G.S.); the project ‘LIFE+ ForBioSensing PL Comprehensive monitoring of stand dynamics in Białowieża Forest supported with remote sensing techniques’ which is co-funded by the EU Life Plus programme (contract number LIFE13 ENV/PL/000048) and the National Fund for Environmental Protection and Water Management in Poland (contract number 485/2014/WN10/OP-NM-LF/D) (K.J.S.); Global Challenges Research Fund (QR allocation, MMU) (M.J.P.S.); Czech Science Foundation project 21-27454S (M.S.); the Russian Foundation for Basic Research, project number 20-05-00540 (N. Tchebakova); Botanical Research Fund, Coalbourn Trust, Bentham Moxon Trust, Emily Holmes scholarship (L.A.T.); the programmes of the current scientific research of the Botanical Garden of the Ural Branch of Russian Academy of Sciences (V.A.U.); FCT—Portuguese Foundation for Science and Technology—Project UIDB/04033/2020. Inventário Florestal Nacional—ICNF (H. Viana); Grant from Kenya Coastal Development Project (KCDP), which was funded by World Bank (C.W.); grants from the Swedish National Forest Inventory, Swedish University of Agricultural Sciences (B.W.); ATTO project (grant number MCTI-FINEP 1759/10 and BMBF 01LB1001A, 01LK1602F) (F.W.); ReVaTene/PReSeD-CI 2 is funded by the Education and Research Ministry of Côte d’Ivoire, as part of the Debt Reduction-Development Contracts (C2Ds) managed by IRD (I.C.Z.-B.); the National Research Foundation of South Africa (NRF, grant 89967) (C.H.). The Tropical Plant Exploration Group 70 1 ha plots in Continental Cameroon Mountains are supported by Rufford Small Grant Foundation, UK and 4 ha in Sierra Leone are supported by the Global Challenge Research Fund through Manchester Metropolitan University, UK; the National Geographic Explorer Grant, NGS-53344R-18 (A.C.-S.); University of KwaZulu-Natal Research Office grant (M.J.L.); Universidad Nacional Autónoma de México, Dirección General de Asuntos de Personal Académico, Grant PAPIIT IN-217620 (J.A.M.). Czech Science Foundation project 21-24186M (R.T., S. Delabye). Czech Science Foundation project 20-05840Y, the Czech Ministry of Education, Youth and Sports (LTAUSA19137) and the long-term research development project of the Czech Academy of Sciences no. RVO 67985939 (J.A.). The American Society of Primatologists, the Duke University Graduate School, the L.S.B. Leakey Foundation, the National Science Foundation (grant number 0452995) and the Wenner-Gren Foundation for Anthropological Research (grant number 7330) (M.B.). Research grants from Conselho Nacional de Desenvolvimento Científico e Tecnologico (CNPq, Brazil) (309764/2019; 311303/2020) (A.C.V., A.L.G.). The Project of Sanya Yazhou Bay Science and Technology City (grant number CKJ-JYRC-2022-83) (H.-F.W.). The Ugandan NBS was supported with funds from the Forest Carbon Partnership Facility (FCPF), the Austrian Development Agency (ADC) and FAO. FAO’s UN-REDD Program, together with the project on ‘Native Forests and Community’ Loan BIRF number 8493-AR UNDP ARG/15/004 and the National Program for the Protection of Native Forests under UNDP funded Argentina’s INBN2. Publisher Copyright: © 2022, The Author(s), under exclusive licence to Springer Nature Limited.Peer reviewedPostprin
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