413 research outputs found

    Soil water content and evaporation determined by thermal parameters obtained from ground-based and remote measurements

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    A procedure is presented for calculating 24-hour totals of evaporation from wet and drying soils. Its application requires a knowledge of the daily solar radiation, the maximum and minimum, air temperatures, moist surface albedo, and maximum and minimum surface temperatures. Tests of the technique on a bare field of Avondale loam at Phoenix, Arizona showed it to be independent of season

    There and back again: molecular phylogenetics of the Brazilian endemic Psyllocarpus (Rubiaceae: Spermacoceae) supports a circumscription of the genus based on its original concept

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    The Spermacoce clade (tribe Spermacoceae) is one of the most taxonomically complex groups in Rubiaceae due to the unclear delimitation of Borreria and Spermacoce, in which several smaller genera are phylogenetically intermingled. One of these genera is the Brazilian endemic Psyllocarpus, whose circumscription was broadened, thereby including two sections. Psyllocarpus sect. Psyllocarpus, being based on the original genus delineation, includes nine species, distributed in the Cerrado and campo rupestre of eastern Brazil, whereas P. sect. Amazonica comprises three species, occurring in the Amazonian campinas. Furthermore, P. intermedius was not classified in any of these sections when it was later described. In order to test the monophyly of Psyllocarpus and assess its relationships to other genera, we conducted phylogenetic analyses, sampling across the whole Spermacoce clade, including nearly all Psyllocarpus species. A combined nuclear ribosomal (ETS and ITS) and plastid (rps16 and trnLtrnF) dataset was generated, representing 124 species (ca 25% of the species in the clade) in 15 genera (ca 65%). Various methodologies were applied to investigate the degree of incongruence among markers and address the lack of resolution and low support values for some branches. Our results revealed that Psyllocarpus is not monophyletic. Psyllocarpus campinorum (from P . sect. Amazonica) and P intermedius are situated as distinct lineages in the Spermacoce clade, yet do not belong to Psyllocarpus. Members of section Psyllocarpus form a strongly supported clade sister to Staelia and was recovered with high to maximum support across different datasets and inference methods. Therefore, Psyllocarpus has to be circumscribed based on its original concept, excluding P. sect. Amazonica and P. intermedius. This establishes the genus as a monophyletic and easily diagnosable taxon, characterized by terete leaves, homostylous flowers, a bilobate calyx, included stamens and style, and compressed, septifragally dehiscent capsules with a persistent septum

    Kruppel-like factor 8 regulates triple negative breast cancer stem cell-like activity

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    IntroductionBreast tumor development is regulated by a sub-population of breast cancer cells, termed cancer stem-like cells (CSC), which are capable of self-renewing and differentiating, and are involved in promoting breast cancer invasion, metastasis, drug resistance and relapse. CSCs are highly adaptable, capable of reprogramming their own metabolism and signaling activity in response to stimuli within the tumor microenvironment. Recently, the nutrient sensor O-GlcNAc transferase (OGT) and O-GlcNAcylation was shown to be enriched in CSC populations, where it promotes the stemness and tumorigenesis of breast cancer cells in vitro and in vivo. This enrichment was associated with upregulation of the transcription factor Kruppel-like-factor 8 (KLF8) suggesting a potential role of KLF8 in regulating CSCs properties.MethodsTriple-negative breast cancer cells were genetically modified to generate KLF8 overexpressing or KLF8 knock-down cells. Cancer cells, control or with altered KLF8 expression were analyzed to assess mammosphere formation efficiency, CSCs frequency and expression of CSCs factors. Tumor growth in vivo of control or KLF8 knock-down cells was assessed by fat-pad injection of these cell in immunocompromised mice.ResultsHere, we show that KLF8 is required and sufficient for regulating CSC phenotypes and regulating transcription factors SOX2, NANOG, OCT4 and c-MYC. KLF8 levels are associated with chemoresistance in triple negative breast cancer patients and overexpression in breast cancer cells increased paclitaxel resistance. KLF8 and OGT co-regulate each other to form a feed-forward loop to promote CSCs phenotype and mammosphere formation of breast cancer cells.DiscussionThese results suggest a critical role of KLF8 and OGT in promoting CSCs and cancer progression, that may serve as potential targets for developing strategy to target CSCs specifically

    Nutrient sensor O-GlcNAc transferase controls cancer lipid metabolism via SREBP-1 regulation

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    Elevated O-GlcNAcylation is associated with disease states such as diabetes and cancer. O-GlcNAc transferase (OGT) is elevated in multiple cancers and inhibition of this enzyme genetically or pharmacologically inhibits oncogenesis. Here we show that O-GlcNAcylation modulates lipid metabolism in cancer cells. OGT regulates expression of the master lipid regulator the transcription factor sterol regulatory element binding protein 1 (SREBP-1) and its transcriptional targets both in cancer and lipogenic tissue. OGT regulates SREBP-1 protein expression via AMP-activated protein kinase (AMPK). SREBP-1 is critical for OGT-mediated regulation of cell survival and of lipid synthesis, as overexpression of SREBP-1 rescues lipogenic defects associated with OGT suppression, and tumor growth in vitro and in vivo. These results unravel a previously unidentified link between O-GlcNAcylation, lipid metabolism and the regulation of SREBP-1 in cancer and suggests a crucial role for O-GlcNAc signaling in transducing nutritional state to regulate lipid metabolism

    On a Sugar High: Role of O-GlcNAcylation in Cancer

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    Recent advances in the understanding of the molecular mechanisms underlying cancer progression have led to the development of novel therapeutic targeting strategies. Aberrant glycosylation patterns and their implication in cancer have gained increasing attention as potential targets due to the critical role of glycosylation in regulating tumor-specific pathways that contribute to cancer cell survival, proliferation, and progression. A special type of glycosylation that has been gaining momentum in cancer research is the modification of nuclear, cytoplasmic, and mitochondrial proteins, termed O-GlcNAcylation. This protein modification is catalyzed by an enzyme called O-GlcNAc transferase (OGT), which uses the final product of the Hexosamine Biosynthetic Pathway (HBP) to connect altered nutrient availability to changes in cellular signaling that contribute to multiple aspects of tumor progression. Both O-GlcNAc and its enzyme OGT are highly elevated in cancer and fulfill the crucial role in regulating many hallmarks of cancer. In this review, we present and discuss the latest findings elucidating the involvement of OGT and O-GlcNAc in cancer

    Kruppel-Like Factor 8 Regulates Triple Negative Breast Cancer Stem Cell-Like Activity

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    INTRODUCTION: Breast tumor development is regulated by a sub-population of breast cancer cells, termed cancer stem-like cells (CSC), which are capable of self-renewing and differentiating, and are involved in promoting breast cancer invasion, metastasis, drug resistance and relapse. CSCs are highly adaptable, capable of reprogramming their own metabolism and signaling activity in response to stimuli within the tumor microenvironment. Recently, the nutrient sensor O-GlcNAc transferase (OGT) and O-GlcNAcylation was shown to be enriched in CSC populations, where it promotes the stemness and tumorigenesis of breast cancer cells in vitro and in vivo. This enrichment was associated with upregulation of the transcription factor Kruppel-like-factor 8 (KLF8) suggesting a potential role of KLF8 in regulating CSCs properties. METHODS: Triple-negative breast cancer cells were genetically modified to generate KLF8 overexpressing or KLF8 knock-down cells. Cancer cells, control or with altered KLF8 expression were analyzed to assess mammosphere formation efficiency, CSCs frequency and expression of CSCs factors. Tumor growth in vivo of control or KLF8 knock-down cells was assessed by fat-pad injection of these cell in immunocompromised mice. RESULTS: Here, we show that KLF8 is required and sufficient for regulating CSC phenotypes and regulating transcription factors SOX2, NANOG, OCT4 and c-MYC. KLF8 levels are associated with chemoresistance in triple negative breast cancer patients and overexpression in breast cancer cells increased paclitaxel resistance. KLF8 and OGT co-regulate each other to form a feed-forward loop to promote CSCs phenotype and mammosphere formation of breast cancer cells. DISCUSSION: These results suggest a critical role of KLF8 and OGT in promoting CSCs and cancer progression, that may serve as potential targets for developing strategy to target CSCs specifically

    Determining Contingencies in the Management of Construction Projects

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    [EN] This research describes the managerial approaches that contractors follow to determine different types of contingencies in construction project management. Two large Spanish general contractors were selected for an in-depth analysis. Interviews and surveys were conducted with six additional companies to explore the external validity of the findings. Managers constrain time and cost buffers through project objectives, applying heuristics to determine inventory buffers. The management of capacity buffers is entrusted to subcontractors. The contractors take advantage of scope and quality buffers to meet project objectives but rarely share these buffers with the owner, unless the owner is an internal client.Ortiz-González, JI.; Pellicer, E.; Molenaar, KR. (2019). Determining Contingencies in the Management of Construction Projects. Project Management Journal. 50(2):226-242. https://doi.org/10.1177/8756972819827389S226242502Adafin, J., Wilkinson, S., Rotimi, J. O. B., & Odeyinka, H. (2014). Accuracy in Design Stage Cost Estimating through Risk-contingency Analysis: A Theoretical Exploration. Construction Research Congress 2014. doi:10.1061/9780784413517.151Ballard, G., & Howell, G. (1998). Shielding Production: Essential Step in Production Control. Journal of Construction Engineering and Management, 124(1), 11-17. doi:10.1061/(asce)0733-9364(1998)124:1(11)Barraza, G. A. (2011). Probabilistic Estimation and Allocation of Project Time Contingency. Journal of Construction Engineering and Management, 137(4), 259-265. doi:10.1061/(asce)co.1943-7862.0000280Blomquist, T., Hällgren, M., Nilsson, A., & Söderholm, A. (2010). Project-as-Practice: In Search of Project Management Research that Matters. Project Management Journal, 41(1), 5-16. doi:10.1002/pmj.20141Chan, E. H., & Au, M. C. (2009). Factors Influencing Building Contractors’ Pricing for Time-Related Risks in Tenders. Journal of Construction Engineering and Management, 135(3), 135-145. doi:10.1061/(asce)0733-9364(2009)135:3(135)De la Cruz, M. P., del Caño, A., & de la Cruz, E. (2006). Downside Risks in Construction Projects Developed by the Civil Service: The Case of Spain. Journal of Construction Engineering and Management, 132(8), 844-852. doi:10.1061/(asce)0733-9364(2006)132:8(844)Ford, D. N. (2002). Achieving Multiple Project Objectives through Contingency Management. Journal of Construction Engineering and Management, 128(1), 30-39. doi:10.1061/(asce)0733-9364(2002)128:1(30)González, V., Alarcón, L. F., & Molenaar, K. (2009). Multiobjective design of Work-In-Process buffer for scheduling repetitive building projects. Automation in Construction, 18(2), 95-108. doi:10.1016/j.autcon.2008.05.005Guest, G., Bunce, A., & Johnson, L. (2006). How Many Interviews Are Enough? Field Methods, 18(1), 59-82. doi:10.1177/1525822x05279903Günhan, S., & Arditi, D. (2007). Budgeting Owner’s Construction Contingency. Journal of Construction Engineering and Management, 133(7), 492-497. doi:10.1061/(asce)0733-9364(2007)133:7(492)Hällgren, M., & Wilson, T. L. (2008). The nature and management of crises in construction projects: Projects-as-practice observations. International Journal of Project Management, 26(8), 830-838. doi:10.1016/j.ijproman.2007.10.005Harbuck R. H. (2004). Competitive bidding for highway construction projects (pp. ES91–ES94). Morgantown, WV: AACE International Transactions.HORMAN, M., & KENLEY, R. (1998). Process Dynamics: Identifying a Strategy for the Deployment of Buffers in Building Projects. International Journal of Logistics Research and Applications, 1(3), 221-237. doi:10.1080/13675569808962049Horman, M. J., & Thomas, H. R. (2005). Role of Inventory Buffers in Construction Labor Performance. Journal of Construction Engineering and Management, 131(7), 834-843. doi:10.1061/(asce)0733-9364(2005)131:7(834)Howell, G., Laufer, A., & Ballard, G. (1993). Interaction between Subcycles: One Key to Improved Methods. Journal of Construction Engineering and Management, 119(4), 714-728. doi:10.1061/(asce)0733-9364(1993)119:4(714)Howell, G., Laufer, A., & Ballard, G. (1993). Uncertainty and project objectives. Project Appraisal, 8(1), 37-43. doi:10.1080/02688867.1993.9726884Idrus, A., Fadhil Nuruddin, M., & Rohman, M. A. (2011). Development of project cost contingency estimation model using risk analysis and fuzzy expert system. Expert Systems with Applications, 38(3), 1501-1508. doi:10.1016/j.eswa.2010.07.061Laryea, S., & Hughes, W. (2011). Risk and Price in the Bidding Process of Contractors. Journal of Construction Engineering and Management, 137(4), 248-258. doi:10.1061/(asce)co.1943-7862.0000293Leach, L. (2003). Schedule and Cost Buffer Sizing: How to Account for the Bias between Project Performance and Your Model. Project Management Journal, 34(2), 34-47. doi:10.1177/875697280303400205Lee, S., Peña-Mora, F., & Park, M. (2006). Reliability and Stability Buffering Approach: Focusing on the Issues of Errors and Changes in Concurrent Design and Construction Projects. Journal of Construction Engineering and Management, 132(5), 452-464. doi:10.1061/(asce)0733-9364(2006)132:5(452)Oviedo-Haito, R. J., Jiménez, J., Cardoso, F. F., & Pellicer, E. (2014). Survival Factors for Subcontractors in Economic Downturns. Journal of Construction Engineering and Management, 140(3), 04013056. doi:10.1061/(asce)co.1943-7862.0000811Pellicer, E., Sanz, M. A., Esmaeili, B., & Molenaar, K. R. (2016). Exploration of Team Integration in Spanish Multifamily Residential Building Construction. Journal of Management in Engineering, 32(5), 05016012. doi:10.1061/(asce)me.1943-5479.0000438Pellicer, E., & Victory, R. (2006). IMPLEMENTATION OF PROJECT MANAGEMENT PRINCIPLES IN SPANISH RESIDENTIAL DEVELOPMENTS. International Journal of Strategic Property Management, 10(4), 233-248. doi:10.3846/1648715x.2006.9637555Rooke, J., Seymour, D., & Fellows, R. (2004). Planning for claims: an ethnography of industry culture. Construction Management and Economics, 22(6), 655-662. doi:10.1080/014461904200026324Slauson N. P. (2005). The effectiveness of the construction contract (pp. PM121–PM127). Morgantown, WV: AACE International Transactions.Tah, J. H. M., Thorpe, A., & McCaffer, R. (1993). Contractor project risks contingency allocation using linguistic approximation. Computing Systems in Engineering, 4(2-3), 281-293. doi:10.1016/0956-0521(93)90052-xTaylor, J. E., Dossick, C. S., & Garvin, M. (2011). Meeting the Burden of Proof with Case-Study Research. Journal of Construction Engineering and Management, 137(4), 303-311. doi:10.1061/(asce)co.1943-7862.0000283Thal, A. E., Cook, J. J., & White, E. D. (2010). Estimation of Cost Contingency for Air Force Construction Projects. Journal of Construction Engineering and Management, 136(11), 1181-1188. doi:10.1061/(asce)co.1943-7862.0000227Thamhain, H. (2013). Managing Risks in Complex Projects. Project Management Journal, 44(2), 20-35. doi:10.1002/pmj.21325Yeo, K. T. (1990). Risks, Classification of Estimates, and Contingency Management. Journal of Management in Engineering, 6(4), 458-470. doi:10.1061/(asce)9742-597x(1990)6:4(458
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