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

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

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

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

Selective and brain-penetrant ACSS2 inhibitors target breast cancer brain metastatic cells

Breast cancer brain metastasis (BCBM) typically results in an end-stage diagnosis and is hindered by a lack of brain-penetrant drugs. Tumors in the brain rely on the conversion of acetate to acetyl-CoA by the enzyme acetyl-CoA synthetase 2 (ACSS2), a key regulator of fatty acid synthesis and protein acetylation. Here, we used a computational pipeline to identify novel brain-penetrant ACSS2 inhibitors combining pharmacophore-based shape screen methodology with absorption, distribution, metabolism, and excretion (ADME) property predictions. We identified compounds AD-5584 and AD-8007 that were validated for specific binding affinity to ACSS2. Treatment of BCBM cells with AD-5584 and AD-8007 leads to a significant reduction in colony formation, lipid storage, acetyl-CoA levels and cell survival in vitro. In an ex vivo brain-tumor slice model, treatment with AD-8007 and AD-5584 reduced pre-formed tumors and synergized with irradiation in blocking BCBM tumor growth. Treatment with AD-8007 reduced tumor burden and extended survival in vivo. This study identifies selective brain-penetrant ACSS2 inhibitors with efficacy towards breast cancer brain metastasis

Determining Contingencies in the Management of Construction Projects

[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

BH3-only proteins BIM and PUMA in the regulation of survival and neuronal differentiation of newly generated cells in the adult mouse hippocampus

Neurogenesis persists in the adult hippocampus, where several thousand neurons are born every day. Most of the newly generated cells are eliminated by apoptosis, possibly because of their failure to integrate properly into neural networks. The BH3-only proteins Bim and Puma have been shown to mediate trophic factor withdrawal- and anoikis-induced apoptosis in various systems. We therefore determined their impact on proliferation, survival, and differentiation of adult-generated cells in the mouse hippocampus using gene-deficient mice. Wild-type, bim-, and puma-deficient mice showed similar rates of precursor cell proliferation, as evidenced by 5-bromo-2-deoxyuridine (BrdU)-incorporation. Deficiency in either bim or puma significantly increased the survival of adult-born cells in the dentate gyrus (DG) after 7 days. Consistently, we detected increased numbers of doublecortin (DCX)-positive and fewer terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelled-positive cells in the DG of bim- and puma-deficient mice. Bim and puma deficiency did not change early markers of neuronal differentiation, as evidenced by BrdU/DCX double-labelling. However, BrdU/NeuN double-labelling revealed that deficiency of bim, but not puma, accelerated the differentiation of newly generated cells into a neuronal phenotype. Our data show that Bim and Puma are prominently involved in the regulation of neuronal progenitor cell survival in the adult DG, but also suggest that Bim has an additional role in neuronal differentiation of adult-born neural precursor cells

Prostaglandin profiling reveals a role for haematopoietic prostaglandin D synthase in adipose tissue macrophage polarisation in mice and humans.

BACKGROUND/OBJECTIVES: Obesity has been associated with both changes in adipose tissue lipid metabolism and inflammation. A key class of lipid-derived signalling molecules involved in inflammation are the prostaglandins. In this study, we aimed to determine how obesity affects the levels of prostaglandins within white adipose tissue (WAT) and determine which cells within adipose tissue produce them. To avoid the effects of cellular stress on prostaglandin levels, we developed a multivariate statistical approach in which metabolite concentrations and transcriptomic data were integrated, allowing the assignment of metabolites to cell types. SUBJECTS/METHODS: Eicosanoids were measured by liquid chromatography-tandem mass spectrometry and mRNA levels using real-time PCR. Eicosanoid levels and transcriptomic data were combined using principal component analysis and hierarchical clustering in order to associate metabolites with cell types. Samples were obtained from C57Bl/6 mice aged 16 weeks. We studied the ob/ob genetically obese mouse model and diet-induced obesity model. We extended our results in mice to a cohort of morbidly obese humans undergoing bariatric surgery. RESULTS: Using our modelling approach, we determined that prostglandin D₂ (PGD₂) in adipose tissue was predominantly produced in macrophages by the haematopoietic isoform of prostaglandin D synthase (H-Pgds). Analysis of sub-fractionated WAT confirmed that H-Pgds was expressed in adipose tissue macrophages (ATMs). Furthermore, H-Pgds expression in ATMs isolated from lean and obese mice was consistent with it affecting macrophage polarisation. Functionally, we demonstrated that H-PGDS-produced PGD₂ polarised macrophages toward an M2, anti-inflammatory state. In line with a potential anti-inflammatory role, we found that H-PGDS expression in ATMs was positively correlated with both peripheral insulin and adipose tissue insulin sensitivity in humans. CONCLUSIONS: In this study, we have developed a method to determine the cellular source of metabolites within an organ and used it to identify a new role for PGD₂ in the control of ATM polarisation.HQL-79 was a kind gift of Professor Yoshihiro Urade. Professor Vidal-Puig was funded by the BHF, MRC and BBSRC. Dr Virtue was funded by the BBSRC and the BHF. Dr Eiden, Dr Masoodi and Dr Griffin were funded by the MRC. Dr Mok was funded by the Wellcome Trust.This is the final published version. It first appeared at http://www.nature.com/ijo/journal/vaop/ncurrent/full/ijo201534a.htm