278 research outputs found
Natural fruitlet abscission as related to apple tree carbon balance estimated with the MaluSim model
Apple trees produce many more flower clusters than needed for a full crop, but natural early season flower and fruitlet abscission drastically reduce the final fruit number. Natural fruit abscission varies significantly year to year. There have been attempts to try to model apple fruit abscission in the past. However, due to the great complexity of a perennial crop system in a dynamic environment with significant plant manipulations, regulatory processes and controlling environmental variables have been difficult to elucidate. In 1995, a field trial was planted at the New York State Agricultural Experiment Station in Geneva, New York with 3 apple cultivars (‘Delicious’, ‘Gala’, and ‘McIntosh’). Beginning in 2000 and for 18 years thereafter, we recorded the natural whole-season fruit abscission of untreated trees that received no chemical or hand thinning. We also estimated early season patterns of carbohydrate supply-to-demand each year with a carbon balance model. These data were used to correlate tree carbon balance status and other environmental variables with natural fruit abscission responses. In general terms, natural set, defined as final fruit/flower cluster, of ‘Gala’ averaged ˜1 fruit for each flower cluster (fruit set = 0.9), whereas fewer fruits were set on ‘Delicious’ and ‘McIntosh’ (fruit set = 0.7 and 0.6, respectively). Fruit set of ‘Gala’ was less variable than of ‘Delicious’ or ‘McIntosh’, and there was a clear pattern for decreasing fruit set when the number of initial flower clusters per tree increased. Fruit weight was less dependent on fruit number for ‘Delicious’ and ‘McIntosh’ than for ‘Gala’. Multiple regression models indicated that number of flower clusters per tree and average carbohydrate balance between 0–60 degree days (DD) after bloom and 300–360 DD after bloom were the main significant variables that explained 60–80% of the variability in natural fruit set or final fruit number. For ‘Delicious’, temperatures of the previous fall also explained a significant amount of variation in final fruit set and final fruit number. For ‘Gala’, carbon balance from bloom to shortly after petal fall and when fruits were about 18 mm were the two main periods, which were more sensible to carbohydrate deficiency triggering fruit abscission. A later susceptible period was also observed for ‘McIntosh’, suggesting a larger thinning window for this cultivar.info:eu-repo/semantics/acceptedVersio
Modelling physiological and environmental factors regulating relative fruit set and final fruit numbers in apple trees
Chemical thinning of apple (Malus domestica Borkh.) has been practised for 50 years but it remains an unpredictable part of apple production with large variations from year to year and within years. Carbohydrate availability to support young fruitlet growth may play a significant role in apple tree response to chemical thinners, especially when the carbohydrate supply is the limiting factor for fruit growth. To address the carbohydrate component, we have tested the MaluSim model that integrates many environmental and tree physiological factors as a tool to predict chemical thinner response. The model suggests that carbon supply-to-demand variations may explain some of the great variations in thinning spray response. Relative fruit set and final fruit number per tree were affected by the carbohydrate balance within 2 days before the spray and up to 5 days after. There was a period, 15–29 days after bloom that thinners showed higher action. The greater the carbohydrate supply relative to demand, the greater the relative set and the final fruit number. This suggested that carbohydrate supply-demand balance may be a baseline for thinner responses, and that integrative modelling of these balances can be useful in understanding variation in thinning responses. Apple relative fruit set and final fruit number per tree could be modelled relatively well with consideration of initial flower density, the carbohydrate balance model, and cumulative growing degree-days since bloom.info:eu-repo/semantics/acceptedVersio
Synthesis and reactivity of 4-oxo-5-trimethylsilanyl derived α-amino acids
A Lewis-acid promoted one-carbon homologation of an aspartic acid semialdehyde with trimethylsilyldiazomethane has led to the efficient synthesis of two silicon-containing α-amino acids. The use of trimethylaluminium or catalytic tin(II) chloride gave novel 4-oxo-5-trimethylsilanyl derived amino acids in yields of 71–88%. An investigation into the reactivity of these highly functional α-amino acids showed that selective cleavage of the C–Si bond could be achieved under mild basic conditions to give a protected derivative of the naturally occurring amino acid, 4-oxo-l-norvaline. Alternatively, Peterson olefination with aryl or alkyl aldehydes resulted in the formation of E-enone derived α-amino acids
A systems study of an RF power source for a 1 TeV next linear collider based upon the relativistic-klystron two-beam accelerator
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
Regulatory control of DNA end resection by Sae2 phosphorylation
DNA end resection plays a critical function in DNA double-strand break repair pathway choice. Resected DNA ends are refractory to end-joining mechanisms and are instead channeled to homology-directed repair. Using biochemical, genetic, and imaging methods, we show that phosphorylation of Saccharomyces cerevisiae Sae2 controls its capacity to promote the Mre11-Rad50-Xrs2 (MRX) nuclease to initiate resection of blocked DNA ends by at least two distinct mechanisms. First, DNA damage and cell cycle-dependent phosphorylation leads to Sae2 tetramerization. Second, and independently, phosphorylation of the conserved C-terminal domain of Sae2 is a prerequisite for its physical interaction with Rad50, which is also crucial to promote the MRX endonuclease. The lack of this interaction explains the phenotype of rad50S mutants defective in the processing of Spo11-bound DNA ends during meiotic recombination. Our results define how phosphorylation controls the initiation of DNA end resection and therefore the choice between the key DNA double-strand break repair mechanisms
International consensus for ultrasound lesions in gout: Results of delphi process and web-reliability exercise
Objective. To produce consensus-based definitions of the US elementary lesions in gout and to test their reliability in a web-based exercise. Methods. The process consisted of two steps. In the first step a written Delphi questionnaire was developed from a systematic literature review and expert international consensus. This collated information resulted in four statements defining US elementary lesions: double contour (DC), tophus, aggregates and erosion. The Delphi questionnaire was sent to 35 rheumatology experts in US, asking them to rate their level of agreement or disagreement with each statement. The second step tested the reliability by a web-exercise. US images of both normal and gouty elementary lesions were collected by the participants. A facilitator then constructed an electronic database of 110 images. The database was sent to the participants, who evaluated the presence/absence of US elementary lesions. A group of 20 images was displayed twice to evaluate intra-reader reliability. Results. A total of 32 participants responded to the questionnaires. Good agreement (>80%) was obtained for US definitions on DC, tophus, aggregates and erosion in the Delphi exercise after three rounds. The reliability on images showed inter-reader κ values for DC, tophus, aggregates, erosion findings of 0.98, 0.71, 0.54 and 0.85, respectively. The mean intra-reader κ values were also acceptable: 0.93, 0.78, 0.65 and 0.78, respectively. Conclusion. This, the first consensus-based US definition of elementary lesions in gout, demonstrated good reliability overall. It constitutes an essential step in developing a core outcome measurement that permits a higher degree of homogeneity and comparability between multicentre studies
Mechanisms of leukocyte lipid body formation and function in inflammation
An area of increasingly interest for the understanding of cell signaling are the spatio-temporal aspects of the different enzymes involved in lipid mediator generation (eicosanoid-forming enzymes, phospholipases and their regulatory kinases and phosphatases) and pools of lipid precursors. The compartmentalization of signaling components within discrete and dynamic sites in the cell is critical for specificity and efficiency of enzymatic reactions of phosphorilation, enzyme activation and function. We hypothesized that lipid bodies - inducible non-membrane bound cytoplasmic lipid domains - function as specialized intracellular sites of compartmentalization of signaling with major roles in lipid mediator formation within leukocytes engaged in inflammatory process. Over the past years substantial progresses have been made demonstrating that all enzymes involved in eicosanoid synthesis localize at lipid bodies and lipid bodies are distinct sites for eicosanoid generation. Here we will review our current knowledge on the mechanisms of formation and functions of lipid bodies pertinent to inflammation
Antineoplastic effects of rosiglitazone and PPARγ transactivation in neuroblastoma cells
Neuroblastoma (NB) is the most common extracranial solid tumour in infants. Unfortunately, most children present with advanced disease and have a poor prognosis. In the present study, we evaluated the role of the peroxisome proliferator-activated receptor γ (PPARγ) agonist rosiglitazone (RGZ) in two NB cell lines (SK-N-AS and SH-SY5Y), which express PPARγ. Rosiglitazone decreased cell proliferation and viability to a greater extent in SK-N-AS than in SH-SY5Y. Furthermore, 20 μM RGZ significantly inhibited cell adhesion, invasiveness and apoptosis in SK-N-AS, but not in SH-SY5Y. Because of the different response of SK-N-AS and SH-SY5Y cells to RGZ, the function of PPARγ as a transcriptional activator was assessed. Noticeably, transient transcription experiments with a PPARγ responsive element showed that RGZ induced a three-fold increase of the reporter activity in SK-N-AS, whereas no effect was observed in SH-SY5Y. The different PPARγ activity may be likely due to the markedly lower amount of phopshorylated (i.e. inactive) protein observed in SK-N-AS. To our knowledge, this is the first demonstration that the differential response of NB cells to RGZ may be related to differences in PPARγ transactivation. This finding indicates that PPARγ activity may be useful to select those patients, for whom PPARγ agonists may have a beneficial therapeutic effect
Type I insulin-like growth factor receptor over-expression induces proliferation and anti-apoptotic signaling in a three-dimensional culture model of breast epithelial cells
INTRODUCTION: Activation of the type I insulin-like growth factor receptor (IGFIR) promotes proliferation and inhibits apoptosis in a variety of cell types. Transgenic mice expressing a constitutively active IGFIR or IGF-I develop mammary tumors and increased levels of IGFIR have been detected in primary breast cancers. However, the contribution of IGFIR activation in promoting breast cancer progression remains unknown. Mammary epithelial cell lines grown in three-dimensional cultures form acinar structures that mimic the round, polarized, hollow and growth-arrested features of mammary alveoli. We used this system to determine how proliferation and survival signaling by IGFIR activation affects breast epithelial cell biology and contributes to breast cancer progression. METHODS: Pooled, stable MCF-10A breast epithelial cells expressing wild-type IGFIR or kinase-dead IGFIR (K1003A) were generated using retroviral-mediated gene transfer. The effects of over-expression of wild-type or kinase-dead IGFIR on breast epithelial cell biology were analyzed by confocal microscopy of three-dimensional cultures. The contribution of signaling pathways downstream of IGFIR activation to proliferation and apoptosis were determined by pharmacological inhibition of phosphatidylinositol 3' kinase (PI3K) with LY294002, MAP kinase kinase (MEK) with UO126 and mammalian target of rapamycin (mTOR) with rapamycin. RESULTS: We found that MCF-10A cells over-expressing the IGFIR formed large, misshapen acinar structures with filled lumina and disrupted apico-basal polarization. This phenotype was ligand-dependent, occurring with IGF-I or supraphysiological doses of insulin, and did not occur in cells over-expressing the kinase-dead receptor. We observed increased proliferation, decreased apoptosis and increased phosphorylation of Ser(473 )of Akt and Ser(2448 )of mTOR throughout IGFIR structures. Inhibition of PI3K with LY294002 or MEK with UO126 prevented the development of acinar structures from IGFIR-expressing but not control cells. The mTOR inhibitor rapamycin failed to prevent IGFIR-induced hyperproliferation and survival signaling. CONCLUSION: Increased proliferation and survival signaling as well as loss of apico-basal polarity by IGFIR activation in mammary epithelial cells may promote early lesions of breast cancer. Three-dimensional cultures of MCF-10A cells over-expressing the IGFIR are a useful model with which to study the role of IGFIR signaling in breast cancer progression and for characterizing the effects of chemotherapeutics targeted to IGFIR signaling
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