Is simulation the only keystone of surgical training?

No abstract availabl

Kinetic modelling of competition and depletion of shared miRNAs by competing endogenous RNAs

Non-conding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting e.g. the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.Comment: review article, 29 pages, 7 figure

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

Modelling negative feedback networks for activating transcription factor 3 predicts a dominant role for miRNAs in immediate early gene regulation

Activating transcription factor 3 (Atf3) is rapidly and transiently upregulated in numerous systems, and is associated with various disease states. Atf3 is required for negative feedback regulation of other genes, but is itself subject to negative feedback regulation possibly by autorepression. In cardiomyocytes, Atf3 and Egr1 mRNAs are upregulated via ERK1/2 signalling and Atf3 suppresses Egr1 expression. We previously developed a mathematical model for the Atf3-Egr1 system. Here, we adjusted and extended the model to explore mechanisms of Atf3 feedback regulation. Introduction of an autorepressive loop for Atf3 tuned down its expression and inhibition of Egr1 was lost, demonstrating that negative feedback regulation of Atf3 by Atf3 itself is implausible in this context. Experimentally, signals downstream from ERK1/2 suppress Atf3 expression. Mathematical modelling indicated that this cannot occur by phosphorylation of pre-existing inhibitory transcriptional regulators because the time delay is too short. De novo synthesis of an inhibitory transcription factor (ITF) with a high affinity for the Atf3 promoter could suppress Atf3 expression, but (as with the Atf3 autorepression loop) inhibition of Egr1 was lost. Developing the model to include newly-synthesised miRNAs very efficiently terminated Atf3 protein expression and, with a 4-fold increase in the rate of degradation of mRNA from the mRNA/miRNA complex, profiles for Atf3 mRNA, Atf3 protein and Egr1 mRNA approximated to the experimental data. Combining the ITF model with that of the miRNA did not improve the profiles suggesting that miRNAs are likely to play a dominant role in switching off Atf3 expression post-induction

Regulation of cellular proliferation, differentiation and cell death by activated Raf

The protein kinases Raf-1, A-Raf and B-Raf connect receptor stimulation with intracellular signaling pathways and function as a central intermediate in many signaling pathways. Gain-of-function experiments shed light on the pleiotropic biological activities of these enzymes. Expression experiments involving constitutively active Raf revealed the essential functions of Raf in controlling proliferation, differentiation and cell death in a cell-type specific manner

Deactylase inhibition in myeloproliferative neoplasms

Myeloproliferative neoplasms (MPN) are clonal haemopoietic progenitor cell disorders characterized by the proliferation of one or more of the haemopoietic lineages (myeloid, erythroid and/or megakaryocytic). The MPNs include eight haematological disorders: chronic myelogenous leukemia (CML), polycythemia vera (PV), essential thrombocythemia (ET), primary myelofibrosis (PMF), systemic mastocytosis (SM), chronic eosinophilic leukemia, not otherwise specified (CEL, NOS), chronic neutrophilic leukemia (CNL), and unclassifiable MPN (MPN, U). Therapeutic interventions for MPNs include the use of tyrosine kinase inhibitors (TKIs) for BCR-ABL1+ CML and JAK2 inhibitors for PV, ET and PMF. Histone deacetylase inhibitors (HDACi) are a novel class of drugs capable of altering the acetylation status of both histone and non-histone proteins, thereby affecting a repertoire of cellular functions in neoplastic cells including proliferation, differentiation, immune responses, angiogenesis and survival. Preliminary studies indicate that HDACi when used in combination with tyrosine kinase or JAK2 inhibitors may overcome resistance to the latter agents and enhance the pro-apoptotic effects on MPN cells. This review provides a review of pre-clinical and clinical studies that have explored the use of HDACi as potential therapeutics for MPNs

Overexpression of the Lung Cancer-Prognostic miR-146b MicroRNAs Has a Minimal and Negative Effect on the Malignant Phenotype of A549 Lung Cancer Cells

INTRODUCTION:Expression levels of miR-146b-5p and -3p microRNAs in human non-small cell lung cancer (NSCLC) are associated with recurrence of the disease after surgery. To understand this, the effect of miR-146b overexpression was studied in A549 human lung cancer cells. METHODS:A549 cells, engineered with lentiviruses to overexpress the human pre-miR-146b precursor microRNA, were examined for proliferation, colony formation on plastic surface and in soft agar, migration and invasiveness in cell culture and in vivo in mice, chemosensitivity to cisplatin and doxorubicin, and global gene expression. miR-146b expressions were assessed in microdissected stroma and epithelia of human NSCLC tumors. Association of miR-146b-5p and -3p expression in early stage NSCLC with recurrence was analyzed. PRINCIPAL FINDINGS:A549 pre-miR-146b-overexpressors had 3-8-fold higher levels of both miR-146b microRNAs than control cells. Overexpression did not alter cellular proliferation, chemosensitivity, migration, or invasiveness; affected only 0.3% of the mRNA transcriptome; and, reduced the ability to form colonies in vitro by 25%. In human NSCLC tumors, expression of both miR-146b microRNAs was 7-10-fold higher in stroma than in cancerous epithelia, and higher miR-146b-5p but lower -3p levels were predictive of recurrence. CONCLUSIONS:Only a minimal effect of pre-miR-146b overexpression on the malignant phenotype was seen in A549 cells. This could be because of opposing effects of miR-146b-5p and -3p overexpression as suggested by the conflicting recurrence-predictive values of the two microRNAs, or because miR-146b expression changes in non-cancerous stroma and not cancerous epithelia of tumors are responsible for the prognostic value of miR-146b

MUC1 alters oncogenic events and transcription in human breast cancer cells

INTRODUCTION: MUC1 is an oncoprotein whose overexpression correlates with aggressiveness of tumors and poor survival of cancer patients. Many of the oncogenic effects of MUC1 are believed to occur through interaction of its cytoplasmic tail with signaling molecules. As expected for a protein with oncogenic functions, MUC1 is linked to regulation of proliferation, apoptosis, invasion, and transcription. METHODS: To clarify the role of MUC1 in cancer, we transfected two breast cancer cell lines (MDA-MB-468 and BT-20) with small interfering (si)RNA directed against MUC1 and analyzed transcriptional responses and oncogenic events (proliferation, apoptosis and invasion). RESULTS: Transcription of several genes was altered after transfection of MUC1 siRNA, including decreased MAP2K1 (MEK1), JUN, PDGFA, CDC25A, VEGF and ITGAV (integrin α(v)), and increased TNF, RAF1, and MMP2. Additional changes were seen at the protein level, such as increased expression of c-Myc, heightened phosphorylation of AKT, and decreased activation of MEK1/2 and ERK1/2. These were correlated with cellular events, as MUC1 siRNA in the MDA-MB-468 line decreased proliferation and invasion, and increased stress-induced apoptosis. Intriguingly, BT-20 cells displayed similar levels of apoptosis regardless of siRNA, and actually increased proliferation after MUC1 siRNA. CONCLUSION: These results further the growing knowledge of the role of MUC1 in transcription, and suggest that the regulation of MUC1 in breast cancer may be more complex than previously appreciated. The differences between these two cell lines emphasize the importance of understanding the context of cell-specific signaling events when analyzing the oncogenic functions of MUC1, and caution against generalizing the results of individual cell lines without adequate confirmation in intact biological systems

Rapid growth of new atmospheric particles by nitric acid and ammonia condensation

New-particle formation is a major contributor to urban smog$^{1,2}$, but how it occurs in cities is often puzzling$^{3}$. If the growth rates of urban particles are similar to those found in cleaner environments (1–10 nanometres per hour), then existing understanding suggests that new urban particles should be rapidly scavenged by the high concentration of pre-existing particles. Here we show, through experiments performed under atmospheric conditions in the CLOUD chamber at CERN, that below about +5 degrees Celsius, nitric acid and ammonia vapours can condense onto freshly nucleated particles as small as a few nanometres in diameter. Moreover, when it is cold enough (below −15 degrees Celsius), nitric acid and ammonia can nucleate directly through an acid–base stabilization mechanism to form ammonium nitrate particles. Given that these vapours are often one thousand times more abundant than sulfuric acid, the resulting particle growth rates can be extremely high, reaching well above 100 nanometres per hour. However, these high growth rates require the gas-particle ammonium nitrate system to be out of equilibrium in order to sustain gas-phase supersaturations. In view of the strong temperature dependence that we measure for the gas-phase supersaturations, we expect such transient conditions to occur in inhomogeneous urban settings, especially in wintertime, driven by vertical mixing and by strong local sources such as traffic. Even though rapid growth from nitric acid and ammonia condensation may last for only a few minutes, it is nonetheless fast enough to shepherd freshly nucleated particles through the smallest size range where they are most vulnerable to scavenging loss, thus greatly increasing their survival probability. We also expect nitric acid and ammonia nucleation and rapid growth to be important in the relatively clean and cold upper free troposphere, where ammonia can be convected from the continental boundary layer and nitric acid is abundant from electrical storms$^{4,5}$

MicroRNA degradation by a conserved target RNA regulates animal behavior

International audiencemicroRNAs (miRNAs) repress target transcripts through partial complementarity. By contrast, highly complementary miRNA-binding sites within viral and artificially engineered transcripts induce miRNA degradation in vitro and in cell lines. Here, we show that a genome-encoded transcript harboring a near-perfect and deeply conserved miRNA-binding site for miR-29 controls zebrafish and mouse behavior. This transcript originated in basal vertebrates as a long noncoding RNA (lncRNA) and evolved to the protein-coding gene NREP in mammals, where the miR-29-binding site is located within the 3′ UTR. We show that the near-perfect miRNA site selectively triggers miR-29b destabilization through 3′ trimming and restricts its spatial expression in the cerebellum. Genetic disruption of the miR-29 site within mouse Nrep results in ectopic expression of cerebellar miR-29b and impaired coordination and motor learning. Thus, we demonstrate an endogenous target-RNA-directed miRNA degradation event and its requirement for animal behavio