559 research outputs found

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

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    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

    Diagnostic accuracy of the primary care screener for affective disorder (PC-SAD) in primary care

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    Background: Depression goes often unrecognised and untreated in non-psychiatric medical settings. Screening has recently gained acceptance as a first step towards improving depression recognition and management. The Primary Care Screener for Affective Disorders (PC-SAD) is a self-administered questionnaire to screen for Major Depressive Disorder (MDD) and Dysthymic Disorder (Dys) which has a sophisticated scoring algorithm that confers several advantages. This study tested its performance against a ‘gold standard’ diagnostic interview in primary care. Methods: A total of 416 adults attending 13 urban general internal medicine primary care practices completed the PC-SAD. Of 409 who returned a valid PC-SAD, all those scoring positive (N=151) and a random sample (N=106) of those scoring negative were selected for a 3-month telephone follow-up assessment including the administration of the Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID-I) by a psychiatrist who was masked to PC-SAD results. Results: Most selected patients (N=212) took part in the follow-up assessment. After adjustment for partial verification bias the sensitivity, specificity, positive and negative predictive value for MDD were 90%, 83%, 51%, and 98%. For Dys, the corresponding figures were 78%, 79%, 8%, and 88%. Conclusions: While some study limitations suggest caution in interpreting our results, this study corroborated the diagnostic validity of the PC-SAD, although the low PPV may limit its usefulness with regard to Dys. Given its good psychometric properties and the short average administration time, the PC-SAD might be the screening instrument of choice in settings where the technology for computer automated scoring is available

    What trans-vaginal ultrasound parameters are better correlated with a shorter labor induction to vaginal delivery interval? A prospective observational cohort study

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    Objective: During the induction of labor (IOL) planning, it is important to provide patients with information regarding how long the induction process might take. This study aimed to determine which ultrasonographic cervical parameters are independently associated with a shorter IOL-to-vaginal delivery (VD) interval. Methods: This was a prospective observational cohort study. For enrollment purposes, women with single pregnancy, fetus in cephalic presentation, age between 18 and 45 years and good Italian proficiency were included. Women with a history of uterine surgery, in active labor, and cases of fetal growth abnormalities were excluded. The enrolled women underwent a transvaginal ultrasound within 7 days from the scheduled labor induction in order to measure the following parameters: the cervical length (CL), the utero-cervical angle (UCA), the cervical sliding sign (CSS) and the cervical consistency index (CCI). Before starting the labor induction process, patients were also digitally evaluated, acquiring the Bishop score (BS). The method of IOL was determined based on the BS. Ultrasound assessments and Bishop score evaluations were performed independently and in a blinded manner to reduce bias. Statistical analyses were performed using STATA 18.0. Results: Between June 2023 and November 2024, 400 women were nonconsecutively enrolled in the study. Of these, 83 experienced spontaneous labor before the scheduled labor induction, resulting in 317 women who underwent IOL. The median IOL-to-VD interval was 1264 min (IQR 694–1940). Univariable regression analysis demonstrated significant associations between the IOL-to-VD interval and CL (β = 29.15; 95% CI 16.16, 42.23; p < 0.001), CCI (β = 12.60; 95% CI 3.93, 21.24; p = 0.004), and BS (β = −211.15; 95% CI −271.59, −150.71; p < 0.001). Multivariable analysis confirmed independent associations with CL (β = 13.89; 95% CI 0.35,27.44; p = 0.044) and BS (β = −183.96; −249.66, −118.27; p < 0.001). When stratified by parity, univariable regression in parous women showed significant associations between the IOL-to-VD interval and CL (β = 37.44; 95% CI 20.17, 54.72; p < 0.001), CSS (β = −582; 95% CI −1014.05, 151.20; p = 0.009), CCI (β = 15.43; 95% CI 1.75, 29.11; p = 0.027), and BS (β = −227.96; −315.57, −140.35; p < 0.001). Conclusions: In summary, among the evaluated parameters, CL consistently showed the strongest and most independent association with a shorter IOL-to-VD interval across analyses, supporting its role as the most reliable predictor. Future research should explore multivariable prediction models incorporating various ultrasonographic cervical parameters to enhance the predictive accuracy of transvaginal ultrasound

    Regulation of microRNA biogenesis and turnover by animals and their viruses

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    Item does not contain fulltextMicroRNAs (miRNAs) are a ubiquitous component of gene regulatory networks that modulate the precise amounts of proteins expressed in a cell. Despite their small size, miRNA genes contain various recognition elements that enable specificity in when, where and to what extent they are expressed. The importance of precise control of miRNA expression is underscored by functional studies in model organisms and by the association between miRNA mis-expression and disease. In the last decade, identification of the pathways by which miRNAs are produced, matured and turned-over has revealed many aspects of their biogenesis that are subject to regulation. Studies in viral systems have revealed a range of mechanisms by which viruses target these pathways through viral proteins or non-coding RNAs in order to regulate cellular gene expression. In parallel, a field of study has evolved around the activation and suppression of antiviral RNA interference (RNAi) by viruses. Virus encoded suppressors of RNAi can impact miRNA biogenesis in cases where miRNA and small interfering RNA pathways converge. Here we review the literature on the mechanisms by which miRNA biogenesis and turnover are regulated in animals and the diverse strategies that viruses use to subvert or inhibit these processes

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

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    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

    The Raf-1 inhibitor GW5074 and dexamethasone suppress sidestream smoke-induced airway hyperresponsiveness in mice

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    <p>Abstract</p> <p>Background</p> <p>Sidestream smoke is closely associated with airway inflammation and hyperreactivity. The present study was designed to investigate if the Raf-1 inhibitor GW5074 and the anti-inflammatory drug dexamethasone suppress airway hyperreactivity in a mouse model of sidestream smoke exposure.</p> <p>Methods</p> <p>Mice were repeatedly exposed to smoke from four cigarettes each day for four weeks. After the first week of the smoke exposure, the mice received either dexamethasone intraperitoneally every other day or GW5074 intraperitoneally every day for three weeks. The tone of the tracheal ring segments was recorded with a myograph system and concentration-response curves were obtained by cumulative administration of agonists. Histopathology was examined by light microscopy.</p> <p>Results</p> <p>Four weeks of exposure to cigarette smoke significantly increased the mouse airway contractile response to carbachol, endothelin-1 and potassium. Intraperitoneal administration of GW5074 or dexamethasone significantly suppressed the enhanced airway contractile responses, while airway epithelium-dependent relaxation was not affected. In addition, the smoke-induced infiltration of inflammatory cells and mucous gland hypertrophy were attenuated by the administration of GW5074 or dexamethasone.</p> <p>Conclusion</p> <p>Sidestream smoke induces airway contractile hyperresponsiveness. Inhibition of Raf-1 activity and airway inflammation suppresses smoking-associated airway hyperresponsiveness.</p
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