971 resultados para College of Medicine events


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Background: Many European countries including Ireland lack high quality, on-going, population based estimates of maternal behaviours and experiences during pregnancy. PRAMS is a CDC surveillance program which was established in the United States in 1987 to generate high quality, population based data to reduce infant mortality rates and improve maternal and infant health. PRAMS is the only on-going population based surveillance system of maternal behaviours and experiences that occur before, during and after pregnancy worldwide.Methods: The objective of this study was to adapt, test and evaluate a modified CDC PRAMS methodology in Ireland. The birth certificate file which is the standard approach to sampling for PRAMS in the United States was not available for the PRAMS Ireland study. Consequently, delivery record books for the period between 3 and 5 months before the study start date at a large urban obstetric hospital [8,900 births per year] were used to randomly sample 124 women. Name, address, maternal age, infant sex, gestational age at delivery, delivery method, APGAR score and birth weight were manually extracted from records. Stillbirths and early neonatal deaths were excluded using APGAR scores and hospital records. Women were sent a letter of invitation to participate including option to opt out, followed by a modified PRAMS survey, a reminder letter and a final survey.Results: The response rate for the pilot was 67%. Two per cent of women refused the survey, 7% opted out of the study and 24% did not respond. Survey items were at least 88% complete for all 82 respondents. Prevalence estimates of socially undesirable behaviours such as alcohol consumption during pregnancy were high [>50%] and comparable with international estimates.Conclusion: PRAMS is a feasible and valid method of collecting information on maternal experiences and behaviours during pregnancy in Ireland. PRAMS may offer a potential solution to data deficits in maternal health behaviour indicators in Ireland with further work. This study is important to researchers in Europe and elsewhere who may be interested in new ways of tailoring an established CDC methodology to their unique settings to resolve data deficits in maternal health.

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This research investigates whether a reconfiguration of maternity services, which collocates consultant- and midwifery-led care, reflects demand and value for money in Ireland. Qualitative and quantitative research is undertaken to investigate demand and an economic evaluation is performed to evaluate the costs and benefits of the different models of care. Qualitative research is undertaken to identify women’s motivations when choosing place of delivery. These data are further used to inform two stated preference techniques: a discrete choice experiment (DCE) and contingent valuation method (CVM). These are employed to identify women’s strengths of preferences for different features of care (DCE) and estimate women’s willingness to pay for maternity care (CVM), which is used to inform a cost-benefit analysis (CBA) on consultant- and midwifery-led care. The qualitative research suggests women do not have a clear preference for consultant or midwifery-led care, but rather a hybrid model of care which closely resembles the Domiciliary Care In and Out of Hospital (DOMINO) scheme. Women’s primary concern during care is safety, meaning women would only utilise midwifery-led care when co-located with consultant-led care. The DCE also finds women’s preferred package of care closely mirrors the DOMINO scheme with 39% of women expected to utilise this service. Consultant- and midwifery-led care would then be utilised by 34% and 27% of women, respectively. The CVM supports this hierarchy of preferences where consultant-led care is consistently valued more than midwifery-led care – women are willing to pay €956.03 for consultant-led care and €808.33 for midwifery-led care. A package of care for a woman availing of consultant- and midwifery-led care is estimated to cost €1,102.72 and €682.49, respectively. The CBA suggests both models of care are cost-beneficial and should be pursued in Ireland. This reconfiguration of maternity services would maximise women’s utility, while fulfilling important objectives of key government policy.

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STUDY DESIGN: The inflammatory responses of primary human intervertebral disc (IVD) cells to tumor necrosis factor α (TNF-α) and an antagonist were evaluated in vitro. OBJECTIVE: To investigate an ability for soluble TNF receptor type II (sTNFRII) to antagonize TNF-α-induced inflammatory events in primary human IVD cells in vitro. SUMMARY OF BACKGROUND DATA: TNF-α is a known mediator of inflammation and pain associated with radiculopathy and IVD degeneration. sTNFRs and their analogues are of interest for the clinical treatment of these IVD pathologies, although information on the effects of sTNFR on human IVD cells remains unknown. METHODS: IVD cells were isolated from surgical tissues procured from 15 patients and cultured with or without 1.4 nmol/L TNF-α (25 ng/mL). Treatment groups were coincubated with varying doses of sTNFRII (12.5-100 nmol/L). Nitric oxide (NO), prostaglandin E₂ (PGE₂), and interleukin-6 (IL6) levels in media were quantified to characterize the inflammatory phenotype of the IVD cells. RESULTS: Across all patients, TNF-α induced large, statistically significant increases in NO, PGE₂, and IL6 secretion from IVD cells compared with controls (60-, 112-, and 4-fold increases, respectively; P < 0.0001). Coincubation of TNF-α with nanomolar doses of sTNFRII significantly attenuated the secretion of NO and PGE₂ in a dose-dependent manner, whereas IL6 levels were unchanged. Mean IC₅₀ values for NO and PGE₂ were found to be 35.1 and 20.5 nmol/L, respectively. CONCLUSION: Nanomolar concentrations of sTNFRII were able to significantly attenuate the effects of TNF-α on primary human IVD cells in vitro. These results suggest this sTNFR to be a potent TNF antagonist with potential to attenuate inflammation in IVD pathology.

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A model of telescoping is proposed that assumes no systematic errors in dating. Rather, the overestimation of recent occurrences of events is based on the combination of three factors: (1) Retention is greater for recent events; (2) errors in dating, though unbiased, increase linearly with the time since the dated event; and (3) intrusions often occur from events outside the period being asked about, but such intrusions do not come from events that have not yet occurred. In Experiment 1, we found that recall for colloquia fell markedly over a 2-year interval, the magnitude of errors in psychologists' dating of the colloquia increased at a rate of .4 days per day of delay, and the direction of the dating error was toward the middle of the interval. In Experiment 2, the model used the retention function and dating errors from the first study to predict the distribution of the actual dates of colloquia recalled as being within a 5-month period. In Experiment 3, the findings of the first study were replicated with colloquia given by, instead of for, the subjects.

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During mitotic cell cycles, DNA experiences many types of endogenous and exogenous damaging agents that could potentially cause double strand breaks (DSB). In S. cerevisiae, DSBs are primarily repaired by mitotic recombination and as a result, could lead to loss-of-heterozygosity (LOH). Genetic recombination can happen in both meiosis and mitosis. While genome-wide distribution of meiotic recombination events has been intensively studied, mitotic recombination events have not been mapped unbiasedly throughout the genome until recently. Methods for selecting mitotic crossovers and mapping the positions of crossovers have recently been developed in our lab. Our current approach uses a diploid yeast strain that is heterozygous for about 55,000 SNPs, and employs SNP-Microarrays to map LOH events throughout the genome. These methods allow us to examine selected crossovers and unselected mitotic recombination events (crossover, noncrossover and BIR) at about 1 kb resolution across the genome. Using this method, we generated maps of spontaneous and UV-induced LOH events. In this study, we explore machine learning and variable selection techniques to build a predictive model for where the LOH events occur in the genome.

Randomly from the yeast genome, we simulated control tracts resembling the LOH tracts in terms of tract lengths and locations with respect to single-nucleotide-polymorphism positions. We then extracted roughly 1,100 features such as base compositions, histone modifications, presence of tandem repeats etc. and train classifiers to distinguish control tracts and LOH tracts. We found interesting features of good predictive values. We also found that with the current repertoire of features, the prediction is generally better for spontaneous LOH events than UV-induced LOH events.

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Four studies are reported that employed an object location task to assess temporal-causal reasoning. In Experiments 1-3, successfully locating the object required a retrospective consideration of the order in which two events had occurred. In Experiment 1, 5- but not 4-year-olds were successful; 4-year-olds also failed to perform at above-chance levels in modified versions of the task in Experiments 2 and 3. However, in Experiment 4, 3-year-olds were successful when they were able to see the object being placed first in one location and then in the other, rather than having to consider retrospectively the sequence in which two events had happened. The results suggest that reasoning about the causal significance of the temporal order of events may not be fully developed before 5 years. (C) 2007 Elsevier Inc. All rights reserved.

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Performance and documentation have long been characterised as oppositional practices, separated by competing voices which argue the virtues of disappearance and reproducibility. In response to this state of affairs, the recently completed Dialogic Evidence project was designed to explore the possibility (and the limits) of a productive co-existence between performance and documentation practices. In this paper I reflect on this project’s processes and outcomes, particular highlighting the potential of social web technologies as a collaborative means to archive, discuss and remember live performance.

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We study the predictability of a theoretical model for earthquakes, using a pattern recognition algorithm similar to the CN and M8 algorithms known in seismology. The model, which is a stochastic spring-block model with both global correlation and local interaction, becomes more predictable as the strength of the global correlation or the local interaction is increased.

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Data on rock temperatures has previously been collected to characterise typical diurnal regimes, and more recently to describe short-term variability in extreme locations. However, there is also the case that little is understood concerning the impact of extreme events in otherwise temperate environments. Internal stone temperatures (5?cm) collected during the atypical cold extreme experienced, throughout the UK, in December 2010 show a difference between ambient air temperatures and aspect-related thermal differences, particularly concerning temperature lows and the influence of radiative heating. In this case, debris release was not visible; however, laboratory simulations have shown that under such conditions, surface loss does not necessarily negate the occurrence of internal stone modifications. This preparatory sequence of change demonstrates that surface loss is not the result of one process, but rather many operating over time to sufficiently decrease stone strength to facilitate obvious damage.