Ontogenic Expression And Characterization Of The Longchained Polyunsaturated Fatty Acid Biosynthesis Enzyme, Elongase In Zebrafish

The importance of long-chained polyunsaturated fatty acids (LC-PUFAs) in vertebrates’ development has been widely studied. Among these, include roles in maintaining cellular membrane integrity, cellular signaling, gene regulation and metabolism. LC-PUFAs such as arachidonic acid, eicosapentaenoic acid and docosahexaenoic acid also mediate physiological processes like inflammation, immunity, reproduction and development. Despite the known importance of LCPUFAs during development, very little is known about their utilization and biosynthesis during embryogenesis

Upregulated mRNA expression of desaturase and elongase, two enzymes involved in highly unsaturated fatty acids biosynthesis pathways during follicle maturation in zebrafish

<p>Abstract</p> <p>Background</p> <p>Although unsaturated fatty acids such as eicosapentaenoic acid (EPA, C20:5n-3), docosahexaenoic acid (DHA, C22:6n-3) and arachidonic acid (ARA, C20:4n-6), collectively known as the highly unsaturated fatty acids (HUFA), play pivotal roles in vertebrate reproduction, very little is known about their synthesis in the ovary. The zebrafish (Danio rerio) display capability to synthesize all three HUFA via pathways involving desaturation and elongation of two precursors, the linoleic acid (LA, C18:2n-6) and linolenic acid (LNA, C18:3n-3). As a prerequisite to gain full understanding on the importance and regulation of ovarian HUFA synthesis, we described here the mRNA expression pattern of two enzymes; desaturase (fadsd6) and elongase (elovl5), involved in HUFA biosynthesis pathway, in different zebrafish ovarian follicle stages. Concurrently, the fatty acid profile of each follicle stage was also analyzed.</p> <p>Methods</p> <p>mRNA levels of fadsd6 and elovl5 in different ovarian follicle stages were determined by semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR) assays. For analysis of the ovarian follicular fatty acid composition, gas chromatography was used.</p> <p>Results</p> <p>Our results have shown that desaturase displayed significant upregulation in expression during the oocyte maturation stage. Expression of elongase was significantly highest in pre-vitellogenic follicles, followed by maturation stage. Fatty acid composition analysis of different ovarian follicle stages also showed that ARA level was significantly highest in pre-vitellogenic and matured follicles. DHA level was highest in both late vitellogenic and maturation stage.</p> <p>Conclusion</p> <p>Collectively, our findings seem to suggest the existence of a HUFA synthesis system, which could be responsible for the synthesis of HUFA to promote oocyte maturation and possibly ovulation processes. The many advantages of zebrafish as model system to understand folliculogenesis will be useful platform to further elucidate the regulatory and mechanism aspects of ovarian HUFA synthesis.</p

Statistical and graphical evidence synthesis methods in health technology assessment

This thesis focusses on the challenges relating to clinical- and cost-effectiveness analysis in Health Technology Assessment (HTA). It includes methodological developments, both statistical and presentational, in evidence synthesis aiming to address those challenges. In HTA, analysts often face problems with limited availability of data required to inform economic model. This thesis proposes innovative evidence synthesis approaches to address this challenge, illustrated in two examples. Bivariate random-effects meta-analysis (BRMA) and network meta-analysis (NMA) were used to synthesise all available evidence to predict progression-free survival (PFS), in metastatic prostate cancer. This enabled the specification of a three-state Markov model previously limited to two states when PFS was not recorded. In the second example, a scenario in multiple sclerosis is considered where utility data for the trials included in a HTA were not available and external utility data from a single study was used instead. This thesis illustrates how BRMA can be applied to include all available evidence to inform utility estimates for use in a cost-effectiveness analysis. NMA, allowing for a simultaneous and coherent comparison of multiple interventions, is increasingly used in HTA. However, due to the inherent complexity of presenting NMA results, it is important to ease their interpretability. A review of existing methods of presenting NMA results in HTA reports revealed that there is no standardised presentational tool for their reporting. Novel presentational approaches were developed which are presented in this thesis. The original contributions of this thesis are the innovative approaches to incorporate historical data to predict and increase the precision of parameter estimates for cost-effectiveness analysis to better inform health policy decision-making; and three novel graphical tools to aid clear presentation and facilitate interpretation of NMA results. Ultimately, the hope is that the graphical tools developed will be recommended in updated guidance setting the standards for future HTAs

Estimation of intervention effects using first or multiple episodes in clinical trials: The Andersen-Gill model re-examined.

Randomized trials of interventions against infectious diseases are often analyzed using data on first or only episodes of disease, even when subsequent episodes have been recorded. It is often said that the Andersen-Gill (AG) model gives a biased estimate of intervention effect if there is event dependency over time. We demonstrate that, in the presence of event dependency, an effective intervention may have an indirect effect on disease risk at time t(j) via its direct effect on disease risk at time t(i), i<j, and that the AG model estimates the total effect instead of the direct effect alone. From a clinical and public health perspective, estimation of the total effect is important. Previous simulation studies showed contradictory results about the performance of the AG model in the presence of unobserved heterogeneity across individuals. We show that some of the previous studies unintentionally created informative censoring in their data generating process by including only a certain maximum number of events per individual. We re-ran some previous simulations with and without altering this maximum. With reference to the situations often seen in pneumococcal vaccine trials, we evaluated the performance of the Cox model for time to first episode and the AG model for multiple episodes. We applied these models to re-analyze data from a pneumococcal conjugate vaccine trial. We maintain that a careful clarification of research purpose is needed before one can choose a statistical model, and that the AG model is useful in the estimation of the total effect of an intervention

Bayesian multi-parameter evidence synthesis to inform decision-making: a case study in metastatic hormone-refractory prostate cancer

In health technology assessment, decisions are based on complex cost-effectiveness models which require numerous input parameters. When not all relevant estimates are available the model may have to be simplified. Multi-parameter evidence synthesis combines data from diverse sources of evidence which results in obtaining estimates required in clinical decision-making that otherwise may not be available. We demonstrate how bivariate meta-analysis can be used to predict an unreported estimate of a treatment effect enabling implementation of a multi-state Markov model, which otherwise needs to be simplified. To illustrate this, we used an example of cost-effectiveness analysis for docetaxel in combination with prednisolone in metastatic hormone-refractory prostate cancer. Bivariate meta-analysis was used to model jointly available data on treatment effects on overall survival and progression-free survival (PFS) to predict the unreported effect on PFS in a study evaluating docetaxel with prednisolone. The predicted treatment effect on PFS enabled implementation of a three-state Markov model comprising of stable disease, progressive disease and dead states, whilst lack of the estimate restricted the model to a two-state model (with alive and dead states). The two-state and three-state models were compared by calculating the incremental cost-effectiveness ratio (which was much lower in the three-state model: £22,148 per QALY gained compared to £30,026 obtained from the two-state model) and the expected value of perfect information (which increased with the three-state model). The three-state model has the advantage of distinguishing surviving patients who progressed from those who did not progress. Hence, the use of advanced meta-analytic techniques allowed obtaining relevant parameter estimates to populate a model describing disease pathway more appropriately, whilst helping to prevent valuable clinical data from being discarded

Sample sizes for estimating differences in proportionscan we keep things simple?

10.1080/10543406.2010.508346Journal of Biopharmaceutical Statistics221133-140JBST

Association of clinical factors with survival outcomes in laryngeal squamous cell carcinoma (LSCC).

10.1371/journal.pone.0224665PLoS One1411e0224665