Telomerase related studies in thyroid cancer

Follicular thyroid neoplasms are diagnostically challenging. On histologic evaluation, it can be difficult, resource-consuming, and observer-dependent to pinpoint the exact location of capsular or vascular invasion. In some cases, it is impossible to do so unequivocally – for those, the term “follicular tumor of uncertain malignant potential” (FT-UMP) was created. On cytologic evaluation, it is less challenging but rather hardly possible to distinguish follicular thyroid adenoma (FTA) from follicular thyroid carcinoma (FTC). With the advent of molecular analyses in clinical diagnostic settings, many mutational events have been associated with specific cancers. Amongst those, two point mutations in the TERT promoter region, named C228T and C250T have been of particular interest as they have been associated with malignant properties in thyroid tumors in general and a worse prognosis with a higher frequency of relapse in particular. This thesis aims to improve the diagnostic accuracy for thyroid tumors in general and for follicular thyroid tumors in particular through the implementation of TERT promoter mutational screening. Study I evaluates the role of TERT promoter mutational screening in a clinical series of FT-UMPs and how this analysis aids in detecting relapse-prone tumors. This could help alter adjuvant treatment modalities even in the absence of clearcut histopathological evidence of malignant potential. Study II shows that digital droplet PCR (ddPCR) can improve the sensitivity for the detection of TERT promoter mutations in follicular thyroid tumors and can even detect TERT promoter mutations when they occur subclonal and are heterogeneously distributed in FT-UMPs. Study III validates TERT promoter mutational testing on preoperative material in the form of frozen pellets from thyroid FNAC material. We were able to show that ddPCR is a reliable analysis for cytologic material and may help to identify high-risk cases and triage them to a more aggressive treatment plan up-front, underlining the markers' diagnostic and prognostic value. Study IV tries to evaluate 5hmC immunoreactivity as an expressional analysis to pinpoint TERT promoter mutations in FTCs. Even though the study was able to show that the loss of 5hmC immunoreactivity may signify TERT promoter mutations in subsets of FTCs, we could not prove its clinical value to predict the TERT promoter mutational status. Further studies are therefore warranted. In summary, the findings in this thesis highlight the clinical importance of TERT promoter mutational screening in follicular thyroid neoplasms. Furthermore, we were able to show that ddPCR is a reliable technique for interrogating specific mutations of the TERT promoter

A Novel and Fast Approach for Population Structure Inference Using Kernel-PCA and Optimization (PSIKO)

Population structure is a confounding factor in Genome Wide Association Studies, increasing the rate of false positive associations. In order to correct for it, several model-based algorithms such as ADMIXTURE and STRUCTURE have been proposed. These tend to suffer from the fact that they have a considerable computational burden, limiting their applicability when used with large datasets, such as those produced by Next Generation Sequencing (NGS) techniques. To address this, non-model based approaches such as SNMF and EIGENSTRAT have been proposed, which scale better with larger data. Here we present a novel non-model based approach, PSIKO, which is based on a unique combination of linear kernel-PCA and least-squares optimization and allows for the inference of admixture coefficients, principal components, and number of founder populations of a dataset. PSIKO has been compared against existing leading methods on a variety of simulation scenarios, as well as on real biological data. We found that in addition to producing results of the same quality as other tested methods, PSIKO scales extremely well with dataset size, being considerably (up to 30 times) faster for longer sequences than even state of the art methods such as SNMF. PSIKO and accompanying manual are freely available at https://www.uea.ac.uk/computing/psiko

Dependent Types for Pragmatics

This paper proposes the use of dependent types for pragmatic phenomena such as pronoun binding and presupposition resolution as a type-theoretic alternative to formalisms such as Discourse Representation Theory and Dynamic Semantics.Comment: This version updates the paper for publication in LEU

Reinforcement Learning Produces Dominant Strategies for the Iterated Prisoner's Dilemma

We present tournament results and several powerful strategies for the Iterated Prisoner's Dilemma created using reinforcement learning techniques (evolutionary and particle swarm algorithms). These strategies are trained to perform well against a corpus of over 170 distinct opponents, including many well-known and classic strategies. All the trained strategies win standard tournaments against the total collection of other opponents. The trained strategies and one particular human made designed strategy are the top performers in noisy tournaments also

The utility of scoring systems in critically ill cirrhotic patients admitted to a general intensive care unit

Purpose: This study aimed to establish which prognostic scoring tool provides the greatest discriminative ability when assessing critically ill cirrhotic patients in a general intensive care unit (ICU) setting.<p></p> Methods: This was a 12-month, single-centered prospective cohort study performed in a general, nontransplant ICU. Forty clinical and demographic variables were collected on admission to calculate 8 prospective scoring tools. Patients were followed up to obtain ICU and inhospital mortality. Receiver operating characteristic curve analysis was used to determine the discriminative ability of the scores. Univariate and multivariate analyses were used to identify any independent predictors of mortality in these patients. The incorporation of any significant variables into the scoring tools was assessed.<p></p> Results: Fifty-nine cirrhotic patients were admitted over the study period, with an ICU mortality of 31%. All scores other than the renal-specific Acute Kidney Injury Network score had similar discriminative abilities, producing area under the curves of between 0.70 and 0.76. None reached the clinically applicable level of 0.8. The Sequential Organ Failure Assessment score was the best performing score. Lactate and ascites were individual predictors of ICU mortality with statistically significant odds ratios of 1.69 and 5.91, respectively. When lactate was incorporated into the Child-Pugh score, its prognostic accuracy increased to a clinically applicable level (area under the curve, 0.86).<p></p> Conclusions: This investigation suggests that established prognostic scoring systems should be used with caution when applied to the general, nontransplant ICU as compared to specialist centers. Our data suggest that serum arterial lactate may improve the prognostic ability of these scores

Confidence Intervals for Asbestos Fiber Counts: Approximate Negative Binomial Distribution

The negative binomial distribution is adopted for analyzing asbestos fiber counts so as to account for both the sampling errors in capturing only a finite number of fibers and the inevitable human variation in identifying and counting sampled fibers. A simple approximation to this distribution is developed for the derivation of quantiles and approximate confidence limits. The success of the approximation depends critically on the use of Stirling’s expansion to sufficient order, on exact normalization of the approximating distribution, on reasonable perturbation of quantities from the normal distribution, and on accurately approximating sums by inverse-trapezoidal integration. Accuracy of the approximation developed is checked through simulation and also by comparison to traditional approximate confidence intervals in the specific case that the negative binomial distribution approaches the Poisson distribution. The resulting statistics are shown to relate directly to early research into the accuracy of asbestos sampling and analysis. Uncertainty in estimating mean asbestos fiber concentrations given only a single count is derived. Decision limits (limits of detection) and detection limits are considered for controlling false-positive and false-negative detection assertions and are compared to traditional limits computed assuming normal distributions

Adjustable Head Tube Angle Headset

This final design review report describes the design, manufacture, and test process of a bicycle headset capable of quickly and easily adjusting the effective head tube angle. The evolution of mountain bike geometry has forced bike designers to compromise between climbing and descending performance when choosing a head tube angle. A headset capable of quickly adjusting the effective head tube angle would allow riders to optimize their bike’s geometry for different stages of riding. This report details the research, idea generation, concept development and selection, design, manufacturing, and testing of our adjustable head tube angle headset