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Whitefish (Coregonus lavaretus) populations diverge into morphs that differ in body size along a benthic-limnetic axis and throughout the depth of the water column. This process is assumedly initiated by the presence of northern pike (Esox lucius) and is followed by morphological adaptations to available food resources. In this study eight populations of whitefish was studied with the purpose of increasing the knowledge about adaptive trait utility in the feeding apparatus of whitefish. This was done by analyzing the mean and absolute maximum and minimum prey size ingested by fish along four morphological trait gradients. The morphological traits was body size, gill raker number and density, and gape size. The results show clear evidence of morphological adaptations in both the benthic and limnetic habitat, furthermore, when comparing the two prey size responses (mean and absolute values) it becomes clear that none of the studied whitefish is physically constrained in terms of the largest prey they can ingest. However, large fish seem to be limited in eating small prey sizes. Interestingly, I also found strong indicators for filter feeding adaptation for one of the studied populations.

Adaptive radiations provide exceptional opportunities to examine the relationships between natural selection, adaptation, and speciation. Neotropical Adelpha butterflies may represent such a radiation, characterized by extraordinary breadth in host plant use and wing color patterns. In this study, we use genome-wide RAD markers to reconstruct the complex evolutionary history of Adelpha and the closely related temperate genus, Limenitis. Despite the presence of significant missing data, a variety of phylogenetic methods produce similar and highly supported trees. These well-resolved phylogenies allow for the identification of an ecologically important shift to a toxic host plant family, as well as the confirmation of rampant wing pattern mimicry throughout the genus. Taken together, our results support the hypothesis that the colonization of novel host plants represents a key evolutionary innovation that is fueling ongoing adaptive diversification within this large, phenotypically diverse butterfly radiation.

A previous approach to robust intensity-modulated radiation therapy (IMRT) treatment planning for moving tumours in the lung involves solving a single planning problem before treatment and using the resulting solution in all of the subsequent treatment sessions. In this thesis, we develop two adaptive robust IMRT optimization approaches for lung cancer, which involve using information gathered in prior treatment sessions to guide the reoptimization of the treatment for the next session. The first method is based on updating an estimate of the uncertain effect, while the second is based on additionally updating the dose requirements to account for prior errors in dose. We present computational results using real patient data for both methods and an asymptotic analysis for the first method. Through these results, we show that both methods lead to improvements in the final dose distribution over the traditional robust approach, but differ greatly in their daily dose performance.

A previous approach to robust intensity-modulated radiation therapy (IMRT) treatment planning for moving tumours in the lung involves solving a single planning problem before treatment and using the resulting solution in all of the subsequent treatment sessions. In this thesis, we develop two adaptive robust IMRT optimization approaches for lung cancer, which involve using information gathered in prior treatment sessions to guide the reoptimization of the treatment for the next session. The first method is based on updating an estimate of the uncertain effect, while the second is based on additionally updating the dose requirements to account for prior errors in dose. We present computational results using real patient data for both methods and an asymptotic analysis for the first method. Through these results, we show that both methods lead to improvements in the final dose distribution over the traditional robust approach, but differ greatly in their daily dose performance.

No description available.

Proton therapy, a promising alternative to conventional photon therapy, has gained widespread acceptance in clinical practice. This is attributed to its superior depth-dose curve that has a negligible dose beyond the maximum range of the proton. A proton treatment planning requires a multitude of parameters and are either manually selected or optimized using mathematical formulation. However, a proton treatment plan is also subject to various systematic and random uncertainties that must be taken into account during optimization. Robust optimization is a commonly used method for integrating the setup and range uncertainties in proton therapy. In addition to the uncertainties accounted for during the treatment planning phase, others can arise during the course of treatment and are often hard to predict. Changes in the patient's anatomy represent uncertainties that can significantly affect planned dose delivery. Therefore, adaptive planning is typically performed intermittently or regularly, depending on the changes in anatomy. Paper II included in this thesis proposed a method of adaptive planning that takes into account the impact of the patient's respiratory motion at the treatment site, such as the lungs and abdomen for 4D robust optimization. This method uses dose mimicking to reproduce the results as initially planned.   This additional stage of adaptive planning can introduce new complexities and uncertainties into the treatment process. One such uncertainty arise from daily cone beam computed tomography (CBCT) images which are required for treatment plan adaptation. Several strategies have been proposed in the past to improve the quality of these images, but each strategy has its advantages and disadvantages, depending on the site of treatment. In Paper I, a method was proposed that combined the advantages of other frequently used methods to create an improved method for generating daily images with CT-like image quality. This can contribute towards the goal of online adaptive in the near future with reduced uncertainties. This thesis will provide a brief introduction and an in-depth chapter to elucidate the background, better understand the physics of proton therapy, the process of treatment planning, and the need for adaptive planning. / European Union’s Horizon 2020 Marie Skłodowska-Curie Actions under Grant Agreement No. 955956

L'imagerie est maintenant partie intégrante des traitements de radiothérapie. Avec la technologie CBCT embarquée sur les appareils de traitement, l'imagerie tomographique permet non seulement de repositionner fidèlement le patient tout au long de son traitement mais aussi d'adapter la planification initiale aux modifications quotidiennes de volume. C'est la radiothérapie adaptative, objet des travaux de cette thèse. Nous avons établi les limites techniques de précision de repositionnement des équipements utilisé. Ensuite, à partir des acquisitions CBCT quotidiennes de patients traités pour la prostate, nous avons élaboré une stratégie de traitement basée sur une banque de plans personnalisés. Nous avons mis au point une méthode semi-automatique de sélection du plan de traitement du jour qui a montré une efficacité supérieure à la sélection par des opérateurs expérimentés. Enfin, nous avons quantifié les doses additionnelles à la dose thérapeutique associées à l'utilisation quotidienne de l'imagerie CBCT. En conclusion, on peut dire qu'avec l'imagerie CBCT embarquée, on peut voir ce que l'on veut traiter, irradier ce que l'on a vu et contrôler ce qu'on a traité. / Imaging is now fully integrated in the radiation therapy process. With on-board CBCT systems, tomography imaging allows not only patient positioning but also treatment planning adaptation with patient anatomy modifications, throughout the entire treatment. This is called adaptive radiation therapy, and is the main subject of this PhD thesis. During this work, we measured the repositioning accuracy of the system used. We also developed a treatment strategy using daily CBCT images and a personalized plan database to adapt treatment plan to patient anatomy. We found a way to select the daily treatment plan that shows superiority over operator selection. Then we also quantified the additional dose delivered while using this technique and the impact with regards to the risks added to patients. As a conclusion, with CBCT imaging, radiation therapy has entered an era where one can see what need to be treated, can treat what has been seen and can control what has been treated.

Penstemon is one of North America's largest endemic genera with over 280 described species. These species are distributed throughout most of North America from the Arctic northern latitudes to tropics of Central America. The genus has historically been divided into six subgenera, but has recently been reorganized into two subgenera following some recent phylogenetic studies. I made a comprehensive assessment of the Penstemon genus' geographic distribution utilizing herbaria databases by ecoregion to discuss the general ecologic adaptations of each historic subgenera. I also assessed the Penstemon genus' bee pollinator diversity utilizing online databases of bee specimen collections associated with Penstemon flowers. I investigated the efficacy of utilizing the plastid genomes (plastomes) of 29 species in the Lamiales order, including five newly sequenced Penstemon plastomes, for analyzing phylogenetic relationships and resolving problematic clades. I compared whole-plastome based phylogenies to phylogenies based on individual gene sequences (matK, ndhF, psaA, psbA, rbcL, rpoC2, and rps2) and concatenated sequences. I found that my whole-plastome based phylogeny had higher nodal support than all other phylogenies, which suggests that it provides greater accuracy in describing the hierarchal relationships among taxa as compared to other methods. I found that the genus Penstemon forms a monophyletic clade sister to, but separate from, the Old World taxa of the Plantaginaceae family included in our study. My whole-plastome based phylogeny also supports the rearrangement of the Scrophulariaceae family and improves resolution of major clades and genera of the Lamiales. I evaluated 16 accessions of P. cyaneus with 14 accessions of closely related Penstemon species in common garden in two distinct environments in Aberdeen, ID and Provo, UT during 2018 and 2019. I evaluated the accessions for key commercial seed production traits including survival, plant height, number of stems, and seed production. Both common gardens received supplemental irrigation during 2018, but I withheld irrigation during 2019. Plant survival in our Aberdeen, ID site was not significantly different between years, but survival was a significantly lower in 2019 than in 2018 at our Provo, UT site. The mean survival for P. cyaneus accessions ranged from 56% to 94%, and the mean seed production ranged from 91.2 kg/ha to 397.6 kg/ha. I recommend developing a commercial seed source derived from pooling germplasm of six accessions (PECY3-367, PECY3-371, PECY3-376, PECY3-443, PECY3-457, and PECY3-458). These accessions had mean survival rates of 82-94%, and seed production of 196.2-397.6 kg/ha.

Ecological opportunity—the availability of open niche space to an evolving lineage—has long been thought to modulate the extent of adaptive diversification. Many microbial evolution experiments have confirmed that ecological opportunity drives diversification of initially homogeneous populations into communities of ecologically distinct sub-lineages (ecotypes). Interactions among ecotypes are crucial for both community function and the maintenance of the ecological diversity produced during adaptive diversification, however the factors influencing the evolution of these interactions remain unexplored. We assessed the influence of ecological opportunity on this process by studying communities of the bacterium Pseudomonas aeruginosa that were evolved in either nutritionally complex (COM) or simple (SIM) environments. We measured the net ecological interactions in these communities by comparing the cellular productivity and competitive fitness of whole communities from each environment to that of their component isolates in both complex and simple media. On average, COM communities had both higher productivity and fitness than their component isolates in complex media, indicating that the components of these communities share net positive interactions. The same was not true of SIM communities, which did not differ in either measure from their component isolates. Follow-up experiments revealed that high fitness in two COM communities was driven by rare variants (frequency < 0.1%) that secrete compounds during growth which inhibit PA14, the strain used as a common competitor for fitness assays. Taken together, our results suggest that environments with high levels of ecological opportunity drive diversification into ecotypes that share net positive ecological interactions. The strong effect of diversity on productivity and fitness we found in newly diversified communities has a number of implications for evolutionary ecology as well as the treatment of P. aeruginosa infections.