Thesis (Ph. D.)--University of Wisconsin--Madison, 1964. / Typescript. Vita. Abstracted in Dissertation abstracts, v. 25 (1964) no. 6, p. 3199. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin, 1964. / Typescript. Vita. Bibliography: leaves 132-136.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliography.

Bemisia tabaci (Genn.) is the vector of cassava mosaic geminiviruses (CMGs), which are the main production constraint to cassava, both in Uganda and elsewhere in Africa. A severe form of cassava mosaic disease (CMD) was responsible for the devastation of cassava in Uganda beginning in the late 1980s. In subsequent years the severe CMD epidemic spread throughout Uganda, and to neighbouring countries, causing devastating effects to cassava production, and its geographical range continues to expand with the pandemic. To further understand the virus-vector dynamics involved in the spread of CMD in the post epidemic zone in Uganda, we investigated the current distribution of B. tabaci genotypes in selected cassava-growing regions. Additionally, the relationship between the vector genotypes and distribution of CMGs in the post-epidemic zone was examined also. CMD-affected cassava leaves were collected from 3 to 5 month-old cassava plants, and B. tabaci adults and fourth instar nymphs were collected from cassava and twenty-two other plant species occurring adjacent to the sampled cassava fields. The mitochondrial cytochrome oxidase I (mtCOI) sequence was used to establish the genotype of B. tabaci adults and nymphs associated with the sampled plant species. African cassava mosaic virus (ACMV) and East African cassava mosaic virus-Uganda 2 (EACMV-UG2) were confirmed to be present in the post-epidemic zone in Uganda, as reported previously. As expected, EACMV-UG2 predominated. However, unlike previous observations in which EACMV-UG2 was consistently associated with the severe disease phenotype, in this study EACMV-UG2 occurred almost equally in the severely and mildly diseased plants. Phylogenetic analyses of Ugandan B. tabaci genotypes (mtCOI) revealed that their closest relatives were other Old World genotypes, as might be expected. Two previously reported B. tabaci genotype clusters, Uganda 1 (Ug1) and Uganda 2 (Ug2), at ~8% nt divergence, were confirmed to occur on cassava in the post-epidemic zone. However, Ug1 occurred more frequently (83%) than Ug2 (17%), and no definite association was established of a particular vector genotype with cassava plants exhibiting the severe disease phenotype, in contrast to the B. tabaci genotype distribution and association with the CMGs reported there at the height of the spread of the severe CMD epidemic. Based on the presence of B. tabaci fourth instar nymphs, the Ug1 genotypes colonized five additional non-cassava plant species: Manihot glaziovii, Jatropha gossypifolia, Euphorbia heterophylla, Aspilia africana and Abelmoschus esculentus, suggesting that in Uganda the Ug1 genotypes are not restricted to cassava. However, no Ug2 genotypes were detected on the non-cassava plant species sampled. This study revealed also the presence in Uganda of five distinct previously unrecorded B. tabaci genotype clusters, Uganda 3 (Ug3), Uganda 4 (Ug4), Uganda 5 (Ug5), Uganda 6 (Ug6) and Uganda 7 (Ug7), and a sweetpotato colonizing genotype cluster, designated Uganda 8 (Ug8), among the collective Ugandan B. tabaci populations. Ug3 was the only exemplar representing one cluster, which was unlike any previously described genotype in Uganda or elsewhere, and diverged at 8%, 10% and 17% from Ug1, Ug2 and Ug8, respectively. The Ug3 genotypes colonized a single species, Ocimum gratissimum. Ug4, Ug5, Ug6 and Ug7 formed four closely related sub-clusters (93-97% nt identity), and diverged from one another by 1-7%, and by 15-18% from Ug1, Ug2, Ug3 and Ug8, respectively. The Ug4 genotypes had as their closest relatives (at 97-99% nt identity) previously reported B. tabaci from okra in the Ivory Coast, whereas, the Ug5 and Ug6 genotypes shared 95-99% and 99% nt identity, respectively, with their closest relatives from the Mediterranean-North Africa- Middle East (MED-NAFR-ME) region, which also includes the well studied B and Q biotypes. The Ug7 genotypes were closely related (at 98-99% nt identity) to B. tabaci from Reunion Island in the Indian Ocean. The Ug4, Ug5, Ug6 and Ug7 genotypes were identified on 54%, 8%, 8%, and 31% of the sampled plants species, respectively. Ug4 were most polyphagous, followed by Ug7 and Ug6. However, none of the new five genotypes (Ug3-Ug7) was found associated with, or colonizing, xx cassava or sweetpotato plants in this study. Squash plants colonized by the Ug6 and Ug7 genotypes, both members of the B biotype/B-like cluster, developed the silvering phenotype, while those colonized by the Ug4 genotypes (most closely related to a non-B like genotype from okra in the Ivory Coast) did not. In addition to colonizing sweetpotato, the Ug8 genotypes also colonized Lycopersicon esculentum and L nepetifolia.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references. Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2001. / Typescript. Vita. Includes bibliographical references. Also available on the Internet.

Objectives: The purpose of this study was to create a checklist that could be used in the training of a college of pharmacy faculty so that there were no gaps in their information literacy; to implement the checklist; and to measure the users response to the intervention. Methods: A checklist was developed that covered the information resources of the library and the information skills needed by pharmacy faculty. All faculty were required to meet with a librarian during the academic year and cover everything on the checklist in one or multiple sessions. Faculty were surveyed as to their responses to the training. Results: Librarians learned the value of using a checklist. Better relationships were developed with the college of pharmacy faculty. Weaknesses in the libraries training of pharmacy faculty were discovered and remedied. Conclusions: Checklists are used in medicine to obtain quality. Checklists can be used in medical librarianship for the same purpose.