Coevolution In Bacterial‐Plasmid Populations

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137199/1/evo04336.pd

Mycobacterium w - a promising immunotherapeutic intervention for diseases

Immunomodulating agents interact with the immune system and alter the outcome of specific immune processes. As our understanding of the immune system continues to evolve, there is a growing effort to identify agents with immunomodulating applications to use therapeutically to treat various diseases. Mycobacterium w (Mw), a heat-killed mycobacterium, is an atypical mycobacterial species that possesses strong immunomodulatory properties. Mw was initially evaluated as an immune-therapeutic against leprosy, but since then Mw has generated a lot of interest and been studied for therapeutic applications across a host of diseases, such as pulmonary tuberculosis, tuberculous pericarditis, sepsis, lung cancer, and more. This article summarizes a large body of work published in the past five decades, describing various aspects of Mw and its potential for further therapeutic development

Evolution in bacterial-plasmid populations of Escherichia coli.

This thesis describes and analyzes evolutionary changes occurring in bacterial-plasmid populations. The reproductive fitness of plasmid-containing strains isolated from two independent long-term chemostat populations grown in a glucose-limited environment increased dramatically over a period of approximately 800 generations. Genetic changes associated with the increase in reproductive fitness were shown to be associated with both the bacterial chromosome and the plasmid. In addition, some of the genetic changes in the bacterial chromosome and plasmid interact and thus may be considered to be co-evolutionary. The structural basis for some of these observed adaptive genetic changes in the evolved plasmid-containing strains were analyzed. Specifically in two independent long term populations, DNA derived from plasmid, and including the transposable element, TN3, was shown to be integrated between 12\sp\prime and 14\sp\prime in the bacterial chromosome. The integration of the transposable element resulted in an increase in the reproductive fitness of the bacterial chromosome. In one long-term population, a spontaneous deletion of about 2.2 Kb in the plasmid, encompassing the tetracycline resistance gene was identified. The change associated with the deletion in the plasmid resulted in a net increase in fitness. That is, the deleterious effect of the plasmid with the deletion, was smaller than that of the plasmid without the deletion. The role of adaptive genetic changes in the microbial genomes is discussed.Ph.D.Biological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/105314/1/9023603.pdfDescription of 9023603.pdf : Restricted to UM users only

Plasma Analysis of Celiprolol by HPTLC: A Useful Technique for Pharmacokinetic Studies

Abstract A rapid and sensitive high performance, thin-layer chromatographic (HPTLC) method has been developed for the measurement of celiprolol in human plasma and its use in pharmacokinetic studies has been evaluated. Detection and quantitation were performed without using an internal standard. A simple extraction procedure was followed for extracting celiprolol from plasma and a known amount of the extract was spotted on precoated silica gel 60 F254 plates using a Camag Linomat IV autosampler. Celiprolol was quantitated using a Camag TLC Scanner 3. The average recovery of authentic analytes (20 to 200 ng/mL) added to plasma was 72.06 ± 2.8% and the lowest amount of celiprolol that could be detected was 10 ng/mL. The method provides a direct estimate of the amount of celiprolol present in plasma. Pharmacokinetic parameters of 2 marketed preparations have also been determined after oral administration to 12 healthy human volunteers.</jats:p

SunPy

The community-developed, free and open-source solar data analysis environment for Python

SunPy

The community-developed, free and open-source solar data analysis environment for Python