Erving Goffman in Toronto, Chicago and London

Dr. Elizabeth Bott Spillius wrote this memoir at the request of Dr. Ruth Horowitz and approved posting the present version in the Goffman Archives

Probing a Complex Dissociation Energy Surface with Experimental and Theoretical Methods

Dendrimers are hyperbranched polymers with a tree-like structure that can be tuned for size, shape, and functionality. Dendrimers have exhibited numerous possibilities in chemical and biochemical processes as their use in host-guest systems and controlled gene and drug delivery vehicles. Distinct properties of dendrimers, such as well-defined architecture and high ratio of functional moieties to molecular volume, make these polymers substantially useful for the development of nanomaterials and medicines. It has recently been demonstrated that polypropylene-imine (PPI) dendrimers have specific physical properties that are well suited for many applications. More specifically, the nitrile-terminated dendrimer creates a unique environment that is both aprotic and polar. Increasing interest in the design and use of these dendrimer systems has created a need for new methods of physical and chemical characterization. The current techniques used for characterization tend to be slow and sample limited, even for monodisperse samples. Polydisperse samples are even more analytically challenging. This thesis used a rapid and precise analytical framework for the characterization of dendrimers by systematically probing the electrospray ionization mass spectrometry (ESI-MS) speciation and the gas-phase collision-induced dissociation (CID) fragmentation patterns for early generation (PPI) dendrimers. Two isotopically labeled dendrimer species were employed for unambiguous assignment of complex structures and mechanisms. Hypothesized mechanisms were verified, while one anomaly presented for the β-labeled dendrimer. Also, the fragmentation patterns of certain alkali and alkaline earth metal-dendrimer complexes were investigated. These complexes of +1 and +2 charges exhibited similar losses, including radicals

A Case Study: Autocatalytic Behavior and its Consideration for a Chemical Process with General application to Handling, Shipping, and Reactive Relief Design

PresentationAutocatalysis is a generally well understood phenomenon. However, since autocatalytic molecules do not have a fixed energy release rate for a given temperature, like nth order reactions, additional considerations are required to ensure safe shipping, handling and relief device sizing. Also, unlike nth order reactions, autocatalytic reactions have an induction time and it is associated with reaching a critical concentration of a catalytic species. Once the induction time is exhausted the reaction accelerates even under isothermal conditions (i.e. dT/dt = f (T,Ccat). Often a thermo- kinetic model is required for adequate hazard evaluation. During model development a first order reaction scheme is often used as a starting point. Such an approach typically leads to an unrealistically high apparent activation energy to get a reasonable fit to the data. Since time impacts the reaction rate, induction times need to be determined to build an accurate kinetic model. Once induction times are determined as a function of temperature, adequate layers of protection and operating discipline can be determined for safe handling. This paper describes: 1) Identification and confirmation of autocatalytic behavior, 2) Induction time model development, and 3) Application to storage, shipping, and reactive relief design. For reactive relief vent sizing, consideration is given not only to credible failure scenarios that may result in relief device activation, but also recovery from contained unplanned events

The Journal of BSN Honors Research, Volume 7, Issue 1, Summer 2014

Papers submitted to the University of Kansas School of Nursing in partial fulfillment of the requirements for the Nursing Honors Program.The University of Kansas School of Nursing Bachelor of Science Nursing Honors Progra

Defining Natural History: Assessment of the Ability of College Students to Aid in Characterizing Clinical Progression of Niemann-Pick Disease, Type C

Niemann-Pick Disease, type C (NPC) is a fatal, neurodegenerative, lysosomal storage disorder. It is a rare disease with broad phenotypic spectrum and variable age of onset. These issues make it difficult to develop a universally accepted clinical outcome measure to assess urgently needed therapies. To this end, clinical investigators have defined emerging, disease severity scales. The average time from initial symptom to diagnosis is approximately 4 years. Further, some patients may not travel to specialized clinical centers even after diagnosis. We were therefore interested in investigating whether appropriately trained, community-based assessment of patient records could assist in defining disease progression using clinical severity scores. In this study we evolved a secure, step wise process to show that pre-existing medical records may be correctly assessed by non-clinical practitioners trained to quantify disease progression. Sixty-four undergraduate students at the University of Notre Dame were expertly trained in clinical disease assessment and recognition of major and minor symptoms of NPC. Seven clinical records, randomly selected from a total of thirty seven used to establish a leading clinical severity scale, were correctly assessed to show expected characteristics of linear disease progression. Student assessment of two new records donated by NPC families to our study also revealed linear progression of disease, but both showed accelerated disease progression, relative to the current severity scale, especially at the later stages. Together, these data suggest that college students may be trained in assessment of patient records, and thus provide insight into the natural history of a disease

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio