Study of the treatment cases referred to the West End Child Guidance Clinic during the fiscal year of 1944

Thesis (M.S.)--Boston University, 1945. This item was digitized by the Internet Archive

Identifying Structural Variation in Haploid Microbial Genomes from Short-Read Resequencing Data Using Breseq

Mutations that alter chromosomal structure play critical roles in evolution and disease, including in the origin of new lifestyles and pathogenic traits in microbes. Large-scale rearrangements in genomes are often mediated by recombination events involving new or existing copies of mobile genetic elements, recently duplicated genes, or other repetitive sequences. Most current software programs for predicting structural variation from short-read DNA resequencing data are intended primarily for use on human genomes. They typically disregard information in reads mapping to repeat sequences, and significant post-processing and manual examination of their output is often required to rule out false-positive predictions and precisely describe mutational events. Results: We have implemented an algorithm for identifying structural variation from DNA resequencing data as part of the breseq computational pipeline for predicting mutations in haploid microbial genomes. Our method evaluates the support for new sequence junctions present in a clonal sample from split-read alignments to a reference genome, including matches to repeat sequences. Then, it uses a statistical model of read coverage evenness to accept or reject these predictions. Finally, breseq combines predictions of new junctions and deleted chromosomal regions to output biologically relevant descriptions of mutations and their effects on genes. We demonstrate the performance of breseq on simulated Escherichia coli genomes with deletions generating unique breakpoint sequences, new insertions of mobile genetic elements, and deletions mediated by mobile elements. Then, we reanalyze data from an E. coli K-12 mutation accumulation evolution experiment in which structural variation was not previously identified. Transposon insertions and large-scale chromosomal changes detected by breseq account for similar to 25% of spontaneous mutations in this strain. In all cases, we find that breseq is able to reliably predict structural variation with modest read-depth coverage of the reference genome (>40-fold). Conclusions: Using breseq to predict structural variation should be useful for studies of microbial epidemiology, experimental evolution, synthetic biology, and genetics when a reference genome for a closely related strain is available. In these cases, breseq can discover mutations that may be responsible for important or unintended changes in genomes that might otherwise go undetected.U.S. National Institutes of Health R00-GM087550U.S. National Science Foundation (NSF) DEB-0515729NSF BEACON Center for the Study of Evolution in Action DBI-0939454Cancer Prevention & Research Institute of Texas (CPRIT) RP130124University of Texas at Austin startup fundsUniversity of Texas at AustinCPRIT Cancer Research TraineeshipMolecular Bioscience

Structure of Extremely Nanosized and Confined In-O Species in Ordered Porous Materials

Perturbed-angular correlation, x-ray absorption, and small-angle x-ray scattering spectroscopies were suitably combined to elucidate the local structure of highly diluted and dispersed InOx species confined in porous of ZSM5 zeolite. These novel approach allow us to determined the structure of extremely nanosized In-O species exchanged inside the 10-atom-ring channel of the zeolite, and to quantify the amount of In2O3 crystallites deposited onto the external zeolite surface.Comment: 4 pages, 5 postscript figures, REVTEX4, published in Physical Review Letter

Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2009 Orton et al.BACKGROUND: The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway. RESULTS: We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors. CONCLUSION: Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems.This work was funded by the Department of Trade and Industry (DTI), under their Bioscience Beacon project programme. AG was funded by an industrial PhD studentship from Scottish Enterprise and Cyclacel

The statistical mechanics of complex signaling networks : nerve growth factor signaling

It is becoming increasingly appreciated that the signal transduction systems used by eukaryotic cells to achieve a variety of essential responses represent highly complex networks rather than simple linear pathways. While significant effort is being made to experimentally measure the rate constants for individual steps in these signaling networks, many of the parameters required to describe the behavior of these systems remain unknown, or at best, estimates. With these goals and caveats in mind, we use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. To establish the usefulness of our approach, we have applied our methods towards modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. Using our approach, we are able to extract predictions that are highly specific and accurate, thereby enabling us to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. We show that extracting biologically relevant predictions from complex signaling models appears to be possible even in the absence of measurements of all the individual rate constants. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems wherein particular ''soft'' combinations of parameters can be varied over wide ranges without impacting the final output and demonstrating that a few ''stiff'' parameter combinations center around the paramount regulatory steps of the network. We refer to this property -- which is distinct from robustness -- as ''sloppiness.''Comment: 24 pages, 10 EPS figures, 1 GIF (makes 5 multi-panel figs + caption for GIF), IOP style; supp. info/figs. included as brown_supp.pd

Structure and Magnetism of well-defined cobalt nanoparticles embedded in a niobium matrix

Our recent studies on Co-clusters embedded in various matrices reveal that the co-deposition technique (simultaneous deposition of two beams : one for the pre-formed clusters and one for the matrix atoms) is a powerful tool to prepare magnetic nanostructures with any couple of materials even though they are miscible. We study, both sharply related, structure and magnetism of the Co/Nb system. Because such a heterogeneous system needs to be described at different scales, we used microscopic and macroscopic techniques but also local selective absorption ones. We conclude that our clusters are 3 nm diameter f.c.c truncated octahedrons with a pure cobalt core and a solid solution between Co and Nb located at the interface which could be responsible for the magnetically inactive monolayers we found. The use of a very diluted Co/Nb film, further lithographed, would allow us to achieve a pattern of microsquid devices in view to study the magnetic dynamics of a single-Co cluster.Comment: 7 TeX pages, 9 Postscript figures, detailed heading adde

Cerebellar Ataxia With Anti-DNER Antibodies: Outcomes and Immunologic Features

BACKGROUND AND OBJECTIVES: There is no report on the long-term outcomes of ataxia with antibodies against Delta and Notch-like epidermal growth factor-related (DNER). We aimed to describe the clinical-immunologic features and long-term outcomes of patients with anti-DNER antibodies. METHODS: Patients tested positive for anti-DNER antibodies between 2000 and 2020 were identified retrospectively. In those with available samples, immunoglobulin G (IgG) subclass analysis, longitudinal cerebellum volumetry, human leukocyte antigen isotyping, and CSF proteomic analysis were performed. Rodent brain membrane fractionation and organotypic cerebellar slices were used to study DNER cell-surface expression and human IgG binding to the Purkinje cell surface. RESULTS: Twenty-eight patients were included (median age, 52 years, range 19-81): 23 of 28 (82.1%) were male and 23 of 28 (82.1%) had a hematologic malignancy. Most patients (27/28, 96.4%) had cerebellar ataxia; 16 of 28 (57.1%) had noncerebellar symptoms (cognitive impairment, neuropathy, and/or seizures), and 27 of 28 (96.4%) became moderately to severely disabled. Half of the patients (50%) improved, and 32.1% (9/28) had no or slight disability at the last visit (median, 26 months; range, 3-238). Good outcome significantly associated with younger age, milder clinical presentations, and less decrease of cerebellar gray matter volumes at follow-up. No human leukocyte antigen association was identified. Inflammation-related proteins were overexpressed in the patients' CSF. In the rodent brain, DNER was enriched in plasma membrane fractions. Patients' anti-DNER antibodies were predominantly IgG1/3 and bound live Purkinje cells in vitro. DISCUSSION: DNER ataxia is a treatable condition in which nearly a third of patients have a favorable outcome. DNER antibodies bind to the surface of Purkinje cells and are therefore potentially pathogenic, supporting the use of B-cell-targeting treatments

Chronic T cell receptor stimulation unmasks NK receptor signaling in peripheral T cell lymphomas via epigenetic reprogramming.

Peripheral T cell lymphomas (PTCLs) represent a significant unmet medical need with dismal clinical outcomes. The T cell receptor (TCR) is emerging as a key driver of T lymphocyte transformation. However, the role of chronic TCR activation in lymphomagenesis and in lymphoma cell survival is still poorly understood. Using a mouse model, we report that chronic TCR stimulation drove T cell lymphomagenesis, whereas TCR signaling did not contribute to PTCL survival. The combination of kinome, transcriptome, and epigenome analyses of mouse PTCLs revealed a NK cell-like reprogramming of PTCL cells with expression of NK receptors (NKRs) and downstream signaling molecules such as Tyrobp and SYK. Activating NKRs were functional in PTCLs and dependent on SYK activity. In vivo blockade of NKR signaling prolonged mouse survival, demonstrating the addiction of PTCLs to NKRs and downstream SYK/mTOR activity for their survival. We studied a large collection of human primary samples and identified several PTCLs recapitulating the phenotype described in this model by their expression of SYK and the NKR, suggesting a similar mechanism of lymphomagenesis and establishing a rationale for clinical studies targeting such molecules