478 research outputs found

    The SWHEL model for studying B cell responses in tolerance and immunity

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    Classical immunoglobulin transgenic (Ig-Tg) mouse models such as the MD4 anti-hen egg lysozyme (-HEL) Ig-Tg line have been used extensively to study B cell responses in tolerance and immunity. This thesis describes a new generation of gene-targeted mice (designated SWHEL mice) whereby the VH10 Ig variable gene encoding the HyHEL-10 specificity of the original anti-HEL Ig-Tg mouse was targeted to the Ig heavy chain locus. B cells in the SWHEL mouse are therefore capable of undergoing class switch recombination (CSR) and somatic hypermutation (SHM), representing a major advance on the original MD4 mouse model. SWHEL mice were found to not only contain a large population of HEL-specific (HEL+) B cells but also a significant population of non-HEL-binding (HEL-) B cells generated by VH gene replacement. HEL+ SWHEL B cells were found to belong to the B2 lineage and displayed high levels of surface IgM. Nevertheless, they matured normally and colonised the primary B cell follicle and marginal zone (MZ) of the spleen. The SWHEL model thus provided an opportunity to re-examine some of the original observations made in the MD4 system and also to extend these observations, particularly with regard to the regulation of CSR by self-reactive B cells. As expected, analysis of SWHEL B cells exposed to high avidity membrane-bound HEL revealed that they underwent clonal deletion in the bone marrow (BM). More interestingly, analysis of HEL+ B cells exposed to low avidity soluble HEL revealed that they were able to emigrate from the BM to the spleen as anergic B cells. However, unlike anergic MD4 B cells, anergic SWHEL B cells were reduced in frequency, displayed an immature B cell phenotype, were excluded from the follicle and had a reduced lifespan. Direct measurement of B cell antigen receptor (BCR) occupancy by HEL and the frequency of HEL- competitor B cells was combined with mixed BM irradiation chimeras to demonstrate unequivocally that the difference in phenotype and fate of HEL+ B cells in the two systems was due solely to competition from HEL- B cells. In addition, the SWHEL model of B cell self-tolerance was used to show that while self-reactive B cells were hypo-responsive to BCR stimulation, BCR-independent signals delivered via anti-CD40 plus IL-4 or lipopolysaccharide could trigger them to undergo CSR and secretion of potentially pathogenic isotype-switched autoantibodies. Finally, the SWHEL model was used to study the responses of adoptively transferred follicular (Fo) and MZ B cells to in vivo activation with HEL conjugated to sheep red blood cells (HEL-SRBC). These studies revealed that both HEL+ MZ and Fo B cells were capable of mounting a robust T cell-dependent IgG1 antibody response to HEL-SRBC. However, HEL+ MZ B cells did not efficiently localise to the T cell-B cell border following antigen engagement and preferentially migrated to the bridging channels and red pulp. In contrast, HEL+ Fo B cells rapidly localised to the T cell-B cell border and subsequently colonised numerous germinal centres. As a result, the rate and pattern of SHM by HEL+ Fo and MZ B cells was shown to be distinct, with preferential targeting of mutations to the second complementarity-determining region in the former and to the second framework region in the latter. Together these data indicate illustrate the value of the SWHEL model and its potential to greatly advance the current understanding of B cell responses in tolerance and immunity

    Sales forecasting in fashion retail chain: A case study in Vietnam

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    Sales forecasting is the key to the success of a supply chain, especially in the fashion industry. Vietnam is a major apparel supplier for international brands and has a dynamic, fast-growing market. The lack of complete forecasting systems in such a market motivates our development of sales forecast procedures featuring quantifiable results and practical implementation. Both statistical and machine learning methods were tested using actual data. We found that Random Forest consistently yields the lowest error metrics, followed closely by XGBoost. Meanwhile, clustering did not provide conclusive evidence of improved accuracy. As the study’s data sources come entirely from one company, these procedures are applicable for other firms to deploy their data without external mining sources.nhhma
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