Labour supply and skills demands in fashion retailing

If, as Adam Smith once famously suggested, Britain was a nation of shopkeepers then it is now a nation of shopworkers. Retail is now a significant part of the UK economy, accounting for £256 billion in sales and one-third of all consumer spending (Skillsmart, 2007). It is the largest private sector employer in the UK, employing 3m workers, or 1 in 10 of the working population. For future job creation in the UK economy retail is also similarly prominent and the sector is expected to create a further 250,000 jobs to 2014 (Skillsmart, 2007). The centrality of retail to economic success and job creation is apparent in other advanced economies. For example, within the US, retail sales is the occupation with the largest projected job growth in the period 2004-2014 (Gatta et al., 2009) and in Australia retail accounts for 1 in 6 workers (Buchanan et al., 2003). Within the UK these workers are employed in approximately 290,000 businesses, encompassing large and small organizations and also a number of sub-sectors. This variance suggests that retail should not be regarded as homogenous in its labour demands. Hart et al. (2007) note how skill requirements and the types of workers employed may differ across the sector. This chapter further opens up this point, providing an analysis of the labour supply and skills demands for the sub-sectors of clothing, footwear and leather goods, which are described by Skillsmart (2007: 48) as being 'significant categories in UK retailing'

Allergic Rhinitis and its Associated Co-Morbidities at Bugando Medical Centre in Northwestern Tanzania; A Prospective Review of 190 Cases.

Allergic rhinitis is one of the commonest atopic diseases which contribute to significant morbidity world wide while its epidemiology in Tanzania remains sparse. There was paucity of information regarding allergic rhinitis in our setting; therefore it was important to conduct this study to describe our experience on allergic rhinitis, associated co-morbidities and treatment outcome in patients attending Bugando Medical Centre. This was descriptive cross-sectional study involving all patients with a clinical diagnosis of allergic rhinitis at Bugando Medical Centre over a three-month period between June 2011 and August 2011. Data was collected using a pre-tested coded questionnaire and analyzed using SPSS statistical computer software version 17.0. A total of 190 patients were studied giving the prevalence of allergic rhinitis 14.7%. The median age of the patients was 8.5 years. The male to female ratio was 1:1. Adenoid hypertrophy, tonsillitis, hypertrophy of inferior turbinate, nasal polyps, otitis media and sinusitis were the most common co-morbidities affecting 92.6% of cases and were the major reason for attending hospital services. Sleep disturbance was common in children with adenoids hypertrophy (χ2 = 28.691, P = 0.000). Allergic conjunctivitis was found in 51.9%. The most common identified triggers were dust, strong perfume odors and cold weather (P < 0.05). Strong perfume odors affect female than males (χ2 = 4.583, P = 0.032). In this study family history of allergic rhinitis was not a significant risk factor (P =0.423). The majority of patients (68.8%) were treated surgically for allergic rhinitis co morbidities. Post operative complication and mortality rates were 2.9% and 1.6% respectively. The overall median duration of hospital stay of in-patients was 3 days (2 - 28 days). Most patients (98.4%) had satisfactory results at discharge. The study shows that allergic rhinitis is common in our settings representing 14.7% of all otorhinolaryngology and commonly affecting children and adolescent. Sufferers seek medical services due to co-morbidities of which combination of surgical and medical treatment was needed. High index of suspicions in diagnosing allergic rhinitis and early treatment is recommended

Gene expression model (in)validation by Fourier analysis

The determination of the right model structure describing a gene regulation network and the identification of its parameters are major goals in systems biology. The task is often hampered by the lack of relevant experimental data with sufficiently low noise level, but the subset of genes whose concentration levels exhibit an oscillatory behavior in time can readily be analyzed on the basis of their Fourier spectrum, known to turn complex signals into few relatively noise-free parameters. Such genes therefore offer opportunities of understanding gene regulation quantitatively.Journal ArticleResearch Support, Non-U.S. Gov'tValidation StudiesSCOPUS: ar.jinfo:eu-repo/semantics/publishe

Genome-Wide Expression Analysis of a Spinal Muscular Atrophy Model: Towards Discovery of New Drug Targets

Spinal Muscular Atrophy is a recessive genetic disease and affects lower motor neurones and muscle tissue. A single gene is disrupted in SMA: SMN1 activity is abolished but a second copy of the gene (SMN2) provides limited activity. While the SMN protein has been shown to function in the assembly of RNA-protein complexes, it is unclear how the overall reduction in SMN activity specifically results in the neuromuscular phenotypes. Similar to humans, reduced smn activity in the fly causes earliest phenotypes in neuromuscular tissues. To uncover the effects of reduced SMN activity, we have studied gene expression in control and diseased fly tissues using whole genome micro-arrays. A number of gene expression changes are recovered and independently validated. Identified genes show trends in their predicted function: several are consistent with the function of SMN, in addition some uncover novel pathways. This and subsequent genetic analysis in the fly indicates some of the identified genes could be taken for further studies as potential drug targets for SMA and other neuromuscular disorders

Metagenes Associated with Survival in Non-Small Cell Lung Cancer

NSCLC (non-small cell lung cancer) comprises about 80% of all lung cancer cases worldwide. Surgery is most effective treatment for patients with early-stage disease. However, 30%–55% of these patients develop recurrence within 5 years. Therefore, markers that can be used to accurately classify early-stage NSCLC patients into different prognostic groups may be helpful in selecting patients who should receive specific therapies

Analysis of gene expression data from non-small celllung carcinoma cell lines reveals distinct sub-classesfrom those identified at the phenotype level

Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC) can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that subclasses were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC

CLU blocks HDACI-mediated killing of neuroblastoma

Clusterin is a ubiquitously expressed glycoprotein with multiple binding partners including IL-6, Ku70, and Bax. Clusterin blocks apoptosis by binding to activated Bax and sequestering it in the cytoplasm, thereby preventing Bax from entering mitochondria, releasing cytochrome c, and triggering apoptosis. Because increased clusterin expression correlates with aggressive behavior in tumors, clusterin inhibition might be beneficial in cancer treatment. Our recent findings indicated that, in neuroblastoma cells, cytoplasmic Bax also binds to Ku70; when Ku70 is acetylated, Bax is released and can initiate cell death. Therefore, increasing Ku70 acetylation, such as by using histone deacetylase inhibitors, may be therapeutically useful in promoting cell death in neuroblastoma tumors. Since clusterin, Bax, and Ku70 form a complex, it seemed likely that clusterin would mediate its anti-apoptotic effects by inhibiting Ku70 acetylation and blocking Bax release. Our results, however, demonstrate that while clusterin level does indeed determine the sensitivity of neuroblastoma cells to histone deacetylase inhibitor-induced cell death, it does so without affecting histone deacetylase-inhibitor-induced Ku70 acetylation. Our results suggest that in neuroblastoma, clusterin exerts its anti-apoptotic effects downstream of Ku70 acetylation, likely by directly blocking Bax activation

Gene expression profiling may improve diagnosis in patients with carcinoma of unknown primary

Carcinomas of unknown primary (CUP) represent between 3 and 10% of malignancies. Treatment with nonspecific chemotherapy is commonly unhelpful and the median survival is between 3 and 6 months. Gene expression microarray (GEM) analysis has demonstrated that molecular signatures can aid in tumour classification and propose foster primaries. In this study, we demonstrate the clinical utility of a diagnostic gene expression profiling tool and discuss its potential implications for patient management strategies. Paraffin tumour samples from 21 cases of ‘true' CUP patients in whom standard investigation had failed to determine a primary site of malignancy were investigated using diagnostic gene profiling. The results were reviewed in the context of histology and clinical history. Classification of tumour origin using the GEM method confirmed the clinicians' suspicion in 16 out of 21 cases. There was a clinical/GEM inconsistency in 4 out of 21 patients and a pathological/GEM inconsistency in 1 patient. The improved diagnoses by the GEM method would have influenced the management in 12 out of 21 cases. Genomic profiling and cancer classification tools represent a promising analytical approach to assist with the management of CUP patients. We propose that GEM diagnosis be considered when the primary clinical algorithm has failed to provide a diagnosis

Robust computational reconstitution – a new method for the comparative analysis of gene expression in tissues and isolated cell fractions

BACKGROUND: Biological tissues consist of various cell types that differentially contribute to physiological and pathophysiological processes. Determining and analyzing cell type-specific gene expression under diverse conditions is therefore a central aim of biomedical research. The present study compares gene expression profiles in whole tissues and isolated cell fractions purified from these tissues in patients with rheumatoid arthritis and osteoarthritis. RESULTS: The expression profiles of the whole tissues were compared to computationally reconstituted expression profiles that combine the expression profiles of the isolated cell fractions (macrophages, fibroblasts, and non-adherent cells) according to their relative mRNA proportions in the tissue. The mRNA proportions were determined by trimmed robust regression using only the most robustly-expressed genes (1/3 to 1/2 of all measured genes), i.e. those showing the most similar expression in tissue and isolated cell fractions. The relative mRNA proportions were determined using several different chip evaluation methods, among which the MAS 5.0 signal algorithm appeared to be most robust. The computed mRNA proportions agreed well with the cell proportions determined by immunohistochemistry except for a minor number of outliers. Genes that were either regulated (i.e. differentially-expressed in tissue and isolated cell fractions) or robustly-expressed in all patients were identified using different test statistics. CONCLUSION: Robust Computational Reconstitution uses an intermediate number of robustly-expressed genes to estimate the relative mRNA proportions. This avoids both the exclusive dependence on the robust expression of individual, highly cell type-specific marker genes and the bias towards an equal distribution upon inclusion of all genes for computation