Differential gains from Business Link support and advice:a treatment effects approach

The provision of advisory support to small firms is almost ubiquitous in OECD countries, although it is organised in different ways and is justified on slightly different grounds. In England publicly supported advisory services are provided through the Business Link (BL) network. Here, we consider two questions: what sort of companies receive advisory support from BL; and, what types of firms benefit most from that support? Our analysis is based on a telephone survey of 2000 firms, around half of which had received intensive assistance from BL between April and October 2003. Probit analysis suggests that the probability of receiving assistance was greater among younger businesses, those with larger numbers of directors in the firm, and those with more gender diversity among the firm's leadership team. Our business-growth models suggest that BL intensive assistance was having a positive effect on employment growth in 2003. BL had a positive but insignificant impact on sales growth over the period. Employment growth effects tend to be larger where firms have a management and organisational structure, which is more conducive to absorbing and making use of external advice. The analysis suggests that BL might increase its impact through targeting these larger, more export-orientated, businesses. Employment growth effects differ little, however, depending on either the ethnic or the gender diversity of the leadership team.

Predictive gene lists for breast cancer prognosis: a topographic visualisation study

Background: The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged 1. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists. Methods: We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether a-posteriori two prognosis groups are separable on the evidence of the gene lists. A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset. Results: The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results. Conclusion: The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers. However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses. We conclude that many of the patients involved in such medical studies are intrinsically unclassifiable on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.

Developing a complex intervention to reduce time to presentation with symptoms of lung cancer

Background - Lung cancer is the commonest cause of cancer in Scotland and is usually advanced at diagnosis. Median time between symptom onset and consultation is 14 weeks, so an intervention to prompt earlier presentation could support earlier diagnosis and enable curative treatment in more cases. Aim - To develop and optimise an intervention to reduce the time between onset and first consultation with symptoms that might indicate lung cancer. Design and setting - Iterative development of complex healthcare intervention according to the MRC Framework conducted in Northeast Scotland. Method - The study produced a complex intervention to promote early presentation of lung cancer symptoms. An expert multidisciplinary group developed the first draft of the intervention based on theory and existing evidence. This was refined following focus groups with health professionals and high-risk patients. Results - First draft intervention components included: information communicated persuasively, demonstrations of early consultation and its benefits, behaviour change techniques, and involvement of spouses/partners. Focus groups identified patient engagement, achieving behavioural change, and conflict at the patient–general practice interface as challenges and measures were incorporated to tackle these. Final intervention delivery included a detailed self-help manual and extended consultation with a trained research nurse at which specific action plans were devised. Conclusion -The study has developed an intervention that appeals to patients and health professionals and has theoretical potential for benefit. Now it requires evaluation.

Tissue Transglutaminase (TG2) is a potential therapeutic target in the treatment of chemoresistant breast cancer

Tissue transglutaminase (TG2) has been suggested to be a key player in the progression and metastasis of chemoresistant breast cancer. One of the foremost survival signalling pathways implicated in causing drug resistance in breast cancer is the constitutive activation of NFκB (Nuclear Factor -kappa B) induced by TG2. This study provides a mechanism by which TG2 constitutively activates NFκB which in turn confers chemoresistance to breast cancer cells against doxorubicin. Breast cancer cell lines with varying expression levels of TG2 as well as TG2 null breast cancer cells transfected with TG2 were used as the major cell models for this study. This study made use of cell permeable and impermeable TG2 inhibitors, specific TG2 and Rel A/ p65 targeting siRNA, TG2 functional blocking antibodies, IKK inhibitors and a specific targeting peptide against Rel A/p65 to investigate the pathway of activation involved in the constitutive activation of NFκB by TG2 leading to drug resistance. Crucial to the activation of Rel A/p65 and drug resistance in the breast cancer cells is the interaction between the complex of IκBα and Rel A/p65 with TG2 which results in the dimerization of Rel A/p65 and polymerization of IκBα. The association of TG2 with the IκBα-NFκB complex was determined to be independent of IKKα/β function. The polymerized IκBα is degraded in the cytoplasm by the μ-calpain pathway which allows the cross linked Rel A/ p65 dimers to translocate into the nucleus. Using R283 and ZDON (cell permeable TG2 activity inhibitors) and specific TG2 targeting siRNA, the Rel A/ p65 dimer formation could be inhibited. Co-immunoprecipitation studies confirmed that the phosphorylation of the Rel A/p65 dimers at the Ser536 residue by IKKε took place in the cell nucleus. Importantly, this study also investigated the transcriptional regulation of the TGM2 gene by the pSer536 Rel A/ p65 dimer and the importance of this TG2-NFκB feedback loop in conferring drug resistance to breast cancer cells. This data provides evidence that TG2 could be a key therapeutic target in the treatment of chemoresistant breast cancer.