Barriers to women in the UK construction industry

Purpose – This paper aims to identify the main barriers that lead to the under-representation of women in the UK construction industry. The study, funded by ConstructionSkills, seeks to explore the issues that women face and investigate the potential positive impact that continuous professional development (CPD) may have upon improving the retention and career progression of women. Design/methodology/approach – The study uses an open-ended grounded theory (GT) approach, including 231 semi-structured questionnaires and nine focus groups with women from a range of professional occupations. All the findings were analysed using keyword analysis to identify the top two barriers that women face, alongside a series of cross-cutting key themes and issues. Findings – The findings reveal that male-dominated organisational cultures and inflexible working practices are the main barriers to women in the UK construction industry, irrespective of job role or profession. This paper concludes by arguing for a sea-change in the expansion of CPD opportunities for women in managerial, confidence and communication based skills, with accompanying networking and support systems to facilitate the retention and advancement of women in the industry sector. Research limitations/implications – Due to the research approach, the data are not generalisable. Therefore, researchers are advised to research and test the findings with a larger group. Researchers are also recommended to investigate the impact of expanded CPD opportunities for both men and women. Originality/value – The paper puts forward a business case for the advancement of specific CPD training for women, to facilitate the expansion of equality and diversity in the workforce in the UK construction industry

Identification and validation of oncologic miRNA biomarkers for Luminal A-like breast cancer

Introduction: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. Methods: Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n=54) and controls (n=56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n=10 Luminal A-like; n=10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n=44 Luminal A; n=46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated. Results: Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis ( miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652 ). The biomarker potential of 4 miRNAs ( miR-29a, miR-181a , miR-223 and miR-652 ) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p=0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs ( miR-29a, miR-181a and miR-652 ) could reliably differentiate between cancers and controls with an AUC of 0.80. Conclusion: This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype- specific breast tumor detection

Integrating complex genomic datasets and tumour cell sensitivity profiles to address a 'simple' question: which patients should get this drug?

It is becoming increasingly apparent that cancer drug therapies can only reach their full potential through appropriate patient selection. Matching drugs and cancer patients has proven to be a complex challenge, due in large part to the substantial molecular heterogeneity inherent to human cancers. This is not only a major hurdle to the improvement of the use of current treatments but also for the development of novel therapies and the ability to steer them to the relevant clinical indications. In this commentary we discuss recent studies from Kuo et al., published this month in BMC Medicine, in which they used a panel of cancer cell lines as a model for capturing patient heterogeneity at the genomic and proteomic level in order to identify potential biomarkers for predicting the clinical activity of a novel candidate chemotherapeutic across a patient population. The findings highlight the ability of a 'systems approach' to develop a better understanding of the properties of novel candidate therapeutics and to guide clinical testing and application

Influenza Virus Infection of the Murine Uterus: A New Model for Antiviral Immunity in the Female Reproductive Tract

Secretory IgA (S-IgA) mediates local immunity to influenza virus in the murine upper respiratory tract and may play an important role in local immunity to various microorganisms in the female reproductive tract as well. Although the presence of IgA in cervicovaginal or uterine secretions has been correlated with immunity to a number of pathogens, there has been no direct demonstration of the mediation of uterine antiviral immunity by S-IgA. Influenza virus, although not a normal pathogen of the reproductive tract, was used to develop a model for the investigation of mucosal immunity in the uterus. PR8 (H1N1) influenza virus injected into the ovarian bursa of BALB/c mice grew well, with peak titers between days 3 and 5. Intravenous injection of polymeric IgA anti-influenza virus monoclonal antibody before or 30 min after viral challenge protected mice against viral infection. We believe this work to be the first direct demonstration of S-IgA-mediated antiviral uterine immunity. It provides a model for further investigation of immunity in the female reproductive tract.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63226/1/vim.2006.19.613.pd

Closing in on Asymmetric Dark Matter I: Model independent limits for interactions with quarks

It is argued that experimental constraints on theories of asymmetric dark matter (ADM) almost certainly require that the DM be part of a richer hidden sector of interacting states of comparable mass or lighter. A general requisite of models of ADM is that the vast majority of the symmetric component of the DM number density must be removed in order to explain the observed relationship $\Omega_B\sim\Omega_{DM}$ via the DM asymmetry. Demanding the efficient annihilation of the symmetric component leads to a tension with experimental limits if the annihilation is directly to Standard Model (SM) degrees of freedom. A comprehensive effective operator analysis of the model independent constraints on ADM from direct detection experiments and LHC monojet searches is presented. Notably, the limits obtained essentially exclude models of ADM with mass 1GeV$\lesssim m_{DM} \lesssim$ 100GeV annihilating to SM quarks via heavy mediator states. This motivates the study of portal interactions between the dark and SM sectors mediated by light states. Resonances and threshold effects involving the new light states are shown to be important for determining the exclusion limits.Comment: 18+6 pages, 18 figures. v2: version accepted for publicatio

Accounting for Redundancy when Integrating Gene Interaction Databases

During the last years gene interaction networks are increasingly being used for the assessment and interpretation of biological measurements. Knowledge of the interaction partners of an unknown protein allows scientists to understand the complex relationships between genetic products, helps to reveal unknown biological functions and pathways, and get a more detailed picture of an organism's complexity. Being able to measure all protein interactions under all relevant conditions is virtually impossible. Hence, computational methods integrating different datasets for predicting gene interactions are needed. However, when integrating different sources one has to account for the fact that some parts of the information may be redundant, which may lead to an overestimation of the true likelihood of an interaction. Our method integrates information derived from three different databases (Bioverse, HiMAP and STRING) for predicting human gene interactions. A Bayesian approach was implemented in order to integrate the different data sources on a common quantitative scale. An important assumption of the Bayesian integration is independence of the input data (features). Our study shows that the conditional dependency cannot be ignored when combining gene interaction databases that rely on partially overlapping input data. In addition, we show how the correlation structure between the databases can be detected and we propose a linear model to correct for this bias. Benchmarking the results against two independent reference data sets shows that the integrated model outperforms the individual datasets. Our method provides an intuitive strategy for weighting the different features while accounting for their conditional dependencies

The implications of the United Nations Paris Agreement on climate change for globally significant biodiversity areas

Climate change is already affecting species and their distributions. Distributional range changes have occurred and are projected to intensify for many widespread plants and animals, creating associated risks to many ecosystems. Here, we estimate the climate change-related risks to the species in globally significant biodiversity conservation areas over a range of climate scenarios, assessing their value as climate refugia. In particular, we quantify the aggregated benefit of countries’ emission reduction pledges (Intended Nationally Determined Contributions and Nationally Determined Contributions under the Paris Agreement), and also of further constraining global warming to 2 °C above pre-industrial levels, against an unmitigated scenario of 4.5 °C warming. We also quantify the contribution that can be made by using smart spatial conservation planning to facilitate some levels of autonomous (i.e. natural) adaptation to climate change by dispersal. We find that without mitigation, on average 33% of each conservation area can act as climate refugium (or 18% if species are unable to disperse), whereas if warming is constrained to 2 °C, the average area of climate refuges doubles to 67% of each conservation area (or, without dispersal, more than doubles to 56% of each area). If the country pledges are fulfilled, an intermediate estimate of 47–52% (or 31–38%, without dispersal) is obtained. We conclude that the Nationally Determined Contributions alone have important but limited benefits for biodiversity conservation, with larger benefits accruing if warming is constrained to 2 °C. Greater benefits would result if warming was constrained to well below 2 °C as set out in the Paris Agreement

Health-seeking behaviour of human brucellosis cases in rural Tanzania

<p>Abstract</p> <p>Background</p> <p>Brucellosis is known to cause debilitating conditions if not promptly treated. In some rural areas of Tanzania however, practitioners give evidence of seeing brucellosis cases with symptoms of long duration. The purpose of this study was to establish health-seeking behaviour of human brucellosis cases in rural Tanzania and explore the most feasible ways to improve it.</p> <p>Methods</p> <p>This was designed as a longitudinal study. Socio-demographic, clinical and laboratory data were collected from patients who reported to selected hospitals in rural northern Tanzania between June 2002 and April 2003. All patients with conditions suspicious of brucellosis on the basis of preliminary clinical examination and history were enrolled into the study as brucellosis suspects. Blood samples were taken and tested for brucellosis using the Rose-Bengal Plate Test (RBPT) and other agglutination tests available at the health facilities and the competitive ELISA (c-ELISA) test at the Veterinary Laboratory Agencies (VLA) in the UK. All suspects who tested positive with the c-ELISA test were regarded as brucellosis cases. A follow-up of 49 cases was made to collect data on health-seeking behaviour of human brucellosis cases.</p> <p>Results</p> <p>The majority of cases 87.7% gave a history of going to hospital as the first point of care, 10.2% purchased drugs from a nearby drug shop before going to hospital and 2% went to a local traditional healer first. Brucellosis cases delayed going to hospital with a median delay time of 90 days, and with 20% of the cases presenting to hospitals more than a year after the onset of symptoms. Distance to the hospital, keeping animals and knowledge of brucellosis were significantly associated with patient delay to present to hospital.</p> <p>Conclusion</p> <p>More efforts need to be put on improving the accessibility of health facilities to the rural poor people who succumb to most of the diseases including zoonoses. Health education on brucellosis in Tanzania should also stress the importance of early presentation to hospitals for prompt treatment.</p