Attention and associative learning in humans: An integrative review

This article presents a comprehensive survey of research concerning interactions between associative learning and attention in humans. Four main findings are described. First, attention is biased toward stimuli that predict their consequences reliably (learned predictiveness). This finding is consistent with the approach taken by Mackintosh (1975) in his attentional model of associative learning in nonhuman animals. Second, the strength of this attentional bias is modulated by the value of the outcome (learned value). That is, predictors of high-value outcomes receive especially high levels of attention. Third, the related but opposing idea that uncertainty may result in increased attention to stimuli (Pearce & Hall, 1980), receives less support. This suggests that hybrid models of associative learning, incorporating the mechanisms of both the Mackintosh and Pearce-Hall theories, may not be required to explain data from human participants. Rather, a simpler model, in which attention to stimuli is determined by how strongly they are associated with significant outcomes, goes a long way to account for the data on human attentional learning. The last main finding, and an exciting area for future research and theorizing, is that learned predictiveness and learned value modulate both deliberate attentional focus, and more automatic attentional capture. The automatic influence of learning on attention does not appear to fit the traditional view of attention as being either goal-directed or stimulus-driven. Rather, it suggests a new kind of “derived” attention

Chemotherapy in patients with unresected pancreatic cancer in Australia: A population-based study of uptake and survival

1 Aim Palliative chemotherapy improves symptom control and prolongs survival in patients with unresectable pancreatic cancer, but there is a paucity of data describing its use and effectiveness in everyday practice. We explored patterns of chemotherapy use in patients with unresected pancreatic cancer in Australia and the impact of use on survival. 2 Methods We reviewed the medical records of residents of New South Wales or Queensland, Australia, diagnosed with unresectable pancreatic adenocarcinoma between July 2009 and June 2011. Associations between receipt of chemotherapy and sociodemographic, clinical and health service factors were evaluated using logistic regression. We used Cox proportional hazards models to analyze associations between chemotherapy use and survival. 3 Results Data were collected for 1173 eligible patients. Chemotherapy was received by 44% (n = 184/414) of patients with localized pancreatic cancer and 53% (n = 406/759) of patients with metastases. Chemotherapy receipt depended on clinical factors, such as performance status and comorbidity burden, and nonclinical factors, such as age, place of residence, multidisciplinary team review and the type of specialist first encountered. Consultation with an oncologist mitigated most of the sociodemographic and service‐related disparities in chemotherapy use. The receipt of chemotherapy was associated with prolonged survival in patients with inoperable pancreatic cancer, including after adjusting for common prognostic factors. 4 Conclusions These findings highlight the need to establish referral pathways to ensure that all patients have the opportunity to discuss treatment options with a medical oncologist. This is particularly relevant for health care systems covering areas with a geographically dispersed population

Translating microarray data for diagnostic testing in childhood leukaemia

BACKGROUND: Recent findings from microarray studies have raised the prospect of a standardized diagnostic gene expression platform to enhance accurate diagnosis and risk stratification in paediatric acute lymphoblastic leukaemia (ALL). However, the robustness as well as the format for such a diagnostic test remains to be determined. As a step towards clinical application of these findings, we have systematically analyzed a published ALL microarray data set using Robust Multi-array Analysis (RMA) and Random Forest (RF). METHODS: We examined published microarray data from 104 ALL patients specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent patient cohort. RESULTS: We achieved very high overall ALL subgroup prediction accuracies of about 98%, and were able to verify the robustness of these genes in an independent panel of 68 specimens obtained from a different institution and processed in a different laboratory. Our study established that the selection of discriminating genes is strongly dependent on the analysis method. This may have profound implications for clinical use, particularly when the classifier is reduced to a small set of genes. We have demonstrated that as few as 26 genes yield accurate class prediction and importantly, almost 70% of these genes have not been previously identified as essential for class distinction of the six ALL subgroups. CONCLUSION: Our finding supports the feasibility of qRT-PCR technology for standardized diagnostic testing in paediatric ALL and should, in conjunction with conventional cytogenetics lead to a more accurate classification of the disease. In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort and with microarray experiments being performed by a different research team

Estrogen Receptor Beta rs1271572 Polymorphism and Invasive Ovarian Carcinoma Risk: Pooled Analysis within the Ovarian Cancer Association Consortium

The association of ovarian carcinoma risk with the polymorphism rs1271572 in the estrogen receptor beta (ESR2) gene was examined in 4946 women with primary invasive ovarian carcinoma and 6582 controls in a pooled analysis of ten case-control studies within the Ovarian Cancer Association Consortium (OCAC). All participants were non-Hispanic white women. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression adjusted for site and age. Women with the TT genotype were at increased risk of ovarian carcinoma compared to carriers of the G allele (OR = 1.10; 95%; CI: 1.01-1.21; p = 0.04); the OR was 1.09 (CI: 0.99-1.20; p = 0.07) after excluding data from the center (Hawaii) that nominated this SNP for OCAC genotyping A stronger association of rs1271572 TT versus GT/GG with risk was observed among women aged <= 50 years versus older women (OR = 1.35; CI: 1.12-1.62; p = 0.002; p for interaction = 0.02) that remained statistically significant after excluding Hawaii data (OR = 1.34; CI: 1.11-1.61; p = 0.009). No heterogeneity of the association was observed by study, menopausal status, gravidity, parity, use of contraceptive or menopausal hormones, tumor histological type, or stage at diagnosis. This pooled analysis suggests that rs1271572 might influence the risk of ovarian cancer, in particular among younger women

Association between DNA Damage Response and Repair Genes and Risk of Invasive Serous Ovarian Cancer

BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results

Small and medium-sized enterprise policy: Designed to fail?

Significant doubts persist over the effectiveness of government policy to increase the numbers or performance of small and medium-sized enterprises in the UK economy. We analyse UK political manifestoes from 1964-2015 to examine the development of SME policy in political discourse. We do this by analysing how the broadly-defined category of ‘SME’ has been characterised in the manifestoes and assess these characterisations in relation to the empirical evidence base. We highlight three consistent themes in UK political manifestoes during 1964-2015 where SMEs have been characterised as having the potential for growth, struggling to access finance and being over-burdened by regulation. We argue that homogenising the broad range of businesses represented by the SME category and characterising them in these terms misrepresents them, undermining policies developed in relation to this mischaracterisation

A qualitative analysis of the enforcement of the regulation of nutrition and health claims made for foods and its implications for health

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. In common with local government organisations across the world, local authorities in the UK have responsibility for promoting health. A key part of this function is the frontline enforcement activities of officers responsible for compliance with health and nutrition claims. This study identifies attitudes, values and practices of enforcers: namely trading standards and environmental health officers, when faced with the problem of non-compliance with the Regulation. Semi-structured interviews with frontline enforcers from local authority regulatory services to investigate challenges with the enforcement of Regulation (EC) 1924/2006. Twenty participants were interviewed; sixteen were based in North West England and two in the North and two in the South of England. The participants were selected for their specialist knowledge and experience of enforcement of nutrition and health claims. Regulation (EC) No. 1924/2006 on nutrition and health claims presents particular challenges for enforcers seeking to apply an optimal strategy to flawed regulatory design. As with other regulations, when faced with non-compliance, enforcers, specifically trading standards and environmental health officers have a wide discretion to determine their response: ranging from the deterrent or accommodative styles of enforcement. The participants reported using advice rather than action and by doing so confronting their bifurcating identity of prosecutor and advisor. Enforcers used advice as a regulatory tool in enforcing the law relating to nutrition and health claims

Marine Biodiversity in the Australian Region

The entire Australian marine jurisdictional area, including offshore and sub-Antarctic islands, is considered in this paper. Most records, however, come from the Exclusive Economic Zone (EEZ) around the continent of Australia itself. The counts of species have been obtained from four primary databases (the Australian Faunal Directory, Codes for Australian Aquatic Biota, Online Zoological Collections of Australian Museums, and the Australian node of the Ocean Biogeographic Information System), but even these are an underestimate of described species. In addition, some partially completed databases for particular taxonomic groups, and specialized databases (for introduced and threatened species) have been used. Experts also provided estimates of the number of known species not yet in the major databases. For only some groups could we obtain an (expert opinion) estimate of undiscovered species. The databases provide patchy information about endemism, levels of threat, and introductions. We conclude that there are about 33,000 marine species (mainly animals) in the major databases, of which 130 are introduced, 58 listed as threatened and an unknown percentage endemic. An estimated 17,000 more named species are either known from the Australian EEZ but not in the present databases, or potentially occur there. It is crudely estimated that there may be as many as 250,000 species (known and yet to be discovered) in the Australian EEZ. For 17 higher taxa, there is sufficient detail for subdivision by Large Marine Domains, for comparison with other National and Regional Implementation Committees of the Census of Marine Life. Taxonomic expertise in Australia is unevenly distributed across taxa, and declining. Comments are given briefly on biodiversity management measures in Australia, including but not limited to marine protected areas

A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis