Expression of androgen receptor and prostate-specific antigen in male breast carcinoma

BACKGROUND: The androgen-regulated proteins prostate-specific antigen (PSA) and prostate-specific acid phosphatase (PSAP) are present in high concentrations in normal prostate and prostatic cancer and are considered to be tissue-specific to prostate. These markers are commonly used to diagnose metastatic prostate carcinoma at various sites including the male breast. However, expression of these two proteins in tumors arising in tissues regulated by androgens such as male breast carcinoma has not been thoroughly evaluated. METHODS: In this study we analyzed the expression of PSA, PSAP and androgen receptor (AR) by immunohistochemistry in 26 cases of male breast carcinomas and correlated these with the expression of other prognostic markers. RESULTS: AR, PSA and PSAP expression was observed in 81%, 23% and 0% of carcinomas, respectively. Combined expression of AR and PSA was observed in only four tumors. CONCLUSION: Although the biological significance of PSA expression in male breast carcinomas is not clear, caution should be exercised when it is used as a diagnostic marker of metastatic prostate carcinoma

Investigating the potential for students to contribute to climate data rescue: Introducing the Climate Data Rescue Africa project (CliDaR‐Africa)

The majority of available climate data in global digital archives consist of data only from the 1940s or 1950s onwards, and many of these series have gaps and/or are available for only a subset of the variables which were actually observed. However, there exist billions of historical weather observations from the 1700s, 1800s, and early 1900s that are still in hard- copy form and are at risk of being lost forever due to deterioration. An assessment of changes in climate extremes in several IPCC regions was not possible in IPCC AR6 WGI owing, in many cases, to the lack of available data. One such region is Africa, where the climate impact research and the ability to predict climate change impacts are hindered by the paucity of access to consistent good- quality historical observational data. The aim of this innovative project was to use classroom- based participatory learning to help transcribe some of the many meteorological observations from Africa that are thus far unavailable to researchers. This project transcribed quickly and ef-fectively station series by enrolling the help of second- year undergraduate stu-dents at Maynooth University in Ireland. The newly digitized African data will increase the temporal and spatial coverage of data in this important data- sparse region. Students gained new skills while helping the global scientific community unearth new insight into past African climate. The project managed to transcribe 79 months of data at Andapa in Madagascar and 56 months of data for Macenta in Guinea. The digitized data will be openly and freely shared with the scientific and wider community via the Pangaea data repository, the C3S Climate Data Store, and the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) data centre in the US. The pro-ject model has the potential for a broader roll- out to other educational contexts and there is no shortage of data to be rescued. This paper provides details of the project, and all supporting information such as project guidelines and templates to enable other organizations to instigate similar programs

No Adverse Effect of Genetically Modified Antifungal Wheat on Decomposition Dynamics and the Soil Fauna Community – A Field Study

The cultivation of genetically modified (GM) plants has raised several environmental concerns. One of these concerns regards non-target soil fauna organisms, which play an important role in the decomposition of organic matter and hence are largely exposed to GM plant residues. Soil fauna may be directly affected by transgene products or indirectly by pleiotropic effects such as a modified plant metabolism. Thus, ecosystem services and functioning might be affected negatively. In a litterbag experiment in the field we analysed the decomposition process and the soil fauna community involved. Therefore, we used four experimental GM wheat varieties, two with a race-specific antifungal resistance against powdery mildew (Pm3b) and two with an unspecific antifungal resistance based on the expression of chitinase and glucanase. We compared them with two non-GM isolines and six conventional cereal varieties. To elucidate the mechanisms that cause differences in plant decomposition, structural plant components (i.e. C∶N ratio, lignin, cellulose, hemicellulose) were examined and soil properties, temperature and precipitation were monitored. The most frequent taxa extracted from decaying plant material were mites (Cryptostigmata, Gamasina and Uropodina), springtails (Isotomidae), annelids (Enchytraeidae) and Diptera (Cecidomyiidae larvae). Despite a single significant transgenic/month interaction for Cecidomyiidae larvae, which is probably random, we detected no impact of the GM wheat on the soil fauna community. However, soil fauna differences among conventional cereal varieties were more pronounced than between GM and non-GM wheat. While leaf residue decomposition in GM and non-GM wheat was similar, differences among conventional cereals were evident. Furthermore, sampling date and location were found to greatly influence soil fauna community and decomposition processes. The results give no indication of ecologically relevant adverse effects of antifungal GM wheat on the composition and the activity of the soil fauna community

Angiogenesis and hypoxia in lymph node metastases is predicted by the angiogenesis and hypoxia in the primary tumour in patients with breast cancer

Hypoxia and angiogenesis are important factors in breast cancer progression. Little is known of hypoxia and angiogenesis in lymph node metastases of breast cancer. The aim of this study was to quantify hypoxia, by hypoxia-induced marker expression levels, and angiogenesis, by endothelial cell proliferation, comparing primary breast tumours and axillary lymph node metastases. Tissue sections of the primary tumour and a lymph node metastasis of 60 patients with breast cancer were immunohistochemically stained for the hypoxia-markers carbonic anhydrase 9 (CA9), hypoxia-inducible factor-1α (Hif-1α) and DEC-1 and for CD34/Ki-67. Endothelial cell proliferation fraction (ECP%) and tumour cell proliferation fraction (TCP%) were assessed. On haematoxylin–eosin stain, the growth pattern and the presence of a fibrotic focus were assessed. Hypoxia-marker expression, ECP% and TCP% in primary tumours and in lymph node metastases were correlated to each other and to clinico-pathological variables. Median ECP% and TCP% in primary tumours and lymph node metastases were comparable (primary tumours: ECP%=4.02, TCP%=19.54; lymph node metastases: ECP%=5.47, TCP%=21.26). ECP% correlated with TCP% (primary tumours: r=0.63, P<0.001; lymph node metastases: r=0.76, P<0.001). CA9 and Hif-1α expression were correlated (primary tumours P=0.005; lymph node metastases P<0.001). In primary tumours, CA9 and Hif-1α expression were correlated with DEC-1 expression (P=0.05), presence of a fibrotic focus (P<0.007) and mixed/expansive growth pattern (P<0.001). Primary tumours and lymph node metastases with CA9 or Hif-1α expression had a higher ECP% and TCP% (P<0.003); in primary tumours, mixed/expansive growth pattern and fibrotic focus were characterised by higher ECP% (P=0.03). Furthermore, between primary tumours and lymph node metastases a correlation was found for ECP%, TCP%, CA9 and Hif-1α expression (ECP% r=0.51, P<0.001; TCP r=0.77, P<0.001; CA9 and Hif-1α P<0.001). Our data demonstrate that the growth of breast cancer lymph node metastases is angiogenesis dependent and that angiogenesis and hypoxia in the primary tumour predict angiogenesis and hypoxia in the lymph node metastases. Together with previous findings in breast cancer liver metastases, which grow in 96% of cases angiogenesis independently, these data suggest that both the intrinsic growth characteristics and angiogenic potential of breast cancer cells and the site-specific tumour microenvironment determine angiogenesis and hypoxia in breast cancer

Prognostic molecular markers in early breast cancer

A multitude of molecules involved in breast cancer biology have been studied as potential prognostic markers. In the present review we discuss the role of established molecular markers, as well as potential applications of emerging new technologies. Those molecules used routinely to make treatment decisions in patients with early-stage breast cancer include markers of proliferation (e.g. Ki-67), hormone receptors, and the human epidermal growth factor receptor 2. Tumor markers shown to have prognostic value but not used routinely include cyclin D(1 )and cyclin E, urokinase-like plasminogen activator/plasminogen activator inhibitor, and cathepsin D. The level of evidence for other molecular markers is lower, in part because most studies were retrospective and not adequately powered, making their findings unsuitable for choosing treatments for individual patients. Gene microarrays have been successfuly used to classify breast cancers into subtypes with specific gene expression profiles and to evaluate prognosis. RT-PCR has also been used to evaluate expression of multiple genes in archival tissue. Proteomics technologies are in development

Perspectives in visual imaging for marine biology and ecology: from acquisition to understanding

Durden J, Schoening T, Althaus F, et al. Perspectives in Visual Imaging for Marine Biology and Ecology: From Acquisition to Understanding. In: Hughes RN, Hughes DJ, Smith IP, Dale AC, eds. Oceanography and Marine Biology: An Annual Review. 54. Boca Raton: CRC Press; 2016: 1-72

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

Ebola: translational science considerations

We are currently in the midst of the most aggressive and fulminating outbreak of Ebola-related disease, commonly referred to as “Ebola”, ever recorded. In less than a year, the Ebola virus (EBOV, Zaire ebolavirus species) has infected over 10,000 people, indiscriminately of gender or age, with a fatality rate of about 50%. Whereas at its onset this Ebola outbreak was limited to three countries in West Africa (Guinea, where it was first reported in late March 2014, Liberia, where it has been most rampant in its capital city, Monrovia and other metropolitan cities, and Sierra Leone), cases were later reported in Nigeria, Mali and Senegal, as well as in Western Europe (i.e., Madrid, Spain) and the US (i.e., Dallas, Texas; New York City) by late October 2014. World and US health agencies declared that the current Ebola virus disease (EVD) outbreak has a strong likelihood of growing exponentially across the world before an effective vaccine, treatment or cure can be developed, tested, validated and distributed widely. In the meantime, the spread of the disease may rapidly evolve from an epidemics to a full-blown pandemic. The scientific and healthcare communities actively research and define an emerging kaleidoscope of knowledge about critical translational research parameters, including the virology of EBOV, the molecular biomarkers of the pathological manifestations of EVD, putative central nervous system involvement in EVD, and the cellular immune surveillance to EBOV, patient-centered anthropological and societal parameters of EVD, as well as translational effectiveness about novel putative patient-targeted vaccine and pharmaceutical interventions, which hold strong promise, if not hope, to curb this and future Ebola outbreaks. This work reviews and discusses the principal known facts about EBOV and EVD, and certain among the most interesting ongoing or future avenues of research in the field, including vaccination programs for the wild animal vectors of the virus and the disease from global translational science perspective

Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data

Objectives: Network meta-analysis (NMA) methods extend the standard pair-wise framework to allow simultaneous comparison of multiple interventions in a single statistical model. Despite published work on NMA mainly focussing on the synthesis of aggregate data (AD), methods have been developed that allow the use of individual patient-level data (IPD) specifically when outcomes are dichotomous or continuous. This paper focuses on the synthesis of IPD and AD time to event data, motivated by a real data example looking at the effectiveness of high compression treatments on the healing of venous leg ulcers. Methods: This paper introduces a novel NMA modelling approach that allows IPD (time to event with censoring) and AD (event count for a given follow-up time) to be synthesised jointly by assuming an underlying, common, distribution of time to healing. Alternative model assumptions were tested within the motivating example. Model fit and adequacy measures were used to compare and select models. Results: Due to the availability of IPD in our example we were able to use a Weibull distribution to describe time to healing; otherwise, we would have been limited to specifying a uniparametric distribution. Absolute effectiveness estimates were more sensitive than relative effectiveness estimates to a range of alternative specifications for the model. Conclusions: The synthesis of time to event data considering IPD provides modelling flexibility, and can be particularly important when absolute effectiveness estimates, and not just relative effect estimates, are of interest