Fundamental Limits on Wavelength, Efficiency and Yield of the Charge Separation Triad

In an attempt to optimize a high yield, high efficiency artificial photosynthetic protein we have discovered unique energy and spatial architecture limits which apply to all light-activated photosynthetic systems. We have generated an analytical solution for the time behavior of the core three cofactor charge separation element in photosynthesis, the photosynthetic cofactor triad, and explored the functional consequences of its makeup including its architecture, the reduction potentials of its components, and the absorption energy of the light absorbing primary-donor cofactor. Our primary findings are two: First, that a high efficiency, high yield triad will have an absorption frequency more than twice the reorganization energy of the first electron transfer, and second, that the relative distance of the acceptor and the donor from the primary-donor plays an important role in determining the yields, with the highest efficiency, highest yield architecture having the light absorbing cofactor closest to the acceptor. Surprisingly, despite the increased complexity found in natural solar energy conversion proteins, we find that the construction of this central triad in natural systems matches these predictions. Our analysis thus not only suggests explanations for some aspects of the makeup of natural photosynthetic systems, it also provides specific design criteria necessary to create high efficiency, high yield artificial protein-based triads

Stillbirth differences according to regions of origin: an analysis of the German perinatal database, 2004-2007

Reeske A, Kutschmann M, Razum O, Spallek J. Stillbirth differences according to regions of origin: an analysis of the German perinatal database, 2004-2007. BMC Pregnancy and Childbirth. 2011;11(1): 63.Background: Stillbirth is a sensitive indicator for access to, and quality of health care and social services in a society. If a particular population group e. g. migrants experiences higher rates of stillbirth, this might be an indication of social deprivation or barriers to health care. This study examines differences in risk of stillbirth for women of different regions of origin compared to women from Germany in order to identify high risk groups/target groups for prevention strategies. Methods: We used the BQS dataset routinely compiled to examine perinatal outcomes in Germany nationwide. Participation of hospitals and completeness of data has been about 98% in recent years. Data on all live births and stillbirths were obtained for the period 2004 to 2007 (N = 2,670,048). We calculated crude and stratified mortality rates as well as corresponding relative mortality risks. Results: A significantly elevated stillbirth rate was found for women from the Middle East and North Africa (incl. Turkey) (RR 1.34, CI 1.22-1.55). The risk was slightly attenuated for low SES. An elevated risk was also found for women from Asia (RR 1.18, CI 1.02-1.65) and from Mediterranean countries (RR 1.14, CI 0.93-1.28). No considerable differences either in use and timing of antenatal care or preterm birth and low birthweight were observed between migrant and non-migrant women. After stratification for light for gestational age, the relative risk of stillbirth for women from the Middle East/North Africa increased to 1.63 (95% CI 1.25-2.13). When adjusted for preterm births with low birthweight, women from Eastern Europe and the Middle East/North Africa experienced a 26% (43%) higher risk compared with women from Germany. Conclusions: We found differences in risk of stillbirth among women from Middle East/North Africa, especially in association with low SES and low birthweight for gestational age. Our findings suggest a need for developing and evaluating socially and culturally sensitive health promotion and prevention programmes for this group. The findings should also stimulate discussion about the quality and appropriateness of antenatal and perinatal care of pregnant women and newborns with migrant backgrounds

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice

Can environmental or occupational hazards alter the sex ratio at birth? A systematic review

More than 100 studies have examined whether environmental or occupational exposures of parents affect the sex ratio of their offspring at birth. For this review, we searched Medline and Web of Science using the terms ‘sex ratio at birth’ and ‘sex ratio and exposure’ for all dates, and reviewed bibliographies of relevant studies to find additional articles. This review focuses on exposures that have been the subject of at least four studies including polychlorinated biphenyls (PCBs), dioxins, pesticides, lead and other metals, radiation, boron, and g-forces. For paternal exposures, only dioxins and PCBs were consistently associated with sex ratios higher or lower than the expected 1.06. Dioxins were associated with a decreased proportion of male births, whereas PCBs were associated with an increased proportion of male births. There was limited evidence for a decrease in the proportion of male births after paternal exposure to DBCP, lead, methylmercury, non-ionizing radiation, ionizing radiation treatment for childhood cancer, boron, or g-forces. Few studies have found higher or lower sex ratios associated with maternal exposures. Studies in humans and animals have found a reduction in the number of male births associated with lower male fertility, but the mechanism by which environmental hazards might change the sex ratio has not yet been established

Consensus guidelines for the use and interpretation of angiogenesis assays

The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference

Framework for strategic wind farm site prioritisation based on modelled wolf reproduction habitat in Croatia

In order to meet carbon reduction targets, many nations are greatly expanding their wind power capacity. However, wind farm infrastructure potentially harms wildlife, and we must therefore find ways to balance clean energy demands with the need to protect wildlife. Wide-ranging carnivores live at low density and are particularly susceptible to disturbance from infrastructure development, so are a particular concern in this respect. We focused on Croatia, which holds an important population of wolves and is currently planning to construct many new wind farms. Specifically, we sought to identify an optimal subset of planned wind farms that would meet energy targets while minimising potential impact on wolves. A suitability model for wolf breeding habitat was carried out using Maxent, based on six environmental variables and 31 reproduction site locations collected between 1997 and 2015. Wind farms were prioritised using Marxan to find the optimal trade-off between energy capacity and overlap with critical wolf reproduction habitat. The habitat suitability model predictions were consistent with the current knowledge: probability of wolf breeding site presence increased with distance to settlements, distance to farmland and distance to roads and decreased with distance to forest. Spatial optimisation showed that it would be possible to meet current energy targets with only 31% of currently proposed wind farms, selected in a way that reduces the potential ecological cost (overall predicted wolf breeding site presence within wind farm sites) by 91%. This is a highly efficient outcome, demonstrating the value of this approach for prioritising infrastructure development based on its potential impact on wide-ranging wildlife species