Immunosignaturing shows promise as a general approach to diagnosis. It has been shown to detect immunological signs of infection early during the course of disease and to distinguish Alzheimer’s disease from healthy controls. Here we test whether immunosignatures correspond to clinical classifications of disease using samples from people with brain tumors. Blood samples from patients undergoing craniotomies for therapeutically naïve brain tumors with diagnoses of astrocytoma (23 samples), Glioblastoma multiforme (22 samples), mixed oligodendroglioma/astrocytoma (16 samples), oligodendroglioma (18 samples), and 34 otherwise healthy controls were tested by immunosignature. Because samples were taken prior to adjuvant therapy, they are unlikely to be perturbed by non-cancer related affects. The immunosignaturing platform distinguished not only brain cancer from controls, but also pathologically important features about the tumor including type, grade, and the presence or absence of O⁶-methyl-guanine-DNA methyltransferase methylation promoter (MGMT), an important biomarker that predicts response to temozolomide in Glioblastoma multiformae patients.

Background: Malignant brain tumors affect people of all ages and are the second leading cause of cancer deaths in children. While current treatments are effective and improve survival, there remains a substantial need for more efficacious therapeutic modalities. The ketogenic diet (KD) - a high-fat, low-carbohydrate treatment for medically refractory epilepsy - has been suggested as an alternative strategy to inhibit tumor growth by altering intrinsic metabolism, especially by inducing glycopenia.

Methods: Here, we examined the effects of an experimental KD on a mouse model of glioma, and compared patterns of gene expression in tumors vs. normal brain from animals fed either a KD or a standard diet.

Results: Animals received intracranial injections of bioluminescent GL261-luc cells and tumor growth was followed in vivo. KD treatment significantly reduced the rate of tumor growth and prolonged survival. Further, the KD reduced reactive oxygen species (ROS) production in tumor cells. Gene expression profiling demonstrated that the KD induces an overall reversion to expression patterns seen in non-tumor specimens. Notably, genes involved in modulating ROS levels and oxidative stress were altered, including those encoding cyclooxygenase 2, glutathione peroxidases 3 and 7, and periredoxin 4.

Conclusions: Our data demonstrate that the KD improves survivability in our mouse model of glioma, and suggests that the mechanisms accounting for this protective effect likely involve complex alterations in cellular metabolism beyond simply a reduction in glucose.

In traditional public good experiments participants receive an endowment from the experimenter that can be invested in a public good or kept in a private account. In this paper we present an experimental environment where participants can invest time during five days to contribute to a public good. Participants can make contributions to a linear public good by logging into a web application and performing virtual actions. We compared four treatments, with different group sizes and information of (relative) performance of other groups. We find that information feedback about performance of other groups has a small positive effect if we control for various attributes of the groups. Moreover, we find a significant effect of the contributions of others in the group in the previous day on the number of points earned in the current day. Our results confirm that people participate more when participants in their group participate more, and are influenced by information about the relative performance of other groups.

Atmospheric radiocarbon (¹⁴C) represents an important observational constraint on emissions of fossil-fuel derived carbon into the atmosphere due to the absence of ¹⁴C in fossil fuel reservoirs. The high sensitivity and precision that accelerator mass spectrometry (AMS) affords in atmospheric ¹⁴C analysis has greatly increased the potential for using such measurements to evaluate bottom-up emissions inventories of fossil fuel CO₂(CO₂ff), as well as those for other co-emitted species. Here we use observations of ¹⁴CO₂ and a series of primary hydrocarbons and combustion tracers from discrete air samples collected between June 2009 and September 2010 at the National Oceanic and Atmospheric Administration Boulder Atmospheric Observatory (BAO; Lat: 40.050° N, Lon: 105.004° W) to derive emission ratios of each species with respect to CO₂ff. The BAO tower is situated at the boundary of the Denver metropolitan area to the south and a large industrial and agricultural region to the north and east, making it an ideal location to study the contrasting mix of emissions from the activities in each region. The species considered in this analysis are carbon monoxide (CO), methane (CH₄), acetylene (C₂H₂), benzene (C₆H₆), and C₃–C₅ alkanes. We estimate emissions for a subset of these species by using the Vulcan high resolution CO2ff emission data product as a reference. We find that CO is overestimated in the 2008 National Emissions Inventory (NEI08) by a factor of ~2. A close evaluation of the inventory suggests that the ratio of CO emitted per unit fuel burned from on-road gasoline vehicles is likely over-estimated by a factor of 2.5. Using a wind-directional analysis of the data, we find enhanced concentrations of CH₄, relative to CO₂ff, in air influenced by emissions to the north and east of the BAO tower when compared to air influenced by emissions in the Denver metro region to the south. Along with enhanced CH₄, the strongest enhancements of the C₃–C₅ alkanes are also found in the north and east wind sector, suggesting that both the alkane and CH₄ enhancements are sourced from oil and gas fields located to the northeast, though it was not possible to rule out the contribution of non oil and gas CH₄ sources.

Urban environments are the primary contributors to global anthropogenic carbon emissions. Because much of the growth in CO₂ emissions will originate from cities, there is a need to develop, assess, and improve measurement and modeling strategies for quantifying and monitoring greenhouse gas emissions from large urban centers. In this study the uncertainties in an aircraft-based mass balance approach for quantifying carbon dioxide and methane emissions from an urban environment, focusing on Indianapolis, IN, USA, are described. The relatively level terrain of Indianapolis facilitated the application of mean wind fields in the mass balance approach. We investigate the uncertainties in our aircraft-based mass balance approach by (1) assessing the sensitivity of the measured flux to important measurement and analysis parameters including wind speed, background CO₂ and CH₄, boundary layer depth, and interpolation technique, and (2) determining the flux at two or more downwind distances from a point or area source (with relatively large source strengths such as solid waste facilities and a power generating station) in rapid succession, assuming that the emission flux is constant. When we quantify the precision in the approach by comparing the estimated emissions derived from measurements at two or more downwind distances from an area or point source, we find that the minimum and maximum repeatability were 12 and 52%, with an average of 31%. We suggest that improvements in the experimental design can be achieved by careful determination of the background concentration, monitoring the evolution of the boundary layer through the measurement period, and increasing the number of downwind horizontal transect measurements at multiple altitudes within the boundary layer.

Astronauts are exposed to a unique combination of stressors during spaceflight, which leads to alterations in their physiology and potentially increases their susceptibility to disease, including infectious diseases. To evaluate the potential impact of the spaceflight environment on the regulation of molecular pathways mediating cellular stress responses, we performed a first-of-its-kind pilot study to assess spaceflight-related gene-expression changes in the whole blood of astronauts. Using an array comprised of 234 well-characterized stress-response genes, we profiled transcriptomic changes in six astronauts (four men and two women) from blood preserved before and immediately following the spaceflight. Differentially regulated transcripts included those important for DNA repair, oxidative stress, and protein folding/degradation, including HSP90AB1, HSP27, GPX1, XRCC1, BAG-1, HHR23A, FAP48, and C-FOS. No gender-specific differences or relationship to number of missions flown was observed. This study provides a first assessment of transcriptomic changes occurring in the whole blood of astronauts in response to spaceflight.

Large urban emissions of greenhouse gases result in large atmospheric enhancements relative to background that are easily measured. Using CO₂ mole fractions and Δ¹⁴C and δ¹³C values of CO₂ in the Los Angeles megacity observed in inland Pasadena (2006–2013) and coastal Palos Verdes peninsula (autumn 2009–2013), we have determined time series for CO₂ contributions from fossil fuel combustion (C_ff) for both sites and broken those down into contributions from petroleum and/or gasoline and natural gas burning for Pasadena. We find a 10 % reduction in Pasadena C_ff during the Great Recession of 2008–2010, which is consistent with the bottom-up inventory determined by the California Air Resources Board. The isotopic variations and total atmospheric CO₂ from our observations are used to infer seasonality of natural gas and petroleum combustion. The trend of CO₂ contributions to the atmosphere from natural gas combustion is out of phase with the seasonal cycle of total natural gas combustion seasonal patterns in bottom-up inventories but is consistent with the seasonality of natural gas usage by the area's electricity generating power plants. For petroleum, the inferred seasonality of CO₂ contributions from burning petroleum is delayed by several months relative to usage indicated by statewide gasoline taxes. Using the high-resolution Hestia-LA data product to compare C_ff from parts of the basin sampled by winds at different times of year, we find that variations in observed fossil fuel CO₂ reflect seasonal variations in wind direction. The seasonality of the local CO₂ excess from fossil fuel combustion along the coast, on Palos Verdes peninsula, is higher in autumn and winter than spring and summer, almost completely out of phase with that from Pasadena, also because of the annual variations of winds in the region. Variations in fossil fuel CO₂ signals are consistent with sampling the bottom-up Hestia-LA fossil CO₂ emissions product for sub-city source regions in the LA megacity domain when wind directions are considered.

Social roles are thought to play an important role in determining the capacity for collective action in a community regarding the use of shared resources. Here we report on the results of a study using a behavioral experimental approach regarding the relationship between social roles and the performance of social-ecological systems. The computer-based irrigation experiment that was the basis of this study mimics the decisions faced by farmers in small-scale irrigation systems. In each of 20 rounds, which are analogous to growing seasons, participants face a two-stage commons dilemma. First they must decide how much to invest in the public infrastructure, e.g., canals and water diversion structures. Second, they must decide how much to extract from the water made available by that public infrastructure. Each round begins with a 60-second communication period before the players make their investment and extraction decisions. By analyzing the chat messages exchanged among participants during the communication stage of the experiment, we coded up to three roles per participant using the scheme of seven roles known to be important in the literature: leader, knowledge generator, connector, follower, moralist, enforcer, and observer. Our study supports the importance of certain social roles (e.g., connector) previously highlighted by several case study analyses. However, using qualitative comparative analysis we found that none of the individual roles was sufficient for groups to succeed, i.e., to reach a certain level of group production. Instead, we found that a combination of at least five roles was necessary for success. In addition, in the context of upstream-downstream asymmetry, we observed a pattern in which social roles assumed by participants tended to differ by their positions. Although our work generated some interesting insights, further research is needed to determine how robust our findings are to different action situations, such as biophysical context, social network, and resource uncertainty.

Recent advances in fossil fuel CO₂ (FFCO₂) emission inventories enable sensitivity tests of simulated atmospheric CO₂ concentrations to sub-annual variations in FFCO₂ emissions and what this implies for the interpretation of observed CO₂. Six experiments are conducted to investigate the potential impact of three cycles of FFCO₂ emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO₂ rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO₂ rectification due to the covariation of diurnal FFCO₂ emissions and diurnal vertical mixing, as well as a smaller positive seasonal FFCO₂ rectification driven by the covariation of monthly FFCO₂ emissions and monthly atmospheric transport. The diurnal FFCO₂ emissions are responsible for a diurnal FFCO₂ concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO₂ emissions are responsible for a simulated seasonal CO₂ amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO₂ emissions, when only sampled in the local afternoon, is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO₂ concentration impacts from the diurnally and seasonally varying FFCO₂ emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO₂ emissions on simulated CO₂ concentration and suggests that inversion studies must take account of these variations in the affected regions.

There is an increasing awareness that health care must move from post-symptomatic treatment to presymptomatic intervention. An ideal system would allow regular inexpensive monitoring of health status using circulating antibodies to report on health fluctuations. Recently, we demonstrated that peptide microarrays can do this through antibody signatures (immunosignatures). Unfortunately, printed microarrays are not scalable. Here we demonstrate a platform based on fabricating microarrays (~10 M peptides per slide, 330,000 peptides per assay) on silicon wafers using equipment common to semiconductor manufacturing. The potential of these microarrays for comprehensive health monitoring is verified through the simultaneous detection and classification of six different infectious diseases and six different cancers. Besides diagnostics, these high-density peptide chips have numerous other applications both in health care and elsewhere.