Whole-organism concentration ratios in wildlife inhabiting Australian uranium mining environments

Wildlife concentration ratios for 226Ra, 210Pb, 210Po and isotopes of Th and U from soil, water, and sediments were evaluated for a range of Australian uranium mining environments. Whole-organism concentration ratios (CRwo-media) were developed for 271 radionuclide-organism pairs within the terrestrial and freshwater wildlife groups. Australian wildlife often has distinct physiological attributes, such as the lower metabolic rates of macropod marsupials as compared with placental mammals. In addition, the Australian CRswo-media originate from tropical and semi-arid climates, rather than from the temperate-dominated climates of Europe and North America from which most (>90%) of internationally available CRwo-media values originate. When compared, the Australian and non-Australian CRs are significantly different for some wildlife categories (e.g. grasses, mammals) but not others (e.g. shrubs). Where differences exist, the Australian values were higher, suggesting that site-, or region-specific CRswo-media should be used in detailed Australian assessments. However, in screening studies, use of the international mean values in the Wildlife Transfer Database (WTD) appears to be appropriate, as long as the values used encompass the Australian 95th percentile values. Gaps in the Australian datasets include a lack of marine parameters, and no CR data are available for freshwater phytoplankton, zooplankton, insects, insect larvae or amphibians; for terrestrial environments, there are no data for amphibians, annelids, ferns, fungi or lichens & bryophytes. The new Australian specific parameters will aide in evaluating remediation plans and ongoing operations at mining and waste sites within Australia. They have also substantially bolstered the body of U- and Th-series CRwo-media data for use internationally

Attention, attention! Posttraumatic stress disorder is associated with altered attention-related brain function

Posttraumatic stress disorder (PTSD) is a debilitating condition characterized by altered arousal, mood, and cognition. Studies report attentional alterations such as threat bias in individuals with PTSD, though this work has largely been conducted within emotionally-charged contexts (e.g., threatening stimuli). Emerging behavioral evidence suggests that PTSD-related attention deficits exist even in the absence of threatening cues or anxiety triggers. However, the role and functioning of attention brain circuits as they relate to PTSD remains underexplored. In this mini review, we highlight recent work using non-emotional stimuli to investigate the neurobiology of attention and disruptions to attention-related brain function among individuals with PTSD. We then discuss gaps in the current literature, including questions pertaining to the neural circuitry of attentional alterations in PTSD, as well as the contributions that trauma exposure, PTSD symptoms, comorbidities, and pre-existing vulnerabilities may have in this relationship. Finally, we suggest future directions for this emerging area of research, which may further inform knowledge surrounding the neurobiological underpinnings of PTSD and potential treatments

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25-5.0 μg/mL) and/or carbendazim (0.8-1.6 μg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the "DeepFlow" neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for 'mononucleates', 'binucleates', 'mononucleates with MN' and 'binucleates with MN', respectively. Successful classifications of 'trinucleates' (90%) and 'tetranucleates' (88%) in addition to 'other or unscorable' phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks

The radio source count at 93.2 GHz from observations of 9C sources using AMI and CARMA

We present results from follow-up observations of a sample of 80 radio sources, originally detected as part of the 15.2-GHz Ninth Cambridge (9C) survey. The observations were carried out, close to simultaneously, at two frequencies: 15.7 GHz, using the Arcminute Microkelvin Imager (AMI) Large Array, and 93.2 GHz, using the Combined Array for Research in Millimeter-wave Astronomy (CARMA). There is currently little direct information on the 90-GHz-band source count for S ≲ 1 Jy. However, we have used the measured 15.7-to-93.2-GHz spectral-index distribution and 9C source count to predict the differential source count at 93.2 GHz as 26 ± 4(S/Jy)^(−2.15) Jy^(−1) sr^(−1); our projection is estimated to be most accurate for 10 ≲ S ≲ 100 mJy. Our estimated differential count is more than twice the 90-GHz prediction made by Waldram et al.; we believe that this discrepancy is because the measured 43-GHz flux densities used in making their prediction were too low. Similarly, our prediction is significantly higher than that of Sadler et al. at 95 GHz. Since our spectral-index distribution is similar to the 20-to-95-GHz distribution measured by Sadler et al. and used in making their prediction, we believe that the difference is almost entirely attributable to the dissimilarity in the lower frequency counts used in making the estimates

Assessing the carcinogenic potential of low-dose exposures to chemical mixtures in the environment: the challenge ahead.

Lifestyle factors are responsible for a considerable portion of cancer incidence worldwide, but credible estimates from the World Health Organization and the International Agency for Research on Cancer (IARC) suggest that the fraction of cancers attributable to toxic environmental exposures is between 7% and 19%. To explore the hypothesis that low-dose exposures to mixtures of chemicals in the environment may be combining to contribute to environmental carcinogenesis, we reviewed 11 hallmark phenotypes of cancer, multiple priority target sites for disruption in each area and prototypical chemical disruptors for all targets, this included dose-response characterizations, evidence of low-dose effects and cross-hallmark effects for all targets and chemicals. In total, 85 examples of chemicals were reviewed for actions on key pathways/mechanisms related to carcinogenesis. Only 15% (13/85) were found to have evidence of a dose-response threshold, whereas 59% (50/85) exerted low-dose effects. No dose-response information was found for the remaining 26% (22/85). Our analysis suggests that the cumulative effects of individual (non-carcinogenic) chemicals acting on different pathways, and a variety of related systems, organs, tissues and cells could plausibly conspire to produce carcinogenic synergies. Additional basic research on carcinogenesis and research focused on low-dose effects of chemical mixtures needs to be rigorously pursued before the merits of this hypothesis can be further advanced. However, the structure of the World Health Organization International Programme on Chemical Safety 'Mode of Action' framework should be revisited as it has inherent weaknesses that are not fully aligned with our current understanding of cancer biology

The Transcriptional Response of Drosophila melanogaster to Infection with the Sigma Virus (Rhabdoviridae)

Bacterial and fungal infections induce a potent immune response in Drosophila melanogaster, but it is unclear whether viral infections induce an antiviral immune response. Using microarrays, we examined the changes in gene expression in Drosophila that occur in response to infection with the sigma virus, a negative-stranded RNA virus (Rhabdoviridae) that occurs in wild populations of D. melanogaster. We detected many changes in gene expression in infected flies, but found no evidence for the activation of the Toll, IMD or Jak-STAT pathways, which control immune responses against bacteria and fungi. We identified a number of functional categories of genes, including serine proteases, ribosomal proteins and chorion proteins that were overrepresented among the differentially expressed genes. We also found that the sigma virus alters the expression of many more genes in males than in females. These data suggest that either Drosophila do not mount an immune response against the sigma virus, or that the immune response is not controlled by known immune pathways. If the latter is true, the genes that we identified as differentially expressed after infection are promising candidates for controlling the host's response to the sigma virus

How to make complexity look simple? Conveying ecosystems restoration complexity for socio-economic research and public engagement

Ecosystems degradation represents one of the major global challenges at the present time, threating people’s livelihoods and well-being worldwide. Ecosystem restoration therefore seems no longer an option, but an imperative. Restoration challenges are such that a dialogue has begun on the need to re-shape restoration as a science. A critical aspect of that reshaping process is the acceptance that restoration science and practice needs to be coupled with socio-economic research and public engagement. This inescapably means conveying complex ecosystem’s information in a way that is accessible to the wider public. In this paper we take up this challenge with the ultimate aim of contributing to making a step change in science’s contribution to ecosystems restoration practice. Using peatlands as a paradigmatically complex ecosystem, we put in place a transdisciplinary process to articulate a description of the processes and outcomes of restoration that can be understood widely by the public. We provide evidence of the usefulness of the process and tools in addressing four key challenges relevant to restoration of any complex ecosystem: (1) how to represent restoration outcomes; (2) how to establish a restoration reference; (3) how to cope with varying restoration time-lags and (4) how to define spatial units for restoration. This evidence includes the way the process resulted in the creation of materials that are now being used by restoration practitioners for communication with the public and in other research contexts. Our main contribution is of an epistemological nature: while ecosystem services-based approaches have enhanced the integration of academic disciplines and non-specialist knowledge, this has so far only followed one direction (from the biophysical underpinning to the description of ecosystem services and their appreciation by the public). We propose that it is the mix of approaches and epistemological directions (including from the public to the biophysical parameters) what will make a definitive contribution to restoration practice

The daily association between affect and alcohol use: a meta-analysis of individual participant data

Influential psychological theories hypothesize that people consume alcohol in response to the experience of both negative and positive emotions. Despite two decades of daily diary and ecological momentary assessment research, it remains unclear whether people consume more alcohol on days they experience higher negative and positive affect in everyday life. In this preregistered meta-analysis, we synthesized the evidence for these daily associations between affect and alcohol use. We included individual participant data from 69 studies (N = 12,394), which used daily and momentary surveys to assess affect and the number of alcoholic drinks consumed. Results indicate that people are not more likely to drink on days they experience high negative affect, but are more likely to drink and drink heavily on days high in positive affect. People self-reporting a motivational tendency to drink-to-cope and drink-to-enhance consumed more alcohol, but not on days they experienced higher negative and positive affect. Results were robust across different operationalizations of affect, study designs, study populations, and individual characteristics. These findings challenge the long-held belief that people drink more alcohol following increases in negative affect. Integrating these findings under different theoretical models and limitations of this field of research, we collectively propose an agenda for future research to explore open questions surrounding affect and alcohol use.The present study was funded by the Canadian Institutes of Health Research Grant MOP-115104 (Roisin M. O’Connor), Canadian Institutes of Health Research Grant MSH-122803 (Roisin M. O’Connor), John A. Hartford Foundation Grant (Paul Sacco), Loyola University Chicago Research Support Grant (Tracy De Hart), National Institute for Occupational Safety and Health Grant T03OH008435 (Cynthia Mohr), National Institutes of Health (NIH) Grant F31AA023447 (Ryan W. Carpenter), NIH Grant R01AA025936 (Kasey G. Creswell), NIH Grant R01AA025969 (Catharine E. Fairbairn), NIH Grant R21AA024156 (Anne M. Fairlie), NIH Grant F31AA024372 (Fallon Goodman), NIH Grant R01DA047247 (Kevin M. King), NIH Grant K01AA026854 (Ashley N. Linden-Carmichael), NIH Grant K01AA022938 (Jennifer E. Merrill), NIH Grant K23AA024808 (Hayley Treloar Padovano), NIH Grant P60AA11998 (Timothy Trull), NIH Grant MH69472 (Timothy Trull), NIH Grant K01DA035153 (Nisha Gottfredson), NIH Grant P50DA039838 (Ashley N. Linden-Carmichael), NIH Grant K01DA047417 (David M. Lydon-Staley), NIH Grant T32DA037183 (M. Kushner), NIH Grant R21DA038163 (A. Moore), NIH Grant K12DA000167 (M. Potenza, Stephanie S. O’Malley), NIH Grant R01AA025451 (Bruce Bartholow, Thomas M. Piasecki), NIH Grant P50AA03510 (V. Hesselbrock), NIH Grant K01AA13938 (Kristina M. Jackson), NIH Grant K02AA028832 (Kevin M. King), NIH Grant T32AA007455 (M. Larimer), NIH Grant R01AA025037 (Christine M. Lee, M. Patrick), NIH Grant R01AA025611 (Melissa Lewis), NIH Grant R01AA007850 (Robert Miranda), NIH Grant R21AA017273 (Robert Miranda), NIH Grant R03AA014598 (Cynthia Mohr), NIH Grant R29AA09917 (Cynthia Mohr), NIH Grant T32AA07290 (Cynthia Mohr), NIH Grant P01AA019072 (P. Monti), NIH Grant R01AA015553 (J. Morgenstern), NIH Grant R01AA020077 (J. Morgenstern), NIH Grant R21AA017135 (J. Morgenstern), NIH Grant R01AA016621 (Stephanie S. O’Malley), NIH Grant K99AA029459 (Marilyn Piccirillo), NIH Grant F31AA022227 (Nichole Scaglione), NIH Grant R21AA018336 (Katie Witkiewitz), Portuguese State Budget Foundation for Science and Technology Grant UIDB/PSI/01662/2020 (Teresa Freire), University of Washington Population Health COVID-19 Rapid Response Grant (J. Kanter, Adam M. Kuczynski), U.S. Department of Defense Grant W81XWH-13-2-0020 (Cynthia Mohr), SANPSY Laboratory Core Support Grant CNRS USR 3413 (Marc Auriacombe), Social Sciences and Humanities Research Council of Canada Grant (N. Galambos), and Social Sciences and Humanities Research Council of Canada Grant (Andrea L. Howard)