Overcoming early career barriers to interdisciplinary climate change research

Climate-change impacts are among the most serious and complex challenges facing society, affecting both natural and social systems. Addressing these requires a new paradigm of interdisciplinary collaboration which incorporates tools, techniques, and insights from across the social, natural, and engineering sciences. Yet, a wide range of intrinsic and extrinsic hurdles need to be overcome to conduct successful, integrated interdisciplinary research. The results of a bibliometric analysis and survey of early to mid-career scientists from 56 countries who were involved with the interdisciplinary DISsertations initiative for the advancement of Climate Change ReSearch (DISCCRS) emphasize the particular challenges faced by early career researchers. Survey respondents perceive conflict between the need for interdisciplinary climate-change research and its potential detriment to career advancement. However, participation in interventions for early career scientists, such as networking and training symposia, had both perceived and measurable impacts on the likelihood of engagement in climate-centric interdisciplinary research. Respondents also ranked alternative mechanisms for encouraging incorporation of interdisciplinary science at early career stages, prioritizing funding of interdisciplinary seed grants, fellowships, and junior faculty networks, interdisciplinary teamwork and communication training, and interdepartmental symposia. To this we add the suggestion that interdisciplinarity be incorporated into tenure and promotion evaluations through the use of exploratory science mapping tools. Despite the need to foster interdisciplinary research and the availability of multiple prospective solutions, there remain expansive structural challenges to its promotion and recognition which, unless collectively addressed, will continue to hinder its potential growth and application to climate-change science

Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system

The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty

PTP1B Suppresses Prolactin Activation of Stat5 in Breast Cancer Cells

Basal levels of nuclear localized, tyrosine phosphorylated Stat5 are present in healthy human breast epithelia. In contrast, Stat5 phosphorylation is frequently lost during breast cancer progression, a finding that correlates with loss of histological differentiation and poor patient prognosis. Identifying the mechanisms underlying loss of Stat5 phosphorylation could provide novel targets for breast cancer therapy. Pervanadate, a general tyrosine phosphatase inhibitor, revealed marked phosphatase regulation of Stat5 activity in breast cancer cells. Lentiviral-mediated shRNA allowed specific examination of the regulatory role of five tyrosine phosphatases (PTP1B, TC-PTP, SHP1, SHP2, and VHR), previously implicated in Stat5 regulation in various systems. Enhanced and sustained prolactin-induced Stat5 tyrosine phosphorylation was observed in T47D and MCF7 breast cancer cells selectively in response to PTP1B depletion. Conversely, PTP1B overexpression suppressed prolactin-induced Stat5 tyrosine phosphorylation. Furthermore, PTP1B knockdown increased Stat5 reporter gene activity. Mechanistically, PTP1B suppression of Stat5 phosphorylation was mediated, at least in part, through inhibitory dephosphorylation of the Stat5 tyrosine kinase, Jak2. PTP1B knockdown enhanced sensitivity of T47D cells to prolactin phosphorylation of Stat5 by reducing the EC50 from 7.2 nmol/L to 2.5 nmol/L. Immunohistochemical analyses of two independent clinical breast cancer materials revealed significant negative correlations between levels of active Stat5 and PTP1B, but not TC-PTP. Collectively, our data implicate PTP1B as an important negative regulator of Stat5 phosphorylation in invasive breast cancer

Measurements of Aerosol Chemistry during New Particle Formation Events at a Remote Rural Mountain Site

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Robust associations of four new chromosome regions from genome-wide analysis of type 1 diabetes

The Wellcome Trust Case Control Consortium (WTCCC) primary genome-wide association (GWA) scan on seven diseases, including the multifactorial autoimmune disease type 1 diabetes (T1D), shows associations at P smaller than 5 x 10-7 between T1D and six chromosome regions: 12q24, 12q13, 16p13, 18p11, 12p13 and 4q27. Here, we attempted to validate these and six other top findings in 4,000 individuals with T1D, 5,000 controls and 2,997 family trios independent of the WTCCC study. We confirmed unequivocally the associations of 12q24, 12q13, 16p13 and 18p11 (P follow-up smaller than or equal to 1.35 x 10 -9; P overall smaller than or equal to 1.15 x 10-14), leaving eight regions with small effects or false-positive associations. We also obtained evidence for chromosome 18q22 (P overall = 1.38 x 10-8) from a GWA study of nonsynonymous SNPs. Several regions, including 18q22 and 18p11, showed association with autoimmune thyroid disease. This study increases the number of T1D loci with compelling evidence from six to at least ten. © 2007 Nature Publishing Group