Oncology providers' perspectives on endocrine therapy prescribing and management.

Adjuvant endocrine therapy (ET) can reduce the risk of recurrence among females with hormone receptor-positive breast cancer. Overall, initiation and adherence to ET are suboptimal, though reasons are not well described. The study's objective was to better understand ET decision making, prescribing, and patient management from oncology providers' perspectives. Using purposive sampling, we recruited oncology providers who saw five or more breast cancer patients per week (n=20). We conducted 30-45-minute telephone interviews, using a semistructured guide to elicit perspectives on ET use. We used thematic content analysis to systematically identify categories of meaning and double-coded transcripts using Atlas.ti. Providers recommend ET to all eligible patients except those with contraindications or other risk factors. Providers base their ET prescribing decisions on the patient's menopausal status, side effects, and comorbidities. ET is typically discussed multiple times: at the onset of breast cancer treatment and in more detail after other treatment completion. Providers felt that the associated recurrence risk reduction is the most compelling argument for patients during ET decision making. While providers rarely perceived noninitiation as a problem, nonadherence was prevalent, often due to unresolvable side effects. From the clinicians' perspectives, side effects from ET are the dominant factor in nonadherence. Efforts to improve adherence should focus on strategies to minimize side effects and ensure clinicians and patients are well informed regarding optimal side effect management. This finding has important implications for novel endocrine regimens that offer improved outcomes through longer duration or more intensive therapy

A Pharmacology-Based Enrichment Program for Undergraduates Promotes Interest in Science

There is a strong need to increase the number of undergraduate students who pursue careers in science to provide the “fuel” that will power a science and technology–driven U.S. economy. Prior research suggests that both evidence-based teaching methods and early undergraduate research experiences may help to increase retention rates in the sciences. In this study, we examined the effect of a program that included 1) a Summer enrichment 2-wk minicourse and 2) an authentic Fall research course, both of which were designed specifically to support students\u27 science motivation. Undergraduates who participated in the pharmacology-based enrichment program significantly improved their knowledge of basic biology and chemistry concepts; reported high levels of science motivation; and were likely to major in a biological, chemical, or biomedical field. Additionally, program participants who decided to major in biology or chemistry were significantly more likely to choose a pharmacology concentration than those majoring in biology or chemistry who did not participate in the enrichment program. Thus, by supporting students\u27 science motivation, we can increase the number of students who are interested in science and science careers

Using peer review to support development of community resources for research data management

This work is licensed under a Creative Commons 1.0 Public Domain Dedication. The definitive version was published in Journal of eScience Librarianship 6 (2017): e1114, doi:10.7191/jeslib.2017.1114.To ensure that resources designed to teach skills and best practices for scientific research data sharing and management are useful, the maintainers of those materials need to evaluate and update them to ensure their accuracy, currency, and quality. This paper advances the use and process of outside peer review for community resources in addressing ongoing accuracy, quality, and currency issues. It further describes the next step of moving the updated materials to an online collaborative community platform for future iterative review in order to build upon mechanisms for open science, ongoing iteration, participation, and transparent community engagement.DataONE is supported by US National Science Foundation Awards 08- 30944 and 14-30508, William Michener, Principal Investigator; Matthew Jones, Patricia Cruse, David Vieglais, and Suzanne Allard, Co-Principal Investigators

Repairing the Leaky Pipeline: A Motivationally Supportive Intervention to Enhance Persistence in Undergraduate Science Pathways

The current study reports on the efficacy of a multi-faceted motivationally designed undergraduate enrichment summer program for supporting science, technology, engineering and math (STEM) persistence. Structural equation modeling was used to compare summer program participants (n = 186), who participated in the program between their first and second years in college, to a propensity score matched comparison sample (n = 401). Participation in the summer program positively predicted science motivation (self-efficacy, task value), assessed eight months after the end of the program (second year in college). The summer enrichment program was also beneficial for science persistence variables, as evidenced by significant direct and indirect effects of the program on science course completion during students’ third year of college and students’ intentions to pursue a science research career assessed during the third year of college. In general, the program was equally beneficial for all participants, but ancillary analyses indicated added benefits with respect to task value for students with relatively lower prior science achievement during the first year of college and with respect to subsequent science course taking for males. Implications for developing effective interventions to reduce the flow of individuals out of STEM fields and for translating motivational theory into practice are discussed

Highly conserved molecular pathways, including Wnt signaling, promote functional recovery from spinal cord injury in lampreys

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 8 (2018): 742, doi:10.1038/s41598-017-18757-1.In mammals, spinal cord injury (SCI) leads to dramatic losses in neurons and synaptic connections, and consequently function. Unlike mammals, lampreys are vertebrates that undergo spontaneous regeneration and achieve functional recovery after SCI. Therefore our goal was to determine the complete transcriptional responses that occur after SCI in lampreys and to identify deeply conserved pathways that promote regeneration. We performed RNA-Seq on lamprey spinal cord and brain throughout the course of functional recovery. We describe complex transcriptional responses in the injured spinal cord, and somewhat surprisingly, also in the brain. Transcriptional responses to SCI in lampreys included transcription factor networks that promote peripheral nerve regeneration in mammals such as Atf3 and Jun. Furthermore, a number of highly conserved axon guidance, extracellular matrix, and proliferation genes were also differentially expressed after SCI in lampreys. Strikingly, ~3% of differentially expressed transcripts belonged to the Wnt pathways. These included members of the Wnt and Frizzled gene families, and genes involved in downstream signaling. Pharmacological inhibition of Wnt signaling inhibited functional recovery, confirming a critical role for this pathway. These data indicate that molecular signals present in mammals are also involved in regeneration in lampreys, supporting translational relevance of the model.We gratefully acknowledge support from the National Institutes of Health (R03NS078519 to OB; R01GM104123 to JJS; R01NS078165 to JRM), The Feinstein Institute for Medical Research and The Marine Biological Laboratory, including the Charles Evans Foundation Research Award, the Albert and Ellen Grass Foundation Faculty Research Award, and The Eugene and Millicent Bell Fellowship Fund in Tissue Engineering

Optimal model complexity for terrestrial carbon cycle prediction

The terrestrial carbon cycle plays a critical role in modulating the interactions of climate with the Earth system, but different models often make vastly different predictions of its behavior. Efforts to reduce model uncertainty have commonly focused on model structure, namely by introducing additional processes and increasing structural complexity. However, the extent to which increased structural complexity can directly improve predictive skill is unclear. While adding processes may improve realism, the resulting models are often encumbered by a greater number of poorly determined or over-generalized parameters. To guide efficient model development, here we map the theoretical relationship between model complexity and predictive skill. To do so, we developed 16 structurally distinct carbon cycle models spanning an axis of complexity and incorporated them into a model–data fusion system. We calibrated each model at six globally distributed eddy covariance sites with long observation time series and under 42 data scenarios that resulted in different degrees of parameter uncertainty. For each combination of site, data scenario, and model, we then predicted net ecosystem exchange (NEE) and leaf area index (LAI) for validation against independent local site data. Though the maximum model complexity we evaluated is lower than most traditional terrestrial biosphere models, the complexity range we explored provides universal insight into the inter-relationship between structural uncertainty, parametric uncertainty, and model forecast skill. Specifically, increased complexity only improves forecast skill if parameters are adequately informed (e.g., when NEE observations are used for calibration). Otherwise, increased complexity can degrade skill and an intermediate-complexity model is optimal. This finding remains consistent regardless of whether NEE or LAI is predicted. Our COMPLexity EXperiment (COMPLEX) highlights the importance of robust observation-based parameterization for land surface modeling and suggests that data characterizing net carbon fluxes will be key to improving decadal predictions of high-dimensional terrestrial biosphere models.</p

The impact of economic recession on maternal and infant mortality: lessons from history

<p>Abstract</p> <p>Background</p> <p>The effect of the recent world recession on population health has featured heavily in recent international meetings. Maternal health is a particular concern given that many countries were already falling short of their MDG targets for 2015.</p> <p>Methods</p> <p>We utilise 20^thcentury time series data from 14 high and middle income countries to investigate associations between previous economic recession and boom periods on maternal and infant outcomes (1936 to 2005). A first difference logarithmic model is used to investigate the association between short run fluctuations in GDP per capita (individual incomes) and changes in health outcomes. Separate models are estimated for four separate time periods.</p> <p>Results</p> <p>The results suggest a modest but significant association between maternal and infant mortality and economic growth for early periods (1936 to 1965) but not more recent periods. Individual country data display markedly different patterns of response to economic changes. Japan and Canada were vulnerable to economic shocks in the post war period. In contrast, mortality rates in countries such as the UK and Italy and particularly the US appear little affected by economic fluctuations.</p> <p>Conclusions</p> <p>The data presented suggest that recessions do have a negative association with maternal and infant outcomes particularly in earlier stages of a country's development although the effects vary widely across different systems. Almost all of the 20 least wealthy countries have suffered a reduction of 10% or more in GDP per capita in at least one of the last five decades. The challenge for today's policy makers is the design and implementation of mechanisms that protect vulnerable populations from the effects of fluctuating national income.</p

Efficacy and Safety of Lenabasum, a Cannabinoid Type 2 Receptor Agonist, in a Phase 3 Randomized Trial in Diffuse Cutaneous Systemic Sclerosis

INTRODUCTION: Efficacy and safety of lenabasum, a cannabinoid type 2-receptor agonist, was tested in a Phase 3 study in patients with diffuse cutaneous systemic sclerosis (dcSSc). METHODS: A multi-national double-blind study was conducted in 365 dcSSc patients who were randomized and dosed 1:1:1 with lenabasum 20 mg, lenabasum 5 mg, or placebo, each twice daily and added to background treatments including immunosuppressive therapies (IST). RESULTS: The primary endpoint, ACR Combined Response Index in dcSSc (ACR-CRISS) score at Week 52, lenabasum 20 mg BID versus placebo, was not met, with ACR-CRISS scores of 0.888 versus 0.887, P = 0.4972, mixed models repeated measures (MMRM). Change in modified Rodnan Skin Score (mRSS) at Week 52 was -6.7 versus -8.1 points for lenabasum 20 mg BID versus placebo, P = 0.1183, MMRM. Pre-specified analyses showed higher ACR-CRISS scores, greater improvement in mRSS, and less decline in forced vital capacity in subjects on background mycophenolate and those receiving IST for ≤ 1 year duration. No deaths or excess in serious or severe adverse events related to lenabasum were observed. CONCLUSIONS: A benefit of lenabasum in dcSSc was not demonstrated. The majority of patients were treated with background IST, and treatment with MMF in particular was associated with better outcomes. This supports the use of IST in the treatment of dcSSc, and highlights the challenge of demonstrating a treatment effect when investigational treatment is added to standard of care IST. These findings have relevance to trial design in SSc, as well as clinical care

Measurement of the Lifetime Difference Between B_s Mass Eigenstates

We present measurements of the lifetimes and polarization amplitudes for B_s --> J/psi phi and B_d --> J/psi K*0 decays. Lifetimes of the heavy (H) and light (L) mass eigenstates in the B_s system are separately measured for the first time by determining the relative contributions of amplitudes with definite CP as a function of the decay time. Using 203 +/- 15 B_s decays, we obtain tau_L = (1.05 +{0.16}/-{0.13} +/- 0.02) ps and tau_H = (2.07 +{0.58}/-{0.46} +/- 0.03) ps. Expressed in terms of the difference DeltaGamma_s and average Gamma_s, of the decay rates of the two eigenstates, the results are DeltaGamma_s/Gamma_s = (65 +{25}/-{33} +/- 1)%, and DeltaGamma_s = (0.47 +{0.19}/-{0.24} +/- 0.01) inverse ps.Comment: 8 pages, 3 figures, 2 tables; as published in Physical Review Letters on 16 March 2005; revisions are for length and typesetting only, no changes in results or conclusion

The Complete Spectrum of Yeast Chromosome Instability Genes Identifies Candidate CIN Cancer Genes and Functional Roles for ASTRA Complex Components

Chromosome instability (CIN) is observed in most solid tumors and is linked to somatic mutations in genome integrity maintenance genes. The spectrum of mutations that cause CIN is only partly known and it is not possible to predict a priori all pathways whose disruption might lead to CIN. To address this issue, we generated a catalogue of CIN genes and pathways by screening ∼2,000 reduction-of-function alleles for 90% of essential genes in Saccharomyces cerevisiae. Integrating this with published CIN phenotypes for other yeast genes generated a systematic CIN gene dataset comprised of 692 genes. Enriched gene ontology terms defined cellular CIN pathways that, together with sequence orthologs, created a list of human CIN candidate genes, which we cross-referenced to published somatic mutation databases revealing hundreds of mutated CIN candidate genes. Characterization of some poorly characterized CIN genes revealed short telomeres in mutants of the ASTRA/TTT components TTI1 and ASA1. High-throughput phenotypic profiling links ASA1 to TTT (Tel2-Tti1-Tti2) complex function and to TORC1 signaling via Tor1p stability, consistent with the role of TTT in PI3-kinase related kinase biogenesis. The comprehensive CIN gene list presented here in principle comprises all conserved eukaryotic genome integrity pathways. Deriving human CIN candidate genes from the list allows direct cross-referencing with tumor mutational data and thus candidate mutations potentially driving CIN in tumors. Overall, the CIN gene spectrum reveals new chromosome biology and will help us to understand CIN phenotypes in human disease