Behavioral Patterns Associated with Chemotherapy-Induced Emesis: A Potential Signature for Nausea in Musk Shrews

Nausea and vomiting are common symptoms in patients with many diseases, including cancer and its treatments. Although the neurological basis of vomiting is reasonably well known, an understanding of the physiology of nausea is lacking. The primary barrier to mechanistic research on the nausea system is the lack of an animal model. Indeed investigating the effects of anti-nausea drugs in pre-clinical models is difficult because the primary readout is often emesis. It is known that animals show a behavioral profile of sickness, associated with reduced feeding and movement, and possibly these general measures are signs of nausea. Studies attempting to relate the occurrence of additional behaviors to emesis have produced mixed results. Here we applied a statistical method, temporal pattern (t-pattern) analysis, to determine patterns of behavior associated with emesis. Musk shrews were injected with the chemotherapy agent cisplatin (a gold standard in emesis research) to induce acute (<24 h) and delayed (>24 h) emesis. Emesis and other behaviors were coded and tracked from video files. T-pattern analysis revealed hundreds of non-random patterns of behavior associated with emesis, including sniffing, changes in body contraction, and locomotion. There was little evidence that locomotion was inhibited by the occurrence of emesis. Eating, drinking, and other larger body movements including rearing, grooming, and body rotation, were significantly less common in emesis-related behavioral patterns in real versus randomized data. These results lend preliminary evidence for the expression of emesis-related behavioral patterns, including reduced ingestive behavior, grooming, and exploratory behaviors. In summary, this statistical approach to behavioral analysis in a pre-clinical emesis research model could be used to assess the more global effects and limitations of drugs used to control nausea and its potential correlates, including reduced feeding and activity levels

Accommodating quality and service improvement research within existing ethical principles

Funds were provided by a Canadian Institute of Health Research grant (Nominated PI: Monica Taljaard, PJT – 153045). Funds were also generously provided by Charles Weijer, who is funded by a Tier 1 Canadian Research Chair.Peer reviewedPublisher PD

ESTIMATION OF AND ADJUSTMENT FOR RESIDUAL EFFECTS IN DAIRY FEEDING EXPERIMENTS UTILIZING CHANGEOVER DESIGNS

A procedure is presented which demonstrates estimation of and adjustment for residual effects in changeover designs. The method utilizes all data collected in an experiment by including treatments imposed on animals prior to initiation of data collection. Estimation is achieved via general linear models. An example is given of a nutrition experiment conducted with dairy cattle. Such analyses should increase efficacy of changeover designs and reduce concern by researchers about biased estimates of direct effects which could result from residual effects. Methods from popular computer programs for estimating direct effect treatment means are compared. Practical problems encountered in computing standard errors of mean estimates in mixed linear models

Evolutionary bursts in Euphorbia (Euphorbiaceae) are linked with photosynthetic pathway

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109954/1/evo12534.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/109954/2/evo12534-sup-0001-SuppMAT.pd

Ants Sow the Seeds of Global Diversification in Flowering Plants

Background: The extraordinary diversification of angiosperm plants in the Cretaceous and Tertiary periods has produced an estimated 250,000–300,000 living angiosperm species and has fundamentally altered terrestrial ecosystems. Interactions with animals as pollinators or seed dispersers have long been suspected as drivers of angiosperm diversification, yet empirical examples remain sparse or inconclusive. Seed dispersal by ants (myrmecochory) may drive diversification as it can reduce extinction by providing selective advantages to plants and can increase speciation by enhancing geographical isolation by extremely limited dispersal distances. Methodology/Principal Findings: Using the most comprehensive sister-group comparison to date, we tested the hypothesis that myrmecochory leads to higher diversification rates in angiosperm plants. As predicted, diversification rates were substantially higher in ant-dispersed plants than in their non-myrmecochorous relatives. Data from 101 angiosperm lineages in 241 genera from all continents except Antarctica revealed that ant-dispersed lineages contained on average more than twice as many species as did their non-myrmecochorous sister groups. Contrasts in species diversity between sister groups demonstrated that diversification rates did not depend on seed dispersal mode in the sister group and were higher in myrmecochorous lineages in most biogeographic regions. Conclusions/Significance: Myrmecochory, which has evolved independently at least 100 times in angiosperms and is estimated to be present in at least 77 families and 11 000 species, is a key evolutionary innovation and a globally important driver of plant diversity. Myrmecochory provides the best example to date for a consistent effect of any mutualism on largescale diversification

Adjuvant chemotherapy with or without bevacizumab in patients with resected non-small-cell lung cancer (E1505): an open-label, multicentre, randomised, phase 3 trial.

BackgroundAdjuvant chemotherapy for resected early-stage non-small-cell lung cancer (NSCLC) provides a modest survival benefit. Bevacizumab, a monoclonal antibody directed against VEGF, improves outcomes when added to platinum-based chemotherapy in advanced-stage non-squamous NSCLC. We aimed to evaluate the addition of bevacizumab to adjuvant chemotherapy in early-stage resected NSCLC.MethodsWe did an open-label, randomised, phase 3 trial of adult patients (aged ≥18 years) with an Eastern Cooperative Oncology Group performance status of 0 or 1 and who had completely resected stage IB (≥4 cm) to IIIA (defined by the American Joint Committee on Cancer 6th edition) NSCLC. We enrolled patients from across the US National Clinical Trials Network, including patients from the Eastern Cooperative Oncology Group-American College of Radiology Imaging Network (ECOG-ACRIN) affiliates in Europe and from the Canadian Cancer Trials Group, within 6-12 weeks of surgery. The chemotherapy regimen for each patient was selected before randomisation and administered intravenously; it consisted of four 21-day cycles of cisplatin (75 mg/m2 on day 1 in all regimens) in combination with investigator's choice of vinorelbine (30 mg/m2 on days 1 and 8), docetaxel (75 mg/m2 on day 1), gemcitabine (1200 mg/m2 on days 1 and 8), or pemetrexed (500 mg/m2 on day 1). Patients in the bevacizumab group received bevacizumab 15 mg/kg intravenously every 21 days starting with cycle 1 of chemotherapy and continuing for 1 year. We randomly allocated patients (1:1) to group A (chemotherapy alone) or group B (chemotherapy plus bevacizumab), centrally, using permuted blocks sizes and stratified by chemotherapy regimen, stage of disease, histology, and sex. No one was masked to treatment assignment, except the Data Safety and Monitoring Committee. The primary endpoint was overall survival, analysed by intention to treat. This trial is registered with ClinicalTrials.gov, number NCT00324805.FindingsBetween June 1, 2007, and Sept 20, 2013, 1501 patients were enrolled and randomly assigned to the two treatment groups: 749 to group A (chemotherapy alone) and 752 to group B (chemotherapy plus bevacizumab). 383 (26%) of 1458 patients (with complete staging information) had stage IB, 636 (44%) had stage II, and 439 (30%) had stage IIIA disease (stage of disease data were missing for 43 patients). Squamous cell histology was reported for 422 (28%) of 1501 patients. All four cisplatin-based chemotherapy regimens were used: 377 (25%) patients received vinorelbine, 343 (23%) received docetaxel, 283 (19%) received gemcitabine, and 497 (33%) received pemetrexed. At a median follow-up of 50·3 months (IQR 32·9-68·0), the estimated median overall survival in group A has not been reached, and in group B was 85·8 months (95% CI 74·9 to not reached); hazard ratio (group B vs group A) 0·99 (95% CI 0·82-1·19; p=0·90). Grade 3-5 toxicities of note (all attributions) that were reported more frequently in group B (the bevacizumab group) than in group A (chemotherapy alone) were overall worst grade (ie, all grade 3-5 toxicities; 496 [67%] of 738 in group A vs 610 [83%] of 735 in group B), hypertension (60 [8%] vs 219 [30%]), and neutropenia (241 [33%] vs 275 [37%]). The number of deaths on treatment did not differ between the groups (15 deaths in group A vs 19 in group B). Of these deaths, three in group A and ten in group B were considered at least possibly related to treatment.InterpretationAddition of bevacizumab to adjuvant chemotherapy did not improve overall survival for patients with surgically resected early-stage NSCLC. Bevacizumab does not have a role in this setting and should not be considered as an adjuvant therapy for patients with resected early-stage NSCLC.FundingNational Cancer Institute of the National Institutes of Health

Education, income, and incident heart failure in post-menopausal women: the Women\u27s Health Initiative Hormone Therapy Trials

OBJECTIVES: The purpose of this study is to estimate the effect of education and income on incident heart failure (HF) hospitalization among post-menopausal women. BACKGROUND: Investigations of socioeconomic status have focused on outcomes after HF diagnosis, not associations with incident HF. We used data from the Women\u27s Health Initiative Hormone Trials to examine the association between socioeconomic status levels and incident HF hospitalization. METHODS: We included 26,160 healthy, post-menopausal women. Education and income were self-reported. Analysis of variance, chi-square tests, and proportional hazards models were used for statistical analysis, with adjustment for demographics, comorbid conditions, behavioral factors, and hormone and dietary modification assignments. RESULTS: Women with household incomes $50,000 a year (16.7/10,000 person-years; p \u3c 0.01). Women with less than a high school education had higher HF hospitalization incidence (51.2/10,000 person-years) than college graduates and above (25.5/10,000 person-years; p \u3c 0.01). In multivariable analyses, women with the lowest income levels had 56% higher risk (hazard ratio: 1.56, 95% confidence interval: 1.19 to 2.04) than the highest income women; women with the least amount of education had 21% higher risk for incident HF hospitalization (hazard ratio: 1.21, 95% confidence interval: 0.90 to 1.62) than the most educated women. CONCLUSIONS: Lower income is associated with an increased incidence of HF hospitalization among healthy, post-menopausal women, whereas multivariable adjustment attenuated the association of education with incident HF. Elsevier Inc. All rights reserved

1969: Abilene Christian College Bible Lectures - Full Text

GOD’S ETERNAL PURPOSE Being the Abilene Christian College Annual Bible Lectures 1969 Published by ABILENE CHRISTIAN COLLEGE BOOK STORE ACC Station Abilene, Texas 7960

Perspectives in machine learning for wildlife conservation

Data acquisition in animal ecology is rapidly accelerating due to inexpensive and accessible sensors such as smartphones, drones, satellites, audio recorders and bio-logging devices. These new technologies and the data they generate hold great potential for large-scale environmental monitoring and understanding, but are limited by current data processing approaches which are inefficient in how they ingest, digest, and distill data into relevant information. We argue that machine learning, and especially deep learning approaches, can meet this analytic challenge to enhance our understanding, monitoring capacity, and conservation of wildlife species. Incorporating machine learning into ecological workflows could improve inputs for population and behavior models and eventually lead to integrated hybrid modeling tools, with ecological models acting as constraints for machine learning models and the latter providing data-supported insights. In essence, by combining new machine learning approaches with ecological domain knowledge, animal ecologists can capitalize on the abundance of data generated by modern sensor technologies in order to reliably estimate population abundances, study animal behavior and mitigate human/wildlife conflicts. To succeed, this approach will require close collaboration and cross-disciplinary education between the computer science and animal ecology communities in order to ensure the quality of machine learning approaches and train a new generation of data scientists in ecology and conservation