Oh, Behave!: PRESIDENTIAL ADDRESS, XXth International Conference on Infant Studies New Orleans, LA, US May 2016.
Ontology highlight
ABSTRACT:
SUBMITTER: Adolph KE
PROVIDER: S-EPMC7580788 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The 29th International Conference on Antiviral Research (ICAR) was held in La Jolla, CA, USA from April 17 to 21, 2016. This report opens with a tribute to the late Chris McGuigan, a Past-President of ISAR, then continues with summaries of the principal invited lectures. Doug Richman (Elion Award) investigated HIV resistance, Bob Vince (Holý Award) showed how carbocyclic nucleoside analogs led to abacavir and Jerome Deval (Prusoff Award) explained how his group chose to seek a nucleoside analog to treat RSV. ALS-8176 was active in a human RSV-challenge study and is being evaluated in children. The first keynote address, by Richard H. Scheuermann, reported on the remarkable progress made in viral genomics. The second keynote address, by Heinz Feldmann, gave an overview of Ebola virus disease. There were four mini-symposia, Structural Biology, Diagnostic Technologies, DNA viruses and Zika virus. Diagnostic assays are approaching an ideal aim, a compact instrument, simple to use with any type of sample, no sample preparation and a result within an hour. The diversity of HCMV is far greater than for other herpesviruses, typically, an individual having >20,000 single nucleotide polymorphisms (SNPs). During antiviral treatment, there is rapid CMV evolution which is presumed to be due to preferential selection of already present variants rather than by the creation of new variants. A selection of contributor presentations includes oral prodrugs for nucleoside triphosphate analogs, a new method for the synthesis of phosphoramidate prodrugs and the clinical evaluation of brincidofovir for treating transplant recipients with adenovirus infections.
| S-EPMC7113867 | biostudies-literature
Project description:Rationale: Learning styles (LS) of medical residents change over time from the more passive Assimilator toward more active preferences like Accommodator or Converger. We have shown pharmacy residents to be predominantly Assimilators at the start of their residency program. Whether learning styles of pharmacy residents change after they enter practice has never been studied. Objective: To describe the evolution of learning styles of pharmacy residents as they transition from residency into practice. Study Design and Methods: Prospective observational survey and semi-structured interviews. A complete provincial cohort of former pharmacy residents (n=28) who had their LS characterized during their residency and were now 1 year post-residency were invited to repeat the Pharmacists’ Inventory of Learning Styles (PILS). Interviews were administered to consenting participants to gain additional insights. Results: 27 residents (96%) completed the PILS survey and 16 (59%) completed the interview. 13 (48%) changed their dominant LS and 20 (74%) changed their secondary LS. Six (22%) participants did not change either LS. The overall proportion of dominant Assimilators (59%) and Convergers (26%) remained similar to baseline (52% and 26%, respectively), meaning participants had adopted and abandoned different learning styles in similar numbers. Change in LS was associated with receiving preceptor training (p<0.05). Of the 12 preceptors interviewed, 58% stated that they had adjusted their teaching practices based on knowledge of their LS. Conclusions: Change in dominant and/or secondary learning style is common after 1 year in practice compared to during pharmacy practice residency. There is no overall direction to the shifts, however, with residents transitioning in and out of more active learning styles with similar frequency. Overall after a year in practice, the cohort of former residents we studied remained mostly Assimilators, who prefer passive learning approaches. These results contrast with medical students, who adopt more active preferences like Accommodator.
| S-EPMC3952913 | biostudies-literature
Project description:There are many ways to classify ectodermal dysplasia syndromes. Clinicians in practice use a list of syndromes from which to choose a potential diagnosis, paging through a volume, such as Freire-Maia and Pinheiro's corpus, matching their patient's findings to listed syndromes. Medical researchers may want a list of syndromes that share one (monothetic system) or several (polythetic system) traits in order to focus research on a narrowly defined group. Special interest groups may want a list from which they can choose constituencies, and insurance companies and government agencies may want a list to determine for whom to provide (or deny) health-care coverage. Furthermore, various molecular biologists are now promoting classification systems based on gene mutation (e.g., TP63-associated syndromes) or common molecular pathways. The challenge will be to balance comprehensiveness within the classification with usability and accessibility so that the benefits truly serve the needs of researchers, health-care providers, and ultimately the individuals and families directly affected by ectodermal dysplasias. It is also recognized that a new classification approach is an ongoing process and will require periodical reviews or updates. Whatever scheme is developed, however, will have far-reaching application for other groups of disorders for which classification is complicated by the number of interested parties and advances in diagnostic acumen. Consensus among interested parties is necessary for optimizing communication among the diverse groups whether it be for equitable distribution of funds, correctness of diagnosis and treatment, or focusing research efforts.
| S-EPMC2756677 | biostudies-literature
Project description:BackgroundThe 2016 presidential election and the controversial policy agenda of its victor have raised concerns about how the election may have impacted mental health.ObjectiveAssess how mental health changed from before to after the November 2016 election and how trends differed in states that voted for Donald Trump versus Hillary Clinton.DesignPre- versus post-election study using monthly cross-sectional survey data.ParticipantsA total of 499,201 adults surveyed in the Behavioral Risk Factor Surveillance System from May 2016 to May 2017.ExposureResidence in a state that voted for Trump versus state that voted for Clinton and the candidate's margin of victory in the state.Main measuresSelf-reported days of poor mental health in the last 30 days and depression rate.Key resultsCompared to October 2016, the mean days of poor mental health in the last 30 days per adult rose from 3.35 to 3.85 in December 2016 in Clinton states (0.50 days difference, p = 0.005) but remained statistically unchanged in Trump states, moving from 3.94 to 3.78 days (- 0.17 difference, p = 0.308). The rises in poor mental health days in Clinton states were driven by older adults, women, and white individuals. The depression rate in Clinton states began rising in January 2017. A 10-percentage point higher margin of victory for Clinton in a state predicted 0.41 more days of poor mental health per adult in December 2016 on average (p = 0.001).ConclusionsIn states that voted for Clinton, there were 54.6 million more days of poor mental health among adults in December 2016, the month following the election, compared to October 2016. Clinicians should consider that elections could cause at least transitory increases in poor mental health and tailor patient care accordingly, especially with the 2020 election upon us.
| S-EPMC7602772 | biostudies-literature
Project description:This study evaluates evidence pertaining to popular narratives explaining the American public's support for Donald J. Trump in the 2016 presidential election. First, using unique representative probability samples of the American public, tracking the same individuals from 2012 to 2016, I examine the "left behind" thesis (that is, the theory that those who lost jobs or experienced stagnant wages due to the loss of manufacturing jobs punished the incumbent party for their economic misfortunes). Second, I consider the possibility that status threat felt by the dwindling proportion of traditionally high-status Americans (i.e., whites, Christians, and men) as well as by those who perceive America's global dominance as threatened combined to increase support for the candidate who emphasized reestablishing status hierarchies of the past. Results do not support an interpretation of the election based on pocketbook economic concerns. Instead, the shorter relative distance of people's own views from the Republican candidate on trade and China corresponded to greater mass support for Trump in 2016 relative to Mitt Romney in 2012. Candidate preferences in 2016 reflected increasing anxiety among high-status groups rather than complaints about past treatment among low-status groups. Both growing domestic racial diversity and globalization contributed to a sense that white Americans are under siege by these engines of change.
| S-EPMC5948965 | biostudies-literature
Project description:Immigration and demographic change have become highly salient in American politics, partly because of the 2016 campaign of Donald Trump. Previous research indicates that local influxes of immigrants or unfamiliar ethnic groups can generate threatened responses, but has either focused on nonelectoral outcomes or analyzed elections in large geographic units, such as counties. Here, we examine whether demographic changes at low levels of aggregation were associated with vote shifts toward an anti-immigration presidential candidate between 2012 and 2016. To do so, we compile a precinct-level dataset of election results and demographic measures for almost 32,000 precincts in the states of Florida, Georgia, Michigan, Nevada, Ohio, Pennsylvania, and Washington. We employ regression analyses varying model specifications and measures of demographic change. Our estimates uncover little evidence that influxes of Hispanics or noncitizen immigrants benefited Trump relative to past Republicans, instead consistently showing that such changes were associated with shifts to Trump's opponent.
| S-EPMC6911220 | biostudies-literature
Project description:We use 19 billion likes on the posts of top 2000 U.S. fan pages on Facebook from 2015 to 2016 to measure the dynamic ideological positions for politicians, news outlets, and users at the national and state levels. We then use these measures to derive support rates for 2016 presidential candidates in all 50 states, to predict the election, and to compare them with state-level polls and actual vote shares. We find that: (1) Assuming that users vote for candidates closer to their own ideological positions, support rates calculated using Facebook predict that Trump will win the electoral college vote while Clinton will win the popular vote. (2) State-level Facebook support rates track state-level polling averages and pass the cointegration test, showing two time series share similar trends. (3) Compared with actual vote shares, polls generally have smaller margin of errors, but polls also often overestimate Clinton's support in right-leaning states. Overall, we provide a method to forecast elections at low cost, in real time, and based on passively revealed preference and little researcher discretion.
| S-EPMC8635376 | biostudies-literature
Project description:ObjectiveResearch suggests that sociopolitical stressors connected with the 2016 presidential election were associated with increases in preterm birth among Latina women. This study determined whether periviable births (<26 weeks gestation), which exhibit extremely high rates of infant morbidity and mortality, among US Latina women increased above expected levels after the 2016 US presidential election.MethodsWe assigned singleton live births among Latina and non-Latina white women in the US to 96 monthly conception cohorts conceived from January 2009 through December 2016. We constructed risk ratios by dividing the rate of periviable birth among Latina women by the rate among non-Latina white women. We used time-series methods to determine if the risk ratio of periviable births in cohorts conceived by Latina women and exposed to the election of 2016 exceeded those expected from autocorrelation and calendar effects.ResultsWe found an outlying sequence of risk ratios among Latina women starting with the cohort conceived in April and ending with that conceived in November 2016. Increases in the ratios ranged from 0.07 above an expected of 1.61 for the cohort conceived in June, to 0.39 above an expected of 1.27 for the cohort conceived in April.ConclusionWe find that pregnancies in gestation at the time of the 2016 election among Latina women yielded more than expected periviable births. These findings support the argument that the prospect of anti-immigrant policies promised by the Trump campaign sufficiently stressed Latina women to affect the timing of birth.
| S-EPMC8128056 | biostudies-literature
Project description:Two studies conducted during the 2016 presidential campaign examined the dynamics of the objectivity illusion, the belief that the views of "my side" are objective while the views of the opposing side are the product of bias. In the first, a three-stage longitudinal study spanning the presidential debates, supporters of the two candidates exhibited a large and generally symmetrical tendency to rate supporters of the candidate they personally favored as more influenced by appropriate (i.e., "normative") considerations, and less influenced by various sources of bias than supporters of the opposing candidate. This study broke new ground by demonstrating that the degree to which partisans displayed the objectivity illusion predicted subsequent bias in their perception of debate performance and polarization in their political attitudes over time, as well as closed-mindedness and antipathy toward political adversaries. These associations, furthermore, remained significant even after controlling for baseline levels of partisanship. A second study conducted 2 d before the election showed similar perceptions of objectivity versus bias in ratings of blog authors favoring the candidate participants personally supported or opposed. These ratings were again associated with polarization and, additionally, with the willingness to characterize supporters of the opposing candidate as evil and likely to commit acts of terrorism. At a time of particular political division and distrust in America, these findings point to the exacerbating role played by the illusion of objectivity.
| S-EPMC7474588 | biostudies-literature
Project description:The dynamics and influence of fake news on Twitter during the 2016 US presidential election remains to be clarified. Here, we use a dataset of 171 million tweets in the five months preceding the election day to identify 30 million tweets, from 2.2 million users, which contain a link to news outlets. Based on a classification of news outlets curated by www.opensources.co , we find that 25% of these tweets spread either fake or extremely biased news. We characterize the networks of information flow to find the most influential spreaders of fake and traditional news and use causal modeling to uncover how fake news influenced the presidential election. We find that, while top influencers spreading traditional center and left leaning news largely influence the activity of Clinton supporters, this causality is reversed for the fake news: the activity of Trump supporters influences the dynamics of the top fake news spreaders.
| S-EPMC6315042 | biostudies-literature