566 research outputs found
Linking the oceans to public health: current efforts and future directions
This is the final version of the article. Available from BioMed Central via the DOI in this recordWe review the major linkages between the oceans and public health, focusing on exposures and potential health effects due to anthropogenic and natural factors including: harmful algal blooms, microbes, and chemical pollutants in the oceans; consumption of seafood; and flooding events. We summarize briefly the current state of knowledge about public health effects and their economic consequences; and we discuss priorities for future research.We find that:* There are numerous connections between the oceans, human activities, and human health that result in both positive and negative exposures and health effects (risks and benefits); and the study of these connections comprises a new interdisciplinary area, "oceans and human health."* The state of present knowledge about the linkages between oceans and public health varies. Some risks, such as the acute health effects caused by toxins associated with shellfish poisoning and red tide, are relatively well understood. Other risks, such as those posed by chronic exposure to many anthropogenic chemicals, pathogens, and naturally occurring toxins in coastal waters, are less well quantified. Even where there is a good understanding of the mechanism for health effects, good epidemiological data are often lacking. Solid data on economic and social consequences of these linkages are also lacking in most cases.* The design of management measures to address these risks must take into account the complexities of human response to warnings and other guidance, and the economic tradeoffs among different risks and benefits. Future research in oceans and human health to address public health risks associated with marine pathogens and toxins, and with marine dimensions of global change, should include epidemiological, behavioral, and economic components to ensure that resulting management measures incorporate effective economic and risk/benefit tradeoffs.Funding was provided in part by the NSF-NIEHS Oceans Centers at Woods Hole, University of Hawaii, University of Miami, and University of Washington, and the NOAA Oceans and Human Health Initiative Centers of Excellent in Charleston, Seattle and Milwaukee, the National Center for Environmental Health (NCEH) of the Centers for Disease Control and Prevention (CDC), and the WHOI Marine Policy Center. Grant numbers are: NIEHS P50 ES012742 and NSF OCE-043072 (HLKP, RJG, PH); NSF OCE-0432368 and NIEHS P50 ES12736 (LEF); NIEHS P50 ES012762 and NSF OCE-0434087 (EMF, AT, LRY); NSF OCE04-32479 and NIEHS P50 ES012740 (BAW
Menstrual cycle phase does not predict political conservatism
Recent authors have reported a relationship between women's fertility status, as indexed by menstrual cycle phase, and conservatism in moral, social and political values. We conducted a survey to test for the existence of a relationship between menstrual cycle day and conservatism. 2213 women reporting regular menstrual cycles provided data about their political views. Of these women, 2208 provided information about their cycle date, 1260 provided additional evidence of reliability in self-reported cycle date, and of these, 750 also indicated an absence of hormonal disruptors such as recent hormonal contraception use, breastfeeding or pregnancy. Cycle day was used to estimate day-specific fertility rate (probability of conception); political conservatism was measured via direct self-report and via responses to the "Moral Foundations” questionnaire. We also recorded relationship status, which has been reported to interact with menstrual cycle phase in determining political preferences. We found no evidence of a relationship between estimated cyclical fertility changes and conservatism, and no evidence of an interaction between relationship status and cyclical fertility in determining political attitudes. Our findings were robust to multiple inclusion/exclusion criteria and to different methods of estimating fertility and measuring conservatism. In summary, the relationship between cycle-linked reproductive parameters and conservatism may be weaker or less reliable than previously thought
Estrogen receptor-alpha (ER-alpha) and defects in uterine receptivity in women
Endometriosis is a disorder that affects 5% of the normal population but is present in up to 40% of women with pelvic pain and/or infertility. Recent evidence suggests that the endometrium of women with endometriosis exhibits progesterone insensitivity. One endometrial protein that fluctuates in response to progesterone is the estrogen receptor-alpha (ER alpha), being down-regulated at the time of peak progesterone secretion during the window of implantation. Here we demonstrate that the biomarker of uterine receptivity, beta 3 integrin subunit, is reduced or absent in some women with endometriosis and that such defects are accompanied by inappropriate over-expression of ER alpha during the mid-secretory phase. Using a well-differentiated endometrial cell line we showed that the beta 3 integrin protein is negatively regulated by estrogen and positively regulated by epidermal growth factor (EGF). By competing against estrogen with various selective estrogen receptor modulators (SERMs) and estrogen receptor agonists and antagonists, inhibition of expression of the beta 3 integrin by estrogen can be mitigated. In conclusion, we hypothesize that certain types of uterine receptivity defects may be caused by the loss of appropriate ER alpha down-regulation in the mid-secretory phase, leading to defects in uterine receptivity. Such changes might be effectively treated by timely administration of the appropriate anti-estrogens to artificially block ER alpha and restore normal patterns of gene expression. Such treatments will require further clinical studies
A nearly continuous measure of birth weight for gestational age using a United States national reference
BACKGROUND: Fully understanding the determinants and sequelae of fetal growth requires a continuous measure of birth weight adjusted for gestational age. Published United States reference data, however, provide estimates only of the median and lowest and highest 5(th )and 10(th )percentiles for birth weight at each gestational age. The purpose of our analysis was to create more continuous reference measures of birth weight for gestational age for use in epidemiologic analyses. METHODS: We used data from the most recent nationwide United States Natality datasets to generate multiple reference percentiles of birth weight at each completed week of gestation from 22 through 44 weeks. Gestational age was determined from last menstrual period. We analyzed data from 6,690,717 singleton infants with recorded birth weight and sex born to United States resident mothers in 1999 and 2000. RESULTS: Birth weight rose with greater gestational age, with increasing slopes during the third trimester and a leveling off beyond 40 weeks. Boys had higher birth weights than girls, later born children higher weights than firstborns, and infants born to non-Hispanic white mothers higher birth weights than those born to non-Hispanic black mothers. These results correspond well with previously published estimates reporting limited percentiles. CONCLUSIONS: Our method provides comprehensive reference values of birth weight at 22 through 44 completed weeks of gestation, derived from broadly based nationwide data. Other approaches require assumptions of normality or of a functional relationship between gestational age and birth weight, which may not be appropriate. These data should prove useful for researchers investigating the predictors and outcomes of altered fetal growth
Stochastic population growth in spatially heterogeneous environments
Classical ecological theory predicts that environmental stochasticity
increases extinction risk by reducing the average per-capita growth rate of
populations. To understand the interactive effects of environmental
stochasticity, spatial heterogeneity, and dispersal on population growth, we
study the following model for population abundances in patches: the
conditional law of given is such that when is small the
conditional mean of is approximately , where and are the abundance and per
capita growth rate in the -th patch respectivly, and is the
dispersal rate from the -th to the -th patch, and the conditional
covariance of and is approximately . We show for such a spatially extended population that if
is the total population abundance, then ,
the vector of patch proportions, converges in law to a random vector
as , and the stochastic growth rate equals the space-time average per-capita growth rate
\sum_i\mu_i\E[Y_\infty^i] experienced by the population minus half of the
space-time average temporal variation \E[\sum_{i,j}\sigma_{ij}Y_\infty^i
Y_\infty^j] experienced by the population. We derive analytic results for the
law of , find which choice of the dispersal mechanism produces an
optimal stochastic growth rate for a freely dispersing population, and
investigate the effect on the stochastic growth rate of constraints on
dispersal rates. Our results provide fundamental insights into "ideal free"
movement in the face of uncertainty, the persistence of coupled sink
populations, the evolution of dispersal rates, and the single large or several
small (SLOSS) debate in conservation biology.Comment: 47 pages, 4 figure
Parametric study of EEG sensitivity to phase noise during face processing
<b>Background: </b>
The present paper examines the visual processing speed of complex objects, here faces, by mapping the relationship between object physical properties and single-trial brain responses. Measuring visual processing speed is challenging because uncontrolled physical differences that co-vary with object categories might affect brain measurements, thus biasing our speed estimates. Recently, we demonstrated that early event-related potential (ERP) differences between faces and objects are preserved even when images differ only in phase information, and amplitude spectra are equated across image categories. Here, we use a parametric design to study how early ERP to faces are shaped by phase information. Subjects performed a two-alternative force choice discrimination between two faces (Experiment 1) or textures (two control experiments). All stimuli had the same amplitude spectrum and were presented at 11 phase noise levels, varying from 0% to 100% in 10% increments, using a linear phase interpolation technique. Single-trial ERP data from each subject were analysed using a multiple linear regression model.
<b>Results: </b>
Our results show that sensitivity to phase noise in faces emerges progressively in a short time window between the P1 and the N170 ERP visual components. The sensitivity to phase noise starts at about 120–130 ms after stimulus onset and continues for another 25–40 ms. This result was robust both within and across subjects. A control experiment using pink noise textures, which had the same second-order statistics as the faces used in Experiment 1, demonstrated that the sensitivity to phase noise observed for faces cannot be explained by the presence of global image structure alone. A second control experiment used wavelet textures that were matched to the face stimuli in terms of second- and higher-order image statistics. Results from this experiment suggest that higher-order statistics of faces are necessary but not sufficient to obtain the sensitivity to phase noise function observed in response to faces.
<b>Conclusion: </b>
Our results constitute the first quantitative assessment of the time course of phase information processing by the human visual brain. We interpret our results in a framework that focuses on image statistics and single-trial analyses
Age-related delay in information accrual for faces: Evidence from a parametric, single-trial EEG approach
Background: In this study, we quantified age-related changes in the time-course of face processing
by means of an innovative single-trial ERP approach. Unlike analyses used in previous studies, our
approach does not rely on peak measurements and can provide a more sensitive measure of
processing delays. Young and old adults (mean ages 22 and 70 years) performed a non-speeded
discrimination task between two faces. The phase spectrum of these faces was manipulated
parametrically to create pictures that ranged between pure noise (0% phase information) and the
undistorted signal (100% phase information), with five intermediate steps.
Results: Behavioural 75% correct thresholds were on average lower, and maximum accuracy was
higher, in younger than older observers. ERPs from each subject were entered into a single-trial
general linear regression model to identify variations in neural activity statistically associated with
changes in image structure. The earliest age-related ERP differences occurred in the time window
of the N170. Older observers had a significantly stronger N170 in response to noise, but this age
difference decreased with increasing phase information. Overall, manipulating image phase
information had a greater effect on ERPs from younger observers, which was quantified using a
hierarchical modelling approach. Importantly, visual activity was modulated by the same stimulus
parameters in younger and older subjects. The fit of the model, indexed by R2, was computed at
multiple post-stimulus time points. The time-course of the R2 function showed a significantly slower
processing in older observers starting around 120 ms after stimulus onset. This age-related delay
increased over time to reach a maximum around 190 ms, at which latency younger observers had
around 50 ms time lead over older observers.
Conclusion: Using a component-free ERP analysis that provides a precise timing of the visual
system sensitivity to image structure, the current study demonstrates that older observers
accumulate face information more slowly than younger subjects. Additionally, the N170 appears to
be less face-sensitive in older observers
Association of Fidaxomicin with C. difficile spores: Effects of Persistence on Subsequent Spore Recovery, Outgrowth and Toxin Production.
Background: We have previously shown that fidaxomicin instillation prevents spore recovery in an in-vitro gut model, whereas vancomycin does not. The reasons for this are unclear. Here, we have investigated persistence of fidaxomicin and vancomycin on C. difficile spores, and examined post-antibiotic exposure spore recovery, outgrowth and toxin production. Methods: Prevalent UK C. difficile ribotypes (n=10) were incubated with 200mg/L fidaxomicin, vancomycin or a non-antimicrobial containing control for 1 h in faecal filtrate or Phosphate Buffered Saline. Spores were washed three times with faecal filtrate or phosphate buffered saline, and residual spore-associated antimicrobial activity was determined by bioassay. For three ribotypes (027, 078, 015), antimicrobial-exposed, faecal filtrate-washed spores and controls were inoculated into broth. Viable vegetative and spore counts were enumerated on CCEYL agar. Percentage phase bright spores, phase dark spores and vegetative cells were enumerated by phase contrast microscopy at 0, 3, 6, 24 and 48 h post-inoculation. Toxin levels (24 and 48h) were determined by cell cytotoxicity assay. Results: Fidaxomicin, but not vancomycin persisted on spores of all ribotypes following washing in saline (mean=10.1mg/L; range= 4.0-14mg/L) and faecal filtrate (mean =17.4mg/L; 8.4-22.1mg/L). Outgrowth and proliferation rates of vancomycin-exposed spores were similar to controls, whereas fidaxomicin-exposed spores showed no vegetative cell growth after 24 and 48 h. At 48h, toxin levels averaged 3.7 and 3.3 relative units (RU) in control and vancomycin-exposed samples, respectively, but were undetectable in fidaxomicin-exposed samples. Conclusion: Fidaxomicin persists on C. difficile spores, whereas vancomycin does not. This persistence prevents subsequent growth and toxin production in vitro. This may have implications on spore viability, thereby impacting CDI recurrence and transmission rates
Social Networks among Elderly Women: Implications for Health Education Practice
The general aim of the present study was to examine and help clarify the properties of the distinctions between social networks and social support, their relationship to health status, and their impli cations for health education practice. More specifically, a secondary data analysis was conducted with 130 white women, community resi dents, between the ages of 60 and 68, which examined the relationship between psychological well-being and social network characteristics. These characteristics are categorized along three broad dimensions: structure—links in the overall network (size and density); interaction— nature of the linkages themselves (frequency, homogeneity, content, reciprocity, intensity, and dispersion); and functions which networks provide (affective support and instrumental support). A combination was made and relative strength investigated of several network char acteristics representative of the quality of interactions (i. e., reciprocal affective support, intensity, and affective support) and those repre senting the quantity of interactions (i.e., size, density, and frequency).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67277/2/10.1177_109019818301000304.pd
Climate change: what competencies and which medical education and training approaches?
<p>Abstract</p> <p>Background</p> <p>Much research has been devoted to identifying healthcare needs in a climate-changing world. However, while there are now global and national policy statements about the importance of health workforce development for climate change, little has been published about what competencies might be demanded of practitioners in a climate-changing world. In such a context, this debate and discussion paper aims to explore the nature of key competencies and related opportunities for teaching climate change in medical education and training. Particular emphasis is made on preparation for practice in rural and remote regions likely to be greatly affected by climate change.</p> <p>Discussion</p> <p>The paper describes what kinds of competencies for climate change might be included in medical education and training. It explores which curricula, teaching, learning and assessment approaches might be involved. Rather than arguing for major changes to medical education and training, this paper explores well established precedents to offer practical suggestions for where a particular kind of literacy--eco-medical literacy--and related competencies could be naturally integrated into existing elements of medical education and training.</p> <p>Summary</p> <p>The health effects of climate change have, generally, not yet been integrated into medical education and training systems. However, the necessary competencies could be taught by building on existing models, best practice and innovative traditions in medicine. Even in crowded curricula, climate change offers an opportunity to reinforce and extend understandings of how interactions between people and place affect health.</p
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