Communicating choice: an exploration of mothers' experiences of birth

YesObjective: This article gives an in-depth insight into the ways in which communication between midwives and the birthing woman shape the birth experience. Background: Birth is a significant life event for many women that can have profound, long-lasting effects on how they see themselves as women and mothers. Within the literature the importance of control over the birth experience and the support that the birthing woman receives from midwives is stressed. Methods: Six women who had recently given birth participated in one-to-one semi-structured interviews designed to explore the kinds of support they received before, during and after their birth. An inductive thematic analysis was employed in order to identify and explore key issues which ran throughout the interviews. Results: Within the interviews the importance of being an active mother, someone who made decisions in relation to her labour, was stressed. The analysis explores the ways in which communication style and compassionate care either enabled or prevented women from adopting the position of ‘active’ mother. Conclusion: It is argued that a personal connection with midwives and clear and open communication which places the birthing woman in a position of control are key to positive birth experiences

HIV-1 Tat causes cognitive deficits and selective loss of parvalbumin, somatostatin, and neuronal nitric oxide synthase expressing hippocampal CA1 interneuron subpopulations

Memory deficits are characteristic of HIV-associated neurocognitive disorders (HAND) and co-occur with hippocampal pathology. The HIV-1 transactivator of transcription (Tat), a regulatory protein, plays a significant role in these events, but the cellular mechanisms involved are poorly understood. Within the hippocampus, diverse populations of interneurons form complex networks; even subtle disruptions can drastically alter synaptic output, resulting in behavioral dysfunction. We hypothesized that HIV-1 Tat would impair cognitive behavior and injure specific hippocampal interneuron subtypes. Male transgenic mice that inducibly expressed HIV-1 Tat (or non-expressing controls) were assessed for cognitive behavior or had hippocampal CA1 subregions evaluated via interneuron subpopulation markers. Tat exposure decreased spatial memory in a Barnes maze and mnemonic performance in a novel object recognition test. Tat reduced the percentage of neurons expressing neuronal nitric oxide synthase (nNOS) without neuropeptide Y immunoreactivity in the stratum pyramidale and the stratum radiatum, parvalbumin in the stratum pyramidale, and somatostatin in the stratum oriens, which are consistent with reductions in interneuron-specific interneuron type 3 (IS3), bistratified, and oriens-lacunosum-moleculare interneurons, respectively. The findings reveal that an interconnected ensemble of CA1 nNOS-expressing interneurons, the IS3 cells, as well as subpopulations of parvalbumin- and somatostatin-expressing interneurons are preferentially vulnerable to HIV-1 Tat. Importantly, the susceptible interneurons form a microcircuit thought to be involved in feedback inhibition of CA1 pyramidal cells and gating of CA1 pyramidal cell inputs. The identification of vulnerable CA1 hippocampal interneurons may provide novel insight into the basic mechanisms underlying key functional and neurobehavioral deficits associated with HAND

The Structure of Pre-transitional Protoplanetary Disks I: Radiative Transfer Modeling of the Disk+Cavity in the PDS 70 system

Through detailed radiative transfer modeling, we present a disk+cavity model to simultaneously explain both the SED and Subaru H-band polarized light imaging for the pre-transitional protoplanetary disk PDS 70. Particularly, we are able to match not only the radial dependence, but also the absolute scale, of the surface brightness of the scattered light. Our disk model has a cavity 65 AU in radius, which is heavily depleted of sub-micron-sized dust grains, and a small residual inner disk which produces a weak but still optically thick NIR excess in the SED. To explain the contrast of the cavity edge in the Subaru image, a factor of ~1000 depletion for the sub-micron-sized dust inside the cavity is required. The total dust mass of the disk may be on the order of 1e-4 M_sun, only weakly constrained due to the lack of long wavelength observations and the uncertainties in the dust model. The scale height of the sub-micron-sized dust is ~6 AU at the cavity edge, and the cavity wall is optically thick in the vertical direction at H-band. PDS 70 is not a member of the class of (pre-)transitional disks identified by Dong et al. (2012), whose members only show evidence of the cavity in the millimeter-sized dust but not the sub-micron-sized dust in resolved images. The two classes of (pre-)transitional disks may form through different mechanisms, or they may just be at different evolution stages in the disk clearing process.Comment: 28 pages (single column), 7 figures, 1 table, ApJ accepte

\textsc{MaGe} - a {\sc Geant4}-based Monte Carlo Application Framework for Low-background Germanium Experiments

We describe a physics simulation software framework, MAGE, that is based on the GEANT4 simulation toolkit. MAGE is used to simulate the response of ultra-low radioactive background radiation detectors to ionizing radiation, specifically the MAJORANA and GERDA neutrinoless double-beta decay experiments. MAJORANA and GERDA use high-purity germanium detectors to search for the neutrinoless double-beta decay of 76Ge, and MAGE is jointly developed between these two collaborations. The MAGE framework contains the geometry models of common objects, prototypes, test stands, and the actual experiments. It also implements customized event generators, GEANT4 physics lists, and output formats. All of these features are available as class libraries that are typically compiled into a single executable. The user selects the particular experimental setup implementation at run-time via macros. The combination of all these common classes into one framework reduces duplication of efforts, eases comparison between simulated data and experiment, and simplifies the addition of new detectors to be simulated. This paper focuses on the software framework, custom event generators, and physics lists.Comment: 12 pages, 6 figure

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

© Copyright © 2020 Sandifer, Knapp, Lichtveld, Manley, Abramson, Caffey, Cochran, Collier, Ebi, Engel, Farrington, Finucane, Hale, Halpern, Harville, Hart, Hswen, Kirkpatrick, McEwen, Morris, Orbach, Palinkas, Partyka, Porter, Prather, Rowles, Scott, Seeman, Solo-Gabriele, Svendsen, Tincher, Trtanj, Walker, Yehuda, Yip, Yoskowitz and Singer. The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

© Copyright © 2020 Sandifer, Knapp, Lichtveld, Manley, Abramson, Caffey, Cochran, Collier, Ebi, Engel, Farrington, Finucane, Hale, Halpern, Harville, Hart, Hswen, Kirkpatrick, McEwen, Morris, Orbach, Palinkas, Partyka, Porter, Prather, Rowles, Scott, Seeman, Solo-Gabriele, Svendsen, Tincher, Trtanj, Walker, Yehuda, Yip, Yoskowitz and Singer. The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop

Factors affecting residency rank-listing: A Maxdiff survey of graduating Canadian medical students

<p>Abstract</p> <p>Background</p> <p>In Canada, graduating medical students consider many factors, including geographic, social, and academic, when ranking residency programs through the Canadian Residency Matching Service (CaRMS). The relative significance of these factors is poorly studied in Canada. It is also unknown how students differentiate between their top program choices. This survey study addresses the influence of various factors on applicant decision making.</p> <p>Methods</p> <p>Graduating medical students from all six Ontario medical schools were invited to participate in an online survey available for three weeks prior to the CaRMS match day in 2010. Max-Diff discrete choice scaling, multiple choice, and drop-list style questions were employed. The Max-Diff data was analyzed using a scaled simple count method. Data for how students distinguish between top programs was analyzed as percentages. Comparisons were made between male and female applicants as well as between family medicine and specialist applicants; statistical significance was determined by the Mann-Whitney test.</p> <p>Results</p> <p>In total, 339 of 819 (41.4%) eligible students responded. The variety of clinical experiences and resident morale were weighed heavily in choosing a residency program; whereas financial incentives and parental leave attitudes had low influence. Major reasons that applicants selected their first choice program over their second choice included the distance to relatives and desirability of the city. Both genders had similar priorities when selecting programs. Family medicine applicants rated the variety of clinical experiences more importantly; whereas specialty applicants emphasized academic factors more.</p> <p>Conclusions</p> <p>Graduating medical students consider program characteristics such as the variety of clinical experiences and resident morale heavily in terms of overall priority. However, differentiation between their top two choice programs is often dependent on social/geographic factors. The results of this survey will contribute to a better understanding of the CaRMS decision making process for both junior medical students and residency program directors.</p

Sociodemographic Variation in Children's Health Behaviors During the COVID-19 Pandemic

Background: Societal changes during the COVID-19 pandemic may affect children's health behaviors and exacerbate disparities. This study aimed to describe children's health behaviors during the COVID-19 pandemic, how they vary by sociodemographic characteristics, and the extent to which parent coping strategies mitigate the impact of pandemic-related financial strain on these behaviors. Methods: This study used pooled data from 50 cohorts in the Environmental influences on Child Health Outcomes Program. Children or parent proxies reported sociodemographic characteristics, health behaviors, and parent coping strategies. Results: Of 3315 children aged 3-17 years, 49% were female and 57% were non-Hispanic white. Children of parents who reported food access as a source of stress were 35% less likely to engage in a higher level of physical activity. Children of parents who changed their work schedule to care for their children had 82 fewer min/day of screen time and 13 more min/day of sleep compared with children of parents who maintained their schedule. Parents changing their work schedule were also associated with a 31% lower odds of the child consuming sugar-sweetened beverages. Conclusions: Parents experiencing pandemic-related financial strain may need additional support to promote healthy behaviors. Understanding how changes in parent work schedules support shorter screen time and longer sleep duration can inform future interventions

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected