Get your facts right : preschoolers systematically extend both object names and category-relevant facts

There is an ongoing debate over the extent to which language development shares common processing mechanisms with other domains of learning. It is well-established that toddlers will systematically extend object labels to similarly-shaped category exemplars (e.g., Landau, Smith, & Jones, 1988; Markman & Hutchinson, 1984). However, previous research is inconclusive as to whether young children will similarly extend factual information about an object to other category members. We explicitly contrast facts varying in category relevance, and test for extension using two different tasks. Three- to four-year-olds (N = 61) were provided with one of three types of information about a single novel object: a category-relevant fact (‘it’s from a place called Modi’), a category-irrelevant fact (‘my uncle gave it to me’), or an object label (‘it’s called a Modi’). At test, children provided with the object name or category-relevant fact were significantly more likely to display systematic category extension than children who learnt the category-irrelevant fact. Our findings contribute to a growing body of evidence that the mechanisms responsible for word learning may be domain-general in nature

Occupational Transitions of Family Caregivers of Loved Ones with Dementia

Purpose: The primary purpose of this study was to explore how family caregivers of people with dementia experience transitions in occupations as they assume the caregiver role. Because unpaid family caregivers play a vital part in the scheme of health care, it is important to understand their supports, their perceptions of themselves as caregivers, and the impact of caregiving on relationships, identity, and physical and mental health. Many researchers have studied the effects of caregiver burden, yet minimal attention has been given to the lived experiences of caregiving on their daily roles and routines. Methods: A qualitative descriptive design was used to obtain data from eight caregivers through semi-structured interviews. Content analysis was then applied to all data. Results: The following categories were identified: 1) Benefits, which consisted of the positive experiences gained as a result of caregiving; 2) Consequences, which included the physical, mental, and emotional burdens attached to being a caregiver; and 3) Supports, which were positive resources utilized by caregivers to be both better prepared to care for their loved ones and more capable within their caregiving role. Conclusion: Findings confirm that unpaid caregivers of loved ones with dementia experience dramatic changes in many aspects of their lives. Caregivers felt a strong responsibility as a family member to provide care for their loved ones. It has been found that caregivers spend most of their time engaged in caregiver related tasks, consequently impacting their occupational balance and ability to engage in what they would like to do. Health care providers must be mindful of the changes that caregivers experience, by assisting them to increase supports, anticipate the consequences, and recognize and value the benefits

Temporal trends and forecasting of COVID-19 hospitalisations and deaths in Scotland using a national real-time patient-level data platform: a statistical modelling study

This study is part of the EAVE II project. EAVE II is funded by the MRC (MR/R008345/1) with the support of BREATHE—The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. Additional support has been provided through Public Health Scotland and Scottish Government Director General Health and Social Care. The original EAVE project was funded by the NIHR Health Technology Assessment programme (11/46/23).Background   As the COVID-19 pandemic continues, national-level surveillance platforms with real-time individual person-level data are required to monitor and predict the epidemiological and clinical profile of COVID-19 and inform public health policy. We aimed to create a national dataset of patient-level data in Scotland to identify temporal trends and COVID-19 risk factors, and to develop a novel statistical prediction model to forecast COVID-19-related deaths and hospitalisations during the second wave.  Methods   We established a surveillance platform to monitor COVID-19 temporal trends using person-level primary care data (including age, sex, socioeconomic status, urban or rural residence, care home residence, and clinical risk factors) linked to data on SARS-CoV-2 RT-PCR tests, hospitalisations, and deaths for all individuals resident in Scotland who were registered with a general practice on Feb 23, 2020. A Cox proportional hazards model was used to estimate the association between clinical risk groups and time to hospitalisation and death. A survival prediction model derived from data from March 1 to June 23, 2020, was created to forecast hospital admissions and deaths from October to December, 2020. We fitted a generalised additive spline model to daily SARS-CoV-2 cases over the previous 10 weeks and used this to create a 28-day forecast of the number of daily cases. The age and risk group pattern of cases in the previous 3 weeks was then used to select a stratified sample of individuals from our cohort who had not previously tested positive, with future cases in each group sampled from a multinomial distribution. We then used their patient characteristics (including age, sex, comorbidities, and socioeconomic status) to predict their probability of hospitalisation or death.  Findings   Our cohort included 5 384 819 people, representing 98·6% of the entire estimated population residing in Scotland during 2020. Hospitalisation and death among those testing positive for SARS-CoV-2 between March 1 and June 23, 2020, were associated with several patient characteristics, including male sex (hospitalisation hazard ratio [HR] 1·47, 95% CI 1·38–1·57; death HR 1·62, 1·49–1·76) and various comorbidities, with the highest hospitalisation HR found for transplantation (4·53, 1·87–10·98) and the highest death HR for myoneural disease (2·33, 1·46–3·71). For those testing positive, there were decreasing temporal trends in hospitalisation and death rates. The proportion of positive tests among older age groups (>40 years) and those with at-risk comorbidities increased during October, 2020. On Nov 10, 2020, the projected number of hospitalisations for Dec 8, 2020 (28 days later) was 90 per day (95% prediction interval 55–125) and the projected number of deaths was 21 per day (12–29). Interpretation The estimated incidence of SARS-CoV-2 infection based on positive tests recorded in this unique data resource has provided forecasts of hospitalisation and death rates for the whole of Scotland. These findings were used by the Scottish Government to inform their response to reduce COVID-19-related morbidity and mortality.Publisher PDFPeer reviewe

The WiggleZ Dark Energy Survey: measuring the cosmic expansion history using the Alcock-Paczynski test and distant supernovae

Astronomical observations suggest that today's Universe is dominated by a dark energy of unknown physical origin. One of the most notable consequences in many models is that dark energy should cause the expansion of the Universe to accelerate: but the expansion rate as a function of time has proven very difficult to measure directly. We present a new determination of the cosmic expansion history by combining distant supernovae observations with a geometrical analysis of large-scale galaxy clustering within the WiggleZ Dark Energy Survey, using the Alcock-Paczynski test to measure the distortion of standard spheres. Our result constitutes a robust and non-parametric measurement of the Hubble expansion rate as a function of time, which we measure with 10-15% precision in four bins within the redshift range 0.1 < z < 0.9. We demonstrate that the cosmic expansion is accelerating, in a manner independent of the parameterization of the cosmological model (although assuming cosmic homogeneity in our data analysis). Furthermore, we find that this expansion history is consistent with a cosmological-constant dark energy.Comment: 13 pages, 7 figures, accepted for publication by MNRA

First dose ChAdOx1 and BNT162b2 COVID-19 vaccinations and cerebral venous sinus thrombosis : a pooled self-controlled case series study of 11.6 million individuals in England, Scotland, and Wales

Funding: This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20029, AS). EAVE II is funded by the Medical Research Council (https://mrc.ukri.org/) (UKRI MC_PC 19075, AS) with the support of BREATHE, The Health Data Research Hub for Respiratory Health (MC_PC_19004, AS), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. This work was supported by the Con-COV team funded by the Medical Research Council (grant number: MR/V028367/1, RL). This work was supported by Health Data Research UK, which receives its funding from HDR UK Ltd (HDR-9006, RL) funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust. This work was supported by the ADR Wales programme of work (https://www.adruk.org/). ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1, RL). SVK acknowledges funding from NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02, SVK), the MRC (MC_UU_00022/2, SVK), and the Scottish Government Chief Scientist Office (SPHSU17, SVK).Background : Several countries restricted the administration of ChAdOx1 to older age groups in 2021 over safety concerns following case reports and observed versus expected analyses suggesting a possible association with cerebral venous sinus thrombosis (CVST). Large datasets are required to precisely estimate the association between Coronavirus Disease 2019 (COVID-19) vaccination and CVST due to the extreme rarity of this event. We aimed to accomplish this by combining national data from England, Scotland, and Wales. Methods and findings : We created data platforms consisting of linked primary care, secondary care, mortality, and virological testing data in each of England, Scotland, and Wales, with a combined cohort of 11,637,157 people and 6,808,293 person years of follow-up. The cohort start date was December 8, 2020, and the end date was June 30, 2021. The outcome measure we examined was incident CVST events recorded in either primary or secondary care records. We carried out a self-controlled case series (SCCS) analysis of this outcome following first dose vaccination with ChAdOx1 and BNT162b2. The observation period consisted of an initial 90-day reference period, followed by a 2-week prerisk period directly prior to vaccination, and a 4-week risk period following vaccination. Counts of CVST cases from each country were tallied, then expanded into a full dataset with 1 row for each individual and observation time period. There was a combined total of 201 incident CVST events in the cohorts (29.5 per million person years). There were 81 CVST events in the observation period among those who a received first dose of ChAdOx1 (approximately 16.34 per million doses) and 40 for those who received a first dose of BNT162b2 (approximately 12.60 per million doses). We fitted conditional Poisson models to estimate incidence rate ratios (IRRs). Vaccination with ChAdOx1 was associated with an elevated risk of incident CVST events in the 28 days following vaccination, IRR = 1.93 (95% confidence interval (CI) 1.20 to 3.11). We did not find an association between BNT162b2 and CVST in the 28 days following vaccination, IRR = 0.78 (95% CI 0.34 to 1.77). Our study had some limitations. The SCCS study design implicitly controls for variables that are constant over the observation period, but also assumes that outcome events are independent of exposure. This assumption may not be satisfied in the case of CVST, firstly because it is a serious adverse event, and secondly because the vaccination programme in the United Kingdom prioritised the clinically extremely vulnerable and those with underlying health conditions, which may have caused a selection effect for individuals more prone to CVST. Although we pooled data from several large datasets, there was still a low number of events, which may have caused imprecision in our estimates. Conclusions : In this study, we observed a small elevated risk of CVST events following vaccination with ChAdOx1, but not BNT162b2. Our analysis pooled information from large datasets from England, Scotland, and Wales. This evidence may be useful in risk–benefit analyses of vaccine policies and in providing quantification of risks associated with vaccination to the general public.Publisher PDFPeer reviewe

SN 2022jox: An extraordinarily ordinary Type II SN with Flash Spectroscopy

We present high cadence optical and ultraviolet observations of the Type II supernova (SN), SN 2022jox which exhibits early spectroscopic high ionization flash features of \ion{H}{1}, \ion{He}{2}, \ion{C}{4}, and \ion{N}{4} that disappear within the first few days after explosion. SN 2022jox was discovered by the Distance Less than 40 Mpc (DLT40) survey $\sim$0.75 days after explosion with followup spectra and UV photometry obtained within minutes of discovery. The SN reached a peak brightness of M$_V \sim$ $-$17.3 mag, and has an estimated $^{56}$Ni mass of 0.04 M$_{\odot}$, typical values for normal Type II SNe. The modeling of the early lightcurve and the strong flash signatures present in the optical spectra indicate interaction with circumstellar material (CSM) created from a progenitor with a mass loss rate of $\dot{M} \sim 10^{-3}-10^{-2}\ M_\odot\ \mathrm{yr}^{-1}$. There may also be some indication of late-time CSM interaction in the form of an emission line blueward of H$\alpha$ seen in spectra around 200 days. The mass-loss rate is much higher than the values typically associated with quiescent mass loss from red supergiants, the known progenitors of Type II SNe, but is comparable to inferred values from similar core collapse SNe with flash features, suggesting an eruptive event or a superwind in the progenitor in the months or years before explosion.Comment: Submitted to Ap

Social and ethical checkpoints for bottom-up synthetic biology, or protocells

An alternative to creating novel organisms through the traditional “top-down” approach to synthetic biology involves creating them from the “bottom up” by assembling them from non-living components; the products of this approach are called “protocells.” In this paper we describe how bottom-up and top-down synthetic biology differ, review the current state of protocell research and development, and examine the unique ethical, social, and regulatory issues raised by bottom-up synthetic biology. Protocells have not yet been developed, but many expect this to happen within the next five to ten years. Accordingly, we identify six key checkpoints in protocell development at which particular attention should be given to specific ethical, social and regulatory issues concerning bottom-up synthetic biology, and make ten recommendations for responsible protocell science that are tied to the achievement of these checkpoints

COVID-19 hospital admissions and deaths after BNT162b2 and ChAdOx1 nCoV-19 vaccinations in 2·57 million people in Scotland (EAVE II):a prospective cohort study

EAVE II is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE—The Health Data Research Hub for Respiratory Health [MC_PC_19004], which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. UA, CM, AA-L, and AFF acknowledge funding from Chief Scientist Office Rapid Research in COVID-19 programme (COV/SAN/20/06) and Health Data Research UK (measuring and understanding multimorbidity using routine data in the UK—HDR-9006; CFC0110). SVK acknowledges funding from a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government's Chief Scientist Office (SPHSU17). SJS is funded by a Wellcome Trust Clinical Career Development Fellowship (209560/Z/17/Z).Background  The UK COVID-19 vaccination programme has prioritised vaccination of those at the highest risk of COVID-19 mortality and hospitalisation. The programme was rolled out in Scotland during winter 2020–21, when SARS-CoV-2 infection rates were at their highest since the pandemic started, despite social distancing measures being in place. We aimed to estimate the frequency of COVID-19 hospitalisation or death in people who received at least one vaccine dose and characterise these individuals. Methods  We conducted a prospective cohort study using the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) national surveillance platform, which contained linked vaccination, primary care, RT-PCR testing, hospitalisation, and mortality records for 5·4 million people (around 99% of the population) in Scotland. Individuals were followed up from receiving their first dose of the BNT162b2 (Pfizer–BioNTech) or ChAdOx1 nCoV-19 (Oxford–AstraZeneca) COVID-19 vaccines until admission to hospital for COVID-19, death, or the end of the study period on April 18, 2021. We used a time-dependent Poisson regression model to estimate rate ratios (RRs) for demographic and clinical factors associated with COVID-19 hospitalisation or death 14 days or more after the first vaccine dose, stratified by vaccine type. Findings Between Dec 8, 2020, and April 18, 2021, 2 572 008 individuals received their first dose of vaccine—841 090 (32·7%) received BNT162b2 and 1 730 918 (67·3%) received ChAdOx1. 1196 (<0·1%) individuals were admitted to hospital or died due to COVID-19 illness (883 hospitalised, of whom 228 died, and 313 who died due to COVID-19 without hospitalisation) 14 days or more after their first vaccine dose. These severe COVID-19 outcomes were associated with older age (≥80 years vs 18–64 years adjusted RR 4·75, 95% CI 3·85–5·87), comorbidities (five or more risk groups vs less than five risk groups 4·24, 3·34–5·39), hospitalisation in the previous 4 weeks (3·00, 2·47–3·65), high-risk occupations (ten or more previous COVID-19 tests vs less than ten previous COVID-19 tests 2·14, 1·62–2·81), care home residence (1·63, 1·32–2·02), socioeconomic deprivation (most deprived quintile vs least deprived quintile 1·57, 1·30–1·90), being male (1·27, 1·13–1·43), and being an ex-smoker (ex-smoker vs non-smoker 1·18, 1·01–1·38). A history of COVID-19 before vaccination was protective (0·40, 0·29–0·54). Interpretation COVID-19 hospitalisations and deaths were uncommon 14 days or more after the first vaccine dose in this national analysis in the context of a high background incidence of SARS-CoV-2 infection and with extensive social distancing measures in place. Sociodemographic and clinical features known to increase the risk of severe disease in unvaccinated populations were also associated with severe outcomes in people receiving their first dose of vaccine and could help inform case management and future vaccine policy formulation.Publisher PDFPeer reviewe

SPLUS J142445.34-254247.1: An R-Process Enhanced, Actinide-Boost, Extremely Metal-Poor star observed with GHOST

We report on the chemo-dynamical analysis of SPLUS J142445.34-254247.1, an extremely metal-poor halo star enhanced in elements formed by the rapid neutron-capture process. This star was first selected as a metal-poor candidate from its narrow-band S-PLUS photometry and followed up spectroscopically in medium-resolution with Gemini South/GMOS, which confirmed its low-metallicity status. High-resolution spectroscopy was gathered with GHOST at Gemini South, allowing for the determination of chemical abundances for 36 elements, from carbon to thorium. At [Fe/H]=-3.39, SPLUS J1424-2542 is one of the lowest metallicity stars with measured Th and has the highest logeps(Th/Eu) observed to date, making it part of the "actinide-boost" category of r-process enhanced stars. The analysis presented here suggests that the gas cloud from which SPLUS J1424-2542 was formed must have been enriched by at least two progenitor populations. The light-element (Z<=30) abundance pattern is consistent with the yields from a supernova explosion of metal-free stars with 11.3-13.4 Msun, and the heavy-element (Z>=38) abundance pattern can be reproduced by the yields from a neutron star merger (1.66Msun and 1.27Msun) event. A kinematical analysis also reveals that SPLUS J1424-2542 is a low-mass, old halo star with a likely in-situ origin, not associated with any known early merger events in the Milky Way.Comment: 26 pages, 11 figures, accepted for publication on Ap

Developing an online learning community for mental health professionals and service users: a discursive analysis

<p>Abstract</p> <p>Background</p> <p>There is increasing interest in online collaborative learning tools in health education, to reduce costs, and to offer alternative communication opportunities. Patients and students often have extensive experience of using the Internet for health information and support, and many health organisations are increasingly trying out online tools, while many healthcare professionals are unused to, and have reservations about, online interaction.</p> <p>Methods</p> <p>We ran three week-long collaborative learning courses, in which 19 mental health professionals (MHPs) and 12 mental health service users (MHSUs) participated. Data were analysed using a discursive approach to consider the ways in which participants interacted, and how this contributed to the goal of online learning about using Internet technologies for mental health practice.</p> <p>Results</p> <p>MHSUs and MHPs were able to discuss issues together, listening to the views of the other stakeholders. Discussions on synchronous format encouraged participation by service users while the MHPs showed a preference for an asynchronous format with longer, reasoned postings. Although participants regularly drew on their MHP or MHSU status in discussions, and participants typically drew on either a medical expert discourse or a "lived experience" discourse, there was a blurred boundary as participants shifted between these positions.</p> <p>Conclusions</p> <p>The anonymous format was successful in that it produced a "co-constructed asymmetry" which permitted the MHPs and MHSUs to discuss issues online, listening to the views of other stakeholders. Although anonymity was essential for this course to 'work' at all, the recourse to expert or lay discourses demonstrates that it did not eliminate the hierarchies between teacher and learner, or MHP and MHSU. The mix of synchronous and asynchronous formats helped MHSUs to contribute. Moderators might best facilitate service user experience by responding within an experiential discourse rather than an academic one.</p