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As part of the Pathology, Alzheimer’s and Related Dementias Study, we conducted uniform structured interviews with knowledgeable informants (72% children) of 1,493 older (age > 65) Brazilian decedents.
The interview included measures of social isolation (number of family and friends in at least monthly contact with decedent), emotional isolation (short form of UCLA Loneliness Scale), and major depression plus the informant portion of the Clinical Dementia Rating Scale to diagnose dementia and its precursor, mild cognitive impairment (MCI).
Decedents had a median social network size of 8.0 (interquartile range = 9.0) and a median loneliness score of 0.0 (interquartile range = 1.0). On the Clinical Dementia Rating Scale, 947 persons had no cognitive impairment, 122 had MCI, and 424 had dementia. In a logistic regression model adjusted for age, education, sex, and race, both smaller network size (odds ratio [OR] = 0.975; 95% confidence interval [CI]: 0.962, 0.989) and higher loneliness (OR = 1.145; 95% CI: 1.060, 1.237) were associated with higher likelihood of dementia. These associations persisted after controlling for depression (present in 10.4%) and did not vary by race. After controlling for depression, neither network size nor loneliness was related to MCI.
Social and emotional isolation are associated with higher likelihood of dementia in older black and white Brazilians.
Much of our current understanding about novel coronavirus disease 2019 (COVID-19) comes from hospitalised patients. However, the spectrum of mild and subclinical disease has implications for population-level screening and control. Forty-nine participants were recruited from a group of 99 adults repatriated from a cruise ship with a high incidence of COVID-19. Respiratory and rectal swabs were tested by polymerase chain reaction (PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Sera were tested for anti-SARS-CoV-2 antibodies by enzyme-linked immunosorbent assay (ELISA) and microneutralisation assay. Symptoms, viral shedding and antibody response were examined. Forty-five participants (92%) were considered cases based on either positive PCR or positive ELISA for immunoglobulin G. Forty-two percent of cases were asymptomatic. Only 15% of symptomatic cases reported fever. Serial respiratory and rectal swabs were positive for 10% and 5% of participants respectively about 3 weeks after median symptom onset. Cycle threshold values were high (range 31–45). Attempts to isolate live virus were unsuccessful. The presence of symptoms was not associated with demographics, comorbidities or antibody response. In closed settings, incidence of COVID-19 could be almost double that suggested by symptom-based screening. Serology may be useful in diagnosis of mild disease and in aiding public health investigations.
To analyse associations between brain morphology and longitudinal and cross-sectional measures of outcomes in schizophrenia in a general population sample.
The sample was the Northern Finland 1966 Birth Cohort. In 1999–2001, structural brain MRI and measures of clinical and functional outcomes were analysed for 54 individuals with schizophrenia around the age of 34. Sex, total grey matter, duration of illness and the use of antipsychotic medication were used as covariates.
After controlling for multiple covariates, increased density of the left limbic area was associated with less hospitalisations and increased total white matter volume with being in remission. Higher density of left frontal grey matter was associated with not being on a disability pension and higher density of the left frontal lobe and left limbic area were related to better functioning. Higher density of the left limbic area was associated with better longitudinal course of illness.
This study, based on unselected general population data, long follow-up and an extensive database, confirms findings of previous studies, that morphological abnormalities in several brain structures are associated with outcome. The difference in brain morphology in patients with good and poor outcomes may reflect separable aetiologies and developmental trajectories in schizophrenia.
The search for life in the Universe is a fundamental problem of astrobiology and modern science. The current progress in the detection of terrestrial-type exoplanets has opened a new avenue in the characterization of exoplanetary atmospheres and in the search for biosignatures of life with the upcoming ground-based and space missions. To specify the conditions favourable for the origin, development and sustainment of life as we know it in other worlds, we need to understand the nature of global (astrospheric), and local (atmospheric and surface) environments of exoplanets in the habitable zones (HZs) around G-K-M dwarf stars including our young Sun. Global environment is formed by propagated disturbances from the planet-hosting stars in the form of stellar flares, coronal mass ejections, energetic particles and winds collectively known as astrospheric space weather. Its characterization will help in understanding how an exoplanetary ecosystem interacts with its host star, as well as in the specification of the physical, chemical and biochemical conditions that can create favourable and/or detrimental conditions for planetary climate and habitability along with evolution of planetary internal dynamics over geological timescales. A key linkage of (astro)physical, chemical and geological processes can only be understood in the framework of interdisciplinary studies with the incorporation of progress in heliophysics, astrophysics, planetary and Earth sciences. The assessment of the impacts of host stars on the climate and habitability of terrestrial (exo)planets will significantly expand the current definition of the HZ to the biogenic zone and provide new observational strategies for searching for signatures of life. The major goal of this paper is to describe and discuss the current status and recent progress in this interdisciplinary field in light of presentations and discussions during the NASA Nexus for Exoplanetary System Science funded workshop ‘Exoplanetary Space Weather, Climate and Habitability’ and to provide a new roadmap for the future development of the emerging field of exoplanetary science and astrobiology.
Movement disorders associated with exposure to antipsychotic drugs are common and stigmatising but underdiagnosed.
To develop and evaluate a new clinical procedure, the ScanMove instrument, for the screening of antipsychotic-associated movement disorders for use by mental health nurses.
Item selection and content validity assessment for the ScanMove instrument were conducted by a panel of neurologists, psychiatrists and a mental health nurse, who operationalised a 31-item screening procedure. Interrater reliability was measured on ratings for 30 patients with psychosis from ten mental health nurses evaluating video recordings of the procedure. Criterion and concurrent validity were tested comparing the ScanMove instrument-based rating of 13 mental health nurses for 635 community patients from mental health services with diagnostic judgement of a movement disorder neurologist based on the ScanMove instrument and a reference procedure comprising a selection of commonly used rating scales.
Interreliability analysis showed no systematic difference between raters in their prediction of any antipsychotic-associated movement disorders category. On criterion validity testing, the ScanMove instrument showed good sensitivity for parkinsonism (90%) and hyperkinesia (89%), but not for akathisia (38%), whereas specificity was low for parkinsonism and hyperkinesia, and moderate for akathisia.
The ScanMove instrument demonstrated good feasibility and interrater reliability, and acceptable sensitivity as a mental health nurse-administered screening tool for parkinsonism and hyperkinesia.
Salmonella is a leading cause of bacterial foodborne illness. We report the collaborative investigative efforts of US and Canadian public health officials during the 2013–2014 international outbreak of multiple Salmonella serotype infections linked to sprouted chia seed powder. The investigation included open-ended interviews of ill persons, traceback, product testing, facility inspections, and trace forward. Ninety-four persons infected with outbreak strains from 16 states and four provinces were identified; 21% were hospitalized and none died. Fifty-four (96%) of 56 persons who consumed chia seed powder, reported 13 different brands that traced back to a single Canadian firm, distributed by four US and eight Canadian companies. Laboratory testing yielded outbreak strains from leftover and intact product. Contaminated product was recalled. Although chia seed powder is a novel outbreak vehicle, sprouted seeds are recognized as an important cause of foodborne illness; firms should follow available guidance to reduce the risk of bacterial contamination during sprouting.
Whole apples have not been previously implicated in outbreaks of foodborne bacterial illness. We investigated a nationwide listeriosis outbreak associated with caramel apples. We defined an outbreak-associated case as an infection with one or both of two outbreak strains of Listeria monocytogenes highly related by whole-genome multilocus sequence typing (wgMLST) from 1 October 2014 to 1 February 2015. Single-interviewer open-ended interviews identified the source. Outbreak-associated cases were compared with non-outbreak-associated cases and traceback and environmental investigations were performed. We identified 35 outbreak-associated cases in 12 states; 34 (97%) were hospitalized and seven (20%) died. Outbreak-associated ill persons were more likely to have eaten commercially produced, prepackaged caramel apples (odds ratio 326·7, 95% confidence interval 32·2–3314). Environmental samples from the grower's packing facility and distribution-chain whole apples yielded isolates highly related to outbreak isolates by wgMLST. This outbreak highlights the importance of minimizing produce contamination with L. monocytogenes. Investigators should perform single-interviewer open-ended interviews when a food is not readily identified.
Radio survey datasets comprise an increasing number of individual observations stored as sets of multidimensional data. In large survey projects, astronomers commonly face limitations regarding: 1) interactive visual analytics of sufficiently large subsets of data; 2) synchronous and asynchronous collaboration; and 3) documentation of the discovery workflow. To support collaborative data inquiry, we present encube, a large-scale comparative visual analytics framework. encube can utilise advanced visualization environments such as the CAVE2 (a hybrid 2D and 3D virtual reality environment powered with a 100 Tflop/s GPU-based supercomputer and 84 million pixels) for collaborative analysis of large subsets of data from radio surveys. It can also run on standard desktops, providing a capable visual analytics experience across the display ecology. encube is composed of four primary units enabling compute-intensive processing, advanced visualisation, dynamic interaction, parallel data query, along with data management. Its modularity will make it simple to incorporate astronomical analysis packages and Virtual Observatory capabilities developed within our community. We discuss how encube builds a bridge between high-end display systems (such as CAVE2) and the classical desktop, preserving all traces of the work completed on either platform – allowing the research process to continue wherever you are.
We compare the results of using a Random Forest Classifier with the results of using Nonparametric Discriminant Analysis to classify whether a filament channel (in the case of a filament eruption) or an active region (in the case of a flare) is about to produce an event. A large number of descriptors are considered in each case, but it is found that only a small number are needed in order to get most of the improvement in performance over always predicting the majority class. There is little difference in performance between the two classifiers, and neither results in substantial improvements over simply predicting the majority class.
Expert judgement has been used since the actuarial profession was founded. In the past, there has often been a lack of transparency regarding the use of expert judgement, even though those judgements could have a very significant impact on the outputs of calculations and the decisions made by organisations. The lack of transparency has a number of dimensions, including the nature of the underlying judgements, as well as the process used to derive those judgements. This paper aims to provide a practical framework regarding expert judgement processes, and how those processes may be validated. It includes a worked example illustrating how the process could be used for setting a particular assumption. It concludes with some suggested tools for use within expert judgement. Although primarily focussed on the insurance sector, the proposed process framework could be applied more widely without the need for significant changes.
The Murchison Widefield Array is a Square Kilometre Array Precursor. The telescope is located at the Murchison Radio–astronomy Observatory in Western Australia. The MWA consists of 4 096 dipoles arranged into 128 dual polarisation aperture arrays forming a connected element interferometer that cross-correlates signals from all 256 inputs. A hybrid approach to the correlation task is employed, with some processing stages being performed by bespoke hardware, based on Field Programmable Gate Arrays, and others by Graphics Processing Units housed in general purpose rack mounted servers. The correlation capability required is approximately 8 tera floating point operations per second. The MWA has commenced operations and the correlator is generating 8.3 TB day−1 of correlation products, that are subsequently transferred 700 km from the MRO to Perth (WA) in real-time for storage and offline processing. In this paper, we outline the correlator design, signal path, and processing elements and present the data format for the internal and external interfaces.
The Millimetre Astronomy Legacy Team 90 GHz (MALT90) survey aims to characterise the physical and chemical evolution of high-mass star-forming clumps. Exploiting the unique broad frequency range and on-the-fly mapping capabilities of the Australia Telescope National Facility Mopra 22 m single-dish telescope1, MALT90 has obtained 3′ × 3′ maps towards ~2 000 dense molecular clumps identified in the ATLASGAL 870 μm Galactic plane survey. The clumps were selected to host the early stages of high-mass star formation and to span the complete range in their evolutionary states (from prestellar, to protostellar, and on to
regions and photodissociation regions). Because MALT90 mapped 16 lines simultaneously with excellent spatial (38 arcsec) and spectral (0.11 km s−1) resolution, the data reveal a wealth of information about the clumps’ morphologies, chemistry, and kinematics. In this paper we outline the survey strategy, observing mode, data reduction procedure, and highlight some early science results. All MALT90 raw and processed data products are available to the community. With its unprecedented large sample of clumps, MALT90 is the largest survey of its type ever conducted and an excellent resource for identifying interesting candidates for high-resolution studies with ALMA.