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Aboriginal Australians experience higher rates of non-communicable chronic disease, injury, dementia, and mortality than non-Aboriginal Australians. Self-reported health is a holistic measure and may fit well with Aboriginal views of health and well-being. This study aimed to identify predictors of self-reported health in older Aboriginal Australians and determine acceptable research methodologies for future aging research.
Longitudinal, population-based study.
Five communities across New South Wales, Australia (two urban and three regional sites).
Aboriginal and Torres Strait Islander people (n = 227; 60–88 years, M = 66.06, SD = 5.85; 145 female).
Participants completed baseline (demographic, medical, cognitive, mental health, and social factors) and follow-up assessments (self-reported health quantified with 5-point scale; sharing thoughts on areas important for future research). Predictors of self-reported health were examined using logistic regression analyses.
Self-reported health was associated with sex, activities of daily living, social activity participation, resilience, alcohol use, kidney problems, arthritis, falls, and recent hospitalization. Arthritis, kidney problems, and resilience remained significant in multiple logistic regression models.
Perceived resilience and the absence of certain chronic age-related conditions predict older Aboriginal peoples’ self-reported health. Understanding these factors could inform interventions to improve well-being. Findings on acceptable research methodologies suggest that many older Aboriginal people would embrace a range of methodologies within long-standing research partnerships, which is an important consideration for Indigenous population research internationally.
The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural–geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
Determining infectious cross-transmission events in healthcare settings involves manual surveillance of case clusters by infection control personnel, followed by strain typing of clinical/environmental isolates suspected in said clusters. Recent advances in genomic sequencing and cloud computing now allow for the rapid molecular typing of infecting isolates.
To facilitate rapid recognition of transmission clusters, we aimed to assess infection control surveillance using whole-genome sequencing (WGS) of microbial pathogens to identify cross-transmission events for epidemiologic review.
Clinical isolates of Staphylococcus aureus, Enterococcus faecium, Pseudomonas aeruginosa, and Klebsiella pneumoniae were obtained prospectively at an academic medical center, from September 1, 2016, to September 30, 2017. Isolate genomes were sequenced, followed by single-nucleotide variant analysis; a cloud-computing platform was used for whole-genome sequence analysis and cluster identification.
Most strains of the 4 studied pathogens were unrelated, and 34 potential transmission clusters were present. The characteristics of the potential clusters were complex and likely not identifiable by traditional surveillance alone. Notably, only 1 cluster had been suspected by routine manual surveillance.
Our work supports the assertion that integration of genomic and clinical epidemiologic data can augment infection control surveillance for both the identification of cross-transmission events and the inclusion of missed and exclusion of misidentified outbreaks (ie, false alarms). The integration of clinical data is essential to prioritize suspect clusters for investigation, and for existing infections, a timely review of both the clinical and WGS results can hold promise to reduce HAIs. A richer understanding of cross-transmission events within healthcare settings will require the expansion of current surveillance approaches.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
By applying a display ecology to the Deeper, Wider, Faster proactive, simultaneous telescope observing campaign, we have shown a dramatic reduction in the time taken to inspect DECam CCD images for potential transient candidates and to produce time-critical triggers to standby telescopes. We also show how facilitating rapid corroboration of potential candidates and the exclusion of non-candidates improves the accuracy of detection; and establish that a practical and enjoyable workspace can improve the experience of an otherwise taxing task for astronomers. We provide a critical road test of two advanced displays in a research context—a rare opportunity to demonstrate how they can be used rather than simply discuss how they might be used to accelerate discovery.
State space models for neural population spike trains Neural computations at all scales of evolutionary and behavioural complexity are carried out by recurrently connected networks of neurons that communicate with each other, with neurons elsewhere in the brain, and with muscles through the firing of action potentials or “spikes.” To understand how nervous tissue computes, it is therefore necessary to understand how the spiking of neurons is shaped both by inputs to the network and by the recurrent action of existing network activity. Whereas most historical spike data were collected one neuron at a time, new techniques including silicon multielectrode array recording and scanning 2-photon, light-sheet or light-field fluorescence calcium imaging increasingly make it possible to record spikes from dozens, hundreds and potentially thousands of individual neurons simultaneously. These new data offer unprecedented empirical access to network computation, promising breakthroughs both in our understanding of neural coding and computation (Stevenson & Kording 2011), and our ability to build prosthetic neural interfaces (Santhanam et al. 2006). Fulfillment of this promise will require powerful methods for data modeling and analysis, able to capture the structure of statistical dependence of network activity across neurons and time.
Probabilistic latent state space models (SSMs) are particularly well-suited to this task. Neural activity often appears stochastic, in that repeated trials under the same controlled experimental conditions can evoke quite different patterns of firing. Some part of this variation may reflect differences in the way the computation unfolds on each trial. Another part might reflect noisy creation and transmission of neural signals. Yet more may come from chaotic amplification of small perturbations. As computational signals are thought to be distributed across the population (in a “population code”), variation in the computation may be distinguished by its common impact on different neurons and the systematic evolution of these common effects in time.
An SSM is able to capture such structured variation through the evolution of its latent state trajectory. This latent state provides a summary description of all factors modulating neural activity that are not observed directly. These factors could include processes such as arousal, attention, cortical state (Harris & Thiele 2011) or behavioural states of the animal (Niell & Stryker 2010; Maimon 2011).
A trend toward greater body size in dizygotic (DZ) than in monozygotic (MZ) twins has been suggested by some but not all studies, and this difference may also vary by age. We analyzed zygosity differences in mean values and variances of height and body mass index (BMI) among male and female twins from infancy to old age. Data were derived from an international database of 54 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins), and included 842,951 height and BMI measurements from twins aged 1 to 102 years. The results showed that DZ twins were consistently taller than MZ twins, with differences of up to 2.0 cm in childhood and adolescence and up to 0.9 cm in adulthood. Similarly, a greater mean BMI of up to 0.3 kg/m2 in childhood and adolescence and up to 0.2 kg/m2 in adulthood was observed in DZ twins, although the pattern was less consistent. DZ twins presented up to 1.7% greater height and 1.9% greater BMI than MZ twins; these percentage differences were largest in middle and late childhood and decreased with age in both sexes. The variance of height was similar in MZ and DZ twins at most ages. In contrast, the variance of BMI was significantly higher in DZ than in MZ twins, particularly in childhood. In conclusion, DZ twins were generally taller and had greater BMI than MZ twins, but the differences decreased with age in both sexes.
For over 100 years, the genetics of human anthropometric traits has attracted scientific interest. In particular, height and body mass index (BMI, calculated as kg/m2) have been under intensive genetic research. However, it is still largely unknown whether and how heritability estimates vary between human populations. Opportunities to address this question have increased recently because of the establishment of many new twin cohorts and the increasing accumulation of data in established twin cohorts. We started a new research project to analyze systematically (1) the variation of heritability estimates of height, BMI and their trajectories over the life course between birth cohorts, ethnicities and countries, and (2) to study the effects of birth-related factors, education and smoking on these anthropometric traits and whether these effects vary between twin cohorts. We identified 67 twin projects, including both monozygotic (MZ) and dizygotic (DZ) twins, using various sources. We asked for individual level data on height and weight including repeated measurements, birth related traits, background variables, education and smoking. By the end of 2014, 48 projects participated. Together, we have 893,458 height and weight measures (52% females) from 434,723 twin individuals, including 201,192 complete twin pairs (40% monozygotic, 40% same-sex dizygotic and 20% opposite-sex dizygotic) representing 22 countries. This project demonstrates that large-scale international twin studies are feasible and can promote the use of existing data for novel research purposes.
The International Network of Twin Registries (INTR) aims to foster scientific collaboration and promote twin research on a global scale by working to expand the resources of twin registries around the world and make them available to researchers who adhere to established guidelines for international collaboration. Our vision is to create an unprecedented scientific network of twin registries that will advance knowledge in ways that are impossible for individual registries, and includes the harmonization of data. INTR will also promote a broad range of activities, including the development of a website, formulation of data harmonization protocols, creation of a library of software tools for twin studies, design of a search engine to identify research partners, establishment of searchable inventories of data and biospecimens, development of templates for informed consent and data sharing, organization of symposia at International Society of Twin Studies conferences, support for scholar exchanges, and writing grant proposals.
The study of twin subjects permits the documentation of crude heritability and may promote the identification of specific causal alleles. We believe that at the current time, the chief research advantage of twins as subjects, especially monozygotic twins, is that the commonality of their genetic and cultural identity simplifies the interpretation of biological associations. In order to study genetic and environmental determinants of cancer and chronic diseases, we developed two twin registries, maintained at the University of Southern California: The International Twin Study (ITS) and the California Twin Program (CTP). The ITS is a volunteer registry of twins with cancer and chronic disease consisting of 17,245 twin pairs affected by cancer and chronic disease, respectively, ascertained by advertising in periodicals from 1980–1991. The CTP is a population-based registry of California-born twin pairs ascertained by linking the California birth records to the State Department of Motor Vehicles. Over 51,000 individual California twins representing 36,965 pairs completed and returned 16-page questionnaires. Cancer diagnoses in the California twins are updated by regular linkage to the California Cancer Registry. Over 5,000 cancer patients are represented in the CTP. Twins from both registries have participated extensively in studies of breast cancer, melanoma, lymphoma, multiple sclerosis, systemic lupus erythematosus, diabetes mellitus type 1, mammographic density, smoking, and other traits and conditions.
Infectious mononucleosis is a clinical manifestation of primary Epstein–Barr virus infection. It is unknown whether genetic factors contribute to risk. To assess heritability, we compared disease concordance in monozygotic to dizygotic twin pairs from the population-based California Twin Program and assessed the risk to initially unaffected co-twins. One member of 611 and both members of 58 twin pairs reported a history of infectious mononucleosis. Pairwise concordance in monozygotic and dizygotic pairs was respectively 12·1% [standard error (s.e.)=1·9%] and 6·1% (s.e.=1·2%). The relative risk (hazard ratio) of monozygotic compared to dizygotic unaffected co-twins of cases was 1·9 [95% confidence interval (CI) 1·1–3·4, P=0·03], over the follow-up period. When the analysis was restricted to same-sex twin pairs, that estimate was 2·5 (95% CI 1·2–5·3, P=0·02). The results are compatible with a heritable contribution to the risk of infectious mononucleosis.
Currently, there is little in the literature regarding the ability of rear seatbacks to act as a protective barrier from cargo in frontal crashes. However, it has been shown that unrestrained rear passengers pose a danger to front seat occupants. The association of rear seatback failures and intrusions with mortality and serious injury were examined.
The Seattle CIREN database for restrained, rear-seat passengers in front-end crashes with seatback failure or intrusion was searched. Injury patterns and crash characteristics, including the role of unrestrained cargo were examined. Next, the National Automotive Sampling System- Crashworthiness Data System (NASS-CDS) database was queried for restrained rear-seat passengers in front-end crashes with recorded seat failure or intrusion. Mortality, maximum Abbreviated Injury Scale (AIS) score and mean Injury Severity Scale (ISS) scores were compared with passengers who had no failure or intrusion. Linear regression was used to identify the differences between the groups. Logistic regression was used to estimate the mortality risk associated with seat failure.
There were four CIREN cases that met the criteria. In each case, the occupant suffered significant injury or death. All four of the seat failures were the result of unrestrained cargo striking the seatback. The CDS data revealed a statistically significantly increased mortality (OR = 18.9, 95% CI = 14.0–25.7) associated with seat failure. Both the maximum AIS and mean of the ISS scores were higher in the failure/intrusion group (p <0.0001).
Rear seatback failure/intrusion is associated with increased mortality and injury. Case reports suggest unrestrained cargo plays a significant role in these injuries.