Service providers’ experience of methamphetamine and the portrayal of the ‘ice epidemic’ in remote Australia

Objective: To contrast service providers’ perceptions about crystalline methamphetamine (henceforth, ice) use and harm with information communicated in media reports and politicians’ statements. Design: In-depth semi structured interviews with service providers about the nature and extent of ice use in the local community and its impact on individual services, clients and town life. Interviews were transcribed verbatim, manually analysed and coded around key themes, interpreted and independently cross-checked for context and accuracy. Setting: Two remote towns located in different states and territories operating as service hubs to very remote communities. Participants: Twenty-seven key service providers representing local organisations that engage with ice users and/or their families. Results: First, compared with alcohol, ice use and ice-related harm were insignificant at the two sites. Ice users were primarily high-earning and -functioning non-Australian Aboriginal tradesmen, and to a lesser extent, professionals and secondary school students. There were few Australian Aboriginal users. Ice was used to ‘party’, keep alert, and escape psychological distress. Second, the ‘Ice Destroys Lives’ campaign and references to an ‘ice epidemic’ amplified public anxiety about ice and ice-related harm in the surveyed communities. Third, the attention on ice distracted from the more extensive harm arising from alcohol use in their communities. Conclusion: The respondents questioned the notion of an ‘ice epidemic’ and the use of federal funding for ice-related initiatives in remote communities, especially while general alcohol and other drug services were under-resourced

The Diversity of Life by E.O. Wilson

In The Diversity of Life, E. O. Wilson tells a tale about how our earth is on track for another extinction event and humans are at fault. Wilson discusses various topics such as environmental preservation, biodiversity and its importance, and how life has evolved over time. Wilson views biodiversity differently than many as he focuses on all species found in the ecosystem rather than narrowing his focus on one. He mentions how new species can be created by groups evolving and developing new skills or existing in new environments. Species are going extinct and being created constantly; these extinctions don\u27t have to be large; they can exist on small scales yet still cause an impact on the entire ecosystem. Wilson goes on to explain that humans have existed for a small period of time yet we are the number one cause of extinction events within species. Ultimately, humans will be the cause of our own downfall as the environment is a reflection and product of human actions.https://scholarworks.moreheadstate.edu/celebration_posters_2023/1008/thumbnail.jp

Heritage, health and place:The legacies of local community-based heritage conservation on social wellbeing

Geographies of health challenge researchers to attend to the positive effects of occupying, creating and using all kinds of spaces, including 'green space' and more recently 'blue space'. Attention to the spaces of community-based heritage conservation has largely gone unexplored within the health geography literature. This paper examines the personal motivations and impacts associated with people's growing interest in local heritage groups. It draws on questionnaires and interviews from a recent study with such groups and a conceptual mapping of their routes and flows. The findings reveal a rich array of positive benefits on the participants' social wellbeing with/in the community. These include personal enrichment, social learning, satisfaction from sharing the heritage products with others, and less anxiety about the present. These positive effects were tempered by needing to face and overcome challenging effects associated with running the projects thus opening up an extension to health-enabling spaces debates

Bivariate analysis of basal serum anti-Müllerian hormone measurements and human blastocyst development after IVF

Background To report on relationships among baseline serum anti-Müllerian hormone (AMH) measurements, blastocyst development and other selected embryology parameters observed in non-donor oocyte IVF cycles. Methods Pre-treatment AMH was measured in patients undergoing IVF (n = 79) and retrospectively correlated to in vitro embryo development noted during culture. Results Mean (+/- SD) age for study patients in this study group was 36.3 ± 4.0 (range = 28-45) yrs, and mean (+/- SD) terminal serum estradiol during IVF was 5929 +/- 4056 pmol/l. A moderate positive correlation (0.49; 95% CI 0.31 to 0.65) was noted between basal serum AMH and number of MII oocytes retrieved. Similarly, a moderate positive correlation (0.44) was observed between serum AMH and number of early cleavage-stage embryos (95% CI 0.24 to 0.61), suggesting a relationship between serum AMH and embryo development in IVF. Of note, serum AMH levels at baseline were significantly different for patients who did and did not undergo blastocyst transfer (15.6 vs. 10.9 pmol/l; p = 0.029). Conclusions While serum AMH has found increasing application as a predictor of ovarian reserve for patients prior to IVF, its roles to estimate in vitro embryo morphology and potential to advance to blastocyst stage have not been extensively investigated. These data suggest that baseline serum AMH determinations can help forecast blastocyst developmental during IVF. Serum AMH measured before treatment may assist patients, clinicians and embryologists as scheduling of embryo transfer is outlined. Additional studies are needed to confirm these correlations and to better define the role of baseline serum AMH level in the prediction of blastocyst formation

Predicting 10-year breast cancer mortality risk in the general female population in England: a model development and validation study

Background Identifying female individuals at highest risk of developing life-threatening breast cancers could inform novel stratified early detection and prevention strategies to reduce breast cancer mortality, rather than only considering cancer incidence. We aimed to develop a prognostic model that accurately predicts the 10-year risk of breast cancer mortality in female individuals without breast cancer at baseline. Methods In this model development and validation study, we used an open cohort study from the QResearch primary care database, which was linked to secondary care and national cancer and mortality registers in England, UK. The data extracted were from female individuals aged 20–90 years without previous breast cancer or ductal carcinoma in situ who entered the cohort between Jan 1, 2000, and Dec 31, 2020. The primary outcome was breast cancer-related death, which was assessed in the full dataset. Cox proportional hazards, competing risks regression, XGBoost, and neural network modelling approaches were used to predict the risk of breast cancer death within 10 years using routinely collected health-care data. Death due to causes other than breast cancer was the competing risk. Internal–external validation was used to evaluate prognostic model performance (using Harrell's C, calibration slope, and calibration in the large), performance heterogeneity, and transportability. Internal–external validation involved dataset partitioning by time period and geographical region. Decision curve analysis was used to assess clinical utility. Findings We identified data for 11 626 969 female individuals, with 70 095 574 person-years of follow-up. There were 142 712 (1·2%) diagnoses of breast cancer, 24 043 (0·2%) breast cancer-related deaths, and 696 106 (6·0%) deaths from other causes. Meta-analysis pooled estimates of Harrell's C were highest for the competing risks model (0·932, 95% CI 0·917–0·946). The competing risks model was well calibrated overall (slope 1·011, 95% CI 0·978–1·044), and across different ethnic groups. Decision curve analysis suggested favourable clinical utility across all age groups. The XGBoost and neural network models had variable performance across age and ethnic groups. Interpretation A model that predicts the combined risk of developing and then dying from breast cancer at the population level could inform stratified screening or chemoprevention strategies. Further evaluation of the competing risks model should comprise effect and health economic assessment of model-informed strategies. Funding Cancer Research UK

Development and internal-external validation of statistical and machine learning models for breast cancer prognostication: cohort study

Objective To develop a clinically useful model that estimates the 10 year risk of breast cancer related mortality in women (self-reported female sex) with breast cancer of any stage, comparing results from regression and machine learning approaches. Design Population based cohort study. Setting QResearch primary care database in England, with individual level linkage to the national cancer registry, Hospital Episodes Statistics, and national mortality registers. Participants 141 765 women aged 20 years and older with a diagnosis of invasive breast cancer between 1 January 2000 and 31 December 2020. Main outcome measures Four model building strategies comprising two regression (Cox proportional hazards and competing risks regression) and two machine learning (XGBoost and an artificial neural network) approaches. Internal-external cross validation was used for model evaluation. Random effects meta-analysis that pooled estimates of discrimination and calibration metrics, calibration plots, and decision curve analysis were used to assess model performance, transportability, and clinical utility. Results During a median 4.16 years (interquartile range 1.76-8.26) of follow-up, 21 688 breast cancer related deaths and 11 454 deaths from other causes occurred. Restricting to 10 years maximum follow-up from breast cancer diagnosis, 20 367 breast cancer related deaths occurred during a total of 688 564.81 person years. The crude breast cancer mortality rate was 295.79 per 10 000 person years (95% confidence interval 291.75 to 299.88). Predictors varied for each regression model, but both Cox and competing risks models included age at diagnosis, body mass index, smoking status, route to diagnosis, hormone receptor status, cancer stage, and grade of breast cancer. The Cox model’s random effects meta-analysis pooled estimate for Harrell’s C index was the highest of any model at 0.858 (95% confidence interval 0.853 to 0.864, and 95% prediction interval 0.843 to 0.873). It appeared acceptably calibrated on calibration plots. The competing risks regression model had good discrimination: pooled Harrell’s C index 0.849 (0.839 to 0.859, and 0.821 to 0.876, and evidence of systematic miscalibration on summary metrics was lacking. The machine learning models had acceptable discrimination overall (Harrell’s C index: XGBoost 0.821 (0.813 to 0.828, and 0.805 to 0.837); neural network 0.847 (0.835 to 0.858, and 0.816 to 0.878)), but had more complex patterns of miscalibration and more variable regional and stage specific performance. Decision curve analysis suggested that the Cox and competing risks regression models tested may have higher clinical utility than the two machine learning approaches. Conclusion In women with breast cancer of any stage, using the predictors available in this dataset, regression based methods had better and more consistent performance compared with machine learning approaches and may be worthy of further evaluation for potential clinical use, such as for stratified follow-up

Next-to leading order analysis of target mass corrections to structure functions and asymmetries

We perform a comprehensive analysis of target mass corrections (TMCs) to spin-averaged structure functions and asymmetries at next-to-leading order. Several different prescriptions for TMCs are considered, including the operator product expansion, and various approximations to it, collinear factorization, and xi-scaling. We assess the impact of each of these on a number of observables, such as the neutron to proton F_2 structure function ratio, and parity-violating electron scattering asymmetries for protons and deuterons which are sensitive to gamma-Z interference effects. The corrections from higher order radiative and nuclear effects on the parity-violating deuteron asymmetry are also quantified.Comment: 32 pages, 15 figures; Fig. 8 corrected (previous version showed 2xR instead of R

Planary Symmetric Static Worlds with Massless Scalar Sources

Motivated by the recent wave of investigations on plane domain wall spacetimes with nontrivial topologies, the present paper deals with (probably) the most simple source field configuration which can generate a spatially planary symmetric static spacetime, namely a minimally coupled massless scalar field that depends only upon a spacelike coordinate, $z$. It is shown that the corresponding exact solutions $({\cal M}, {\bf{\rm g}}_{\pm})$ are algebraically special, type $D - [S - 3T]_{(11)}$, and represent globally pathologic spacetimes with a $G_{4}$ - group of motion acting on ${\bf{\rm R}}^{2} \times {\bf{\rm R}}$ orbits. In spite of the model simplicity, these $\phi$ - generated worlds possess naked timelike singularities (reached within a finite universal time by normal non-spacelike geodesics), are completely free of Cauchy surfaces and contain into the $t$ - leveled sections points which can not be jointed by ${\rm C}^{1}$ - trajectories images of oblique non-spacelike geodesics. Finally, we comment on the possibility of deriving from $({\cal M}, {\bf{\rm g}}_{\pm})$ two other physically interesting ^^ ^^ $\phi$ - generated'' spacetimes, by appropiate jonction conditions in the $(z = 0)$ - plane.Comment: 14 pages, LaTeX format, figures not include

'Weather cloudy & cool harvest begun’: St Andrews output usage beyond the repository

St Andrews might be small but, as a research intensive University with around 700 research active staff and over 8500 students, its research output is considerable. The St Andrews Research Repository has been accepting deposits since 2006 and since 2007 the University has required electronic thesis submission. Use has grown and the repository currently comprises electronic theses, research articles, conference proceedings, working papers, book chapters, research monographs and other items. The Library Open Access and Cataloguing teams have marked several deposit milestones in the Repository - 5000 (February 2015), 8000 (July 2016) and 9000 (February 2017) - so content has risen sharply. Deposits of research publications are driven from a connected CRIS, primarily due to funderimposed Open Access mandates, with continued direct deposit of new theses and an ongoing programme of thesis digitisation adding to the increase. Our mature infrastructure and supporting processes mean the University has excellent funder compliance rates – RCUK (93%), Hefce (92%). But it's not all about compliance. We are keen to understand and share how institutional research outputs can have wide reach and visibility, and how the repository can be used to promote user engagement and public outreach with other content. We use reports from the British Library EThOS service and IRUS-UK (Institutional Repository Usage Statistics UK) for signs and hints of how downloaded items might be used and suggest how usage statistics might be publicly presented. In this brief 10 x 10 presentation we're excited to show several items from the St Andrews Research Repository and what we discovered about their life in St Andrews and beyond