Influence of gender, ethnicity and makeup on age estimation by adults in the community

Recent history has witnessed an emerging social issue concerning children and teenagers appearing older than their age, reasons for which may include clothing, makeup, false identification, dating websites or social media. This has ramifications for statutory rape, whereby a sexual act takes place involving a person under the age of consent, since many perpetrators claim they were unaware of their sexual partner’s age before participating. The current study investigated the ability of adults in the community to estimate the age of Asian and White 12, 14, 16 and 18-year-olds, with reference to the age, gender, and ethnicity of the participant and model, as well as the influence of makeup. Participants were exposed to photographs of 12 models at each age, whilst each female was presented once more with makeup. Participants were required to estimate the models’ age in a within-subjects design. Results showed that participants overestimated the age of all age-groups, with an average of 3.07 years older than the actual age. Paired samples t-tests found that this was most pronounced for White female and Asian male models, and females between 12 and 16-years-old with makeup on. Results of one-way ANOVA’s found that participant gender and age had no effect, but found significant differences between Asian and White participant responses. The study concluded that people cannot accurately estimate age using only facial cues, and that model gender, ethnicity and makeup, and participant ethnicity, significantly impact perceptions. This study has implications for the application of statutory rape laws and victim protection

Four Strategies for Driving a University Pre-College Computing Outreach Program

A public university’s computing outreach program focused on four key strategies for increasing the depth and breadth of science, technology, engineering, and mathematics (STEM) education. This paper describes the development and implementation of a project management hands-on learning laboratory activity within the context of the university’s outreach strategies. The first two strategies, establishing relationships with the primary and secondary (K–12) level partner schools and implementing whole-grade participation, have led to repeat visits by students over several years. The third strategy, hands-on learning laboratory activities, has successfully engaged K–12 students, as indicated by the assessment results that provide evidence of successful student learning. The fourth strategy, producer–consumer collaborations, has facilitated the efficient matching of faculty expertise with K–12 teacher needs. The results include the evidence that outreach strategies can have a positive influence on student engagement in STEM education at multiple points in the K–12 education experience

How paradata can illuminate technical, social and professional role changes between the Poverty in the UK (1967/1968) and Poverty and Social Exclusion in the UK (2012) surveys

© 2016, The Author(s). This article brings together analyses of the micro paradata ‘by-products’ from the 1967/1968 Poverty in the United Kingdom (PinUK) and 2012 Poverty and Social Exclusion in the UK (PSE) surveys to explore changes in the conditions of production over this 45year period. We highlight technical, social and professional role continuities and changes, shaped by the institutionalisation of survey researchers, the professionalization of the field interviewer, and economisation. While there are similarities between the surveys in that field interviewers were and are at the bottom of the research hierarchy, we demonstrate an increasing segregation between the core research team and field interviewers. In PinUK the field interviewers are visible in the paper survey booklets; through their handwritten notes on codes and in written marginalia they can ‘talk’ to the central research team. In PSE they are absent from the computer mediated data, and from communication with the central team. We argue that, while there have been other benefits to field interviewers, their relational labour has become less visible in a shift from the exercise of observational judgement to an emphasis on standardisation. Yet, analyses of what field interviewers actually do show that they still need to deploy the same interpersonal skills and resourcefulness to secure and maintain interviews as they did 45years previously

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

The difference myth

Women are the chatty sex, using three times as many words each day as men. They are society’s great communicators. The verbal parts of their brains are larger than men’s and they are hard-wired for empathy, but they lack a natural ability to reach the top levels of math and science. Men, on the other hand, have brains that are good at understanding systems, and they are adept at acquiring and using power. They are hard-wired to excel at math and science, but lag behind women in reading ability. They talk less and are not naturally inclined toward caring for others. [...] Scientists have turned up some intriguing findings of anatomical differences between the sexes. But we know very little about their real-world effect on how boys and girls behave – meaning that any conclusions based on these findings are premature. (DIPF/Orig.