Linking emerging contaminants to production and consumption practices

Emerging contaminants (ECs) associated with consumer products such as pharmaceuticals, personal care products, and plastics, are an issue of growing concern for water quality and human and environmental health. Growth in use of products associated with ECs is an outcome of growing populations, increased incomes and the emergence of new consumer products. Two examples are used illustrate the value of social science research in understanding patterns of consumption and sources of ECs, in order to identify potential interventions to reduce ECs in the environment—flushing inappropriate materials down the toilet, and antibiotic use in global livestock production. Antimicrobial resistance is a major policy driver to control the use of antibiotics in human healthcare and livestock production. Global antibiotic consumption increased 65% 2000–2015. Disposal of products, including unused pharmaceuticals and plastics, is influenced by regulation, consumer behavior, and infrastructure. This range of factors and trends demonstrates the complexity in understanding why ECs enter the aquatic environment and the extent that the issue can be tackled at the source rather than mitigated once in the environment

Co-designing Infrastructures

Co-designing Infrastructures tells the story of a research programme designed to bring the power of engineering and technology into the hands of grassroots community groups, to create bottom-up solutions to global crises. Four projects in London are described in detail, exemplifying community collaboration with engineers, designers and scientists to enact urban change. The projects co-designed solutions to air pollution, housing, the water-energy-food nexus, and water management. Rich case-study accounts are underpinned by theories of participation, environmental politics and socio-technical systems. The projects at the heart of the book are grounded in specific settings facing challenges familiar to urban communities throughout the world. This place-based approach to infrastructure is of international relevance as a foundation for urban resilience and sustainability. The authors document the tools used to deliver this work, providing guidance for others who are working to deliver local technical solutions to complex social and environmental problems around the world. This is a book for engineers, designers, community organisers and researchers. Co-authored by researchers, it includes voices of community collaborators, their experiences, frustrations and aspirations. It explores useful theories about infrastructure, engineering and resilience from international academic research, and situates them in community-based co-design experience, to explain why bottom-up approaches are needed and how they might succeed

EFFECTS AND PERCEPTIONS OF PARENTAL INVOLVEMENT ON THE MATHEMATICAL ACHIEVEMENT OF STUDENTS IN A STEM COURSE: A MIXED-METHODS STUDY

To understand how to identify and examine factors that influence parental involvement and math achievement of high school students, I conducted a mixed- methods study was guided by the following questions: 1. What are the perceptions of students, teachers and parents regarding parental involvement in secondary math education? 2. Does parental involvement in MINDSET influence mathematics performance for students? 3. Do the weekly newsletters and progress reports used in the MINDSET class influence the perception students, teachers and parents have about parental involvement? This study builds on research that suggests parental involvement impacts students’ academic achievement. Data were collected over a period of twelve weeks and included 8 weeks of implementing weekly newsletters and progress reports in a fourth-year math course that consisted of eleventh and 12th graders. The data included students’ writing, field notes, conferencing transcriptions, my journal mathematical assessment performance, grades, surveys, field notes, and interviews with the students, parents, and teachers. I analyzed these data to answer the research questions above. According to my findings, parents, students, and teachers’ perceptions about parental involvement were placed in four categories: strategies for parental involvement, barriers of parental involvement, parents and students’ transitional roles, and students’ independence. Quantitative analysis revealed that the implementation of weekly newsletters and progress reports did not improve students’ academic achievement, as well as influence students, parents, and teachers’ perception of parental involvement. However, qualitative analysis revealed that parents and students perceived that the weekly progress reports and newsletters helped improved students grades because of accountability and helped parents to have a positive outlook in involving themselves with their teenagers’ math education

Short-term health and social impacts of energy-efficiency investments in low-income communities: a controlled field study

Background During 2012–15, £45 million was invested to improve the energy-efficiency of 4800 houses in low-income areas across Wales. Houses received measures such as external wall insulation, new windows and doors, upgrades to the heating system, and connection to the gas network. This study aimed to establish the short-term health and social impacts of these investments. Methods A quasi-experimental field study with a controlled, before and after design was conducted (364 individuals in improved houses [intervention], 418 in houses with no improvements [control]). Any adult living in 24 selected intervention areas and matched control areas (n=23) was eligible for inclusion. Self-completed questionnaires, administered via a drop-off-and-collect method, were collected in the winter months (December to February) before and after installation of the energy efficiency measures. Health outcomes were mental health composite scale (MCS) and physical health composite scale (PCS) scores of the SF-12v2, SF-6D utility scores derived from the SF-12v2, self-reported respiratory symptoms, and subjective wellbeing. Social outcomes were financial difficulties and stress, food security, thermal comfort, housing conditions, and social isolation. The study used measures validated in previous research. Linear, ordered multinomial, and logistic multilevel models were constructed with measurement occasions nested within individuals. Findings After controlling for sex, age, housing benefit, household income, and smoking status, we found that investments were not associated with improvements in MCS (B=0·00, 95% CI −1·60 to 1·60) or PCS (0·98, −0·34 to 2·28) scores, SF-6D utilities (−0·01, −0·04 to 0·02), or self-reported respiratory symptoms (−0·14, −0·54 to 0·26). However, people who received energy-efficiency measures reported improved subjective wellbeing compared with controls (B=0·38, 95% CI 0·12 to 0·65), and fewer financial difficulties (−0·15, −0·25 to −0·05); they reported higher thermal comfort (odds ratio 3·83, 95% CI 2·40 to 5·90), higher satisfaction with the improvement of their homes (3·87, 2·51 to 5·96), and less reluctance to invite friends or family to their homes (0·32, 0·13 to 0·77). Interpretation Although there is no evidence that energy-efficiency investments provide physical health benefits in the short term, they improve social and economic conditions that are conducive to better health. Longer term studies are needed to establish the health impacts of energy-efficiency investments

Stellar migration and chemical enrichment in the milky way disc: a hybrid model

We develop a hybrid model of galactic chemical evolution that combines a multiring computation of chemical enrichment with a prescription for stellar migration and the vertical distribution of stellar populations informed by a cosmological hydrodynamic disc galaxy simulation. Our fiducial model adopts empirically motivated forms of the star formation law and star formation history, with a gradient in outflow mass loading tuned to reproduce the observed metallicity gradient. With this approach, the model reproduces many of the striking qualitative features of the Milky Way disc’s abundance structure: (i) the dependence of the [O/Fe]–[Fe/H] distribution on radius Rgal and mid-plane distance |z|; (ii) the changing shapes of the [O/H] and [Fe/H] distributions with Rgal and |z|; (iii) a broad distribution of [O/Fe] at sub-solar metallicity and changes in the [O/Fe] distribution with Rgal, |z|, and [Fe/H]; (iv) a tight correlation between [O/Fe] and stellar age for [O/Fe] > 0.1; (v) a population of young and intermediate-age α-enhanced stars caused by migration-induced variability in the Type Ia supernova rate; (vi) non-monotonic age–[O/H] and age–[Fe/H] relations, with large scatter and a median age of ∼4 Gyr near solar metallicity. Observationally motivated models with an enhanced star formation rate ∼2 Gyr ago improve agreement with the observed age–[Fe/H] and age–[O/H] relations, but worsen agreement with the observed age–[O/Fe] relation. None of our models predict an [O/Fe] distribution with the distinct bimodality seen in the observations, suggesting that more dramatic evolutionary pathways are required. All code and tables used for our models are publicly available through the Versatile Integrator for Chemical Evolution (VICE; https://pypi.org/project/vice)

Gestational length assignment based on last menstrual period, first trimester crown-rump length, ovulation, and implantation timing.

PURPOSE: Understanding the natural length of human pregnancy is central to clinical care. However, variability in the reference methods to assign gestational age (GA) confound our understanding of pregnancy length. Assignation from ultrasound measurement of fetal crown-rump length (CRL) has superseded that based on last menstrual period (LMP). Our aim was to estimate gestational length based on LMP, ultrasound CRL, and implantation that were known, compared to pregnancy duration assigned by day of ovulation. METHODS: Prospective study in 143 women trying to conceive. In 71 ongoing pregnancies, gestational length was estimated from LMP, CRL at 10-14 weeks, ovulation, and implantation day. For each method of GA assignment, the distribution in observed gestational length was derived and both agreement and correlation between the methods determined. RESULTS: Median ovulation and implantation days were 16 and 27, respectively. The gestational length based on LMP, CRL, implantation, and ovulation was similar: 279, 278, 276.5 and 276.5 days, respectively. The distributions for observed gestational length were widest where GA was assigned from CRL and LMP and narrowest when assigned from implantation and ovulation day. The strongest correlation for gestational length assessment was between ovulation and implantation (r = 0.98) and weakest between CRL and LMP (r = 0.88). CONCLUSIONS: The most accurate method of predicting gestational length is ovulation day, and this agrees closely with implantation day. Prediction of gestational length from CRL and known LMP are both inferior to ovulation and implantation day. This information could have important implications on the routine assignment of gestational age

High-resolution μCT of a mouse embryo using a compact laser-driven X-ray betatron source

High-resolution microcomputed tomography with benchtop X-ray sources requires long scan times because of the heat load limitation on the anode. We present an alternative, high-brightness plasma-based X-ray source that does not suffer from this restriction. A demonstration of tomography of a centimeter-scale complex organism achieves equivalent quality to a commercial scanner. We will soon be able to record such scans in minutes, rather than the hours required by conventional X-ray tubes

Establishing a core outcome set for peritoneal dialysis : report of the SONG-PD (standardized outcomes in nephrology-peritoneal dialysis) consensus workshop

Outcomes reported in randomized controlled trials in peritoneal dialysis (PD) are diverse, are measured inconsistently, and may not be important to patients, families, and clinicians. The Standardized Outcomes in Nephrology-Peritoneal Dialysis (SONG-PD) initiative aims to establish a core outcome set for trials in PD based on the shared priorities of all stakeholders. We convened an international SONG-PD stakeholder consensus workshop in May 2018 in Vancouver, Canada. Nineteen patients/caregivers and 51 health professionals attended. Participants discussed core outcome domains and implementation in trials in PD. Four themes relating to the formation of core outcome domains were identified: life participation as a main goal of PD, impact of fatigue, empowerment for preparation and planning, and separation of contributing factors from core factors. Considerations for implementation were identified: standardizing patient-reported outcomes, requiring a validated and feasible measure, simplicity of binary outcomes, responsiveness to interventions, and using positive terminology. All stakeholders supported inclusion of PD-related infection, cardiovascular disease, mortality, technique survival, and life participation as the core outcome domains for PD

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.

BACKGROUND: With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. FOCUS: The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. DATA: We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. METHODS: We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data