Propionic acid promotes the virulent phenotype of Crohn's disease-associated adherent-invasive Escherichia coli

Propionic acid (PA) is a bacterium-derived intestinal antimicrobial and immune modulator used widely in food production and agriculture. Passage of Crohn’s disease-associated adherent-invasive Escherichia coli (AIEC) through a murine model, in which intestinal PA levels are increased to mimic the human intestine, leads to the recovery of AIEC with significantly increased virulence. Similar phenotypic changes are observed outside the murine model when AIEC is grown in culture with PA as the sole carbon source; such PA exposure also results in AIEC that persists at 20-fold higher levels in vivo. RNA sequencing identifies an upregulation of genes involved in biofilm formation, stress response, metabolism, membrane integrity, and alternative carbon source utilization. PA exposure also increases virulence in a number of E. coli isolates from Crohn’s disease patients. Removal of PA is sufficient to reverse these phenotypic changes. Our data indicate that exposure to PA results in AIEC resistance and increased virulence in its presence

Roadmap on Li-ion battery manufacturing research

Growth in the Li-ion battery market continues to accelerate, driven primarily by the increasing need for economic energy storage for electric vehicles. Electrode manufacture by slurry casting is the first main step in cell production but much of the manufacturing optimisation is based on trial and error, know-how and individual expertise. Advancing manufacturing science that underpins Li-ion battery electrode production is critical to adding to the electrode manufacturing value chain. Overcoming the current barriers in electrode manufacturing requires advances in materials, manufacturing technology, in-line process metrology and data analytics, and can enable improvements in cell performance, quality, safety and process sustainability. In this roadmap we explore the research opportunities to improve each stage of the electrode manufacturing process, from materials synthesis through to electrode calendering. We highlight the role of new process technology, such as dry processing, and advanced electrode design supported through electrode level, physics-based modelling. Progress in data driven models of electrode manufacturing processes is also considered. We conclude there is a growing need for innovations in process metrology to aid fundamental understanding and to enable feedback control, an opportunity for electrode design to reduce trial and error, and an urgent imperative to improve the sustainability of manufacture

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Roadmap on Li-ion battery manufacturing research

Growth in the Li-ion battery market continues to accelerate, driven by increasing need for economic energy storage in the electric vehicle market. Electrode manufacture is the first main step in production and in an industry dominated by slurry casting, much of the manufacturing process is based on trial and error, know-how and individual expertise. Advancing manufacturing science that underpins Li-ion battery electrode production is critical to adding value to the electrode manufacturing value chain. Overcome the current barriers in the electrode manufacturing requires advances in material innovation, manufacturing technology, in-line process metrology and data analytics to improve cell performance, quality, safety and process sustainability. In this roadmap we present where fundamental research can impact advances in each stage of the electrode manufacturing process from materials synthesis to electrode calendering. We also highlight the role of new process technology such as dry processing and advanced electrode design supported through electrode level, physics-based modelling. To compliment this, the progresses in data driven models of full manufacturing processes is reviewed. For all the processes we describe, there is a growing need process metrology, not only to aid fundamental understanding but also to enable true feedback control of the manufacturing process. It is our hope this roadmap will contribute to this rapidly growing space and provide guidance and inspiration to academia and industry

Projected WIMP sensitivity of the LUX-ZEPLIN dark matter experiment

LUX-ZEPLIN (LZ) is a next-generation dark matter direct detection experiment that will operate 4850 feet underground at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, USA. Using a two-phase xenon detector with an active mass of 7 tonnes, LZ will search primarily for low-energy interactions with weakly interacting massive particles (WIMPs), which are hypothesized to make up the dark matter in our galactic halo. In this paper, the projected WIMP sensitivity of LZ is presented based on the latest background estimates and simulations of the detector. For a 1000 live day run using a 5.6-tonne fiducial mass, LZ is projected to exclude at 90% confidence level spin-independent WIMP-nucleon cross sections above 1.4 × 10-48cm2 for a 40 GeV/c2 mass WIMP. Additionally, a 5σ discovery potential is projected, reaching cross sections below the exclusion limits of recent experiments. For spin-dependent WIMP-neutron(-proton) scattering, a sensitivity of 2.3 × 10−43 cm2 (7.1 × 10−42 cm2) for a 40 GeV/c2 mass WIMP is expected. With underground installation well underway, LZ is on track for commissioning at SURF in 2020

Transitions in welfare participation and female headship

This study uses data from the 1990, 1992, 1993 and 1996 panels of the Survey of Income and Program Participation to examine how welfare policies and local economic conditions contribute to women's transitions into and out of female headship and into and out of welfare participation. It also examines whether welfare participation is directly associated with longer spells of headship. The study employs a simultaneous hazards approach that accounts for unobserved heterogeneity in all of its transition models and for the endogeneity of welfare participation in its headship model. The estimation results indicate that welfare participation significantly reduces the chances of leaving female headship. The estimates also reveal that more generous welfare benefits contribute indirectly to headship by increasing the chances that mothers will enter welfare. More generous Earned Income Tax Credit benefits are associated with longer spells of headship, non-headship, welfare participation and nonparticipation. Other measures of welfare policies, including indicators for the adoption of welfare waivers and the implementation of Temporary Assistance for Needy Families programs, are generally not significantly associated with headship or welfare receipt. Better economic opportunities are estimated to increase headship but reduce welfare participation among unmarried mothers

The impact of age on genetic testing decisions in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a heterogeneous neurodegenerative syndrome. In up to 20% of cases, a family history is observed. Although Mendelian disease gene variants are found in apparently sporadic ALS, genetic testing is usually restricted to those with a family history or younger patients with sporadic disease. With the advent of therapies targeting genetic ALS, it is important that everyone treatable is identified. We therefore sought to determine the probability of a clinically actionable ALS genetic test result by age of onset, globally, but using the UK as an exemplar. Blood-derived DNA was sequenced for ALS genes, and the probability of a clinically actionable genetic test result estimated. For a UK subset, age- and sex-specific population incidence rates were used to determine the number of such results missed by restricting testing by age of onset according to UK’s National Genomic Test Directory criteria. There were 6274 people with sporadic ALS, 1551 from the UK. The proportion with a clinically actionable genetic test result ranged between 0.21 [95% confidence interval (CI) 0.18–0.25] in the youngest age group to 0.15 (95% CI 0.13–0.17) in the oldest age group for a full gene panel. For the UK, the equivalent proportions were 0.23 (95% CI 0.13–0.33) in the youngest age group to 0.17 (95% CI 0.13–0.21) in the oldest age group. By limiting testing in those without a family history to people with onset below 40 years, 115 of 117 (98% of all, 95% CI 96%–101%) clinically actionable test results were missed. There is a significant probability of a clinically actionable genetic test result in people with apparently sporadic ALS at all ages. Although some countries limit testing by age, doing so results in a significant number of missed pathogenic test results. Age of onset and family history should not be a barrier to genetic testing in ALS

Mapping child growth failure across low- and middle-income countries

Childhood malnutrition is associated with high morbidity and mortality globally1. Undernourished children are more likely to experience cognitive, physical, and metabolic developmental impairments that can lead to later cardiovascular disease, reduced intellectual ability and school attainment, and reduced economic productivity in adulthood2. Child growth failure (CGF), expressed as stunting, wasting, and underweight in children under five years of age (0�59 months), is a specific subset of undernutrition characterized by insufficient height or weight against age-specific growth reference standards3�5. The prevalence of stunting, wasting, or underweight in children under five is the proportion of children with a height-for-age, weight-for-height, or weight-for-age z-score, respectively, that is more than two standard deviations below the World Health Organization�s median growth reference standards for a healthy population6. Subnational estimates of CGF report substantial heterogeneity within countries, but are available primarily at the first administrative level (for example, states or provinces)7; the uneven geographical distribution of CGF has motivated further calls for assessments that can match the local scale of many public health programmes8. Building from our previous work mapping CGF in Africa9, here we provide the first, to our knowledge, mapped high-spatial-resolution estimates of CGF indicators from 2000 to 2017 across 105 low- and middle-income countries (LMICs), where 99 of affected children live1, aggregated to policy-relevant first and second (for example, districts or counties) administrative-level units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the ambitious World Health Organization Global Nutrition Targets to reduce stunting by 40 and wasting to less than 5 by 2025. Large disparities in prevalence and progress exist across and within countries; our maps identify high-prevalence areas even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where the highest-need populations reside, these geospatial estimates can support policy-makers in planning interventions that are adapted locally and in efficiently directing resources towards reducing CGF and its health implications. © 2020, The Author(s)