Britain’s slow movement to a gender egalitarian equilibrium: parents and employment in the UK 2001–13

This article examines the working lives of British couple families across the first decade of the millennium using EU Labour Force Survey data (2001–13) taking a multiple equilibria approach. Some growth in dual full-time earners, increased working hours of mothers in part-time employment and a growing proportion of households with ‘non-standard’ working patterns are all identified, suggesting both a convergence and greater diversity in economic provisioning within parent couple households. Household employment patterns remain strongly associated with maternal education and family size but are becoming less sensitive to the age of the youngest child. The dual full-time earner model is growing in significance for British parents of young children but a new gender egalitarian equilibrium has not yet been reached

An Integrated Architecture for Corrosion Monitoring and Testing, Data mining, Modeling and Diagnostics/Prognostics

It has been established that corrosion is one of the most important factors causing deterioration and decreased performance and reliability in critical aerospace and industrial systems. Corrosion monitoring, detection, and quantification are recognized as key enabling technologies to reduce the impact of corrosion on the integrity of aircraft and industrial assets. Accurate and reliable detection of corrosion initiation and propagation, with specified false alarm rates, requires novel tools and methods, including verifiable simulation and modeling methods. This paper reports an experimental investigation of the detection and quantification of pitting corrosion on aluminum alloy panels using 3D surface metrology methods and image processing techniques. Panel surfaces were evaluated by laser microscopy and stylus-based profilometry to characterize global and local surface features. Promising imaging and texture features were extracted and compared between coated and uncoated aluminum panels at different exposure times under accelerated corrosion conditions. Image processing, information processing, and data mining techniques were utilized to evaluate the presence and extent of pitting corrosion. A new modeling framework for corrosion stages is introduced that emphasizes the representation of pitting corrosion and ultimately the crack formation process. Detection and prediction of the evolution of corrosion stages relies on data, a particle filtering method, and the corrosion propagation model. Results from these experimental studies demonstrate the efficacy of this proposed methodology

Toll-like receptor orchestrates a tumor suppressor response in non-small cell lung cancer

Targeting early-stage lung cancer is vital to improve survival. However, the mechanisms and components of the early tumor suppressor response in lung cancer are not well understood. In this report, we study the role of Toll-like receptor 2 (TLR2), a regulator of oncogene-induced senescence, which is a key tumor suppressor response in premalignancy. Using human lung cancer samples and genetically engineered mouse models, we show that TLR2 is active early in lung tumorigenesis, where it correlates with improved survival and clinical regression. Mechanistically, TLR2 impairs early lung cancer progression via activation of cell intrinsic cell cycle arrest pathways and the proinflammatory senescence-associated secretory phenotype (SASP). The SASP regulates non-cell autonomous anti-tumor responses, such as immune surveillance of premalignant cells, and we observe impaired myeloid cell recruitment to lung tumors after Tlr2 loss. Last, we show that administration of a TLR2 agonist reduces lung tumor growth, highlighting TLR2 as a possible therapeutic target.F.R.M. is funded by a Wellcome Trust clinical research fellowship through the Edinburgh Clinical Academic Track (ECAT) program (203913/Z/16/Z), a Wellcome Trust-ISSF3 award (IS3-R1.07 20/21), and a Wellcome Trust iTPA award (209710/Z/17/Z). J.C.A. core lab funding was received from Cancer Research UK (C47559/A16243, Training and Career Development Board – Career Development Fellowship), the University of Edinburgh (Chancellor’s Fellowship), and the Ministry of Science and Innovation of the Government of Spain (Proyecto PID2020-117860GB-100 financiado por MCIN/AEI/10.13039/501100011033). S.W. is supported by a Cancer Research UK senior fellowship (A29576). J.C. is supported by a Wellcome Trust clinical lectureship through the ECAT program (203913/Z/16/Z). M.M. is supported by a CRUK Edinburgh Centre Award (C157/A25140). S.V. and J.F.P. are funded by National Institute on Aging (NIA) grants (R01AG 68048-1 and UG3CA 268103-1)

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

The SPHERE Study. Secondary prevention of heart disease in general practice: protocol of a randomised controlled trial of tailored practice and patient care plans with parallel qualitative, economic and policy analyses. [ISRCTN24081411]

BACKGROUND: The aim of the SPHERE study is to design, implement and evaluate tailored practice and personal care plans to improve the process of care and objective clinical outcomes for patients with established coronary heart disease (CHD) in general practice across two different health systems on the island of Ireland. CHD is a common cause of death and a significant cause of morbidity in Ireland. Secondary prevention has been recommended as a key strategy for reducing levels of CHD mortality and general practice has been highlighted as an ideal setting for secondary prevention initiatives. Current indications suggest that there is considerable room for improvement in the provision of secondary prevention for patients with established heart disease on the island of Ireland. The review literature recommends structured programmes with continued support and follow-up of patients; the provision of training, tailored to practice needs of access to evidence of effectiveness of secondary prevention; structured recall programmes that also take account of individual practice needs; and patient-centred consultations accompanied by attention to disease management guidelines. METHODS: SPHERE is a cluster randomised controlled trial, with practice-level randomisation to intervention and control groups, recruiting 960 patients from 48 practices in three study centres (Belfast, Dublin and Galway). Primary outcomes are blood pressure, total cholesterol, physical and mental health status (SF-12) and hospital re-admissions. The intervention takes place over two years and data is collected at baseline, one-year and two-year follow-up. Data is obtained from medical charts, consultations with practitioners, and patient postal questionnaires. The SPHERE intervention involves the implementation of a structured systematic programme of care for patients with CHD attending general practice. It is a multi-faceted intervention that has been developed to respond to barriers and solutions to optimal secondary prevention identified in preliminary qualitative research with practitioners and patients. General practitioners and practice nurses attend training sessions in facilitating behaviour change and medication prescribing guidelines for secondary prevention of CHD. Patients are invited to attend regular four-monthly consultations over two years, during which targets and goals for secondary prevention are set and reviewed. The analysis will be strengthened by economic, policy and qualitative components

Incidence and prevalence of dementia in linked administrative health data in Saskatchewan, Canada: a retrospective cohort study.

Determining the epidemiology of dementia among the population as a whole in specific jurisdictions - including the long-term care population-is essential to providing appropriate care. The objectives of this study were to use linked administrative databases in the province of Saskatchewan to determine the 12-month incidence and prevalence of dementia for the 2012/13 period (1) among individuals aged 45 and older in the province of Saskatchewan, (2) according to age group and sex, and (3) according to diagnosis code and other case definition criteria

Avicin D: A Protein Reactive Plant Isoprenoid Dephosphorylates Stat 3 by Regulating Both Kinase and Phosphatase Activities

Avicins, a class of electrophilic triterpenoids with pro-apoptotic, anti-inflammatory and antioxidant properties, have been shown to induce redox-dependant post-translational modification of cysteine residues to regulate protein function. Based on (a) the cross-talk that occurs between redox and phosphorylation processes, and (b) the role of Stat3 in the process of apoptosis and carcinogenesis, we chose to study the effects of avicins on the processes of phosphorylation/dephosphorylation in Stat3. Avicins dephosphorylate Stat3 in a variety of human tumor cell lines, leading to a decrease in the transcriptional activity of Stat3. The expression of Stat3-regulated proteins such as c-myc, cyclin D1, Bcl2, survivin and VEGF were reduced in response to avicin treatment. Underlying avicin-induced dephosphorylation of Stat3 was dephosphorylation of JAKs, as well as activation of protein phosphatase-1. Downregulation of both Stat3 activity and expression of Stat 3-controlled pro-survival proteins, contributes to the induction of apoptosis in avicin treated tumor cells. Based on the role of Stat3 in inflammation and wounding, and the in vivo inhibition of VEGF by avicins in a mouse skin carcinogenesis model, it is likely that avicin-induced inhibition of Stat3 activity results in the suppression of the pro-inflammatory and pro-oxidant stromal environment of tumors. Activation of PP-1, which also acts as a cellular economizer, combined with the redox regulation by avicins, can aid in redirecting metabolism from growth promoting anabolic to energy sparing pathways

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible

Exome sequencing and the management of neurometabolic disorders

BACKGROUND: Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. METHODS: To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. RESULTS: We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). CONCLUSIONS: Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.)