Protocol of the Nutritional, Psychosocial, and Environmental Determinants of Neurodevelopment and Child Mental Health (COINCIDE) study

BACKGROUND: Over 250 million children are developing sub-optimally due to their exposure to early life adversities. While previous studies have examined the independent effects of nutritional status, psychosocial adversities, and environmental pollutants on children's outcomes, little is known about their interaction and cumulative effects.OBJECTIVES: This study aims to investigate the independent, interaction, and cumulative effects of nutritional, psychosocial, and environmental factors on children's cognitive development and mental health in urban and rural India. It also seeks to explain pathways leading to inequities in child outcomes at the individual, household, and neighbourhood levels.METHODS: A mixed-methods prospective cohort study will be conducted on 1600 caregiver-child dyads (child age 3-10 years) in urban and rural India. Nutritional status, psychosocial adversities, environmental pollutants, and child mental health outcomes will be assessed using parent-report questionnaires. Performance-based measures will be used to assess cognitive outcomes. Venous blood and urine samples will be used to measure nutritional and pesticide biomarkers in 500 children. Indoor air pollution will be monitored in 200 households twice, during two seasons. Multilevel regression, weighted quantile sum regression, and Bayesian kernel machine regression will assess the individual and combined effects of exposures on child outcomes. Thematic analysis of in-depth interviews and focus group discussions will explore pathways to middle-and late childhood development inequities.DISCUSSION: The data will be used to formulate a Theory of Change (ToC) to explain the biological, psychosocial, and environmental origins of children's cognitive and mental health outcomes across the first decade of life in diverse Indian settings, which can inform interventions targets for promoting children's outcomes beyond the first 1000 days, potentially generalizable to similar under-resourced global settings. The COINCIDE research infrastructure will comprise a valuable global health resource, including prospective cohort data, validated study tools, and stored biological and environmental samples for future studies.</p

Human predecidual stromal cells are mesenchymal stromal/stem cells and have a therapeutic effect in an immune-based mouse model of recurrent spontaneous abortion

Human decidual stromal cells (DSCs) are involved in the maintenance and development of pregnancy, in which they play a key role in the induction of immunological maternal–fetal tolerance. Precursors of DSCs (preDSCs) are located around the vessels, and based on their antigen phenotype, previous studies suggested a relationship between preDSCs and mesenchymal stromal/stem cells (MSCs). This work aimed to further elucidate the MSC characteristics of preDSCs. Under the effect of P4 and cAMP, the preDSC lines and clones decidualized in vitro: the cells became rounder and secreted PRL, a marker of physiological decidualization. PreDSC lines and clones also exhibited MSC characteristics. They differentiated into adipocytes, osteoblasts, and chondrocytes, and preDSC lines expressed stem cell markers OCT- 4, NANOG, and ABCG2; exhibited a cloning efficiency of 4 to 15%; significantly reduced the embryo resorption rate (P < 0.001) in the mouse model of abortion; and survived for prolonged periods in immunocompetent mice. The fact that 3 preDSC clones underwent both decidualization and mesenchymal differentiation shows that the same type of cell exhibited both DSC and MSC characteristics. Together, our results confirm that preDSCs are decidual MSCs and suggest that these cells are involved in the mechanisms of maternal–fetal immune toleranceThis work was supported by the Plan Estatal de Investigación Científica y Técnica y de Innovación 2013–2016, ISCIII-Subdirección General de Evaluación y Fomento de la Investigación, the Ministerio de Economía y Competitividad, Spain (Grant PI16/01642) and European Regional Development Fund (ERDF/ FEDER funding), the European Community, and the Cátedra de Investigación Anto nio Chamorro–Alejandro Otero, Universidad de Granada (CACH2017-1)

Accuracy enhancement of the viola-jones algorithm for thermal face detection

Face detection is the first step for many facial analysis applications and has been extensively researched in the visible spectrum. While significant progress has been made in the field of face detection in the visible spectrum, the performance of current face detection methods in the thermal infrared spectrum is far from perfect and unable to cope with real-time applications. As the Viola-Jones algorithm has become a common method of face detection, this paper aims to improve the performance of the Viola-Jones algorithm in the thermal spectrum for detecting faces with or without eyeglasses. A performance comparison has been made of three different features, HOG, LBP, and Haar-like, to find the most suitable one for face detection from thermal images. Additionally, to accelerate the detection speed, a pre-processing stage is added in both training and detecting phases. Two pre-processing methods have been tested and compared, together with the three features. It is found that the proposed process for performance enhancement gave higher detection accuracy (95%) than the Viola-Jones method (90%) and doubled the detection speed as well