Geo-additive models of Childhood Undernutrition in three Sub-Saharan African Countries

We investigate the geographical and socioeconomic determinants of childhood undernutrition in Malawi, Tanzania and Zambia, three neighboring countries in Southern Africa using the 1992 Demographic and Health Surveys. We estimate models of undernutrition jointly for the three countries to explore regional patterns of undernutrition that transcend boundaries, while allowing for country-specific interactions. We use semiparametric models to flexibly model the effects of selected so-cioeconomic covariates and spatial effects. Our spatial analysis is based on a flexible geo-additive model using the district as the geographic unit of anal-ysis, which allows to separate smooth structured spatial effects from random effect. Inference is fully Bayesian and uses recent Markov chain Monte Carlo techniques. While the socioeconomic determinants generally confirm what is known in the literature, we find distinct residual spatial patterns that are not explained by the socioeconomic determinants. In particular, there appears to be a belt run-ning from Southern Tanzania to Northeastern Zambia which exhibits much worse undernutrition, even after controlling for socioeconomic effects. These effects do transcend borders between the countries, but to a varying degree. These findings have important implications for targeting policy as well as the search for left-out variables that might account for these residual spatial patterns

Realizing the potential of artificial intelligence in healthcare: Learning from intervention, innovation, implementation and improvement sciences

Introduction: Artificial intelligence (AI) is widely seen as critical for tackling fundamental challenges faced by health systems. However, research is scant on the factors that influence the implementation and routine use of AI in healthcare, how AI may interact with the context in which it is implemented, and how it can contribute to wider health system goals. We propose that AI development can benefit from knowledge generated in four scientific fields: intervention, innovation, implementation and improvement sciences. Aim: The aim of this paper is to briefly describe the four fields and to identify potentially relevant knowledge from these fields that can be utilized for understanding and/or facilitating the use of AI in healthcare. The paper is based on the authors' experience and expertise in intervention, innovation, implementation, and improvement sciences, and a selective literature review. Utilizing knowledge from the four fields: The four fields have generated a wealth of often-overlapping knowledge, some of which we propose has considerable relevance for understanding and/or facilitating the use of AI in healthcare. Conclusion: Knowledge derived from intervention, innovation, implementation, and improvement sciences provides a head start for research on the use of AI in healthcare, yet the extent to which this knowledge can be repurposed in AI studies cannot be taken for granted. Thus, when taking advantage of insights in the four fields, it is important to also be explorative and use inductive research approaches to generate knowledge that can contribute toward realizing the potential of AI in healthcare

The lung environment controls alveolar macrophage metabolism and responsiveness in type 2 inflammation

Fine control of macrophage activation is needed to prevent inflammatory disease, particularly at barrier sites such as the lungs. However, the dominant mechanisms that regulate the activation of pulmonary macrophages during inflammation are poorly understood. We found that alveolar macrophages (AlvMs) were much less able to respond to the canonical type 2 cytokine IL-4, which underpins allergic disease and parasitic worm infections, than macrophages from lung tissue or the peritoneal cavity. We found that the hyporesponsiveness of AlvMs to IL-4 depended upon the lung environment but was independent of the host microbiota or the lung extracellular matrix components surfactant protein D (SP-D) and mucin 5b (Muc5b). AlvMs showed severely dysregulated metabolism relative to that of cavity macrophages. After removal from the lungs, AlvMs regained responsiveness to IL-4 in a glycolysis-dependent manner. Thus, impaired glycolysis in the pulmonary niche regulates AlvM responsiveness during type 2 inflammation

The establishment of the GENEQOL consortium to investigate the genetic disposition of patient-reported quality-of-life outcomes

To our knowledge, no comprehensive, interdisciplinary initiatives have been taken to examine the role of genetic variants on patient-reported quality-of-life outcomes. The overall objective of this paper is to describe the establishment of an international and interdisciplinary consortium, the GENEQOL Consortium, which intends to investigate the genetic disposition of patient-reported quality-of-life outcomes. We have identified five primary patient-reported quality-of-life outcomes as initial targets: negative psychological affect, positive psychological affect, self-rated physical health, pain, and fatigue. The first tangible objective of the GENEQOL Consortium is to develop a list of potential biological pathways, genes and genetic variants involved in these quality-of-life outcomes, by reviewing current genetic knowledge. The second objective is to design a research agenda to investigate and validate those genes and genetic variants of patient-reported quality-of-life outcomes, by creating large datasets. During its first meeting, the Consortium has discussed draft summary documents addressing these questions for each patient-reported quality-of-life outcome. A summary of the primary pathways and robust findings of the genetic variants involved is presented here. The research agenda outlines possible research objectives and approaches to examine these and new quality-of-life domains. Intriguing questions arising from this endeavor are discussed. Insight into the genetic versus environmental components of patient-reported quality-of-life outcomes will ultimately allow us to explore new pathways for improving patient care. If we can identify patients who are susceptible to poor quality of life, we will be able to better target specific clinical interventions to enhance their quality of life and treatment outcome

Surface-enhanced Raman scattering measurement from a lipid bilayer encapsulating a single decahedral nanoparticle mediated by an optical trap

We present a new technique for the study of model membranes on the length-scale of a single nanosized liposome. Silver decahedral nanoparticles have been encapsulated by a model unilamellar lipid bilayer creating nano-sized lipid vesicles. The metal core has two roles (i) increasing the polarizability of vesicles, enabling a single vesicle to be isolated and confined in an optical trap, and (ii) enhancing Raman scattering from the bilayer, via the high surface-plasmon field at the sharp vertices of the decahedral particles. Combined this has allowed us to measure a Raman fingerprint from a single vesicle of 50 nmdiameter, containing just ∼104 lipid molecules in a bilayer membrane over a surface area of <0.01 µm2, equivalent to a volume of approximately 1 zepto-litre. Raman scattering is a weak and inefficient process and previous studies have required either a substantially larger bilayer area in order to obtain a detectable signal, or the tagging of lipid molecules with a chromophore to provide an indirect probe of the bilayer. Our approach is fully label-free and bio-compatible and, in the future, it will enable much more localized studies of the heterogeneous structure of lipid bilayers and of membrane-bound components than is currently possible

Oil and gas:a blessing for the few. Hydrocarbons and inequality within regions in Russia

Building on earlier work on regional inequality in Russia the article seeks to demonstrate that the regional oil and gas abundance is associated with high within-region inequality. It provides empirical evidence that hydrocarbons represent one of the leading determinants of an increased gap between rich and poor in the producing regions. The discussion focuses on a possible cluster of geographic, economic and political factors underlying the phenomenon

Inequities in under-five child malnutrition in South Africa

OBJECTIVES: To assess and quantify the magnitude of inequalities in under-five child malnutrition, particularly those ascribable to socio-economic status and to consider the policy implications of these findings. METHODS: Data on 3765 under-five children were derived from the Living Standards and Development Survey. Household income, proxied by per capita household expenditure, was used as the main indicator of socio-economic status. Socio-economic inequality in malnutrition (stunting, underweight and wasting) was measured using the illness concentration index. The concentration index was calculated for the whole sample, as well as for different population groups, areas of residence (rural, urban and metropolitan) and for each province. RESULTS: Stunting was found to be the most prevalent form of malnutrition in South Africa. Consistent with expectation, the rate of stunting is observed to be the highest in the Eastern Cape and the Northern Province – provinces with the highest concentration of poverty. There are considerable pro-rich inequalities in the distribution of stunting and underweight. However, wasting does not manifest gradients related to socio-economic position. Among White children, no inequities are observed in all three forms of malnutrition. The highest pro-rich inequalities in stunting and underweight are found among Coloured children and metropolitan areas. There is a tendency for high pro-rich concentration indices in those provinces with relatively lower rates of stunting and underweight (Gauteng and the Western Cape). CONCLUSION: There are significant differences in under-five child malnutrition (stunting and underweight) that favour the richest of society. These are unnecessary, avoidable and unjust. It is demonstrated that addressing such socio-economic gradients in ill-health, which perpetuate inequalities in the future adult population requires a sound evidence base. Reliance on global averages alone can be misleading. Thus there is a need for evaluating policies not only in terms of improvements in averages, but also improvements in distribution. Furthermore, addressing problems of stunting and underweight, which are found to be responsive to improvements in household income status, requires initiatives that transcend the medical arena