MAIZE MARKETS AND RURAL STORAGE IN MOZAMBIQUE: A SPATIAL AND TEMPORAL ANALYSIS

We employ a mixed complementarity problem (MCP) approach to a spatial and temporal equilibrium model of the maize market in Mozambique. The MCP approach efficiently captures interactions between transpost costs and interest rates, which captures interactions between transport costs and interest rates, which may differ across agents. Results indicate that differentials in interest rates significantly impact marketing patterns.Marketing, Public Economics,

Protocol for ADDITION-PRO: a longitudinal cohort study of the cardiovascular experience of individuals at high risk for diabetes recruited from Danish primary care.

BACKGROUND: Screening programmes for type 2 diabetes inevitably find more individuals at high risk for diabetes than people with undiagnosed prevalent disease. While well established guidelines for the treatment of diabetes exist, less is known about treatment or prevention strategies for individuals found at high risk following screening. In order to make better use of the opportunities for primary prevention of diabetes and its complications among this high risk group, it is important to quantify diabetes progression rates and to examine the development of early markers of cardiovascular disease and microvascular diabetic complications. We also require a better understanding of the mechanisms that underlie and drive early changes in cardiometabolic physiology. The ADDITION-PRO study was designed to address these issues among individuals at different levels of diabetes risk recruited from Danish primary care. METHODS/DESIGN: ADDITION-PRO is a population-based, longitudinal cohort study of individuals at high risk for diabetes. 16,136 eligible individuals were identified at high risk following participation in a stepwise screening programme in Danish general practice between 2001 and 2006. All individuals with impaired glucose regulation at screening, those who developed diabetes following screening, and a random sub-sample of those at lower levels of diabetes risk were invited to attend a follow-up health assessment in 2009-2011 (n=4,188), of whom 2,082 (50%) attended. The health assessment included detailed measurement of anthropometry, body composition, biochemistry, physical activity and cardiovascular risk factors including aortic stiffness and central blood pressure. All ADDITION-PRO participants are being followed for incident cardiovascular disease and death. DISCUSSION: The ADDITION-PRO study is designed to increase understanding of cardiovascular risk and its underlying mechanisms among individuals at high risk of diabetes. Key features of this study include (i) a carefully characterised cohort at different levels of diabetes risk; (ii) detailed measurement of cardiovascular and metabolic risk factors; (iii) objective measurement of physical activity behaviour; and (iv) long-term follow-up of hard clinical outcomes including mortality and cardiovascular disease. Results will inform policy recommendations concerning cardiovascular risk reduction and treatment among individuals at high risk for diabetes. The detailed phenotyping of this cohort will also allow a number of research questions concerning early changes in cardiometabolic physiology to be addressed.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

MAIZE MARKETS AND RURAL STORAGE IN MOZAMBIQUE: A SPATIAL AND TEMPORAL ANALYSIS

We employ a mixed complementarity problem (MCP) approach to a spatial and temporal equilibrium model of the maize market in Mozambique. The MCP approach efficiently captures interactions between transpost costs and interest rates, which captures interactions between transport costs and interest rates, which may differ across agents. Results indicate that differentials in interest rates significantly impact marketing patterns

Reduction of Specific Circulating Lymphocyte Populations with Metabolic Risk Factors in Patients at Risk to Develop Type 2 Diabetes

<div><p>Low-grade inflammation, characterized by increased pro-inflammatory cytokine levels, is present in patients with obesity-linked insulin resistance, hyperglycemia and hyperlipidemia and considered to play a leading role to progression into type 2 diabetes (T2D). In adipose tissue in obese patients and in pancreatic islets in T2D patients cellular inflammation is present. However, the systemic leukocyte compartment and the circulating endothelial/precursor compartment in patients at risk to develop T2D has so far not been analyzed in detail. To address this, peripheral blood cells from a cohort of 20 subjects at risk to develop diabetes with normal to impaired glucose tolerance were analyzed by flow cytometry using a wide range of cellular markers and correlated to known metabolic risk factors for T2D i.e. fasting plasma glucose (FPG), 2 h plasma glucose (2 h PG), HbA1c, body mass index (BMI), homeostasis model assessment of β-cell function (HOMA-B), homeostasis model assessment of insulin sensitivity (HOMA-IS) and fasting insulin (FI). The four highest ranked cell markers for each risk factor were identified by random forest analysis. In the cohort, a significant negative correlation between the number of TLR4⁺ CD4 T cells and increased FPG was demonstrated. Similarly, with increased BMI the frequency of TLR4⁺ B cells was significantly decreased, as was the frequency of IL-21R⁺ CD4 T cells. Unlinked to metabolic risk factors, the frequency of regulatory T cells was reduced and TLR4⁺ CD4 T cells were increased with age. Taken together, in this small cohort of subjects at risk to develop T2D, a modulation of the circulating immune cell pool was demonstrated to correlate with risk factors like FPG and BMI. This may provide novel insights into the inflammatory mechanisms involved in the progression to diabetes in subjects at risk.</p></div

Representative flow cytometric analysis of peripheral blood, CD45 versus CD31 (A), CD31⁺CD34⁺CD45^dimCD133^dim CPC cells (B) and CD31^brightCD34⁻CD45⁻CD133⁻ CEC cells (C).

<p>The numbers represent percentage of cells within the gates. At least 10⁶ total cells were acquired followed by gating on size versus granularity followed by exclusion of dead cells and finally detection of markers described in plots.</p

Circulating endothelial and endothelial precursor cells.

<p>Data is displayed as mean ± standard deviation.</p><p>Circulating endothelial and endothelial precursor cells.</p

Representative flow cytometric analysis of peripheral blood CD68 positive monocytes (A), M1-like CD163^−/intCD11c^high monocytes and M2-like CD163^int/hiCD11c^int monocytes (B), IL-21R⁺ monocytes and TLR4⁺ monocytes (C).

<p>The numbers represent percentage of cells within the gates. At least 10⁶ total cells were acquired followed by gating on size versus granularity followed by exclusion of dead cells and finally detection of markers described in plots.</p

Representative flow cytometric analysis of peripheral blood CD19 positive B cells (A), IL-21R versus TLR4 on B cells (B).

<p>The numbers represent percentage of cells within the gates/quadrants. At least 10⁶ total cells were acquired followed by gating on size versus granularity followed by exclusion of dead cells and finally detection of markers described in plots.</p

Frequency of TLR4⁺ T cells in peripheral blood before and 75 min post meal (A).

<p>Cytokine production in CD4⁺ T cells in peripheral blood before and after activation of the cells for 4 h <i>ex vivo</i>: IL-4 (B), IFN-γ (C), IL-17 (D), IL-21 (E). Frequency of CECs (F) and CPCs (G) in peripheral blood before and 75 min post meal. Statistics was obtained using unpaired two-way T-test using Welsh correction.</p

Peripheral blood B cells. Data is displayed as mean ± standard deviation.

<p>Peripheral blood B cells. Data is displayed as mean ± standard deviation.</p