18 research outputs found

    Lack of PPARγ in Myeloid Cells Confers Resistance to Listeria monocytogenes Infection

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    The peroxisomal proliferator-activated receptor γ (PPARγ) is a nuclear receptor that controls inflammation and immunity. Innate immune defense against bacterial infection appears to be compromised by PPARγ. The relevance of PPARγ in myeloid cells, that organize anti-bacterial immunity, for the outcome of immune responses against intracellular bacteria such as Listeria monocytogenes in vivo is unknown. We found that Listeria monocytogenes infection of macrophages rapidly led to increased expression of PPARγ. This prompted us to investigate whether PPARγ in myeloid cells influences innate immunity against Listeria monocytogenes infection by using transgenic mice with myeloid-cell specific ablation of PPARγ (LysMCre×PPARγflox/flox). Loss of PPARγ in myeloid cells results in enhanced innate immune defense against Listeria monocytogenes infection both, in vitro and in vivo. This increased resistance against infection was characterized by augmented levels of bactericidal factors and inflammatory cytokines: ROS, NO, IFNγ TNF IL-6 and IL-12. Moreover, myeloid cell-specific loss of PPARγ enhanced chemokine and adhesion molecule expression leading to improved recruitment of inflammatory Ly6Chi monocytes to sites of infection. Importantly, increased resistance against Listeria infection in the absence of PPARγ was not accompanied by enhanced immunopathology. Our results elucidate a yet unknown regulatory network in myeloid cells that is governed by PPARγ and restrains both listeriocidal activity and recruitment of inflammatory monocytes during Listeria infection, which may contribute to bacterial immune escape. Pharmacological interference with PPARγ activity in myeloid cells might represent a novel strategy to overcome intracellular bacterial infection

    Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

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    Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

    Rising rural body-mass index is the main driver of the global obesity epidemic in adults

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    Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

    Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)

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    From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions

    From research to clinical practice: a European neuroradiological survey on quantitative advanced MRI implementation

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    Objective: Quantitative MRI (qMRI) methods provide versatile neuroradiological applications and are a hot topic in research. The degree of their clinical implementation is however barely known. This survey was created to illuminate which and how qMRI techniques are currently applied across Europe. Methods: In total, 4753 neuroradiologists from 27 countries received an online questionnaire. Demographic and professional data, experience with qMRI techniques in the brain and head and neck, usage, reasons for/against application, and knowledge of the QIBA and EIBALL initiatives were assessed. Results: Two hundred seventy-two responders in 23 countries used the following techniques clinically (mean values in %): DWI (82.0%, n = 223), DSC (67.3%, n = 183), MRS (64.3%, n = 175), DCE (43.4%, n = 118), BOLD-fMRI (42.6%, n = 116), ASL (37.5%, n = 102), fat quantification (25.0%, n = 68), T2 mapping (16.9%, n = 46), T1 mapping (15.1%, n = 41), PET-MRI (11.8%, n = 32), IVIM (5.5%, n = 15), APT-CEST (4.8%, n = 13), and DKI (3.3%, n = 9). The most frequent usage indications for any qMRI technique were tissue differentiation (82.4%, n = 224) and oncological monitoring (72.8%, n = 198). Usage differed between countries, e.g. ASL: Germany (n = 13/63; 20.6%) vs. France (n = 31/40; 77.5%). Neuroradiologists endorsed the use of qMRI because of an improved diagnostic accuracy (89.3%, n = 243), but 50.0% (n = 136) are in need of better technology, 34.9% (n = 95) wish for more communication, and 31.3% need help with result interpretation/generation (n = 85). QIBA and EIBALL were not well known (12.5%, n = 34, and 11.0%, n = 30). Conclusions: The clinical implementation of qMRI methods is highly variable. Beyond the aspect of readiness for clinical use, better availability of support and a wider dissemination of guidelines could catalyse a broader implementation. Key Points: • Neuroradiologists endorse the use of qMRI techniques as they subjectively improve diagnostic accuracy. • Clinical implementation is highly variable between countries, techniques, and indications. • The use of advanced imaging could be promoted through an increase in technical support and training of both doctors and technicians

    Enhanced effector functions following abelation of PPARγ from myeloid cells.

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    <p>(A) BMDM from LysM- PPARγ<sup>WT</sup> and LysM- PPARγ<sup>KO</sup> mice were infected <i>in vitro</i> with <i>L.monocytogenes</i> at a MOI 10. Expression of IFNγ, TNF, IL-1β, IL-6 and IL-12 was determined 6 hrs post infection in cell culture supernatant by ELISA. The data shown are means ± SE of three independent experiments. (B) Looking at the paracrine effects of PPARγ ablation in myeloid cells, we infected BMDM from wild type C57BL/6 mice with <i>Listeria</i> at an MOI of 10 and incubated them with sterile filtered conditioned medium from PPARγ<sup>WT</sup> or PPARγ<sup>KO</sup> macrophages infected previously for 18 hrs with <i>L. monocytogenes</i>; at the indicated time points intracellular <i>Listeria</i> growth was determined as CFU/ml in the lysates of infected cells. Experiments were performed in triplicates. One representative out of four experiments is shown. The <i>p</i> value for titers of wt vs. ko at 4 hrs post infection were <0.05.</p

    PPARγ expression is induced in bone-marrow derived monocytes after infection with <i>Listeria monocytogenes</i>.

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    <p>(A) Time course of PPARγ expression in human monocytes following <i>Listeria monocytogenes</i> infection detected by Western blot. (B) PPARγ target genes (n = 80) with the most significant differential expression in human macrophages post infection. Gene expression differences (log scale) are visualized as a heat map following hierarchical clustering of rows and columns (red = increased expression). (C,D) Time course of PPARγ expression in bone marrow derived macrophages (BMDM) post infection detected by Western blot or immunohistochemistry. (blue = DAPI staining the cell nucleus and <i>Listeria</i> DNA; green = PPARγ).</p

    Similar phagocytic capacity in myeloid cells from LysM- PPARγ<sup>WT</sup> and LysM- PPARγ<sup>KO</sup> mice.

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    <p>Bone marrow derived macrophages (BMDM) and peritoneal exudates cells (PEC) from LysM- PPARγ<sup>WT</sup> and LysM- PPARγ<sup>KO</sup> mice were infected with FITC-labelled <i>Listeria</i> at MOI 2 or MOI 5). (A) Mean fluorescence intensity (MFI) of FITC positive cells was assessed by flow cytometry. and (B) Percentage of <i>Listeria</i> containing macrophages (FITC positive). (C) BMDM or PEC from LysM- PPARγ<sup>WT</sup> and LysM- PPARγ<sup>KO</sup> mice were infected with <i>Listeria</i> (MOI 10) and intracellular <i>Listeria</i> growth was determined as CFU/ml in the lysates of infected cells. The <i>p</i> values for titres of WT vs. KO at 4 hrs p.i. were <0.05 and <0.01 for BMDM and PEC, respectively. (D–F) BMDM from LysM- PPARγ<sup>WT</sup> and LysM- PPARγ<sup>KO</sup> mice were infected with <i>Listeria</i> (MOI of 10). The capacity to produce reactive oxygen species (ROS) in <i>Listeria</i> infected macrophages was determined by the OxyBURST reagent (D). At 24 hrs p.i. the concentration of NO2- as surrogate marker for the production of reactive nitrogen intermediates was determined with Griess reagent (E). Expression of iNOS was analyzed by quantitative RT-PCR (F).</p
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