The Latin American Consortium of Studies in Obesity (LASO)

Current, high-quality data are needed to evaluate the health impact of the epidemic of obesity in Latin America. The Latin American Consortium of Studies of Obesity (LASO) has been established, with the objectives of (i) Accurately estimating the prevalence of obesity and its distribution by sociodemographic characteristics; (ii) Identifying ethnic, socioeconomic and behavioural determinants of obesity; (iii) Estimating the association between various anthropometric indicators or obesity and major cardiovascular risk factors and (iv) Quantifying the validity of standard definitions of the various indexes of obesity in Latin American population. To achieve these objectives, LASO makes use of individual data from existing studies. To date, the LASO consortium includes data from 11 studies from eight countries (Argentina, Chile, Colombia, Costa Rica, Dominican Republic, Peru, Puerto Rico and Venezuela), including a total of 32 462 subjects. This article describes the overall organization of LASO, the individual studies involved and the overall strategy for data analysis. LASO will foster the development of collaborative obesity research among Latin American investigators. More important, results from LASO will be instrumental to inform health policies aiming to curtail the epidemic of obesity in the region

Variability in transmissibility of the 2009 H1N1 pandemic in Canadian communities

Abstract Background The prevalence and severity of the 2009 H1N1 pandemic appeared to vary significantly across populations and geographic regions. We sought to investigate the variability in transmissibility of H1N1 pandemic in different health regions (including urban centres and remote, isolated communities) in the province of Manitoba, Canada. Methods The Richards model was used to fit to the daily number of laboratory-confirmed cases and estimate transmissibility (referred to as the basic reproduction number, R0), doubling times, and turning points of outbreaks in both spring and fall waves of the H1N1 pandemic in several health regions. Results We observed considerable variation in R0 estimates ranging from 1.55 to 2.24, with confidence intervals ranging from 1.45 to 2.88, for an average generation time of 2.9 days, and shorter doubling times in some remote and isolated communities compared to urban centres, suggesting a more rapid spread of disease in these communities during the first wave. For the second wave, R e , the effective reproduction number, is estimated to be lower for remote and isolated communities; however, outbreaks appear to have been driven by somewhat higher transmissibility in urban centres. Conclusions There was considerable geographic variation in transmissibility of the 2009 pandemic outbreaks. While highlighting the importance of estimating R0 for informing health responses, the findings indicate that projecting the transmissibility for large-scale epidemics may not faithfully characterize the early spread of disease in remote and isolated communities

Exhaled Aerosol Transmission of Pandemic and Seasonal H1N1 Influenza Viruses in the Ferret

Person-to-person transmission of influenza viruses occurs by contact (direct and fomites) and non-contact (droplet and small particle aerosol) routes, but the quantitative dynamics and relative contributions of these routes are incompletely understood. The transmissibility of influenza strains estimated from secondary attack rates in closed human populations is confounded by large variations in population susceptibilities. An experimental method to phenotype strains for transmissibility in an animal model could provide relative efficiencies of transmission. We developed an experimental method to detect exhaled viral aerosol transmission between unanesthetized infected and susceptible ferrets, measured aerosol particle size and number, and quantified the viral genomic RNA in the exhaled aerosol. During brief 3-hour exposures to exhaled viral aerosols in airflow-controlled chambers, three strains of pandemic 2009 H1N1 strains were frequently transmitted to susceptible ferrets. In contrast one seasonal H1N1 strain was not transmitted in spite of higher levels of viral RNA in the exhaled aerosol. Among three pandemic strains, the two strains causing weight loss and illness in the intranasally infected ‘donor’ ferrets were transmitted less efficiently from the donor than the strain causing no detectable illness, suggesting that the mucosal inflammatory response may attenuate viable exhaled virus. Although exhaled viral RNA remained constant, transmission efficiency diminished from day 1 to day 5 after donor infection. Thus, aerosol transmission between ferrets may be dependent on at least four characteristics of virus-host relationships including the level of exhaled virus, infectious particle size, mucosal inflammation, and viral replication efficiency in susceptible mucosa

The spatial and temporal patterns of falciparum and vivax malaria in Perú: 1994–2006

<p>Abstract</p> <p>Background</p> <p>Malaria is the direct cause of approximately one million deaths worldwide each year, though it is both preventable and curable. Increasing the understanding of the transmission dynamics of falciparum and vivax malaria and their relationship could suggest improvements for malaria control efforts. Here the weekly number of malaria cases due to <it>Plasmodium falciparum </it>(1994–2006) and <it>Plasmodium vivax </it>(1999–2006) in Perú at different spatial scales in conjunction with associated demographic, geographic and climatological data are analysed.</p> <p>Methods</p> <p>Malaria periodicity patterns were analysed through wavelet spectral analysis, studied patterns of persistence as a function of community size and assessed spatial heterogeneity via the Lorenz curve and the summary Gini index.</p> <p>Results</p> <p>Wavelet time series analyses identified annual cycles in the incidence of both malaria species as the dominant pattern. However, significant spatial heterogeneity was observed across jungle, mountain and coastal regions with slightly higher levels of spatial heterogeneity for <it>P. vivax </it>than <it>P. falciparum</it>. While the incidence of <it>P. falciparum </it>has been declining in recent years across geographic regions, <it>P. vivax </it>incidence has remained relatively steady in jungle and mountain regions with a slight decline in coastal regions. Factors that may be contributing to this decline are discussed. The time series of both malaria species were significantly synchronized in coastal (ρ = 0.9, P < 0.0001) and jungle regions (ρ = 0.76, P < 0.0001) but not in mountain regions. Community size was significantly associated with malaria persistence due to both species in jungle regions, but not in coastal and mountain regions.</p> <p>Conclusion</p> <p>Overall, findings highlight the importance of highly refined spatial and temporal data on malaria incidence together with demographic and geographic information in improving the understanding of malaria persistence patterns associated with multiple malaria species in human populations, impact of interventions, detection of heterogeneity and generation of hypotheses.</p

Planning for the next influenza H1N1 season: a modelling study

<p>Abstract</p> <p>Background</p> <p>The level of herd immunity before and after the first 2009 pandemic season is not precisely known, and predicting the shape of the next pandemic H1N1 season is a difficult challenge.</p> <p>Methods</p> <p>This was a modelling study based on data on medical visits for influenza-like illness collected by the French General Practitioner Sentinel network, as well as pandemic H1N1 vaccination coverage rates, and an individual-centred model devoted to influenza. We estimated infection attack rates during the first 2009 pandemic H1N1 season in France, and the rates of pre- and post-exposure immunity. We then simulated various scenarios in which a pandemic influenza H1N1 virus would be reintroduced into a population with varying levels of protective cross-immunity, and considered the impact of extending influenza vaccination.</p> <p>Results</p> <p>During the first pandemic season in France, the proportion of infected persons was 18.1% overall, 38.3% among children, 14.8% among younger adults and 1.6% among the elderly. The rates of pre-exposure immunity required to fit data collected during the first pandemic season were 36% in younger adults and 85% in the elderly. We estimated that the rate of post-exposure immunity was 57.3% (95% Confidence Interval (95%CI) 49.6%-65.0%) overall, 44.6% (95%CI 35.5%-53.6%) in children, 53.8% (95%CI 44.5%-63.1%) in younger adults, and 87.4% (95%CI 82.0%-92.8%) in the elderly.</p> <p>The shape of a second season would depend on the degree of persistent protective cross-immunity to descendants of the 2009 H1N1 viruses. A cross-protection rate of 70% would imply that only a small proportion of the population would be affected. With a cross-protection rate of 50%, the second season would have a disease burden similar to the first, while vaccination of 50% of the entire population, in addition to the population vaccinated during the first pandemic season, would halve this burden. With a cross-protection rate of 30%, the second season could be more substantial, and vaccination would not provide a significant benefit.</p> <p>Conclusions</p> <p>These model-based findings should help to prepare for a second pandemic season, and highlight the need for studies of the different components of immune protection.</p

The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group

The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival in several cancer settings. A subgroup of women with breast cancer (BC) has immunogenic infiltration of lymphocytes with expression of programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the programmed death 1 (PD-1)/PD-L1 signaling axis. The use of tumor-infiltrating lymphocytes (TILs) as predictive and prognostic biomarkers has been under intense examination. Emerging data suggest that TILs are associated with response to both cytotoxic treatments and immunotherapy, particularly for patients with triple-negative BC. In this review from The International Immuno-Oncology Biomarker Working Group, we discuss (a) the biological understanding of TILs, (b) their analytical and clinical validity and efforts toward the clinical utility in BC, and (c) the current status of PD-L1 and TIL testing across different continents, including experiences from low-to-middle-income countries, incorporating also the view of a patient advocate. This information will help set the stage for future approaches to optimize the understanding and clinical utilization of TIL analysis in patients with BC

Identification and Pathway Analysis of microRNAs with No Previous Involvement in Breast Cancer

microRNA expression signatures can differentiate normal and breast cancer tissues and can define specific clinico-pathological phenotypes in breast tumors. In order to further evaluate the microRNA expression profile in breast cancer, we analyzed the expression of 667 microRNAs in 29 tumors and 21 adjacent normal tissues using TaqMan Low-density arrays. 130 miRNAs showed significant differential expression (adjusted P value = 0.05, Fold Change = 2) in breast tumors compared to the normal adjacent tissue. Importantly, the role of 43 of these microRNAs has not been previously reported in breast cancer, including several evolutionary conserved microRNA*, showing similar expression rates to that of their corresponding leading strand. The expression of 14 microRNAs was replicated in an independent set of 55 tumors. Bioinformatic analysis of mRNA targets of the altered miRNAs, identified oncogenes like ERBB2, YY1, several MAP kinases, and known tumor-suppressors like FOXA1 and SMAD4. Pathway analysis identified that some biological process which are important in breast carcinogenesis are affected by the altered microRNA expression, including signaling through MAP kinases and TP53 pathways, as well as biological processes like cell death and communication, focal adhesion and ERBB2-ERBB3 signaling. Our data identified the altered expression of several microRNAs whose aberrant expression might have an important impact on cancer-related cellular pathways and whose role in breast cancer has not been previously described

Behavioral modeling of human choices reveals dissociable effects of physical effort and temporal delay on reward devaluation

There has been considerable interest from the fields of biology, economics, psychology, and ecology about how decision costs decrease the value of rewarding outcomes. For example, formal descriptions of how reward value changes with increasing temporal delays allow for quantifying individual decision preferences, as in animal species populating different habitats, or normal and clinical human populations. Strikingly, it remains largely unclear how humans evaluate rewards when these are tied to energetic costs, despite the surge of interest in the neural basis of effort-guided decision-making and the prevalence of disorders showing a diminished willingness to exert effort (e.g., depression). One common assumption is that effort discounts reward in a similar way to delay. Here we challenge this assumption by formally comparing competing hypotheses about effort and delay discounting. We used a design specifically optimized to compare discounting behavior for both effort and delay over a wide range of decision costs (Experiment 1). We then additionally characterized the profile of effort discounting free of model assumptions (Experiment 2). Contrary to previous reports, in both experiments effort costs devalued reward in a manner opposite to delay, with small devaluations for lower efforts, and progressively larger devaluations for higher effort-levels (concave shape). Bayesian model comparison confirmed that delay-choices were best predicted by a hyperbolic model, with the largest reward devaluations occurring at shorter delays. In contrast, an altogether different relationship was observed for effort-choices, which were best described by a model of inverse sigmoidal shape that is initially concave. Our results provide a novel characterization of human effort discounting behavior and its first dissociation from delay discounting. This enables accurate modelling of cost-benefit decisions, a prerequisite for the investigation of the neural underpinnings of effort-guided choice and for understanding the deficits in clinical disorders characterized by behavioral inactivity