A major T cell antigen of Mycobacterium leprae is a 10-kD heat-shock cognate protein.

Several mycobacterial antigens, identified by monoclonal antibodies and patient sera, have been found to be homologous to stress or heat-shock proteins (hsp) defined in Escherichia coli and yeast. A major antigen recognized by most Mycobacterium leprae-reactive human T cell lines and cell wall-reactive T cell clones is a 10-kD protein that has now been cloned and sequenced. The predicted amino acid sequence of this protein is 44% homologous to the hsp 10 (GroES) of E. coli. The purified native and recombinant 10-kD protein was found to be a stronger stimulator of peripheral blood T cell proliferation than other native and recombinant M. leprae proteins tested. The degree of reactivity paralleled the response to intact M. leprae throughout the spectrum of leprosy. Limiting-dilution analysis of peripheral blood lymphocytes from a patient contact and a tuberculoid patient indicated that approximately one third of M. leprae-reactive T cell precursors responded to the 10-kD antigen. T cell lines derived from lepromin skin tests were strongly responsive to the 10-kD protein. T cell clones reactive to both the purified native and recombinant 10-kD antigens recognized M. leprae-specific epitopes as well as epitopes crossreactive with the cognate antigen of M. tuberculosis. Further, the purified hsp 10 elicited strong delayed-type hypersensitivity reactions in guinea pigs sensitized to M. leprae. The strong T cell responses against the M. leprae 10-kD protein suggest a role for this heat-shock cognate protein in the protective/resistant responses to infection

Real-time numerical forecast of global epidemic spreading: Case study of 2009 A/H1N1pdm

Background Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches. Methods We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability. Results Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model. Conclusions Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models

Seasonal transmission potential and activity peaks of the new influenza A(H1N1): a Monte Carlo likelihood analysis based on human mobility

On 11 June the World Health Organization officially raised the phase of pandemic alert (with regard to the new H1N1 influenza strain) to level 6. We use a global structured metapopulation model integrating mobility and transportation data worldwide in order to estimate the transmission potential and the relevant model parameters we used the data on the chronology of the 2009 novel influenza A(H1N1). The method is based on the maximum likelihood analysis of the arrival time distribution generated by the model in 12 countries seeded by Mexico by using 1M computationally simulated epidemics. An extended chronology including 93 countries worldwide seeded before 18 June was used to ascertain the seasonality effects. We found the best estimate R0 = 1.75 (95% CI 1.64 to 1.88) for the basic reproductive number. Correlation analysis allows the selection of the most probable seasonal behavior based on the observed pattern, leading to the identification of plausible scenarios for the future unfolding of the pandemic and the estimate of pandemic activity peaks in the different hemispheres. We provide estimates for the number of hospitalizations and the attack rate for the next wave as well as an extensive sensitivity analysis on the disease parameter values. We also studied the effect of systematic therapeutic use of antiviral drugs on the epidemic timeline. The analysis shows the potential for an early epidemic peak occurring in October/November in the Northern hemisphere, likely before large-scale vaccination campaigns could be carried out. We suggest that the planning of additional mitigation policies such as systematic antiviral treatments might be the key to delay the activity peak inorder to restore the effectiveness of the vaccination programs.Comment: Paper: 29 Pages, 3 Figures and 5 Tables. Supplementary Information: 29 Pages, 5 Figures and 7 Tables. Print version: http://www.biomedcentral.com/1741-7015/7/4

A major T cell antigen of Mycobacterium leprae is a 10-kD heat-shock cognate protein.

Several mycobacterial antigens, identified by monoclonal antibodies and patient sera, have been found to be homologous to stress or heat-shock proteins (hsp) defined in Escherichia coli and yeast. A major antigen recognized by most Mycobacterium leprae-reactive human T cell lines and cell wall-reactive T cell clones is a 10-kD protein that has now been cloned and sequenced. The predicted amino acid sequence of this protein is 44% homologous to the hsp 10 (GroES) of E. coli. The purified native and recombinant 10-kD protein was found to be a stronger stimulator of peripheral blood T cell proliferation than other native and recombinant M. leprae proteins tested. The degree of reactivity paralleled the response to intact M. leprae throughout the spectrum of leprosy. Limiting-dilution analysis of peripheral blood lymphocytes from a patient contact and a tuberculoid patient indicated that approximately one third of M. leprae-reactive T cell precursors responded to the 10-kD antigen. T cell lines derived from lepromin skin tests were strongly responsive to the 10-kD protein. T cell clones reactive to both the purified native and recombinant 10-kD antigens recognized M. leprae-specific epitopes as well as epitopes crossreactive with the cognate antigen of M. tuberculosis. Further, the purified hsp 10 elicited strong delayed-type hypersensitivity reactions in guinea pigs sensitized to M. leprae. The strong T cell responses against the M. leprae 10-kD protein suggest a role for this heat-shock cognate protein in the protective/resistant responses to infection

Optimizing Tactics for Use of the U.S. Antiviral Strategic National Stockpile for Pandemic Influenza

Nedialko B. Dimitrov is with UT Austin, Sebastian Goll is with UT Austin, Nathaniel Hupert is with the CDC and Weill Cornell Medical College, Babak Pourbohloul is with British Columbia Centre for Disease Control, Lauren Ancel Meyers is with UT Austin and The Santa Fe Institute.In 2009, public health agencies across the globe worked to mitigate the impact of the swine-origin influenza A (pH1N1) virus. These efforts included intensified surveillance, social distancing, hygiene measures, and the targeted use of antiviral medications to prevent infection (prophylaxis). In addition, aggressive antiviral treatment was recommended for certain patient subgroups to reduce the severity and duration of symptoms. To assist States and other localities meet these needs, the U.S. Government distributed a quarter of the antiviral medications in the Strategic National Stockpile within weeks of the pandemic's start. However, there are no quantitative models guiding the geo-temporal distribution of the remainder of the Stockpile in relation to pandemic spread or severity. We present a tactical optimization model for distributing this stockpile for treatment of infected cases during the early stages of a pandemic like 2009 pH1N1, prior to the wide availability of a strain-specific vaccine. Our optimization method efficiently searches large sets of intervention strategies applied to a stochastic network model of pandemic influenza transmission within and among U.S. cities. The resulting optimized strategies depend on the transmissability of the virus and postulated rates of antiviral uptake and wastage (through misallocation or loss). Our results suggest that an aggressive community-based antiviral treatment strategy involving early, widespread, pro-rata distribution of antivirals to States can contribute to slowing the transmission of mildly transmissible strains, like pH1N1. For more highly transmissible strains, outcomes of antiviral use are more heavily impacted by choice of distribution intervals, quantities per shipment, and timing of shipments in relation to pandemic spread. This study supports previous modeling results suggesting that appropriate antiviral treatment may be an effective mitigation strategy during the early stages of future influenza pandemics, increasing the need for systematic efforts to optimize distribution strategies and provide tactical guidance for public health policy-makers.This work was supported by grants to LM from NIH Models of Infectious Disease Agent Study (MIDAS) (U01-GM087719-01), the James S. McDonnell Foundation, and NSF (DEB-0749097) and grants to BP from CIHR(PTL-97125 and PAP-93425) and the Michael Smith Foundation for Health Research.Biological Sciences, School o

Inter-disciplinary European guidelines on surgery of severe obesity

In 2005, for the first time in European history, an extraordinary Expert panel named 'The BSCG' (Bariatric Scientific Collaborative Group), was appointed through joint effort of the major European Scientific Societies which are active in the field of obesity management. Societies that constituted this panel were: IFSO - International Federation for the Surgery of Obesity, IFSO-EC - International Federation for the Surgery of Obesity - European Chapter, EASO - European Association for Study of Obesity, ECOG - European Childhood Obesity Group, together with the IOTF (International Obesity Task Force) which was represented during the completion process by its representative. The BSCG was composed not only of the top officers representing the respective Scientific Societies (four acting presidents, two past presidents, one honorary president, two executive directors), but was balanced with the presence of many other key opinion leaders in the field of obesity. The BSCG composition allowed the coverage of key disciplines in comprehensive obesity management, as well as reflecting European geographical and ethnic diversity. This joint BSCG expert panel convened several meetings which were entirely focused on guidelines creation, during the past two years. There was a specific effort to develop clinical guidelines, which will reflect current knowledge, expertise and evidence based data on morbid obesity treatmen

Interdisciplinary European Guidelines on Metabolic and Bariatric Surgery

In 2012, an outstanding expert panel derived from IFSO-EC (International Federation for the Surgery of Obesity - European Chapter) and EASO (European Association for the Study of Obesity), composed by key representatives of both Societies including past and present presidents together with EASO's OMTF (Obesity Management Task Force) chair, agreed to devote the joint Medico-Surgical Workshop of both institutions to the topic of metabolic surgery as a pre-satellite of the 2013 European Congress on Obesity (ECO) to be held in Liverpool given the extraordinarily advancement made specifically in this field during the past years. It was further agreed to revise and update the 2008 Interdisciplinary European Guidelines on Surgery of Severe Obesity produced in cooperation of both Societies by focusing in particular on the evidence gathered in relation to the effects on diabetes during this lustrum and the subsequent changes that have taken place in patient eligibility criteria. The expert panel composition allowed the coverage of key disciplines in the comprehensive management of obesity and obesity-associated diseases, aimed specifically at updating the clinical guidelines to reflect current knowledge, expertise and evidence-based data on metabolic and bariatric surgery