Improving training condition assessment in endurance cyclists : Effects of ganoderma lucidum and ophiocordyceps sinensis dietary supplementation

The main reasons for taking daily dietary supplements are to maintain good health, to improve homeostasis, and to create conditions for reducing the risk of disease. Due to growing market demand, the search for effective, nontoxic, natural compounds with antioxidant and ergogenic properties has increasingly become a matter of interest. This paper describes how a specific combination of fungal supplements can help improve the performance of endurance athletes. We report the effects of a brief 3-month trial of two fungal supplements, Ganoderma lucidum and Cordyceps sinensis (3 capsules of O. sinensis and 2 capsules of G. lucidum per day), in 7 healthy male volunteers, aged between 30 and 40 years, who are all amateur cyclists that participate in "Gran Fondo" cycling races. This trial investigated the effects of fungal supplements on the level of physical fitness of the athletes by monitoring and comparing the following biomarkers just before and after physical exertion: the testosterone/cortisol ratio in the saliva and oxidative stress (DPPH free radical scavenging activity). A decrease of more than 30% in the testosterone/cortisol ratio after race compared to before race was considered as a risk factor for nonfunctional overreaching (NFO) or the overtraining syndrome (OTS). The results show that, after 3 months of supplementation, the testosterone/cortisol ratio changed in a statistically significant manner, thereby protecting the athletes from NFO and OTS. Antioxidant activity was measured by quantifying the scavenging ability of the human serum on the synthetic free radical DPPH. After 3 months of fungal supplementation, the data demonstrate an increased scavenger capacity of free radicals in the athletes' serum after the race, thereby protecting the athletes from oxidative stress

Little-Italy: an Agent-Based Approach to the Estimation of Contact Patterns. Fitting Predicted Matrices to Serological Data.

Knowledge of social contact patterns still represents the most critical step for understanding the spread of directly transmitted infections. Data on social contact patterns are, however, expensive to obtain. A major issue is then whether the simulation of synthetic societies might be helpful to reliably reconstruct such data. In this paper, we compute a variety of synthetic age-specific contact matrices through simulation of a simple individual-based model (IBM). The model is informed by Italian Time Use data and routine socio-demographic data (e.g., school and workplace attendance, household structure, etc.). The model is named “Little Italy” because each artificial agent is a clone of a real person. In other words, each agent's daily diary is the one observed in a corresponding real individual sampled in the Italian Time Use Survey. We also generated contact matrices from the socio-demographic model underlying the Italian IBM for pandemic prediction. These synthetic matrices are then validated against recently collected Italian serological data for Varicella (VZV) and ParvoVirus (B19). Their performance in fitting sero-profiles are compared with other matrices available for Italy, such as the Polymod matrix. Synthetic matrices show the same qualitative features of the ones estimated from sample surveys: for example, strong assortativeness and the presence of super- and sub-diagonal stripes related to contacts between parents and children. Once validated against serological data, Little Italy matrices fit worse than the Polymod one for VZV, but better than concurrent matrices for B19. This is the first occasion where synthetic contact matrices are systematically compared with real ones, and validated against epidemiological data. The results suggest that simple, carefully designed, synthetic matrices can provide a fruitful complementary approach to questionnaire-based matrices. The paper also supports the idea that, depending on the transmissibility level of the infection, either the number of different contacts, or repeated exposure, may be the key factor for transmission

Immunological fingerprint of 4CMenB recombinant antigens via protein microarray reveals key immunosignatures correlating with bactericidal activity

Serogroup B meningococcus (MenB) is a leading cause of meningitis and sepsis across the world and vaccination is the most effective way to protect against this disease. 4CMenB is a multi-component vaccine against MenB, which is now licensed for use in subjects >2 months of age in several countries. In this study, we describe the development and use of an ad hoc protein microarray to study the immune response induced by the three major 4CMenB antigenic components (fHbp, NHBA and NadA) in individual sera from vaccinated infants, adolescents and adults. The resulting 4CMenB protein antigen fingerprinting allowed the identification of specific human antibody repertoire correlating with the bactericidal response elicited in each subject. This work represents an example of epitope mapping of the immune response induced by a multicomponent vaccine in different age groups with the identification of protective signatures. It shows the high flexibility of this microarray based methodology in terms of high-throughput information and minimal volume of biological samples needed

Efeito do tratamento das fibras nas propriedades do biocompósito de amido termoplástico/policaprolactona/sisal

Fibras de sisal com quatro tratamentos, a saber: fibra lavada com água, lavada com cicloexano/etanol, tratamento alcalino (NaOH) e tratamento com peróxido alcalino (branqueamento), foram incorporadas na blenda amido termoplástico/policaprolactona 80/20 (TPS/PCL). As propriedades morfológicas, mecânicas e térmicas dos biocompósitos TPS/PCL/Sisal foram analisadas. Os compósitos com a fibra branqueada apresentaram os melhores resultados de resistência à tração e estabilidade térmica. Verificou-se também melhora da adesão fibra-matriz no compósito com a fibra branqueada, com aumento de 145% na resistência à tração.Sisal fibers treated with four methods, namely washing with water, washing with cyclohexane/ethanol, alkali treatment (NaOH) and bleaching (alkaline peroxide treatment), were incorporated in thermoplastic starch/polycaprolactone 80/20 (TPS/PCL) samples. Morphological, mechanical and thermal properties of TPS/PCL/Sisal biocomposites were analysed. The best results were obtained with the composite using the bleached fiber, which had improved tensile strength and thermal stability. An increased adhesion between the fiber and matrix was also observed with the bleached fiber, with 145% increase in the tensile strengthFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Laboratório Nacional de Nanotecnologia para o AgronegócioUNESP Departamento de Bioquímica e MicrobiologiaUNESP Departamento de Bioquímica e Microbiologi

A systematic review to identify areas of enhancements of pandemic simulation models for operational use at provincial and local levels

<p>Abstract</p> <p>Background</p> <p>In recent years, computer simulation models have supported development of pandemic influenza preparedness policies. However, U.S. policymakers have raised several <it>concerns </it>about the practical use of these models. In this review paper, we examine the extent to which the current literature already addresses these <it>concerns </it>and identify means of enhancing the current models for higher operational use.</p> <p>Methods</p> <p>We surveyed PubMed and other sources for published research literature on simulation models for influenza pandemic preparedness. We identified 23 models published between 1990 and 2010 that consider single-region (e.g., country, province, city) outbreaks and multi-pronged mitigation strategies. We developed a plan for examination of the literature based on the concerns raised by the policymakers.</p> <p>Results</p> <p>While examining the concerns about the adequacy and validity of data, we found that though the epidemiological data supporting the models appears to be adequate, it should be validated through as many updates as possible during an outbreak. Demographical data must improve its interfaces for access, retrieval, and translation into model parameters. Regarding the concern about credibility and validity of modeling assumptions, we found that the models often simplify reality to reduce computational burden. Such simplifications may be permissible if they do not interfere with the performance assessment of the mitigation strategies. We also agreed with the concern that social behavior is inadequately represented in pandemic influenza models. Our review showed that the models consider only a few social-behavioral aspects including contact rates, withdrawal from work or school due to symptoms appearance or to care for sick relatives, and compliance to social distancing, vaccination, and antiviral prophylaxis. The concern about the degree of accessibility of the models is palpable, since we found three models that are currently accessible by the public while other models are seeking public accessibility. Policymakers would prefer models scalable to any population size that can be downloadable and operable in personal computers. But scaling models to larger populations would often require computational needs that cannot be handled with personal computers and laptops. As a limitation, we state that some existing models could not be included in our review due to their limited available documentation discussing the choice of relevant parameter values.</p> <p>Conclusions</p> <p>To adequately address the concerns of the policymakers, we need continuing model enhancements in critical areas including: updating of epidemiological data during a pandemic, smooth handling of large demographical databases, incorporation of a broader spectrum of social-behavioral aspects, updating information for contact patterns, adaptation of recent methodologies for collecting human mobility data, and improvement of computational efficiency and accessibility.</p