1,532 research outputs found

    Sterilization of lung matrices by supercritical carbon dioxide

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    Lung engineering is a potential alternative to transplantation for patients with end-stage pulmonary failure. Two challenges critical to the successful development of an engineered lung developed from a decellularized scaffold include (i) the suppression of resident infectious bioburden in the lung matrix, and (ii) the ability to sterilize decellularized tissues while preserving the essential biological and mechanical features intact. To date, the majority of lungs are sterilized using high concentrations of peracetic acid (PAA) resulting in extracellular matrix (ECM) depletion. These mechanically altered tissues have little to no storage potential. In this study, we report a sterilizing technique using supercritical carbon dioxide (ScCO(2)) that can achieve a sterility assurance level 10(−6) in decellularized lung matrix. The effects of ScCO(2) treatment on the histological, mechanical, and biochemical properties of the sterile decellularized lung were evaluated and compared with those of freshly decellularized lung matrix and with PAA-treated acellular lung. Exposure of the decellularized tissue to ScCO(2) did not significantly alter tissue architecture, ECM content or organization (glycosaminoglycans, elastin, collagen, and laminin), observations of cell engraftment, or mechanical integrity of the tissue. Furthermore, these attributes of lung matrix did not change after 6 months in sterile buffer following sterilization with ScCO(2), indicating that ScCO(2) produces a matrix that is stable during storage. The current study's results indicate that ScCO(2) can be used to sterilize acellular lung tissue while simultaneously preserving key biological components required for the function of the scaffold for regenerative medicine purposes

    Incidence of Obesity Among Young US Children Living in Low-Income Families, 2008–2011

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    OBJECTIVE: To examine the incidence and reverse of obesity among young low-income children and variations across population subgroups. METHODS: We included 1.2 million participants in federally funded child health and nutrition programs who were 0 to 23 months old in 2008 and were followed up 24 to 35 months later in 2010–2011. Weight and height were measured. Obesity at baseline was defined as gender-specific weight-for-length \u3e/=95th percentile on the 2000 Centers for Disease Control and Prevention growth charts. Obesity at follow-up was defined as gender-specific BMI-for-age \u3e/=95th percentile. We used a multivariable log-binomial model to estimate relative risk of obesity adjusting for gender, baseline age, race/ethnicity, duration of follow-up, and baseline weight-for-length percentile. RESULTS: The incidence of obesity was 11.0% after the follow-up period. The incidence was significantly higher among boys versus girls and higher among children aged 0 to 11 months at baseline versus those older. Compared with non-Hispanic whites, the risk of obesity was 35% higher among Hispanics and 49% higher among American Indians (AIs)/Alaska Natives (ANs), but 8% lower among non-Hispanic African Americans. Among children who were obese at baseline, 36.5% remained obese and 63.5% were nonobese at follow-up. The proportion of reversing of obesity was significantly lower among Hispanics and AIs/ANs than that among other racial/ethnic groups. CONCLUSIONS: The high incidence underscores the importance of earlylife obesity prevention in multiple settings for low-income children and their families. The variations within population subgroups suggest that culturally appropriate intervention efforts should be focused on Hispanics and AIs/ANs

    On Tanzania’s Precipitation Climatology, Variability, and Future Projection

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    We investigate historical and projected precipitation in Tanzania using observational and climate model data. Precipitation in Tanzania is highly variable in both space and time due to topographical variations, coastal influences, and the presence of lakes. Annual and seasonal precipitation trend analyses from 1961 to 2016 show maximum rainfall decline in Tanzania during the long rainy season in the fall (March–May), and an increasing precipitation trend in northwestern Tanzania during the short rainy season in the spring (September–November). Empirical orthogonal function (EOF) analysis applied to Tanzania’s precipitation patterns shows a stronger correlation with warmer temperatures in the western Indian Ocean than with the eastern-central Pacific Ocean. Years with decreasing precipitation in Tanzania appear to correspond with increasing sea surface temperatures (SST) in the Indian Ocean, suggesting that the Indian Ocean Dipole (IOD) may have a greater effect on rainfall variability in Tanzania than the El Niño-Southern Oscillation (ENSO) does. Overall, the climate model ensemble projects increasing precipitation trend in Tanzania that is opposite with the historical decrease in precipitation. This observed drying trend also contradicts a slightly increasing precipitation trend from climate models for the same historical time period, reflecting challenges faced by modern climate models in representing Tanzania’s precipitation
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