1,721,252 research outputs found

    "GA-banding": a new terminology and a study of the glutaraldehyde-induced band pattern of type I collagen fibrils

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    The negative staining D-band patterns of glutaraldehyde-reacted collagen fibrils were compared to those of fresh collagen fibrils. Negative staining was obtained by using 1% phosphotungstic acid (PTA) diluted in phosphate buffer 0.1 M, pH 7.4. The stain was dripped onto grids where native type I collagen fibrils, isolated from bovine dermis, were collected. Ultrastructural pictures were digitized to form microdensitometric traces. The glutaraldehyde-induced patterns showed fifteen light bands (micrographs) or negative peaks (microdensitograms), whose D-locations were constant and characteristic. In order to make this ultrastructural feature a precise reference parameter, these bands were called "GA-bands" and numbered. When comparing this averaged microdensitogram with that of negatively stained fresh fibrils, peak "GA1" and peak "GA7" were observed to correspond to peak "X2" (known as N-terminal telopeptide region) and peak "X3" (known as C-terminal telopeptide region) respectively, while there was no correspondence between the other peaks of the two traces. It means that the regions where preexistent crosslinks exist are unaffected by interaction with glutaraldehyde, while in the other regions, where new glutaraldehyde-crosslinks occur, the band pattern modifies. The unchanged D-location of peaks "GA1" and "GA7" leads to the conclusion that the D-shortening induced by glutaraldehyde is not due to shifting of tropocollagen molecules but to changes in their orientation with respect to fibril long axis or in secondary-tertiary structure of collagen

    Integrating R and Excel for automatic business forecasting

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    We present a simple exercise in bridging the gap between statistics and everyday business practice, based on two powerful tools already available in the R system: the forecast package Hyndman (2011) for automatic time series forecasting and the RExcel add-in for MS Excel Baier and Neuwirth (2007), allowing to embed R functionality into spreadsheets and to interact with their built-in macro language. The application we developed makes forecasting practice accessible to those who are not familiar with statistical programs and, possibly, do not even have a sound statistical background. Many processes inside the firm involve forecasting. Some build on models and relationships between bal- ance sheet items, but sometimes an a-theoretical extrapolation of past tendencies is needed. As few firms can afford to have trained statisticians dedicated to supply-chain forecasting and the like, budgeting and other activities are often based on simple, heuristic extrapolation of past data. It is commonplace, especially in small enterprises, to ”pick last year/month’s value”, either in terms of stocks or of increments, as the best estimate for the coming period. Fully automatic forecasting of time series, based on model fitting and model comparing algorhythms selecting the ’best’ model for the data at hand, provides a statistically well founded solution to the forecasting problem and can be of great use to the firm in obtaining accurate predictions for variables like sales, commodities’ input needs and the like, where forecast errors cost money. Such fully automatic procedures are implemented in a variety of commercial software. We show how an open-source solution is also very easy to set up. The ideal way is thus to have the forecaster dealing only with Excel for data input, commmand issuing and results’ retrieval, while a ’real’ statistical engine transparently does the computing in the background. Now the forecaster just has to select the data vector, press the trigger keys for showing up the userform, select the data frequency and press OK. He will get the forecasts at the end of the original series

    Ectopic mineralization in heart valves: New insights from in vivo and in vitro procalcific models and promising perspectives on noncalcifiable bioengineered valves

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    Ectopic calcification of native and bioprosthetic heart valves represents a major public health problem causing severe morbidity and mortality worldwide. Valve procalcific degeneration is known to be caused mainly by calcium salt precipitation onto membranes of suffering non-scavenged cells and dead-cellderived products acting as major hydroxyapatite nucleators. Although etiopathogenesis of calcification in native valves is still far from being exhaustively elucidated, it is well known that bioprosthesis mineralization may be primed by glutaraldehyde-mediated toxicity for xenografts, cryopreservation-related damage for allografts and graft immune rejection for both. Instead, mechanical valves, which are free from calcification, are extremely thrombogenic, requiring chronic anticoagulation therapies for transplanted patients. Since surgical substitution of failed valves is still the leading therapeutic option, progressive improvements in tissue engineering techniques are crucial to attain readily available valve implants with good biocompatibility, proper functionality and long-term durability in order to meet the considerable clinical demand for valve substitutes. Bioengineered valves obtained from acellular non-valvular scaffolds or decellularized native valves are proving to be a compelling alternative to mechanical and bioprosthetic valve implants, as they appear to permit repopulation by the host’s own cells with associated tissue remodelling, growth and repair, besides showing less propensity to calcification and adequate hemodynamic performances. In this review, insights into valve calcification onset as revealed by in vivo and in vitro procalcific models are updated as well as advances in the field of valve bioengineering
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