Predictive factors of mortality in burn patients

Burn mortality statistics may be misleading unless they account properly for the many factors that can influence outcome. Such estimates are useful for patients and others making medical and financial decisions concerning their care. This study aimed to define the clinical, microbiological and laboratorial predictors of mortality with a view to focus on better burn care. Data were collected using independent variables, which were analyzed sequentially and cumulatively, employing univariate statistics and a pooled, cross-sectional, multivariate logistic regression to establish which variables better predict the probability of mortality. Survivors and non-survivors among burn patients were compared to define the predictive factors of mortality. Mortality rate was 5.0%. Higher age, larger burn area, presence of fungi in the wound, shorter length of stay and the presence of multi-resistant bacteria in the wound significantly predicted increased mortality. The authors conclude that those patients who are most apt to die are those with age > 50 years, with limited skin donor sites and those with multi-resistant bacteria and fungi in the wound.

New perspectives on the history of brazilian agriculture.

One of the objectives of this book has been to highlight the importance of the history of agriculture in today's food production and consumption patterns, recovering parts of this history which are not easily found or which have been forgotten or neglected, but which have had a large impact on what we are today.

Release of insulin from PLGA-alginate dressing stimulates regenerative healing of burn wounds in rats

Burn wound healing involves a complex set of overlapping processes in an environment conducive to ischemia, inflammation, and infection costing $7.5 billion/year in the US alone, in addition to the morbidity and mortality that occur when the burns are extensive. We previously showed that insulin, when topically applied to skin excision wounds, accelerates re-epithelialization, and stimulates angiogenesis. More recently, we developed an alginate sponge dressing (ASD) containing insulin encapsulated in PLGA microparticles that provides a sustained release of bioactive insulin for >20days in a moist and protective environment. We hypothesized that insulin-containing ASD accelerates burn healing and stimulates a more regenerative, less scarring, healing. Using a heat-induced burn injury in rats, we show that burns treated with dressings containing 0.04mg insulin/cm2, every three days for 9 days, have faster closure, faster rate of disintegration of dead tissue, and decreased oxidative stress.In addition, in insulin-treated wounds the pattern of neutrophil inflammatory response suggests faster clearing of the burn dead tissue. We also observe faster resolution of the pro-inflammatory macrophages. We also found that insulin stimulates collagen deposition and maturation with the fibers organized more like a basket weave (normal skin) than aligned and crosslinked (scar tissue). In summary , application of ASD-containing insulin-loaded PLGA particles on burns every three days stimulates faster and more regenerative healing. These results suggest insulin as a potential therapeutic agent in burn healing and, because of its long history of safe use in humans, insulin could become one of the treatments of choice when repair and regeneration are critical for proper tissue function.

Improved burn wound healing using a bioactive peptide

[Excerpt] Antimicrobial peptides (AMPs) are good candidates to treat burn wounds, a major cause of morbidity, impaired life quality and resources consumption in developed countries. We took advantage of a commercially available hydrogel, Carbopol, a vehicle for topical administration that maintains a moist environment within the wound site. We hypothesized that the incorporation of LLKKK18 conjugated to dextrin would improve the healing process in rat burns. Whereas the hydrogel improves healing, LLKKK18 released from the dextrin conjugates further accelerates wound closure, and simultaneously improving the quality of healing. Indeed, the release of LLKKK18 reduces oxidative stress and inflammation (low neutrophil and macrophage infiltration and pro-inflammatory cytokines levels). Importantly, it induced a faster resolution of the inflammatory stage through early M2 macrophage recruitment. In addition, LLKKK18 stimulates angiogenesis (increased VEGF and microvessel development in vivo), potentially contributing to more effective transport of nutrients and cytokines. Moreover, collagen staining evaluated by Masson’s Trichrome was visually much more intense after treatment with LLKKK18, suggesting higher collagen deposition. (...)

DESARROLLO DE APLICACIONES ESTADÍSTICAS PARA LA AGRICULTURA DE PRECISIÓN. STATISTICAL APPLICATIONS FOR PRECISION AGRICULTURE

A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.

Report of the State board of agriculture on the work of extermination of the gypsy moth.

1898:Jan.

Report of the State board of agriculture on the work of extermination of the gypsy moth.

1897:Jan.

Spatial data mining in precision agriculture

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Marine investigations in South Africa / Cape of Good Hope Dept. of Agriculture.

v. 1 (1902)

Marine investigations in South Africa / Cape of Good Hope Dept. of Agriculture.

v. 3 (1905)

Letters and papers on agriculture and planting, etc.

4

Letters and papers on agriculture and planting, etc.

2

Letters and papers on agriculture and planting, etc.

5