3 resultados para Hyperbaric oxygen, Optimal protocol, Chronic wound, Mathematical modelling, Diabetes
em Bucknell University Digital Commons - Pensilvania - USA
Resumo:
The lack of effective tools have hampered our ability to assess the size, growth and ages of clonal plants. With Serenoa repens (saw palmetto) as a model, we introduce a novel analytical framework that integrates DNA fingerprinting and mathematical modelling to simulate growth and estimate ages of clonal plants. We also demonstrate the application of such life-history information of clonal plants to provide insight into management plans. Serenoa is an ecologically important foundation species in many Southeastern United States ecosystems; yet, many land managers consider Serenoa a troublesome invasive plant. Accordingly, management plans have been developed to reduce or eliminate Serenoa with little understanding of its life history. Using Amplified Fragment Length Polymorphisms, we genotyped 263 Serenoa and 134 Sabal etonia (a sympatric non-clonal palmetto) samples collected from a 20 X 20 m study plot in Florida scrub. Sabal samples were used to assign small field-unidentifiable palmettos to Serenoa or Sabal and also as a negative control for clone detection. We then mathematically modelled clonal networks to estimate genet ages. Our results suggest that Serenoa predominantly propagate via vegetative sprouts and 10000-year-old genets may be common, while showing no evidence of clone formation by Sabal. The results of this and our previous studies suggest that: (i) Serenoa has been part of scrub associations for thousands of years, (ii) Serenoa invasion are unlikely and (ii) once Serenoa is eliminated from local communities, its restoration will be difficult. Reevaluation of the current management tools and plans is an urgent task.
Resumo:
The lack of effective tools has hampered our ability to assess the size, growth and ages of clonal plants. With Serenoa repens (saw palmetto) as a model, we introduce a novel analytical frame work that integrates DNA fingerprinting and mathematical modelling to simulate growth and estimate ages of clonal plants. We also demonstrate the application of such life-history information of clonal plants to provide insight into management plans. Serenoa is an ecologically important foundation species in many Southeastern United States ecosystems; yet, many land managers consider Serenoa a troublesome invasive plant. Accordingly, management plans have been developed to reduce or eliminate Serenoa with little understanding of its life history. Using Amplified Fragment Length Polymorphisms, we genotyped 263 Serenoa and 134 Sabal etonia (a sympatric non-clonal palmetto) samples collected from a 20 x 20 m study plot in Florida scrub. Sabal samples were used to assign small field-unidentifiable palmettos to Serenoa or Sabal and also as a negative control for clone detection. We then mathematically modelled clonal networks to estimate genet ages. Our results suggest that Serenoa predominantly propagate via vegetative sprouts and 10000-year-old genets maybe common, while showing no evidence of clone formation by Sabal. The results of this and our previous studies suggest that: (i) Serenoa has been part of scrub associations for thousands of years, (ii) Serenoa invasions are unlikely and (ii) once Serenoa is eliminated from local communities, its restoration will be difficult. Reevaluation of the current management tools and plans is an urgent task.
Resumo:
Since the 1980s, the prevalence of obesity has more than doubled to over 30 percent of the adult population (Thorpe, 2004). Obesity is a key contributing factor to continually rising national healthcare costs. Addressing its negative implications is essential not only from a cost perspective, but also for the betterment of our nation¿s general health and wellbeing. Obesity is reportedly associated with a 35% increase in inpatient and outpatient spending, as well as a 77% increase in related necessary medications (Sturm, 2002). Obesity, which some have argued should be classified as a disease in itself, has roughly the same association with the development of chronic health conditions as does 20 years of aging (Sturm, 2002). Defined as ambulatory care-sensitive conditions, these obesity-related chronic health diagnoses ¿ like diabetes, cardiovascular disease, and hypertension ¿ are in turn the primary drivers of current healthcare spending, as well as future predicted health expenditures. It is well established that lower socioeconomic status (SES) is associated with higher rates of obesity and the subsequent development of aforementioned obesity-related conditions. Socioeconomic status has traditionally been defined by education, income, and occupation (Adler, 2002); however, this study found empirical evidence for education being the most fundamental of these three SES indicators in determining obesity outcomes. For both men and women, as education levels increased, the likelihood of an individual being obese decreased. However, with less education, there was increased disparity between the obesity rates for men and women. Women consistently saw higher rates of obesity and were more impacted in terms of obesity onset by belonging to a lower SES category than men. In addition, this study assessed whether the impact of one¿s socioeconomic status on obesity-related health outcomes (specifically the negative impact low-SES as measured by education level) has changed over time. Results deriving from annual data from the National Health Interview Survey (NHIS) for all years from 2002 to 2012 indicate that the association between low-socioeconomic status and negative health outcomes has not increased in magnitude over the past decade. Instead, obesity rates have increased across the overall U.S. adult population, most likely due to a number of larger external societal factors resulting in increased caloric intake and decreased energy expenditure across every SES group. In addition, while the association between low-SES and obesity has not worsened, a consequence of the Great Recession has been a larger percentage of the U.S. population in lower-SES, which is still consistently subject to the same worse health outcomes.