Patchiness and Demographic Noise in Three Ecological Examples

Understanding the causes and effects of spatial aggregation is one of the most fundamental problems in ecology. Aggregation is an emergent phenomenon arising from the interactions between the individuals of the population, able to sense only -at most- local densities of their cohorts. Thus, taking into account the individual-level interactions and fluctuations is essential to reach a correct description of the population. Classic deterministic equations are suitable to describe some aspects of the population, but leave out features related to the stochasticity inherent to the discreteness of the individuals. Stochastic equations for the population do account for these fluctuation-generated effects by means of demographic noise terms but, owing to their complexity, they can be difficult (or, at times, impossible) to deal with. Even when they can be written in a simple form, they are still difficult to numerically integrate due to the presence of the "square-root" intrinsic noise. In this paper, we discuss a simple way to add the effect of demographic stochasticity to three classic, deterministic ecological examples where aggregation plays an important role. We study the resulting equations using a recently-introduced integration scheme especially devised to integrate numerically stochastic equations with demographic noise. Aimed at scrutinizing the ability of these stochastic examples to show aggregation, we find that the three systems not only show patchy configurations, but also undergo a phase transition belonging to the directed percolation universality class.Comment: 20 pages, 5 figures. To appear in J. Stat. Phy

Aislamiento de un extracto de BMP y estudio anatomopatológico del fenómeno de inducción ósea tras su implante en defectos óseos

El objetivo del presente trabajo fue determinar el potencial osteogénico de la proteína morfogenética ósea (BMP) en la reparación de grandes defectos diafisarios. Además, se investiga la acción coadyuvante de la fibronectina (FN). La BMP fue extraída a partir de hueso cortical bovino. Se utilizaron un total de 108 ratas Sprague Dawley. En cada animal, se resecó un segmento de diáfisis femoral de 1.5 cm, siendo inmovilizado el defecto óseo con una aguja en omega. Se rellenó el defecto implantando 25 mg de BMP con o sin 0.5 mg de FN en una cápsula de gelatina (36 animales en ambos grupos). Los resultados se compararon con los obtenidos en otro grupo (36 animales) en el que sólo se implantó FN que sirvió como grupo control. El proceso de reparación se evaluó mediante métodos histológicos y ultraestructurales. La aparición del fenómeno de inducción ósea con reconstrucción del defecto óseo fue mayor en el grupo con implante de BMP más FN (23 animales, 64%) que en el grupo en el que sólo se implantó BMP (20 animales, 56%). Ningún animal del grupo control manifestaba signos de inducción ósea.The aim of the present work was to evaluate the osteogenic potential of Bone Morphogenetic Protein (BMP) for reparation of large segmental bone defects. In addition, the coadjuvant efect of fibronectin (FN) was investigated. BMP was partially purified from bovine cortical bone. A total of 108 Sprague Dawley rats were used in the experiment. Diaphyseal segments of the femur (1.5 cm) were removed in each animal, manteinant the bone defect with a wire. A gelatine capsula containing 25 mg of BMP without or with 0.5 mg of FN, were implanted into the bone defect (36 animal in each group). Results were compared to those obtained in a control group (36 animals) in which FN alone was implanted. The bone repair process was assessed by histologic and ultrastructural methods. Bone induction with reconstruction of the defect was found more of ten in the group with both BMP and FN implanted (23 animals, 64%) than in the group with BMP implant alone (20 animals, 56%). Animals of the control group showed no bone induction. The results suggest that BMP augments the capacity of the host bed to sucessfully regenerate large segmental bone defects. FN seens to increase bone induction. This protein migth stabilize BMP locally improving contact between BMP and the surrounding cells

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Ecological Invasion, Roughened Fronts, and a Competitor's Extreme Advance: Integrating Stochastic Spatial-Growth Models

Both community ecology and conservation biology seek further understanding of factors governing the advance of an invasive species. We model biological invasion as an individual-based, stochastic process on a two-dimensional landscape. An ecologically superior invader and a resident species compete for space preemptively. Our general model includes the basic contact process and a variant of the Eden model as special cases. We employ the concept of a "roughened" front to quantify effects of discreteness and stochasticity on invasion; we emphasize the probability distribution of the front-runner's relative position. That is, we analyze the location of the most advanced invader as the extreme deviation about the front's mean position. We find that a class of models with different assumptions about neighborhood interactions exhibit universal characteristics. That is, key features of the invasion dynamics span a class of models, independently of locally detailed demographic rules. Our results integrate theories of invasive spatial growth and generate novel hypotheses linking habitat or landscape size (length of the invading front) to invasion velocity, and to the relative position of the most advanced invader.Comment: The original publication is available at www.springerlink.com/content/8528v8563r7u2742

Effectiveness of an mHealth intervention combining a smartphone app and smart band on body composition in an overweight and obese population: Randomized controlled trial (EVIDENT 3 study)

Background: Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear. Objective: This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese. Methods: A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire. Results: The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m2, 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m2 (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m2 (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m2 (95% CI –0.83 to –0.19). Conclusions: The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m2 and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect