Population Viability Analysis of the Blue-Throated Macaw (Ara Glaucogularis) Using Individual-Based and Cohort-Based PVA Programs

We developed a demographic model to perform a population viability analysis (PVA) of the Blue-throated Macaw (Ara glaucogularis), a critically endangered species endemic to Bolivia. PVA simulations were run using individual based (VORTEX 9.72) and cohort-based (RAMAS GIS 4.0) programs. A baseline simulation allowed for the assessment of the status of the species based on estimates of extinction risk and population declines under current conditions of abundance and habitat availability. The role of multiple demographic, environmental, and anthropogenic parameters was evaluated to assess changes affecting population declines and extinction risk. The baseline simulation showed that the Blue-throated Macaw has a relatively low probability of extinction during the next fifty years. However, continuing threats, including declines in abundance, small population size, and low population growth rates, make this species highly vulnerable to any change. Elasticity analysis of the baseline simulation and sensitivity analysis of changes in different demographic parameters demonstrated that increases in adult mortality had the greatest effect on population growth rate and extinction risk. Furthermore, simulations of anthropogenic impacts showed that small increases in habitat loss (2%) and population harvesting (3%) had drastic effects on population decline. Results from this study emphasize the need for conservation actions aimed at protecting breeding individuals (i.e., decreasing adult mortality), preventing poaching activities, and promoting the conservation of available habitat for nesting sites. © Strem and Bouzat; Licensee Bentham Open

Effect of Perturbation-Based Balance Training on Fall Risk and Fear of Falls in Community-Dwelling Older Adults – A Pilot Study

Falls are a major health concern among adults ≥65 years as it is the leading cause of injury and injury related death in the United States. Perturbation-based training (PBT) has been shown to reduce rate of falls by 50% and 24 slips has been shown to be optimal. It is unknown whether falls reduction would be greater with one session or spread out over multiple sessions. The purpose of this study was to determine the effects of PBT dosage (12 slips over 2 sessions vs. 24 slips in one session) on falls incidence, fear of falling, and reactive stepping in community-dwelling older adults

Fresh and cryopreserved, uncultured adipose tissue-derived stem and regenerative cells ameliorate ischemia–reperfusion-induced acute kidney injury

Background. Acute kidney injury (AKI) represents a major clinical problem with high mortality and limited causal treatments. The use of cell therapy has been suggested as a potential modality to improve the course and outcome of AKI

A Scenario-Based Model Comparison for Short-Term Day-Ahead Electricity Prices in Times of Economic and Political Tension

In recent years, energy prices have become increasingly volatile, making it more challenging to predict them accurately. This uncertain market trend behavior makes it harder for market participants, e.g., power plant dispatchers, to make reliable decisions. Machine learning (ML) has recently emerged as a powerful artificial intelligence (AI) technique to get reliable predictions in particularly volatile and unforeseeable situations. This development makes ML models an attractive complement to other approaches that require more extensive human modeling effort and assumptions about market mechanisms. This study investigates the application of machine and deep learning approaches to predict day-ahead electricity prices for a 7-day horizon on the German spot market to give power plants enough time to ramp up or down. A qualitative and quantitative analysis is conducted, assessing model performance concerning the forecast horizon and their robustness depending on the selected hyperparameters. For evaluation purposes, three test scenarios with different characteristics are manually chosen. Various models are trained, optimized, and compared with each other using common performance metrics. This study shows that deep learning models outperform tree-based and statistical models despite or because of the volatile energy prices

Osteogenic differentiation of two distinct subpopulations of human adipose-derived stem cells: an in vitro and in vivo study

The first stem cells considered for the reconstruction of bone were bone marrow mesenchymal stem cells (BMSCs). Subsequently, cells with similar marker expression panel and differentiation potential were found in new sources of cells, such as adipose tissue. This source of stem cells has a promising future in tissue-engineering applications, considering the abundance of this tissue in the human body, the easy harvesting and the high number of stem cells that are available from such a small amount of tissue. The isolation of the adipose stem cells is generally performed by means of enzymatic digestion of the tissues, followed by a natural selection of the stem cells based on their capacity to adhere to the culture flasks, leading to a quite heterogeneous population. This constitutes a major drawback for the use of these cells, since the heterogeneity of the cell culture obtained can compromise their proliferation and differentiation potential. In the present study we have analysed the in vitro and in vivo behaviour of two selected subpopulations with high osteogenic potential. For this purpose, ASCsCD29+ and ASCs STRO−1+ subpopulations were isolated and in vitro cultured onto a biodegradable polymeric scaffold, using osteogenic medium, before implantation in a nude mice model. The biodegradable polymeric scaffold used is a fibre-mesh structure based on a blend of starch and polycaprolatone (SPCL) that has been successfully used in several bone tissue-engineering studies. The implanted ASCs–scaffold constructs promoted the formation of new bone tissue in nude mice. However, the results obtained show differences in the behaviour of the two ASCs subpopulations under study, particularly regarding their potential to differentiate into the osteogenic lineage, and allowed the identification of ASCs STRO−1+ as the best subpopulation for bone tissue-engineering applications

A novel method for the isolation of subpopulations of rat adipose stem cells with different proliferation and osteogenic differentiation potentials

Bone marrow has been the elected cell source of studies published so far concerning bone and cartilage tissue-engineering approaches. Recent studies indicate that adipose tissue presents significant advantages over bone marrow as a cell source for tissue engineering. Most of these studies report the use of adipose stem cells (ASCs) isolated by a method based on the enzymatic digestion of the adipose tissue and on the ability of stem cells to adhere to a cell culture plastic surface. Using this method, a heterogeneous population was obtained containing different cell types that have been shown to compromise the proliferation and differentiation potential of the stem cells. This paper reports the development and optimization of a new isolation method that enables purified cell populations to be obtained that exhibit higher osteogenic differentiation and/or proliferation potential. This method is based on the use of immunomagnetic beads coated with specific antibodies and it is compared with other methods described in the literature for the selection of stem cell populations, e.g. methods based on a gradient solution and enzymatic digestion. The results showed that the isolation method based on immunomagnetic beads allows distinct subpopulations of rat ASCs to be isolated, showing different stem cells marker expressions and different osteogenic differentiation potentials. Therefore, this method can be used to study niches in ASC populations and/or also allow adipose tissue to be used as a stem cell source in a more efficient manner, increasing the potential of this cell source in future clinical applications.T. Rada thanks the EU Marie Curie Actions Alea Jacta Est for a PhD fellowship. This work was partially supported by the European Union-funded STREP Project HIPPOCRATES (Grant No. NMP3-CT-2003-505758) and was carried out under the scope of the European NoE EXPERTISSUES (Grant No. NMP3-CT-2004-500283)