The influence of butorphanol dose on characteristics of xylazine-butorphanol-propofol anesthesia in horses at altitude

OBJECTIVE: To characterize behavioral and physiological responses to short-term, unsupplemented intravenous (IV) anesthesia in healthy horses at high altitude (2240 m), and to test the hypothesis that the dose of butorphanol modifies the response of the horse to propofol anesthesia following xylazine pre-medication. STUDY DESIGN: Randomized prospective butorphanol dose cross-over experimental design. Animals Eight healthy horses, 13 +/- 6 (mean +/- SD) years of age, and weighing 523 +/- 26 kg. METHODS: Each horse was anesthetized three times with at least 3 weeks between each anesthesia. After collecting pre-drug data, xylazine (0.5 mg kg(-1)) was given IV. Five minutes later butorphanol was given IV according to a randomized order of three doses: 0.025, 0.05 and 0.075 mg kg(-1). Five minutes later, anesthesia was induced with propofol, 2 mg kg(-1) IV. Data on heart rate (HR) and respiratory rate (f(r)), mean arterial blood pressure, P(a)O(2), P(a)CO(2) and pH(a) were collected before, during and for 60 minutes following anesthesia, and quality of induction and recovery was scored. RESULTS: The pre-drug values for the three butorphanol groups did not differ. The combined pre-drug values from the 24 studies were HR, 33 +/- 7 beats minute(-1); f(r), 11 +/- 3 breaths minute(-1); P(a)O(2), 67 +/- 7 mmHg; P(a)CO(2), 36 +/- 4 mmHg; and pH(a), 7.42 +/- 0.04. Five minutes after anesthetic induction P(a)O(2) decreased and P(a)CO(2) increased 14.5 +/- 7.7 and 5.1 +/- 4.9 mmHg, respectively, but returned to pre-drug levels within 15 minutes of anesthetic recovery. There were no significant butorphanol dose-related differences in physiological results, anesthetic induction and recovery quality scores or recovery time. CONCLUSIONS AND CLINICAL RELEVANCE: Dose of butorphanol did not markedly influence study results. Notably, low P(a)O(2) values related to geographic location of study and general anesthesia indicates a narrow margin of error for hypoxemia-related complications in anesthetized horses breathing unsupplemented air at high altitude.     

Genetic Diversity in Argentine Andean Potatoes by Means of Functional Markers

Andean Potato is a major crop for farmers in the Andes and represents an important gene pool for potato improvement. We present the population structure and genetic diversity of 88 Andigena accessions collected in Northwestern Argentina based on functional markers (25 SSR) distributed along 12 chromosomes. Polymorphic information content ranged from 0.40 to 0.87. A Bayesian approach, a Principal Coordinate Analysis and a Cluster Analysis revealed the presence of: I) a major group containing most of the Andean accessions and II) a smaller group including the out-group cv. Spunta and the sequenced genotype DM. Several group specific alleles were detected. AMOVA showed that 81% of the variability was within each group. Eleven of the SSRs analyzed are linked or within genes reported to regulate traits of nutritional and industrial interest. Additionally, the allelic variant of a photoperiod dependent tuberization regulator gene, StCDF1.2, was exclusively detected in accessions clustered in group II.     

Effect of Extrusion Conditions and the Optimization of Phenolic Compound Content and Antioxidant Activity of Wheat Bran Using Response Surface Methodology

The extrusion process (EP) consists of heat and mechanical treatments under different conditions of moisture, shear, and pressure and rapidly causes structural alterations and changes in the functional properties of the extruded material. The aim of this study was to evaluate the effect of extrusion conditions and optimize the wheat bran extrusion conditions to achieve the greatest content of phenolic compounds and antioxidant activity using response surface methodology. The EP factors evaluated were feed moisture (FM) (25–33.54%) and final extrusion temperature (T) (140–180 °C). The properties evaluated in the extruded material were bound total phenol content (BTPC), total phenolic compounds and antioxidant activity (AOX). Analysis of variance (ANOVA) and response surface methodology were used in the evaluation. The determination coefficients, (FM)² and (T)², very significantly affected the BTPC and bound 2,2-diphenyl-1-picrylhydrazyl content (BDPPHC). The optimization was performed by overlaying two contour plots to predict the best combination regions. The optimized extrusion conditions were the following: FM?=?30% and T?=?140 °C, which provided BTPC?=?3547.01 μgGAE/g (predicted: 3589.3 μgGAE/g) and BDPPHC?=?9.5 μmolTE/g (predicted: 10.4 μmolTE/g); and FM?=?30% and T?=?180 °C, which provided BTPC?=?3342.3 μgGAE/g (predicted: 3727.7 μgGAE/g) and BDPPHC?=?9.5 μmolTE/g (predicted: 9.3 μmolTE/g). The EP increased the phenolic compounds and AOX, and enhancement of these properties in wheat bran products could make them functional foods.     

Spatially modeling wildland fire severity in pine forests of Galicia,Spain

Fire is a major disturbance in forests and one of the most important carbon emissions sources, which contributes to climate change. Carbon emissions are directly correlated with the degree of organic matter consumption or fire severity. Gaining knowledge about the relative strength of the various explanatory variables is essential to mitigate its environmental impact. We tested an approach that combines wind modeling, light detection and ranging (LiDAR), remotely sensed vegetation indices and topography data for assessing the occurrence of high-severity fire using the random forests ensemble learning method. Data from four wildfires that occurred in Galicia (northwestern Spain) were used to exemplify the application of this approach. The models predicted high-severity occurrence with a classification accuracy ranging from 77 to 94%. High-severity fire occurred more frequently in areas of high simulated wind speed, and more pronouncedly, for cases reported as wind-driven fires. High severity also occurred more frequently in areas of high terrain roughness, on sunny slopes and in low canopy base height stands. This approach allowed predicting spatially explicit fire severity at a mean scale level (resolution of 25 m) with accuracy rates from 80 to 95%. This approach may be helpful for fire managers when delimiting and planning fuel treatments for severity mitigation or during fire suppression, and for post hoc case studies.