Effect of L-arginine Oral Supplementation on Response to Myocardial Infarction in Hypercholesterolemic and Hypertensive Rats

The well known metabolic functions of L-arginine have been recently increased with the discovery of its role as the substrate for the synthesis of nitric oxide (NO), which has emerged as an endogenous signaling molecule with potential therapeutic implications for cardiovascular disease. Steady-state levels of NO are derived in part from dietary sources. It has been reported that supplementation of L-arginine reduces atherosclerosis in rabbits and reduces the arterial pressure in hypertensive rats. Therefore, we investigated the effect of L-arginine supplementation using a group of induced hypercholesterolemic rats and a group of spontaneously hypertensive rats; the infarcted area in cardiac tissue of both groups was measured during the response to myocardial infarction in the ischemia-reperfusion model. Hypercholesterolemic rats supplemented with 170 mg kg⁻¹ of L-arginine showed a significant (P ≤ 0.05) reduction in total cholesterol (25.2%) and LDL (27.8%). Spontaneously hypertensive rats supplemented with L-arginine presented a significant reduction (20.3%) in mean blood pressure (P ≤ 0.05). The index infarcted area / total heart area, in both: hypercholesterolemic and hypertensive rats supplemented with L-arginine, showed a significant 36% and 29% of cardio protection (P ≤ 0.05) effect, respectively. Dietary supplementation with L-arginine may represent a potentially novel nutritional strategy for the treatment of cardiovascular disease.     

Effects of feeding yeast(Saccharomyces cerevisiae), organic selenium and chromium mixed on growth performance and carcass traits of hair lambs

Yeasts and organic minerals are used in diets to improve health, productive performance and some carcass characteristics of ruminants and non-ruminants. Thirty-two lambs(Pelibuey×Katahdin; BW=(30.55±1.67) kg; n=8) were used in a 56-d feeding experiment to study the effects of different levels of live yeast(Saccharomyces cerevisiae; yeast), selenium(Se) and chromium(Cr) mixed(Se-Cr), and a mixture of yeast-Se-Cr on growth performance and carcass traits. Animals were stratified by body weight(BW) and randomly assigned to one of four treatments: 1) control group(0.0 g kg–1 yeast); 2) yeast(1.50 g kg–1 dry matter intake(DMI) d–1); 3) Se-Cr premix(1.5 mg kg–1 DMI d–1 for each mineral); and 4) yeast-Se-Cr mixture. There were no treatment effects on final BW; whereas lambs fed Se-Cr or yeast-Se-Cr had higher(P0.05) DMI than animals supplemented with only yeast. Average daily gain(ADG), gain:feed ratio, chop area, dorsal fat and carcass yield were similar(P0.05) among treatment groups. In conclusion, supplementation with yeast, Se-Cr mixed or yeast-Se-Cr did not improve ADG, final BW, back fat content and carcass yield of growing of Pelibuey×Katahdin lambs. Supplementation with Se-Cr and yeast-Se-Cr increased DMI, and approximately 250 g ADG animal–1 d–1 was produced with no negative effects on growth and health of the animals.     

Carbon Stocks and Fluxes in Rangelands of the Río de la Plata Basin

Grasslands are one of the most modified biomes on Earth. Land use changes had a large impact on carbon (C) stocks of grasslands. Understanding the impact of land use/land cover changes on C stocks and fluxes is critical to evaluate the potential of rangeland ecosystem as C sinks. In this article we analyze C stocks and fluxes across the environmental gradients of one of the most extensive temperate rangeland areas: the Río de la Plata Grasslands (RPG) in South America. The analysis summarizes information provided by field studies, remote sensing estimates, and modeling exercises. Average estimates of aboveground net primary production (ANPP) ranged from 240 to 316 g C· m^?2·yr^?1. Estimates of belowground NPP (BNPP) were more variable than ANPP and ranged from 264 to 568 g C· m^?2·yr^?1. Total Carbon ranged from 5 004 to 15 008 g C· m^?2. Plant biomass contribution to Total Carbon averaged 13% and varied from 9.5% to 27% among sites. The largest plant C stock corresponded to belowground biomass. Aboveground green biomass represented less than 7% of the plant C. Soil organic carbon (SOC) was concentrated in the slow and passive compartments of the organic matter. Active soil pool represented only 6.7% of the SOC. The understanding of C dynamics and stocks in the RPG grasslands is still partial and incomplete. Field estimates of ANPP and BNPP are scarce, and they are not based on a common measurement protocol. Remotely sensed techniques have the potential to generate a coherent and spatially explicit database on ANPP. However, more work is needed to improve estimates of the spatial and temporal variability of radiation use efficiency. The absence of a flux tower network restricts the ability to track seasonal changes in C uptake and to understand fine-scale controls of C dynamics.     

Forecasting Apple Fruit Color Intensity with Machine Learning Methods

In this study, we focused on the possibility of forecasting the development of skin color in apples on the basis of weather forecast by using a machine learning methods. We used supervised learning and generated models via the use of six decision trees. The purpose of the research was to build models that would allow for in-practice-acceptable accuracy in the prediction of the development of fruit skin color (especial a colour parameter a*), for three apple varieties. For cv. ‘Gala, Brookfield’, the most accurate models were generated by using decision tree J48 (89.13% accuracy). For late ripening cv. ‘Fuji, Kiku 8’ and cv. ‘Braeburn, Maririred’, the most accurate model was obtained by using decision tree LMT (91.73 and 96.65% accuracy). The data confirm that the applicability of predictive models strongly depends on the accuracy of weather forecasts. In regard to the seven-day weather forecast, which was used for expert models, the accuracy of the models was, on average, reduced by 10.73%.     

Supervised pattern recognition procedures for discrimination of whiskeys from gas chromatography/mass spectrometry congener analysis

The volatile congener analysis of 52 commercialized whiskeys (24 samples of single malt Scotch whiskey, 18 samples of bourbon whiskey, and 10 samples of Irish whiskey) was carried out by gas chromatography/mass spectrometry after liquid-liquid extraction with dichloromethane. Pattern recognition procedures were applied for discrimination of different whiskey categories. Multivariate data analysis includes linear discriminant analysis (LDA), k nearest neighbors (KNN), soft independent modeling of class analogy (SIMCA), procrustes discriminant analysis (PDA), and artificial neural networks techniques involving multilayer perceptrons (MLP) and probabilistic neural networks (PNN). Classification rules were validated by considering the number of false positives (FPs) and false negatives (FNs) of each class associated to the prediction set. Artificial neural networks led to the best results because of their intrinsic nonlinear features. Both techniques, MLP and PNN, gave zero FPs and zero FNs for all of the categories. KNN is a nonparametric method that also provides zero FPs and FNs for every class but only when selecting K = 3 neighbors. PDA produced good results also (zero FPs and FNs always) but only by selecting nine principal components for class modeling. LDA shows a lesser classification performance, because of the building of linear frontiers between classes that does not apply in many real situations. LDA led to one FP for bourbons and one FN for scotches. The worse results were obtained with SIMCA, which gave a higher number of FPs (five for both scotches and bourbons) and FNs (six for scotchs and two for bourbons). The possible cause of these findings is the strong influence of class inhomogeneities on the SIMCA performance. It is remarkable that in any case, all of the methodologies lead to zero FPs and FNs for the Irish whiskeys.     

Failure to establish infection with Tetratrichomonas sp. in the reproductive tracts of heifers and bulls

Experimental infection of the reproductive tracts of heifers and bulls with Tetratrichomonas sp. isolated from preputial smegma of virgin bulls was attempted. Nine heifers and four bulls were challenged by inoculation of 7 x 10(6) Tetratrichomonas sp. into the vaginal lumen and preputial cavity, respectively. Vaginal mucus and preputial smegma samples were collected and cultured for Tetratrichomonas sp. Heifers were slaughtered in groups of three at 2, 9 and 21 days after inoculation. Two heifers and two bulls infected with Tritrichomonas foetus and two uninfected heifers were used as controls for the model infection. Tetratrichomonas sp. were only isolated in vaginal mucus of 7/9 inoculated heifers at 6h post-inoculation, and genital secretions taken at slaughter time from vagina, uterus and oviduct were cultural negative. Bulls challenged with Tetratrichomonas sp. remained cultural negative. Since Tetratrichomonas sp. survived only a few hours in the female genitalia and did not survive in the male genitalia after experimental challenge, Tetratrichomonas sp. did not colonize the genital tract. These were likely trichomonads from the digestive tract. Collection of clean samples without fecal contamination from the reproductive tract is proposed as a measure to avoid Tetratrichomonas sp. transitory genital infection.     

Influence of separating home range and dispersal movements on characterizing corridors and effective distances

Context

Corridors are usually delineated as areas of minimum cumulative resistance to movement through a resistance surface and characterized by their effective distance (accumulated resistance along the least-cost path). The results of these assessments depend on resistance values, which are typically derived from the inverse of habitat suitability models or from presence data of individuals within their home ranges, rather than from data on dispersal or exploratory movements.

Objective

Evaluate the extent to which corridor delineation and effective distance estimates may vary depending on whether home range locations or dispersal data are used to characterize species habitat selection and landscape resistance to movement.

Methods

We analyzed a large telemetry dataset (GPS collars) for the endangered Iberian lynx. We modeled corridors and effective distances three ways: (1) considering only GPS locations within home ranges, (2) considering only locations in dispersal or exploratory movements outside home ranges, and (3) considering all locations together.

Results

Delineated least-cost corridors followed similar trajectories and sometimes overlapped in the three models. The estimated effective distances were 42 % lower in the dispersal-based model than in the model based solely on home range use.

Conclusions

Models derived exclusively from locations within home ranges may provide lower connectivity estimates than models derived from dispersal locations, affecting estimates of resistance to move between habitat areas, even when the most likely movement routes are similar. Although dispersal data are costly to gather, they potentially provide more realistic assessments of the actual isolation of populations in heterogeneous landscapes.

     

Binderless fiberboard from steam exploded banana bunch

Musacea bunch was pretreated and used to produce fiberboard with non-synthetic binders. The lignocellulosic material was steam exploded with a thermomechanical aqueous vapor process in a batch reactor. The effect of the pretreatment and the pressure conditions on the physical–mechanical responses of the fiberboard was evaluated and the conditions maximizing the responses were found. Response surface methodology with a central composite design was used. The variables studied and their respective variation ranges were: pretreatment severity, 3.16–4.84; pressing temperature, 133–217 °C; pressing pressure, 3.95–14.04 MPa. The fiberboards obtained were good quality and satisfied the requirements of the relevant standard specifications. The effect of the pretreatment severity on the lignin, cellulose and xylans content was also determined by an analysis of variance. The decrease in xylans was clearly related to the increase in the dimensional stability of the fiberboards.