Carcass characteristics and meat evaluation of Nelore cattle subjected to different antioxidant treatments

Forty Nelore cattle were used to evaluate the effects of supplementation with different antioxidants on carcass characteristics and meat quality of feedlot cattle. Animals were fed Brachiaria brizantha hay and subjected to five treatments (control and four antioxidants: zinc, selenium, vitamin E, and selenium + vitamin E). After a 105-day feeding period, cattle were slaughtered. Tissue composition, as well as carcass proximate composition, color, tenderness, pH, and fatty acid profile were evaluated. Analysis of variance was carried out and means compared by Tukey test at 0.05 probability. The group fed selenium showed the lowest muscle amount (66.61 g/100 g) compared with the other antioxidants evaluated. There was no difference among treatments for bone, fat, and comestible portion percentages as well as muscle:bone, muscle:fat, and comestible portion:bone ratios, with mean values of 16.85 g/100 g, 14.70 g/100 g, 82.99 g/100 g, 4.06, 4.85, and 4.95, respectively. Neither brightness, red, or yellow contents of the meat nor carcass pH were affected by treatments. For tenderness and losses during thawing and cooking, there were no differences among treatments, with averages of 6.43 kgf cm2, 3.22 g/100 g, and 21.15 g/100 g, respectively. Supplementation of Nelore cattle fed Brachiaria brizantha hay with antioxidants do not influence carcass characteristics or meat quality. However, vitamin E supplementation reduces the levels of omega 3 fatty acid, whereas supplementation with selenium + vitamin E promotes an increase in linoleic and palmitoleic acids and a decrease in myristoleic acid, making the supplementation feasible due to the beneficial effects provided by these acids

Additives on in vitro ruminal fermentation characteristics of rice straw

The objective of this study was to evaluate the effects of mineral and protein-energy (MPES), exogenous fibrolytic enzyme supplements (ES), combination of MPES + ES, and straw without supplement (WS) on digestibility, fermentation kinetic parameters, cumulative gas production, methane, CO2 production, and volatile fatty acid concentration of rice straw of low and high nutritional value, estimated by in vitro techniques. The experimental design was randomized and factorial 2 × 4: two straws (low and high nutritional value) incubated with four supplements (MPES, ES, MPES + ES, and WS) and their interactions. Four experimental periods were used, totaling four replications per treatment over time. Data were analyzed by PROC MIXED of SAS. The in vitro dry matter and organic matter digestibilities of the rice straw with high nutritional value was improved by MPES, while the combination of MPES + ES supplements inhibited the digestibility of this straw. Dietary carbohydrate and nitrogen increased through MPES and MPES + ES supplements resulted in an increase in NH3-N concentration and a decrease in CO2 production due to the microbial mass formation. However, this increase was not enough to improve organic matter degradability parameters, cummulative gas production, gas production kinetics, and acetate:propionate ratio and reduce methane emissions. The straw with high nutritional value showed greater content of nitrogen fraction a, effective degradability, cummulative gas production, and methane and CO2 productions comparing with low-nutritional value straw. The use of MPES and MPES + ES supplements can be used as strategy to mitigate CO2 in ruminant production systems that use rice straw

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight NCD Risk Factor Collaboration (NCD-RisC)

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions