scholarly journals Straw as an Alternative to Grass Forage in Horses—Effects on Post-Prandial Metabolic Profile, Energy Intake, Behaviour and Gastric Ulceration

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2197
Author(s):  
Anna Jansson ◽  
Patricia Harris ◽  
Sara Larsdotter Davey ◽  
Nanna Luthersson ◽  
Sveinn Ragnarsson ◽  
...  

Straw’s low energy content means it is a roughage option for horses with low energy requirements. Previously, in a field study, straw was associated with an increased risk for gastric ulcers. This study evaluated the effect on gastric ulcers, metabolic profile and behaviour of replacing, in a forage-only ration, 50% of the daily allowance with wheat straw. Six equines were studied in a 2 × 21-day cross-over design. The control diet (CON: 100% grass forage) and the straw diet (S: 50% grass forage and 50% straw [DM basis]) were iso-energetic. Gastroscopy was performed prior to the study and on day 21 and blood samples were collected and behavioural observations were performed. Diet did not affect squamous or glandular gastric ulcer scores (p > 0.05). Feed intake time was longer (p < 0.05) plus energy intake and plasma insulin concentrations were lower on diet S compared to CON (p < 0.0001). Plasma serotonin concentrations tended to be higher on diet S compared to CON (p = 0.05). The results suggest that good hygienic quality wheat straw can be included for up to 50% of the diet without causing gastric ulcers and that it can extend feeding time and promote a metabolic profile more suitable for overweight horses.

Author(s):  
Tommy Slater ◽  
William J. A. Mode ◽  
John Hough ◽  
Ruth M. James ◽  
Craig Sale ◽  
...  

Abstract Purpose This study aimed to assess the effects of consuming a very-low-energy placebo breakfast on subsequent appetite and lunch energy intake. Methods Fourteen healthy males consumed water-only (WAT), very-low-energy, viscous placebo (containing water, low-calorie flavoured squash, and xanthan gum; ~ 16 kcal; PLA), and whole-food (~ 573 kcal; FOOD) breakfasts in a randomised order. Subjects were blinded to the energy content of PLA and specific study aims. Venous blood samples were collected pre-breakfast, 60- and 180-min post-breakfast to assess plasma acylated ghrelin and peptide tyrosine tyrosine concentrations. Subjective appetite was measured regularly, and energy intake was assessed at an ad libitum lunch meal 195-min post-breakfast. Results Lunch energy intake was lower during FOOD compared to WAT (P < 0.05), with no further differences between trials (P ≥ 0.132). Cumulative energy intake (breakfast plus lunch) was lower during PLA (1078 ± 274 kcal) and WAT (1093 ± 249 kcal), compared to FOOD (1554 ± 301 kcal; P < 0.001). Total area under the curve (AUC) for hunger, desire to eat and prospective food consumption were lower, and fullness was greater during PLA and FOOD compared to WAT (P < 0.05). AUC for hunger was lower during FOOD compared to PLA (P < 0.05). During FOOD, acylated ghrelin was suppressed compared to PLA and WAT at 60 min (P < 0.05), with no other hormonal differences between trials (P ≥ 0.071). Conclusion Consuming a very-low-energy placebo breakfast does not alter energy intake at lunch but may reduce cumulative energy intake across breakfast and lunch and attenuate elevations in subjective appetite associated with breakfast omission. Trial registration NCT04735783, 2nd February 2021, retrospectively registered.


1963 ◽  
Vol 43 (2) ◽  
pp. 290-293 ◽  
Author(s):  
J. R. Aitken ◽  
E. S. Merritt ◽  
H. E. W. Meyer ◽  
L. Griesbach

Three replicate trials were conducted to test the possibility that high mortality of non-specific origin being encountered in a genetic control strain of meat-type laying hens might be due to excessive energy intake. In each trial, the medium energy laying ration on which this strain of birds has been maintained for a number of years was compared with the same ration diluted with 20 per cent pulverized oat hulls, for a period in excess of 330 days.Mortality was not influenced by the energy content of the ration, nor was rate of egg production. The low energy ration reduced final body weight by only 0.1 to 0.2 pounds, suggesting that the birds on the control diet were not unduly fat. Comparison of these results with others reported in the literature leads to the speculation that mortality due to obesity may be a problem only in heavier and faster-growing strains than the strain used in this study.


1986 ◽  
Vol 251 (4) ◽  
pp. E483-E488
Author(s):  
M. S. Kurzer ◽  
D. H. Calloway

To determine whether short-term energy deprivation affects sex hormone patterns, six healthy women were studied for two menstrual cycles. Two diets containing recommended levels of all nutrients and differing substantially only with respect to energy content were provided in sequence. During the first cycle, energy intake was 40 +/- 2 kcal/kg body weight, and weight was essentially constant. For the second cycle, energy intake was reduced to 41% of the original intake, averaging 17 +/- 1 kcal/kg initial body weight. During the low-energy diet, weight loss ranged from 3.2 to 6.7 kg. The two leanest women, who also lost the most weight, became anovulatory and amenorrheic in the low-energy period. Within a specific phase of cycle, however, the diet did not affect concentrations of estradiol, progesterone, luteinizing hormone, or follicle-stimulating hormone. Testosterone and androstenedione levels peaked midcycle normally and were decreased with the low-energy diet, while levels of sex hormone-binding globulin increased and those of dehydroepiandrosterone sulfate did not change. These results demonstrate short-term dietary and body composition effects on the menstrual cycle and serum androgens.


1967 ◽  
Vol 9 (1) ◽  
pp. 107-113 ◽  
Author(s):  
J. B. Owen ◽  
W. J. Ridgman

1. An experiment to investigate the effect of dietary energy concentration on the voluntary intake and growth of pigs from 27·2 to 118·0 kg. (60 to 260 lb.) live-weight is described and the results discussed.2. From 27·2 to 50·0 kg. live-weight energy intake was substantially restricted and growth retarded by diets of low energy concentration but from 50·0 to 118·0 kg. there was little difference between diets in either energy intake or growth because daily food intake of the low energy diets was increased.3. Effects of diet on carcass quality as measured by full dissection were small except that killing-out percentage was lower on one of the low energy diets.4. It is concluded that limited differences in the energy concentration and palatability of ingredients are unimportant in formulating pelleted diets for self-fed pigs.


2021 ◽  
Vol 10 (15) ◽  
pp. 3309
Author(s):  
Gisella Gennaro ◽  
Melissa L. Hill ◽  
Elisabetta Bezzon ◽  
Francesca Caumo

Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms.


2017 ◽  
Vol 8 (4) ◽  
pp. 225-230 ◽  
Author(s):  
Sanjit R. Konda ◽  
Ariana Lott ◽  
Hesham Saleh ◽  
Sebastian Schubl ◽  
Jeffrey Chan ◽  
...  

Introduction: Frailty in elderly trauma populations has been correlated with an increased risk of morbidity and mortality. The Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) is a validated mortality risk score that evaluates 4 major physiologic criteria: age, comorbidities, vital signs, and anatomic injuries. The aim of this study was to investigate whether the addition of additional frailty variables to the STTGMA tool would improve risk stratification of a middle-aged and elderly trauma population. Methods: A total of 1486 patients aged 55 years and older who met the American College of Surgeons Tier 1 to 3 criteria and/or who had orthopedic or neurosurgical traumatic consultations in the emergency department between September 2014 and September 2016 were included. The STTGMAORIGINAL and STTGMAFRAILTY scores were calculated. Additional “frailty variables” included preinjury assistive device use (disability), independent ambulatory status (functional independence), and albumin level (nutrition). The ability of the STTGMAORIGINAL and the STTGMAFRAILTY models to predict inpatient mortality was compared using area under the receiver operating characteristic curves (AUROCs). Results: There were 23 high-energy inpatient mortalities (4.7%) and 20 low-energy inpatient mortalities (2.0%). When the STTGMAORIGINAL model was used, the AUROC in the high-energy and low-energy cohorts was 0.926 and 0.896, respectively. The AUROC for STTGMAFRAILTY for the high-energy and low-energy cohorts was 0.905 and 0.937, respectively. There was no significant difference in predictive capacity for inpatient mortality between STTGMAORIGINAL and STTGMAFRAILTY for both the high-energy and low-energy cohorts. Conclusion: The original STTGMA tool accounts for important frailty factors including cognition and general health status. These variables combined with other major physiologic variables such as age and anatomic injuries appear to be sufficient to adequately and accurately quantify inpatient mortality risk. The addition of other common frailty factors that account for does not enhance the STTGMA tool’s predictive capabilities.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 233-234
Author(s):  
David N Kelly ◽  
Roy D Sleator ◽  
Craig P Murphy ◽  
Stephen B Conroy ◽  
Donagh P Berry

Abstract To the best of our knowledge, the genetic variability in feeding behavior, as well as relationships with performance and feed efficiency, has not been investigated in a cattle population of greater than 1,500 animals. Our objective was to quantify the genetic parameters of several feeding behavior traits, and their genetic associations with both performance and feed efficiency traits, in crossbred growing cattle. Feed intake and live-weight data were available on 6,088 bulls, steers and heifers; of these, 4,672 cattle had backfat and muscle ultrasound data, and 1,548 steers and heifers had feeding behavior data. Genetic (co)variance parameters were estimated using animal linear mixed models; fixed effects included test group, heterosis, recombination loss, dam parity, age in months at the end of test, and the two-way interaction between age in months at the end of test and sex. Heritability was estimated to be 0.51 (0.097), 0.61 (0.100), 0.44 (0.093), 0.48 (0.094), and 0.47 (0.095) for feed events per day, feeding time per day, feeding rate, feed event duration, and energy intake per feed event, respectively. Coefficients of genetic variation ranged from 0.11 (feeding time per day) to 0.22 (feed event duration). Genetically heavier cattle with a higher energy intake per day, and faster growth rate, had a faster feeding rate and a greater energy intake per feed event. Genetic correlations between feeding behavior and feed efficiency were generally not different from zero, however, there was a genetic correlation of 0.36 (0.11) between feeding time per day and residual energy intake. Significant heritable and exploitable genetic variation exists in several feeding behavior traits in crossbred growing cattle which are also correlated with several performance traits. As some feeding behavior traits may be relatively less resource intensive to measure, they could be useful as predictor traits in beef cattle genetic evaluations.


2001 ◽  
Vol 72 (2) ◽  
pp. 335-342 ◽  
Author(s):  
R. Schwager-Suter ◽  
C. Stricker ◽  
D. Erdin ◽  
N. Künzi

Abstract Net energy efficiencies were calculated from data of an experimental herd with respect to type of cow, lactation number, stage of lactation and diet. The trial consisted of 71 Holstein-Friesians, 71 Jerseys and 71 Holstein-Jersey F1-crosses in 1st, 2nd and > 2nd lactation. Data were collected during 210 days of lactation, from calving to week 30 and included total dry matter intake, energy content of foods, milk yield, milk solids, body weight, body condition scores and several body measurements. The cows were divided into four feeding groups : high and low energy content of roughage as well as high and low proportion of concentrates. Net energy efficiency was calculated as the ratio of milk energy to total net energy intake after subtracting energy utilized for maintenance and body tissue change. Body tissue change was calculated either via body-weight changes or body condition-score changes. Due to the distribution of the efficiencies being skewed, efficiencies were transformed applying a Box-Cox transformation. Transformed net energy efficiencies were analysed using a repeated measurements design considering the sequential nature of the observations. Mixed models with a compound symmetry structure for the variance components were applied. Final models contained the fixed effects of type, lactation number, feeding group and the covariates week of lactation and its square. Holstein-Jersey crosses were more efficient than purebreds, second lactation cows were least efficient, cows given low energy roughage and a lower proportion of concentrates were more efficient than cows on the other diets. Least efficient were the cows belonging to the high energy roughage and higher proportion of concentrates group. The coefficients of determination of the final models were between 0·357 and 0·492.


2007 ◽  
Vol 97 (3) ◽  
pp. 579-583 ◽  
Author(s):  
Angela Harper ◽  
Anita James ◽  
Anne Flint ◽  
Arne Astrup

The rising rate of obesity has been blamed on increased consumption of sugar-sweetened soft drinks, such as carbonated sodas, which fail to satisfy hunger. The objective of the present study was to compare the effect on appetite and energy intake of a sugar-sweetened beverage (cola) and a chocolate milk drink, matched for energy content and volume. It was hypothesised that chocolate milk may be more satiating because of its protein content. Twenty-two healthy young men (age 23 (sd 1·8) years) of normal weight (BMI 22·2 (sd 1·5) kg/m2) were recruited to the randomised cross-over study. Visual analogue scales were used to record subjective appetite ratings every 30 min on each of two test days. A drink of 500 ml cola or chocolate milk (900 kJ) was ingested 30 min before an ad libitum lunch. Satiety and fullness were significantly greater (P = 0·0007, P = 0·0004, respectively) 30 min after chocolate milk than after cola. Ratings of prospective consumption and hunger were significantly greater after cola than after chocolate milk, both immediately after preload intake (P = 0·008, P = 0·01, respectively) and 30 min afterwards (P = 0·004, P = 0·01, respectively). There was no significant difference (P = 0·42) in ad libitum lunch intake after ingestion of chocolate milk (3145 (sd 1268) kJ) compared with cola (3286 (sd 1346) kJ). The results support the hypothesis that sweetened soft drinks are different from milk products in their impact on short-term hunger and satiety, although differences in subjective appetite scores were not translated into differences in energy intake.


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