Dietary intake of artificial food color additives containing food products by school-going children

Nutritional risk in children is associated with food safety. This is the first study to identify the food type consumed by 6–17-year-old school-going children in Saudi Arabia. Eight permitted artificial food color additives, including Tartrazine (E102), Sunset Yellow (E110), Carmoisine (E122), Allura Red (E129), Indigo Carmine (E132), Brilliant Blue (E133), Fast Green (E143), and Black PN (E151), and two non-permitted ones, Erythrosine (E127) and Red 2G (E128), were determined using 24-h dietary recall questionnaires. Artificial color additives in 839 food products were divided into nine categories, including biscuits, cakes, chocolates, chips, ice cream, juices and drinks, candy, jelly, and chewing gum, are determined using high performance liquid chromatography and diode array detector. The results indicated a high intake of juices and drinks, ice cream, and cakes, but low consumption of chewing gum among school-going children. Among the permitted artificial food color additives, Brilliant Blue (E133) (54.1%) and Tartrazine (E102) (42.3%) were the most commonly used. Sunset Yellow (E110) in one chocolate sample, Tartrazine (E102) and Sunset Yellow (E110) in one and two juice and drink samples, respectively, and Brilliant Blue (E133) in two candy samples exceeded the permitted level. Therefore, further investigations are needed to provide insights into the possible adverse health effects of high intake of these additives in artificial food coloring on the test population are warranted.     

The response of weaned piglets to dietary valine and leucine

Valine (Val) is considered to be the fifth-limiting amino acid in a maize–soyabean meal diet for pigs. Excess leucine (Leu) levels often occur in commercial diets, which may attenuate the effect of Val deficiency because of an increased oxidation of Val. The objective of the present experiment was to determine the effect of increasing concentrations of Leu on the response of young piglets to dietary Val. In all, 75 Large White×Landrace entire male pigs, 44 days of age and with a mean starting weight of 13.5 kg, were used. Three of these were sacrificed at the start to determine their mean initial chemical composition. A summit feed first limiting in Val was serially diluted with a non-protein diluent to produce a series of five digestible Val concentrations of 11.9, 10.1, 8.3, 6.6 and 4.8 g/kg, with a sixth treatment being added to test that the feeds were limiting in Val. Three identical Val series, each with six levels of Val, were supplemented with increasing amounts of Leu (23, 45 and 67 g/kg), thus 18 treatments in total. All pigs were killed at the end of the trial after 18 days for analysis of water, protein, lipid and ash in the carcass. The levels of Val and Leu and their interaction significantly influenced all the measurements taken in the trial. Daily gain in liveweight, water and protein, and feed conversion efficiency all increased with dietary Val content, whereas feed intake decreased as both Val and Leu contents increased. The deleterious effect of increased Leu on feed intake and growth was more marked at lower levels of Val. Supplementing the feed with the lowest Val content with additional Val largely overcame the effect of excess Leu. The efficiency of utilisation of Val for protein growth was unaffected by the level of Leu in the feed, the primary response to excess Leu being a reduction in feed intake. An intake of around 9 g Val/day yielded maximal protein growth during the period from 44 to 62 days of age in pigs of the genotype used in this trial.     

Iron supplementation moderates but does not cure the Belgrade anemia

Belgrade rats inherit microcytic, hypochromic anemia as an autosomalrecessive trait (gene symbol b). Erythrocytes and tissue are iron deficientin the face of elevated TIBC (total iron binding capacity) and percent ironsaturation; iron injections increased the number of erythrocytes but theirappearance remained abnormal. We have investigated iron supplements toimprove husbandry of b/b rats and to learn more about the underlying defectand its tissue distribution. Weekly IM (intramuscular) injections ofiron–dextran (Imferon at 30 mg kg) improved the anemia but did not alter thered cell morphology. Certain diets also improved the health of b/b rats whencompared to standard rat chows by the criteria of weight, survival toadulthood, hematology and reproduction. The critical nutritional factorturned out to be iron bioavailability, with ferrous iron added to the dietimproving the health of Belgrade rats without affecting the underlyingerythroid defect. Tissue iron measurements after dietary or parenteralsupplementation confirmed the iron deficient status of untreated b/b rats andestablished that dietary ferrous iron partially relieved this deficiency,with injections leading to greater amounts of tissue iron. Serum iron andTIBC were also found to be elevated in untreated b/b rats, with dietarysupplementation decreasing but not eliminating the elevation in TIBC. Thesestudies indicate that iron supplements can improve the health of b/b ratswithout altering the underlying defect and also suggest that the mutationcould alter iron uptake in the GI (gastrointestinal) tract.     

Integration of the effects of animal and dietary factors on total dry matter intake of dairy cows fed silage-based diets

An empirical regression model for the prediction of total dry matter intake (DMI) of dairy cows was developed and compared with four published intake models. The model was constructed to include both animal and dietary factors, which are known to affect DMI. For model development, a data set based on individual cow data from 10 change-over and four continuous milk production studies was collected (n = 1554). Relevant animal (live weight (LW), days in milk (DIM), parity and breed) and dietary (total and concentrate DMI, concentrate composition, forage digestibility and fermentation quality) data were collected. The model factors were limited to those that are available before the diets are fed to animals, that is, standardized energy corrected milk (sECM) yield, LW, DIM and diet quality (total diet DMI index (TDMI index)). As observed ECM yield is a function of both the production potential of the cow and diet quality, ECM yield standardized for DIM, TDMI index and metabolizable protein concentration was used in modelling. In the individual data set, correlation coefficients between sECM and TDMI index or DIM were much weaker (0.16 and 0.03) than corresponding coefficients with observed ECM (0.65 and 0.46), respectively. The model was constructed with a mixed model regression analysis using cow within trial as a random factor. The following mixed model was estimated for DMI prediction: DMI (kg DM/day) = -2.9 (±0.56)+0.258 (±0.011) × sECM (kg/day) + 0.0148 (±0.0009) × LW (kg) -0.0175 (±0.001) × DIM -5.85 (±0.41) × exp (-0.03 × DIM) + 0.09 (±0.002) × TDMI index. The mixed DMI model was evaluated with a treatment mean data set (207 studies, 992 diets), and the following relationship was found: Observed DMI (kg DM/day) = -0.10 (±0.33) + 1.004 (±0.019) × Predicted DMI (kg DM/day) with an adjusted residual mean square error of 0.362 kg/day. Evaluation of the residuals did not result in a significant mean bias or linear slope bias, and random error accounted for proportionally >0.99 of the error. In conclusion, the DMI model developed is considered robust because of low mean prediction error, accurate and precise validation, and numerically small differences in the parameter values of model variables when estimated with mixed or simple regression models. The Cornell Net Carbohydrate and Protein System was the most accurate of the four other published DMI models evaluated using individual or treatment mean data, but in most cases mean and linear slope biases were relatively high, and, interestingly, there were large differences in both mean and linear slope biases between the two data sets.     

A mathematical model on fractional Lotka-Volterra equations

While there are many mechanisms that may be involved in the regulation of body mass in humans and other animals, it is not so clear how much regulation is needed beyond the negative feedback effect of body mass itself. Here we model weight changes as a stochastic process, and show that it behaves approximately as an autoregressive process. Using published estimates of the energy cost of weight gain, the effect of weight on resting metabolic rate and the daily variation in intake and activity, we show that fluctuations in weight will be small. The effect of excess intake is also examined, and the assumptions and limitations of the model are discussed.     

鳜配合饲料的最适蛋白质含量

以美国白鱼粉为蛋白源 ,设计了 6个不同蛋白质水平 (32 .6 1%、38.10 %、4 3.5 5 %、4 8.95 %、5 3.6 4 %、5 6 .30 % )的实验饲料 ,在平均水温 2 2 .5℃的条件下 ,在水泥池网箱中 ,对平均尾重为 6 5 .0 0± 2 .2 5g的鳜进行 4 1d的生长实验。结果显示 :随饲料蛋白质含量的升高 ,特定生长率 (SGR)最初快速上升 ,在 4 8.95 %转为缓慢下降 ;蛋白质效率(PER)的变化则呈抛物线型 ,在 4 4 .2 7%处为顶点。据此提出鳜配合饲料的最适蛋白质含量为 4 4 .2 7%— 4 8.4 1%。     

Dietary choices are influenced by genotype,mating status,and sex in Drosophila melanogaster

Mating causes many changes in physiology, behavior, and gene expression in a wide range of organisms. These changes are predicted to be sex specific, influenced by the divergent reproductive roles of the sexes. In female insects, mating is associated with an increase in egg production which requires high levels of nutritional input with direct consequences for the physiological needs of individual females. Consequently, females alter their nutritional acquisition in line with the physiological demands imposed by mating. Although much is known about the female mating‐induced nutritional response, far less is known about changes in males. In addition, it is unknown whether variation between genotypes translates into variation in dietary behavioral responses. Here we examine mating‐induced shifts in male and female dietary preferences across genotypes of Drosophila melanogaster. We find sex‐ and genotype‐specific effects on both the quantity and quality of the chosen diet. These results contribute to our understanding of sex‐specific metabolism and reveal genotypic variation that influences responses to physiological demands.