Predictive models for disease detection in group-housed preweaning dairy calves using data collected from automated milk feeders.

In the United States, dairy calves are typically housed individually due to the perception of reduced risk of spreading infectious diseases between calves and the ability to monitor health on an individual calf basis. However, automated milk feeders (AMF) can provide individual monitoring of group-housed calves while allowing them to express more natural feeding behaviors and interact with each other. Research has shown that feeding behaviors recorded by AMF can be a helpful screening tool for detecting disease in dairy calves. Altogether, there is an opportunity to use the data from AMF to create a more robust and efficient model to predict disease, reducing the need for visual observation. Therefore, the objective of this observational study was to predict disease in preweaning dairy calves using AMF feeding behavior data and machine learning (ML) algorithms. This study was conducted on a dairy farm located in the Upper Midwest United States and visited weekly from July 2018 to May 2019. During farm visits, AMF data and calves' treatment records were collected, and calves were visually health-scored for attitude, ear position, ocular discharge, nasal discharge, hide dirtiness, and cough score. The final datasets used for the analyses consisted of 740 and 741 calves, with 1,007 (healthy = 594 and sick = 413) and 1,044 (healthy = 560 and sick = 484) observations (health events) for Data 1 and Data 2, respectively. Data 1 included only the weekly calf health scores observed by research personnel, whereas Data 2 included primarily daily calf treatment records by farm staff in addition to weekly health scores. Calf visit-level feeding behaviors from AMF data included milk intake (mL/d), drinking speed (mL/min), visit duration (min), rewarded (with milk being offered) and unrewarded (without milk) visits (number per d), and the interval between visits (min). Three approaches were used to predict health status: generalized linear model, random forest, and gradient boosting machine. A total of 16 models were built using different combinations of behavior parameters, including the number of rewarded visits, number of unrewarded visits, visit duration, the interval between visits, intake, intake divided by rewarded visits, drinking speed, and drinking speed divided by rewarded visits, and also calf age at the sick day as predictor variables. Of all algorithms, random forest and gradient boosting had the best performance predicting the health status of dairy calves. The results indicated that weekly health scores were not enough to predict calf health status. However, daily treatment records and AMF data were sufficient for creating predictive algorithms (e.g., F1-scores of 0.775 and 0.784 for random forest and gradient boosting, Data 2). This study suggests that ML was effective in determining the specific visit-level feeding behaviors that can be used to predict disease in group-housed preweaning dairy calves. Implementing these ML algorithms could reduce the need for visual calf observation on farms, minimizing labor time and improving calf health.

Assessing optimal frequency for image acquisition in computer vision systems developed to monitor feeding behavior of group-housed Holstein heifers.

Computer vision systems have emerged as a potential tool to monitor the behavior of livestock animals. Such high-throughput systems can generate massive redundant data sets for training and inference, which can lead to higher computational and economic costs. The objectives of this study were (1) to develop a computer vision system to individually monitor detailed feeding behaviors of group-housed dairy heifers, and (2) to determine the optimal frequency of image acquisition to perform inference with minimal effect on feeding behavior prediction quality. Eight Holstein heifers (96 ± 6 d old) were housed in a group and a total of 25,214 images (1 image every second) were acquired using 1 RGB camera. A total of 2,209 images were selected and each animal in the image was labeled with its respective identification (1-8). The label was annotated only on animals that were at the feed bunk (head through the feed rail). From the labeled images, 1,392 were randomly selected to train a deep learning algorithm for object detection with YOLOv3 ("You Only Look Once" version 3) and 154 images were used for validation. An independent data set (testing set = 663 out of the 2,209 images) was used to test the algorithm. The average accuracy for identifying individual animals in the testing set was 96.0%, and for each individual heifer from 1 to 8 the accuracy was 99.2, 99.6, 99.2, 99.6, 99.6, 99.2, 99.4, and 99.6%, respectively. After identifying the animals at the feed bunk, we computed the following feeding behavior parameters: number of visits (NV), mean visit duration (MVD), mean interval between visits (MIBV), and feeding time (FT) for each heifer using a data set composed by 8,883 sequential images (1 image every second) from 4 time points. The coefficient of determination (R2) was 0.39, 0.78, 0.48, and 0.99, and the root mean square error (RMSE) were 12.3 (count), 0.78, 0.63, and 0.31 min for NV, MVD, MIBV, and FT, respectively, considering 1 image every second. When we moved from 1 image per second to 1 image every 5 (MIBV) or 10 (NV, MDV, and FT) s, the R2 observed were 0.55 (NV), 0.74 (MVD), 0.70 (MIBV), and 0.99 (FT); and the RMSE were 2.27 (NV, count), 0.38 min (MVD), 0.22 min (MIBV), and 0.44 min (FT). Our results indicate that computer vision systems can be used to individually identify group-housed Holstein heifers (overall accuracy = 99.4%). Based on individual identification, feeding behavior such as MVD, MIBV, and FT can be monitored with reasonable accuracy and precision. Regardless of the frequency for optimal image acquisition, our results suggested that longer time intervals of image acquisition would reduce data collecting and model inference while maintaining adequate predictive performance. However, we did not find an optimal time interval for all feeding behavior; instead, the optimal frequency of image acquisition is phenotype-specific. Overall, the best R2 and RMSE for NV, MDV, and FT were achieved using 1 image every 10 s, and for MIBV it was achieved using 1 image every 5 s, and in both cases model inference and data storage could be drastically reduced.

Feeding behaviors collected from automated milk feeders were associated with disease in group-housed dairy calves in the Upper Midwest United States.

Automated milk feeders (AMF) are an attractive option for producers interested in adopting practices that offer greater behavioral freedom for calves and can potentially improve labor management. These feeders give farmers the opportunity to have a more flexible labor schedule and more efficiently feed group-housed calves. However, housing calves in group systems can pose challenges for monitoring calf health on an individual basis, potentially leading to increased morbidity and mortality. Feeding behavior recorded by AMF software could potentially be used as an indicator of disease. Therefore, the objective of this observational study was to investigate the association between feeding behaviors and disease in preweaning group-housed dairy calves fed with AMF. The study was conducted at a dairy farm located in the Upper Midwest United States and included a final data set of 599 Holstein heifer calves. The farm was visited on a weekly basis from May 2018, to May 2019, when calves were visually health scored and AMF data were collected. Calf health scores included calf attitude, ear position, ocular discharge, nasal discharge, hide dirtiness, cough score, and rectal temperatures. Generalized additive mixed models (GAMM) were used to identify associations between feeding behavior and disease. The final quasibinomial GAMM included the fixed (main and interactions) effects of feeding behavior at calf visit-level including milk intake (mL/d), drinking speed (mL/min), visit duration (min), rewarded (with milk being offered) and unrewarded (without milk) visits (number per day), and interval between visits (min), as well as the random effects of calf age in regard to their relationship with calf health status. Total milk intake (mL/d), drinking speed (mL/min), interval between visits (min) to the AMF, calf age (d), and rewarded visits were significantly associated with dairy calf health status. These results indicate that as total milk intake and drinking speed increased, the risk of calves being sick decreased. In contrast, as the interval between visits and age increased, the risk of calves being sick also increased. This study suggests that AMF data may be a useful screening tool for detecting disease in dairy calves. In addition, GAMM were shown to be a simple and flexible approach to modeling calf health status, as they can cope with non-normal data distribution of the response variable, capture nonlinear relationships between explanatory and response variables and accommodate random effects.

Increasing the prepartum dose of rumen-protected choline: Effects on milk production and metabolism in high-producing Holstein dairy cows.

Peripartum rumen-protected choline (RPC) supplementation is beneficial for cow health and production, yet the optimal dose is unknown. In vivo and in vitro supplementation of choline modulates hepatic lipid, glucose, and methyl donor metabolism. The objective of this experiment was to determine the effects of increasing the dose of prepartum RPC supplementation on milk production and blood biomarkers. Pregnant multiparous Holstein cows (n = 116) were randomly assigned to one of 4 prepartum choline treatments that were fed from -21 d relative to calving (DRTC) until calving. From calving until +21 DRTC, cows were fed diets targeting 0 g/d choline ion (control, CTL) or the recommended dose (15 g/d choline ion; RD) of the same RPC product that they were fed prepartum. The resulting treatments targeted: (1) 0 g/d pre- and postpartum [0.0 ± 0.000 choline ion, percent of dry matter (%DM); CTL]; (2) 15 g/d pre- and postpartum of choline ion from an established product (prepartum: 0.10 ± 0.004 choline ion, %DM; postpartum: 0.05 ± 0.004 choline ion, %DM; ReaShure, Balchem Corp.; RPC1RD▸RD); (3) 15 g/d pre- and postpartum of choline ion from a concentrated RPC prototype (prepartum: 0.09 ± 0.004 choline ion, %DM; postpartum: 0.05 ± 0.003 choline ion, %DM; RPC2, Balchem Corp.; RPC2RD▸RD); or (4) 22 g/d prepartum and 15 g/d postpartum from RPC2 [prepartum: 0.13 ± 0.005 choline ion, %DM; postpartum: 0.05 ± 0.003 choline ion, %DM; high prepartum dose (HD), RPC2HD▸RD]. Treatments were mixed into a total mixed ration, and cows had ad libitum access via a roughage intake control system (Hokofarm Group). From calving to +21 DRTC, all cows were fed a common base diet and treatments were mixed into the total mixed ration (supplementation period, SP). Thereafter, all cows were fed a common diet (0 g/d choline ion) until +100 DRTC (postsupplementation period, postSP). Milk yield was recorded daily and composition analyzed weekly. Blood samples were obtained via tail vessel upon enrollment, approximately every other day from -7 to +21 DRTC, and at +56 and +100 DRTC. Feeding any RPC treatment reduced prepartum dry matter intake compared with CTL. During the SP, no evidence for a treatment effect on energy-corrected milk (ECM) yield was found, but during the postSP, RPC1RD▸RD and RPC2RD▸RD treatments tended to increase ECM, protein, and fat yields. During the postSP, the RPC1RD▸RD and RPC2RD▸RD treatments tended to increase, and RPC2HD▸RD increased, the de novo proportion of total milk fatty acids. During the early lactation SP, RPC2HD▸RD tended to increase plasma fatty acids and ß-hydroxybutyrate concentrations, and RPC1RD▸RD and RPC2RD▸RD reduced blood urea nitrogen concentrations compared with CTL. The RPC2HD▸RD treatment reduced early lactation serum lipopolysaccharide binding protein compared with CTL. Overall, peripartum RPC supplementation at the recommended dose tended to increase ECM yield postSP, but no evidence was seen of an additional benefit on milk production with an increased prepartum dose of choline ion. The effects of RPC on metabolic and inflammatory biomarkers support the potential for RPC supplementation to affect transition cow metabolism and health and may support the production gains observed.

Using rumination and activity data for early detection of anaplasmosis disease in dairy heifer calves.

Bovine anaplasmosis causes considerable economic losses in dairy cattle production systems worldwide, ranging from $300 million to $900 million annually. It is commonly detected through rectal temperature, blood smear microscopy, and packed cell volume (PCV). Such methodologies are laborious, costly, and difficult to systematically implement in large-scale operations. The objectives of this study were to evaluate (1) rumination and activity data collected by Hr-Tag sensors (SCR Engineers Ltd.) in heifer calves exposed to anaplasmosis; and (2) the predictive ability of recurrent neural networks in early identification of anaplasmosis. Additionally, we aimed to investigate the effect of time series length before disease diagnosis (5, 7, 10, or 12 consecutive days) on the predictive performance of recurrent neural networks, and how early anaplasmosis disease can be detected in dairy calves (5, 3, and 1 d in advance). Twenty-three heifer calves aged 119 ± 15 (mean ± SD) d and weighing 148 ± 20 kg of body weight were challenged with 2 × 107 erythrocytes infected with UFMG1 strain (GenBank no. EU676176) isolated from Anaplasma marginale. After inoculation, animals were monitored daily by assessing PCV. The lowest PCV value (14 ± 1.8%) and the finding of rickettsia on blood smears were used as a criterion to classify an animal as sick (d 0). Rumination and activity data were collected continuously and automatically at 2-h intervals, using SCR Heatime Hr-Tag collars. Two time series were built including last sequence of -5, -7, -10, or -12 d preceding d 0 or a sequence of 5, 7, 10, or 12 d randomly selected in a window from -50 to -15 d before d 0 to ensure a sequence of days in which PCV was considered normal (32 ± 2.4%). Long short-term memory was used as a predictive approach, and a leave-one-animal-out cross-validation (LOAOCV) was used to assess prediction quality. Anaplasmosis disease reduced 34 and 11% of rumination and activity, respectively. The accuracy, sensitivity, and specificity of long short-term memory in detecting anaplasmosis ranged from 87 to 98%, 83 to 100%, and 83 to 100%, respectively, using rumination data. For activity data, the accuracy, sensitivity, and specificity varied from 70 to 98%, 61 to 100%, and 74 to 100%, respectively. Predictive performance did not improve when combining rumination and activity. The use of longer time-series did not improve the performance of models to predict anaplasmosis. The accuracy and sensitivity in predicting anaplasmosis up to 3 d before clinical diagnosis (d 0) were greater than 80%, confirming the possibility for early identification of anaplasmosis disease. These findings indicate the great potential of wearable sensors in early identification of anaplasmosis diseases. This could positively affect the profitability of dairy farmers and animal welfare.

Genome-wide scan reveals genomic regions and candidate genes underlying direct and maternal effects of preweaning calf mortality in Nellore cattle.

We conducted analysis to estimate genetic parameters and to identify genomic regions and candidate genes affecting direct and maternal effects of preweaning calf mortality (PWM) in Nellore cattle. Phenotypic records of 67,196 animals, and 8443 genotypes for 410,936 SNPs were used. Analysis were performed through the weighted single-step GBLUP approach and considering a threshold animal model via Bayesian Inference. Direct and maternal heritability estimates were of 0.2143 ± 0.0348 and 0.0137 ± 0.0066, respectively. The top 10 genomic regions accounted for 13.61 and 14.23% of the direct and maternal additive genetic variances and harbored a total of 63 and 91 positional candidate genes, respectively. Two overlapping regions on BTA2 were identified for both direct and maternal effects. Candidate genes are involved in biological mechanisms i.e. embryogenesis, immune response, feto-maternal communication, circadian rhythm, hormone alterations, myometrium adaptation, and milk secretion, which are critical for the successful calf growth and survival during preweaning period.

Genome-enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods.

This study aimed to assess the predictive ability of different machine learning (ML) methods for genomic prediction of reproductive traits in Nellore cattle. The studied traits were age at first calving (AFC), scrotal circumference (SC), early pregnancy (EP) and stayability (STAY). The numbers of genotyped animals and SNP markers available were 2342 and 321 419 (AFC), 4671 and 309 486 (SC), 2681 and 319 619 (STAY) and 3356 and 319 108 (EP). Predictive ability of support vector regression (SVR), Bayesian regularized artificial neural network (BRANN) and random forest (RF) were compared with results obtained using parametric models (genomic best linear unbiased predictor, GBLUP, and Bayesian least absolute shrinkage and selection operator, BLASSO). A 5-fold cross-validation strategy was performed and the average prediction accuracy (ACC) and mean squared errors (MSE) were computed. The ACC was defined as the linear correlation between predicted and observed breeding values for categorical traits (EP and STAY) and as the correlation between predicted and observed adjusted phenotypes divided by the square root of the estimated heritability for continuous traits (AFC and SC). The average ACC varied from low to moderate depending on the trait and model under consideration, ranging between 0.56 and 0.63 (AFC), 0.27 and 0.36 (SC), 0.57 and 0.67 (EP), and 0.52 and 0.62 (STAY). SVR provided slightly better accuracies than the parametric models for all traits, increasing the prediction accuracy for AFC to around 6.3 and 4.8% compared with GBLUP and BLASSO respectively. Likewise, there was an increase of 8.3% for SC, 4.5% for EP and 4.8% for STAY, comparing SVR with both GBLUP and BLASSO. In contrast, the RF and BRANN did not present competitive predictive ability compared with the parametric models. The results indicate that SVR is a suitable method for genome-enabled prediction of reproductive traits in Nellore cattle. Further, the optimal kernel bandwidth parameter in the SVR model was trait-dependent, thus, a fine-tuning for this hyper-parameter in the training phase is crucial.

Finishing precocity visual score and genetic associations with growth traits in Angus beef cattle.

Finishing precocity visual score selection was adopted to estimate the time from birth to reach slaughter age. This study estimated (co)variance components and genetic correlations for the finishing precocity score at weaning (WP) and yearling (YP) stages by using daily weight gain (BWG = from birth to weaning; WYG = from weaning to yearling) and speed of weight gain (BWR = from birth to weaning; WYR = from weaning to yearling) as support for a genetic evaluation program for Angus beef cattle. Genetic parameters were estimated using Bayesian inference, considering multi-trait analysis and assuming a nonlinear model for WP and YP and linear model for all other traits. Direct heritability estimates were 0.17 (WP), 0.19 (YP), 0.15 (BWG), 0.16 (WYG), 0.15 (BWR), and 0.16 (WYR). The genetic correlation between the finishing precocity score at two ages (weaning and yearling) was 0.61. Positive and moderate genetic correlations were obtained between WP and BWG (0.47) and WP and BWR (0.46). In contrast, negative and low genetic associations were estimated between WP and yearling growth traits (-0.16, WYG; -0.15, WYR). Genetic correlations between YP and other traits were positive 0.29 (BWG), 0.28 (BWR), 0.48 (WYG), and 0.47 (WYR). The selection response for the finishing precocity score at weaning and yearling ages would be low. Selection to increase WP and YP should result in favorable genetic changes in daily weight gains as a correlated response. Therefore, to obtain animals suited for beef cattle production systems, finishing precocity score and growth traits should be considered as selection criteria.

Chitosan composite microparticles: A promising gastroadhesive system for taxifolin.

Taxifolin possesses gastroprotective property but is characterized by low water solubility, is instabile in alkaline medium, and is degraded by the intestinal bacteria flora. The purpose of the work was therefore to produce a gastroadhesive formulation to prolong taxifolin residence time and release in the stomach. We first demonstrated that taxifolin is stable in simulated gastric fluid with or without pepsin and mucus, and is able to cross pig gastric mucus layer and stomach mucosa. Next, gastromucoadhesive microparticles composed of Syloid® AL-1 mesoporous silica, chitosan and HPMC were produced using spray-drying. Microparticles were characterized by a spherical shape and a mean volume-equivalent diameter around 12 µm. The optimized microparticles were able to release taxifolin and to adhere to pig stomach mucosa for 5 h.

Peel flour of Passiflora edulis Var. Flavicarpa supplementation prevents the insulin resistance and hepatic steatosis induced by low-fructose-diet in young rats.

The increase in fructose consumption in the last decades has an important correlation with the growth of overweight population. Fructose is a monosaccharide found in fruits, vegetables and honey, however, it is widely used in processed food and beverages such as sweeteners. This monosaccharide is metabolized in the liver, so it can produce glucose, lactate, triglycerides, free fatty acids and uric acid, which are responsible for negative effects on the liver and extrahepatic tissues. One effect of the high consumption of fructose is the resistance to Insulin, which appears to be an important issue in the development of metabolic abnormalities observed in animals that were subjected to a high fructose diet. The population and, consequently, the market search for natural sources to manage metabolic abnormalities is increasing, but, adequate scientific proof still is necessary. The Passiflora edulis peel flour (PEPF) is a byproduct of the juice industry, and, represents an important source of fiber and bioactive compounds. The present study investigates the PEPF supplementation (30%) effects on insulin sensitivity, adiposity and metabolic parameters in young rats that were given beverages enriched with 10% of fructose for 8 weeks. Fructose intake induced insulin resistance, increased serum triglycerides levels, growth of fat deposits in the liver and widening of the diameter of adipocytes. In contrast, the group that received PEPF did not present such abnormalities, which could be related to the presence of fiber or bioactive compounds (phenolics compounds, e.g., caffeic acid and isoorientin) in its composition, as identified by analytical methods. Thus, for the first time, it has been demonstrated that PEPF supplementation prevents insulin resistance and hepatic steatosis induced by low-fructose-diet in young rats.

Genome-wide association study for growth traits in Nelore cattle.

The objective of this study was to investigate the association of single nucleotide polymorphisms (SNPs) with birth weight, weight gain from birth to weaning and from weaning to yearling, yearling height and cow weight in Nelore cattle. Data from 5064 animals participating in the DeltaGen and PAINT breeding programs were used. The animals were genotyped with a panel of 777 962 SNPs (Illumina BovineHD BeadChip) and 412 993 SNPs remained after quality control analysis of the genomic data. A genome-wide association study was performed using a single-step methodology. The analyses were processed with the BLUPF90 family of programs. When applied to a genome-wide association studies, the single-step GBLUP methodology is an iterative process that estimates weights for the SNPs. The weights of SNPs were included in all analyses by iteratively applying the single-step GBLUP methodology and repeated twice so that the effect of the SNP and the effect of the animal were recalculated in order to increase the weight of SNPs with large effects and to reduce the weight of those with small effects. The genome-wide association results are reported based on the proportion of variance explained by windows of 50 adjacent SNPs. Considering the two iterations, only windows with an additive genetic variance >1.5% were presented in the results. Associations were observed with birth weight on BTA 14, with weight gain from birth to weaning on BTA 5 and 29, with weight gain from weaning to yearling on BTA 11, and with yearling height on BTA 8, showing the genes TMEM68 (transmembrane protein 8B) associated with birth weight and yearling height, XKR4 (XK, Kell blood group complex subunit-related family, member 4) associated with birth weight, NPR2 (natriuretic peptide receptor B) associated with yearling height, and REG3G (regenerating islet-derived 3-gamma) associated with weight gain from weaning to yearling. These genes play an important role in feed intake, weight gain and the regulation of skeletal growth.

Genetic parameter estimates for carcass traits and visual scores including or not genomic information.

The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix ( and ) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix () or combining the genomic and the numerator relationship matrices (). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix and 0.29, 0.16, and 0.23, respectively, using matrix . The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores.

Genome scan for postmortem carcass traits in Nellore cattle.

Carcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA; chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT; and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes ( and ) involved in the cell cycle biological process which affects many aspects of animal growth and development. The and genes, both from AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (, , , , , and ) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the . There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies.

Xanthan and galactomannan (from M. scabrella) matrix tablets for oral controlled delivery of theophylline.

Directly compressed theophylline tablets, containing commercial xanthan (X) (Keltrol) and a highly hydrophilic galactomannan (G) from the seeds of Mimosa scabrella (a brazilian leguminous tree called bracatinga) as release-controlling agents, were obtained. Gums were used at 4, 8, 12.5 and 25% (w/w), either alone or in mixture (X:G 1:1). During galactomannan extraction process, the biopolymer was dried in a scale up, by vacuum oven (VO) or spray dryer (SD). The in vitro drug release was evaluated at different time intervals during 8 h using apparatus 1 (USP 26) at 100 rpm. The pH of the dissolution medium (1.4) was changed to 4.0 and 6.8 after 2 and 3 h, respectively. Tablets containing G(SD) resulted in more uniform drug release than G(VO) ones, due to their smaller particle size. The drug release decreased with the increase of polymer concentration and all formulations at 25% w/w of gums showed excessive sustained release effect. The matrices made with alone X showed higher drug retention for all concentrations, compared with G matrices that released the drug too fast. The XG matrices were able to produce near zero-order drug release. The XG(SD) 8% tablets provided the required release rate (about 90% at the end of 8 h), with zero-order release kinetics. Tablets containing G(VO) in low concentration showed a complete erosion, while the others demonstrated fast hydration and swelling in contact with the dissolution medium. The release mechanism was a combination of diffusion and relaxation. The relative importance of these two processes varied with matrix composition. The XG(SD) 8% matrix showed higher contribution of polymer relaxation.

Evaluation of xanthan and highly substituted galactomannan from M. scabrella as a sustained release matrix.

A highly substituted galactomannan (G) from Mimosa scabrella Bentham (Man:Gal 1.1:1), isolated from the seeds of a Brazilian leguminous tree and xanthan (X), an exopolysaccharide secreted by Xanthomonas campestris (Keltrol), were evaluated as a hydrophilic matrix system (XG) for controlled release (CR) of diclofenac sodium (DS) in tablets and capsules. The performance of XG (2:1) matrices containing 50 mg (A) or 100 mg (B) of DS was compared with a commercial CR product of DS. The drug release studies were carried out using a dissolution apparatus (paddle method) with gradual increase of pH values, from pH 1.4, to pH 4.0 (after 1 h) and to pH 6.8 (after 2 h). The results suggested the potential of XG systems as release retarding materials, which released 78.6 and 35.1% of drug after 24 h for capsules (A) and tablets (A), respectively. Drug release decreased with the increase of amount of drug and it is dependent of dosage form. Analysis of release data indicate a rather zero-order drug release with the erosion mechanism playing a dominant role.

Xanthan-galactomannan interactions as related to xanthan conformations.

The influence of xanthan conformation on the physicochemical behaviour of their mixtures with galactomannan from Schizolobium parahybae mannose:galactose ratio (M/G=3), was studied by viscoelastic measurements, differential scanning calorimetry (DSC) and chiroptical (circular dichroism) methods. The results suggested a more effective interaction of the galactomannan with disordered xanthan segments, which are more abundant in low salt concentrations but are still present in lower proportion at temperatures lower than the temperature of xanthan conformational transition (Tm). The dependence of ellipticity with temperature in a circular dichroism (CD) spectra suggested an ordering of the xanthan chains induced by galactomannan at the temperature of gel formation (Tg approximately 25 degrees C), under conditions where xanthan alone exhibits a disordered conformation. The lower Tg value found (approximately 25 degrees C) compared with that (60 degrees C) usually described in the literature is certainly related to the M/G ratio and the galactosyl unit distribution along the mannan main chain.

Role of galactomannan composition on the binary gel formation with xanthan.

The influence of the galactomannan characteristic ratios (M/G) on the temperature of gelation (Tg) and the gel strength of mixtures of galactomannan with xanthan is reported. Two galactomannans were investigated: one highly substituted from the seeds of Mimosa scabrella (M/G = 11), and the other, less substituted, from the endosperm of Schizolobium parahybae, with (M/G = 30) [Ganter JLMS, Zawadzki-Baggio SF, Leitner SC, Sierakowski MR, Reicher F. J Carbohydr Chem 1993;12:753]. The xanthan:galactomannan systems (4:2 g l(-1), in 5 mM NaCl) showed a temperature of gel formation (Tg) of 24 degrees C for that of S. parahybae [Bresolin TMB, Milas M, Rinaudo M and Ganter JLMS. Int J Biol Macromol 1998;23:263] and 20 degrees C for the galactomannan of M. scabrella, determined by viscoelastic measurements and microcalorimetry. A Tg of 40-50 degrees C was found by Shatwell et al. [Shatwell KP, Sutherland IW, Ross-Murphy SB, Dea ICM. Carbohydr Polym 1991;14:29] for locust bean gum-LBG (M/G = 43). Lundin and Hermansson [Lundin L, Hermansson AM. Carbohydr Polym 1995;26:129] reported a difference of 13 degrees C for Tg of two LBG samples with M/G = 3 (40 degrees C) and 5 (53 degrees C), in mixtures with xanthan. It appears that the more substituted galactomannans have lower temperatures of gelation in the presence of xanthan. The mechanism of gelation depends also on the M/G ratio. For the lower values it involves only disordered xanthan chains in contrast to M/G ratios higher than 3. In addition, the presence of the galactomannan from M. scabrella increased slightly the temperature of the conformational change (Tm) of xanthan probably due to the ionic strength contribution of proteins (3.9%) present in the galactomannan. On the other hand, the galactomannans from S. parahybae, with 1.5% of proteins and M. scabrella, with 2.4% of protein, did not show this effect, the Tm of xanthan alone or in a mixture being practically unchanged.

Antinociceptive, anti-inflammatory and wound healing features in animal models treated with a semisolid herbal medicine based on Aleurites moluccana L. Willd. Euforbiaceae standardized leaf extract: semisolid herbal.

ETHNOPHARMACOLOGICAL RELEVANCE: Aleurites moluccana L. (Willd) Euforbiaceae is a native tree of Indonesia and India that has become acclimatized and well-adapted to the South and Southwest of Brazil. It is commonly used in traditional medicine to treat pain, fever, inflammation, asthma, hepatitis, headache, gastric ulcer, cuts, skin sores and other ailments. The oral antinociceptive effects of standardized 70:30 (v/v) ethanol:water spray dried extract of A. moluccana leaf, as well as its flavonoids 2"-O-rhamnosylswertisin (I) and swertisin (II), have previously been reported. AIM: The aim of this study was to develop a stable and effective semisolid herbal medicine for topical use in the treatment of pain, inflammation and wound healing, containing 0.5 and 1.0% of standardized dried extract of A. moluccana. MATERIALS AND METHODS: The chemical markers I and II were assayed by HPLC-UV analysis after extraction by matrix solid dispersion phase (MSDP) followed analytical validation as ICH Guidelines. The semisolid preparations of Hostacerin CG(®) vehicle containing 0.5 and 1.0% of dried extract of A. moluccana were submitted to stability studies (180 day of accelerated and long-term studies). The phytomedicine semisolid was analysed in croton oil-induced ear oedema model in mice, in the healing process, using the excisional wound model in rats, and to prevent mechanical sensitization following plantar incision in rats in the postoperative model of pain. RESULTS: The MSDP method showed average recovery of 101.6 and 105.7% for I and II, respectively, with good precision (RSD<2.0%) and selectivity, without interference of the excipients. The formulations were approved in the stability studies, maintaining conformity after 180 day of accelerated and long-term studies, with variation<10% in the analytical parameters. The phytomedicine reduced the ear oedema in 37.6±5.7% and 64.8±6.2%, for 0.5 and 1.0% of dried extract, respectively. The formulation also accelerated the healing process by up to 50.8±4.1% and 46.0±4.0% at 0.5 and 1.0% of extract, respectively, and both amounts were capable of preventing the development of mechanical sensitization following plantar incision in rats. CONCLUSIONS: The MSDP followed by HPLC-UV analytical method was appropriate for the quality control of the topical phytomedicine based on A. moluccana. The formulation developed at 0.5 and 1.0% of A. moluccana dried extract proved to be effective as an analgesic, anti-inflammatory and wound healing in the pre-clinical studies, which is in agreement with the ethnopharmacological data.

Effect of binders on 500mg metformin hydrochloride tablets produced by wet granulation

Metformin hydrochloride (MH) is an oral hypoglycemic agent and a high-dose drug that has poor flow and compression properties. In this study, the feasibility of developing adequate, low cost 500mg tablets of metformin hydrochloride by wet granulation was tested with several binders (Starch / PVP K30®; Starch1500® /PVP K30®, PVP K30® and PVP K90®) in a simple tablet press of the type used in small pharmaceutical laboratories. The drug powder was tested for ability to flow, by determining Carr?s Index (CI) and the Hausner ratio (HR). Differential scanning calorimetry and thermogravimetric analysis were carried out on isolated MH and 1:1 (w/w) binary mixtures with the excipients. The size distribution, friability, flow properties and drug content of the granules were analyzed, as were the hardness, friability, disintegration, dissolution and uniformity of the dosage form. The drug powder showed CI > 22% and HR > 1.25, characteristic of a poor flow powder, and no significant incompatibilities with the excipients. All the granules showed adequate flow properties and were suitable for pressing into tablets, all of which complied with pharmacopeial specifications. The starch /PVP K30® and starch 1500®/PVP K30® mixtures were best for producing 500 mg MH tablets.

Cloridrato de metformina é um fármaco hipoglicemiante oral que apresenta propriedades pobres de fluxo e compressibilidade. Este trabalho teve como objetivo o desenvolvimento de comprimidos de baixo custo,após granulação por via úmida, contendo 500 mg de cloridrato de metformina e diferentes aglutinantes (F1-amido / PVP K30®; F2- Starch 1500® / PVP K30®, F3-PVP K30®, F4- PVP K90®) em máquinas de compressão de baixo desempenho usadas em laboratórios farmacêuticos de pequeno porte. As propriedades defluxo do fármaco foram analisadas através do índice de Carr (IC) e fator de Hausner (FH). Cloridrato de metformina e suas misturas binárias com os excipientes na relação 1:1 (m/m) foram analisadas por calorimetria diferencial por varredura e análise termogravimétrica. Os granulados foram analisados quanto a distribuição granulométrica, friabilidade, propriedades de fluxo e teor e os comprimidos em relação à dureza, friabilidade, desintegração, dissolução e uniformidade de conteúdo.O cloridrato de metformina apresentou IC > 22% e FH> 1,25, característicos de fluxo pobre e não apresentou incompatibilidades com os outros excipientes. Todos os granulados demonstraram adequadas propriedades de fluxo e facilidade no processo de compressão. Os comprimidos apresentaram conformidade com as especificações farmacopeicas. As misturas amido / PVPK30® e Starch 1500® / PVP K30® foram mais adequadas para produzir comprimidos de cloridrato de metformina 500 mg.

Pharmaceutical equivalence of metformin tablets with various binders

Metformin hydrochloride is a high-dose drug widely used as an oral anti-hyperglycemic agent. As it is highly crystalline and has poor compaction properties, it is difficult to form tablets by direct compression. The aim of this study was to develop adequate metformin tablets, pharmaceutically equivalent to the reference product, Glucophage® (marketed as Glifage® in Brazil). Metformin 500mg tablets were produced by wet granulation with various binders (A equal starch, B equal starch 1500®, C equal PVP K30®, D equal PVP K90®). The tablets were analyzed for their hardness, friability, disintegration, dissolution, content uniformity and dissolution profile (basket apparatus at 50 rpm, pH 6.8 phosphate buffer). The 4 formulations, F1 (5% A and 5% C), F2 (5% Band 5% C), F3 (10% C) and F4 (5% D), demonstratedadequate uniformity of content, hardness, friability, disintegration and total drug dissolution after 30minutes (F1, F2 and F4), and after 60 minutes (F3). The drug release time profiles fitted a Higuchi model (F1, F2and F3), similarly to the pharmaceutical reference, or a zero order model (F4). The dissolution efficiency for all the formulations was 75%, except for F3 (45%). F1 andF2 were thus equivalent to Glifage®.