Leukocyte and platelet rich fibrin in the management of medication-related osteonecrosis of the jaw: A systematic review and meta-analysis.

BACKGROUND: Osteonecrosis of the jaw (ONJ) has a frequent adverse effect after the administration of nitrogenous bisphosphonates, as non-nitrogenous bisphosphonates are metabolized more rapidly and would produce this effect to a lesser extent. The objective of this study is to analyze the results obtained in the literature with the use of L-PRF in the treatment of ONJ through a systematic review and meta-analysis. MATERIAL AND METHODS: Medline (via PubMed), Cochrane, Web of Science and Grey Literature Database was screened from which 10 were selected. RESULTS: In the meta-analysis with full resolution, combining the use of L-PRF in the treatment of ONJ, a weighted proportion (PP) of 94.3% of complete resolution is obtained (95% CI: 91.2-97.4, p<0.001), with a low degree of heterogeneity, statistically significant (I2 = 29.02%; p<0.001). When analyzing the non-resolution data, a weighted proportion (PP) of 7.7% (95% CI: 3.6-11.9; p<0.001) was obtained with moderate heterogeneity (I2: 41.87%; p=0.112). In the meta-regression, no significant correlation was found between complete resolution and year of publication (intercept = 2.88, p=0.829). In consistency analysis no major changes in PP are identified when any of the studies are eliminated, demonstrating a high reliability in the combined results. CONCLUSION: L-PRF alone or in combination with other therapies in treatment of ONJ achieved high percentages of complete lesion resolution (94.3%). In studies where L-PRF is combined with other therapies, and where the effectiveness of the other therapy alone is analyzed, L-PRF has been shown higher percentages of resolution.

Genotype by environment interaction for Holstein cattle populations using autoregressive and within- and across-country multi-trait reaction norms test-day models.

The progenies of international bulls in diverse climatic conditions and management levels may lead to different expressions of their genetic potential resulting in a re-ranking of these bulls. Therefore, evaluate the presence of genotype by environment interaction (G×E) within and across countries is important to guide the decision-making on alternative selection strategies. Thus, a two-step reaction norm (RN) approach was used to investigate the presence of G×E in Portuguese and Brazilian Holstein cattle. In step 1, we performed a within-country genetic evaluation using an autoregressive model to obtain precorrected phenotypes and environmental gradients (herd test-day solutions, HTD levels). In step 2, the precorrected phenotypes were considered as two distinct traits in a bi-trait RN model to estimate variance components across HTD levels, genetic correlation between HTD levels in Portugal and Brazil, and RN of the estimated breeding values. Additionally, the genetic correlation between countries using a bi-trait random regression (RR) sire model was obtained. In step 1, genetic additive variance for milk yield (MY) in Portugal was 14.1% higher than in Brazil. For somatic cell score (SCS), the genetic additive variance in Portugal was 12.7% lower than in Brazil. Although similar heritability estimates for SCS were observed in both countries, MY heritabilities were 0.31 for Portugal and 0.23 for Brazil. Genetic correlations (SD) between both countries obtained using RR sire model were 0.78 (0.051) for MY and 0.75 (0.062) for SCS. In step 2, MY genetic correlations among HTD levels within countries were higher than 0.94 for Portugal and 0.98 for Brazil. Somatic cell score genetic correlations among HTD levels ranged from 0.70 to 0.99 for Portugal and from 0.84 to 0.99 for Brazil. The average (SD) of genetic correlation estimates between Portuguese and Brazilian HTD levels were 0.74 (0.009) for MY and 0.57 (0.060) for SCS. These results suggest the presence of G×E for MY and SCS of Holstein cattle between both countries. Although there was no indication of G×E between Brazilian herd environments, the low genetic correlation for SCS indicates potential re-ranking of bulls between extreme environmental gradient in Portugal. Overall, the results of this study evidence the importance of national and international genetic evaluation systems to assist dairy farmers in the selection of the best genotypes to obtain the expected returns from investments in imported semen and to realize genetic progress in dairy populations under local environmental conditions.

Exploring the use of residual variance for uniformity of body weight in meat quail lines using Bayesian inference.

1. Uniformity in animal products is an important aspect of the production system. Several studies have reported estimates of genetics on residual variance in different species, indicating that it could be exploited to improve uniformity by selection. Nevertheless, there are no reports about the possibilities of such a selection strategy in meat quail.2. Records of hatching weight (HW) and body weight at 42 days (W42) of female and male birds from two meat quail lines (UFV1 and UFV2) were analysed. A three-step genetic evaluation was used to investigate the effect of genetic variation on residual variance of HW and W42 in both lines. In Step 1, a single-trait model was fitted to the data. In Step 2, log-transformed squared estimated residuals (ln(ê2)) were evaluated for these traits. In Step 3, a multi-trait analysis was performed to estimate the genetic correlation between the additive genetic effects for HW, W42, and their respective ln(ê2).3. The heritability estimates ranged from 0.12 to 0.23 for HW and from 0.22 to 0.35 for W42. The estimated heritabilities for the residual part were low and ranged from 0.0003 to 0.02 for both traits, and the genetic coefficient of variation residual variance estimates ranged from 0.31 to 0.42 for HW and from 0.09 to 0.25 for W42. Genetic correlations between the means (HW and W42) and ln(ê2) values were both positive and did not differ from zero, indicating no association between mean and ln(ê2).4. In conclusion, the uniformity of HW and W42 could be improved by selecting for lower residual variance in both meat quail lines, but the accuracy of selection may be low due to low heritability for uniformity, mainly for W42.

Predicting Rice Stem Stink Bug Population Dynamics Based on GAMLSS Models.

The rice stem stink bug, Tibraca limbativentris Stål (Hemiptera: Pentatomidae), is one of the most harmful insects for Brazilian rice fields. Aiming to define the most appropriate time and place for pest management measures in commercial paddy fields, we adjusted regression models (Poisson, Zero Inflated Poisson, reparametrized Zero Inflated Poisson, Negative Binomial and Zero Inflated Negative Binomial) for modeling the population variation of T. limbativentris along the phenological cycle of the flooded rice cultivation. We hypothesize that the rice stem stink bug population's size is influenced by the rice cycle (time) and geographical positions within the crop. It was possible to predict the occurrence of the rice stem stink bug in the commercial flooded rice crop. The population of the rice stem stink bug increased significantly with the time or phenological evolution of rice. Our results indicated that the start of T. limbativentris monitoring should occur up to 45 d After Plant Emergence (DAE), from the regions along the edges of the rice paddies, which are the points of entry and higher concentration of the insect. In addition, 45 and 60 DAE were considered the crucial times for T. limbativentris control decision making in flooded rice paddies.

Laminite endocrinopática em equinos com síndrome metabólica: características clínicas, tratamento e evolução em três pacientes ˗ relato de caso / [Endocrinopathic laminitis in horses with metabolic syndrome: clinical characteristics, treatment and evolution in three patients ˗ case report]

Laminite endocrinopática designa os casos de laminite cuja etiologia está associada a uma endocrinopatia. Cavalos com síndrome metabólica equina (SME) apresentam adiposidade regional e obesidade. Existe uma correlação positiva entre obesidade e resistência à insulina. Este relato descreve três casos de laminite endocrinopática em cavalos com SME. Os pacientes apresentaram escore de condição corporal (ECC) variando de 8 a 9 (escala de 1 a 9), sensibilidade ao teste de pinçamento do casco e claudicação de grau 3 ou 4 (escala de 1 a 4). Não havia histórico de cólica recente, trauma ou excesso de exercício. O tratamento incluiu medicação anti-inflamatória não esteroidal, repouso na baia, restrição energética para perda de peso, revestimento e bandagem dos membros, conforme a necessidade de cada paciente. A restrição alimentar ajudou no tratamento da SME e reduziu o ECC. Tratamento medicamentoso, casqueamento e bandagem diminuíram o grau de claudicação. Conclui-se que o tratamento anti-inflamatório não esteroidal, a restrição energética, o repouso em baia, o casqueamento e a bandagem do casco são eficazes no tratamento da laminite endocrinopática em cavalos com síndrome metabólica equina.(AU)

Endocrinopathic laminitis refers to cases of laminitis whose etiology is associated with an endocrinopathy. Horses with Equine Metabolic Syndrome (EMS) have regional adiposity and obesity. There is a positive correlation between obesity and insulin resistance. This report describes three cases of endocrinopathic laminitis in horses with EMS. Patients had body condition score (BCS) ranging from 8 to 9 (scale from 1 to 9), sensitivity to the hoof clamping test and claudication grade 3 or 4 (scale from 1 to 4). There was no history of recent colic, trauma or over exercise. Treatment included non-steroidal anti-inflammatory medication, stall rest, energy restriction for weight loss, hoofing and hoof bandage as needed by each patient. Dietary restriction helped in the treatment of EMS and reduced BCS. Drug treatment, hoofing and hoof bandage decreased the degree of lameness. It is concluded that non-steroidal anti-inflammatory treatment, energy restriction, stall rest, hoofing and hoof bandage are effective in the treatment of endocrinopathic laminitis in horses with equine metabolic syndrome.(AU)

Genomic analyses for predicted milk fatty acid composition throughout lactation in North American Holstein cattle.

Milk fat composition has important implications in the nutritional and processing properties of milk. Additionally, milk fat composition is associated with cow physiological and health status. The main objectives of this study were (1) to estimate genetic parameters for 5 milk fatty acid (FA) groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted from milk infrared spectra using a large data set; (2) to predict genomic breeding values using a longitudinal single-step genomic BLUP approach; and (3) to conduct a single-step GWAS aiming to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA, and consequently, to understand the underlying biology of these traits. We used 629,769 test-day records of 201,465 first-parity Holstein cows from 6,105 herds. A total of 8,865 genotyped (Illumina BovineSNP50K BeadChip, Illumina, San Diego, CA) animals were considered for the genomic analyses. The average daily heritability ranged from 0.24 (unsaturated FA) to 0.47 (medium-chain and saturated FA). The reliability of the genomic breeding values ranged from 0.56 (long-chain fatty acid) to 0.74 (medium-chain fatty acid) when using the default τ and ω scaling parameters, whereas it ranged from 0.58 (long-chain fatty acid) to 0.73 (short-chain fatty acid) when using the optimal τ and ω values (i.e., τ = 1.5 and ω = 0.6), as defined in a previous study in the same population. Relevant chromosomal regions were identified in Bos taurus autosomes 5 and 14. The proportion of the variance explained by 20 adjacent single nucleotide polymorphisms ranged from 0.71% (saturated FA) to 15.12% (long-chain FA). Important candidate genes and pathways were also identified. In summary, our results contribute to a better understanding of the genetic architecture of predicted milk FA in dairy cattle and reinforce the relevance of using genomic information for genetic analyses of these traits.

Short communication: Time-dependent genetic parameters and single-step genome-wide association analyses for predicted milk fatty acid composition in Ayrshire and Jersey dairy cattle.

Milk fat content and fatty acid (FA) composition have great economic value to the dairy industry as they are directly associated with taste and chemical-physical characteristics of milk and dairy products. In addition, consumers' choices are not only based on the nutritional aspects of food, but also on products known to promote better health. Milk FA composition is also related to the metabolic status and physiological stages of cows and thus can also be used as indicator for other novel traits of interest (e.g., metabolic diseases and methane yield). Genetic selection is a promising alternative to manipulate milk FA composition. In this study, we aimed to (1) estimate time-dependent genetic parameters for 5 milk FA groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted based on milk mid-infrared spectroscopy, for Canadian Ayrshire and Jersey breeds, and (2) conduct a time-dependent, single-step genome-wide association study to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA. We analyzed 31,709 test-day records of 9,648 Ayrshire cows from 268 herds, and 34,341 records of 11,479 Jersey cows from 883 herds. The genomic database contained a total of 2,330 Ayrshire and 1,019 Jersey animals. The average daily heritability ranged from 0.18 (long-chain FA) to 0.34 (medium-chain FA) in Ayrshire, and from 0.25 (long-chain and unsaturated FA) to 0.52 (medium-chain and saturated FA) in Jersey. Important genomic regions were identified in Bos taurus autosomes BTA3, BTA5, BTA12, BTA13, BTA14, BTA16, BTA18, BTA20, and BTA21. The proportion of the variance explained by 20 adjacent SNP ranged from 0.71% (saturated FA) to 1.11% (long-chain FA) in Ayrshire, and from 0.70% (unsaturated FA) to 3.09% (medium-chain FA) in Jersey cattle. Important candidate genes and pathways were also identified, such as the PTK2 and TRAPPC9 genes, associated with milk fat percentage, and HMGCS, FGF10, and C6 genes, associated with fertility traits and immune response. Our findings on the genetic parameters and candidate genes contribute to a better understanding of the genetic architecture of milk FA composition in Ayrshire and Jersey dairy cattle.

Short communication: Genetic parameter estimates for caprine arthritis encephalitis in dairy goats.

Caprine arthritis encephalitis (CAE) is a chronic disease caused by a retrovirus from the Lentivirus genus. No effective vaccines or treatments exist, and therefore genetic selection for CAE resistance might be a feasible alternative. To our best knowledge, no other studies have investigated the genetic architecture of CAE resistance in dairy goats. In this context, this study was designed to estimate genetic parameters for CAE infection in Alpine and Saanen goats using a Bayesian threshold model. A total of 542 adult goats (and >3-generation pedigree), which were group-housed in a population with high CAE prevalence, were tested based on a serological infection assessment test (negative = 1 or positive = 2) and used for this study. Genetic parameters were estimated using the BLUPF90 family programs. There was considerable genetic variability for CAE resistance, and pedigree-based heritability was significantly different from zero (0.026 < heritability < 0.128). Our findings indicate that the prevalence of CAE in goat herds can be reduced or eliminated through direct genetic selection for CAE resistance in addition to proper management strategies.

Energy and protein requirements of Holstein × Gyr crossbred heifers.

Nutrient requirements in cattle are dependent on physiological stage, breed and environmental conditions. In Holstein × Gyr crossbred dairy heifers, the lack of data remains a limiting factor for estimating energy and protein requirements. Thus, we aimed to estimate the energy and protein requirements of Holstein × Gyr crossbred heifers raised under tropical conditions. Twenty-two crossbred (½ Holstein × ½ Gyr) heifers with an average initial BW of 102.2 ± 3.4 kg and 3 to 4 months of age were used. To estimate requirements, the comparative slaughter technique was used: four animals were assigned to the reference group, slaughtered at the beginning of the experiment to estimate the initial empty BW (EBW) and composition of the animals that remained in the experiment. The remaining animals were randomized into three treatments based on targeted rates of BW gain: high (1.0 kg/day), low (0.5 kg/day) and close to maintenance (0.1 kg/day). At the end of the experiment, all animals were slaughtered to determine EBW, empty body gain (EBG) and body energy and protein contents. The linear regression parameters were estimated using PROC MIXED of SAS (version 9.4). Estimates of the parameters of non-linear regressions were adjusted through PROC NLIN of SAS using the Gauss-Newton method for parameter fit. The net requirements of energy for maintenance (NEm) and metabolizable energy for maintenance (MEm) were 0.303 and 0.469 MJ/EBW0.75 per day, respectively. The efficiency of use of MEm was 64.5%. The estimated equation to predict the net energy requirement for gain (NEg) was: NEg (MJ/day) = 0.299 × EBW0.75 × EBG0.601. The efficiency of use of ME for gain (kg) was 30.7%. The requirement of metabolizable protein for maintenance was 3.52 g/EBW0.75 per day. The equation to predict net protein requirement for gain (NPg) was: NPg (g/day) = 243.65 × EBW-0.091 × EBG. The efficiency of use of metabolizable protein for gain (k) was 50.8%. We observed noteworthy differences when comparing to ME and protein requirements of Holstein × Gyr crossbred heifers with other systems. In addition, we also observed differences in estimates for NEm, NEg, NPg, kg and k. Therefore, we propose that the equations generated in the present study should be used to estimate energy and protein requirements for Holstein × Gyr crossbred dairy heifers raised in tropical conditions in the post-weaning phase up to 185 kg of BW.

Genetic evaluation for latent variables derived from factor analysis in broilers.

1. The aim of this study was to investigate the associations between several carcass, performance and meat quality traits in broilers through factor analysis and use the latent variables (i.e. factors) as pseudo-phenotypes in genetic evaluations.2. Factors were extracted using the principal components method and varimax rotation algorithm. Genetic parameters were estimated via Bayesian inference under a multiple-trait animal model.3. All factors taken together explained 71% of the original variance of the data. The first factor, denominated as 'weight', was associated with carcass and body weight traits; and the second factor, defined as 'tenderness', represented traits related to water-holding capacity and shear force. The third factor, 'colour', was associated with traits related to meat colour, whereas the fourth, referenced as 'viscera', was related to heart, liver and abdominal fat.4. The four biological factors presented moderate to high heritability (ranging from 0.35 to 0.75), which may confer genetic gains in this population.5. In conclusion, it seems possible to reduce the number of traits in the genetic evaluation of broilers using latent variables derived from factor analysis.

Short communication: Molecular characterization and antimicrobial resistance of pathogenic Escherichia coli isolated from raw milk and Minas Frescal cheeses in Brazil.

The aim of this study was to quantify, identify, evaluate antimicrobial resistance, and characterize the virulence factors of enteropathogenic (EPEC), Shiga-toxigenic (STEC), and enterohemorrhagic (EHEC) Escherichia coli in raw milk (RM) and legal (LMFC) and illegal (IMFC) Minas Frescal cheeses in southern and northeast Brazil. Illegal cheeses are those made without official inspection service or sanitary surveillance. We evaluated samples of RM produced in Paraná (southern) and Maranhão (northeast) States, LMFC produced using pasteurized milk in inspected industries, and IMFC potentially produced with raw milk. Mean total coliform counts were 8.4 × 104 cfu/mL for RM, 1.4 × 107 cfu/mL for LMFC, and 2.9 × 107 cfu/mL for IMFC. Mean E. coli counts were 2.4 × 103 cfu/mL for RM, 1.9 × 102 cfu/mL for LMFC, and 1.1 × 105 cfu/mL for IMFC. Among the 205 E. coli isolates from RM, 9.75% were identified as EPEC, mainly (90%) in samples from Paraná. Of the total isolates from the cheese samples, 97.4% (n = 111) came from IMFC, of which 1.8 and 2.7% were identified as EPEC and STEC, respectively; no EHEC was detected. The phylogenetic group A (60%) and typical EPEC (68%) predominated, which confirms the possible human origin of pathogenic isolates in RM and IMFC. Of these, 50% were resistant to at least one antibiotic, and streptomycin was the antimicrobial with the highest number (8) of EPEC and STEC resistant isolates. This study reports the first isolation of serogroup O28ac in Brazilian milk. We found no predominance of a specific serogroup of EPEC or STEC in milk or cheese or clonal isolates in the same sample, indicating different origins of the contamination in these products, presumably mostly related to poor hygienic handling.

Single-step genome-wide association for longitudinal traits of Canadian Ayrshire, Holstein, and Jersey dairy cattle.

Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression.

Genome-wide association for milk production traits and somatic cell score in different lactation stages of Ayrshire, Holstein, and Jersey dairy cattle.

We performed genome-wide association analyses for milk, fat, and protein yields and somatic cell score based on lactation stages in the first 3 parities of Canadian Ayrshire, Holstein, and Jersey cattle. The genome-wide association analyses were performed considering 3 different lactation stages for each trait and parity: from 5 to 95, from 96 to 215, and from 216 to 305 d in milk. Effects of single nucleotide polymorphisms (SNP) for each lactation stage, trait, parity, and breed were estimated by back-solving the direct breeding values estimated using the genomic best linear unbiased predictor and single-trait random regression test-day models containing only the fixed population average curve and the random genomic curves. To identify important genomic regions related to the analyzed lactation stages, traits, parities and breeds, moving windows (SNP-by-SNP) of 20 adjacent SNP explaining more than 0.30% of total genetic variance were selected for further analyses of candidate genes. A lower number of genomic windows with a relatively higher proportion of the explained genetic variance was found in the Holstein breed compared with the Ayrshire and Jersey breeds. Genomic regions associated with the analyzed traits were located on 12, 8, and 15 chromosomes for the Ayrshire, Holstein, and Jersey breeds, respectively. Especially for the Holstein breed, many of the identified candidate genes supported previous reports in the literature. However, well-known genes with major effects on milk production traits (e.g., diacylglycerol O-acyltransferase 1) showed contrasting results among lactation stages, traits, and parities of different breeds. Therefore, our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the analyzed traits across breeds, parities, and lactation stages. Further functional studies are needed to validate our findings in independent populations.

Lipolytic Enzymes with Hydrolytic and Esterification Activities Produced by Filamentous Fungi Isolated from Decomposition Leaves in an Aquatic Environment.

Microbial lipases are prominent biocatalysts able to catalyze a wide variety of reactions in aqueous and nonaqueous media. In this work, filamentous fungi isolated from leaves decomposed in an aquatic environment were screened for lipase production with hydrolytic activity and esterification. Agar plates with Tween 20 and Rhodamine B were used for selection, while submerged cultures with olive oil were subsequently used to select 38 filamentous fungi. Trichoderma harzianum, Fusarium solani, Trichoderma harzianum F5, and Penicillium sp. F36 were grown in six different culture media. F. solani presented the highest lipase production (2.37 U/mL) with esterification activity of 0.07 U/mL using medium composed of (g.L-1) KH2PO4 1.00, MgSO4 H2O 1.123, and CuSO4 0.06. Supplementation of this culture medium with organic nitrogen sources increased lipase production by 461.3% using tryptone and by 419.4% using yeast extract. Among the vegetable oils from the Amazon region, degummed cotton oil induced lipase production up to 8.14 U/mL. The lipase produced by F. solani F61 has great potential to application in conventional processes and biodiesel production by transesterification of vegetable oils, as well as food industries in the production of fatty acid esters by hydrolysis and esterification.

Invited review: Advances and applications of random regression models: From quantitative genetics to genomics.

An important goal in animal breeding is to improve longitudinal traits; that is, traits recorded multiple times during an individual's lifetime or physiological cycle. Longitudinal traits were first genetically evaluated based on accumulated phenotypic expression, phenotypic expression at specific time points, or repeatability models. Until now, the genetic evaluation of longitudinal traits has mainly focused on using random regression models (RRM). Random regression models enable fitting random genetic and environmental effects over time, which results in higher accuracy of estimated breeding values compared with other statistical approaches. In addition, RRM provide insights about temporal variation of biological processes and the physiological implications underlying the studied traits. Despite the fact that genomic information has substantially contributed to increase the rates of genetic progress for a variety of economically important traits in several livestock species, less attention has been given to longitudinal traits in recent years. However, including genomic information to evaluate longitudinal traits using RRM is a feasible alternative to yield more accurate selection and culling decisions, because selection of young animals may be based on the complete pattern of the production curve with higher accuracy compared with the use of traditional parent average (i.e., without genomic information). Moreover, RRM can be used to estimate SNP effects over time in genome-wide association studies. Thus, by analyzing marker associations over time, regions with higher effects at specific points in time are more likely to be identified. Despite the advances in applications of RRM in genetic evaluations, more research is needed to successfully combine RRM and genomic information. Future research should provide a better understanding of the temporal variation of biological processes and their physiological implications underlying the longitudinal traits.

Autoregressive single-step test-day model for genomic evaluations of Portuguese Holstein cattle.

The multiple-lactation autoregressive test-day (AR) model is the adopted model for the national genetic evaluation of dairy cattle in Portugal. Under this model, animals' permanent environment effects are assumed to follow a first-order autoregressive process over the long (auto-correlations between parities) and short (auto-correlations between test-days within lactation) terms. Given the relevance of genomic prediction in dairy cattle, it is essential to include marker information in national genetic evaluations. In this context, we aimed to evaluate the feasibility of applying the single-step genomic (G)BLUP to analyze milk yield using the AR model in Portuguese Holstein cattle. In total, 11,434,294 test-day records from the first 3 lactations collected between 1994 and 2017 and 1,071 genotyped bulls were used in this study. Rank correlations and differences in reliability among bulls were used to compare the performance of the traditional (A-AR) and single-step (H-AR) models. These 2 modeling approaches were also applied to reduced data sets with records truncated after 2012 (deleting daughters of tested bulls) to evaluate the predictive ability of the H-AR. Validation scenarios were proposed, taking into account young and proven bulls. Average EBV reliabilities, empirical reliabilities, and genetic trends predicted from the complete and reduced data sets were used to validate the genomic evaluation. Average EBV reliabilities for H-AR (A-AR) using the complete data set were 0.52 (0.16) and 0.72 (0.62) for genotyped bulls with no daughters and bulls with 1 to 9 daughters, respectively. These results showed an increase in EBV reliabilities of 0.10 to 0.36 when genomic information was included, corresponding to a reduction of up to 43% in prediction error variance. Considering the 3 validation scenarios, the inclusion of genomic information improved the average EBV reliability in the reduced data set, which ranged, on average, from 0.16 to 0.26, indicating an increase in the predictive ability. Similarly, empirical reliability increased by up to 0.08 between validation tests. The H-AR outperformed A-AR in terms of genetic trends when unproven genotyped bulls were included. The results suggest that the single-step GBLUP AR model is feasible and may be applied to national Portuguese genetic evaluations for milk yield.

In vitro anthelmintic activity of Siparuna guianensis extract and essential oil against Strongyloides venezuelensis.

New therapeutic approaches are necessary to control strongyloidiasis due to the side effects of, and resistance to, currently available drugs thiabendazole, albendazole, and ivermectin. This study examined the anthelmintic properties of extracts and isolated compounds from Siparuna guianensis against Strongyloides venezuelensis eggs and larvae, using the egg hatching test (EHT) and larval motility test (LMT). Albendazole (0.025 mg/ml) and ivermectin (0.316 mg/ml) were used as the positive controls for the EHT and LMT assays, respectively. Strongyloides venezuelensis eggs or larvae (±50 specimens) were treated with ethanol extract (0.05-1.0 mg/ml), ethyl acetate and aqueous fractions (0.05-0.8 mg/ml), essential oil (0.2-1.0 mg/ml) and α-bisabolol (0.2-1.0 mg/ml) from S. guianensis, and analysed by optical microscopy after 48 h (EHT), or after 24, 48 and 72 h (LMT). All the tested compounds exhibited ovicidal activity equivalent to the positive control and changed the morphology of the eggs. The S. guianensis ethanol extract and aqueous fraction were as effective as the positive control. Phytochemical analysis of the ethanol extract and fractions revealed the presence of phenolic compounds, tannins and flavonoids. Therefore, S. guianensis is effective against S. venezuelensis eggs and larvae in vitro, and can be considered as a potential alternative treatment for strongyloidiasis.

Genome-wide association studies pathway-based meta-analysis for residual feed intake in beef cattle.

Genome-wide association studies (GWASes) have been performed to search for genomic regions associated with residual feed intake (RFI); however inconsistent results have been obtained. A meta-analysis may improve these results by decreasing the false-positive rate. Additionally, pathway analysis is a powerful tool that complements GWASes, as it enables identification of gene sets involved in the same pathway that explain the studied phenotype. Because there are no reports on GWAS pathways-based meta-analyses for RFI in beef cattle, we used several GWAS results to search for significant pathways that may explain the genetic mechanism underlying this trait. We used an efficient permutation hypothesis test that takes into account the linkage disequilibrium patterns between SNPs and the functional feasibility of the identified genes over the whole genome. One significant pathway (valine, leucine and isoleucine degradation) related to RFI was found. The three genes in this pathway-methylcrotonoyl-CoA carboxylase 1 (MCCC1), aldehyde oxidase 1 (AOX1) and propionyl-CoA carboxylase alpha subunit (PCCA)-were found in three different studies. This same pathway was also reported in a transcriptome analysis from two cattle populations divergently selected for high and low RFI. We conclude that a GWAS pathway-based meta-analysis can be an appropriate method to uncover biological insights into RFI by combining useful information from different studies.

Application of single-step genomic evaluation using multiple-trait random regression test-day models in dairy cattle.

Test-day traits are important for genetic evaluation in dairy cattle and are better modeled by multiple-trait random regression models (RRM). The reliability and bias of genomic estimated breeding values (GEBV) predicted using multiple-trait RRM via single-step genomic best linear unbiased prediction (ssGBLUP) were investigated in the 3 major dairy cattle breeds in Canada (i.e., Ayrshire, Holstein, and Jersey). Individual additive genomic random regression coefficients for the test-day traits were predicted using 2 multiple-trait RRM: (1) one for milk, fat, and protein yields in the first, second, and third lactations, and (2) one for somatic cell score in the first, second, and third lactations. The predicted coefficients were used to derive GEBV for each lactation day and, subsequently, the daily GEBV were compared with traditional daily parent averages obtained by BLUP. To ensure compatibility between pedigree and genomic information for genotyped animals, different scaling factors for combining the inverse of genomic (G-1) and pedigree (A-122) relationship matrices were tested. In addition, the inclusion of only genotypes from animals with accurate breeding values (defined in preliminary analysis) was compared with the inclusion of all available genotypes in the analyzes. The ssGBLUP model led to considerably larger validation reliabilities than the BLUP model without genomic information. In general, scaling factors used to combine the G-1 and A-122 matrices had small influence on the validation reliabilities. However, a greater effect was observed in the inflation of GEBV. Less inflated GEBV were obtained by the ssGBLUP compared with the parent average from traditional BLUP when using optimal scaling factors to combine the G-1 and A-122 matrices. Similar results were observed when including either all available genotypes or only genotypes from animals with accurate breeding values. These findings indicate that ssGBLUP using multiple-trait RRM increases reliability and reduces bias of breeding values of young animals when compared with parent average from traditional BLUP in the Canadian Ayrshire, Holstein, and Jersey breeds.

Genomic prediction of lactation curves for milk, fat, protein, and somatic cell score in Holstein cattle.

Application of random regression models (RRM) in a 2-step genomic prediction might be a feasible way to select young animals based on the complete pattern of the lactation curve. In this context, the prediction reliability and bias of genomic estimated breeding value (GEBV) for milk, fat, and protein yields and somatic cell score over days in milk (DIM) using a 2-step genomic approach were investigated. In addition, the effect of including cows in the training and validation populations was investigated. Estimated breeding values for each DIM (from 5 to 305 d) from the first 3 lactations of Holstein animals were deregressed and used as pseudophenotypes in the second step. Individual additive genomic random regression coefficients for each trait were predicted using RRM and genomic best linear unbiased prediction and further used to derive GEBV for each DIM. Theoretical reliabilities of GEBV obtained by the RRM were slightly higher than theoretical reliabilities obtained by the accumulated yield up to 305 d (P305). However, validation reliabilities estimated for GEBV using P305 were higher than for GEBV using RRM. For all traits, higher theoretical and validation reliabilities were estimated when incorporating genomic information. Less biased GEBV estimates were found when using RRM compared with P305, and different validation reliability and bias patterns for GEBV over time were observed across traits and lactations. Including cows in the training population increased the theoretical reliabilities and bias of GEBV; nonetheless, the inclusion of cows in the validation population does not seem to affect the regression coefficients and the theoretical reliabilities. In summary, the use of RRM in 2-step genomic prediction produced fairly accurate GEBV over the entire lactation curve for all analyzed traits. Thus, selecting young animals based on the pattern of lactation curves seems to be a feasible alternative in genomic selection of Holstein cattle for milk production traits.