The objective of this study was to develop statistical models to predict empty body weight (EBW) by body weight (BW), testing the influence of sex (females, intact males or castrated males), type of diet (suckling or postweaning), and genotype (Saanen, ½ Boer × ½ Saanen, ¾ Boer × ¼ Saanen, and Indigenous goats). Individual records of 311 goats combined from 10 studies, with BW ranging from 4.3 to 47.4 kg were used. The EBW was computed as the BW at slaughter minus the weight of the contents of the digestive tract, urinary bladder, and biliary vesicle. Linear regression analyses were performed to develop the models, considering sex, type of diet, and genotype as fixed effects and random effect of study. CONTRAST statements were used to conduct all pairwise comparisons of fixed effects and all the statistical analyses were performed using SAS. The present study revealed that sex did not affect both intercept (P = 0.53) and slope (P = 0.19). On the other hand, the EBW prediction was affected by type of diet (P < 0.01), and genotype (P = 0.02). Therefore, were proposed different equations to predict EBW from BW for suckling and post-weaning Saanen goats, where gastrointestinal tract content (g/kg EBW) in suckling goat kids increased as they grew, oppositely it remained slightly constant in postweaning goats. The effect of genotype on the EBW:BW relationship was tested considering only post-weaning goats, and one equation was proposed for each genotype. In general, gastrointestinal tract content (g/kg EBW) decreased as goat kids grew in all genotypes but Indigenous goats. The results also highlighted different gastrointestinal relative capacity between genotypes. The development of these equations would enable producers and researchers to predict the animal EBW, and develop strategic plans in a goat herd.
O interesse nas pesquisas com células-tronco derivadas de anexos fetais de diversas espécies cresceu exponencialmente nas últimas décadas em virtude de serem fontes de células-tronco adultas com potencial de diferenciação em diversas linhagens celulares que apresentam pouca ou nenhuma imunogenicidade, apresentando-se assim como alternativa de grande importância para a formação de bancos celulares. Apesar do crescente interesse, os estudos para espécie equina ainda são escassos. O objetivo deste trabalho foi isolar, caracterizar e diferenciar células-tronco mesenquimais (CTMs) derivadas do líquido amniótico equino obtidas do terço inicial, médio e final da gestação (LA-CTMs), comparando suas características. Foram colhidas 23 amostras de líquido amniótico as quais foram submetidas às análises morfológica, imunocitoquímica, imunofenotípica por citometria de fluxo e às diferenciações osteogênica, adipogênica e condrogênica in vitro. Todas as amostras demonstraram adesão ao plástico e morfologia fibroblastóide. No ensaio imunocitoquímico as células de todos os grupos foram imunomarcadas para CD44, PCNA e vimentina com ausência de marcação para citoqueratina e Oct-4. Na citometria de fluxo observou-se a expressão de CD44 e CD90 e ausência de expressão de CD34, sendo que os marcadores CD44 e CD90 mostraram padrão de expressão decrescente em relação ao desenvolvimento gestacional. As amostras obtidas de todas as fases da gestação foram capazes de diferenciação nas linhagens osteogênica, condrogênica e adipogênica. Portanto, as células obtidas do líquido amniótico apresentaram características morfológicas, imunofenotípicas e potencial de diferenciação típicos das CTMs, demonstrando que a colheita pode ser realizada em qualquer fase gestacional. No entanto, mais pesquisas devem ser realizadas principalmente quanto à expressão de marcadores de pluripotencialidade (como o Oct-4) e ao seu potencial de diferenciação em linhagens extra mesodermais já relatados na literatura.
Stem cells are undifferentiated cells with a high proliferation potential. These cells can be characterized by their in vivo ability to self-renew and to differentiate into specialized cell lines. The most used stem cell types, in both human and veterinary fields, are the mesenchymal stem cells (MSC) derived from bone marrow and adipose tissue. Nowadays, there is a great interest in using stem cells derived from fetal tissues, such as amniotic membrane (AM) and umbilical cord tissue (UCT), which can be obtained non-invasively at delivery time. Due to the scarcity of studies in bovine species, the aim of this study was to isolate, characterize, differentiate and cryopreserve MSC derived from the mesenchymal layer of amniotic membrane (AM), for the first time, and umbilical cord tissue (UCT) of dairy cow neonates after assisted delivery (AD) and from fetus at initial third of pregnancy (IT) obtained in slaughterhouse. Cells were isolated by enzymatic digestion of the tissue fragments with 0.1% collagenase solution. Six samples of AM and UCT at delivery time and six samples of AM and UCT at first trimester of pregnancy were subjected to morphology evaluation, imunophenotype characterization, in vitro osteogenic, adipogenic and chondrogenic differentiation and viability analysis after cryopreservation. All samples showed adherence to plastic and fibroblast-like morphology. Immunocytochemistry revealed expression of CD 44, NANOG and OCT-4 and lack of expression of MHC II in MSC from all samples. Flow cytometry demonstrated that cells from all samples expressed CD 44, did not or low expressed CD 34 (AM: IT-0.3%a, AD-3.4%b; UCT: 0.4%, 1.4%) and MHC II (AM: IT-1.05%a, AD-9.7%b; UCT: IT-0.7%a, AD-5.7%b). They were also capable of trilineage mesenchymal differentiation and showed 80% viability after cryopreservation. According to the results, bovine AM and UCT-derived cells, either obtained at delivery time or from slaughterhouse, are a painless and non-invasive source of MSC and can be used for stem cell banking.
Animal dimensions are essential indicators for monitoring their growth rate, diet efficiency, and health status. A computer vision system is a recently emerging precision livestock farming technology that overcomes the previously unresolved challenges pertaining to labor and cost. Depth sensor cameras can be used to estimate the depth or height of an animal, in addition to two-dimensional information. Collecting top-view depth images is common in evaluating body mass or conformational traits in livestock species. However, in the depth image data acquisition process, manual interventions are involved in controlling a camera from a laptop or where detailed steps for automated data collection are not documented. Furthermore, open-source image data acquisition implementations are rarely available. The objective of this study was to 1) investigate the utility of automated top-view dairy cow depth data collection methods using picture- and video-based methods, 2) evaluate the performance of an infrared cut lens, 3) and make the source code available. Both methods can automatically perform animal detection, trigger recording, capture depth data, and terminate recording for individual animals. The picture-based method takes only a predetermined number of images whereas the video-based method uses a sequence of frames as a video. For the picture-based method, we evaluated 3- and 10-picture approaches. The depth sensor camera was mounted 2.75 m above-the-ground over a walk-through scale between the milking parlor and the free-stall barn. A total of 150 Holstein and 100 Jersey cows were evaluated. A pixel location where the depth was monitored was set up as a point of interest. More than 89% of cows were successfully captured using both picture- and video-based methods. The success rates of the picture- and video-based methods further improved to 92% and 98%, respectively, when combined with an infrared cut lens. Although both the picture-based method with 10 pictures and the video-based method yielded accurate results for collecting depth data son cows, the former was more efficient in terms of data storage. The current study demonstrates automated depth data collection frameworks and a Python implementation available to the community, which can help facilitate the deployment of computer vision systems for dairy cows.
This study aimed to evaluate the use of total odd-chain fatty acids (OCFA) as a marker to estimate microbial nitrogen flow (MicN) and calculate the efficiency of microbial nitrogen synthesis (EMNS) in Nellore steers fed high-concentrate diets supplemented with different nitrogen supplements (NS). Ruminally and duodenally cannulated Nellore steers (n = 6; 354 ± 12 kg) were used in a 6×6 repeated switchback design balanced for residual effects. Treatments were arranged in a 3 x 3 factorial of 3 nitrogen (N) supplements (urea plus soybean meal, U+SBM; corn gluten meal, CGM; dried distillers’ grains plus solubles, DDGS) and 3 microbial markers (OCFA; double-labeled urea, 15N; microbial nucleic acid bases, MNAB). The total mixed ration was composed of fresh chopped sugar cane as the forage source in an 83:17 concentrate: forage ratio (dry matter basis). Linear regression was used to develop predictions of MicN from OCFA using 15N and MNAB as response variables. Microbial N flow was underestimated by the MNAB marker compared to 15N. Neither NS nor their respective interactions with the marker methods (MM) affected MicN or EMNS (P > 0.05). However, MicN was different for 15N and MNAB (P > 0.001 for both treatments). Marker methods affected EMNS in all energetic bases (total digestible carbohydrates P < 0.001; rumen-fermentable carbohydrates P < 0.001; organic matter truly degradable in the rumen P < 0.001). Equations that utilized OCFA as a regressor to predict MicN under different MM resulted in good fits of the data as observed by the coefficient of determination (R 2; 15N = 0.78; MNAB = 0.69). Microbial N flow estimated from OCFA was overpredicted (15N by 7.46%; MNAB by 4.30%) compared to observed values. The OCFA model presented a small slope bias when methodological validation was applied (15N = 0.96%; MNAB = 3.90%), ensuring reliability of the proposed alternative method. Based on the conditions of this experiment, OCFA may be a suitable alternative to other methods that quantify MicN under different dietary conditions.
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