P.R. Menta , J. Prim , E. de Oliveira , F. Lima , K.N. Galvão , N. Noyes , M.A. Ballou , V.S. Machado
Our objective was to evaluate the accuracy of predictive models for metritis spontaneous cure (SC) and cure among ceftiofur-treated cows using farm-collected data only, and with the addition of hemogram variables and circulating concentration of metabolites, minerals, and biomarkers (BM) of inflammation measured at time of diagnosis. Data related to parity, calving-related issues, BCS, rectal temperature, and DIM at metritis diagnosis were collected from a randomized clinical trial that included 422 metritic cows from 4 herds in Texas, California, and Florida. Metritis was defined as the presence of red-brownish, watery, and fetid vaginal discharge, and cure was defined as the absence of metritis 14 d after initial diagnosis. Cows were randomly allocated to receive systemic ceftiofur therapy (2 subcutaneous doses of 6.6 mg/kg of ceftiofur crystalline-free acid on the day of diagnosis and 3 d later; CEF) or to remain untreated (control). At enrollment (day of metritis diagnosis), blood samples were collected and submitted to complete blood count (CBC) and processed for the measurement of 13 minerals and BM of metabolism and inflammation. Univariable analysis to evaluate the association of farm-collected data and blood-assessed variables with metritis cure were performed, and variables with P ≤ 0.20 were offered to multivariable logistic regression models and retained if P ≤ 0.15. The areas under the curve for models predicting SC using farm data only and farm + BM were 0.70 and 0.76, respectively. Complete blood count variables were not retained in the models for SC. For models predicting cure among CEF cows, the area under the curve was 0.75, 0.77, 0.80, and 0.80 for models using farm data only, farm + CBC, farm + BM, and farm + CBC + BM, respectively. Predictive models of metritis cure had fair accuracy, with SC models being less accurate than models predictive of cure among CEF cows. Additionally, adding BM variables marginally improved the accuracy of models using farm collected data, and CBC data did not improve the accuracy of predictive models.
{"title":"Predictive models for metritis cure using farm-collected data, metabolic and inflammation biomarkers, and hemogram variables measured at diagnosis","authors":"P.R. Menta , J. Prim , E. de Oliveira , F. Lima , K.N. Galvão , N. Noyes , M.A. Ballou , V.S. Machado","doi":"10.3168/jds.2023-24452","DOIUrl":"10.3168/jds.2023-24452","url":null,"abstract":"<div><p>Our objective was to evaluate the accuracy of predictive models for metritis spontaneous cure (SC) and cure among ceftiofur-treated cows using farm-collected data only, and with the addition of hemogram variables and circulating concentration of metabolites, minerals, and biomarkers (BM) of inflammation measured at time of diagnosis. Data related to parity, calving-related issues, BCS, rectal temperature, and DIM at metritis diagnosis were collected from a randomized clinical trial that included 422 metritic cows from 4 herds in Texas, California, and Florida. Metritis was defined as the presence of red-brownish, watery, and fetid vaginal discharge, and cure was defined as the absence of metritis 14 d after initial diagnosis. Cows were randomly allocated to receive systemic ceftiofur therapy (2 subcutaneous doses of 6.6 mg/kg of ceftiofur crystalline-free acid on the day of diagnosis and 3 d later; CEF) or to remain untreated (control). At enrollment (day of metritis diagnosis), blood samples were collected and submitted to complete blood count (CBC) and processed for the measurement of 13 minerals and BM of metabolism and inflammation. Univariable analysis to evaluate the association of farm-collected data and blood-assessed variables with metritis cure were performed, and variables with <em>P</em> ≤ 0.20 were offered to multivariable logistic regression models and retained if <em>P</em> ≤ 0.15. The areas under the curve for models predicting SC using farm data only and farm + BM were 0.70 and 0.76, respectively. Complete blood count variables were not retained in the models for SC. For models predicting cure among CEF cows, the area under the curve was 0.75, 0.77, 0.80, and 0.80 for models using farm data only, farm + CBC, farm + BM, and farm + CBC + BM, respectively. Predictive models of metritis cure had fair accuracy, with SC models being less accurate than models predictive of cure among CEF cows. Additionally, adding BM variables marginally improved the accuracy of models using farm collected data, and CBC data did not improve the accuracy of predictive models.</p></div>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224005253/pdfft?md5=ad5faf5aee85adb595bb14dbf18525d9&pid=1-s2.0-S0022030224005253-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140011791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seoyoung Jeon , Sophie Lemosquet , Anne-Cécile Toulemonde , Tristan Senga Kiessé , Pierre Nozière
In the feeding system for ruminants developed in 2018 by the French National Institute of Agricultural Research (INRA), the prediction of multiple animal responses is based on the integration of the characteristics of the animal and the available feedstuff characteristics, as well as the rationing objectives. In this framework, the characterization of feedstuffs in terms of net energy, digestible protein, and fill units requires information on their chemical composition, digestibility, and degradability. Despite the importance of these feed characteristics, a comprehensive assessment of their impact on the responses predicted by the INRA 2018 feeding system has not been carried out. Thus, our study investigated how variables predicted by the INRA feeding system (i.e., outputs) for dairy cows are affected by variation in feed characterization (i.e., inputs). We selected 5 input variables for the sensitivity analysis: CP, OM apparent digestibility (OMd), gross energy (GE), effective degradability of nitrogen assuming a passage rate of 6%/h (ED6_N), and true intestinal digestibility (dr_N) of nitrogen. A one-at-a-time sensitivity analysis was performed on predicted digestive, productive, and environmental output variables for dairy cows with 6 contrasted diets. These 6 diets were formulated to meet 95% of the potential daily milk production (37.5 kg) of a multiparous cow at wk 14 of lactation. The values of the 5 key input variables of each feedstuff were then randomly sampled around the INRA 2018 feed table values (reference point). The response of the output variable to the variation of the input variable was quantified and compared using the tangent value at the reference point and the normalized sensitivity coefficient. Among the major final output variables, CP and dr_N had the greatest impact on N excretion in urine (as a proportion of total fecal and urinary N excretion; UN/TN); OMd and GE had the greatest impact on N utilization efficiency (NUE; N in milk as proportion of intake N); and ED6_N had the greatest impact on milk protein yield (MPY). Additionally, CP, GE, and dr_N had the least effect on methane emission, OMd had the least effect on UN/TN, and ED6_N had the least effect on NUE. The responses of most output variables to ED6_N and dr_N variations were highly dependent on diet and were related to the ratio between protein truly digestible in the intestine (PDI; i.e., MP) and net energy for lactation (UFL; i.e., NEL) at the reference point of each diet. Overall, we were able to analyze the response of output variables to the variations of the input variables, using the tangent and its normalized value at the reference point. The predicted final outputs were more affected by variations in CP, GE, and OMd. The other 2 input variables, ED6_N and dr_N, had a smaller effect on the final output variables, but the responses varied between the diets according to their PDI/UFL ratio. Our present study was conducted using 6 r
{"title":"Sensitivity analysis of the INRA 2018 feeding system for ruminants by a one-at-a-time approach: Effects of dietary input variables on predictions of multiple responses of dairy cattle","authors":"Seoyoung Jeon , Sophie Lemosquet , Anne-Cécile Toulemonde , Tristan Senga Kiessé , Pierre Nozière","doi":"10.3168/jds.2023-24361","DOIUrl":"10.3168/jds.2023-24361","url":null,"abstract":"<div><p>In the feeding system for ruminants developed in 2018 by the French National Institute of Agricultural Research (INRA), the prediction of multiple animal responses is based on the integration of the characteristics of the animal and the available feedstuff characteristics, as well as the rationing objectives. In this framework, the characterization of feedstuffs in terms of net energy, digestible protein, and fill units requires information on their chemical composition, digestibility, and degradability. Despite the importance of these feed characteristics, a comprehensive assessment of their impact on the responses predicted by the INRA 2018 feeding system has not been carried out. Thus, our study investigated how variables predicted by the INRA feeding system (i.e., outputs) for dairy cows are affected by variation in feed characterization (i.e., inputs). We selected 5 input variables for the sensitivity analysis: CP, OM apparent digestibility (OMd), gross energy (GE), effective degradability of nitrogen assuming a passage rate of 6%/h (ED6_N), and true intestinal digestibility (dr_N) of nitrogen. A one-at-a-time sensitivity analysis was performed on predicted digestive, productive, and environmental output variables for dairy cows with 6 contrasted diets. These 6 diets were formulated to meet 95% of the potential daily milk production (37.5 kg) of a multiparous cow at wk 14 of lactation. The values of the 5 key input variables of each feedstuff were then randomly sampled around the INRA 2018 feed table values (reference point). The response of the output variable to the variation of the input variable was quantified and compared using the tangent value at the reference point and the normalized sensitivity coefficient. Among the major final output variables, CP and dr_N had the greatest impact on N excretion in urine (as a proportion of total fecal and urinary N excretion; UN/TN); OMd and GE had the greatest impact on N utilization efficiency (NUE; N in milk as proportion of intake N); and ED6_N had the greatest impact on milk protein yield (MPY). Additionally, CP, GE, and dr_N had the least effect on methane emission, OMd had the least effect on UN/TN, and ED6_N had the least effect on NUE. The responses of most output variables to ED6_N and dr_N variations were highly dependent on diet and were related to the ratio between protein truly digestible in the intestine (PDI; i.e., MP) and net energy for lactation (UFL; i.e., NE<sub>L</sub>) at the reference point of each diet. Overall, we were able to analyze the response of output variables to the variations of the input variables, using the tangent and its normalized value at the reference point. The predicted final outputs were more affected by variations in CP, GE, and OMd. The other 2 input variables, ED6_N and dr_N, had a smaller effect on the final output variables, but the responses varied between the diets according to their PDI/UFL ratio. Our present study was conducted using 6 r","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224005332/pdfft?md5=21d29700f278499a31904518d7b4c934&pid=1-s2.0-S0022030224005332-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140067981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Rossi, Fabio Marroni, Niccolò Renoldi, Giulia Di Filippo, Elisabetta Gover, Marilena Marino, Nadia Innocente
The use of natural milk culture (NMC) represents a key factor in Protected Designation of Origin (PDO) Montasio cheese, contributing to its distinctive sensory profile. The complex microbial ecosystem of NMC is the result of heat treatment and incubation conditions, which can vary considerably among different production plants. In this study, the microbiota of NMC collected from 10 PDO Montasio cheese dairies was investigated by employing colony counts and metagenomic analysis. Furthermore, residual sugars, organic acids, and volatile profiles were quantitatively investigated. Results showed that Streptococcus thermophilus was the dominant species in all NMC, and a subdominant population made of other streptococci and Ligilactobacillus salivarius was also present. The incubation temperature appeared to be the main driver of biodiversity in NMC. Metagenomics allowed us to evidence the presence of minor species involving safety (e.g., Staphylococcus aureus) as well as possible functional aspects (Next Generation Probiotics). Statistical analysis based on residual sugars, organic acids, and volatiles' content allowed to correlate the presence of specific microbial groups with metabolites of great technological and sensory relevance, which can contribute to giving value to the artisanal production procedures of NMC and clarify their role in the creation of the characteristics of PDO Montasio cheese.
{"title":"An integrated approach to explore the microbial biodiversity of natural milk cultures for cheesemaking","authors":"Anna Rossi, Fabio Marroni, Niccolò Renoldi, Giulia Di Filippo, Elisabetta Gover, Marilena Marino, Nadia Innocente","doi":"10.3168/jds.2024-24463","DOIUrl":"10.3168/jds.2024-24463","url":null,"abstract":"<div><p>The use of natural milk culture (NMC) represents a key factor in Protected Designation of Origin (PDO) Montasio cheese, contributing to its distinctive sensory profile. The complex microbial ecosystem of NMC is the result of heat treatment and incubation conditions, which can vary considerably among different production plants. In this study, the microbiota of NMC collected from 10 PDO Montasio cheese dairies was investigated by employing colony counts and metagenomic analysis. Furthermore, residual sugars, organic acids, and volatile profiles were quantitatively investigated. Results showed that <em>Streptococcus thermophilus</em> was the dominant species in all NMC, and a subdominant population made of other streptococci and <em>Ligilactobacillus salivarius</em> was also present. The incubation temperature appeared to be the main driver of biodiversity in NMC. Metagenomics allowed us to evidence the presence of minor species involving safety (e.g., <em>Staphylococcus aureus</em>) as well as possible functional aspects (Next Generation Probiotics). Statistical analysis based on residual sugars, organic acids, and volatiles' content allowed to correlate the presence of specific microbial groups with metabolites of great technological and sensory relevance, which can contribute to giving value to the artisanal production procedures of NMC and clarify their role in the creation of the characteristics of PDO Montasio cheese.</p></div>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224005356/pdfft?md5=9c4cd0e80c41fa3fdf17a5e9e63cb304&pid=1-s2.0-S0022030224005356-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140093169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J.-Y. Kim , S. Lee , G. Kim , H.J. Shin , E.J. Lee , C.S. Lee , S. Yoon , E. Lee , A. Lim , S.H. Kim
Human milk oligosaccharides (HMO) affect gut microbiota during neonatal development, particularly with respect to the immune system. Bovine milk-based infant formulas have low oligosaccharide contents. Thus, efforts to fortify infant formulas with HMO are being undertaken. Two major HMO, 2′-fucosyllactose (2′-FL) and 6′-sialyllactose (6′-SL), exert anti-inflammatory effects; however, the associations between anti-inflammatory effects induced by 2′-FL and 6′-SL cotreatment and gut microbiota composition and metabolite modulation remain unclear. Therefore, in this study, we evaluated the effects of a mixture of these HMO. To determine the optimal HMO ratio for anti-inflammatory effects and elucidate its mode of action, LPS-induced inflammatory HT-29 epithelial cells and intestinal-inflamed suckling mice were treated with various mixtures of 2′-FL and 6′-SL. A 2′-FL:6′-SL ratio of 5:1 was identified as the most effective pretreatment HMO mixture in vitro; thus, this ratio was selected and used for low-, middle-, and high-dose treatments for subsequent in vivo studies. In vivo, high-dose HMO treatment restored LPS-induced inflammation symptoms, such as BW loss, colon length reduction, histological structural damage, and intestinal gene expression related to inflammatory responses. High-dose HMO was the only treatment that modulated the major phyla Bacteroidetes and Firmicutes and the genera Ihubacter, Mageeibacillus, and Saccharofermentans. These changes in microbial composition were correlated with intestinal inflammation-related gene expression and short-chain fatty acid production. To our knowledge, our study is the first to report the effects of Ihubacter, Mageeibacillus, and Saccharofermentans on short-chain fatty acid levels, which can subsequently affect inflammatory cytokine and tight junction protein levels. Conclusively, the HMO mixture exerted anti-inflammatory effects through changes in microbiota and metabolite production. These findings suggest that supplementation of infant formula with HMO may benefit formula-fed infants by forming unique microbiota contributing to neonatal development.
{"title":"Ameliorating effect of 2′-fucosyllactose and 6′-sialyllactose on lipopolysaccharide-induced intestinal inflammation","authors":"J.-Y. Kim , S. Lee , G. Kim , H.J. Shin , E.J. Lee , C.S. Lee , S. Yoon , E. Lee , A. Lim , S.H. Kim","doi":"10.3168/jds.2024-24325","DOIUrl":"10.3168/jds.2024-24325","url":null,"abstract":"<div><p>Human milk oligosaccharides (HMO) affect gut microbiota during neonatal development, particularly with respect to the immune system. Bovine milk-based infant formulas have low oligosaccharide contents. Thus, efforts to fortify infant formulas with HMO are being undertaken. Two major HMO, 2′-fucosyllactose (2′-FL) and 6′-sialyllactose (6′-SL), exert anti-inflammatory effects; however, the associations between anti-inflammatory effects induced by 2′-FL and 6′-SL cotreatment and gut microbiota composition and metabolite modulation remain unclear. Therefore, in this study, we evaluated the effects of a mixture of these HMO. To determine the optimal HMO ratio for anti-inflammatory effects and elucidate its mode of action, LPS-induced inflammatory HT-29 epithelial cells and intestinal-inflamed suckling mice were treated with various mixtures of 2′-FL and 6′-SL. A 2′-FL:6′-SL ratio of 5:1 was identified as the most effective pretreatment HMO mixture in vitro; thus, this ratio was selected and used for low-, middle-, and high-dose treatments for subsequent in vivo studies. In vivo, high-dose HMO treatment restored LPS-induced inflammation symptoms, such as BW loss, colon length reduction, histological structural damage, and intestinal gene expression related to inflammatory responses. High-dose HMO was the only treatment that modulated the major phyla <em>Bacteroidetes</em> and <em>Firmicutes</em> and the genera <em>Ihubacter</em>, <em>Mageeibacillus</em>, and <em>Saccharofermentans</em>. These changes in microbial composition were correlated with intestinal inflammation-related gene expression and short-chain fatty acid production. To our knowledge, our study is the first to report the effects of <em>Ihubacter, Mageeibacillus</em>, and <em>Saccharofermentans</em> on short-chain fatty acid levels, which can subsequently affect inflammatory cytokine and tight junction protein levels. Conclusively, the HMO mixture exerted anti-inflammatory effects through changes in microbiota and metabolite production. These findings suggest that supplementation of infant formula with HMO may benefit formula-fed infants by forming unique microbiota contributing to neonatal development.</p></div>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S002203022400568X/pdfft?md5=7b5cc2e45db1896e32fee55dd4f4e4d6&pid=1-s2.0-S002203022400568X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140136136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genetic improvement in small countries rely heavily on foreign genetics. In an importing country such as Uruguay, consideration of unknown parent groups (UPG) for foreign sires is essential. However, the use of UPG in genomic model evaluations may lead to bias in genomic estimated breeding values (GEBV). The objective of this study was to study different models including UPG or metafounders (MF) in the Uruguayan Holstein evaluation and to analyze bias, dispersion, and accuracy of GEBV predictions in BLUP and single-step genomic BLUP (ssGBLUP). A gamma matrix (Γ) was estimated either by using base allele population frequencies obtained by bounded linear regression (MFbounded), or by using 2 values to design Γ (i.e., a single value for the diagonal and a different value for the off-diagonal [MFrobust]). Both Γ estimators performed well in terms of GEBV predictions, but MFbounded was the best option. There is, however, some bias whose origin was not completely understood. UPG or MF seem to model correctly genetic progress for unknown parents except for the very first groups (earlier time period). As for validation bulls, bias was observed across all models, whereas for validation cows it was only observed with UPG in BLUP. Overdispersion was found in all models, but it was mostly detected in validation bulls. Ratio of accuracies indicated that ssGBLUP gave better predictions than BLUP.
{"title":"Modeling missing pedigree with metafounders and validating single-step genomic predictions in a small dairy cattle population with a great influence of foreign genetics","authors":"R.D. López-Correa , A. Legarra , I. Aguilar","doi":"10.3168/jds.2023-23732","DOIUrl":"10.3168/jds.2023-23732","url":null,"abstract":"<div><p>Genetic improvement in small countries rely heavily on foreign genetics. In an importing country such as Uruguay, consideration of unknown parent groups (UPG) for foreign sires is essential. However, the use of UPG in genomic model evaluations may lead to bias in genomic estimated breeding values (GEBV). The objective of this study was to study different models including UPG or metafounders (MF) in the Uruguayan Holstein evaluation and to analyze bias, dispersion, and accuracy of GEBV predictions in BLUP and single-step genomic BLUP (ssGBLUP). A gamma matrix (<strong>Γ</strong>) was estimated either by using base allele population frequencies obtained by bounded linear regression (MFbounded), or by using 2 values to design Γ (i.e., a single value for the diagonal and a different value for the off-diagonal [MFrobust]). Both <strong>Γ</strong> estimators performed well in terms of GEBV predictions, but MFbounded was the best option. There is, however, some bias whose origin was not completely understood. UPG or MF seem to model correctly genetic progress for unknown parents except for the very first groups (earlier time period). As for validation bulls, bias was observed across all models, whereas for validation cows it was only observed with UPG in BLUP. Overdispersion was found in all models, but it was mostly detected in validation bulls. Ratio of accuracies indicated that ssGBLUP gave better predictions than BLUP.</p></div>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224000547/pdfft?md5=afbc5208b50edcf6123238c43e9db3d5&pid=1-s2.0-S0022030224000547-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139662633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B.J. Van Soest , R.D. Matson , D.E. Santschi , T.F. Duffield , M.A. Steele , K. Orsel , E.A. Pajor , G.B. Penner , T. Mutsvangwa , T.J. DeVries
The objective of this study was to describe the nutritional strategies used on Canadian dairy farms with automated milking systems (AMS), both at the feed bunk and the concentrate offered at the AMS, as well as to determine what dietary components and nutrients, as formulated, were associated with milk production and milking behaviors on those farms. Formulated diets (including ingredients and nutrient content) and AMS data were collected from April 1, 2019, until September 30, 2020, on 160 AMS farms (eastern Canada [East] = 8, Ontario [ON] = 76, Quebec [QC] = 22, and western Canada [West] = 54). Both partial mixed ration (PMR) and AMS concentrate samples were collected from May 1 to September 30, 2019, on 169 farms (East = 12, ON = 63, QC = 42, West = 52). We collected AMS milking data for 154 herds. For each farm (n = 161), milk recording data were collected and summarized by farm to calculate average milk yield and components. Multivariable regression models were used to associate herd-level formulated nutrient composition and feeding management practices with milk production and milking behavior. Milk yield (mean ± SD = 37.0 ± 0.3 kg/d) was positively associated with the PMR ether extract (EE) concentration (+0.97 kg/d per percentage point [p.p.] increase) and with farms that fed barley silage as their major forage source (n = 16; +2.18 kg/d) as compared with haylage (n = 42), whereas farms that fed corn silage (n = 96; +1.23 kg/d) tended to produce more milk than farms that fed haylage. Greater milk fat content (4.09 ± 0.28%) was associated with a greater PMR-to-AMS concentrate ratio (+0.02 p.p. per unit increase) and total diet net energy for lactation (+0.046 p.p. per 0.1 Mcal/kg increase), but a lesser percentage of NFC of the PMR (−0.016 p.p. per p.p. increase of NFC percentage). Milk protein content (3.38 ± 0.14%) was positively associated with the forage percentage of the PMR (+0.003 p.p. per p.p. increase of forage percentage) and the total diet starch percentage (+0.009 p.p. per p.p. increase of starch percentage), but was negatively associated with farms feeding corn silage (−0.1 p.p. compared with haylage) as their major forage. Greater milking frequency (2.77 ± 0.40 milkings/d) was observed on farms with free-flow cow traffic systems (+0.62 milkings/d) and was positively associated with feed push-up frequency (+0.013 milkings/d per additional feed push-up), but negatively associated with PMR NFC content and forage percentage of the total ration (−0.017 milkings/d per p.p. increase of forage percentage). Lastly, greater milking refusal frequency (1.49 ± 0.82 refusals/d) was observed on farms with free-flow cow traffic systems (+0.84 refusals/d) and farms feeding barley silage (+0.58 refusals/d) than with guided flow and farms feeding either corn silage or haylage, respectively. These data give insight into the ingredients, nutrient formulations and type of diets fed on AMS dairy farms across Canada and the
{"title":"Farm-level nutritional factors associated with milk production and milking behavior on Canadian farms with automated milking systems","authors":"B.J. Van Soest , R.D. Matson , D.E. Santschi , T.F. Duffield , M.A. Steele , K. Orsel , E.A. Pajor , G.B. Penner , T. Mutsvangwa , T.J. DeVries","doi":"10.3168/jds.2023-24355","DOIUrl":"10.3168/jds.2023-24355","url":null,"abstract":"<div><p>The objective of this study was to describe the nutritional strategies used on Canadian dairy farms with automated milking systems (AMS), both at the feed bunk and the concentrate offered at the AMS, as well as to determine what dietary components and nutrients, as formulated, were associated with milk production and milking behaviors on those farms. Formulated diets (including ingredients and nutrient content) and AMS data were collected from April 1, 2019, until September 30, 2020, on 160 AMS farms (eastern Canada [East] = 8, Ontario [ON] = 76, Quebec [QC] = 22, and western Canada [West] = 54). Both partial mixed ration (PMR) and AMS concentrate samples were collected from May 1 to September 30, 2019, on 169 farms (East = 12, ON = 63, QC = 42, West = 52). We collected AMS milking data for 154 herds. For each farm (n = 161), milk recording data were collected and summarized by farm to calculate average milk yield and components. Multivariable regression models were used to associate herd-level formulated nutrient composition and feeding management practices with milk production and milking behavior. Milk yield (mean ± SD = 37.0 ± 0.3 kg/d) was positively associated with the PMR ether extract (EE) concentration (+0.97 kg/d per percentage point [<strong>p.p.</strong>] increase) and with farms that fed barley silage as their major forage source (n = 16; +2.18 kg/d) as compared with haylage (n = 42), whereas farms that fed corn silage (n = 96; +1.23 kg/d) tended to produce more milk than farms that fed haylage. Greater milk fat content (4.09 ± 0.28%) was associated with a greater PMR-to-AMS concentrate ratio (+0.02 p.p. per unit increase) and total diet net energy for lactation (+0.046 p.p. per 0.1 Mcal/kg increase), but a lesser percentage of NFC of the PMR (−0.016 p.p. per p.p. increase of NFC percentage). Milk protein content (3.38 ± 0.14%) was positively associated with the forage percentage of the PMR (+0.003 p.p. per p.p. increase of forage percentage) and the total diet starch percentage (+0.009 p.p. per p.p. increase of starch percentage), but was negatively associated with farms feeding corn silage (−0.1 p.p. compared with haylage) as their major forage. Greater milking frequency (2.77 ± 0.40 milkings/d) was observed on farms with free-flow cow traffic systems (+0.62 milkings/d) and was positively associated with feed push-up frequency (+0.013 milkings/d per additional feed push-up), but negatively associated with PMR NFC content and forage percentage of the total ration (−0.017 milkings/d per p.p. increase of forage percentage). Lastly, greater milking refusal frequency (1.49 ± 0.82 refusals/d) was observed on farms with free-flow cow traffic systems (+0.84 refusals/d) and farms feeding barley silage (+0.58 refusals/d) than with guided flow and farms feeding either corn silage or haylage, respectively. These data give insight into the ingredients, nutrient formulations and type of diets fed on AMS dairy farms across Canada and the ","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224000651/pdfft?md5=a60f5e123fddb8e26740b9c104234b28&pid=1-s2.0-S0022030224000651-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139662626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giulio Giagnoni , Nicolas C. Friggens , Marianne Johansen , Morten Maigaard , Wenji Wang , Peter Lund , Martin R. Weisbjerg
Enteric CH4 produced from dairy cows contributes to the emission of greenhouse gases from anthropogenic sources. Recent studies have shown that the selection of lower CH4-emitting cows is possible, but doing so would be simpler if performance measures already recorded on farm could be used, instead of measuring gas emissions from individual cows. These performance measures could be used for selection of low emitting cows. The aim of this analysis was to quantify how much of the between-cow variation in CH4 production can be explained by variation in performance measures. A dataset with 3 experiments and a total of 149 lactating dairy cows with repeated measures was used to estimate the between-cow variation (the variation between cow estimates) for performance and gas measures from GreenFeed (C-Lock, Rapid City, SD). The cow estimates were obtained with a linear mixed model with the diet within period effect as a fixed effect and the cow within experiment as a random effect. The cow estimates for CH4 production were first regressed on the performance and gas measures individually, and then performance and CO2 production measures were grouped in 3 subsets for principal component analysis and principal component regression. The variables that explained most of the between-cow variation in CH4 production were DMI (R2 = 0.44), among the performance measures, and CO2 production (R2 = 0.61), among gas measures. Grouping the measures increased the R2 to 0.53 when only performance measures were used, and to 0.66 when CO2 production was added to the significant performance measures. We found the marginal improvement to be insufficient to justify the use of grouped measures rather than an individual measure because the latter simplifies the model and avoids over-fitting. Investigation of other measures that can be explored to increase explanatory power of between-cow variation in CH4 production is briefly discussed. Finally, the use of residual CH4 as a measure for CH4 efficiency could be considered by using either DMI or CO2 production as the sole predicting variables.
{"title":"How much can performance measures explain of the between-cow variation in enteric methane?","authors":"Giulio Giagnoni , Nicolas C. Friggens , Marianne Johansen , Morten Maigaard , Wenji Wang , Peter Lund , Martin R. Weisbjerg","doi":"10.3168/jds.2023-24094","DOIUrl":"10.3168/jds.2023-24094","url":null,"abstract":"<div><p>Enteric CH<sub>4</sub> produced from dairy cows contributes to the emission of greenhouse gases from anthropogenic sources. Recent studies have shown that the selection of lower CH<sub>4</sub>-emitting cows is possible, but doing so would be simpler if performance measures already recorded on farm could be used, instead of measuring gas emissions from individual cows. These performance measures could be used for selection of low emitting cows. The aim of this analysis was to quantify how much of the between-cow variation in CH<sub>4</sub> production can be explained by variation in performance measures. A dataset with 3 experiments and a total of 149 lactating dairy cows with repeated measures was used to estimate the between-cow variation (the variation between cow estimates) for performance and gas measures from GreenFeed (C-Lock, Rapid City, SD). The cow estimates were obtained with a linear mixed model with the diet within period effect as a fixed effect and the cow within experiment as a random effect. The cow estimates for CH<sub>4</sub> production were first regressed on the performance and gas measures individually, and then performance and CO<sub>2</sub> production measures were grouped in 3 subsets for principal component analysis and principal component regression. The variables that explained most of the between-cow variation in CH<sub>4</sub> production were DMI (R<sup>2</sup> = 0.44), among the performance measures, and CO<sub>2</sub> production (R<sup>2</sup> = 0.61), among gas measures. Grouping the measures increased the R<sup>2</sup> to 0.53 when only performance measures were used, and to 0.66 when CO<sub>2</sub> production was added to the significant performance measures. We found the marginal improvement to be insufficient to justify the use of grouped measures rather than an individual measure because the latter simplifies the model and avoids over-fitting. Investigation of other measures that can be explored to increase explanatory power of between-cow variation in CH<sub>4</sub> production is briefly discussed. Finally, the use of residual CH<sub>4</sub> as a measure for CH<sub>4</sub> efficiency could be considered by using either DMI or CO<sub>2</sub> production as the sole predicting variables.</p></div>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224000596/pdfft?md5=23a1545b91b5fd779672e52481b9064c&pid=1-s2.0-S0022030224000596-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139662855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuxue Sun , Jiafei Liu , Xiaowen Pi , Shilong Jiang , Jianjun Cheng , Mingruo Guo
The composition of milk lipids varies across different ethnic sources. The lipidome profiles of Chinese Han human milk (HHM) and Chinese Korean human milk (KHM) were investigated in this study. A total of 741 lipids were identified in HHM and KHM. Twenty-eight differentially expressed lipids (DEL) were screened between the 2 milk groups; among these, 6 triacylglycerols (TG), 13 diacylglycerols (DG), 7 free fatty acids (FFA), and 1 monoglyceride (MG) were upregulated in KHM. Carnitine (CAR) was upregulated in HHM. Most DEL showed a single peak distribution in both groups. The correlations, related pathways and diseases of these DEL were further analyzed. The results demonstrated that DG, MG, and FFA showed highly positive correlations with each other (r > 0.8). The most enriched Kyoto Encyclopedia of Genes and Genomes (https://www.kegg.jp/kegg/) and Human Metabolome Database (http://www.hmdb.ca) pathways were inositol phosphate metabolism, and α-linolenic acid and linolenic acid metabolism, respectively. Major depressive disorder-related FFA (20:5) and FFA (22:6) were more abundant in KHM, whereas HHM showed more obesity-related CAR. These data potentially provide lipidome information regarding human milk from different ethnicities in China.
{"title":"Comparison of lipidome profiles in human milk from Chinese Han and Korean ethnic groups based on high-throughput lipidomic techniques","authors":"Yuxue Sun , Jiafei Liu , Xiaowen Pi , Shilong Jiang , Jianjun Cheng , Mingruo Guo","doi":"10.3168/jds.2023-23610","DOIUrl":"10.3168/jds.2023-23610","url":null,"abstract":"<div><p>The composition of milk lipids varies across different ethnic sources. The lipidome profiles of Chinese Han human milk (HHM) and Chinese Korean human milk (KHM) were investigated in this study. A total of 741 lipids were identified in HHM and KHM. Twenty-eight differentially expressed lipids (DEL) were screened between the 2 milk groups; among these, 6 triacylglycerols (TG), 13 diacylglycerols (DG), 7 free fatty acids (FFA), and 1 monoglyceride (MG) were upregulated in KHM. Carnitine (CAR) was upregulated in HHM. Most DEL showed a single peak distribution in both groups. The correlations, related pathways and diseases of these DEL were further analyzed. The results demonstrated that DG, MG, and FFA showed highly positive correlations with each other (r > 0.8). The most enriched Kyoto Encyclopedia of Genes and Genomes (<span>https://www.kegg.jp/kegg/</span><svg><path></path></svg>) and Human Metabolome Database (<span>http://www.hmdb.ca</span><svg><path></path></svg>) pathways were inositol phosphate metabolism, and α-linolenic acid and linolenic acid metabolism, respectively. Major depressive disorder-related FFA (20:5) and FFA (22:6) were more abundant in KHM, whereas HHM showed more obesity-related CAR. These data potentially provide lipidome information regarding human milk from different ethnicities in China.</p></div>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224005149/pdfft?md5=d073f43b0c351593117c36e29cef6719&pid=1-s2.0-S0022030224005149-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140011823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Lung , A. Doyen , G. Remondetto , Y. Pouliot , G. Brisson
Buttermilk differs from skim milk by the presence of milk fat globule membrane (MFGM) fragments that are released during cream churning. Milk fat globule membrane is rich in health-promoting components, such as phospholipids and membrane proteins, but these compounds have a negative impact on buttermilk techno-functional properties in dairy applications. The isolation of MFGM from buttermilk improved its functionality while also recovering the MFGM bioactive components. Hydroxyapatite (HA) can be used to extract MFGM by adsorption via charged site interactions. However, the affinity of HA to MFGM or the main buttermilk proteins (casein micelles [CM], β-LG, and α-LA) is not known. The influence of important physicochemical parameters such as pH and temperature on these interactions is also unclear. For each buttermilk component, a quartz crystal microbalance diffusion analysis was performed to determine the maximum adsorption time and the attached mass density on HA-coated gold sensors. The influence of pH, ionic strength (IS), and temperature (T) on the affinity of each buttermilk component for HA particles was assessed using a 3-levels and 3-factors Box-Behnken design. The absorption rate was highest for the CM, followed by β-LG and α-LA, and then by the MFGM. Nevertheless, the final maximal attached mass densities to the HA were similar for the MFGM and CM, and 2.5 times higher than for β-LG and α-LA. This difference can be explained by the higher number of binding sites found in CM and their heavier mass. The model obtained by the Box-Behnken design plan showed that the adsorption of the CM changed with T, pH, and IS. These results suggest that the techno-functional properties of buttermilk may be restored by specifically extracting MFGM with HA. Experiments are ongoing to determine conditions for fractionating MFGM directly from buttermilk.
酪乳与脱脂奶的不同之处在于，酪乳中含有乳脂球膜（MFGM）碎片，这些碎片会在搅打奶油时释放出来。乳脂球膜富含磷脂和膜蛋白等促进健康的成分，但这些化合物对酪乳在乳制品应用中的技术功能特性有负面影响。从酪乳中分离出 MFGM 可提高其功能性，同时还可回收 MFGM 的生物活性成分。羟基磷灰石（HA）可通过带电位点相互作用吸附来提取 MFGM。然而，HA 与 MFGM 或主要酪乳蛋白质（酪蛋白胶束（CM）、β-乳球蛋白（β-lg）和α-乳白蛋白（α-lac））的亲和力尚不清楚。pH 值和温度等重要理化参数对这些相互作用的影响也不清楚。对每种酪乳成分都进行了石英晶体微天平扩散分析，以确定 HA 涂层金传感器上的最大吸附时间和附着质量密度。采用三水平三因素方框-贝肯设计评估了 pH 值、离子强度（IS）和温度（T）对每种酪乳成分与 HA 颗粒亲和力的影响。CM的吸收率最高，其次是β-lg和α-lac，然后是MFGM。尽管如此，MFGM 和 CM 最终附着在 HA 上的最大质量密度相似，比 β-lg 和 α-lac 高 2.5 倍。这种差异可以用 CM 中发现的更多结合位点及其更重的质量来解释。通过方框-贝肯设计方案得到的模型显示，中药的吸附量随温度、pH 值和 IS 的变化而变化。这些结果表明，通过用 HA 专门提取酪乳中的 MFGM，可以恢复酪乳的技术功能特性。目前正在进行实验，以确定直接从酪乳中分馏 MFGM 的条件。
{"title":"The affinity of milk fat globule membrane fragments and buttermilk proteins to hydroxyapatite","authors":"J. Lung , A. Doyen , G. Remondetto , Y. Pouliot , G. Brisson","doi":"10.3168/jds.2024-24353","DOIUrl":"10.3168/jds.2024-24353","url":null,"abstract":"<div><p>Buttermilk differs from skim milk by the presence of milk fat globule membrane (MFGM) fragments that are released during cream churning. Milk fat globule membrane is rich in health-promoting components, such as phospholipids and membrane proteins, but these compounds have a negative impact on buttermilk techno-functional properties in dairy applications. The isolation of MFGM from buttermilk improved its functionality while also recovering the MFGM bioactive components. Hydroxyapatite (HA) can be used to extract MFGM by adsorption via charged site interactions. However, the affinity of HA to MFGM or the main buttermilk proteins (casein micelles [CM], β-LG, and α-LA) is not known. The influence of important physicochemical parameters such as pH and temperature on these interactions is also unclear. For each buttermilk component, a quartz crystal microbalance diffusion analysis was performed to determine the maximum adsorption time and the attached mass density on HA-coated gold sensors. The influence of pH, ionic strength (IS), and temperature (T) on the affinity of each buttermilk component for HA particles was assessed using a 3-levels and 3-factors Box-Behnken design. The absorption rate was highest for the CM, followed by β-LG and α-LA, and then by the MFGM. Nevertheless, the final maximal attached mass densities to the HA were similar for the MFGM and CM, and 2.5 times higher than for β-LG and α-LA. This difference can be explained by the higher number of binding sites found in CM and their heavier mass. The model obtained by the Box-Behnken design plan showed that the adsorption of the CM changed with T, pH, and IS. These results suggest that the techno-functional properties of buttermilk may be restored by specifically extracting MFGM with HA. Experiments are ongoing to determine conditions for fractionating MFGM directly from buttermilk.</p></div>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224005721/pdfft?md5=bb4adb4d5f2c4a4c3ad9588b56f8a8bd&pid=1-s2.0-S0022030224005721-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140136145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahdieh Zare, Mohammad-Taghi Golmakani, Mehrdad Niakousari, Mohammad Hadi Eskandari, Fatemeh Ghiasi, Seyed Mohammad Hashem Hosseini
The effects of partial or full replacement of margarine by alginate/whey protein isolate-based olive oil emulgel on nutritional, physicochemical, mechanical, and rheological properties of processed cheese (PC) were investigated in this work. All formulated samples had the same amount of total fat, DM, and pH. According to the results of the fatty acids profile, the PC sample in which the margarine was fully replaced by the emulgel (EPC100) had the highest (49.84%) oleic acid content and showed a reduction of 23.7% in SFA compared with the control sample (EPC0; formulated just with margarine). In addition, EPC0 had the highest hardness among various cheese samples, which was also confirmed by its compact microstructure. Dynamic oscillatory measurements revealed that EPC100 had the highest crossover strain (or resistance to deformation). The high rigidity of this sample was related to the 3-dimensional structure of emulgel. According to the creep test results, EPC100 showed the lowest relative recovery (flowability). A high temperature dependency of viscoelastic moduli was observed in EPC0 at 42°C. No significant differences were observed between the color attributes and sensory properties of the various cheese samples. Alginate/whey protein isolate-based olive oil emulgel can be considered as a healthy margarine replacer in PC.
{"title":"Alginate/whey protein isolate-based emulgel as an alternative margarine replacer in processed cheese: Impact on rheological, mechanical, nutritional, and sensory characteristics","authors":"Mahdieh Zare, Mohammad-Taghi Golmakani, Mehrdad Niakousari, Mohammad Hadi Eskandari, Fatemeh Ghiasi, Seyed Mohammad Hashem Hosseini","doi":"10.3168/jds.2024-24140","DOIUrl":"10.3168/jds.2024-24140","url":null,"abstract":"<div><p>The effects of partial or full replacement of margarine by alginate/whey protein isolate-based olive oil emulgel on nutritional, physicochemical, mechanical, and rheological properties of processed cheese (PC) were investigated in this work. All formulated samples had the same amount of total fat, DM, and pH. According to the results of the fatty acids profile, the PC sample in which the margarine was fully replaced by the emulgel (EPC<sub>100</sub>) had the highest (49.84%) oleic acid content and showed a reduction of 23.7% in SFA compared with the control sample (EPC<sub>0</sub>; formulated just with margarine). In addition, EPC<sub>0</sub> had the highest hardness among various cheese samples, which was also confirmed by its compact microstructure. Dynamic oscillatory measurements revealed that EPC<sub>100</sub> had the highest crossover strain (or resistance to deformation). The high rigidity of this sample was related to the 3-dimensional structure of emulgel. According to the creep test results, EPC<sub>100</sub> showed the lowest relative recovery (flowability). A high temperature dependency of viscoelastic moduli was observed in EPC<sub>0</sub> at 42°C. No significant differences were observed between the color attributes and sensory properties of the various cheese samples. Alginate/whey protein isolate-based olive oil emulgel can be considered as a healthy margarine replacer in PC.</p></div>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0022030224005496/pdfft?md5=90cbdaa073c1f314ba6fdce42d97ac65&pid=1-s2.0-S0022030224005496-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140136197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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