Ultrasonographic measurement of liver, portal vein, hepatic vein and perivisceral adipose tissue in high-yielding dairy cows with fatty liver during the transition period

Serum macroelements and microelements levels in periparturient dairy cows in relation to fatty liver diseases

BACKGROUND

Fatty liver in dairy cows is a common metabolic disease defined by triglyceride (TG) buildup in the hepatocyte. Clinical diagnosis of fatty liver is usually done by liver biopsy, causing considerable economic losses in the dairy industry owing to the lack of more effective diagnostic methods. Therefore, this study aimed to investigate the potential utility of blood biomarkers for the diagnosis and early warning of fatty liver in dairy cows.

RESULTS

A total of twenty-four lactating cows within 28 days after parturition were randomly selected as experimental animals and divided into healthy cows (liver biopsy tested, n = 12) and cows with fatty liver (liver biopsy tested, n = 12). Inductively coupled plasma mass spectrometry (ICP-MS) was used to determine the macroelements and microelements in the serum of two groups of cows. Compared to healthy cows (C), concentrations of calcium (Ca), potassium (K), magnesium (Mg), strontium (Sr), selenium (Se), manganese (Mn), boron (B) and molybdenum (Mo) were lower and copper (Cu) was higher in fatty liver cows (F). Meanwhile, the observed differences in macroelements and microelements were related to delivery time, with the greatest major disparity between C and F occurring 7 days after delivery. Multivariable analysis was used to test the correlation between nine serum macroelements, microelements and fatty liver. Based on variable importance projection and receiver operating characteristic (ROC) curve analysis, minerals Ca, Se, K, B and Mo were screened as the best diagnostic indicators of fatty liver in postpartum cows.

CONCLUSIONS

Our data suggested that serum levels of Ca, K, Mg, Se, B, Mo, Mn, and Sr were lower in F than in C. The most suitable period for an early-warning identification of fatty liver in cows was 7 days after delivery, and Ca, Se, K, B and Mo were the best diagnostic indicators of fatty liver in postpartum cows.

Near-infrared spectroscopy analysis of blood plasma for predicting nonesterified fatty acid concentrations in dairy cows

During the transition period, dairy cows are often exposed to negative energy balance (NEB), leading to lipid mobilization from adipose tissue into nonesterified fatty acids (NEFA), a common indicator of heightened illness risk. This study aimed to use blood near-infrared (NIR) spectra data to classify NEB into high or low categories, based on early-lactation cow NEFA thresholds. We collected a total of 186 plasma samples from 100 Holstein cows. The samples were categorized into critical thresholds, based on previous literature, of ≥0.60 and ≥0.70 mEq/L for identifying high NEB. Spectral data were preprocessed before the development of the predictive modes, which included the implementation of multiplicative scatter correction, standard normal variate (SNV), and first and second derivatives. The classification was performed using partial least square discriminant analyses (PLS-DA), and predictive performance was assessed using leave-one-out cross-validation. Predictive quality for each class was evaluated through specificity, precision, sensitivity, and F1 score. The study showed promising results, with the SNV technique achieving higher F1 scores. The model found 72.7% specificity, 78.9% precision, 80.8% sensitivity, and 79.8% F1 score to classify animals with NEFA levels of ≥0.60 mEq/L, and 82.1% specificity, 78.7% precision, 80.8% sensitivity, and 79.7% F1 score to classify animals with NEFA levels ≥0.70 mEq/L. These results indicate that NIR spectroscopy could serve as a tool for detecting cows under severe NEB, also showing potential for broader application across the entire transition period, as the spectral signal carried relevant information regarding cow metabolism. Furthermore, the combination of predictors derived from plasma spectra and other cow-level information can lead to more accurate disease alerts, given their relationship with the NEB.

Colour Doppler study of blood flow in the portal vein in relation to blood flow in the milk vein, milk yield and body condition of dairy cows during dry period and lactation

In dairy cows, the liver supports the increased nutrient demands of the udder for milk production. Blood flow is key for the transport of these nutrients. This study investigated portal vein blood flow volume (PVBFVol) in relation to daily milk yield (DMY), milk vein blood flow volume (MVBFVol) and body condition parameters of high-producing dairy cows, starting from late lactation, throughout dry period, and consecutive early lactation. Seventeen repeated examinations were performed on 19 Holstein cows and 313 measurement days were finally included. Vein morphology and blood flow were examined via B-mode and spectral Doppler (triplex) ultrasonography, respectively. Body condition parameters recorded were body condition score (BCS), backfat thickness (BFT) measurement with ultrasonography, heart girth circumference (HG) and withers height (WH). Longitudinal relationship of PVBFVol with MVBFVol, DMY, BCS, BFT, HG and WH was analyzed with linear mixed models, with random intercept effects, using restricted cubic splines. A significant increase of 8.28% (p < 0.01) in PVBFVol appeared for every 1 L/min increase in MVBFVol in the univariable model. PVBFVol presented a significant negative association with BCS (p < 0.01) and BFT (p = 0.02), while interaction with production stage was significant, too. PVBFVol significantly increased by 0.38% (p = 0.04) for every 1 kg increase in DMY in the multivariable model. In conclusion, the increased PVBFVol during lactation accompanies the escalation in metabolic activity of the liver and the increased blood circulation through the udder, coping with the udder's escalating nutrient demands for milk synthesis.

Associations between the detailed milk mineral profile, milk composition, and metabolic status in Holstein cows

The causes of variation in the milk mineral profile of dairy cattle during the first phase of lactation were studied under the hypothesis that the milk mineral profile partially reflects the animals' metabolic status. Correlations between the minerals and the main milk constituents (i.e., protein, fat, and lactose percentages), and their associations with the cows' metabolic status indicators were explored. The metabolic status indicators (MET) that we used were blood energy-protein metabolites [nonesterified fatty acids, β-hydroxybutyrate (BHB), glucose, cholesterol, creatinine, and urea], and liver ultrasound measurements (predicted triacylglycerol liver content, portal vein area, portal vein diameter and liver depth). Milk and blood samples, and ultrasound measurements were taken from 295 Holstein cows belonging to 2 herds and in the first 120 d in milk (DIM). Milk mineral contents were determined by ICP-OES; these were considered the response variable and analyzed through a mixed model which included DIM, parity, milk yield, and MET as fixed effects, and the herd/date as a random effect. The MET traits were divided in tertiles. The results showed that milk protein was positively associated with body condition score (BCS) and glucose, and negatively associated with BHB blood content; milk fat was positively associated with BHB content; milk lactose was positively associated with BCS; and Ca, P, K and S were the minerals with the greatest number of associations with the cows' energy indicators, particularly BCS, predicted triacylglycerol liver content, glucose, BHB and urea. We conclude that the protein, fat, lactose, and mineral contents of milk partially reflect the metabolic adaptation of cows during lactation and within 120 DIM. Variations in the milk mineral profile were consistent with changes in the major milk constituents and the metabolic status of cows.

Hemato-biochemical and ultrasonographic evaluation of hepatic lipidosis in dairy buffaloes

Around 60% dairy animals developed moderate to severe hepatic lipidosis at the time of parturition or during early lactation stage. Most of clinician suspect the hepatic lipidosis during above time window only. However, negative energy balance or feeding of high concentrate diet can lead to hepatic lipidosis at any phase of life. The aim of the present study was to evaluate the potential for diagnosis of hepatic lipidosis by means of hemato-biochemical parameters and ultrasonography of the liver at any stage of life. Here, ultrasonographic back fat thickness measurement was correlated with ultrasonographic features of hepatic lipidosis. A total 60 buffaloes were included under the study and sampled for hematological and biochemical parameters. Hematological parameters did not exhibit any significant difference between healthy and hepatic lipidosis-affected buffaloes. Biochemical parameters like beta hydroxy butyric acid, non esterified fatty acid, aspartate amino transferase, gamma glutamyl transferase and alkaline phosphatase revealed a significant increase, while triglyceride, cholesterol, and glucose declined significantly in hepatic lipidosis-affected buffaloes. Total protein, albumin, and total bilirubin levels did not exhibit any significant difference. Based on ultrasonographic findings, the hepatic lipidosis-affected buffaloes were further sub divided into mild, moderate, and severe groups. Portal vein diameter and depth of portal vein were also estimated in current study. Ultrasonographic examination could diagnose 53.33% hepatic lipidosis cases in buffaloes. Among it, 37.50% buffalo had mild hepatic lipidosis, 33.33% had moderate hepatic lipidosis, and 29.16% had severe hepatic lipidosis. Depth of portal vein significantly increased in hepatic lipidosis cases. However, portal vein diameter exhibited a non-significant difference in mild, moderate, and severe groups of hepatic lipidosis. Back fat thickness also revealed a non-significant difference in mild, moderate, and severe hepatic lipidosis. Above study indicate that B mode ultrasonography of the liver can be employed to differentiate various grades of hepatic lipidosis in buffaloes. Biochemical parameters like NEFA, BHBA, AST, GGT, ALP, TG, cholesterol, and glucose can be helpful to screen the hepatic lipidosis at farm level.

Associations between Milk Fatty Acid Profile and Body Condition Score, Ultrasound Hepatic Measurements and Blood Metabolites in Holstein Cows

Dairy cows have high incidences of metabolic disturbances, which often lead to disease, having a subsequent significant impact on productivity and reproductive performance. As the milk fatty acid (FA) profile represents a fingerprint of the cow’s nutritional and metabolic status, it could be a suitable indicator of metabolic status at the cow level. In this study, we obtained milk FA profile and a set of metabolic indicators (body condition score, ultrasound liver measurements, and 29 hematochemical parameters) from 297 Holstein–Friesian cows. First, we applied a multivariate factor analysis to detect latent structure among the milk FAs. We then explored the associations between these new synthetic variables and the morphometric, ultrasonographic and hematic indicators of immune and metabolic status. Significant associations were exhibited by the odd-chain FAs, which were inversely associated with β-hydroxybutyrate and ceruloplasmin, and positively associated with glucose, albumin, and γ-glutamyl transferase. Short-chain FAs were inversely related to predicted triacylglycerol liver content. Rumen biohydrogenation intermediates were associated with glucose, cholesterol, and albumin. These results offer new insights into the potential use of milk FAs as indicators of variations in energy and nutritional metabolism in early lactating dairy cows.

Associations between ultrasound measurements and hematochemical parameters for the assessment of liver metabolic status in Holstein-Friesian cows

Metabolic disorders, including hepatic lipidosis and ketosis, severely affect animal health status and welfare with a large economic burden in dairy herds. The gold standard for diagnosing hepatic lipidosis is the liver biopsy, which is impractical and invasive for the screening at farm level. Ultrasound (US) imaging is a promising technique for identifying liver dysfunction, but standardized specifications in physiological conditions are needed. Herein, we described the features of four US measurements, namely the liver predicted triacylglycerol (pTAG) content, liver depth (LD), and portal vein area (PVA) and depth (PVD) and we investigated their associations with a set of hematochemical (HC) indicators in 342 clinically healthy Holstein Friesian dairy cows. Liver pTAG content was negatively associated with hematocrit and positively with globulin, whereas PVA was negatively associated with thiol group levels, and LD positively with ceruloplasmin. We found significant interactions between some HC parameters and parity: in particular, creatinine, thiol groups and globulin for PVA, and aspartate aminotransferase, paraoxonase and ceruloplasmin for PVD. This study offers new insights on variations in liver function occurring after calving and pave the way for the potential use of minimally invasive techniques for prompt detection of metabolic disorders in dairy herds.

Application of Ultrasound Images Texture Analysis for the Estimation of Intramuscular Fat Content in the Longissimus Thoracis Muscle of Beef Cattle after Slaughter: A Methodological Study

Simple Summary

Fat content in the muscle mass (IMF) is one of the most important characteristics influencing the aroma, tenderness, and juiciness of the meat and therefore has high importance for both commercialization purposes and consumers. However, IMF determination currently relies on visual inspection, which is a subjective and inconsistent technique. The aim of the present study is the elaboration of a procedure capable of predicting IMF% in beef carcasses using ultrasound imaging texture analysis. Ultrasound images taken on meat samples were compared to meat composition measured by chemical extraction. Determination coefficient between the two techniques was R² = 0.76, while Receiver Operating Characteristic analysis showed a sensitivity of 88% and a specificity of 90%. The results therefore suggest that the described procedure is expected to determine IMF% in muscle with good accuracy. Ultrasound imaging could be applied in routine beef grading practices. This may help to solve the issues related to subjectivity and leave to the operator only imaging acquisition. Better consistency in beef products could enhance consumers’ satisfaction and commercial standardization programs.

Abstract

Intramuscular fat (IMF) is a major trait in the evaluation of beef meat, but its determination is subjective and inconsistent and still relies on visual inspection. This research objective was a method to predict IMF% from beef meat using ultrasound (US) imaging texture analysis. US images were performed on the longissimus thoracis muscle of 27 Charolaise heifers. Cuts from the 12th to 13th ribs were scanned. The lipid content of the muscle samples was determined with the petrol ether (Randall) extraction method. A stepwise linear discriminant analysis was used to screen US texture parameters. IMF% measured by chemical extraction (IMFqa) was the dependent variable and the results of the texture analysis were the explanatory variables. The model highlighted seven parameters, as a predictive and a multiple regression equation was created. Prediction of IMF content (IMFpred) was then validated using IMFqa as ground truth. Determination coefficient between IMFqa and IMFpred was R² = 0.76, while the ROC analysis showing a sensitivity of 88% and a specificity of 90%. Bland-Altman plot upper and lower limit were +1.34 and −1.42, respectively (±1.96 SD), with a mean of −0.04. The results from the present study therefore suggest that prediction of IMF content in muscle mass by US texture analysis is possible.

Gain and loss of subcutaneous and abdominal adipose tissue depot mass of German Holstein dairy cows with different body conditions during the transition period

Subcutaneous adipose tissue (SCAT) and abdominal adipose tissue (AAT) depots are mobilized during the fresh cow period (FCP) and early lactation period (ELP) to counteract the negative energy balance (NEB). Earlier studies suggested that fat depots contribute differently to lipomobilization and may vary in functionality. Differences between the adipose depots might influence the development of metabolic disorders. Thus, the gain and loss of subcutaneous and abdominal adipose depot masses in Holstein cows with lower and higher body condition (mean body condition scores: 3.48 and 3.87, respectively) were compared in the period from d -42 to d 70 relative to parturition in this study. Animals of the 2 experimental groups represented adequately conditioned and overconditioned cows. Estimated depot mass (eDM) of SCAT, AAT, retroperitoneal, omental, and mesenteric adipose depots of 31 pluriparous German Holstein cows were determined via ultrasonography at d -42, 7, 28, and 70 relative to parturition. The cows were grouped according to the eDM of SCAT on d -42 [low body condition (LBC) group: n = 16, mean eDM 8.6 kg; high body condition (HBC) group: n = 15, mean eDM 15.6 kg]. Average daily change (prepartum gain and postpartum loss) in depot masses during dry period (DP; from d -42 to d 7), FCP (d 7 to d 28), and ELP (d 28 to d 70) were calculated and daily dry matter intake and lactation performance recorded. Cows of this study stored about 2 to 3 times more fat in AAT than in SCAT depots. After parturition, on average more adipose tissue mass was lost from the AAT than the SCAT depot (0.23 kg/d vs. 0.14 kg/d). Cows with high compared with low body condition had similar gains in AAT (0.33 kg/d) and SCAT (0.14 kg/d) masses during the DP but mobilized significantly more adipose tissue mass from both depots after calving (AAT, HBC vs. LBC: 0.30 vs. 0.17 kg/d; SCAT, HBC vs. LBC: 0.19 vs. 0.10 kg/d). Correlation analysis indicated a functional disparity between AAT and SCAT. In the case of AAT (R² = 0.36), the higher the gain in adipose mass during DP, the higher the loss in FCP, but this was not the case for SCAT. During FCP, a greater NEB resulted in greater loss of mass from SCAT (R² = 0.18). In turn, greater mobilization of SCAT mass led to a higher calculated feed efficiency (R² = 0.18). However, AAT showed no such correlations. On the other hand, during ELP, loss of both SCAT and AAT mass correlated positively with feed efficiency (R² = 0.35 and 0.33, respectively). The results indicate that feed efficiency may not be an adequate criterion for performance evaluation in cows during NEB. Greater knowledge of functional disparities between AAT and SCAT depots may improve our understanding of excessive lipomobilization and its consequences for metabolic health and performance of dairy cows during the transition period.

Application of texture analysis of b-mode ultrasound images for the quantification and prediction of intramuscular fat in living beef cattle: A methodological study

Intramuscular fat (IMF) contributes significantly to the aroma and tenderness of the meat, therefore playing a key role in quality determination. Yet, IMF determination methods rely on visual inspection or on fat extraction from meat samples after animals' slaughter. The aim of this methodological study was the elaboration of a process capable of predicting IMF% using real-time ultrasound (RTU) images in live beef cattle. The longissimus dorsi (LD) muscle of 26 Charolaise heifers was investigated. In vivo ultrasound images were taken and texture analysis was performed. One week after the animals' slaughter, the whole twelfth rib cut was collected, and IMF% was determined by extraction with petrol ether (Randall) method. Animals were divided in 3 groups depending on their mean lipid content percentage in 100 g meat (Group 1: IMF ≤ 4.24%; Group 2: 4.25% ≤ IMF ≤ 5.75%; Group 3: IMF ≥ 5.76%). Texture parameters were selected by a stepwise linear discriminant analysis using IMF% measured by chemical extraction (IMFqa) as the dependent variable, and the results of the texture analysis as explanatory variables. 6 variables were found predictive and molded into a multiple regression equation, this equation was then validated using IMFqa as ground truth. A high linear correlation between IMFqa and IMFpred was evident (r² = 0.8504), ROC analysis perfomed on IMFpred comparing it to IMFqa showed a sensitivity of 80% and a specificity of 93.7%, while results from the Bland-Altman plot were ± 1.96 (±1.11SD).