Early Warning System of Risk in Dairy Cows with Inactive Ovaries

The incidence of Inactive ovaries of dairy cows in China is relatively high. There is no complete early warning system for the occurrence of ovarian quiescence in clinical cows. This test provides early warning indicators for clinical prediction of ovary cessation in dairy cows. This experiment selected blood samples of dairy cows from 60 to 90 days postpartum in the inactive ovaries group and control group. Differential proteins were selected on the basis of proteomics, three energy indexes: AST, Glu, NEFA. Four reproductive hormones: E2, P4, FSH, LH, and four differentially expressed proteins: IGFBP-2, AHSG, APO-A4, and RBP-4. Key enzyme activities: ALDOB, LDHB, ITIH3, GPX3, SPAM1, PKM2. The ELISA test kit was used to detect the content and activity of the above markers in the test bovine serum. Through correlation analysis, binary logistic regression modeling and ROC analysis, a single indicator early warning technique for APOA4 and ITIH3 was established. The early warning values were APOA4 > 28.825 μg/L and ITIH3 > 195.07 ng/L. A multi-index early warning system based on potential biomarkers of APOA4 + ITIH3 and APOA4 + ITIH3 + E2 was established. The former had an early warning value of: APOA4 > 19.55 μg/I; ITIH3 > 191.14 ng/L; the latter has an early warning value: APOA4 > 47.56 μg/L, ITIH4 > 187.80 ng/L, E2 < 69.63 ng/L.

At present, there is a bit research on early warning systems for common diseases in dairy cattle in China. The use of biomarkers screened by proteomics technology at home and abroad to establish a disease risk early warning system has become an important method and tool for monitoring the risk of disease.
Lin et al. [2]. Used proteomics, mass spectrometry, and ELISA methods combined with statistical receiver operating characteristic curve (ROC) analysis to screen and identify differentially expressed proteins in human nasopharyngeal carcinoma. Determination of biomarker markers. Xinhuan Xiao [3] also used a combination of proteomics and ROC analysis to determine that a protein can diagnose early postmortem ovarian quiescence in dairy cows. However, because the differential proteins screened by multiple platforms of proteomics complement each other, and ROC analysis can be used for multi-monitoring and early warning of diseases, this study has carried out multi-index joint warning of disease risk.
At present, there is no complete warning system for the occurrence of ovarian static in dairy cows. This experiment provides an early warning indicator for the prediction of ovarian static in cows.

The Level of Blood Energy Indicators
The results of the blood energy index tests of cows (CON) in the inactive ovaries group (IO) and the healthy control group are shown in Table 2.
According to the energy index test results, there was no significant difference between the two groups in AST, Glu and NEFA (p > 0.05). This shows that the energy metabolism of ovarian stationary cows is normal.

Blood Reproductive Hormone Levels
The results of the test on blood reproductive hormones of dairy cows in the ovarian static group and the healthy control group are shown in Table 3.
According to the analysis of the test results of reproductive hormones, we can see that among the four indicators of reproductive hormones detected between the two groups, there was only a significant difference between the two groups (p < 0.05). Table 4 shows the levels of 10 major differential proteins and key enzyme assays in the blood of dairy cows in the quiescent group and the healthy control group. Note: *indicates that there is a significant difference between the two groups (p < 0.05); **indicates that there is a very significant difference between the two groups (p < 0.01); if there is no shoulder note, the index is in both groups. There was no significant difference between the two groups (p > 0.05).  Note: *indicates that there is a significant difference between the two groups (p < 0.05); **indicates that there is a very significant difference between the two groups (p < 0.01); if there is no shoulder note, the index is in both groups. There was no significant difference between the two groups (p > 0.05).

The Level of Major Differential Proteins and Key Enzymes in Blood
According to the results of key differential proteins and key enzyme assays, APOA4, ALDOB, and ITIH3 were significantly different between the two groups (p < 0.01). The ovarian quiescence group was higher than the healthy control group; AHSG and RBP4 existed between the two groups. Significant difference (p < 0.05).

Correlation Analysis of Energy Index, Reproductive Hormones and Key Different Proteins, Key Enzymes, and Occurrence of Ovarian Metastasis
The results of all testing indicators were analyzed using the Pearson correlation coefficient in the statistical analysis software. The results of the analysis were shown in Table 5.

The Establishment of Binary Logistic Regression and the Determination of Early Warning Indicators
According to the classification of relevant detection indicators, two modules were established to perform binary logistic regression on the data to determine the degree of regression fit and the determination of early warning indicators.

1) Model I
Model I is mainly based on the results of serum reproductive hormone indicators for the determination of binary logistic regression and early warning indicators. According to Table 6, the chi-square of the model is 4.841. According to the significance (0.05) and the degree of freedom (df), the chi-squared value can be calculated using the CHIINV (significance, degree of freedom) in EXCEL.
The settlement is CHIINV (0.05, 8) = 15.507 and the chi-square statistic is less than the critical value of the chi-square.
According to the analysis results in Table 7, the model has a good prediction According to the analysis results in Tables 8-9, if the variable E2 is removed from the model, the significance of the change is 0015 < 0.05. This shows that E2 is significantly associated with prevention of ovarian quiescence and cannot be removed.

2) Model II
Model II determines the binary logistic regression and early warning indicators based on the results of serum key differentiating proteins and key enzymes (Table 10).
According to the analysis results in Table 11, it can be seen that APOA4 is better for warning to healthy cows than ovary stationary cows; after adding GPX3, both groups of warnings are improved, the total percentage is 80%; and further progress in adding RBP4 will reduce the early warning effect. 78.6%; further progress in joining ITIH3 resulted in a noticeable increase in early warning effectiveness, both at 80%; and finally at SPAM1, the total percentage of Table 6. Hosmer and Leme show test.
Step Bangla df Sig.

Risk Warning System of Single Indicator
In this experiment, ROC analysis was performed on the above-mentioned early warning indicators, and the Youden value was calculated based on the experimental results. Youden = sensitivity + specificity − 1. Select the critical value of the indicator based on the Youden value. The results are shown in Table 14, and the ROC analysis curve is shown in Figure 1.

Multiple Indicators Joint Risk Early Warning System
According to the single-indicator warning results, although 8 indicators can provide early warning of ovarian inactivity, in order to explore better warning   Note: E2 is estradiol; APOA4 is apolipoprotein 4; RBP4 is retinol binding protein 4; ITIH3 is Inter-α-trypsin inhibitor heavy chain H3; GPX3 is glutathione peroxidase; SPAM1 Hyaluronidase.  Table 15, and the ROC analysis chart is shown in  Note: Due to the fact that the area under the curve of some prediction results is the same, multiple analytical curves overlap. APOA4 is apolipoprotein 4; ITIH3 is Inter-α-trypsin inhibitor heavy chain H3; E2 is estradiol; SPAM1 is hyaluronidase; RBP4 is retinol binding protein 4; GPX3 is glutathione Oxide enzyme.

Discussion
Ovarian quiescence in cows is usually diagnosed by estrus identification 50 -60 days after childbirth. The estrus identification method is usually to observe the estrus detection, rectal examination and B-ultrasound, and then use hormones to treat ovarian static cows. The existing problems: 1) The diagnosis of ovarian static is mostly after the occurrence; 2) The rectal examination is more stressful to dairy cows and does not meet the animal welfare requirements; 3) Hormone treatment after ovarian static, the effect is not the same, dairy hormones Residues. In view of the above-mentioned problems of quiescence in the ovaries, this study carried out early warning and analysis of the risk of ovarian static in cows from the aspects of mineral elements, energy indexes, reproductive hormones, and major differential proteins and key enzymes.
In a single indicator early warning, APOA4 and ITIH3 have a better warning effect on the risk of ovarian static. APOA4 + ITIH3 and APOA4 + ITIH3 + E2 have a better warning effect on the risk of ovarian static in multi-index early warning. It is well-known that E2 is a reproductive hormone and is directly related to ovarian disease. However, APOA4 and ITIH3, as representative substances of lipids and enzymes, have a prewarning effect on a single indicator or multi-indicator combination of ovarian static, suggesting their potential role in ovarian function and its application value.
APOA4 is a member of the apolipoprotein A1/C3/A4/A5 gene cluster [4]. Inter-α-trypsin inhibitor (ITI) is a blood-derived protein necessary for reproduction in females. It consists of two heavy chains (HC2 and HC3) and core protein bikunin [5]. ITIH3 can be used as a carrier of hyaluronic acid in serum or as a binding protein between hyaluronic acid and other matrix proteins to regulate the localization, synthesis, and degradation of hyaluronan necessary for cells. The only function of Bikunin in binding to ITIH3 is covalent attachment to hyaluronic acid [6], which is the main component of the extracellular matrix (ECM) but is also secreted into body fluids such as blood and lymph [7]. This is the reason for the detection of ITIH3 in the blood [8]. Hyaluronic acid is a high molecular weight glycosaminoglycan that exists in the ECM with high molecular weight and high hydrophilicity. The complex of serum-derived hyaluronan-associated protein (SHAP) and hyaluronic acid is bound to hyaluronic acid via the ester bond in bikunin [9]. However, no bikunin was found in the purified complex, indicating that it was released during complex formation. Studies have shown that hyaluronic acid and ITI were detected during granulocyte expansion, suggesting that ITI is important during follicular growth [10]. It is speculated that in the development of follicles, the body produces bikunin to bind ITIH3, which in turn binds hyaluronic acid, which in turn promotes the growth of follicles.

Conclusion
Based on the correlation analysis, binary logistic regression, and ROC analysis, this experiment established a single early warning index and early warning value of post-natal ovarian rest risk based on APOA4 and ITIH3; established the risk of ovarian static based on APOA4 + ITIH4 + E2 A number of early warning indicators and their early warning values; established a single index and multiple indicator early warning system for the occurrence of post-natal ovarian static in dairy cows, providing a methodological basis for future prediction of post-natal ovarian static in dairy cows.