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短篇交流:牛奶中红外预测生物标志物与泌乳后期跛行事件之间的时相关系的研究。

Short communication: Investigation of the temporal relationships between milk mid-infrared predicted biomarkers and lameness events in later lactation.

机构信息

TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.

Centre Wallon de Recherches Agronomiques (CRA-W), 5030 Gembloux, Belgium.

出版信息

J Dairy Sci. 2020 May;103(5):4475-4482. doi: 10.3168/jds.2019-16826. Epub 2020 Feb 26.

Abstract

This study reports on the exploration of temporal relationships between milk mid-infrared predicted biomarkers and lameness events. Lameness in dairy cows is an issue that can vary greatly in severity and is of concern for both producers and consumers. Metabolic disorders are often associated with lameness. However, lameness can arise weeks or even months after the metabolic disorder, making the detection of causality difficult. We already use mid-infrared technology to predict major milk components, such as fat or protein, during routine milk recording and for milk payment. It was recently shown that this technology can also be used to predict novel biomarkers linked to metabolic disorders in cows, such as oleic acid (18:1 cis-9), β-hydroxybutyrate, acetone, and citrate in milk. We used these novel biomarkers as proxies for metabolic issues. Other studies have explored the possibility of using mid-infrared spectra to predict metabolic diseases and found it (potentially) usable for indicating classes of metabolic problems. We wanted to explore the possible relationship between mid-infrared-based metabolites and lameness over the course of lactation. In total, data were recorded from 6,292 cows on 161 farms in Austria. Lameness data were recorded between March 2014 and March 2015 and consisted of 37,555 records. Mid-infrared data were recorded between July and December 2014 and consisted of 9,152 records. Our approach consisted of fitting preadjustments to the data using fixed effects, computing pair-wise correlations, and finally applying polynomial smoothing of the correlations for a given biomarker at a certain month in lactation and the lameness events scored on severity scale from sound or non-lame (lameness score of 1) to severely lame (lameness score of 5) throughout the lactation. The final correlations between biomarkers and lameness scores were significant, but not high. However, for the results of the present study, we should not look at the correlations in terms of absolute values, but rather as indicators of a relationship through time. When doing so, we can see that metabolic problems occurring in mo 1 and 3 seem more linked to long-term effects on hoof and leg health than those in mo 2. However, the quantity (only 1 pair-wise correlation exceeded 1,000 observations) and the quality (due to limited data, no separation according to more metabolic-related diseases could be done) of the data should be improved.

摘要

本研究报告了牛奶中中红外预测生物标志物与跛行事件之间时间关系的探索。奶牛跛行是一个严重程度差异很大的问题,不仅生产者关注,消费者也关注。代谢紊乱通常与跛行有关。然而,跛行可能在代谢紊乱发生后数周甚至数月才出现,这使得因果关系的检测变得困难。我们已经使用中红外技术在常规牛奶记录和牛奶支付时预测主要牛奶成分,如脂肪或蛋白质。最近表明,该技术还可用于预测与奶牛代谢紊乱相关的新型生物标志物,如油酸(18:1cis-9)、β-羟丁酸、丙酮和柠檬酸。我们使用这些新型生物标志物作为代谢问题的替代物。其他研究探索了使用中红外光谱预测代谢疾病的可能性,并发现它(可能)可用于指示代谢问题的类别。我们希望探索泌乳过程中基于中红外的代谢物与跛行之间的可能关系。总共,在奥地利的 161 个农场中,有 6292 头奶牛记录了数据。跛行数据记录于 2014 年 3 月至 2015 年 3 月之间,共有 37555 条记录。中红外数据记录于 2014 年 7 月至 12 月之间,共有 9152 条记录。我们的方法包括使用固定效应对数据进行预调整,计算成对相关性,最后对给定生物标志物在泌乳某个月的相关性进行多项式平滑,并根据跛行严重程度评分(从声音或非跛行(跛行评分 1)到严重跛行(跛行评分 5))在整个泌乳期进行评分。生物标志物与跛行评分之间的最终相关性是显著的,但不是很高。然而,对于本研究的结果,我们不应该根据绝对值来看待相关性,而应该将其视为时间关系的指标。这样做,我们可以看到,1 月和 3 月发生的代谢问题似乎与蹄和腿部健康的长期影响更相关,而 2 月发生的代谢问题则不然。然而,数据的数量(只有一对相关性超过 1000 个观测值)和质量(由于数据有限,无法根据更多与代谢相关的疾病进行分离)都需要改进。

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