ABSTRACT
Among the dairy sector's current concerns, the assessment of global animal health status is a complex challenge. Its multidimensionality means that global monitoring tools are rarely considered. Instead, specific disease detection is often studied separately and, due to financial and ethical issues, uses small-scale data sets focusing on few biomarkers. Several studies have already been conducted using milk Fourier transform mid-infrared (FT-MIR) spectroscopy to detect mastitis and lameness or to quantify health-related biomarkers in milk or blood. Those studies are relevant but they focus mainly on one biomarker or disease. To solve this issue and the small-scale data set, in this study, we proposed a holistic approach using big data obtained from milk recording, including milk yield, somatic cell count, and 27 FT-MIR-based predictors related to milk composition and animal health status. Using 740,454 records collected from 114,536 first-parity Holstein cows in southern Belgium, we performed repeated unsupervised learning algorithms based on Ward's agglomerative hierarchical clustering method to find potential interesting patterns. A divide-and-conquer approach was used to overcome the limitation of computational resources in clustering a relatively large data set. Five groups of records were identified. Differences observed in the fourth group suggested a relationship to metabolic disorders. The fifth group seemed to be related to mastitis. In a second step, we performed a partial least squares discriminant analysis (PLS-DA) to predict the probability of belonging to those specific groups for the entire data set. The obtained global accuracy was 0.77 and the balanced accuracy (i.e., the mean between sensitivity and specificity) of discriminating the fourth and fifth groups was 0.88 and 0.96, respectively. Then, a validation of the interpretation of those groups was performed using 204 milk and blood reference records. The predicted probability associated with the metabolic disorders issue had significant correlations of 0.54 with blood ß-hydroxybutyrate, 0.44 with blood nonesterified fatty acids, -0.32 with blood glucose, -0.23 with milk glucose-6-phosphate, and 0.38 with milk isocitrate. In contrast, the predicted probability of belonging to the mastitis group had correlations of 0.69 with milk lactate dehydrogenase, 0.46 with milk N-acetyl-ß-d-glucosaminidase, -0.18 with milk free glucose, and 0.16 with milk glucose-6-phosphate. Consequently, these results suggest that the obtained quantitative traits indirectly reflect some of the main health disorders in dairy farming and could be used to monitor dairy cows on a large scale. By using unsupervised learning on large-scale milk recording data and then validating the pattern using reference laboratory measures, we propose a new approach to quickly assess dairy cow health status.
Subject(s)
Cattle Diseases , Mastitis , Animals , Big Data , Biomarkers , Cattle , Female , Glucose-6-Phosphate , Lactation , Mastitis/veterinary , Pregnancy , Unsupervised Machine LearningABSTRACT
STUDY QUESTION: Is the pain associated with levonorgestrel-releasing intrauterine system (LNG-IUS) insertion reduced by intracervical anesthesia in women without previous vaginal birth? SUMMARY ANSWER: Intracervical anesthesia was not associated with reduced pain in women without previous vaginal birth. WHAT IS KNOWN ALREADY: The pain associated with the insertion of intrauterine contraceptives (IUCs) is a limiting factor for the use of these contraceptives by some women. No prophylactic pharmacological intervention has proven efficacy in relieving pain during or after the insertion of IUCs. However, previous studies included women with previous vaginal delivery, and injectable intracervical anesthesia was not evaluated in any of these studies. STUDY DESIGN, SIZE, DURATION: This was a randomized, open, parallel-group clinical trial that evaluated 100 women without previous vaginal delivery who wished to use the LNG-IUS for the first time. These women were evaluated immediately after LNG-IUS insertion and then 2 h and 6 h later. PARTICIPANTS/MATERIALS, SETTING, METHODS: The 100 women were randomized into two groups: (i) use of a non-steroidal anti-inflammatory drug (NSAID) (ibuprofen, 400 mg) 1 h prior to LNG-IUS insertion; or (ii) 2% lidocaine intracervical injection 5 min prior to LNG-IUS insertion. The women were evaluated immediately after LNG-IUS insertion and then 2 h and 6 h after insertion. Two pain scales were used (the visual analogue scale and the facial pain scale) in addition to assessing the ease of insertion (as rated by the provider) and the level of discomfort during the procedure (as rated by the patient). Multivariate logistic regression was performed to analyze the predictors associated with moderate/severe pain. MAIN RESULTS AND THE ROLE OF CHANCE: The pain and discomfort associated with LNG-IUS insertion, and the ease of insertion of the LNG-IUS did not differ between the groups. Nulliparity was more associated with moderate/severe pain [adjusted odds ratio (OR): 3.1 (95% confidence interval (CI): 1.3-7.80]. Injectable intracervical anesthesia use reduced the risk of moderate/severe pain by 40% [adjusted OR: 0.6 (95% CI: 0.2-1.4)]. The difference between the mean pain score in the intracervical anesthesia group and the NSAID group was <10%; thus, the effect size of the intervention was not significant. LIMITATIONS, REASONS FOR CAUTION: Intracervical anesthesia was compared with an oral medication in this study. Intracervical injection of a saline solution or even a dry needling as the placebo for a double-blind study could be a more adequate control; however, this approach was not a protocol approved by the institutional review board. Considering that the majority of the insertions were easy (>80% in both groups), the results may not be extrapolated to difficult insertions with moderate/severe pain where local anesthesia may have a role. WIDER IMPLICATIONS OF THE FINDINGS: The findings can be generalized to most insertions in nulliparous women or in those without a previous vaginal delivery. There is currently no evidence to recommend the routine use of prophylactic intracervical anesthesia prior to LNG-IUS insertion; there is no evidence that this treatment reduces insertion-related pain. STUDY FUNDING/COMPETING INTERESTS: RAF and CSV give occasional lectures for Bayer Healthcare. This study received funding from the National Institute of Hormones and Women's Health, National Council for Scientific and Technological Development (CNPq). TRIAL REGISTRATION NUMBER: NCT02155166.
Subject(s)
Anesthetics, Local/therapeutic use , Anti-Inflammatory Agents, Non-Steroidal/therapeutic use , Cervix Uteri/drug effects , Intrauterine Devices, Medicated/adverse effects , Lidocaine/therapeutic use , Pain/drug therapy , Adult , Anesthetics, Local/administration & dosage , Female , Humans , Levonorgestrel/administration & dosage , Lidocaine/administration & dosage , Middle Aged , Pain/etiology , Pain Measurement , Treatment OutcomeABSTRACT
AIMS: To assess the effect of different concentrations of gossypol (0, 2, 4, 10 and 20 mg l(-1)) in combination with NaCl and Na(2)SO(4) (20 mS cm(-1)) on the conidial germination and viability of Fusarium oxysporum f.sp. vasinfectum (Fov). METHODS AND RESULTS: A multinomial logistic model was developed to estimate the germination probability of Fov. The inhibitory effect was markedly evident at the two highest concentrations of gossypol; it varied among the isolates tested and with time, and it was attenuated by the presence of sodium salts. The inhibition was temporary as the germination probability increased after 8 h. Fluorescent staining revealed that gossypol either killed the conidia or retarded the elongation of the germ tubes. CONCLUSION: Fov showed the ability to overcome gossypol inhibition over time, and the inhibitory effect is reduced under saline conditions. Differential responses among Fov isolates to the presence of gossypol suggest that gossypol tolerance is genetically determined in the pathogen. SIGNIFICANCE AND IMPACT OF THE STUDY: This study suggests that selecting for high plant gossypol cultivars would have minimal effect on the overall Fov resistance of cotton. A new statistical model was developed to explore the statistical significance of plant-pathogen interactions.