Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Determinants of outcome in critically ill patients

Assessment of the outcome of critical illness is complex. Severity scoring systems and organ dysfunction scores are traditional tools in mortality and morbidity prediction in intensive care. Their ability to explain risk of death is impressive for large cohorts of patients, but insufficient for an individual patient. Although events before intensive care unit (ICU) admission are prognostically important, the prediction models utilize data collected at and just after ICU admission. In addition, several biomarkers have been evaluated to predict mortality, but none has proven entirely useful in clinical practice. Therefore, new prognostic markers of critical illness are vital when evaluating the intensive care outcome. The aim of this dissertation was to investigate new measures and biological markers of critical illness and to evaluate their predictive value and association with mortality and disease severity. The impact of delay in emergency department (ED) on intensive care outcome, measured as hospital mortality and health-related quality of life (HRQoL) at 6 months, was assessed in 1537 consecutive patients admitted to medical ICU. Two new biological markers were investigated in two separate patient populations: in 231 ICU patients and 255 patients with severe sepsis or septic shock. Cell-free plasma DNA is a surrogate marker of apoptosis. Its association with disease severity and mortality rate was evaluated in ICU patients. Next, the predictive value of plasma DNA regarding mortality and its association with the degree of organ dysfunction and disease severity was evaluated in severe sepsis or septic shock. Heme oxygenase-1 (HO-1) is a potential regulator of apoptosis. Finally, HO-1 plasma concentrations and HO-1 gene polymorphisms and their association with outcome were evaluated in ICU patients. The length of ED stay was not associated with outcome of intensive care. The hospital mortality rate was significantly lower in patients admitted to the medical ICU from the ED than from the non-ED, and the HRQoL in the critically ill at 6 months was significantly lower than in the age- and sex-matched general population. In the ICU patient population, the maximum plasma DNA concentration measured during the first 96 hours in intensive care correlated significantly with disease severity and degree of organ failure and was independently associated with hospital mortality. In patients with severe sepsis or septic shock, the cell-free plasma DNA concentrations were significantly higher in ICU and hospital nonsurvivors than in survivors and showed a moderate discriminative power regarding ICU mortality. Plasma DNA was an independent predictor for ICU mortality, but not for hospital mortality. The degree of organ dysfunction correlated independently with plasma DNA concentration in severe sepsis and plasma HO-1 concentration in ICU patients. The HO-1 -413T/GT(L)/+99C haplotype was associated with HO-1 plasma levels and frequency of multiple organ dysfunction. Plasma DNA and HO-1 concentrations may support the assessment of outcome or organ failure development in critically ill patients, although their value is limited and requires further evaluation.

New approaches to improve the cord blood unit hematopoietic progenitor cell content

Cord blood is a well-established alternative to bone marrow and peripheral blood stem cell transplantation. To this day, over 400 000 unrelated donor cord blood units have been stored in cord blood banks worldwide. To enable successful cord blood transplantation, recent efforts have been focused on finding ways to increase the hematopoietic progenitor cell content of cord blood units. In this study, factors that may improve the selection and quality of cord blood collections for banking were identified. In 167 consecutive cord blood units collected from healthy full-term neonates and processed at a national cord blood bank, mean platelet volume (MPV) correlated with the numbers of cord blood unit hematopoietic progenitors (CD34+ cells and colony-forming units); this is a novel finding. Mean platelet volume can be thought to represent general hematopoietic activity, as newly formed platelets have been reported to be large. Stress during delivery is hypothesized to lead to the mobilization of hematopoietic progenitor cells through cytokine stimulation. Accordingly, low-normal umbilical arterial pH, thought to be associated with perinatal stress, correlated with high cord blood unit CD34+ cell and colony-forming unit numbers. The associations were closer in vaginal deliveries than in Cesarean sections. Vaginal delivery entails specific physiological changes, which may also affect the hematopoietic system. Thus, different factors may predict cord blood hematopoietic progenitor cell numbers in the two modes of delivery. Theoretical models were created to enable the use of platelet characteristics (mean platelet volume) and perinatal factors (umbilical arterial pH and placental weight) in the selection of cord blood collections with high hematopoietic progenitor cell counts. These observations could thus be implemented as a part of the evaluation of cord blood collections for banking. The quality of cord blood units has been the focus of several recent studies. However, hemostasis activation during cord blood collection is scarcely evaluated in cord blood banks. In this study, hemostasis activation was assessed with prothrombin activation fragment 1+2 (F1+2), a direct indicator of thrombin generation, and platelet factor 4 (PF4), indicating platelet activation. Altogether three sample series were collected during the set-up of the cord blood bank as well as after changes in personnel and collection equipment. The activation decreased from the first to the subsequent series, which were collected with the bank fully in operation and following international standards, and was at a level similar to that previously reported for healthy neonates. As hemostasis activation may have unwanted effects on cord blood cell contents, it should be minimized. The assessment of hemostasis activation could be implemented as a part of process control in cord blood banks. Culture assays provide information about the hematopoietic potential of the cord blood unit. In processed cord blood units prior to freezing, megakaryocytic colony growth was evaluated in semisolid cultures with a novel scoring system. Three investigators analyzed the colony assays, and the scores were highly concordant. With such scoring systems, the growth potential of various cord blood cell lineages can be assessed. In addition, erythroid cells were observed in liquid cultures of cryostored and thawed, unseparated cord blood units without exogenous erythropoietin. This was hypothesized to be due to the erythropoietic effect of thrombopoietin, endogenous erythropoietin production, and diverse cell-cell interactions in the culture. This observation underscores the complex interactions of cytokines and supporting cells in the heterogeneous cell population of the thawed cord blood unit.