Development and evaluation of predictive models for pregnancy risk in UK dairy cows.

One suggested approach to improve the reproductive performance of dairy herds is through the targeted management of subgroups of biologically similar animals, such as those with similar probabilities of becoming pregnant, termed pregnancy risk. We aimed to use readily available farm data to develop predictive models of pregnancy risk in dairy cows. Data from a convenience sample of 108 dairy herds in the UK were collated and each herd was randomly allocated, at a ratio of 80:20, to either training or testing data sets. Following data cleaning, there were a total of 78 herds in the training data set and 20 herds in the testing data set. Data were further split by parity into nulliparous, primiparous, and multiparous subsets. An XGBoost model was trained to predict the insemination outcome in each parity subset, with predictors from farm records of breeding, calving and milk recording. Training data comprised 74,511 inseminations in 45,909 nulliparous animals, 86,420 inseminations in 39,439 primiparous animals, and 158,294 inseminations in 32,520 multiparous animals. The final models were evaluated by predicting with the testing data, comprising 31,740 inseminations in 19,647 nulliparous animals, 38,588 inseminations in 16,215 primiparous animals, and 65,049 inseminations in 12,439 multiparous animals. Model discrimination was assessed by calculating the area under receiver operating characteristic curves (AUC); model calibration was assessed by plotting calibration curves and compared across test herds by calculating the expected calibration error (ECE) in each test herd. The models were unable to discriminate between insemination outcomes with high accuracy, with an AUC of 0.63, 0.59 and 0.62 in the nulliparous, primiparous and multiparous subsets, respectively. The models were generally well-calibrated, meaning the model-predicted pregnancy risks were similar to the observed pregnancy risks. The mean (SD) ECE in the test herds was 0.038 (0.023), 0.028 (0.012) and 0.020 (0.008) in the nulliparous, primiparous and multiparous subsets respectively. The predictive models reported here could theoretically be used to identify subgroups of animals with similar pregnancy risk to facilitate targeted reproductive management; or provide information about cows' relative pregnancy risk compared with the herd average, which may support on-farm decision-making. Further research is needed to evaluate the generalizability of these predictive models and understand the source of variation in ECE between herds; however, this study demonstrates that it is possible to accurately predict pregnancy risk in dairy cows using readily available farm data.

Quantification of the effect of in utero events on lifetime resilience in dairy cows.

Currently, the dairy industry is facing many challenges that could affect its sustainability, including climate change and public perception of the industry. As a result, interest is increasing in the concept of identifying resilient animals, those with a long productive lifespan, as well as good reproductive performance and milk yield. There is much evidence that events in utero, that is, the developmental origins of health and disease hypothesis, alter the life-course health of offspring and we hypothesized that these could alter resilience in calves, where resilience is identified using lifetime data. The aim of this study was to quantify lifetime resilience scores (LRS) using an existing scoring system, based on longevity with secondary corrections for age at first calving and calving interval, and to quantify the effects of in utero events on the LRS using 2 datasets. The first was a large dataset of cattle on 83 farms in Great Britain born from 2006 to 2015 and the second was a smaller, more granular dataset of cattle born between 2003 and 2015 in the Langhill research herd at Scotland's Rural College. Events during dam's pregnancy included health events (lameness, mastitis, use of an antibiotic or anti-inflammatory medication), the effect of heat stress as measured by temperature-humidity index, and perturbations in milk yield and quality (somatic cell count, percentage fat, percentage protein and fat:protein ratio). Daughters born to dams that experienced higher temperature-humidity indexes while they were in utero during the first and third trimesters of pregnancy had lower LRS. Daughter LRS were also lower where milk yields or median fat percentages in the first trimester were low, and when milk yields were high in the third trimester. Dam LRS was positively associated with LRS of their offspring; however, as parity of the dam increased, LRS of their calves decreased. Similarly, in the Langhill herd, dams of a higher parity produced calves with lower LRS. Additionally, dams that recorded a high maximum locomotion score in the third trimester of pregnancy were negatively associated with lower calf LRS in the Langhill herd. Our results suggest that events that occur during pregnancy have lifelong consequences for the calf's lifetime performance. However, experience of higher temperature-humidity indexes, higher dam LRS, and mothers in higher parities explained a relatively small proportion of variation in offspring LRS, which suggests that other factors play a substantial role in determining calf LRS. Although "big data" can contain a considerable amount of noise, similar findings between the 2 datasets indicate it is likely these findings are real.

Emerging Roles for Artificial Intelligence in Heart Failure Imaging.

Artificial intelligence (AI) applications are expanding in cardiac imaging. AI research has shown promise in workflow optimization, disease diagnosis, and integration of clinical and imaging data to predict patient outcomes. The diagnostic and prognostic paradigm of heart failure is heavily reliant on cardiac imaging. As AI becomes increasingly validated and integrated into clinical practice, AI influence on heart failure management will grow. This review discusses areas of current research and potential clinical applications in AI as applied to heart failure cardiac imaging.

The relationship between physical activity, BMI, circadian rhythm, and sleep with cognition in bipolar disorder.

BACKGROUND: Cognitive deficits affect a significant proportion of patients with bipolar disorder (BD). Problems with sustained attention have been found independent of mood state and the causes are unclear. We aimed to investigate whether physical parameters such as activity levels, sleep, and body mass index (BMI) may be contributing factors. METHODS: Forty-six patients with BD and 42 controls completed a battery of neuropsychological tests and wore a triaxial accelerometer for 21 days which collected information on physical activity, sleep, and circadian rhythm. Ex-Gaussian analyses were used to characterise reaction time distributions. We used hierarchical regression analyses to examine whether physical activity, BMI, circadian rhythm, and sleep predicted variance in the performance of cognitive tasks. RESULTS: Neither physical activity, BMI, nor circadian rhythm predicted significant variance on any of the cognitive tasks. However, the presence of a sleep abnormality significantly predicted a higher intra-individual variability of the reaction time distributions on the Attention Network Task. CONCLUSIONS: This study suggests that there is an association between sleep abnormalities and cognition in BD, with little or no relationship with physical activity, BMI, and circadian rhythm.

Mass spectrometry and machine learning for the accurate diagnosis of benzylpenicillin and multidrug resistance of Staphylococcus aureus in bovine mastitis.

Staphylococcus aureus is a serious human and animal pathogen threat exhibiting extraordinary capacity for acquiring new antibiotic resistance traits in the pathogen population worldwide. The development of fast, affordable and effective diagnostic solutions capable of discriminating between antibiotic-resistant and susceptible S. aureus strains would be of huge benefit for effective disease detection and treatment. Here we develop a diagnostics solution that uses Matrix-Assisted Laser Desorption/Ionisation-Time of Flight Mass Spectrometry (MALDI-TOF) and machine learning, to identify signature profiles of antibiotic resistance to either multidrug or benzylpenicillin in S. aureus isolates. Using ten different supervised learning techniques, we have analysed a set of 82 S. aureus isolates collected from 67 cows diagnosed with bovine mastitis across 24 farms. For the multidrug phenotyping analysis, LDA, linear SVM, RBF SVM, logistic regression, naïve Bayes, MLP neural network and QDA had Cohen's kappa values over 85.00%. For the benzylpenicillin phenotyping analysis, RBF SVM, MLP neural network, naïve Bayes, logistic regression, linear SVM, QDA, LDA, and random forests had Cohen's kappa values over 85.00%. For the benzylpenicillin the diagnostic systems achieved up to (mean result ± standard deviation over 30 runs on the test set): accuracy = 97.54% ± 1.91%, sensitivity = 99.93% ± 0.25%, specificity = 95.04% ± 3.83%, and Cohen's kappa = 95.04% ± 3.83%. Moreover, the diagnostic platform complemented by a protein-protein network and 3D structural protein information framework allowed the identification of five molecular determinants underlying the susceptible and resistant profiles. Four proteins were able to classify multidrug-resistant and susceptible strains with 96.81% ± 0.43% accuracy. Five proteins, including the previous four, were able to classify benzylpenicillin resistant and susceptible strains with 97.54% ± 1.91% accuracy. Our approach may open up new avenues for the development of a fast, affordable and effective day-to-day diagnostic solution, which would offer new opportunities for targeting resistant bacteria.

Towards data-driven quantification of skin ageing using reflectance confocal microscopy.

INTRODUCTION: Evaluation of skin ageing is a non-standardized, subjective process, with typical measures relying coarse, qualitatively defined features. Reflectance confocal microscopy depth stacks contain indicators of both chrono-ageing and photo-ageing. We hypothesize that an ageing scale could be constructed using machine learning and image analysis, creating a data-driven quantification of skin ageing without human assessment. METHODS: En-face sections of reflectance confocal microscopy depth stacks from the dorsal and volar forearm of 74 participants (36/18/20 training/testing/validation) were represented using a histogram of visual features learned using unsupervised clustering of small image patches. A logistic regression classifier was trained on these histograms to differentiate between stacks from 20- to 30-year-old and 50- to 70-year-old volunteers. The probabilistic output of the logistic regression was used as the fine-grained ageing score for that stack in the testing set ranging from 0 to 1. Evaluation was performed in two ways: on the test set, the AUC was collected for the binary classification problem as well as by statistical comparison of the scores for age and body site groups. Final validation was performed by assessing the accuracy of the ageing score measurement on 20 depth stacks not used for training or evaluating the classifier. RESULTS: The classifier effectively differentiated stacks from age groups with a test set AUC of 0.908. Mean scores were significantly different when comparing age groups (mean 0.70 vs. 0.44; t = -6.62, p = 0.0000) and also when comparing stacks from dorsal and volar body sites (mean 0.64 vs. 0.53; t = 3.12, p = 0.0062). On the final validation set, 17 out of 20 depth stacks were correctly labelled. DISCUSSION: Despite being limited to only coarse training information in the form of example stacks from two age groups, the trained classifier was still able to effectively discriminate between younger skin and older skin. Curiously, despite being only trained with chronological age, there was still evidence for measurable differences in age scores due to sun exposure-with marked differences in scores on sun-exposed dorsal sites of some volunteers compared with less sun-exposed volar sites. These results suggest that fine-grained data-driven quantification of skin ageing is achievable.

INTRODUCTION: L'évaluation du vieillissement de la peau est un processus subjectif et non standardisé, dont les mesures typiques reposent sur des caractéristiques grossières et définies qualitativement. Les strates de profondeur observées grâce à la microscopie confocale par réflectance contiennent des indicateurs de chrono-vieillissement et de photo-vieillissement. Nous émettons l'hypothèse selon laquelle il serait possible d'établir une échelle de vieillissement à l'aide de l'apprentissage automatique et de l'analyse d'images, permettant la mise en place d'une quantification du vieillissement cutané fondée sur les données et sans évaluation humaine. MÉTHODES: À l'aide d'un histogramme des caractéristiques visuelles apprises à partir de petits ensembles d'images regroupées sans supervision, on a représenté des coupes faciales de strates de profondeur observées grâce à la microscopie confocale par réflectance et issues des faces dorsale et palmaire de l'avant-bras de 74 participants (36/18/20 entraînement/analyse/validation). Après un processus d'entraînement portant sur ces histogrammes, un classificateur de régression logistique a appris à différencier les strates prélevées sur des volontaires âgés de 20 à 30 ans et celles prélevées sur des volontaires âgés de 50 à 70 ans. Le résultat probabiliste de la régression logistique a été utilisé comme score du vieillissement de haute précision, allant de 0 à 1, pour cette strate dans l'ensemble d'analyse. L'évaluation a été effectuée de deux manières : dans l'ensemble d'analyse, l'aire sous la courbe (ASC) a été identifiée pour le problème de classification binaire ainsi que par comparaison statistique des scores selon les tranches d'âge et les catégories de site corporel. La validation finale est passée par une évaluation de l'exactitude de la mesure du score de vieillissement sur 20 strates de profondeur non utilisées dans le cadre du processus d'entraînement ou d'évaluation du classificateur. RÉSULTATS: Le classificateur différenciait efficacement les strates des tranches d'âge, avec une ASC dans l'ensemble d'analyse de 0,908. Les scores moyens affichaient des différences significatives lors de la comparaison entre les tranches d'âge (moyenne de 0,70 contre 0,44 ; t = 6,62 ; p = 0,0000) et lors de la comparaison entre les strates issues des faces dorsale et palmaire des sites corporels (moyenne de 0,64 contre 0,53 ; t = 3,12 ; p = 0,0062). Dans l'ensemble de validation finale, 17 strates sur 20 ont été correctement classées.

A Starling-like total work controller for rotary blood pumps: An in vitro evaluation.

Due to improved durability and survival rates, rotary blood pumps (RBPs) are the preferred left ventricular assist device when compared to volume displacement pumps. However, when operated at constant speed, RBPs lack a volume balancing mechanism which may result in left ventricular suction and suboptimal ventricular unloading. Starling-like controllers have previously been developed to balance circulatory volumes; however, they do not consider ventricular workload as a feedback and may have limited sensitivity to adjust RBP workload when ventricular function deteriorates or improves. To address this, we aimed to develop a Starling-like total work controller (SL-TWC) that matched the energy output of a healthy heart by adjusting RBP hydraulic work based on measured left ventricular stroke work and ventricular preload. In a mock circulatory loop, the SL-TWC was evaluated using a HeartWare HVAD in a range of simulated patient conditions. These conditions included changes in systemic hypertension and hypotension, pulmonary hypertension, blood circulatory volume, exercise, and improvement and deterioration of ventricular function by increasing and decreasing ventricular contractility. The SL-TWC was compared to constant speed control where RBP speed was set to restore cardiac output to 5.0 L/min at rest. Left ventricular suction occurred with constant speed control during pulmonary hypertension but was prevented with the SL-TWC. During simulated exercise, the SL-TWC demonstrated reduced LVSW (0.51 J) and greater RBP flow (9.2 L/min) compared to constant speed control (LVSW: 0.74 J and RBP flow: 6.4 L/min). In instances of increased ventricular contractility, the SL-TWC reduced RBP hydraulic work while maintaining cardiac output similar to the rest condition. In comparison, constant speed overworked and increased cardiac output. The SL-TWC balanced circulatory volumes by mimicking the Starling mechanism, while also considering changes in ventricular workload. Compared to constant speed control, the SL-TWC may reduce complications associated with volume imbalances, adapt to changes in ventricular function and improve patient quality of life.

Investigation of the inherent left-right flow balancing of rotary total artificial hearts by means of a resistance box.

With the incidence of end-stage heart failure steadily increasing, the need for a practical total artificial heart (TAH) has never been greater. Continuous flow TAHs (CFTAH) are being developed using rotary blood pumps (RBPs), leveraging their small size, mechanical simplicity, and excellent durability. To completely replace the heart with currently available RBPs, two are required; one for providing pulmonary flow and one for providing systemic flow. To prevent hazardous states, it is essential to maintain balance between the pulmonary and systemic circulation at a wide variety of physiologic states. In this study, we investigated factors determining a CFTAH's inherent ability to balance systemic and pulmonary flow passively, without active management of pump rotational speed. Four different RBPs (ReliantHeart HA5, Thoratec HMII, HeartWare HVAD, and Ventracor VentrAssist) were used in various combinations to construct CFTAHs. Each CFTAH's ability to autonomously maintain pressures and flows within defined ranges was evaluated in a hybrid mock loop as systemic and pulmonary vascular resistance (PVR) were changed. The resistance box, a method to quantify the range of vascular resistances that can be safely supported by a CFTAH, was used to compare different CFTAH configurations in an efficient and predictive way. To reduce the need for future in vitro tests and to aid in their analysis, a novel analytical evaluation to predict the resistance box of various CFTAH configurations was also performed. None of the investigated CFTAH configurations fully satisfied the predefined benchmarks for inherent flow balancing, with the VentrAssist (left) and HeartAssist 5 (right) offering the best combination. The extent to which each CFTAH was able to autonomously maintain balance was determined by the pressure sensitivity of each RPB: the sensitivity of outflow to changes in the pressure head. The analytical model showed that by matching left and right pressure sensitivity the inherent balancing performance can be improved. These findings may ultimately lead to a reduced need for manual speed changes or active control systems.

Guinea worm infection in northern Nigeria: reflections on a disease approaching eradication.

Global eradication of the guinea worm (Dracunculus medinensis) is near, although perhaps delayed a little by the discovery of a transmission cycle in dogs. It is therefore an appropriate time to reflect on the severe impact of this infection on the life of the communities where it was endemic prior to the start of the global eradication programme in 1981. From 1971 to 1974, we conducted a series of unpublished studies on guinea worm in a group of villages in Katsina State, northern Nigeria, where the infection was highly endemic. These studies demonstrated the high rate of infection in affected communities, the frequent recurrence of the infection in some subjects and the long-standing disability that remained in some infected individuals. Immunological studies showed a high level of immediate hypersensitivity to adult worm and larval antigens but a downregulation of Th1-type T-cell responses to worm antigens. Freeing communities such as those described in this article from the scourge of guinea worm infection for good will be an important public health triumph.

Barriers to living donor kidney transplantation in the United Kingdom: a national observational study.

BACKGROUND: Living donor kidney transplantation (LDKT) provides more timely access to transplantation and better clinical outcomes than deceased donor kidney transplantation (DDKT). This study investigated disparities in the utilization of LDKT in the UK. METHODS: A total of 2055 adults undergoing kidney transplantation between November 2011 and March 2013 were prospectively recruited from all 23 UK transplant centres as part of the Access to Transplantation and Transplant Outcome Measures (ATTOM) study. Recipient variables independently associated with receipt of LDKT versus DDKT were identified. RESULTS: Of the 2055 patients, 807 (39.3%) received LDKT and 1248 (60.7%) received DDKT. Multivariable modelling demonstrated a significant reduction in the likelihood of LDKT for older age {odds ratio [OR] 0.11 [95% confidence interval (CI) 0.08-0.17], P < 0.0001 for 65-75 years versus 18-34 years}; Asian ethnicity [OR 0.55 (95% CI 0.39-0.77), P = 0.0006 versus White]; Black ethnicity [OR 0.64 (95% CI 0.42-0.99), P = 0.047 versus White]; divorced, separated or widowed [OR 0.63 (95% CI 0.46-0.88), P = 0.030 versus married]; no qualifications [OR 0.55 (95% CI 0.42-0.74), P < 0.0001 versus higher education qualifications]; no car ownership [OR 0.51 (95% CI 0.37-0.72), P = 0.0001] and no home ownership [OR 0.65 (95% CI 0.85-0.79), P = 0.002]. The odds of LDKT varied significantly between countries in the UK. CONCLUSIONS: Among patients undergoing kidney transplantation in the UK, there are significant age, ethnic, socio-economic and geographic disparities in the utilization of LDKT. Further work is needed to explore the potential for targeted interventions to improve equity in living donor transplantation.

Closed-form equation to estimate the dielectric properties of biological tissues as a function of age.

Developing microwave systems for biomedical applications requires accurate dielectric properties of biological tissues for reliable modeling before prototyping and subject testing. Dielectric properties of tissues decrease with age due to the change in their water content, but there are no detailed age-dependent data, especially for young tissue-like newborns, in the literature. In this article, an age-dependent formula to predict the dielectric properties of biological tissues was derived. In the proposed method, the variation of water concentration in each type of tissue as a function of age was used to calculate its relative permittivity and conductivity. The derived formula shows that the concentration of water in each tissue type can be modeled as a negative exponential function of age. The dielectric properties of each tissue type can then be calculated as a function of the dielectric properties of water and dielectric properties of the organ forming the tissue and its water concentration. The derived formula was used to generate the dielectric properties of several types of human tissues at different ages using the dielectric properties of a human adult. Moreover, the formula was validated on pig tissues of different ages. A close agreement was achieved between the calculated and measured data with a maximum difference of only 2%. Bioelectromagnetics. 38:474-481, 2017. © 2017 Wiley Periodicals, Inc.

Using ventricular modeling to robustly probe significant deep gray matter pathologies: Application to cerebral palsy.

Understanding the relationships between the structure and function of the brain largely relies on the qualitative assessment of Magnetic Resonance Images (MRIs) by expert clinicians. Automated analysis systems can support these assessments by providing quantitative measures of brain injury. However, the assessment of deep gray matter structures, which are critical to motor and executive function, remains difficult as a result of large anatomical injuries commonly observed in children with Cerebral Palsy (CP). Hence, this article proposes a robust surrogate marker of the extent of deep gray matter injury based on impingement due to local ventricular enlargement on surrounding anatomy. Local enlargement was computed using a statistical shape model of the lateral ventricles constructed from 44 healthy subjects. Measures of injury on 95 age-matched CP patients were used to train a regression model to predict six clinical measures of function. The robustness of identifying ventricular enlargement was demonstrated by an area under the curve of 0.91 when tested against a dichotomised expert clinical assessment. The measures also showed strong and significant relationships for multiple clinical scores, including: motor function (r2 = 0.62, P < 0.005), executive function (r2 = 0.55, P < 0.005), and communication (r2 = 0.50, P < 0.005), especially compared to using volumes obtained from standard anatomical segmentation approaches. The lack of reliance on accurate anatomical segmentations and its resulting robustness to large anatomical variations is a key feature of the proposed automated approach. This coupled with its strong correlation with clinically meaningful scores, signifies the potential utility to repeatedly assess MRIs for clinicians diagnosing children with CP. Hum Brain Mapp 37:3795-3809, 2016. © 2016 Wiley Periodicals, Inc.

Alterations in regional shape on ipsilateral and contralateral cortex contrast in children with unilateral cerebral palsy and are predictive of multiple outcomes.

Congenital brain lesions result in a wide range of cerebral tissue alterations observed in children with cerebral palsy (CP) that are associated with a range of functional impairments. The relationship between injury severity and functional outcomes, however, remains poorly understood. This research investigates the differences in cortical shape between children with congenital brain lesions and typically developing children (TDC) and investigates the correlations between cortical shape and functional outcome in a large cohort of patients diagnosed with unilateral CP. Using 139 structural magnetic resonance images, including 95 patients with clinically diagnosed CP and 44 TDC, cortical segmentations were obtained using a modified expectation maximization algorithm. Three shape characteristics (cortical thickness, curvature, and sulcal depth) were computed within a number of cortical regions. Significant differences in these shape measures compared to the TDC were observed on both the injured hemisphere of children with CP (P < 0.004), as well as on the apparently uninjured hemisphere, illustrating potential compensatory mechanisms in these children. Furthermore, these shape measures were significantly correlated with several functional outcomes, including motor, cognition, vision, and communication (P < 0.012), with three out of these four models performing well on test set validation. This study highlights that cortical neuroplastic effects may be quantified using MR imaging, allowing morphological changes to be studied longitudinally, including any influence of treatment. Ultimately, such approaches could be used for the long term prediction of outcomes and the tailoring of treatment to individuals. Hum Brain Mapp 37:3588-3603, 2016. © 2016 Wiley Periodicals, Inc.

Dielectric properties of dog brain tissue measured in vitro across the 0.3-3 GHz band.

Dielectric properties of dead Greyhound female dogs' brain tissues at different ages were measured at room temperature across the frequency range of 0.3-3 GHz. Measurements were made on excised tissues, in vitro in the laboratory, to carry out dielectric tests on sample tissues. Each dataset for a brain tissue was parametrized using the Cole-Cole expression, and the relevant Cole-Cole parameters for four tissue types are provided. A comparison was made with the database available in literature for other animals and human brain tissue. Results of two types of tissues (white matter and skull) showed systematic variation in dielectric properties as a function of animal age, whereas no significant change related to age was noticed for other tissues. Results provide critical information regarding dielectric properties of animal tissues for a realistic animal head model that can be used to verify the validity and reliability of a microwave head scanner for animals prior to testing on live animals. Bioelectromagnetics. 37:549-556, 2016. © 2016 Wiley Periodicals, Inc.

Cortisol awakening response and spatial working memory in man: a U-shaped relationship.

OBJECTIVE: The association between hypothalamic-pituitary-adrenal (HPA)-axis function and cognition has long been investigated. An inverted U-shaped relationship has been described between various measures of HPA-axis function and neuropsychological performance in animals and man. Work with glucocorticoid receptor manipulation has corroborated these findings, with particular effects observed in relation to spatial working memory (SWM). As HPA-axis dysfunction is frequently found in patients with psychiatric illness, research in this area has potential implications for the treatment of the commonly observed cognitive impairment in such disorders. Here, we present the results of a pilot study examining the relationship between cortisol awakening response (CAR) and cognitive functions known to be susceptible to HPA-axis manipulation. METHODS: Nineteen healthy male volunteers were recruited, and their CAR and performance in a task of SWM were assessed. RESULTS: A highly significant quadratic relationship was observed between the CAR and SWM error rate (R(2)=0.63, p=0.001). CONCLUSION: We provide novel evidence supporting the existence of an inverted U-shaped relationship between corticosteroid levels and cognitive function in humans.

Modeling of a rotary blood pump.

The accurate representation of rotary blood pumps in a numerical environment is important for meaningful investigation of pump-cardiovascular system interactions. Although numerous models for ventricular assist devices (VADs) have been developed, modeling methods for rotary total artificial hearts (rTAHs) are still required. Therefore, an rTAH prototype was characterized in a steady flow, hydraulic test bench over a wide operational range for pump and hydraulic parameters. In order to develop a generic modeling method, a data-driven modeling approach was chosen. k-Nearest-neighbors, artificial neural networks, and support vector machines (SVMs) were the machine learning approaches evaluated. The best performing parameters for each algorithm were determined via optimization. The resulting multiple-input-multiple-output models were subsequently assessed under identical conditions, and a SVM with a radial basis function kernel was identified as the best performing. The achieved root mean squared errors were 0.03 L/min, 0.06 L/min, and 0.18 W for left and right flow and motor power consumption, respectively. In comparison with existing models for VADs, the flow errors are more than 70% lower. Further advantages of the SVM model are the robustness to measurement noise and the capability to operate outside of the trained parameter range. This proposed modeling method will accelerate further device refinements by providing a more appropriate numerical environment in which to evaluate the pump-cardiovascular system interaction.

Physiological control of dual rotary pumps as a biventricular assist device using a master/slave approach.

Dual rotary left ventricular assist devices (LVADs) can provide biventricular mechanical support during heart failure. Coordination of left and right pump speeds is critical not only to avoid ventricular suction and to match cardiac output with demand, but also to ensure balanced systemic and pulmonary circulatory volumes. Physiological control systems for dual LVADs must meet these objectives across a variety of clinical scenarios by automatically adjusting left and right pump speeds to avoid catastrophic physiological consequences. In this study we evaluate a novel master/slave physiological control system for dual LVADs. The master controller is a Starling-like controller, which sets flow rate as a function of end-diastolic ventricular pressure (EDP). The slave controller then maintains a linear relationship between right and left EDPs. Both left/right and right/left master/slave combinations were evaluated by subjecting them to four clinical scenarios (rest, postural change, Valsalva maneuver, and exercise) simulated in a mock circulation loop. The controller's performance was compared to constant-rotational-speed control and two other dual LVAD control systems: dual constant inlet pressure and dual Frank-Starling control. The results showed that the master/slave physiological control system produced fewer suction events than constant-speed control (6 vs. 62 over a 7-min period). Left/right master/slave control had lower risk of pulmonary congestion than the other control systems, as indicated by lower maximum EDPs (15.1 vs. 25.2-28.4 mm Hg). During exercise, master/slave control increased total flow from 5.2 to 10.1 L/min, primarily due to an increase of left and right pump speed. Use of the left pump as the master resulted in fewer suction events and lower EDPs than when the right pump was master. Based on these results, master/slave control using the left pump as the master automatically adjusts pump speed to avoid suction and increases pump flow during exercise without causing pulmonary venous congestion.

A hybrid mock circulation loop for a total artificial heart.

Rotary blood pumps are emerging as a viable technology for total artificial hearts, and the development of physiological control algorithms is accelerated with new evaluation environments. In this article, we present a novel hybrid mock circulation loop (HMCL) designed specifically for evaluation of rotary total artificial hearts (rTAH). The rTAH is operated in the physical domain while all vasculature elements are embedded in the numerical domain, thus combining the strengths of both approaches: fast and easy exchange of the vasculature model together with improved controllability of the pump. Parameters, such as vascular resistance, compliance, and blood volume, can be varied dynamically in silico during operation. A hydraulic-numeric interface creates a real-time feedback loop between the physical and numerical domains. The HMCL uses computer-controlled resistance valves as actuators, thereby reducing the size and number of hydraulic elements. Experimental results demonstrate a stable interaction over a wide operational range and a high degree of flexibility. Therefore, we demonstrate that the newly created design environment can play an integral part in the hydraulic design, control development, and durability testing of rTAHs.

In vitro susceptibility of bovine mastitis pathogens to a combination of penicillin and framycetin: development of interpretive criteria for testing by broth microdilution and disk diffusion.

Dry cow therapy is an important part of mastitis control. This therapy typically consists of an antibiotic or antibiotics administered at a single dose by intramammary infusion at dry off to treat or prevent infection by prevalent mastitis pathogens. A combination dry cow therapy consisting of the active components penicillin and framycetin is currently used in several countries. Despite its use, standardized methods for the susceptibility testing of this combination against mastitis pathogens have not been established. In this study, which used Clinical and Laboratory Standards Institute methodology, preliminary interpretive criteria for the broth microdilution minimum inhibitory concentration (MIC) testing of mastitis pathogens to penicillin combined with framycetin (2:1 wt/wt) were established based on the amount of drug achieved and maintained postadministration in the udder. Based on resulting MIC distributions of recent veterinary field isolates and a subset of isolates preselected for resistance to ß-lactams or aminoglycosides and concentrations achieved postadministration, criteria for broth microdilution testing of the combination (susceptible, intermediate, resistant in micrograms per milliliter) were set as follows: Escherichia coli ≤8/4, 16/8, ≥32/16; Staphylococcus spp. ≤2/1, 4/2-8/4, >16/8; Streptococcus uberis and Streptococcus dysgalactiae <0.25/0.12, 0.5/0.25-2/1, >4/2. A disk diffusion test using disks containing 100 µg of framycetin and 10 IU of penicillin was also developed, and preliminary interpretive criteria (susceptible, intermediate, resistant in millimeters) were set based on correlation to broth MIC values and the minimization of interpretive errors between isolates tested concurrently by broth microdilution and disk diffusion as follows: E. coli ≥18, 16-17, ≤15; Staphylococcus spp. ≥21, 18-20, ≤17; Strep. uberis and Strep. dysgalactiae ≥21, 19-20, ≤18. In addition, ranges for the quality control of the testing of this combination by both broth microdilution and disk diffusion are provided. Based on these criteria and recent veterinary mastitis isolates, 96.0/96.8% of E. coli, 93.7/89.1% of Staph. aureus, 94.6/96.4% coagulase-negative staphylococci, 94.5/97.0% of Strep. uberis, and 96.7/100.0% Strep. dysgalactiae were susceptible to the combination by broth microdilution or disk diffusion, respectively. The availability of these methods will allow for the susceptibility testing of clinical isolates in the field and will also provide a way to monitor for resistance development as this combination is used going forward.

A preliminary investigation into the use of an auditory brainstem response (ABR) simulator for training audiology students in waveform analysis.

OBJECTIVE: To determine if a computer simulation can be used to improve the ability of audiology students to analyse ABR waveforms. DESIGN: A pretest-posttest, quasi-experimental design was used. All participants completed a pretraining examination of their ability to analyse ABR waveforms, eight hours of ABR analysis training over eight weeks using one of three training modes-manual, simulator or combined manual and simulator training, and a posttraining examination of their ability to analyse ABR waveforms. STUDY SAMPLE: Fourteen third-year audiology students (13 female, one male, aged 21 to 22 years) participated in this study. RESULTS: Participants who completed the manual or the combined manual and simulator training achieved significantly higher normalized gain scores on their ABR waveform analysis examinations compared to those who completed the simulator training (p < 0.05). CONCLUSIONS: Our findings suggest that the improvements seen in the ability of these audiology students to analyse ABR waveforms were driven primarily by the manual training. The minimal improvements seen in the students who received the simulator training suggest that face-to-face instruction could be required to enhance the ability of audiology students to analyse ABR waveforms.