13 research outputs found
Dynamic three-dimensional computed tomographic imaging facilitates evaluation of the equine cervical articular process joint in motion
Background
Dynamic computed tomography (CT) imaging has been introduced in human orthopaedics and is continuing to gain popularity. With dynamic CT, video sequences of anatomical structures can be evaluated in motion.
Objectives
To investigate the feasibility of dynamic CT for diagnostic imaging of the equine cervical articular process joints (APJs) and to give a detailed description of the APJ movement pattern.
Study design
Descriptive cadaver imaging.
Methods
Cervical specimens of twelve Warmblood horses were included. A custom-made motorised testing device was used to position and manipulate the neck specimens and perform dynamic 2D and 3D CT imaging. Images were obtained with a 320-detector-row CT scanner with a 160 mm wide-area (2D) solid-state detector design that allows image acquisition of a volumetric axial length of 160 mm without moving the CT couch. Dynamic videos were acquired and divided into four phases of movement. Three blinded observers used a subjective scale of 1 (excellent) to 4 (poor) to grade the overall image quality in each phases of motion cycle.
Results
With an overall median score of 1 the image quality, a significantly lower score was observed in the dynamic 3D videos over the four phases by the three observers compared with the 2D videos for both flexion (3D 95% CI: 1-2 and 2D 95% CI: 1-3; P = .007) and extension movement (3D 95% CI: 1-2 and 2D 95% CI: 1-3; P = .008). Median Translational displacement of the APJ surface was significantly greater in flexion than in extension movement (P = .002).
Main limitations
The small number of specimens included. Excision of spines and removal of musculature.
Conclusions
The study is a first step in the investigation of the potential of dynamic 3D CT in veterinary medicine, a technique that has only begun to be explored and leaves much room for refinement prior to its introduction in routine practice. CT with a detector coverage of 16 cm and a rotation speed of 0.32 seconds provides high-quality images of moving objects and gives new insight into the movement pattern of equine cervical APJs
Which phenotypic traits of resistance should be improved in cattle to control paratuberculosis dynamics in a dairy herd: a modelling approach
Assessment of the effectiveness of bovine paratuberculosis control strategies : genetic selection or reduction of exposure in herds
La paratuberculosis (PTB) est une maladie endémique des ruminants causée par Mycobacterium avium subsp. paratuberculosis (Map). Les stratégies de maîtrise actuelles ne sont pas suffisamment efficaces. La réponse à l'exposition à Map varie entre les animaux avec une part de déterminisme génétique. Des marqueurs génétiques pourraient permettre une sélection. L'objectif était d'évaluer par modélisation l'efficacité potentielle attendue de stratégies de maîtrise utilisant la sélection génétique ou la réduction de l'exposition en élevage. Nous avons identifié quatre traits phénotypiques de résistance influençant principalement la propagation de Map à l'échelle du troupeau et montré la valeur ajoutée de leur amélioration simultanée. Nous avons évalué l'effet de l'environnement du troupeau et du système d’élevage sur la propagation et la maîtrise de Map. Nous avons montré une différence d’efficacité des stratégies de maîtrise les plus pertinentes entre deux systèmes d'élevage bovins laitiers contrastés d'Europe: l'ouest de la France et l'Irlande. Nous avons évalué l'efficacité que pourrait apporter la sélection génomique en évaluant le temps nécessaire pour atteindre des niveaux de variation des traits sélectionnés permettant un bon contrôle de l‘infection sous l’hypothèse que des marqueurs de sélection soient disponibles. Nous avons identifié 2 paramètres du modèle de sélection génomique influents sur l’efficacité de la sélection. Notre modèle permet d’intégrer de nouvelles connaissances biologiques sur le déterminisme génétique de la résistance à Map pour évaluer des stratégies de maîtrise complexes comprenant une composante de sélection génomique.Paratuberculosis (PTB) is an endemic disease of ruminants caused by Mycobacterium avium subsp. paratuberculosis (Map). Current control strategies are not effective enough. The response to Map exposure varies between animals with evidence of a partial genetic determinism. Genetic markers could allow selection. The objective was to assess the potential expected effectiveness of control strategies relying on genetic selection or reduction of exposure in herds, using a modelling approach. We identified four phenotypic traits of resistance mainly influencing the spread of Map at the herd scale and showed the added value of their simultaneous improvement. We evaluated the effect of the herd environment and management on the spread and control of Map. We showed a difference in effectiveness of the most relevant control strategies between two contrasting dairy cattle systems in Europe: western France and Ireland. We evaluated the effectiveness of genomic selection by assessing the time required to reach levels of variation in the selected traits allowing to achieve a good control of infection, assuming that associated genomic markers could be available. Effectiveness of selection was mainly influenced by 2 of the parameters of the developed genomic selection model. Our model allows to account for future knowledge about the genetic determinism of cattle resistance to Map in order to assess the effectiveness of complex control strategies including a genomic selection component
Control measures to prevent the increase of paratuberculosis prevalence in dairy cattle herds: an individual-based modelling approach
Paratuberculosis, a gastrointestinal disease caused by Mycobacterium avium subsp. paratuberculosis (Map), can lead to severe economic losses in dairy cattle farms. Current measures are aimed at controlling prevalence in infected herds, but are not fully effective. Our objective was to determine the most effective control measures to prevent an increase in adult prevalence in infected herds. We developed a new individual-based model coupling population and infection dynamics. Animals are characterized by their age (6 groups) and health state (6 states). The model accounted for all transmission routes and two control measures used in the field, namely reduced calf exposure to adult faeces and test-and-cull. We defined three herd statuses (low, moderate, and high) based on realistic prevalence ranges observed in French dairy cattle herds. We showed that the most relevant control measures depend on prevalence. Calf management and test-and-cull both were required to maximize the probability of stabilizing herd status. A reduced calf exposure was confirmed to be the most influential measure, followed by test frequency and the proportion of infected animals that were detected and culled. Culling of detected high shedders could be delayed for up to 3 months without impacting prevalence. Management of low prevalence herds is a priority since the probability of status stabilization is high after implementing prioritized measures. On the contrary, an increase in prevalence was particularly difficult to prevent in moderate prevalence herds, and was only feasible in high prevalence herds if the level of control was high
Modelling transmission and control of Mycobacterium avium subspecies paratuberculosis within Irish dairy herds with compact spring calving
Paratuberculosis is a chronic bacterial infection of the intestine in cattle caused by Mycobacterium avium subspecies paratuberculosis (Map). To better understand Map transmission in Irish dairy herds, we adapted the French stochastic individual-based epidemiological simulation model to account for seasonal herd demographics. We investigated the probability of Map persistence over time, the within-herd prevalence over time, and the relative importance of transmission pathways, and assessed the relative effectiveness of test-and-cull control strategies. We investigated the impact on model outputs of calf separation from cows (calves grazed on pasture adjacent to cows vs. were completely separated from cows) and test-and-cull. Test-and-cull scenarios consisted of highly test-positive cows culled within 13 or 4 weeks after detection, and calf born to highly test-positive cows kept vs removed. We simulated a typical Irish dairy herd with on average 82 lactating cows, 112 animals in total. Each scenario was iterated 1000 times to adjust variation caused by stochasticity. Map was introduced in the fully naive herd through the purchase of a moderately infectious primiparous cow. Infection was considered to persist when at least one infected animal remained in the herd or when Map was present in the environment. The probability of Map persistence 15 years after introduction ranged between 32.2–42.7 % when calves and cows had contact on pasture, and between 18.9–29.4 % when calves and cows were separated on pasture. The most effective control strategy was to cull highly test-positive cows within four weeks of detection (absolute 10 % lower persistence compared to scenarios without control). Removing the offspring of highly test-positive dams did not affect either Map persistence or within-herd prevalence of Map. Mean prevalence 15 years after Map introduction was highest (63.5 %) when calves and cows had contact on pasture. Mean prevalence was 15 % lower (absolute decrease) when cows were culled within 13 weeks of a high test-positive result, and 28 % lower when culled within 4 weeks. Around calving, the infection rate was high, with calves being infected in utero or via the general indoor environment (most important transmission routes). For the remainder of the year, the incidence rate was relatively low with most calves being infected on pasture when in contact with cows. Testing and culling was an effective control strategy when it was used prior to the calving period to minimize the number of highly infectious cows present when calves were born.Department of Agriculture, Food and the MarineFrench Research Agency Gran
Which phenotypic traits of resistance should be improved in cattle to control paratuberculosis dynamics in a dairy herd: a modelling approach
Abstract Paratuberculosis is a worldwide disease causing production losses in dairy cattle herds. Variability of cattle response to exposure to Mycobacterium avium subsp. paratuberculosis (Map) has been highlighted. Such individual variability could influence Map spread at larger scale. Cattle resistance to paratuberculosis has been shown to be heritable, suggesting genetic selection could enhance disease control. Our objective was to identify which phenotypic traits characterising the individual course of infection influence Map spread in a dairy cattle herd. We used a stochastic mechanistic model. Resistance consisted in the ability to prevent infection and the ability to cope with infection. We assessed the effect of varying (alone and combined) fourteen phenotypic traits characterising the infection course. We calculated four model outputs 25 years after Map introduction in a naïve herd: cumulative incidence, infection persistence, and prevalence of infected and affected animals. A cluster analysis identified influential phenotypes of cattle resistance. An ANOVA quantified the contribution of traits to model output variance. Four phenotypic traits strongly influenced Map spread: the decay in susceptibility with age (the most effective), the quantity of Map shed in faeces by high shedders, the incubation period duration, and the required infectious dose. Interactions contributed up to 12% of output variance, highlighting the expected added-value of improving several traits simultaneously. Combinations of the four most influential traits decreased incidence to less than one newly infected animal per year in most scenarios. Future genetic selection should aim at improving simultaneously the most influential traits to reduce Map spread in cattle populations
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Additional file 2. Sample of 11 trajectories of infected adult prevalence obtained with the reference scenario. Reference scenario was defined as the introduction of an infected heifer (IM) in a naĂŻve herd and no control implementation. Each trajectory represents the variation of infected adult prevalence over time since Map introduction. The sample of 11 trajectories has been extracted from the 5000 trajectories used to build initial conditions. Two trajectories (blue and brown) have been highlighted to illustrate model stochasticity and the absence of an early epidemic phase followed by a steady-state prevalence on the contrary to what is classically encountered in epidemiology
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Additional file 4. Influence of control measure modalities on the probability of non-degrading herd status over a 10-year period. (Panel A) Relative importance of each test-and-cull parameter linked to the predictive statistical model built with the Random Forest Classifier method, and (panel B) associated probability of non-degrading herd status over a 10-year period and according to initial herd status (A2, B, and C, in lines) and reduction of calf exposure (expoâ=â0.65, 0.5, and 0.35, in columns)
MOESM1 of Control measures to prevent the increase of paratuberculosis prevalence in dairy cattle herds: an individual-based modelling approach
Additional file 1. Model parameters for processes related to population and infection dynamics. Value and source for each parameter of the population and infection dynamics processes
MOESM5 of Control measures to prevent the increase of paratuberculosis prevalence in dairy cattle herds: an individual-based modelling approach
Additional file 5. Influence of control measure modalities on the probability of non-degrading herd status over a 15-year period. (Panel A) Relative importance of each test-and-cull parameter linked to the predictive statistical model built with the Random Forest Classifier method, and (panel B) associated probability of non-degrading herd status over a 15-year period and according to initial herd status (A2, B, and C, in lines) and reduction of calf exposure (expoâ=â0.65, 0.5, and 0.35, in columns)