Estimation of sensitivity and specificity of bulk tank milk PCR and 2 antibody ELISA tests for herd-level diagnosis of Mycoplasma bovis infection using Bayesian latent class analysis.

Mycoplasmosis (due to infection with Mycoplasma bovis) is a serious disease of beef and dairy cattle that can adversely impact health, welfare and productivity (Maunsell et al. (2011)). Mycoplasmosis can lead to a range of often severe, clinical presentations. Mycoplasma bovis (M. bovis) infection can present either clinically or subclinically, with the potential for recrudescence of shedding in association with stressful periods. Infection can be maintained within herds because of intermittent shedding (Calcutt et al., 2018, Hazelton et al., 2018). M. bovis is recognized as poorly responsive to treatment which represents a major challenge for control in infected herds. Given this, particular focus is needed on biosecurity measures to prevent introduction into uninfected herds in the first place. A robust and reliable laboratory test for surveillance is important both for herd-level prevention and control. The objective of this study was to estimate the sensitivity and specificity of 3 diagnostic tests (one PCR and 2 ELISA tests) on bulk tank milk, for the herd-level detection of M. bovis using Bayesian latent class analysis. In autumn 2018, bulk tank milk samples from 11,807 herds, covering the majority of the main dairy regions in Ireland had been submitted to the Department of Agriculture testing laboratory for routine surveillance were made available. A stratified random sample approach was used to select a cohort of herds for testing from this larger sample set. A final study population of 728 herds had bulk tank milk samples analyzed using a Bio-X ELISA (ELISA 1), an IDvet ELISA (ELISA 2) and a PCR test. A Bayesian latent class analysis (BLCA) was conducted to estimate the sensitivity (Se) and specificity (Sp) of the 3 diagnostic tests applied to bulk tank milk (BTM) for the detection of the herd-level infection. An overall LCA was conducted on all herds within a single population (a 3-test, 1-population model). The herds were also split into 2 populations based on herd size (small herds had < 82 cattle) (a 3-test, 2-population model) and separately into 3 regions in Ireland (Leinster, Munster and Connacht/Ulster) (a 3-test, 3-population model). The latent variable of interest was the herd-level M. bovis infection status. In total, 363/728 (50%) were large herds, 7 (1.0%) were positive on PCR, 88 (12%) positive on ELISA 1, and 406 (56%) positive on ELISA 2. Based on the 2-population model, the sensitivity (95% Bayesian credible interval (BCI) was 0.03 (0.02, 0.05), 0.22 (0.18, 0.27), 0.94 (0.88, 0.98) for PCR, ELISA 1 and ELISA 2 respectively. The specificity (95% BCI) was 0.99 (0.99, 1.0), 0.97 (0.95, 0.99), and 0.92 (0.86, 0.97) for PCR, ELISA 1 and ELISA 2 respectively. The herd-level true prevalence was estimated at 0.43 (BCI 0.35, 0.5) for smaller herds. The true prevalence was estimated at 0.62 (BCI 0.55, 0.69) for larger herds. The true prevalence was estimated at 0.56 (BCI 0.49, 0.463) in the 1-population model. For the 3-population model, the sensitivity (95% BCI) was 0.03 (0.02, 0.05), 0.24 (0.18, 0.29), 0.95 (0.9, 0.98) for PCR, ELISA 1 and ELISA 2 respectively. The specificity (95% BCI) was 0.99 (0.99, 1.0), 0.98 (0.96, 0.99), and 0.88 (0.79, 0.95) for PCR, ELISA 1 and ELISA 2 respectively. The herd-level true prevalence (95% BCI) was estimated at 0.65 (0.56, 0.73), 0.38 (0.28, 0.46) and 0.53 (0.4, 0.65) for population 1, 2, 3 respectively. Across all 3 models, the range in true prevalence was 38% to 65% of Irish dairy herds infected with M. bovis. The operating characteristics vary substantially between tests. The IDvet ELISA had a relatively high Se (the highest Se of the 3 tests studied) but it was estimated at 0.95 at its highest in 3-test, 3-population model. This test may be an appropriate test for herd-level screening or prevalence estimation within the context of the endemically infected Irish dairy cattle population. Further work is required to optimize this test and its interpretation when applied at herd-level to offset concerns related to the lower than optimal test Sp.

A framework for assessing confidence in freedom from infection in animal disease control programmes.

In the Surveillance Tool for Outcome-based Comparison of FREEdom from infection (STOC free) project (https://www.stocfree.eu), a data collection tool was constructed to facilitate standardised collection of input data, and a model was developed to allow a standardised and harmonised comparison of the outputs of different control programmes (CPs) for cattle diseases. The STOC free model can be used to evaluate the probability of freedom from infection for herds in CPs and to determine whether these CPs comply with the European Union's pre-defined output-based standards. Bovine viral diarrhoea virus (BVDV) was chosen as the case disease for this project because of the diversity in CPs in the six participating countries. Detailed BVDV CP and risk factor information was collected using the data collection tool. For inclusion of the data in the STOC free model, key aspects and default values were quantified. A Bayesian hidden Markov model was deemed appropriate, and a model was developed for BVDV CPs. The model was tested and validated using real BVDV CP data from partner countries, and corresponding computer code was made publicly available. The STOC free model focuses on herd-level data, although that animal-level data can be included after aggregation to herd level. The STOC free model is applicable to diseases that are endemic, given that it needs the presence of some infection to estimate parameters and enable convergence. In countries where infection-free status has been achieved, a scenario tree model could be a better suited tool. Further work is recommended to generalise the STOC free model to other diseases.

Dans le cadre du projet européen STOC free (Surveillance Tool for Outcome-based Comparison of FREEdom from infection, outil de surveillance permettant de comparer les probabilités d'absence d'infection sur la base des résultats, https://www.stocfree.eu), un outil de recueil des données a été construit pour faciliter une collecte normalisée des données d'entrée ; un modèle a également été élaboré pour permettre une comparaison normalisée et harmonisée des données sur les résultats des différents programmes de contrôle des maladies des bovins. Le modèle STOC free peut être utilisé pour évaluer la probabilité d'absence d'infection au sein des troupeaux dans le cadre des programmes de contrôle et déterminer si ces programmes sont conformes aux normes définies par l'Union européenne en termes de résultats attendus. L'infection par le virus de la diarrhée virale bovine a été choisie comme maladie d'étude pour ce projet en raison de la diversité des programmes de contrôle dans les six pays participants. Les informations relatives aux programmes de contrôle et aux facteurs de risque d'infection ont été recueillies à l'aide de l'outil de collecte des données. Les aspects clés et valeurs par défaut ont été quantifiés en vue d'être inclus dans le modèle STOC free. Un modèle de Markov caché dont les paramètres sont estimés par inférence bayésienne a été considéré comme le plus adapté et développé pour une application aux données issues des programmes de contrôle de la diarrhée virale bovine. Ce modèle a été testé et validé en utilisant des données réelles des programmes de contrôle du virus de la diarrhée virale bovine des pays participants ; le code informatique correspondant a été rendu public. Le modèle STOC free utilise des données au niveau des troupeaux, même si des données au niveau des animaux individuels peuvent être incluses une fois agrégées au niveau du troupeau. Le modèle STOC free s'applique aux maladies endémiques, puisqu'un certain niveau de présence de l'infection est nécessaire pour estimer les paramètres et permettre la convergence. Dans les pays ayant obtenu le statut indemne d'infection, un modèle du type arbre de scénario pourrait être un outil plus adapté. Des travaux supplémentaires sont recommandés pour généraliser le modèle STOC free à d'autres maladies.

Como parte del proyecto europeo STOC free (Surveillance Tool for Outcome-based Comparison of FREEdom from infection, herramienta de vigilancia para comparaciones por resultados respecto a la ausencia de infecciones, https://www.stocfree.eu), se confeccionó una herramienta de obtención de datos para facilitar la recogida normalizada de datos entrantes y se elaboró un modelo que posibilitara una comparación normalizada y armonizada de los resultados (datos salientes) de distintos programas de control de enfermedades bovinas. El modelo STOC free puede servir para calcular la probabilidad de ausencia de infección en los rebaños como parte de los programas de control y para determinar si estos programas se ajustan a las normas predefinidas de resultados de la Unión Europea. Como ejemplo de estudio para el proyecto se eligió el virus de la diarrea viral bovina (virus DVB) por la diversidad que presentaban los correspondientes programas de control de los seis países participantes. Empleando la herramienta de obtención de datos, se reunió información pormenorizada de los programas de control del virus DVB y los factores de riesgo. Para incluir los datos en el modelo STOC free, se cifraron unos aspectos clave y valores predeterminados Juzgando conveniente el empleo de un modelo oculto de Markov cuyos parámetros se estiman por inferencia bayesiana, se elaboró un modelo de esta índole aplicable a los programas de control del virus DVB. Para ensayar y validar el modelo se utilizaron datos reales de los programas de control del virus DVB de los países participantes, tras lo cual se hizo público el correspondiente código informático. El modelo STOC free trabaja con los datos por rebaño, aunque tras la agregación por rebaños pueden incluirse también datos por individuo. Para que este modelo sea aplicable a una enfermedad es preciso que esta sea endémica, pues el modelo requiere la presencia de cierto nivel de infección para calcular los parámetros y determinar convergencias. En aquellos países donde ya esté reconocida la ausencia de infección, sería más apropiado utilizar como herramienta un modelo de árbol de hipótesis. Los autores recomiendan ahondar en esta línea de trabajo para poder extender a otras enfermedades el uso del modelo STOC free.

Seroprevalence of Mycoplasma bovis in bulk milk samples in Irish dairy herds and risk factors associated with herd seropositive status.

Mycoplasma bovis is a serious disease of cattle worldwide; mastitis, pneumonia, and arthritis are particularly important clinical presentations in dairy herds. Mycoplasma bovis was first identified in Ireland in 1994, and the reporting of Mycoplasma-associated disease has substantially increased over the last 5 years. Despite the presumed endemic nature of M. bovis in Ireland, there is a paucity of data on the prevalence of infection, and the effect of this disease on the dairy industry. The aim of this observational study was to estimate apparent herd prevalence for M. bovis in Irish dairy herds using routinely collected bulk milk surveillance samples and to assess risk factors for herd seropositivity. In autumn 2018, 1,500 herds out of the 16,858 herds that submitted bulk tank milk (BTM) samples to the Department of Agriculture testing laboratory for routine surveillance were randomly selected for further testing. A final data set of 1,313 sampled herds with a BTM ELISA result were used for the analysis. Testing was conducted using an indirect ELISA kit (ID Screen Mycoplasma bovis). Herd-level risk factors were used as explanatory variables to determine potential risk factors associated with positive herd status (reflecting past or current exposure to M. bovis). A total of 588 of the 1,313 BTM samples were positive to M. bovis, providing an apparent herd prevalence of 0.45 (95% CI: 0.42, 0.47) in Irish dairy herds in autumn 2018. Multivariable analysis was conducted using logistic regression. The final model identified herd size, the number of neighboring farms, in-degree and county as statistically significant risk factors for herd BTM seropositivity to M. bovis. The results suggest a high apparent herd prevalence of seropositivity to M. bovis, and evidence that M. bovis infection is now endemic in the Irish dairy sector. In addition, risk factors identified are closely aligned to what we would expect of an infectious disease. Awareness raising and education about this important disease is warranted given the widespread nature of exposure and likely infection in Irish herds. Further work on the validation of diagnostic tests for herd-level diagnosis should be undertaken as a matter of priority.

Herd-level factors associated with detection of calves persistently infected with bovine viral diarrhoea virus (BVDV) in Irish cattle herds with negative herd status (NHS) during 2017.

A compulsory national BVD eradication programme commenced in Ireland in 2013. Since then considerable progress has been made, with the animal-level prevalence of calves born persistently infected (PI) falling from 0.67 % in 2013 to 0.06 % in 2018. The herd-level prevalence fell from 11.3 % in 2013 to 1.1 % in 2018. In the Irish programme, herds in which all animals have a known negative status and which have not contained any PI animals for 12 months or more are assigned a negative herd status (NHS). While considerable progress towards eradication has been made, PI calves have been identified in a small proportion of herds that had previously been assigned NHS. Given this context, a case-control study was conducted to investigate potential risk factors associated with loss of NHS in 2017. 546 herds which had NHS on 1 January 2017 and lost that status during 2017 (case herds) were matched with 2191 herds (control herds) that retained their NHS status throughout 2017. Previous history of BVD infection, herd size, herd expansion, the purchase of cattle including potential Trojan cattle and the density of BVD infection within 10 km of the herd emerged as significant factors in a multivariable logistic regression model. This work adds to the evidence base in support of the BVD eradication programme, particularly establishing why BVD re-emerged in herds which had been free of BVD for at least the previous 12 months prior to the identification of a BVD positive calf. This information will be especially important in the context of identifying herds which may be more likely to contain BVD positive animals once the programme moves to herd-based serology status for trading purposes in the post-eradication phase.

Emergence of a non-sporulating secondary phenotype in Clostridium (Clostridioides) difficile ribotype 078 isolated from humans and animals.

Clostridium (Clostridioides) difficile is a Gram positive, spore forming anaerobic bacterium that is a leading cause of antibiotic associated diarrhoea in the developed world. C. difficile is a genetically diverse species that can be divided into 8 phylogenetically distinct clades with clade 5 found to be genetically distant from all others. Isolates with the PCR ribotype 078 belong to clade 5, and are often associated with C. difficile infection in both humans and animals. Colonisation of animals and humans by ribotype 078 raises questions about possible zoonotic transmission, and also the diversity of reservoirs for ribotype 078 strains within the environment. One of the key factors which enables C. difficile to be a successful, highly transmissible pathogen is its ability to produce oxygen resistant spores capable of surviving harsh conditions. Here we describe the existence of a non-sporulating variant of C. difficile ribotype 078 harbouring mutations leading to premature stop codons within the master regulator, Spo0A. As sporulation is imperative to the successful transmission of C. difficile this study was undertaken to investigate phenotypic characteristics of this asporogenous phenotype with regards to growth rate, antibiotic susceptibility, toxin production and biofilm formation.

[Acute renal failure due to thrombotic microangiopathy associated with Castleman's disease]. / Fracaso renal agudo por microangiopatía trombótica asociado a enfermedad de Castleman.

We report a case of a 30-year-old man presenting with abdominal pain, fever, homodynamic instability, hepatosplenomegaly, acute renal failure, cervical lymph nodes, anaemia and thrombocytopenia. The patient was treated with empiric antibiotics, high dose corticosteroids, gammaglobulins, noradrenalin and diary intermittent haemodialysis, with an excellent response. The renal biopsy showed a thrombotic microangiopathy, the lymph node biopsy showed a Castleman s disease. Castleman s disease (also known as giant lymph node hyperplasia or angiofollicular lymph node hyperplasia) is a clinicopathological entity of unknown aetiology. A number of renal alterations have been described in association with the Castleman s disease.

[Changes in the metabolism of iron, copper and zinc in obesity]. / Alteraciones del metabolismo del hierro, cobre y zinc en la obesidad.

Iron, copper and zinc levels in serum and urine of obese patients are studied. Hyperzincurie, hypocuprurie, hypozinquemie, and hypercupremie are observed in the studied groups, in relation to normal controls. There are serious disturbances in the metabolism of the cited oligoelements. The diet has no influence on the observed values. The iron metabolism does not show marked alterations in the case of obesity.