Effect of pooled tracheal sample testing on the probability of Mycoplasma hyopneumoniae detection.

Tracheal pooling for Mycoplasma hyopneumoniae (M. hyopneumoniae) DNA detection allows for decreased diagnostic cost, one of the main constraints in surveillance programs. The objectives of this study were to estimate the sensitivity of pooled-sample testing for the detection of M. hyopneumoniae in tracheal samples and to develop probability of M. hyopneumoniae detection estimates for tracheal samples pooled by 3, 5, and 10. A total of 48 M. hyopneumoniae PCR-positive field samples were pooled 3-, 5-, and 10-times using field M. hyopneumoniae DNA-negative samples and tested in triplicate. The sensitivity was estimated at 0.96 (95% credible interval [Cred. Int.]: 0.93, 0.98) for pools of 3, 0.95 (95% Cred. Int: 0.92, 0.98) for pools of 5, and 0.93 (95% Cred. Int.: 0.89, 0.96) for pools of 10. All pool sizes resulted in PCR-positive if the individual tracheal sample Ct value was < 33. Additionally, there was no significant decrease in the probability of detecting at least one M. hyopneumoniae-infected pig given any pool size (3, 5, or 10) of tracheal swabs. Furthermore, this manuscript applies the probability of detection estimates to various real-life diagnostic testing scenarios. Combining increased total animals sampled with pooling can be a cost-effective tool to maximize the performance of M. hyopneumoniae surveillance programs.

Detection and disease diagnosis trends (2017-2022) for Streptococcus suis, Glaesserella parasuis, Mycoplasma hyorhinis, Actinobacillus suis and Mycoplasma hyosynoviae at Iowa State University Veterinary Diagnostic Laboratory.

BACKGROUND: Accurate measurement of disease associated with endemic bacterial agents in pig populations is challenging due to their commensal ecology, the lack of disease-specific antemortem diagnostic tests, and the polymicrobial nature of swine diagnostic cases. The main objective of this retrospective study was to estimate temporal patterns of agent detection and disease diagnosis for five endemic bacteria that can cause systemic disease in porcine tissue specimens submitted to the Iowa State University Veterinary Diagnostic Laboratory (ISU VDL) from 2017 to 2022. The study also explored the diagnostic value of specific tissue specimens for disease diagnosis, estimated the frequency of polymicrobial diagnosis, and evaluated the association between phase of pig production and disease diagnosis. RESULTS: S. suis and G. parasuis bronchopneumonia increased on average 6 and 4.3%, while S. suis endocarditis increased by 23% per year, respectively. M. hyorhinis and A. suis associated serositis increased yearly by 4.2 and 12.8%, respectively. A significant upward trend in M. hyorhinis arthritis cases was also observed. In contrast, M. hyosynoviae arthritis cases decreased by 33% average/year. Investigation into the diagnostic value of tissues showed that lungs were the most frequently submitted sample, However, the use of lung for systemic disease diagnosis requires caution due to the commensal nature of these agents in the respiratory system, compared to systemic sites that diagnosticians typically target. This study also explored associations between phase of production and specific diseases caused by each agent, showcasing the role of S. suis arthritis in suckling pigs, meningitis in early nursery and endocarditis in growing pigs, and the role of G. parasuis, A. suis, M. hyorhinis and M. hyosynoviae disease mainly in post-weaning phases. Finally, this study highlighted the high frequency of co-detection and -disease diagnosis with other infectious etiologies, such as PRRSV and IAV, demonstrating that to minimize the health impact of these endemic bacterial agents it is imperative to establish effective viral control programs. CONCLUSIONS: Results from this retrospective study demonstrated significant increases in disease diagnosis for S. suis, G. parasuis, M. hyorhinis, and A. suis, and a significant decrease in detection and disease diagnosis of M. hyosynoviae. High frequencies of interactions between these endemic agents and with viral pathogens was also demonstrated. Consequently, improved control programs are needed to mitigate the adverse effect of these endemic bacterial agents on swine health and wellbeing. This includes improving diagnostic procedures, developing more effective vaccine products, fine-tuning antimicrobial approaches, and managing viral co-infections.

The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs.

The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species, this can affect the health of humans as well as livestock. Here, we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography, and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realized.

Mycoplasma hyopneumoniae infection dynamics in naïve replacement gilts introduced to positive farms.

This study was designed to characterize the dynamics of infection of Mycoplasma hyopneumoniae in naïve replacement gilts after introduction to positive systems. Ninety-eight naïve gilts were monitored in three positive commercial farms (A, B, and C). The näive gilts were housed for 21 days in pens adjacently located to older gilt cohorts (named seeders), which have been naturally exposed to the positive farms. The infection dynamics was evaluated by PCR and ELISA, from laryngeal swabs and serum samples, respectively. Samples were collected at 150 (arrival), 165, 180, 210, 240, 270, 300 days of age (doa), and pre-farrowing. Infection occurred rapidly on farms A and B, taking 25.2 and 23.9 days for 95% of gilts to be PCR positive, respectively. There was no influence on the number of seeders at the time of exposure, but their absence (farm C) could explain the extended period it took for gilts to get infected (69.4 days). On average, it took 162.2 days after the first PCR detection for 85% of gilts to stop shedding the bacterium. The serology results were consistent with the herd infection curve. At pre-farrowing, 100% of gilts seroconverted and 36.7% remained PCR positive. A total of 1.33% of piglets were positive at weaning. Fifteen variants were detected among the three farms by MLVA. The acclimation protocol was efficient and easy to perform, and the presence of seeders was likely critical for early acclimation for M. hyopneumoniae.

Infection prediction in swine populations with machine learning.

The pork industry is an essential part of the global food system, providing a significant source of protein for people around the world. A major factor restraining productivity and compromising animal wellbeing in the pork industry is disease outbreaks in pigs throughout the production process: widespread outbreaks can lead to losses as high as 10% of the U.S. pig population in extreme years. In this study, we present a machine learning model to predict the emergence of infection in swine production systems throughout the production process on a daily basis, a potential precursor to outbreaks whose detection is vital for disease prevention and mitigation. We determine features that provide the most value in predicting infection, which include nearby farm density, historical test rates, piglet inventory, feed consumption during the gestation period, and wind speed and direction. We utilize these features to produce a generalizable machine learning model, evaluate the model's ability to predict outbreaks both seven and 30 days in advance, allowing for early warning of disease infection, and evaluate our model on two swine production systems and analyze the effects of data availability and data granularity in the context of our two swine systems with different volumes of data. Our results demonstrate good ability to predict infection in both systems with a balanced accuracy of [Formula: see text] on any disease in the first system and balanced accuracies (average prediction accuracy on positive and negative samples) of [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] on porcine reproductive and respiratory syndrome, porcine epidemic diarrhea virus, influenza A virus, and Mycoplasma hyopneumoniae in the second system, respectively, using the six most important predictors in all cases. These models provide daily infection probabilities that can be used by veterinarians and other stakeholders as a benchmark to more timely support preventive and control strategies on farms.

Evaluation of the application of sequence data to the identification of outbreaks of disease using anomaly detection methods.

Anomaly detection methods have a great potential to assist the detection of diseases in animal production systems. We used sequence data of Porcine Reproductive and Respiratory Syndrome (PRRS) to define the emergence of new strains at the farm level. We evaluated the performance of 24 anomaly detection methods based on machine learning, regression, time series techniques and control charts to identify outbreaks in time series of new strains and compared the best methods using different time series: PCR positives, PCR requests and laboratory requests. We introduced synthetic outbreaks of different size and calculated the probability of detection of outbreaks (POD), sensitivity (Se), probability of detection of outbreaks in the first week of appearance (POD1w) and background alarm rate (BAR). The use of time series of new strains from sequence data outperformed the other types of data but POD, Se, POD1w were only high when outbreaks were large. The methods based on Long Short-Term Memory (LSTM) and Bayesian approaches presented the best performance. Using anomaly detection methods with sequence data may help to identify the emergency of cases in multiple farms, but more work is required to improve the detection with time series of high variability. Our results suggest a promising application of sequence data for early detection of diseases at a production system level. This may provide a simple way to extract additional value from routine laboratory analysis. Next steps should include validation of this approach in different settings and with different diseases.

Molecular characterization of Glaesserella parasuis strains circulating in North American swine production systems.

BACKGROUND: Glaesserella parasuis is the causative agent of Glässer's disease in pigs. Serotyping is the most common method used to type G. parasuis isolates. However, the high number of non-typables (NT) and low discriminatory power make serotyping problematic. In this study, 218 field clinical isolates and 15 G. parasuis reference strains were whole-genome sequenced (WGS). Multilocus sequence types (MLST), serotypes, core-genome phylogeny, antimicrobial resistance (AMR) genes, and putative virulence gene information was extracted. RESULTS: In silico WGS serotyping identified 11 of 15 serotypes. The most frequently detected serotypes were 7, 13, 4, and 2. MLST identified 72 sequence types (STs), of which 66 were novel. The most predominant ST was ST454. Core-genome phylogeny depicted 3 primary lineages (LI, LII, and LIII), with LIIIA sublineage isolates lacking all vtaA genes, based on the structure of the phylogenetic tree and the number of virulence genes. At least one group 1 vtaA virulence genes were observed in most isolates (97.2%), except for serotype 8 (ST299 and ST406), 15 (ST408 and ST552) and NT (ST448). A few group 1 vtaA genes were significantly associated with certain serotypes or STs. The putative virulence gene lsgB, was detected in 8.3% of the isolates which were predominantly of serotype 5/12. While most isolates carried the bcr, ksgA, and bacA genes, the following antimicrobial resistant genes were detected in lower frequency;  blaZ (6.9%), tetM (3.7%), spc (3.7%), tetB (2.8%), bla-ROB-1 (1.8%), ermA (1.8%), strA (1.4%), qnrB (0.5%), and aph3''Ia (0.5%).   CONCLUSION: This study showed the use of WGS to type G. parasuis isolates and can be considered an alternative to the more labor-intensive and traditional serotyping and standard MLST. Core-genome phylogeny provided the best strain discrimination. These findings will lead to a better understanding of the molecular epidemiology and virulence in G. parasuis that can be applied to the future development of diagnostic tools, autogenous vaccines, evaluation of antibiotic use, prevention, and disease control.

Predicting antimicrobial resistance of bacterial pathogens using time series analysis.

Antimicrobial resistance (AMR) is arguably one of the major health and economic challenges in our society. A key aspect of tackling AMR is rapid and accurate detection of the emergence and spread of AMR in food animal production, which requires routine AMR surveillance. However, AMR detection can be expensive and time-consuming considering the growth rate of the bacteria and the most commonly used analytical procedures, such as Minimum Inhibitory Concentration (MIC) testing. To mitigate this issue, we utilized machine learning to predict the future AMR burden of bacterial pathogens. We collected pathogen and antimicrobial data from >600 farms in the United States from 2010 to 2021 to generate AMR time series data. Our prediction focused on five bacterial pathogens (Escherichia coli, Streptococcus suis, Salmonella sp., Pasteurella multocida, and Bordetella bronchiseptica). We found that Seasonal Auto-Regressive Integrated Moving Average (SARIMA) outperformed five baselines, including Auto-Regressive Moving Average (ARMA) and Auto-Regressive Integrated Moving Average (ARIMA). We hope this study provides valuable tools to predict the AMR burden not only of the pathogens assessed in this study but also of other bacterial pathogens.

A tool to enhance antimicrobial stewardship using similarity networks to identify antimicrobial resistance patterns across farms.

Antimicrobial resistance (AMR) is one of the major challenges of the century and should be addressed with a One Health approach. This study aimed to develop a tool that can provide a better understanding of AMR patterns and improve management practices in swine production systems to reduce its spread between farms. We generated similarity networks based on the phenotypic AMR pattern for each farm with information on important bacterial pathogens for swine farming based on the Euclidean distance. We included seven pathogens: Actinobacillus suis, Bordetella bronchiseptica, Escherichia coli, Glaesserella parasuis, Pasteurella multocida, Salmonella spp., and Streptococcus suis; and up to seventeen antibiotics from ten classes. A threshold criterion was developed to reduce the density of the networks and generate communities based on their AMR profiles. A total of 479 farms were included in the study although not all bacteria information was available on each farm. We observed significant differences in the morphology, number of nodes and characteristics of pathogen networks, as well as in the number of communities and susceptibility profiles of the pathogens to different antimicrobial drugs. The methodology presented here could be a useful tool to improve health management, biosecurity measures and prioritize interventions to reduce AMR spread in swine farming.

Vivencias en la integración psicosocial de jóvenes y adultos jóvenes sobrevivientes de cáncer / Experiences in the psychosocial integration of youth and young adult cancer survivors

Objetivo principal: Analizar la experiencia de jóvenes sobrevivientes de cáncer en su transitar hacia la integración socio familiar. Metodología: Revisión narrativa de artículos científicos publicados entre 2012 y 2022, indexados en las bases de datos Pubmed, CINHAL, CUIDEN y Web of Science, los cuales fueron sometidos a un análisis temático. Resultados principales: Por la enfermedad y tratamiento intensivo, la sobrevivencia les exige integrarse a una nueva vida, marcada por secuelas físicas, psicoemocionales, sociales, valóricas y espirituales, que llevan a modificar su calidad de vida y prioridades en busca de la normalidad. Conclusión principal: Es necesario que los jóvenes se hagan parte de su proceso de integración, permitiendo trascender con bienestar a su adultez, a través de un seguimiento activo por parte de los equipos de salud. Una adecuada integración y adquisición de responsabilidades sobre la enfermedad y cuidado.(AU)

Objective: To analyze the experience of young cancer survivors in their transition to social and family integration. Methods: Narrative review of scientific articles published between 2012 and 2022, indexed in Pubmed, CINHAL, CUIDEN y Web of Science databases, which were subjected to a thematic analysis. Results: Due to the disease and intensive treatment, survival requires them to integrate into a new life, marked by physical, psychoemotional, social, value and spiritual sequelae, which lead them to modify their quality of life and priorities in search of normality. Conclusions: It is necessary that young people become part of their integration process, allowing them to transcend with wellbeing into adulthood, through an active follow-up by the health teams. An adequate integration and acquisition of responsibility for the disease and care.(AU)

Effect of testing protocol and within-pen prevalence on the detection of Mycoplasma hyopneumoniae DNA in oral fluid samples.

Combinations of 2 nucleic acid extractions and 3 Mycoplasma hyopneumoniae (MHP) PCRs (namely Protocol 1, 2, 3, and 4) were compared in terms of the probability of detecting DNA in pen-based oral fluid samples as a function of within-pen MHP prevalence. Oral fluid samples were created by randomly assigning 39 7-week old pigs to one of 5 pens, i.e., negative control pen (3 pigs) and 4 pens of 9 pigs each that differed in the proportion of MHP-inoculated pigs (1, 3, 6, or 9). Deep tracheal swabs were collected twice weekly to establish individual pig MHP infection status and derive within-pen prevalence estimation. On DPI 3, tracheal swabs from 15 of 19 inoculated pigs were MHP DNA positive. Oral fluids (n = 320) were collected daily from - 4 to 59 days post inoculation (DPI). Using a piecewise exponential model to account for within-pen transmission dynamics followed by a mixed-effect logistic regression, the probability of detecting MHP DNA in oral fluids was positively associated with within-pen prevalence (P < 0.0001) and differed among test protocols. MHP DNA was detected in 173 oral fluid samples with Protocol 3 versus 148, 134, and 101 with Protocols 4, 2, and 1, respectively. At 100% within-pen prevalence, the probability of detecting MHP DNA in oral fluids was highest using Protocol 3 (95.7%), followed by Protocols 4 (70.1%), 2 (60.1%), and 1 (34.0%). The fact that PCR protocols performed differently suggests that further improvements in extraction methods and MHP PCRs are possible. In the field, the dynamics of MHP infections should be taken into account if using oral fluid samples in surveillance.

Cough associated with the detection of Mycoplasma hyopneumoniae DNA in clinical and environmental specimens under controlled conditions.

BACKGROUND: The association of cough with Mycoplasma hyopneumoniae (MHP) DNA detection in specimens was evaluated under conditions in which the MHP status of inoculated and contact-infected pen mates was closely monitored for 59 days post-inoculation (DPI). METHODS: Seven-week-old pigs (n = 39) were allocated to five rooms (with one pen). Rooms contained 9 pigs each, with 1, 3, 6, or 9 MHP-inoculated pigs, respectively, except Room 5 (three sham-inoculated pigs). Cough data (2 × week) and specimens, tracheal swabs (2 × week), oral fluids (daily), drinker wipes (~ 1 × week), and air samples (3 × week) were collected. At 59 DPI, pigs were euthanized, and lung and trachea were evaluated for gross and microscopic lesions. Predictive cough value to MHP DNA detection in drinker and oral fluid samples were estimated using mixed logistic regression. RESULTS: Following inoculation, MHP DNA was first detected in tracheal swabs from inoculated pigs (DPI 3), then oral fluids (DPI 8), air samples (DPI 10), and drinker wipes (21 DPI). MHP DNA was detected in oral fluids in 17 of 59 (Room 1) to 43 of 59 (Room 3) samples, drinker wipes in 4 of 8 (Rooms 2 and 3) to 5 of 8 (Rooms 1 and 4) samples, and air samples in 5 of 26 (Room 2) or 3 of 26 (Room 4) samples. Logistic regression showed that the frequency of coughing pigs in a pen was associated with the probability of MHP DNA detection in oral fluids (P < 0.01) and nearly associated with drinker wipes (P = 0.08). Pathology data revealed an association between the period when infection was first detected and the severity of gross lung lesions. CONCLUSIONS: Dry, non-productive coughs suggest the presence of MHP, but laboratory testing and MHP DNA detection is required for confirmation. Based on the data from this study, oral fluids and drinker wipes may provide a convenient alternative for MHP DNA detection at the pen level when cough is present. This information may help practitioners in specimen selection for MHP surveillance.

Mild COVID-19 Illness as a Risk Factor for Venous Thromboembolism.

Introduction From the beginning of the current coronavirus disease 2019 (COVID-19) pandemic, there is cumulative evidence suggesting that patients hospitalized due to this disease are at a high risk for venous thromboembolism (VTE). The association between mild non-hospitalized illness and VTE is unclear. The purpose of this research is to assess the association between VTE and mild COVID-19 infection. Methods A case-control study was conducted. The cases were adult patients diagnosed with VTE from March 1, 2020 to March 31, 2021. The controls were randomly chosen adult patients who required healthcare services that were equivalent to those of the cases, for any cause, during the same time period, without a VTE diagnosis. To assess the association between mild COVID and VTE, a multivariate logistic regression analysis was conducted, considering other thromboembolic risk variables, such as age, gender and active cancer, among others. A p-value <0.05 was considered statistically significant. Results A total of 186 cases and 475 controls were analyzed. There were 21 (11.3%) and 31 (6.5%) patients infected with mild COVID-19 in the previous three months in the groups of cases and controls, respectively. Mild COVID-19 infection was statistically significant as a risk factor for VTE both in the univariate analysis and in the multivariate analysis, OR=1.82 (95% CI 1.02-3.26) and OR=2.62 (95% CI 1.34-5.13), respectively. Conclusion Mild COVID-19 infection might be an independent risk factor for VTE. We conclude that the results suggest some thromboprophylaxis strategy should be considered in certain patients with COVID-19 infection in an outpatient fashion.

Comparison of Mycoplasma hyopneumoniae response to infection by route of exposure.

Mycoplasma hyopneumoniae (MHP) is a concern both for pig well-being and producer economic viability. In the absence of fully protective health interventions, producers rely on controlled exposure to induce an immune response in pigs and minimize the clinical outcomes of MHP infection in pig populations. This study compared the effect of route of exposure on MHP infection, antibody response, clinical signs, and pathology. Six-week-old MHP-negative pigs (n = 78) were allocated to negative control (n = 6) or one of three MHP exposure routes: intratracheal (n = 24, feeding catheter), intranasal (n = 24, atomization device), and aerosol (n = 24, fogger). Body weight, cough indices, and samples (serum, oral fluid, tracheal) were collected weekly through 49 days post-exposure (DPE). Intratrachal exposure produced the highest proportion (24/24) of MHP DNA-positive pigs on DPE 7, as well as earlier and higher serum antibody response. Intranasal and aerosol exposures resulted in infection with MHP DNA detected in tracheal samples from 18/24 and 21/24 pigs on DPE 7, respectively. Aerosol exposure had the least impact on weight gain (0.64 kg/day). No difference was observed among treatment groups in coughing and lung lesions at necropsy. While intratracheal inoculation and seeder animals are frequently used in swine production settings, intranasal or aerosol exposure are viable alternatives to achieve MHP infection. Regardless of the route, steps should be taken to verify the purity of the inoculum and, in the case of aerosol exposure, avert the unintended exposure of personnel and animals to other pathogens.

Molecular characterization of Glaesserella parasuis strains isolated from North America, Europe and Asia by serotyping PCR and LS-PCR.

Glaesserella parasuis strains were characterized by serotyping PCR, vtaA virulence marker Leader Sequence (LS)-PCR, clinical significance, and geographic region. Overall, the serovars 4, 5/12, 7, 1, and 13 were the most commonly detected. Serovars of greatest clinical relevance were systemic isolates that had a higher probability of being serovar 5/12, 13, or 7. In comparison, pulmonary isolates had a higher likelihood of being serovars 2, 4, 7, or 14. Serovars 5/12 and 13 have previously been considered disease-associated, but this study agrees with other recent studies showing that serovar 7 is indeed associated with systemic G. parasuis disease. Serovar 4 strains illustrated how isolates can have varying degrees of virulence and be obtained from pulmonary, systemic, or nasal sites. Serovars 8, 9, 15, and 10 were predominantly obtained from nasal samples, which indicates a limited clinical significance of these serovars. Additionally, most internal G. parasuis isolates were classified as virulent by LS-PCR and were disease-associated isolates, including serovars 1, 2, 4, 5/12, 7, 13, and 14. Isolates from the nasal cavity, including serovars 6, 9, 10, 11, and 15, were classified as non-virulent by LS-PCR. In conclusion, the distribution of G. parasuis serovars remains constant, with few serovars representing most of the strains isolated from affected pigs. Moreover, it was confirmed that the LS-PCR can be used for G. parasuis virulence prediction of field strains worldwide.

Mycoplasma hyopneumoniae Surveillance in Pig Populations: Establishing Sampling Guidelines for Detection in Growing Pigs.

Antemortem detection of Mycoplasma hyopneumoniae infection in swine production systems has relied on antibody testing, but the availability of tests based on DNA detection and novel diagnostic specimens, e.g., tracheal swabs and oral fluids, has the potential to improve M. hyopneumoniae surveillance. A field study was performed over a 14-week period during which 10 pigs in one pen at the center of a room with 1,250 6-week-old pigs housed in 46 pens were intratracheally inoculated with M. hyopneumoniae Thereafter, one tracheal sample, four serum samples, and one oral fluid sample were collected from every pen at 2-week intervals. Tracheal and oral fluid samples were tested for M. hyopneumoniae DNA and serum samples for M. hyopneumoniae antibody. Test results were modeled using a hierarchical Bayesian model, based on a latent spatial piecewise exponential survival model, to estimate the probability of detection by within-pen prevalence, number of positive pens in the barn, sample allocation, sample size, and sample type over time. Analysis showed that tracheal samples provided the earliest detection, especially at large sample sizes. While serum samples are more commonly collected and are less expensive to test, high probability of detection estimates were only obtained 30 days postexposure at large sample sizes. In all scenarios, probability of detection estimates for oral fluids within 30 days were significantly lower than those for tracheal and serum samples. Ultimately, the choice of specimen type, sample number, and assay will depend on testing objectives and economics, but the estimates provided here will assist in the design of M. hyopneumoniae surveillance and monitoring programs for different situations.

Adapting a porcine reproductive and respiratory syndrome virus (PRRSV) oral fluid antibody ELISA to routine surveillance.

Distinct from tests used in diagnostics, tests used in surveillance must provide for detection while avoiding false alarms, i.e., acceptable diagnostic sensitivity but high diagnostic specificity. In the case of the reproductive and respiratory syndrome virus (PRRSV), RNA detection meets these requirements during the period of viremia, but antibody detection better meets these requirements in the post-viremic stage of the infection. Using the manufacturer's recommended cut-off (S/P ≥ 0.4), the diagnostic specificity of a PRRSV oral fluid antibody ELISA (IDEXX Laboratories, Inc., Westbrook, ME, USA) evaluated in this study was previously reported as ≥ 97 %. The aim of this study was to improve its use in surveillance by identifying a cut-off that would increase diagnostic specificity yet minimally impact its diagnostic sensitivity. Three sample sets were used to achieve this goal: oral fluids (n = 596) from pigs vaccinated with a modified live PRRSV vaccine under experimental conditions, field oral fluids (n = 1574) from 94 production sites of known negative status, and field oral fluids (n = 1380) from 211 sites of unknown PRRSV status. Based on the analysis of samples of known status (experimental samples and field samples from negative sites), a cut-off of S/P ≥ 1.0 resulted in a diagnostic specificity of 99.2 (95 % CI: 98.8, 99.7) and a diagnostic sensitivity of 96.5 (95 % CI: 85.2, 99.2). Among 211 sites of unknown status, 81 sites were classified as antibody positive using the manufacturer's cut-off; 20 of which were reclassified as negative using a cut-off of S/P ≥ 1.0. Further analysis showed that these 20 sites had a small proportion of samples (18.0 %) with S/P values just exceeding the manufacturer's cut-off (x̄ = 0.5). Whereas the remainder of positive sites (n = 61) had a high proportion of samples (76.3 %) with high S/P values (x̄ = 6.6). Thus, the manufacturer's cut-off (S/P ≥ 0.4) is appropriate for diagnostic applications, but a cut-off of S/P ≥ 1.0 provided the higher specificity required for surveillance. A previously unreported finding in this study was a statistically significant association between unexpected reactors and specific production sites and animal ages or stages. While beyond the scope of this study, these data suggested that certain animal husbandry or production practices may be associated with non-specific reactions.

Performance of Commercial Mycoplasma hyopneumoniae Serum Enzyme-Linked Immunosorbent Assays under Experimental and Field Conditions.

Mycoplasma hyopneumoniae is an economically significant pathogen of swine. M. hyopneumoniae serum antibody detection via commercial enzyme-linked immunosorbent assays (ELISAs) is widely used for routine surveillance in commercial swine production systems. Samples from two studies were used to evaluate assay performance. In study 1, 6 commercial M. hyopneumoniae ELISAs were compared using serum samples from 8-week-old cesarean-derived, colostrum-deprived (CDCD) pigs allocated to the following 5 inoculation groups of 10 pigs each: (i) negative control, (ii) Mycoplasma flocculare (strain 27399), (iii) Mycoplasma hyorhinis (strain 38983), (iv) Mycoplasma hyosynoviae (strain 34428), and (v) M. hyopneumoniae (strain 232). Weekly serum and daily oral fluid samples were collected through 56 days postinoculation (dpi). The true status of pigs was established by PCR testing on oral fluids samples over the course of the observation period. Analysis of ELISA performance at various cutoffs found that the manufacturers' recommended cutoffs were diagnostically specific, i.e., produced no false positives, with the exceptions of 2 ELISAs. An analysis based on overall misclassification error rates found that 4 ELISAs performed similarly, although one assay produced more false positives. In study 2, the 3 best-performing ELISAs from study 1 were compared using serum samples generated under field conditions. Ten 8-week-old pigs were intratracheally inoculated with M. hyopneumoniae Matched serum and tracheal samples (to establish the true pig M. hyopneumoniae status) were collected at 7- to 14-day intervals through 98 dpi. Analyses of sensitivity and specificity showed similar performance among these 3 ELISAs. Overall, this study provides an assessment of the performance of current M. hyopneumoniae ELISAs and an understanding of their use in surveillance.

Genetic characterization of Streptococcus equi subspecies zooepidemicus associated with high swine mortality in the United States.

High mortality events due to Streptococcus equi subspecies zooepidemicus (Streptococcus zooepidemicus) in swine have not previously been reported in the United States. In September and October 2019, outbreaks with swine mortality up to 50% due to S. zooepidemicus septicaemia were reported in Ohio and Tennessee. Genomic epidemiological analysis revealed that the eight outbreak isolates were clustered together with ATCC 35246, a Chinese strain caused outbreaks with high mortality, also closely related to three isolates from human cases from Virginia, but significantly different from an outbreak-unrelated swine isolate from Arizona and most isolates from other animal species. Comparative genomic analysis on two outbreak isolates and another outbreak-unrelated isolate identified several genomic islands and virulence genes specifically in the outbreak isolates only, which are likely associated with the high mortality observed in the swine population. These findings have implications for understanding, tracking and possibly preventing diseases caused by S. zooepidemicus in swine.

Risk factors and role of low molecular weight heparin in obstetric complications among women with inherited thrombophilia - a cohort study

ABSTRACT Introduction: Although there is a vast literature regarding the association between inherited thrombophilia, obstetric complications and the effect of low molecular weight heparin (LMWH), these are controversial and we have not found publications related to additional risk factors other than thrombophilia.Our objectives were to assess the prevalence of miscarriage, placenta-mediated pregnancy complications and fetal loss in pregnant women with IT, establishing associated risk factors and the effect of LMWH. Materials and methods: A retrospective cohort of pregnant women with IT was formed. Risk factors considered were: high-risk IT, age ≥35 years, body mass index ≥25 and ≥30, assisted reproductive technology, antiphospholipid antibodies, autoimmune disease, first-degree family history of obstetric complications and personal history of venous or arterial thromboembolic disease, the outcomes being M, FL and PMPC. Results and conclusions: Data from 250 pregnancies in 88 women were obtained.There were 112 (45%) Ms, 13 (5.2%) FLs and 25 (10%) PMPCs.High-risk IT was associated with FL (OR = 4.96; 95% CI, 1.42-17.3). Antiphospholipid antibodies and family history of obstetric complications were associated with PMPC (OR = 7.12; 95% CI, 1.89-26.74, OR = 3.88; 95% CI, 1.18-12.78, respectively). The LMWH presented a benefit in the combined outcome (any obstetric complication, OR = 0.25; 95% CI, 0.12-0.54) and M (OR = 0.41; 95% CI, 0.20-0.82).We conclude that obstetric complications are common in women with IT. Antiphospholipid antibodies, family history of obstetric complications and high-risk IT might be additional risk factors. The LMWH has an apparent protective effect against obstetric complications, which is consistent with some previous studies.