Identifying patient-level risk factors associated with non-ß-lactam resistance outcomes in invasive MRSA infections in the United States using chain graphs.

Background: MRSA is one of the most common causes of hospital- and community-acquired infections. MRSA is resistant to many antibiotics, including ß-lactam antibiotics, fluoroquinolones, lincosamides, macrolides, aminoglycosides, tetracyclines and chloramphenicol. Objectives: To identify patient-level characteristics that may be associated with phenotype variations and that may help improve prescribing practice and antimicrobial stewardship. Methods: Chain graphs for resistance phenotypes were learned from invasive MRSA surveillance data collected by the CDC as part of the Emerging Infections Program to identify patient level risk factors for individual resistance outcomes reported as MIC while accounting for the correlations among the resistance traits. These chain graphs are multilevel probabilistic graphical models (PGMs) that can be used to quantify and visualize the complex associations among multiple resistance outcomes and their explanatory variables. Results: Some phenotypic resistances had low connectivity to other outcomes or predictors (e.g. tetracycline, vancomycin, doxycycline and rifampicin). Only levofloxacin susceptibility was associated with healthcare-associated infections. Blood culture was the most common predictor of MIC. Patients with positive blood culture had significantly increased MIC of chloramphenicol, erythromycin, gentamicin, lincomycin and mupirocin, and decreased daptomycin and rifampicin MICs. Some regional variations were also observed. Conclusions: The differences in resistance phenotypes between patients with previous healthcare use or positive blood cultures, or from different states, may be useful to inform first-choice antibiotics to treat clinical MRSA cases. Additionally, we demonstrated multilevel PGMs are useful to quantify and visualize interactions among multiple resistance outcomes and their explanatory variables.

Etiology and risk factors for bovine respiratory disease in pre-weaned calves on California dairies and calf ranches.

Our study objective was to estimate the magnitude of association of BRD risk factors including failure of passive immunity transfer, sex, age, and the detection of suspected BRD etiological pathogens in pre-weaned dairy calves in California. A conditional logistic regression model and a mixed-effects logistic regression model were used to estimate the association of these potential risk factors with BRD from a matched and nested case-control studies, respectively. For each exposure covariate, the odds ratio (OR) is the ratio of odds of an exposure in a BRD calf (case) to that in a non-BRD calf (control). In the matched case-control study, an interaction term between failure of transfer of passive immunity and sex of calf showed that female calves were more negatively impacted by failure of transfer of passive immunity compared to male calves. The odds ratios comparing failure of transfer of passive immunity in BRD score positive calves versus controls for male calves was 1.34 (95 % CI: 0.87, 2.06) and was 2.47 (95 % CI: 1.54, 3.96) for female calves. The model odds ratios varied from 1.74 (95 % CI: 1.26, 2.42) for Mycoplasma spp. to 9.18 (95 % CI: 2.60, 32.40) for Histophilus somni, with Mannheimia haemolytica and Pasteurella multocida having an OR of 6.64 (95 % CI: 4.39, 10.03) and 6.53 (95 % CI: 4.44, 9.59), respectively. For bovine respiratory syncytial virus positive calves, the OR was 4.60 (95 % CI: 3.04, 6.97). Findings from the nested case-control study showed that based on thoracic ultrasonography findings consistent with BRD, the odds of a calf being 1 day older compared to a day younger were 1.01 (95 % CI: 1.00, 1.02) among BRD cases. For the bacterial and viral pathogens, the OR for Mycoplasma spp. and Pasteurella multocida were 1.85 (95 % CI: 1.24, 2.75) and 1.86 (95 % CI: 1.28, 2.71), respectively. The OR values for these pathogens were similar when both thoracic auscultation and ultrasound findings were used to detect cases of BRD. Based on positive scores for BRD using the California BRD scoring system, the OR for facility type, calf ranch versus dairy farm, was 3.17 (95 % CI: 1.43, 7.01), Mannheimia haemolytica was 3.50 (95 % CI: 2.00, 6.11), Pasteurella multocida was 1.78 (95 % CI: 1.21, 2.60), and bovine coronavirus was 2.61 (95 % CI: 1.85, 3.70). Results from both study designs showed the difference in relative contributions of age, sex, immune status, and pathogens in BRD occurrence between cases and controls in pre-weaned dairy calves.

Corrigendum: Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining.

[This corrects the article DOI: 10.3389/fmicb.2019.00687.].

Shared Multidrug Resistance Patterns in Chicken-Associated Escherichia coli Identified by Association Rule Mining.

Using multiple antimicrobials in food animals may incubate genetically-linked multidrug-resistance (MDR) in enteric bacteria, which can contaminate meat at slaughter. The U.S. National Antimicrobial Resistance Monitoring System tested 21,243 chicken-associated Escherichia coli between 2004 and 2012 for resistance to 15 antimicrobials, resulting in >32,000 possible MDR patterns. We analyzed MDR patterns in this dataset with association rule mining, also called market-basket analysis. The association rules were pruned with four quality measures resulting in a <1% false-discovery rate. MDR rules were more stable across consecutive years than between slaughter and retail. Rules were decomposed into networks with antimicrobials as nodes and rules as edges. A strong subnetwork of beta-lactam resistance existed in each year and the beta-lactam resistances also had strong associations with sulfisoxazole, gentamicin, streptomycin and tetracycline resistances. The association rules concur with previously identified E. coli resistance patterns but provide significant flexibility for studying MDR in large datasets.

Association of plasma haptoglobin concentration and other biomarkers with bovine respiratory disease status in pre-weaned dairy calves.

We conducted a nested, case-control study of pre-weaned dairy calves ( n = 477; 4 California dairy farms) to assess the association between bovine respiratory disease (BRD) and hematologic biomarkers, including plasma haptoglobin (Hp) and plasma bactericide (PB). At each location, heifer or bull dairy calves were observed 2-4 times per week until confirmed as BRD-positive using parallel interpretation of thoracic ultrasound examination and auscultation. In addition, control calves were enrolled after being confirmed as BRD-negative using ultrasound and auscultation. Complete blood counts (CBC), PB, and Hp concentrations were measured. Hp values were higher in calves with confirmed BRD than in controls ( p < 0.01). The area under the curve (AUC) for the various biomarkers was obtained from the corresponding receiver operating characteristic curves. The AUC for Hp was 0.68, a value greater than those for PB or the remaining CBC parameters, indicating that Hp may be the most useful biomarker of BRD in pre-weaned dairy calves. The cutoff value for Hp was 0.195 g/L.

Markov Networks of Collateral Resistance: National Antimicrobial Resistance Monitoring System Surveillance Results from Escherichia coli Isolates, 2004-2012.

Surveillance of antimicrobial resistance (AMR) is an important component of public health. Antimicrobial drug use generates selective pressure that may lead to resistance against to the administered drug, and may also select for collateral resistances to other drugs. Analysis of AMR surveillance data has focused on resistance to individual drugs but joint distributions of resistance in bacterial populations are infrequently analyzed and reported. New methods are needed to characterize and communicate joint resistance distributions. Markov networks are a class of graphical models that define connections, or edges, between pairs of variables with non-zero partial correlations and are used here to describe AMR resistance relationships. The graphical least absolute shrinkage and selection operator is used to estimate sparse Markov networks from AMR surveillance data. The method is demonstrated using a subset of Escherichia coli isolates collected by the National Antimicrobial Resistance Monitoring System between 2004 and 2012 which included AMR results for 16 drugs from 14418 isolates. Of the 119 possible unique edges, 33 unique edges were identified at least once during the study period and graphical density ranged from 16.2% to 24.8%. Two frequent dense subgraphs were noted, one containing the five ß-lactam drugs and the other containing both sulfonamides, three aminoglycosides, and tetracycline. Density did not appear to change over time (p = 0.71). Unweighted modularity did not appear to change over time (p = 0.18), but a significant decreasing trend was noted in the modularity of the weighted networks (p < 0.005) indicating relationships between drugs of different classes tended to increase in strength and frequency over time compared to relationships between drugs of the same class. The current method provides a novel method to study the joint resistance distribution, but additional work is required to unite the underlying biological and genetic characteristics of the isolates with the current results derived from phenotypic data.

Sensitivity and specificity of on-farm scoring systems and nasal culture to detect bovine respiratory disease complex in preweaned dairy calves.

The California (CA) and Wisconsin (WI) clinical scoring systems have been proposed for bovine respiratory disease complex (BRDC) detection in preweaned dairy calves. The screening sensitivity (SSe), for estimating BRDC prevalence in a cohort of calves, diagnostic sensitivity (DSe), for confirming BRDC in ill calves, and specificity (Sp) were estimated for each of the scoring systems, as well as for nasal swab cultures for aerobic bacteria and mycoplasma species. Thoracic ultrasound and auscultation were used as the reference standard tests interpreted in parallel. A total of 536 calves (221 with BRDC and 315 healthy) were sampled from 5 premises in California. The SSe of 46.8%, DSe of 72.6%, and Sp of 87.4% was determined for the CA system. The SSe of 46.0%, DSe of 71.1%, and Sp of 91.2% was determined for the WI system. For aerobic culture, the SSe was 43.4%, DSe was 52.6%, and Sp was 71.3%; for Mycoplasma spp. culture, the SSe was 57.5%, DSe was 68.9%, and Sp was 59.7%. The screening and diagnostic sensitivities of the scoring systems were not significantly different but the Sp of the WI system was greater by 3.8%. Scoring systems can serve as rapid on-farm tools to determine the burden of BRDC in preweaned dairy calves. However, users may expect the SSe to be less than the DSe when confirming BRDC in an ill calf.

Agreement between bovine respiratory disease scoring systems for pre-weaned dairy calves.

Clinical scoring systems have been proposed for respiratory disease diagnosis in calves, including the Wisconsin (WI) system (McGuirk in 2008) which uses five clinical signs, each partitioned into four levels of severity. Recently, we developed the California (CA) bovine respiratory disease (BRD) scoring system requiring less calf handling and consisting of six clinical signs, each classified as normal or abnormal. The objective of this study was to estimate the on-farm agreement between the WI and the CA scoring systems. A total of 100 calves were enrolled on a CA dairy and assessed for BRD case status using the two scoring systems simultaneously. The Kappa coefficient of agreement between these two systems was estimated to be 0.85, which indicated excellent agreement beyond chance. The simpler design and reduced calf handling required by the CA BRD scoring system may make it advantageous for on-farm use.

Development of a novel clinical scoring system for on-farm diagnosis of bovine respiratory disease in pre-weaned dairy calves.

Several clinical scoring systems for diagnosis of bovine respiratory disease (BRD) in calves have been proposed. However, such systems were based on subjective judgment, rather than statistical methods, to weight scores. Data from a pair-matched case-control study on a California calf raising facility was used to develop three novel scoring systems to diagnose BRD in preweaned dairy calves. Disease status was assigned using both clinical signs and diagnostic test results for BRD-associated pathogens. Regression coefficients were used to weight score values. The systems presented use nasal and ocular discharge, rectal temperature, ear and head carriage, coughing, and respiratory quality as predictors. The systems developed in this research utilize fewer severity categories of clinical signs, require less calf handling, and had excellent agreement (Kappa > 0.8) when compared to an earlier scoring system. The first scoring system dichotomized all clinical predictors but required inducing a cough. The second scoring system removed induced cough as a clinical abnormality but required distinguishing between three levels of nasal discharge severity. The third system removed induced cough and forced a dichotomized variable for nasal discharge. The first system presented in this study used the following predictors and assigned values: coughing (induced or spontaneous coughing, 2 points), nasal discharge (any discharge, 3 points), ocular discharge (any discharge, 2 points), ear and head carriage (ear droop or head tilt, 5 points), fever (≥39.2°C or 102.5°F, 2 points), and respiratory quality (abnormal respiration, 2 points). Calves were categorized "BRD positive" if their total score was ≥4. This system correctly classified 95.4% cases and 88.6% controls. The second presented system categorized the predictors and assigned weights as follows: coughing (spontaneous only, 2 points), mild nasal discharge (unilateral, serous, or watery discharge, 3 points), moderate to severe nasal discharge (bilateral, cloudy, mucoid, mucopurlent, or copious discharge, 5 points), ocular discharge (any discharge, 1 point), ear and head carriage (ear droop or head tilt, 5 points), fever (≥39.2°C, 2 points), and respiratory quality (abnormal respiration, 2 points). Calves were categorized "BRD positive" if their total score was ≥4. This system correctly classified 89.3% cases and 92.8% controls. The third presented system used the following predictors and scores: coughing (spontaneous only, 2 points), nasal discharge (any, 4 points), ocular discharge (any, 2 points), ear and head carriage (ear droop or head tilt, 5 points), fever (≥39.2°C, 2 points), and respiratory quality (abnormal respiration, 2 points). Calves were categorized "BRD positive" if their total score was ≥5. This system correctly classified 89.4% cases and 90.8% controls. Each of the proposed systems offer few levels of clinical signs and data-based weights for on-farm diagnosis of BRD in dairy calves.

Endothelial cells enhance tumor cell invasion through a crosstalk mediated by CXC chemokine signaling.

Field cancerization involves the lateral spread of premalignant or malignant disease and contributes to the recurrence of head and neck tumors. The overall hypothesis underlying this work is that endothelial cells actively participate in tumor cell invasion by secreting chemokines and creating a chemotactic gradient for tumor cells. Here we demonstrate that conditioned medium from head and neck tumor cells enhance Bcl-2 expression in neovascular endothelial cells. Oral squamous cell carcinoma-3 (OSCC3) and Kaposi's sarcoma (SLK) show enhanced invasiveness when cocultured with pools of human dermal microvascular endothelial cells stably expressing Bcl-2 (HDMEC-Bcl-2), compared to cocultures with empty vector controls (HDMEC-LXSN). Xenografted OSCC3 tumors vascularized with HDMEC-Bcl-2 presented higher local invasion than OSCC3 tumors vascularized with control HDMEC-LXSN. CXCL1 and CXCL8 were upregulated in primary endothelial cells exposed to vascular endothelial growth factor (VEGF), as well as in HDMEC-Bcl-2. Notably, blockade of CXCR2 signaling, but not CXCR1, inhibited OSCC3 and SLK invasion toward endothelial cells. These data demonstrate that CXC chemokines secreted by endothelial cells induce tumor cell invasion and suggest that the process of lateral spread of tumor cells observed in field cancerization is guided by chemotactic signals that originated from endothelial cells.