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INTRODUCTION Background In recent years, several studies have demonstrated that central blood pressure (BP) and central hemodynamic indexes appear to be better predictors of cardiovascular outcomes, end-organ damage, and mortality than peripheral BP, underlining the special importance of central aortic BP. 1–7 Despite having a similar impact on the peripheral BP, various classes of antihypertensive medications have different effects on the central BP. 2,8 Specifically, β-blockers are associated with more arterial stiffness and therefore, with a lesser reduction in systolic central BP. 2,9–11 This raises the question of whether the effect of b-blockers on the central BP is maintained when part of a multidrug regimen. Exclusion criteria were: arrhythmia, kidney disease requiring dialysis regardless of their glomerular filtration rate, a change in treatment in the month preceding recruitment, and patients who were unable to complete the radial applanation tonometry assessment. Table 2 Uni- and multivariable association between β-blocker exposure, potential confounders, and the delta systolic pressure Crude beta * Multi-variable beta * Potential confounders (95% CI) p-value (95% CI) p-value β-blocker exposure −1.49 (−2.94, −0.03) 0.04 −1.96 (−3.37, −0.56) 0.006 Age † −0.87 (−1.48, −0.28) 0.004 −0.58 (−1.17, 0.01) 0.05 Sex (female vs. male) −2.05 (−3.49, −0.62) 0.005 −2.02 (−3.39, −0.65) 0.004 BMI ‡ 2.07 (0.74, 3.41) 0.002 1.90 (0.55, 3.26) 0.006 History of diabetes 1.77 (0.33, 3.23) 0.02 1.49 (0.09, 2.89) 0.04 History of coronary artery disease 0.37 (−1.65, 2.39) 0.72 - History of kidney disease - eGFR <60 ml/min per 1.73 m2, n (%) −0.86 (−2.57, 0.84) 0.32 - Treatment for dyslipidemia −0.28 (−1.78, 1.23) 0.72 - Active tobacco consumption 2.72 (−0.85, 6.29) 0.13 - Sedentarity 1.07 (−0.40, 2.53) 0.15 - Abbreviations: BMI, body mass index; CI, confidence interval. * The crude and multivariable beta are the mean predicted change in the delta systolic pressures in the uni and multivariable models, respectively. The disparity in the central systolic BP and the delta systolic pressure may explain the worse clinical outcomes associated with β-blockers. 1,2,18 While the less favorable hemodynamic profile of b-blockers might be explained by its negative chronotropic effect, recent data shows that the effect of b-blockers is both heart rate dependent and independent. 2,19 Data regarding the interaction between diabetes and central systolic BP is sparse, however, diabetes seems to be associated with increased arterial stiffness. 10,12–16 In type 2 diabetes, increased arterial stiffness is associated with cardiovascular risk, independently of glycemic control and ambulatory BP. 13 We found that diabetes was associated with an increase in the delta systolic pressure, independently of b-blocker exposure.

Control strains of bacterial pathogens such as Escherichia coli O157:H7 are commonly processed in parallel with test samples in food microbiology laboratories as a quality control measure to assure the satisfactory performance of materials used in the analytical procedure. Before positive findings can be reported for risk management purposes, analysts must have a means of verifying that pathogenic bacteria (e.g., E. coli O157:H7) recovered from test samples are not due to inadvertent contamination with the control strain routinely handled in the laboratory environment. Here, we report on the application of an in-house bioinformatic pipeline for the identification of unique genomic signature sequences in the development of specific oligonucleotide primers enabling the identification of a common positive control strain, E. coli O157:H7 (ATCC 35150), using a simple PCR procedure.

Genomic antimicrobial resistance (AMR) prediction tools have the potential to support foodborne illness outbreak investigations through their application in the analysis of bacterial genomes from causative strains. The AMR marker profile of a strain of interest, initially identified in outbreak-associated clinical samples, may serve as the basis for customization of selective enrichment media, facilitating its recovery from samples in a food safety investigation. Different possibilities for AMR analyses include the use of comprehensive AMR gene databases such as the Comprehensive Antibiotic Resistance Database, which can be mined with in-house bioinformatics alignment tools (e.g., Antimicrobial Resistance Marker Identifier), or publicly available tools based on clinically relevant acquired AMR gene databases (e.g., ResFinder). In combination with a previously reported pipeline (SigSeekr) designed to identify specific DNA sequences associated with a particular strain for its rapid identification by PCR, it should be possible to deploy custom recovery and identification tools for the efficient detection of priority pathogens such as Shiga toxigenic Escherichia coli (STEC) outbreak strains within the time frame of an active investigation. Using a laboratory STEC strain as a model, trimethoprim resistance identified by both Antimicrobial Resistance Marker Identifier and ResFinder was used as the basis for its selective recovery against a background of commensal E. coli bacteria in ground beef samples. Enrichment in modified tryptic soy broth containing trimethoprim greatly enhanced the recovery of low numbers of model strain cells inoculated in ground beef samples, as verified by the enumeration of colonies on plating media using a strain-specific PCR method to determine the recovery efficiency for the target strain. We discuss the relative merits of different AMR marker prediction tools for this purpose and describe how such tools can be utilized to good effect in a typical outbreak investigation scenario.

A method has been developed for the detection in beef trim of priority Shiga toxin–producing E. coli (STEC) strains, defined as E. coli possessing the virulence factors stx 1 and/or stx 2 and intimin (eae), with O serogroups O26, O45, O103, O111, O121, O145, or O157. The method is based on recovery of the target bacteria by overnight enrichment in a broth optimized for recovery of O157 and non-O157 STEC, followed by screening using multiplex PCR techniques targeting (i) stx 1, stx 2, and eae (STE PCR) and (ii) gene sequences associated with the seven priority O serogroups (Poly O PCR), and then direct plating of broth samples positive in both STE and Poly O PCR onto Rainbow agar. Colonies on agar media were screened batchwise for STEC by the STE PCR, and presumptive isolates were characterized using a multiplex PCR and cloth-based hybridization array system targeting key virulence and O serogroup-specific markers. Using one representative strain of each priority O serogroup individually inoculated in beef trim samples, the method exhibited a limit of detection approaching 1 to 2 viable STEC cells per 65 g. None of the uninoculated trim samples produced positive results with either of the screening PCR procedures or on analysis of colonies recovered on plating media. STEC-negative samples were readily identified by screening PCR within 24 h, with a turnaround time of fewer than 4 days for confirmation of positives. The inclusivity and exclusivity characteristics of the screening PCR techniques were verified using a total of 65 different priority STEC strains: 24 nonpriority STEC, 15 non-STEC bacteria, and only those strains bearing the targeted characteristics produced screening PCR-positive results.

The determination of Shiga toxin (ST) subtypes can be an important element in the risk characterization of foodborne ST-producing Escherichia coli (STEC) isolates for making risk management decisions. ST subtyping methods include PCR techniques based on electrophoretic or pyrosequencing analysis of amplicons and in silico techniques based on whole genome sequence analysis using algorithms that can be readily incorporated into bioinformatics analysis pipelines for characterization of isolates by their genetic composition. The choice of technique will depend on the performance characteristics of the method and an individual laboratory's access to specialized equipment or personnel. We developed two whole genome sequence-based ST subtyping tools: (i) an in silico PCR algorithm requiring genome assembly to replicate a reference PCR-based method developed by the Statens Serum Institut (SSI) and (ii) an assembly-independent routine in which raw sequencing results are mapped to a database of known ST subtype sequence variants (V-Typer). These tools were evaluated alongside the SSI reference PCR method and a recently described PCR-based pyrosequencing technique. The V-Typer method results corresponded closely with the reference method in the analysis of 67 STEC cultures obtained from a World Health Organization National Reference Laboratory. In contrast, the in silico PCR method failed to detect ST subtypes in several cases, a result which we attribute to assembly-induced errors typically encountered with repetitive gene sequences. The V-Typer can be readily integrated into bioinformatics protocols used in the identification and characterization of foodborne STEC isolates.

A cloth-based hybridization array system (CHAS) was developed for the identification of foodborne colony isolates of seven priority enterohemorrhagic Escherichia coli (EHEC-7) serogroups targeted by U. S. food inspection programs. Gene sequences associated with intimin; Shiga-like toxins 1 and 2; and the antigenic markers O26, O45, O103, O111, O121, O145, and O157 were amplified in a multiplex PCR incorporating a digoxigenin label, and detected by hybridization of the PCR products with an array of specific oligonucleotide probes immobilized on a polyester cloth support, with subsequent immunoenzymatic assay of the captured amplicons. The EHEC-7 CHAS exhibited 100 % inclusivity and 100 % exclusivity characteristics with respect to detection of the various markers among 89 different E. coli strains, with various marker gene profiles and 15 different strains of non-E. coli bacteria.

A simple immunoenzymatic enterohemorrhagic Escherichia coli (EHEC) colony check (ECC) assay was developed for the presumptive identification of priority EHEC colonies isolated on plating media from enrichment broth cultures of foods. With this approach, lipopolysaccharide extracted from a colony is spotted on the grid of a polymyxin-coated polyester cloth strip, and bound E. coli serogroup O26, O45, O103, O111, O121, O145, and O157 antigens are subsequently detected by sequential reactions with a pool of commercially available peroxidase-conjugated goat antibodies and tetramethylbenzidine substrate solution. Each strip can accommodate up to 15 colonies, and test results are available within 30 min. Assay performance was verified using colonies from a total of 73 target EHEC isolates covering the range of designated priority serogroups (all of which were reactive), 41 nontarget E. coli isolates including several nontarget Shiga toxin-producing E. coli serogroups (all unreactive), and 33 non-E. coli strains (all unreactive except two bacterial strains possessing O-antigenic structures in common with those of the priority EHEC). The ECC assay was reactive with target colonies grown on several types of selective and nonselective plating media designed for their cultivation. These results support the use of the ECC assay for high-throughput screening of colonies isolated on plating media for detecting priority EHEC strains in foods.

Non-O157 enterohemorrhagic Escherichia coli in priority serogroups O26, O45, O103, O111, O121, and O145 are increasingly recognized as important human pathogens. In the present study, a panel of monoclonal antibodies (MAbs) to the lipopolysaccharide O antigens of E. coli in serogroups O26, O45, O103, O111, O121, and O145 was produced. The specificity was evaluated by examining the reactivity of the MAbs with 50 E. coli strains and 42 non-E. coli bacteria, and several MAbs highly specific for E. coli strains in each of the six non-O157 priority serogroups were identified. The use of these highly specific MAbs may be of considerable value for determining whether an E. coli isolate belongs to one of the six priority non-O157 serogroups, for developing specific detection assays for these organisms, and for characterizing the lipopolysaccharide O antigens of isolates in these serogroups.