Expression of an Epitope-Tagged Virulence Protein in Rickettsia parkeri Using Transposon Insertion

Despite recent advances in our ability to genetically manipulate Rickettsia, little has been done to employ genetic tools to study the expression and localization of Rickettsia virulence proteins. Using a mariner-based Himar1 transposition system, we expressed an epitope-tagged variant of the actin polymerizing protein RickA under the control of its native promoter in Rickettsia parkeri, allowing the detection of RickA using commercially-available antibodies. Native RickA and epitope-tagged RickA exhibited similar levels of expression and were specifically localized to bacteria. To further facilitate protein expression in Rickettsia, we also developed a plasmid for Rickettsia insertion and expression (pRIE), containing a variant Himar1 transposon with enhanced flexibility for gene insertion, and used it to generate R. parkeri strains expressing diverse fluorescent proteins. Expression of epitope-tagged proteins in Rickettsia will expand our ability to assess the regulation and function of important virulence factors

Estimating Myocardial Infarction Size With a Simple Electrocardiographic Marker Score

© 2020 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. Background: Myocardial infarction (MI) size is a key predictor of prognosis in post-MI patients. Cardiovascular magnetic resonance (CMR) is the gold standard test for MI quantification, but the ECG is less expensive and more widely available. We sought to quantify the relationship between ECG markers and cardiovascular magnetic resonance infarct size. Methods and Results: Patients with prior MI enrolled in the DETERMINE (Defibrillators to Reduce Risk by Magnetic Resonance Imaging Evaluation) and PRE-DETERMINE Trial and Registry were included. ECG leads were analyzed for markers of MI: Q waves, fragmented QRS, and T wave inversion. DETERMINE Score=number of leads with [Q waves×2]+[fragmented QRS]+[T wave inversion]. Left ventricular ejection fraction (LVEF) and infarct size as a percentage of left ventricular mass (MI%) were quantified by cardiovascular magnetic resonance. The Modified Selvester Score estimates MI size from 37 ECG criteria. In 551 patients (aged 62.1±10.9 years, 79% men, and LVEF=40.3±11.0%), MI% increased as the number of ECG markers increased (P\u3c0.001). By univariable linear regression, the DETERMINE Score (range 0–26) estimated MI% (R2=0.18, P\u3c0.001) with an accuracy approaching that of LVEF (R2=0.22, P\u3c0.001) and higher than the Modified Selvester Score (R2=0.09, P\u3c0.001). By multivariable linear regression, addition of the DETERMINE Score improved estimation of MI% over LVEF alone (P\u3c0.001) and over Modified Selvester Score alone (P\u3c0.001). Conclusions: In patients with prior MI, a simple ECG score estimates infarct size and improves infarct size estimation over LVEF alone. Because infarct size is a powerful prognostic indicator, the DETERMINE Score holds promise as a simple and inexpensive risk assessment tool

Estimating Myocardial Infarction Size With a Simple Electrocardiographic Marker Score

Background Myocardial infarction ( MI ) size is a key predictor of prognosis in post‐ MI patients. Cardiovascular magnetic resonance ( CMR ) is the gold standard test for MI quantification, but the ECG is less expensive and more widely available. We sought to quantify the relationship between ECG markers and cardiovascular magnetic resonance infarct size. Methods and Results Patients with prior MI enrolled in the DETERMINE (Defibrillators to Reduce Risk by Magnetic Resonance Imaging Evaluation) and PRE‐DETERMINE Trial and Registry were included. ECG leads were analyzed for markers of MI : Q waves, fragmented QRS , and T wave inversion. DETERMINE Score=number of leads with [Q waves×2]+[fragmented QRS ]+[T wave inversion]. Left ventricular ejection fraction ( LVEF ) and infarct size as a percentage of left ventricular mass ( MI %) were quantified by cardiovascular magnetic resonance. The Modified Selvester Score estimates MI size from 37 ECG criteria. In 551 patients (aged 62.1±10.9 years, 79% men, and LVEF =40.3±11.0%), MI % increased as the number of ECG markers increased ( P &lt;0.001). By univariable linear regression, the DETERMINE Score (range 0–26) estimated MI % ( R 2 =0.18, P &lt;0.001) with an accuracy approaching that of LVEF ( R 2 =0.22, P &lt;0.001) and higher than the Modified Selvester Score ( R 2 =0.09, P &lt;0.001). By multivariable linear regression, addition of the DETERMINE Score improved estimation of MI % over LVEF alone ( P &lt;0.001) and over Modified Selvester Score alone ( P &lt;0.001). Conclusions In patients with prior MI , a simple ECG score estimates infarct size and improves infarct size estimation over LVEF alone. Because infarct size is a powerful prognostic indicator, the DETERMINE Score holds promise as a simple and inexpensive risk assessment tool. </jats:sec

Validation of electrocardiographic criteria for identifying left ventricular dysfunction in patients with previous myocardial infarction

Background Eleven criteria correlating electrocardiogram (ECG) findings with reduced left ventricular ejection fraction (LVEF) have been previously published. These have not been compared head‐to‐head in a single study. We studied their value as a screening test to identify patients with reduced LVEF estimated by cardiac magnetic resonance (CMR) imaging. Methods ECGs and CMR from 548 patients (age 61 + 11 years, 79% male) with previous myocardial infarction (MI), from the DETERMINE and PRE‐DETERMINE studies, were analyzed. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each criterion for identifying patients with LVEF ≤ 30% and ≤ 40% were studied. A useful screening test should have high sensitivity and NPV. Results Mean LVEF was 40% (SD = 11%); 264 patients (48.2%) had LVEF ≤ 40%, and 96 patients (17.5%) had LVEF ≤ 30%. Six of 11 criteria were associated with a significant lower LVEF, but had poor sensitivity to identify LVEF ≤ 30% (range 2.1%–55.2%) or LVEF ≤ 40% (1.1%–51.1%); NPVs were good for LVEF ≤ 30% (range 82.8%–85.9%) but not for LVEF ≤ 40% (range 52.1%–60.6%). Goldberger's third criterion (RV4/SV4  124 ms + either Goldberger's third criterion or Goldberger's first criterion (SV1 or SV2 + RV5 or RV6 ≥ 3.5 mV) had high specificity (95.4%–100%) for LVEF ≤ 40%, although seen in only 48 (8.8%) patients; predictive values were similar on subgroup analysis. Conclusions None of the ECG criteria qualified as a good screening test. Three criteria had high specificity for LVEF ≤ 40%, although seen in < 9% of patients. Whether other ECG criteria can better identify LV dysfunction remains to be determined

Resting state alpha-band functional connectivity and recovery after stroke

After cerebral ischemia, disruption and subsequent reorganization of functional connections occur both locally and remote to the lesion. However, the unpredictable timing and extent of sensorimotor recovery reflects a gap in understanding of these underlying neural mechanisms. We aimed to identify plasticity of alpha-band functional neural connections within the perilesional area and the predictive value of functional connectivity with respect to motor recovery of the upper extremity after stroke. Our results show improvements in upper extremity motor recovery in relation to distributed changes in MEG-based alpha band functional connectivity, both in the perilesional area and contralesional cortex. Motor recovery was found to be predicted by increased connectivity at baseline in the ipsilesional somatosensory area, supplementary motor area, and cerebellum, contrasted with reduced connectivity of contralesional motor regions, after controlling for age, stroke onset-time and lesion size. These findings support plasticity within a widely distributed neural network and define brain regions in which the extent of network participation predicts post-stroke recovery potentia