Acetylcholine Engages Distinct Amygdala Microcircuits to Gate Internal Theta Rhythm.

Acetylcholine (ACh) is released from basal forebrain cholinergic neurons in response to salient stimuli and engages brain states supporting attention and memory. These high ACh states are associated with theta oscillations, which synchronize neuronal ensembles. Theta oscillations in the basolateral amygdala (BLA) in both humans and rodents have been shown to underlie emotional memory, yet their mechanism remains unclear. Here, using brain slice electrophysiology in male and female mice, we show large ACh stimuli evoke prolonged theta oscillations in BLA local field potentials that depend upon M3 muscarinic receptor activation of cholecystokinin (CCK) interneurons (INs) without the need for external glutamate signaling. Somatostatin (SOM) INs inhibit CCK INs and are themselves inhibited by ACh, providing a functional SOM→CCK IN circuit connection gating BLA theta. Parvalbumin (PV) INs, which can drive BLA oscillations in baseline states, are not involved in the generation of ACh-induced theta, highlighting that ACh induces a cellular switch in the control of BLA oscillatory activity and establishes an internally BLA-driven theta oscillation through CCK INs. Theta activity is more readily evoked in BLA over the cortex or hippocampus, suggesting preferential activation of the BLA during high ACh states. These data reveal a SOM→CCK IN circuit in the BLA that gates internal theta oscillations and suggest a mechanism by which salient stimuli acting through ACh switch the BLA into a network state enabling emotional memory.

Improving localization accuracy for non-invasive automated early left ventricular origin localization approach.

Background: We previously developed a non-invasive approach to localize the site of early left ventricular activation origin in real time using 12-lead ECG, and to project the predicted site onto a generic LV endocardial surface using the smallest angle between two vectors algorithm (SA). Objectives: To improve the localization accuracy of the non-invasive approach by utilizing the K-nearest neighbors algorithm (KNN) to reduce projection errors. Methods: Two datasets were used. Dataset #1 had 1012 LV endocardial pacing sites with known coordinates on the generic LV surface and corresponding ECGs, while dataset #2 included 25 clinically-identified VT exit sites and corresponding ECGs. The non-invasive approach used "population" regression coefficients to predict the target coordinates of a pacing site or VT exit site from the initial 120-m QRS integrals of the pacing site/VT ECG. The predicted site coordinates were then projected onto the generic LV surface using either the KNN or SA projection algorithm. Results: The non-invasive approach using the KNN had a significantly lower mean localization error than the SA in both dataset #1 (9.4 vs. 12.5 mm, p < 0.05) and dataset #2 (7.2 vs. 9.5 mm, p < 0.05). The bootstrap method with 1,000 trials confirmed that using KNN had significantly higher predictive accuracy than using the SA in the bootstrap assessment with the left-out sample (p < 0.05). Conclusion: The KNN significantly reduces the projection error and improves the localization accuracy of the non-invasive approach, which shows promise as a tool to identify the site of origin of ventricular arrhythmia in non-invasive clinical modalities.

Optimization of a 12-Lead Electrocardiography Subset for Automated Early Left Ventricular Activation Localization Approach Based on Pace-Mapping Technology.

BACKGROUND: We previously developed an automated approach based on pace mapping to localise early left ventricular (LV) activation origin. To avoid a singular system, we require pacing from at least 2 more known sites than the number of electrocardiography (ECG) leads used. Fewer leads used means fewer pacing sites required. We sought to identify an optimal minimal ECG lead set for the automated approach. METHODS: We used 1715 LV endocardial pacing sites to create derivation and testing data sets. The derivation data set, consisting of 1012 known pacing sites pooled from 38 patients, was used to identify an optimal 3-lead set by means of random forest regression (RFR), and a second 3-lead set by means of exhaustive search. The performance of these sets and the calculated Frank leads was compared within the testing data set with 703 pacing sites pooled from 25 patients. RESULTS: The RFR yielded III, V1, and V4, whereas the exhaustive search identified leads II, V2 and V6. Comparison of these sets and the calculated Frank leads demonstrated similar performance when using 5 or more known pacing sites. Accuracy improved with additional pacing sites, achieving mean accuracy of < 5 mm, after including up to 9 pacing sites when they were focused on a suspected area of ventricular activation origin (radius < 10 mm). CONCLUSIONS: The RFR identified the quasi-orthogonal leads set to localise the source of LV activation, minimizing the training set of pacing sites. Localization accuracy was high with the use of these leads and was not significantly different from using leads identified by exhaustive search or empiric use of Frank leads.

Differential Regulation of Prelimbic and Thalamic Transmission to the Basolateral Amygdala by Acetylcholine Receptors.

The amygdalar anterior basolateral nucleus (BLa) plays a vital role in emotional behaviors. This region receives dense cholinergic projections from basal forebrain which are critical in regulating neuronal activity in BLa. Cholinergic signaling in BLa has also been shown to modulate afferent glutamatergic inputs to this region. However, these studies, which have used cholinergic agonists or prolonged optogenetic stimulation of cholinergic fibers, may not reflect the effect of physiological acetylcholine release in the BLa. To better understand these effects of acetylcholine, we have used electrophysiology and optogenetics in male and female mouse brain slices to examine cholinergic regulation of afferent BLa input from cortex and midline thalamic nuclei. Phasic ACh release evoked by single pulse stimulation of cholinergic terminals had a biphasic effect on transmission at cortical input, producing rapid nicotinic receptor-mediated facilitation followed by slower mAChR-mediated depression. In contrast, at this same input, sustained ACh elevation through application of the cholinesterase inhibitor physostigmine suppressed glutamatergic transmission through mAChRs only. This suppression was not observed at midline thalamic nuclei inputs to BLa. In agreement with this pathway specificity, the mAChR agonist, muscarine more potently suppressed transmission at inputs from prelimbic cortex than thalamus. Muscarinic inhibition at prelimbic cortex input required presynaptic M4 mAChRs, while at thalamic input it depended on M3 mAChR-mediated stimulation of retrograde endocannabinoid signaling. Muscarinic inhibition at both pathways was frequency-dependent, allowing only high-frequency activity to pass. These findings demonstrate complex cholinergic regulation of afferent input to BLa that is pathway-specific and frequency-dependent.SIGNIFICANCE STATEMENT Cholinergic modulation of the basolateral amygdala regulates formation of emotional memories, but the underlying mechanisms are not well understood. Here, we show, using mouse brain slices, that ACh differentially regulates afferent transmission to the BLa from cortex and midline thalamic nuclei. Fast, phasic ACh release from a single optical stimulation biphasically regulates glutamatergic transmission at cortical inputs through nicotinic and muscarinic receptors, suggesting that cholinergic neuromodulation can serve precise, computational roles in the BLa. In contrast, sustained ACh elevation regulates cortical input through muscarinic receptors only. This muscarinic regulation is pathway-specific with cortical input inhibited more strongly than midline thalamic nuclei input. Specific targeting of these cholinergic receptors may thus provide a therapeutic strategy to bias amygdalar processing and regulate emotional memory.

Assessment of an ECG-Based System for Localizing Ventricular Arrhythmias in Patients With Structural Heart Disease.

Background We have previously developed an intraprocedural automatic arrhythmia-origin localization (AAOL) system to identify idiopathic ventricular arrhythmia origins in real time using a 3-lead ECG. The objective was to assess the localization accuracy of ventricular tachycardia (VT) exit and premature ventricular contraction (PVC) origin sites in patients with structural heart disease using the AAOL system. Methods and Results In retrospective and prospective case series studies, a total of 42 patients who underwent VT/PVC ablation in the setting of structural heart disease were recruited at 2 different centers. The AAOL system combines 120-ms QRS integrals of 3 leads (III, V2, V6) with pace mapping to predict VT exit/PVC origin site and projects that site onto the patient-specific electroanatomic mapping surface. VT exit/PVC origin sites were clinically identified by activation mapping and/or pace mapping. The localization error of the VT exit/PVC origin site was assessed by the distance between the clinically identified site and the estimated site. In the retrospective study of 19 patients with structural heart disease, the AAOL system achieved a mean localization accuracy of 6.5±2.6 mm for 25 induced VTs. In the prospective study with 23 patients, mean localization accuracy was 5.9±2.6 mm for 26 VT exit and PVC origin sites. There was no difference in mean localization error in epicardial sites compared with endocardial sites using the AAOL system (6.0 versus 5.8 mm, P=0.895). Conclusions The AAOL system achieved accurate localization of VT exit/PVC origin sites in patients with structural heart disease; its performance is superior to current systems, and thus, it promises to have potential clinical utility.

Prospective Multicenter Assessment of a New Intraprocedural Automated System for Localizing Idiopathic Ventricular Arrhythmia Origins.

OBJECTIVES: The objective of this study was to present a new system, the Automatic Arrhythmia Origin Localization (AAOL) system, which used incomplete electroanatomic mapping (EAM) for localization of idiopathic ventricular arrhythmia (IVA) origin on the patient-specific geometry of left ventricular, right ventricular, and neighboring vessels. The study assessed the accuracy of the system in localizing IVA source sites on cardiac structures where pace mapping is challenging. BACKGROUND: An intraprocedural automated site of origin localization system was previously developed to identify the origin of early left ventricular activation by using 12-lead electrocardiograms (ECGs). However, it has limitations, as it could not identify the site of origin in the right ventricle and relied on acquiring a complete EAM. METHODS: Twenty patients undergoing IVA catheter ablation had a 12-lead ECG recorded during clinical arrhythmia and during pacing at various locations identified on EAM geometries. The new system combined 3-lead (III, V2, and V6) 120-ms QRS integrals and patient-specific EAM geometry with pace mapping to predict the site of earliest ventricular activation. The predicted site was projected onto EAM geometry. RESULTS: Twenty-three IVA origin sites were clinically identified by activation mapping and/or pace mapping (8, right ventricle; 15, left ventricle, including 8 from the posteromedial papillary muscle, 2 from the aortic root, and 1 from the distal coronary sinus). The new system achieved a mean localization accuracy of 3.6 mm for the 23 mapped IVAs. CONCLUSIONS: The new intraprocedural AAOL system achieved accurate localization of IVA origin in ventricles and neighboring vessels, which could facilitate ablation procedures for patients with IVAs.

Prospective Assessment of an Automated Intraprocedural 12-Lead ECG-Based System for Localization of Early Left Ventricular Activation.

BACKGROUND: To facilitate ablation of ventricular tachycardia (VT), an automated localization system to identify the site of origin of left ventricular activation in real time using the 12-lead ECG was developed. The objective of this study was to prospectively assess its accuracy. METHODS: The automated site of origin localization system consists of 3 steps: (1) localization of ventricular segment based on population templates, (2) population-based localization within a segment, and (3) patient-specific site localization. Localization error was assessed by the distance between the known reference site and the estimated site. RESULTS: In 19 patients undergoing 21 catheter ablation procedures of scar-related VT, site of origin localization accuracy was estimated using 552 left ventricular endocardial pacing sites pooled together and 25 VT-exit sites identified by contact mapping. For the 25 VT-exit sites, localization error of the population-based localization steps was within 10 mm. Patient-specific site localization achieved accuracy of within 3.5 mm after including up to 11 pacing (training) sites. Using 3 remotes (67.8±17.0 mm from the reference VT-exit site), and then 5 close pacing sites, resulted in localization error of 7.2±4.1 mm for the 25 identified VT-exit sites. In 2 emulated clinical procedure with 2 induced VTs, the site of origin localization system achieved accuracy within 4 mm. CONCLUSIONS: In this prospective validation study, the automated localization system achieved estimated accuracy within 10 mm and could thus provide clinical utility.

Automated intraprocedural localization of origin of ventricular activation using patient-specific computed tomographic imaging.

BACKGROUND: To facilitate catheter ablation of ventricular tachycardia (VT), we previously developed an automated method to identify sources of left ventricular (LV) activation in real time using 12-lead electrocardiography (ECG), the accuracy of which depends on acquisition of a complete electroanatomic (EA) map. OBJECTIVE: The purpose of this study was to assess the feasibility of using a registered cardiac computed tomogram (CT) rather than an EA map to permit real-time localization and avoid errors introduced by incomplete maps. METHODS: Before LV VT ablation, 10 patients underwent CT imaging and 3-dimensional reconstruction of the cardiac surface to create a triangle mesh surface, which was registered to the EA map during the procedure and imported into custom localization software. The software uses QRS integrals from leads III, V2, and V6; derives personalized regression coefficients from pacing at ≥5 sites with known locations; and estimates the location of unknown activation sites on the 3-dimensional patient-specific LV endocardial surface. Localization accuracy was quantified for VT exit sites in millimeters by comparing the calculated against the known locations. RESULTS: The VT exit site was identified for 20 VTs using activation and entrainment mapping, supplemented by pace-mapping at the scar margin. The automated localization software achieved incremental accuracy with additional pacing sites and had a mean localization error of 6.9 ± 5.7 mm for the 20 VTs. CONCLUSION: Patient-specific CT geometry is feasible for use in real-time automated localization of ventricular activation and may avoid reliance on a complete EA map.

Localization of Ventricular Activation Origin from the 12-Lead ECG: A Comparison of Linear Regression with Non-Linear Methods of Machine Learning.

We have previously developed an automated localization method based on multiple linear regression (MLR) model to estimate the activation origin on a generic left-ventricular (LV) endocardial surface in real time from the 12-lead ECG. The present study sought to investigate whether machine learning-namely, random-forest regression (RFR) and support-vector regression (SVR)-can improve the localization accuracy compared to MLR. For 38 patients the 12-lead ECG was acquired during LV endocardial pacing at 1012 sites with known coordinates exported from an electroanatomic mapping system; each pacing site was then registered to a generic LV endocardial surface subdivided into 16 segments tessellated into 238 triangles. ECGs were reduced to one variable per lead, consisting of 120-ms time integral of the QRS. To compare three regression models, the entire dataset ([Formula: see text]) was partitioned at random into a design set with 80% and a test set with the remaining 20% of the entire set, and the localization error-measured as geodesic distance on the generic LV surface-was assessed. Bootstrap method with replacement, using 1000 resampling trials, estimated each model's error distribution for the left-out sample ([Formula: see text]). In the design set ([Formula: see text]), the mean accuracy was 8.8, 12.1, and 12.9 mm, respectively for SVR, RVR and MLR. In the test set ([Formula: see text]), the mean value of the localization error in the SVR model was consistently lower than the other two models, both in comparison with the MLR (11.4 vs. 12.5 mm), and with the RFR (11.4 vs. 12.0 mm); the RFR model was also better than the MLR model for estimating localization accuracy (12.0 vs. 12.5 mm). The bootstrap method with 1,000 trials confirmed that the SVR and RFR models had significantly higher predictive accurate than the MLR in the bootstrap assessment with the left-out sample (SVR vs. MLR ([Formula: see text]), RFR vs. MLR ([Formula: see text])). The performance comparison of regression models showed that a modest improvement in localization accuracy can be achieved by SVR and RFR models, in comparison with MLR. The "population" coefficients generated by the optimized SVR model from our dataset are superior to the previously-derived "population" coefficients generated by the MLR model and can supersede them to improve the localization of ventricular activation on the generic LV endocardial surface.

Rapid 12-lead automated localization method: Comparison to electrocardiographic imaging (ECGI) in patient-specific geometry.

BACKGROUND: Rapid accurate localization of the site of ventricular activation origin during catheter ablation for ventricular arrhythmias could facilitate the procedure. Electrocardiographic imaging (ECGI) using large lead sets can localize the origin of ventricular activation. We have developed an automated method to identify sites of early ventricular activation in real time using the 12-lead ECG. We aim to compare the localization accuracy of ECGI and the automated method, identifying pacing sites/VT exit based on a patient-specific model. METHODS: A patient undergoing ablation of VT on the left-ventricular endocardium and epicardium had 120-lead body-surface potential mapping (BSPM) recorded during the procedure. (1) ECGI methodology: The L1-norm regularization was employed to reconstruct epicardial potentials based on patient-specific geometry for localizing endocardial ventricular activation origin. We used the BSPM data corresponding to known endocardial pacing sites and a VT exit site identified by 3D contact mapping to analyze them offline. (2) The automatedmethod: location coordinates of pacing sites together with the time integral of the first 120 ms of the QRS complex of 3 ECG predictors (leads III, V2 and V6) were used to calculate patient-specific regression coefficients to predict the location of unknown sites of ventricular activation origin ("target" sites). Localization error was quantified over all pacing sites in millimeters by comparing the calculated location and the known reference location. RESULTS: Localization was tested for 14 endocardial pacing sites and 1 epicardial VT exit site. For 14 endocardial pacing sites the mean localization error of the automated method was significantly lower than that of the ECGI (8.9 vs. 24.9 mm, p < 0.01), when 10 training pacing sites are used. Emulation of a clinical procedure demonstrated that the automated method achieved localization error of <5 mm for the VT-exit site; while the ECGI approach approximately correlates with the site of VT exit from the scar within a distance of 18.4 mm. CONCLUSIONS: The automated method using only 3 ECGs shows promise to localize the origin of ventricular activation as tested by pacing, and the VT-exit site and compares favourably to inverse solution calculation, avoiding cumbersome lead sets. As 12-lead ECG data is acquired by current 3D mapping systems, it is conceivable that the algorithm could be directly incorporated into a mapping system. Further validation in a prospective cohort study is needed to confirm and extend observations reported in this study.

Criteria for ECG detection of acute myocardial ischemia: Sensitivity versus specificity.

BACKGROUND: Criteria for electrocardiographic detection of acute myocardial ischemia recommended by the Consensus Document of ESC/ACCF/AHA/WHF consist of two parts: The ST elevation myocardial infarction (STEMI) criteria based on ST elevation (ST↑) in 10 pairs of contiguous leads and the other on ST depression (ST↓) in the same 10 contiguous pairs. Our aim was to assess sensitivity (SE) and specificity (SP) of these criteria-and to seek their possible improvements-in three databases of 12­lead ECGs. METHODS: We used (1) STAFF III data of controlled ischemic episodes recorded from 99 patients (pts) during percutaneous coronary intervention (PCI) involving either left anterior descending (LAD) coronary artery, right coronary artery (RCA), or left circumflex (LCx) coronary artery. (2) Data from the University of Glasgow for 58 pts with acute myocardial infarction (AMI) and 58 pts without AMI, as confirmed by MRI. (3) Data from Lund University retrieved from a centralized ECG management system for 100 pts with various pathological ST changes-other than acute coronary occlusion-including ventricular pre-excitation, acute pericarditis, early repolarization syndrome, left ventricular hypertrophy, and left bundle branch block. ST measurements at J-point in ECGs of all 315 pts were obtained automatically on the averaged beat with manual review and the recommended criteria as well as their proposed modifications, were applied. Performance measures included SE, SP, positive predictive value (PPV), and benefit-to-harm ratio (BHR), defined as the ratio of true-positive vs. false-positive detections. RESULTS: We found that the SE of widely-used STEMI criteria can be indeed improved by the additional ST↓ criteria, but at the cost of markedly decreased SP. In contrast, using ST↑ in only 3 additional contiguous pairs of leads (STEMI13) can boost SE without any loss of SP. In the STAFF III database, SE/SP/PPV were 56/98/97% for the STEMI, 79/79/79% for the STEMI with added ST↓ and 67/97/96% for the STEMI13. In the Glasgow database, corresponding SE/SP/PPV were 43/98/96%, 84/90/89%, and 55/98/97%. For the Lund database, SP was 56% for the STEMI, 24% for the STEMI with ST↓, and 56% for the STEMI13. CONCLUSION: Current recommended criteria for detecting acute myocardial ischemia, involving ST↓, boost SE of widely-used STEMI criteria, at the cost of SP. To keep the SP high, we propose either the adjustment of threshold for the added ST↓ criteria or a selective use of ST↓ only in contiguous leads V2 and V3 plus ST↑ in lead pairs (aVL, -III) and (III, -aVL).

Real-Time Localization of Ventricular Tachycardia Origin From the 12-Lead Electrocardiogram.

OBJECTIVES: The aim of this study was to develop rapid computational methods for identifying the site of origin of ventricular activation from the 12-lead electrocardiogram. BACKGROUND: Catheter ablation of ventricular tachycardia in patients with structural heart disease frequently relies on a substrate-based approach, which may use pace mapping guided by body-surface electrocardiography to identify culprit exit sites. METHODS: Patients undergoing ablation of scar-related VT (n = 38) had 12-lead electrocardiograms recorded during pacing at left ventricular endocardial sites (n = 1,012) identified on 3-dimensional electroanatomic maps and registered to a generic left ventricular endocardial surface divided into 16 segments and tessellated into 238 triangles; electrocardiographic data were reduced for each lead to 1 variable, consisting of QRS time integral. Two methods for estimating the origin of activation were developed: 1) a discrete method, estimating segment of activation origin using template matching; and 2) a continuous method, using population-based multiple linear regression to estimate triangle of activation origin. A variant of the latter method was derived, using patient-specific multiple linear regression. RESULTS: The optimal QRS time integral included the first 120 ms of the QRS interval. The mean localization error of population-based regressions was 12 ± 8 mm. Patient-specific regressions can achieve localization accuracy better than 5 mm when at least 10 training-set pacing sites are used; this accuracy further increases with each added pacing site. CONCLUSIONS: Computational intraprocedure methods can automatically identify the segment and site of left ventricular activation using novel algorithms, with accuracy within <10 mm.

Validation of the vessel-specific leads (VSLs) for detection of acute ischemia on a dataset with non-ischemic ST-segment deviation.

BACKGROUND: Existing criteria recommended by ACC/ESC for identifying patients with ST elevation myocardial infarction (STEMI) from the 12-lead ECG perform with high specificity (SP) but low sensitivity (SE). In our previous studies, we found that the SE of acute ischemia detection can be markedly improved without any loss of SP by calculating, from the 12-lead ECG, ST deviation in 3 "optimal" vessel-specific leads (VSLs). To further validate the method, we evaluated the SP performance using a dataset with non-ischemic ST-segment changes. METHODS: 12-lead ECGs of 100 patients (75 males/25 females, age range 12-83years, average age 52years) were retrieved from a centralized ECG management system at Skåne University Hospital, Lund, Sweden. These ECGs were chosen to represent five subgroups with various causes of pathological ST deviation, other than acute coronary occlusion: a) ventricular preexcitation (n=12), b) acute pericarditis (n=26), c) early repolarization syndrome (ERS) (n=14), d) left ventricular hypertrophy (LVH) with "strain" (n=26), and e) left bundle branch block (LBBB) (n=22). ECGs with inadequate signal quality, heart rate exceeding 120bpm and/or atrial flutter were not selected for this study population. Both STEMI criteria and VSLs criteria with and without a new augmented LVH-specific derived lead were tested. SP, calculated for each subgroup and combined, was used as the performance measure for comparison. RESULTS: SP test results for the STEMI criteria vs. the VSLs method without the augmented LVH lead were 100% vs. 92%, 4% vs. 88%, 29% vs. 100%, 100% vs. 77%, and 64% vs. 68% for the five subgroups with preexcitation, pericarditis, ERS, LVH, and LBBB, respectively. For the whole group, SP was 57% for the STEMI criteria and 83% for the VSLs criteria; this improvement was statistically significant (p<0.001). With the augmented LVH lead, SP for the VSLs improved from 77% to 96% for the LVH subgroup and SP for the other subgroups remained unchanged. For the whole study group, SP improved from 83% to 88%. CONCLUSION: Based on these results, we conclude that the VSLs criteria are not only more sensitive in detecting acute ischemia but also more specific in recognizing patients with non-ischemic ST deviation than the existing STEMI criteria. This finding needs to be further corroborated on a larger patient population with AMI prevalence typical of the population presenting to the emergency room.

Validation of improved vessel-specific leads (VSLs) for detecting acute myocardial ischemia.

BACKGROUND: Existing criteria recommended by ACC/ESC for identifying patients with ST elevation myocardial infarction (STEMI) from the 12-lead ECG perform with high specificity (SP), but low sensitivity (SE). In our previous studies, we found that the SE of ischemia detection can be markedly improved without any loss of SP by calculating, from the 12-lead ECG, ST deviation in 3 "optimal" vessel-specific leads (VSLs). Our original VSLs, based on ΔST body-surface potential maps (BSPMs), have been modified by using the more appropriate J-point BSPMs at peak ischemia (without subtraction of pre-occlusion distributions). The aim of the present study was to compare the performance of these new VSLs with that achieved by the STEMI criteria used in current practice. METHODS: Two independent datasets of 12-lead ECGs were used: the STAFF III dataset acquired during ischemic episodes caused by balloon inflation in LAD (n=35), RCA (n=47), and LCx (n=17) coronary arteries, and the Glasgow dataset comprising admission 12-lead ECGs of 116 patients who were hospitalized for chest pain and underwent contrast-enhanced cardiac MRI that confirmed AMI in 58 patients (50%). RESULTS: We found that, in the STAFF III dataset, the detection of ischemic state by the STEMI criteria attained SE/SP of 60/97%, whereas SE/SP values of VSLs were 72/98%. In the Glasgow dataset, STEMI criteria yielded SE/SP of 43/98%, whereas the VSLs improved SE/SP to 60/98%. The most significant increase in diagnostic performance appeared in patients with LCx coronary artery occlusion: in STAFF III data (n=17) SE achieved by STEMI criteria was improved by the VSLs from 35% to 71%; in Glasgow data (n=12) SE of 31% achieved by STEMI criteria was improved by the VSLs to 69%. CONCLUSION: In our study population, existing ACC/ESC STEMI criteria complemented by the new VSLs yielded much improved sensitivity of ischemia detection without any detrimental effect on specificity. This finding needs to be corroborated on a larger chest-pain patient population with typical prevalence of acute ischemia presented to the emergency rooms.

SB-205384 is a positive allosteric modulator of recombinant GABAA receptors containing rat α3, α5, or α6 subunit subtypes coexpressed with ß3 and γ2 subunits.

Many drugs used to treat anxiety are positive modulators of GABAA receptors, which mediate fast inhibitory neurotransmission. The GABAA receptors can be assembled from a combination of at least 16 different subunits. The receptor's subunit composition determines its pharmacologic and functional properties, and subunit expression varies throughout the brain. A primary goal for new treatments targeting GABAA receptors is the production of subunit-selective modulators acting upon a discrete population of receptors. The anxiolytic 4-amino-7-hydroxy-2-methyl-5,6,7,8,-tetrahydrobenzo[b]thieno[2,3-b]pyridine-3-carboxylic acid, but-2-ynyl ester (SB-205384) is widely considered to be selective for α3-containing GABAA receptors. However, it has been tested only on α1-, α2-, and α3-containing receptors. We examined the activity of SB-205384 at recombinant receptors containing the six different α subunits and found that receptors containing the α3, α5, and α6 subunits were potentiated by SB-205384, with the α6 subunit conferring the greatest responsiveness. Properties associated with chimeric α1/α6 subunits suggested that multiple structural domains influence sensitivity to SB-205384. Point mutations of residues within the extracellular N-terminal domain identified a leucine residue located in loop E of the agonist binding site as an important determinant of high sensitivity to modulation. In the α6 subunit the identity of this residue is species-dependent, with the leucine found in rat subunits but not in human. Our results indicate that SB-205384 is not an α3-selective modulator, and instead acts at several GABAA receptor isoforms. These findings have implications for the side-effect profile of this anxiolytic as well as for its use in neuronal and animal studies as a marker for contribution from α3-containing receptors.

Discrimination of ST deviation caused by acute coronary occlusion from normal variants and other abnormal conditions, using computed electrocardiographic imaging based on 12-lead ECG.

BACKGROUND: Many graphical methods for displaying ST-segment deviation in the ECG have been tried for enhancing decision-making in patients with suspected acute coronary syndromes. Computed electrocardiographic imaging (CEI), based on a mathematical inverse solution, has been recently applied to transform ST-J point measurements made in conventional 12-lead ECG into a display of epicardial potentials in bull's-eye format. The purpose of this study is to assess utility of CEI in the clinical setting. METHODS: In 99 patients with stable coronary disease, 12-lead ECGs were recorded during elective percutaneous coronary intervention (PCI), first before balloon-catheter insertion and then when an intracoronary balloon blocked blood supply to a region of myocardium for more than 4minutes (typically 5minutes). Four groups of patients were additionally studied, namely those with preexcitation, pericarditis, early repolarization syndrome (ERS), and left ventricular hypertrophy (LVH) with strain. Comparisons between performances of published criteria for ST-elevation myocardial infarction (STEMI) and quantitative as well as visual assessment of CEI images were based on sensitivities and specificities. RESULTS: Visual assessment of CEI outperformed STEMI criteria. This was especially evident for the capability of detecting LCx occlusion with sensitivities for STEMI criteria=35% and for visual assessment of CEI by 2 physicians=71%, i. e. twice as many patients were correctly identified by CEI. False positive rates for CEI were low in patients with LVH with strain as well as with preexcitation for both methods. For pericarditis and ERS, visual as well as quantitative assessment of CEI performed better than STEMI criteria. CONCLUSION: Visual assessment of CEI is a promising method for increasing the accuracy of ECG-based triage to PCI or conservative care.

Comparison of epicardial potential maps derived from the 12-lead electrocardiograms with scintigraphic images during controlled myocardial ischemia.

Our aim was to cross-validate electrocardiographic (ECG) and scintigraphic imaging of acute myocardial ischemia. The former method was based on inverse calculation of heart-surface potentials from the body-surface ECGs, and the latter, on a single photon emission computed tomography (SPECT). A boundary-element torso model with 352 body-surface and 202 heart-surface nodes was used to perform the ECG inverse solution. Potentials at 352 body-surface nodes were calculated from those acquired at 12-lead ECG measurement sites using regression coefficients developed from a design set (n = 892) of body-surface potential mapping (BSPM) data. The test set (n = 18) consisted of BSPM data from patients who underwent a balloon-inflation angioplasty of either the left anterior descending coronary artery (LAD) (n = 7), left circumflex coronary artery (LCx) (n = 2), or the right coronary artery (RCA) (n = 9). Body-surface potential mapping distributions at J point for 352 nodes were estimated from the 12-lead ECG, and an agreement with those estimated from 120 leads was assessed by a correlation coefficient (CC) (in percent). These estimates yielded very similar BSPM distributions, with a CC of 91.0% ± 8.1% (mean ± SD) for the entire test set and 94.1% ± 1.4%, 96.7% ± 0.8%, and 87.4% ± 10.3% for LAD, LCx, and RCA subgroups, respectively. Corresponding heart-surface potential distributions obtained by inverse solution correlated with a lower CC of 69.3% ± 18.0% overall and 73.7% ± 10.8%, 84.7% ± 1.1%, and 62.6% ± 21.8%, respectively, for subgroups. Bull's-eye displays of heart-surface potentials calculated from estimated BSPM distributions had an area of positive potentials that qualitatively corresponded, in general, with the underperfused territory suggested by SPECT images. For the LAD and LCx groups, all 9 ECG-derived bull's-eye images indicated the expected territory; for the RCA group, 6 of 9 ECG-derived images were as expected; 2 of 3 misclassified cases had very small ECG changes in response to coronary-artery occlusion, and their SPECT images showed indiscernible patterns. In conclusion, our findings demonstrate that noninvasive ECG imaging based on just the 12-lead ECG might provide useful estimates of the regions of myocardial ischemia that agree with those provided by scintigraphic techniques.

Human pregnancy specific beta-1-glycoprotein 1 (PSG1) has a potential role in placental vascular morphogenesis.

Previous studies suggest that human pregnancy specific beta-1-glycoproteins (PSGs) play immunomodulatory roles during pregnancy; however, other possible functions of PSGs have yet to be explored. We have observed that PSGs induce transforming growth factor beta 1 (TGFB1), which among its other diverse functions inhibits T-cell function and has proangiogenic properties. The present study investigates a potential role for PSG1, the most abundant PSG in maternal serum, as a possible inducer of proangiogenic growth factors known to play an important role in establishment of the vasculature at the maternal-fetal interface. To this end, we measured TGFB1, vascular endothelial growth factors (VEGFs) A and C, and placental growth factor (PGF) protein levels in several cell types after PSG1 treatment. In addition, tube formation and wound healing assays were performed to investigate a possible direct interaction between PSG1 and endothelial cells. PSG1 induced up-regulation of both TGFB1 and VEGFA in human monocytes, macrophages, and two human extravillous trophoblast cell lines. We did not observe induction of VEGFC or PGF by PSG1 in any of the cells tested. PSG1 treatment resulted in endothelial tube formation in the presence and absence of VEGFA. Site-directed mutagenesis was performed to map the essential regions within the N-domain of PSG1 required for functional activity. We found that the aspartic acid at position 95, previously believed to be required for binding of PSGs to cells, is not required for PSG1 activity but that the amino acids implicated in the formation of a salt bridge within the N-domain are essential for PSG1 function.

Detection of myocardial ischemia by vessel-specific leads derived from the 12-lead electrocardiogram and its subsets.

Currently used electrocardiographic criteria for identifying patients with ST-elevation myocardial infarction (STEMI) perform with high specificity but low sensitivity. Our aim was to enhance ischemia-detection ability of conventional STEMI criteria based on 12-lead electrocardiogram (ECG) by adding new criteria using 3 vessel-specific leads (VSLs) derived from 12-lead ECG. Study data consisted of 12-lead ECGs acquired during 99 ischemic episodes caused by balloon inflation in, respectively, left anterior descending coronary artery (LAD; n = 35), right coronary artery (RCA; n = 47), and left circumflex coronary artery (LCx; n = 17). ST deviation was measured at J point in 12 standard leads, and for 3 VSLs, its value was derived from 12-lead ECG by using 8 independent predictor leads or just a pair of precordial leads combined with a pair of limb leads. Mean values of sensitivity (SE) and specificity (SP) of ischemia detection achieved with conventional STEMI vs VSL criteria were then obtained from bootstrap trials. We found that the detection of ischemic state by conventional criteria achieved the mean SE/SP of 60%/96% in the total set of ischemic episodes, 74%/97% in the LAD subgroup, 60%/94% in the RCA subgroup, and 36%/100% in the LCx subgroup. In comparison, the mean SE/SP values of VSLs derived from 8 independent leads of 12-lead ECG were, at 125-microV threshold, 76%(*)/96% in the total set, 91%(*)/97% in the LAD subgroup, 70%/94% in the RCA subgroup, and 71%(*)/100% in the LCx subgroup (with asterisk denoting a statistically significant increase). The mean SE/SP of VSLs derived from some of the 4-predictor lead sets (namely, those including lead V(3)) matched or exceeded values achieved by VSLs derived from 8 predictors; for instance, with predictor leads I, II, V(3), V(6) derived VSLs attained at 125-microV threshold the mean SE/SP of 80%(*)/95% in the total set, 91%(*)/97% in the LAD subgroup, 74%/92% in the RCA subgroup, and 71%(*)/100% in the LCx subgroup. Based on these results, we conclude that, in our data set, 3 VSLs derived from the complete standard 12-lead ECG-and even from its subsets-can identify acute ischemia better than existing STEMI criteria.

On designing and testing transformations for derivation of standard 12-lead/18-lead electrocardiograms and vectorcardiograms from reduced sets of predictor leads.

The aim of this study was to develop and evaluate transformation coefficients for deriving the standard 12-lead electrocardiogram (ECG), 18-lead ECG (with additional leads V7, V8, V9, V3R, V4R, V5R), and Frank vectorcardiogram (VCG) from reduced lead sets using 3 "limb" electrodes at Mason-Likar torso sites combined with 2 chest electrodes at precordial sites V1 to V6; 15 such lead sets exist and each can be recorded with 6-wire cable. As a study population, we used Dalhousie Superset (n = 892) that includes healthy subjects, postinfarction patients, and patients with a history of ventricular tachycardia. For each subject, 120-lead ECG recordings of 15-second duration were averaged, and all samples of the QRST complex for leads of interest were extracted; these data were used to derive--by regression analysis--general and patient-specific coefficients for lead transformations. These coefficients were then used to predict 12-lead/18-lead ECG sets and 3-lead VCG from 15 reduced lead sets, and the success of these predictions was assessed by 3 goodness-of-fit measures applied to the entire QRST waveform and to the ST deviation at J point; these 3 measures were similarity coefficient (SC in percentage), relative error (in percentage), and RMS error (in microvolts). Our results show that the best pair for predicting the standard 12-lead ECG by either general coefficients (mean SC = 95.56) or patient-specific coefficients (mean SC = 99.11) is V2 and V4; the best pair for deriving the 18-lead set by general coefficients (mean SC = 93.74) or by patient-specific coefficients (mean SC = 98.71) is V1 and V4; the best pair for deriving the Frank X, Y, Z leads is V1 and V3 for general coefficients (mean SC = 95.76) and V3 and V6 for patient-specific coefficients (mean SC = 99.05). The differences in mean SC among the first 8 to 10 predictor sets in each ranking table are within 1% of the highest SC value. Thus, in conclusion, there are several near-equivalent choices of reduced lead set using 6-wire cable that offer a good prediction of 12-lead/18-lead ECG and VCG; a pair most appropriate for the clinical application can be selected.