Approach to the Diagnosis and Management of Complex Fascicular Ventricular Tachycardias.

Complex ventricular tachycardias involving the fascicular system (fascicular ventricular tachycardias [FVTs]) can be challenging. In this review, we describe our approach to the diagnosis and ablation of these arrhythmias with 10 illustrative cases that involve (1) differentiation from supraventricular tachycardia; (2) assessment for atypical bundle branch reentry and other interfascicular FVTs; (3) examination of P1/P2 activation sequences in sinus rhythm, pacing, and tachycardia; and (4) entrainment techniques to establish the tachycardia mechanism and aid circuit localization. To summarize, 5 cases had prior ablation with 2 previously misdiagnosed as supraventricular tachycardia.

The Value of Programmed Ventricular Extrastimuli From the Right Ventricular Basal Septum During Supraventricular Tachycardia.

Background: The difference between the right ventricular (RV) apical stimulus-atrial electrogram (SA) interval during resetting of supraventricular tachycardia (SVT) versus the ventriculoatrial (VA) interval during SVT (ΔSA-VA) is an established technique for discerning SVT mechanisms but is limited by a significant diagnostic overlap.

Objectives: This study hypothesized that the difference between the RV SA interval during resetting of SVTs versus the VA interval during SVTs (ΔSA-VA) would yield a more robust differentiation of atrioventricular nodal re-entrant tachycardia (AVNRT) from atrioventricular reciprocating tachycardia (AVRT) when using the RV basal septal stimulation (ΔSA-VA) as compared to the RV apical stimulation (ΔSA-VA). Moreover, it was predicted that the ΔSA-VA might distinguish septal from free wall accessory pathways (APs) effectively.

Electrophysiologic and imaging evidence for an occult myopathic substrate in patients with idiopathic ventricular arrhythmias.

Background: Idiopathic VA are traditionally considered benign, although occasional patients develop an ectopy-mediated cardiomyopathy (EMC). It is unclear whether patients with idiopathic VA in the absence of left ventricular (LV) dysfunction harbor a subclinical cardiomyopathy. We aim to assess for cardiomyopathic substrate in patients with idiopathic ventricular arrhythmias (VA) using imaging and electrophysiologic markers of early fibrosis.

Electrophysiologic approach to diagnosis and ablation of patients with permanent junctional reciprocating tachycardia associated with complex anatomy and/or physiology.

Introduction: Permanent junctional reciprocating tachycardia (PJRT) is a rare supraventricular tachycardia (SVT), typically involving a single decremental posteroseptal accessory pathway (AP).

Methods: Four patients with long RP SVT underwent electrophysiology (EP) study and ablation. The cases were reviewed.

Right Ventricular Electrogram Characteristics in a T1 Mapping-Validated Normal Population: Implications for Unipolar Voltage Mapping.

Objectives: The aim of this study was to define normal ventricular electrographic characteristics in T1 mapping-validated normal patients using a contemporary contact force catheter.

Background: Reference values for human endocardial ventricular electrographic characteristics have not been defined using contemporary mapping equipment in patients without heart disease or ventricular arrhythmias.

Methods: Fourteen patients undergoing SVT ablation underwent mapping of the right ventricle and cardiac magnetic resonance imaging with T1 mapping.

Leadless Permanent Pacing: A Single Centre Australian Experience.

Background: To describe the performance and clinical outcomes of consecutive patients having a leadless pacemaker (LP) implanted at a single institution.

Methods: Clinical data and device parameters were prospectively collected on all patients undergoing LP implantation from November 2015 to April 2018.

Results: A total of 79 patients (52 male), median age of 78 years, was included.

Development of Positron Emission Tomography Radiotracers for the GABA Transporter 1.

In vivo positron emission tomography (PET) imaging of the γ-aminobutyric acid (GABA) receptor complex has been accomplished using radiolabeled benzodiazepine derivatives, but development of specific presynaptic radioligands targeting the neuronal membrane GABA transporter type 1 (GAT-1) has been less successful. The availability of new structure-activity studies of GAT-1 inhibitors and the introduction of a GAT-1 inhibitor (tiagabine, Gabatril) into clinical use prompted us to reinvestigate the syntheses of PET ligands for this transporter. Initial synthesis and rodent PET studies of N-[C]methylnipecotic acid confirmed the low brain uptake of that small and polar molecule.

Toward Good Read-Across Practice (GRAP) guidance.

Grouping of substances and utilizing read-across of data within those groups represents an important data gap filling technique for chemical safety assessments. Categories/analogue groups are typically developed based on structural similarity and, increasingly often, also on mechanistic (biological) similarity. While read-across can play a key role in complying with legislations such as the European REACH regulation, the lack of consensus regarding the extent and type of evidence necessary to support it often hampers its successful application and acceptance by regulatory authorities.

Using beta binomials to estimate classification uncertainty for ensemble models.

Background: Quantitative structure-activity (QSAR) models have enormous potential for reducing drug discovery and development costs as well as the need for animal testing. Great strides have been made in estimating their overall reliability, but to fully realize that potential, researchers and regulators need to know how confident they can be in individual predictions.

Results: Submodels in an ensemble model which have been trained on different subsets of a shared training pool represent multiple samples of the model space, and the degree of agreement among them contains information on the reliability of ensemble predictions.

Predicting pKa.

One of the most important physicochemical properties of small molecules and macromolecules are the dissociation constants for any weakly acidic or basic groups, generally expressed as the pK(a) of each group. This is a major factor in the pharmacokinetics of drugs and in the interactions of proteins with other molecules. For both the protein and small molecule cases, we survey the sources of experimental pK(a) values and then focus on current methods for predicting them.

pKa prediction of monoprotic small molecules the SMARTS way.

Realizing favorable absorption, distribution, metabolism, elimination, and toxicity profiles is a necessity due to the high attrition rate of lead compounds in drug development today. The ability to accurately predict bioavailability can help save time and money during the screening and optimization processes. As several robust programs already exist for predicting logP, we have turned our attention to the fast and robust prediction of pK(a) for small molecules.

Data mining the NCI60 to predict generalized cytotoxicity.

Elimination of cytotoxic compounds in the early and later stages of drug discovery can help reduce the costs of research and development. Through the application of principal components analysis (PCA), we were able to data mine and prove that approximately 89% of the total log GI 50 variance is due to the nonspecific cytotoxic nature of substances. Furthermore, PCA led to the identification of groups of structurally unrelated substances showing very specific toxicity profiles, such as a set of 45 substances toxic only to the Leukemia_SR cancer cell line.

Chemical data mining of the NCI human tumor cell line database.

The NCI Developmental Therapeutics Program Human Tumor cell line data set is a publicly available database that contains cellular assay screening data for over 40 000 compounds tested in 60 human tumor cell lines. The database also contains microarray assay gene expression data for the cell lines, and so it provides an excellent information resource particularly for testing data mining methods that bridge chemical, biological, and genomic information. In this paper we describe a formal knowledge discovery approach to characterizing and data mining this set and report the results of some of our initial experiments in mining the set from a chemoinformatics perspective.