Neuraxial modulation for treatment of VT storm.

In the hyperadrenergic state of VT storm where shocks are psychologically and physiologically traumatizing, suppression of sympathetic outflow from the organ level of the heart up to higher braincenters plays a significant role in reducing the propensity for VT recurrence. The autonomic nervous system continuously receives input from the heart (afferent signaling), integrates them, and sends efferent signals to modify or maintain cardiac function and arrhythmogenesis. Spinal anesthesia with thoracic epidural infusion of bupivicaine and surgical removal of the sympathetic chain including the stellate ganglion has been shown to decrease recurrences of VT. Excess sympathetic outflow with catecholamine release can be modified with catheter-based renal denervation. The insights provided from animal experiments and in patients that are refractory to conventional therapy have significantly improved our working understanding of the heart as an end organ in the autonomic nervous system

Ablation of Post Transplant Atrial Flutter and Pseudo-fibrillation Using Magnetic Navigation via a Superior Approach.

Ablation of cavotricuspid ishtmus flutter and atrial tachycardia in a complex substrate has never been reported using remote navigation via superior approach. Venous access was obtained via right internal jugular for ablation and left subclavian for duodecapolar catheter placement into the coronary sinus. In a posttransplant patient presenting with both regular and irregular tachycardia, both cavotricuspid isthmus flutter in the donor and atrial tachycardia in the recipient was mapped using a two catheter approach. Successful ablation of typical atrial flutter and anastomotic block was achieved. This is the first report of successful ablation of cavotricuspid isthmus flutter and posttransplant atrial tachycardia using magnetic navigation via superior approach. Using only two catheters, this approach is logical and feasible in complex substrates with interrupted inferior venous access

Detecting and monitoring arrhythmia recurrence following catheter ablation of atrial fibrillation.

Atrial fibrillation (AF) is the most common arrhythmia prompting clinical presentation, is associated with significant morbidity and mortality. The incidence and prevalence of this arrhythmia is expected to grow significantly in the coming decades. Of the available pharmacologic and non-pharmacologic treatment options, the fastest growing and most intensely studied is catheter-based ablation therapy for AF. Given the varying success rates for AF ablation, the increasingly complex factors that need to be taken into account when deciding to proceed with ablation, as well as varying definitions of procedural success, accurate detection of arrhythmia recurrence and its burden is of significance. Detecting and monitoring AF recurrence following catheter ablation is therefore an important consideration. Multiple studies have demonstrated the close relationship between the intensity of rhythm monitoring with wearable ambulatory cardiac monitors, or implantable cardiac rhythm monitors and the detection of arrhythmia recurrence. Other studies have employed algorithms dependent on intensive monitoring and arrhythmia detection in the decision tree on whether to proceed with repeat ablation or medical therapy. In this review, we discuss these considerations, types of monitoring devices, and implications for monitoring AF recurrence following catheter ablation

Intensity Scale Sensitometer

None provided

Interactive logical analysis of planning domains

Humans exhibit a significant ability to answer a wide range of questions about previously unencountered planning domains, and leverage this ability to construct “general-purpose\u27\u27 solution plans for the domain. The long term vision of this research is to automate this ability, constructing a system that utilizes reasoning to automatically verify claims about a planning domain. The system would use this ability to automatically construct and verify a generalized plan to solve any planning problem in the domain. The goal of this thesis is to start with baseline results from the interactive verification of claims about planning domains and develop the necessary knowledge representation and reasoning methods to progressively reduce the amount of human interaction required. To achieve this goal, a representation of planning domains in a class-based logic syntax was developed. A novel proof assistant was then used to perform semi-automatic machine analysis of two benchmark planning domains: Blocksworld and Logistics. This analysis was organized around the interactive formal verification of state invariants and specifications of the state-change effects of handwritten recursive program-like generalized plans. The human interaction required for these verifications was metered and qualitatively characterized. This characterization motivated several algorithmic changes to the proof assistant resulting in significant savings in the interactions required. A strict limit was enforced on the time spent by the base reasoner in response to user queries; interactions taking longer were studied to direct improvements to the inference engine\u27s efficiency. A complete account of these changes is provided

Anesthetizing the Fibrillating Heart.

See Article Lee et al

Facts and Fabrications about Ebola: A Twitter Based Study

Microblogging websites like Twitter have been shown to be immensely useful for spreading information on a global scale within seconds. The detrimental effect, however, of such platforms is that misinformation and rumors are also as likely to spread on the network as credible, verified information. From a public health standpoint, the spread of misinformation creates unnecessary panic for the public. We recently witnessed several such scenarios during the outbreak of Ebola in 2014 [14, 1]. In order to effectively counter the medical misinformation in a timely manner, our goal here is to study the nature of such misinformation and rumors in the United States during fall 2014 when a handful of Ebola cases were confirmed in North America. It is a well known convention on Twitter to use hashtags to give context to a Twitter message (a tweet). In this study, we collected approximately 47M tweets from the Twitter streaming API related to Ebola. Based on hashtags, we propose a method to classify the tweets into two sets: credible and speculative. We analyze these two sets and study how they differ in terms of a number of features extracted from the Twitter API. In conclusion, we infer several interesting differences between the two sets. We outline further potential directions to using this material for monitoring and separating speculative tweets from credible ones, to enable improved public health information.Comment: Appears in SIGKDD BigCHat Workshop 201

On the emergence of the Λ{\bf\Lambda}CDM model from self-interacting Brans-Dicke theory in d=5{\bf d= 5}

We investigate whether a self-interacting Brans-Dicke theory in $d=5$ without matter and with a time-dependent metric can describe, after dimensional reduction to $d=4$, the FLRW model with accelerated expansion and non-relativistic matter. By rewriting the effective 4-dimensional theory as an autonomous three-dimensional dynamical system and studying its critical points, we show that the $\Lambda$CDM cosmology cannot emerge from such a model. This result suggests that a richer structure in $d=5$ may be needed to obtain the accelerated expansion as well as the matter content of the 4-dimensional universe.Comment: 7 pages, 7 figure