Beyond pulmonary vein isolation for persistent atrial fibrillation: sequential high-resolution mapping to guide ablation

Purpose We aimed to evaluate whether outcomes with ablation in persistent (PsAF) and long-standing persistent (LsPsAF) AF can be improved beyond what can be achieved with pulmonary vein isolation (PVI) alone, using individualized mapping to guide ablation. Methods We studied 20 pts (15 M, 68 ± 11y) with PsAF (14) or LsPsAF (6) referred for first-time AF ablation. Following antral PVI, individualized mapping (IM) was performed using a high-density mapping catheter stably and fully deployed for 30 s at each of 23 ± 9 sites per patient. Activation data were reviewed, and an ablation strategy designed to intersect areas of focal and rotational activity. Mean follow-up was 429 ± 131 days. The study population was compared to a matched contemporary control cohort (CC) of 20 consecutive patients undergoing conventional ablation. Results Despite the IM group having a higher median comorbidities score, 3.5 vs. 2.5 in the CC group, indicating potentially more complex patients and more advanced substrate, cumulative freedom from AF after a single procedure was achieved in 94% of patients in the IM group vs. 75% in the CC group at 1 year and remained the same in both groups at the conclusion of the study (p = 0.02). There was a similar trend in atrial arrhythmia-free survival between both groups (84% vs. 67% at 1 year) that did not reach statistical significance. The procedure duration was longer in the IM group by a median of 31.5 min (p = 0.004). Conclusions Individualized mapping to guide AF ablation appears to achieve significantly greater AF-free survival compared to conventional PVI when applied as a primary ablation treatment. The results of this pilot study need to be confirmed in a larger, randomized trial.

Proteomic Changes of Activated Hepatic Stellate Cells

Hepatic stellate cells (HSC) are the major cellular drivers of liver fibrosis. Upon liver inflammation caused by a broad range of insults including non-alcoholic fatty liver, HSC transform from a quiescent into a proliferating, fibrotic phenotype. Although much is known about the pathophysiology of this process, exact cellular processes which occur in HSC and enable this transformation remain yet to be elucidated. In order to investigate this HSC transformation, we employed a simple, yet reliable model of HSC activation via an increase in growth medium serum concentration (serum activation). For that purpose, immortalized human LX-2 HSC were exposed to either 1% or 10% fetal bovine serum (FBS). Resulting quiescent (1% FBS) and activated (10% FBS) LX-2 cells were then subjected to in-depth mass spectrometry-based proteomics analysis as well as comprehensive phenotyping. Protein network analysis of activated LX-2 cells revealed an increase in the production of ribosomal proteins and proteins related to cell cycle control and migration, resulting in higher proliferation and faster migration phenotypes. Interestingly, we also observed a decrease in the expression of cholesterol and fatty acid biosynthesis proteins in accordance with a concomitant loss of cytosolic lipid droplets during activation. Overall, this work provides an update on HSC activation characteristics using contemporary proteomic and bioinformatic analyses and presents an accessible model for HSC activation. Data are available via ProteomeXchange with identifier PXD029121.

Singers show enhanced performance and neural representation of vocal imitation

Humans have a remarkable capacity to finely control the muscles of the larynx, via distinct patterns of cortical topography and innervation that may underpin our sophisticated vocal capabilities compared with non-human primates. Here, we investigated the behavioural and neural correlates of laryngeal control, and their relationship to vocal expertise, using an imitation task that required adjustments of larynx musculature during speech. Highly trained human singers and non-singer control participants modulated voice pitch and vocal tract length (VTL) to mimic auditory speech targets, while undergoing real-time anatomical scans of the vocal tract and functional scans of brain activity. Multivariate analyses of speech acoustics, larynx movements and brain activation data were used to quantify vocal modulation behaviour and to search for neural representations of the two modulated vocal parameters during the preparation and execution of speech. We found that singers showed more accurate task-relevant modulations of speech pitch and VTL (i.e. larynx height, as measured with vocal tract MRI) during speech imitation; this was accompanied by stronger representation of VTL within a region of the right somatosensory cortex. Our findings suggest a common neural basis for enhanced vocal control in speech and song. This article is part of the theme issue ‘Voice modulation: from origin and mechanism to social impact (Part I)’.

Age-associated changes to neuronal dynamics involve a loss of inhibitory signaling in C. elegans

In the aging brain, many of the alterations underlying cognitive and behavioral decline remain opaque. C. elegans offers a powerful model for aging research, with a simple, well-studied nervous system to further our understanding of the cellular modifications and functional alterations accompanying senescence. We perform multi-neuronal functional imaging across the aged C. elegans nervous system, measuring an age-associated breakdown in system-wide functional organization. At single-cell resolution, we detect shifts in activity dynamics toward higher frequencies, alongside a specific loss of inhibitory signaling occurring early in the aging process. These effects are partially delayed or accelerated by a long-lived or neurodegenerative mutant background, respectively. We further provide evidence that these effects are partially mediated through degradation of GABA signaling, via a pathway involving UNC-2/CaV2α and caspase activation. Data from mammals are consistent with our findings, suggesting a conserved shift in the balance of excitatory/inhibitory signaling with age leading to functional decline.

Singers and non-singers differ in the performance and neural representation of vocal imitation

Humans have a remarkable capacity to finely control the muscles of the larynx, via distinct patterns of cortical topography and innervation that may underpin our sophisticated vocal capabilities compared with non-human primates. Here, we investigated the behavioural and neural correlates of laryngeal control, and their relationship to vocal expertise, using an imitation task that required adjustments of larynx musculature during speech. Highly-trained human singers and non-singer control participants modulated voice pitch and vocal tract length (VTL) to mimic auditory speech targets, while undergoing real-time anatomical scans of the vocal tract and functional scans of brain activity. Multivariate analyses of speech acoustics, larynx movements and brain activation data were used to quantify vocal modulation behaviour, and to search for neural representations of the two modulated vocal parameters during the preparation and execution of speech. We found that singers showed more accurate task-relevant modulations of speech pitch and VTL (i.e. larynx height, as measured with vocal tract MRI) during speech imitation; this was accompanied by stronger representation of VTL within a region of right dorsal somatosensory cortex. Our findings suggest a common neural basis for enhanced vocal control in speech and song.

THIXOTROPIC FLOCCULATION EFFECTS IN CARBON BLACK–REINFORCED RUBBER: KINETICS AND THERMAL ACTIVATION

ABSTRACT A new rheological methodology is used to quantify the kinetics and thermal activation of thixotropic recovery (flocculation) of uncrosslinked carbon black–reinforced emulsion SBR following high shears and over a range of annealing temperatures. A wide range of carbon black types are examined to determine the influence of aggregate morphology and surface area on compound flocculation. Several kinetic parameters are correlated with the carbon black aggregate structure and surface area, the results of which imply a transition in mechanisms controlling modulus recovery between shorter and longer recovery time scales. Thermal activation of flocculation is found to scale to the surface area and to the mean aggregate diameter of the carbon blacks following power law relationships. The thermal activation data for a subset of compounds with different carbon blacks prepared at different loadings collapses onto a single master line by rescaling the data to a parameter that is proportional to the theoretical interparticle force calculated for the idealized situation of two spherical particles in proximity. Three different van der Waals force models are evaluated, and in each case, an effective superposition of the thermal activation data is achieved. This indicates that the attractive force between aggregates plays a key role in the flocculation of carbon black in rubber, and this force can be traced back to the aggregate and primary particle sizes, interaggregate distances, and effective volume fractions. The activation energy for the viscosity of the unfilled, uncrosslinked SBR is similar to analogous values calculated for the thermal activation of flocculation. This coupling of energetics may be the result of creep/flow of rubber out of gaps between aggregates resulting from interaggregate attractive forces and any potential diffusive motion of the aggregates. Bound rubber data appear to contain information relating to aggregate packing, which could be exploited in future work to further explore the mechanism of flocculation.

Estimation of Pre-COVID19 Daily Ridership Patterns From Paper and Electronic Ticket Sales Data With Origin-Destination, Time-Of-Day, and Train-Start Detail on a Commuter Railroad: Quick-Response Big Data Analytics in a World Steeped With Tradition

Our niche method independently estimates hourly commuter rail station-to-station origin-destination (OD) matrix data each day from ticket sales and activation data from four sales channels (paper/mobile tickets, mail order, and onboard sales) by extending well-established transportation modelling methodologies. This algorithm’s features include: (1) handles multi-pack pay-per-ride fare instruments not requiring electronic validation, like ten-trip paper tickets “punched” onboard by railroad conductors; (2) correctly infers directionality for direction-agnostic ticket-types; (3) estimates unlimited ride ticket utilization patterns sufficiently precisely to inform vehicle assignment/scheduling; (4) provides integer outputs without allowing rounding to affect control totals nor introduce artifacts; (5) deals gracefully with cliff-edge changes in demand, like the COVID19 related lockdown; and (6) allocates hourly traffic to each train-start based on passenger choice. Our core idea is that the time of ticket usage is ultimately a function of the time of sale and ticket type, and mutual transformation is made via probability density functions (“patterns”) given sufficient distribution data. We generated pre-COVID daily OD matrices and will eventually extend this work to post-COVID inputs. Results were provided to operations planners using visual and tabular interfaces. These matrices represent data never previously available by any method; prior OD surveys required 100,000 respondents, and even then could neither provide daily nor hourly levels of detail, and could not monitor special event ridership nor specific seasonal travel such as summer Friday afternoons.

Heuristic assessment of choices for risk network control

Data-driven risk networks describe many complex system dynamics arising in fields such as epidemiology and ecology. They lack explicit dynamics and have multiple sources of cost, both of which are beyond the current scope of traditional control theory. We construct the global economy risk network by combining the consensus of experts from the World Economic Forum with risk activation data to define its topology and interactions. Many of these risks, including extreme weather and drastic inflation, pose significant economic costs when active. We introduce a method for converting network interaction data into continuous dynamics to which we apply optimal control. We contribute the first method for constructing and controlling risk network dynamics based on empirically collected data. We simulate applying this method to control the spread of COVID-19 and show that the choice of risks through which the network is controlled has significant influence on both the cost of control and the total cost of keeping network stable. We additionally describe a heuristic for choosing the risks trough which the network is controlled, given a general risk network.

Abstract P666: Covid-19 Geographic Distribution and Stroke Code Activation Within San Diego County

Introduction: In the early months of the COVID-19 pandemic, decreased numbers of stroke code activations were reported nationwide. In San Diego County, a diverse region that borders Mexico with over 4500 square miles and population 3.3 million, trends in COVID-19 cases varied geographically. We saw an overall decrease in stroke cases across our systems and aimed to better understand if high COVID infection rates in subregions affected stroke code activations. Methods: Stroke code activation data from 15 Stroke Receiving Centers were matched with COVID-19 case rates by patient home zip code. Patients arriving via emergency medical services (EMS) or private transportation were included. Patients with home zip codes outside of San Diego County were excluded. Data represented the cumulative rate of stroke codes and COVID-19 cases per 100,000 population per zip code for the period of March 1 through June 30, 2020. Results: We counted 1,927 stroke code activations across 106 zip codes in San Diego County. The average stroke code activation rate was 58.4 per 100,000 (range: 0-310.6) The median stroke code activation rate was 55.95 (IQR=32.1-73.1) per 100,000 population. The median COVID rate per zip code was 244.9 (IQR=177-448.4) per 100,000 population. There were 958 (49.7%) non-stroke diagnoses, 576 (29.9%) AIS, 272 (14.1%) TIA, 104 (5.4%) ICH and 17 (.9%) SAH. We did not identify a correlation between stroke code activation rates and COVID rates across zip codes (r=.17, p=.09, 95% CI(-.02, .35)). Conclusions: Across a large and diverse single-county region, no correlation was found between COVID positivity rate per zip code and stroke code activations. We found no decreases in stroke code activations in areas with high COVID rates.

Abstract P286: The Effects of COVID-19 on the Reasons for Not Calling 911 for Acute Stroke

Objective: Our Stroke Program regularly provides community outreach and stroke education. The stroke team educates on signs and symptoms of stroke, risks factors, and 911 activation. Within a few days of discharge, Neuroscience nurses call stroke patients to ensure patients have obtained their prescription medications, have follow-up appointments, inquire about their satisfaction with our services, and reinforce stroke education. As part of these calls, our team asked why patients/families did not call 911. The purpose of this study was to determine if the COVID-19 crisis influenced the reasons why 911 was not called for possible stroke to better plan for targeted stroke education. Method: Discharge phone survey data from our stroke network was collected from Feb-Jul 2019 and compared to Feb-Jul 2020. Our stroke network includes 1 comprehensive stroke center and 2 primary stroke centers. Emergency Department (ED) stroke activation data was gathered for the same time periods. Discharge phone calls data was based on discharge date, whereas ED stroke alert data was based on admission date. Results: There was a notable decline in stroke volume between 2019 to 2020 with the largest decline occurring during the first peak (Apr 2020) in COVID-19 cases within our state. This decline was driven by a 16% decline in walk-in ED stroke arrivals as compared to a 1% decline in EMS stroke arrivals. Of those who did not call 911 in 2020, there was a 7% increase in failing to recognize stroke symptoms as an emergency, a 6% increase in concern about EMS cost, and 6% decrease in hospital preference. Conclusion: The COVID-19 crisis negatively influenced stroke volumes within our system stroke program. Reductions in stroke walk-ins accounted for this decline. COVID-19 affected the reasons why 911 was not called. The largest increase was in not recognizing stroke symptoms as an emergency and increased concern about EMS associated costs. Surprisingly, COVID-19 was not listed as a reasons for avoiding 911. Targeted community educational efforts on these concerns may lead to improved 911 usage for suspected stroke during the COVID-19 pandemic. Limitations: Further research is needed to investigate why those with a stroke who would have been walk-ins decided not to seek urgent medical attention.