Contact force sensing in ablation of ventricular arrhythmias using a 56-hole open-irrigation catheter: a propensity-matched analysis.

PURPOSE: The effect of adding contact force (CF) sensing to 56-hole tip irrigation in ventricular arrhythmia (VA) ablation has not been previously studied. We aimed to compare outcomes with and without CF sensing in VA ablation using a 56-hole radiofrequency (RF) catheter. METHODS: A total of 164 patients who underwent first-time VA ablation using Thermocool SmartTouch Surround Flow (TC-STSF) catheter (Biosense-Webster, Diamond Bar, CA, USA) were propensity-matched in a 1:1 fashion to 164 patients who had first-time ablation using Thermocool Surround Flow (TC-SF) catheter. Patients were matched for age, gender, cardiac aetiology, ejection fraction and approach. Acute success, complications and long-term follow-up were compared. RESULTS: There was no difference between procedures utilising either TC-SF or TC-STSF in acute success (TC-SF: 134/164 (82%), TC-STSF: 141/164 (86%), p = 0.3), complications (TC-SF: 11/164 (6.7%), TC-STSF: 11/164 (6.7%), p = 1.0) or VA-free survival (TC-SF: mean arrhythmia-free survival time = 5.9 years, 95% CI = 5.4-6.4, TC-STSF: mean = 3.2 years, 95% CI = 3-3.5, log-rank p = 0.74). Fluoroscopy time was longer in normal hearts with TC-SF (19 min, IQR: 14-30) than TC-STSF (14 min, IQR: 8-25; p = 0.04). CONCLUSION: Both TC-SF and TC-STSF catheters are safe and effective in treating VAs. The use of CF sensing catheters did not improve safety or acute and long-term outcomes, but reduced fluoroscopy time in normal heart VA

Improved Cellular Specificity of Plasmonic Nanobubbles versus Nanoparticles in Heterogeneous Cell Systems

The limited specificity of nanoparticle (NP) uptake by target cells associated with a disease is one of the principal challenges of nanomedicine. Using the threshold mechanism of plasmonic nanobubble (PNB) generation and enhanced accumulation and clustering of gold nanoparticles in target cells, we increased the specificity of PNB generation and detection in target versus non-target cells by more than one order of magnitude compared to the specificity of NP uptake by the same cells. This improved cellular specificity of PNBs was demonstrated in six different cell models representing diverse molecular targets such as epidermal growth factor receptor, CD3 receptor, prostate specific membrane antigen and mucin molecule MUC1. Thus PNBs may be a universal method and nano-agent that overcome the problem of non-specific uptake of NPs by non-target cells and improve the specificity of NP-based diagnostics, therapeutics and theranostics at the cell level

Developing A Speaker Identification System For The DARPA RATS Project

This paper describes the speaker identification (SID) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state of the art detection capabilities on audio from highly degraded communication channels. We present results using multiple SID systems differing mainly in the algorithm used for voice activity detection (VAD) and feature extraction. We show that (a) unsupervised VAD performs as well supervised methods in terms of downstream SID performance, (b) noise-robust feature extraction methods such as CFCCs out-perform MFCC front-ends on noisy audio, and (c) fusion of multiple systems provides 24% relative improvement in EER compared to the single best system when using a novel SVM-based fusion algorithm that uses side information such as gender, language, and channel i

Developing A Speaker Identification System For The DARPA RATS Project

This paper describes the speaker identification (SID) system developed by the Patrol team for the first phase of the DARPA RATS (Robust Automatic Transcription of Speech) program, which seeks to advance state of the art detection capabilities on audio from highly degraded communication channels. We present results using multiple SID systems differing mainly in the algorithm used for voice activity detection (VAD) and feature extraction. We show that (a) unsupervised VAD performs as well supervised methods in terms of downstream SID performance, (b) noise-robust feature extraction methods such as CFCCs out-perform MFCC front-ends on noisy audio, and (c) fusion of multiple systems provides 24% relative improvement in EER compared to the single best system when using a novel SVM-based fusion algorithm that uses side information such as gender, language, and channel id

Left ventricle unloading strategies in ECMO: A single‐center experience

ECMO is a life-saving technology capable of restoring perfusion but is not without significant complications that limit its realizable therapeutic benefit. ECMO-induced hemodynamics increase cardiac afterload risking left ventricular distention and impaired cardiac recovery. To mitigate potentially harmful effects, multiple strategies to unload the left ventricle (LV) are used in clinical practice but data supporting the optimal approach is presently lacking. We reviewed outcomes of our ECMO population from September 2015 through January 2019 to determine if our LV unloading strategies were associated with patient outcomes. We compared reactive (Group 1, n=30) versus immediate (Group 2, n=33) LV unloading and then compared patients unloaded with an Impella CP (n=19) versus an intra-aortic balloon pump (IABP, n=16), analyzing survival and ECMO-related complications. Survival was similar between Groups 1 and 2 (33 vs 42%, p=0.426) with Group 2 experiencing more clinically-significant hemorrhage (40 vs. 67%, p=0.034). Survival and ECMO-related complications were similar between patients unloaded with an Impella versus an IABP. However, the Impella group exhibited a higher rate of survival (37%) than predicted by their median SAVE score (18%). Our findings correlate with recent large cohort studies and motivate further work to design clinical guidelines and future trial design

THE UMD-JHU 2011 SPEAKER RECOGNITION SYSTEM

In recent years, there have been significant advances in the field of speaker recognition that has resulted in very robust recognition systems. The primary focus of many recent developments have shifted to the problem of recognizing speakers in adverse conditions, e.g in the presence of noise/reverberation. In this paper, we present the UMD-JHU speaker recognition system applied on the NIST 2010 SRE task. The novel aspects of our systems are: 1) Improved performance on trials involving different vocal effort via the use of linearscale features; 2) Expected improved recognition performance in the presence of reverberation and noise via the use of frequency domain perceptual linear predictor and cortical features; 3) A new discriminative kernel partial least squares (KPLS) framework that complements state-of-the-art back-end systems JFA and PLDA to aid in better overall recognition; and 4) Acceleration of JFA, PLDA and KPLS back-ends via distributed computing. The individual components of the system and the fused system are compared against a baseline JFA system and results reported by SRI and MIT-LL on SRE2010

N-myc-interactor mediates microbiome induced epithelial to mesenchymal transition and is associated with chronic lung allograft dysfunction.

BACKGROUND: Recent evidence suggests a role for lung microbiome in occurrence of chronic lung allograft dysfunction (CLAD). However, the mechanisms linking the microbiome to CLAD are poorly delineated. We investigated a possible mechanism involved in microbial modulation of mucosal response leading to CLAD with the hypothesis that a Proteobacteria dominant lung microbiome would inhibit N-myc-interactor (NMI) expression and induce epithelial to mesenchymal transition (EMT). METHODS: Explant CLAD, non-CLAD, and healthy nontransplant lung tissue were collected, as well as bronchoalveolar lavage from 14 CLAD and matched non-CLAD subjects, which were followed by 16S rRNA amplicon sequencing and quantitative polymerase chain reaction (PCR) analysis. Pseudomonas aeruginosa (PsA) or PsA-lipopolysaccharide was cocultured with primary human bronchial epithelial cells (PBEC). Western blot analysis and quantitative reverse transcription (qRT) PCR was performed to evaluate NMI expression and EMT in explants and in PsA-exposed PBECs. These experiments were repeated after siRNA silencing and upregulation (plasmid vector) of EMT regulator NMI. RESULTS: 16S rRNA amplicon analyses revealed that CLAD patients have a higher abundance of phyla Proteobacteria and reduced abundance of the phyla Bacteroidetes. At the genera level, CLAD subjects had an increased abundance of genera Pseudomonas and reduced Prevotella. Human CLAD airway cells showed a downregulation of the N-myc-interactor gene and presence of EMT. Furthermore, exposure of human primary bronchial epithelial cells to PsA resulted in downregulation of NMI and induction of an EMT phenotype while NMI upregulation resulted in attenuation of this PsA-induced EMT response. CONCLUSIONS: CLAD is associated with increased bacterial biomass and a Proteobacteria enriched airway microbiome and EMT. Proteobacteria such as PsA induces EMT in human bronchial epithelial cells via NMI, demonstrating a newly uncovered mechanism by which the microbiome induces cellular metaplasia