New System for Digital to Analog Transformation and Reconstruction of 12-Lead ECGs

Introduction

We describe initial validation of a new system for digital to analog conversion (DAC) and reconstruction of 12-lead ECGs. The system utilizes an open and optimized software format with a commensurately optimized DAC hardware configuration to accurately reproduce, from digital files, the original analog electrocardiographic signals of previously instrumented patients. By doing so, the system also ultimately allows for transmission of data collected on one manufacturer''s 12-lead ECG hardware/software into that of any other.

Materials and Methods

To initially validate the system, we compared original and post-DAC re-digitized 12-lead ECG data files (∼5-minutes long) in two types of validation studies in 10 patients. The first type quantitatively compared the total waveform voltage differences between the original and re-digitized data while the second type qualitatively compared the automated electrocardiographic diagnostic statements generated by the original versus re-digitized data.

Results

The grand-averaged difference in root mean squared voltage between the original and re-digitized data was 20.8 µV per channel when re-digitization involved the same manufacturer''s analog to digital converter (ADC) as the original digitization, and 28.4 µV per channel when it involved a different manufacturer''s ADC. Automated diagnostic statements generated by the original versus reconstructed data did not differ when using the diagnostic algorithm from the same manufacturer on whose device the original data were collected, and differed only slightly for just 1 of 10 patients when using a third-party diagnostic algorithm throughout.

Conclusion

Original analog 12-lead ECG signals can be reconstructed from digital data files with accuracy sufficient for clinical use. Such reconstructions can readily enable automated second opinions for difficult-to-interpret 12-lead ECGs, either locally or remotely through the use of dedicated or cloud-based servers.     

A novel tetravalent bispecific TandAb (CD30/CD16A) efficiently recruits NK cells for the lysis of CD30+ tumor cells

To improve recruitment and activation of natural killer (NK) cells to lyse tumor cells, we isolated a human anti-CD16A antibody with similar affinity for the CD16A 158F/V allotypes, but no binding to the CD16B isoform. Using CD16A-targeting Fv domains, we constructed a tetravalent bispecific CD30/CD16A tandem diabody (TandAb®) consisting solely of Fv domains. This TandAb has two binding sites for CD16A and two for CD30, the antigen identifying Hodgkin lymphoma cells. The binding and cytotoxicity of the TandAb were compared with antibodies with identical anti-CD30 domains: (1) a native IgG, (2) an IgG optimized for binding to Fc receptors, and (3) a bivalent bispecific CD30/CD16A diabody. Due to its CD16A-bivalency and reduced k_off, the TandAb was retained longer on the surface of NK cells than the IgGs or the diabody. This contributed to the higher potency and efficacy of the TandAb relative to those of the other anti-CD30 antibodies. TandAb cytotoxicity was independent of the CD16A allotype, whereas the anti-CD30 IgGs were substantially less cytotoxic when NK cells with low affinity CD16A allotype were employed. TandAb activation of NK cells was strictly dependent on the presence of CD30⁺ target cells. Therefore, the CD30/CD16A TandAb may represent a promising therapeutic for the treatment of Hodgkin’s lymphoma; further, anti-CD16A TandAbs may function as potent immunotherapeutics that specifically recruit NK cells to destroy cancer cells.     

Responses of woody vegetation to exclusion of large herbivores in semi‐arid savannas

The Nkuhlu large‐scale long‐term exclusion experiment in Kruger National Park was designed to study the long‐term effects of large herbivores on vegetation. One treatment excludes elephants, another excludes all herbivores larger than hares and another one comprises an open, control area. Vegetation monitoring was implemented in 2002 when a baseline survey was conducted prior to exclusion. Monitoring was repeated 5 years after exclusion. Data from the surveys were analysed to establish how structure and composition of woody vegetation had changed 5 years after herbivore exclusion. The analysis showed that neither plant assemblage nor mean vegetation height had changed significantly since exclusion. However, both species richness and density of woody plants increased 5 years after exclusion of all large herbivores, but not after the exclusion of elephants alone. One already common species, Dichrostachys cinerea, became more common after excluding all large herbivores compared with either no exclusion or elephant exclusion, possibly leading to competitive suppression of other species. Species other than D. cinerea tended to either increase or decrease in density, but the changes were insufficient to induce significant shifts in the overall assemblage of woody plants. The results indicate that after 5 years of exclusion, the combined assemblage of large herbivores, and not elephants alone, could induce changes in species richness and abundances of woody plants, but the effect was so far insufficient to induce measureable shifts in the assemblages of woody plants. It is possible that assemblages will change with time and increasing elephant numbers may amplify future changes.     

An efficient variance component approach implementing an average information REML suitable for combined LD and linkage mapping with a general complex pedigree

Variance component (VC) approaches based on restricted maximum likelihood (REML) have been used as an attractive method for positioning of quantitative trait loci (QTL). Linkage disequilibrium (LD) information can be easily implemented in the covariance structure among QTL effects (e.g. genotype relationship matrix) and mapping resolution appears to be high. Because of the use of LD information, the covariance structure becomes much richer and denser compared to the use of linkage information alone. This makes an average information (AI) REML algorithm based on mixed model equations and sparse matrix techniques less useful. In addition, (near-) singularity problems often occur with high marker densities, which is common in fine-mapping, causing numerical problems in AIREML based on mixed model equations. The present study investigates the direct use of the variance covariance matrix of all observations in AIREML for LD mapping with a general complex pedigree. The method presented is more efficient than the usual approach based on mixed model equations and robust to numerical problems caused by near-singularity due to closely linked markers. It is also feasible to fit multiple QTL simultaneously in the proposed method whereas this would drastically increase computing time when using mixed model equation-based methods.     

Computational investigation of epithelial cell dynamic phenotype in vitro

Background  

When grown in three-dimensional (3D) cultures, epithelial cells typically form cystic organoids that recapitulate cardinal features of in vivo epithelial structures. Characterizing essential cell actions and their roles, which constitute the system's dynamic phenotype, is critical to gaining deeper insight into the cystogenesis phenomena.     

Identification of a selective thieno[2,3-c]pyridine inhibitor of COT kinase and TNF-α production

COT (Tpl2 in mice) is a serine/threonine MAP3 kinase that regulates production of TNF-α and other pro-inflammatory cytokines such as IL-1β via the ERK/MAP kinase pathway. As TNF-α and IL-1β are clinically validated targets for therapeutic intervention in rheumatoid arthritis (RA), blocking COT provides a potential avenue for amelioration of disease. Herein we describe identification of a cellular active selective small molecule inhibitor of COT kinase.