Dataset Information

A Matched-Filter-Based Algorithm for Subcellular Classification of T-System in Cardiac Tissues.

ABSTRACT: In mammalian ventricular cardiomyocytes, invaginations of the surface membrane form the transverse tubular system (T-system), which consists of transverse tubules (TTs) that align with sarcomeres and Z-lines as well as longitudinal tubules (LTs) that are present between Z-lines in some species. In many cardiac disease etiologies, the T-system is perturbed, which is believed to promote spatially heterogeneous, dyssynchronous Ca²⁺ release and inefficient contraction. In general, T-system characterization approaches have been directed primarily at isolated cells and do not detect subcellular T-system heterogeneity. Here, we present MatchedMyo, a matched-filter-based algorithm for subcellular T-system characterization in isolated cardiomyocytes and millimeter-scale myocardial sections. The algorithm utilizes "filters" representative of TTs, LTs, and T-system absence. Application of the algorithm to cardiomyocytes isolated from rat disease models of myocardial infarction (MI), dilated cardiomyopathy induced via aortic banding, and sham surgery confirmed and quantified heterogeneous T-system structure and remodeling. Cardiomyocytes from post-MI hearts exhibited increasing T-system disarray as proximity to the infarct increased. We found significant (p < 0.05, Welch's t-test) increases in LT density within cardiomyocytes proximal to the infarct (12 ± 3%, data reported as mean ± SD, n = 3) versus sham (4 ± 2%, n = 5), but not distal to the infarct (7 ± 1%, n = 3). The algorithm also detected decreases in TTs within 5° of the myocyte minor axis for isolated aortic banding (36 ± 9%, n = 3) and MI cardiomyocytes located intermediate (37 ± 4%, n = 3) and proximal (34 ± 4%, n = 3) to the infarct versus sham (57 ± 12%, n = 5). Application of bootstrapping to rabbit MI tissue revealed distal sections comprised 18.9 ± 1.0% TTs, whereas proximal sections comprised 10.1 ± 0.8% TTs (p < 0.05), a 46.6% decrease. The matched-filter approach therefore provides a robust and scalable technique for T-system characterization from isolated cells through millimeter-scale myocardial sections.

SUBMITTER: Colli DF

PROVIDER: S-EPMC6486484 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Matched-Filter-Based Algorithm for Subcellular Classification of T-System in Cardiac Tissues.

Colli Dylan F DF Blood S Ryan SR Sankarankutty Aparna C AC Sachse Frank B FB Frisk Michael M Louch William E WE Kekenes-Huskey Peter M PM

Biophysical journal 20190322 8

In mammalian ventricular cardiomyocytes, invaginations of the surface membrane form the transverse tubular system (T-system), which consists of transverse tubules (TTs) that align with sarcomeres and Z-lines as well as longitudinal tubules (LTs) that are present between Z-lines in some species. In many cardiac disease etiologies, the T-system is perturbed, which is believed to promote spatially heterogeneous, dyssynchronous Ca<sup>2+</sup> release and inefficient contraction. In general, T-syste ...[more]

PMID: 30979553

Similar Datasets

Project description:: Pre-harvest fruit yield estimation is useful to guide harvesting and marketing resourcing, but machine vision estimates based on a single view from each side of the tree ("dual-view") underestimates the fruit yield as fruit can be hidden from view. A method is proposed involving deep learning, Kalman filter, and Hungarian algorithm for on-tree mango fruit detection, tracking, and counting from 10 frame-per-second videos captured of trees from a platform moving along the inter row at 5 km/h. The deep learning based mango fruit detection algorithm, MangoYOLO, was used to detect fruit in each frame. The Hungarian algorithm was used to correlate fruit between neighbouring frames, with the improvement of enabling multiple-to-one assignment. The Kalman filter was used to predict the position of fruit in following frames, to avoid multiple counts of a single fruit that is obscured or otherwise not detected with a frame series. A "borrow" concept was added to the Kalman filter to predict fruit position when its precise prediction model was absent, by borrowing the horizontal and vertical speed from neighbouring fruit. By comparison with human count for a video with 110 frames and 192 (human count) fruit, the method produced 9.9% double counts and 7.3% missing count errors, resulting in around 2.6% over count. In another test, a video (of 1162 frames, with 42 images centred on the tree trunk) was acquired of both sides of a row of 21 trees, for which the harvest fruit count was 3286 (i.e., average of 156 fruit/tree). The trees had thick canopies, such that the proportion of fruit hidden from view from any given perspective was high. The proposed method recorded 2050 fruit (62% of harvest) with a bias corrected Root Mean Square Error (RMSE) = 18.0 fruit/tree while the dual-view image method (also using MangoYOLO) recorded 1322 fruit (40%) with a bias corrected RMSE = 21.7 fruit/tree. The video tracking system is recommended over the dual-view imaging system for mango orchard fruit count.

Dataset Information

A Matched-Filter-Based Algorithm for Subcellular Classification of T-System in Cardiac Tissues.

Publications

A Matched-Filter-Based Algorithm for Subcellular Classification of T-System in Cardiac Tissues.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets