Vector angle dyssynchrony differentiates varying levels of exposure to afterload stress.

<p>Dyssynchrony measured as the mean vector angle (for 48 regional curves) for sham, AAC, and de-AAC animals at 7 weeks.</p

Changes in global and regional contractile function in an experimental model of pressure overload.

<p>The schematic of the experimental design is shown (<b>A</b>). Global peak longitudinal strain (endocardial) in the sham and aortic constricted animals at 1 week before randomization (<b>B</b>) and in the AAC and de-AAC animals at 7 weeks (<b>C</b>). Basal peak longitudinal strain (endocardial) in the sham and aortic constricted animals at 1 week (<b>D</b>) and in the AAC and de-AAC animals at 7 weeks (<b>E</b>). Apical peak longitudinal strain changes were similar to global peak longitudinal strain changes observed at 1 and 7 weeks (<b>F</b> and <b>G</b>).</p

Spot Identification and Quality Control in Cell-Based Microarrays

Cell-based microarrays are being increasingly used as a tool for combinatorial and high throughput screening of cellular microenvironments. Analysis of microarrays requires several steps, including microarray imaging, identification of cell spots, quality control, and data exploration. While high content image analysis, cell counting, and cell pattern recognition methods are established, there is a need for new postprocessing and quality control methods for cell-based microarrays used to investigate combinatorial microenvironments. Previously, microarrayed cell spot identification and quality control were performed manually, leading to excessive processing time and potentially resulting in human bias. This work introduces an automated approach to identify cell-based microarray spots and spot quality control. The approach was used to analyze the adhesion of murine cardiac side population cells on combinatorial arrays of extracellular matrix proteins. Microarrays were imaged by automated fluorescence microscopy and cells were identified using open-source image analysis software (CellProfiler). From these images, clusters of cells making up single cell spots were reliably identified by analyzing the distances between cells using a density-based clustering algorithm (OPTICS). Naïve Bayesian classifiers trained on manually scored training sets identified good and poor quality spots using spot size, number of cells per spot, and cell location as quality control criteria. Combined, the approach identified 78% of high quality spots and 87% of poor quality spots. Full factorial analysis of the resulting microarray data revealed that collagen IV exhibited the highest positive effect on cell attachment. This data processing approach allows for fast and unbiased analysis of cell-based microarray data

Cell patterning and aggregate formation inside microwells.

<p><b>A)</b> Cell patterning. Cells were localized inside the microwells. <b>B)</b> After cell seeding, the cells in the microwell array were cultured in a petri dish and aggregates formed within 24 h. <b>C)</b> Once the aggregate formation is complete inside the microwells, they can be stained. <b>D)</b> Aggregates can be imaged inside microwells. <b>E)</b> Aggregates can be easily released from the microwells by gentle flushing with media for other applications.</p

Aggregate integrity and survival in fluidic manipulations.

<p><b>A)</b> Aggregates formed in microwells can be easily flushed out from the microwell and centrifuged while remaining intact. <b>B)</b> Aggregate can be easily passed through a 30G needle without loosing integrity. <b>C)</b> A representative DAPI/EthD fluorescent image of aggregates before injection. <b>D)</b> A representative DAPI/EthD fluorescent image of aggregates after injection. <b>E)</b> Quantification of dead CSP cells in aggregates passing a 30G needle using EthD/DAPI fluorescent intensity ratio. (All bars represent 100 µm).</p

Characteristics of the Clinical Study Sample.

<p>Values are shown as means±standard deviations or percent frequencies.</p

Activation of NFκB mediates TWEAK-induced downregulation of PGC1α.

<p>(A) Immunoblots of phospho-p65, phospho-IκBα, total-IκBα and GAPDH in isolated cardiomyocytes incubated with 100 ng/ml IgG or rTWEAK at designated time points. (B) Inhibition of NFκB activation with SC-514 (25µM) abolished TWEAK-mediated downregulation of PGC1α expression. * p<0.05 vs. IgG and # p<0.05 vs. rTWEAK in the absence of SC-514.</p

Aggregate survival tests <i>in vitro</i>.

<p><b>A)</b> Subsets of microwell arrays with 2D monolayer of cell culture (2D) and aggregates of three sizes (S, M, and L). Hydrogen peroxide and anoxia/reoxygenation treatments were employed to induce cell death. EthD (red) and DAPI (blue) staining were performed for the determination of cell death. <b>B)</b> Quantification of dead CSP cells in 2D single layer culture and aggregates with variable diameters subjected to 200 µM-hydrogen peroxide treatment using EthD/DAPI fluorescent intensity ratio. Data were normalized to the vehicle groups of 2D monolayer culture and aggregates in three sizes. <b>C)</b> Quantification of dead CSP cells in 2D single layer culture and aggregates with variable diameters subjected to anoxia/reoxygenation using EthD/DAPI fluorescent intensity ratio. Data were normalized to the vehicle groups of 2D monolayer culture and aggregates in three sizes.</p

CSP cell survival <i>in vivo</i> following cardiac injury.

<p><b>A)</b> Protocol to measure the <i>in vivo</i> survival of CSP aggregates and suspensions. <b>B)</b> Representative serial bioluminescence images (BLI) of mice injected with CSP cell aggregates and CSP single cell suspensions. <b>C)</b> Percentage of CSP cell survival measured with BLI.</p

Associations of Echocardiographic Parameters with Hypertension Status.

<p>*Estimated regression coefficients represent the change in blood pressure measure per 1-SD change in the echocardiographic parameter.</p