Quantification of Multicellular Organization, Junction Integrity, and Substrate Features in Collective Cell Migration.

Quantitative analysis of multicellular organization, cell-cell junction integrity, and substrate properties is essential to understand the mechanisms underlying collective cell migration. However, spatially and temporally defining these properties is difficult within collectively migrating cell groups due to challenges in accurate cell segmentation within the monolayer. In this paper, we present Matlab®-based algorithms to spatially quantify multicellular organization (migration distance, interface roughness, and cell alignment, area, and morphology), cell-cell junction integrity, and substrate features in confocal microscopy images of two-dimensional collectively migrating endothelial monolayers. We used novel techniques, including measuring the migrating front roughness using a parametric curve formulation, automatically binning cells to obtain data as a function of distance from the migrating front, using iterative morphological closings to fully define cell boundaries, quantifying ß-catenin localization as a measure of cell-cell junction integrity, and skeletonizing fibronectin to determine fiber length and orientation. These algorithms are widely accessible, as they use common fluorescent markers and Matlab® functions, and provide high-throughput critical feature quantification within collectively migrating cell groups. These image analysis algorithms can help standardize feature quantification among different experimental techniques, cell types, and research groups studying collective cell migration.

Engineering musculoskeletal tissues with human embryonic germ cell derivatives.

The cells derived from differentiating embryoid bodies of human embryonic germ (hEG) cells express a broad spectrum of gene markers and have been induced toward ecto- and endodermal lineages. We describe here in vitro and in vivo differentiation of hEG-derived cells (LVEC line) toward mesenchymal tissues. The LVEC cells express many surface marker proteins characteristic of mesenchymal stem cells and differentiated into cartilage, bone, and fat. Homogenous hyaline cartilage was generated from cells after 63 population doublings. In vivo results demonstrate cell survival, differentiation, and tissue formation. The high proliferative capacity of hEG-derived cells and their ability to differentiate and form three-dimensional mesenchymal tissues without teratoma formation underscores their significant potential for regenerative medicine. The adopted coculture system also provides new insights into how a microenvironment comprised of extracellular and cellular components may be harnessed to generate hierarchically complex tissues from pluripotent cells.

Chondroitin sulfate based niches for chondrogenic differentiation of mesenchymal stem cells.

Bone marrow-derived mesenchymal stem cells (MSCs) have strong potential in regeneration of musculoskeletal tissues including cartilage and bone. The microenvironment, comprising of scaffold and soluble factors, plays a pivotal role in determining the efficacy of cartilage tissue regeneration from MSCs. In this study, we investigated the effect of a three-dimensional synthetic-biological composite hydrogel scaffold comprised of poly (ethylene glycol) (PEG) and chondroitin sulfate (CS) on chondrogenesis of MSCs. The cells in CS-based bioactive hydrogels aggregated in a fashion which mimicked the mesenchymal condensation and produced cartilaginous tissues with characteristic morphology and basophilic extracellular matrix production. The aggregation of cells resulted in an enhancement of both chondrogenic gene expressions and cartilage specific matrix production compared to control PEG hydrogels containing no CS-moieties. Moreover, a significant down-regulation of type X collagen expression was observed in PEG/CS hydrogels, indicating that CS inhibits the further differentiation of MSCs into hypertrophic chondrocytes. Overall, this study demonstrates the morphogenetic role of bioactive scaffold-mediated microenvironment on temporal pattern of cartilage specific gene expressions and subsequent matrix production during MSC chondrogenesis.

Histamine H1 and H2 receptor-mediated vasoreactivity of human internal thoracic and radial arteries.

BACKGROUND: Although internal thoracic arteries (ITAs) and radial arteries (RAs) have been shown to have similar patency, RAs tend to be more vasospastic postoperatively compared with ITAs. Therefore, the purpose of this study was to examine the effect of histamine subclass 1 (H1) receptors and histamine subclass 2 (H2) receptors on vasoreactivity in human ITAs and RAs. METHODS: Vessels were obtained from coronary artery bypass grafting patients. Human arterial rings (2 mm) were mounted in tissue baths, and baseline contractility was determined. Histamine concentration response curves (10(-9)-10(-3) mol/L) were performed in the absence or presence of diphenhydramine (H1 antagonist, 10(-4) mol/L) or famotidine (H2 antagonist, 10(-4) mol/L). Comparison of curves was performed by 2-way analysis of variance with repeated measures and a Bonferroni post-t test. RESULTS: Maximal contraction to histamine was significantly greater in RA (8.3 +/- 0.8 g, n = 6) than in ITA (2.9 +/- 0.3, n = 6), (P < .05). However, there was no difference in sensitivity. Histamine-mediated responses of both RA and ITA were blocked by pre-exposure to H1 antagonist, whereas an H2 antagonist only partially inhibited RA responses while blocking most of the ITA response to histamine. CONCLUSION: These studies suggest that H1 receptors alone cause contraction in RA but not in ITA, which may have potential linkage to patency and vasospasm. Further studies are necessary to identify the exact role of H2 receptors in ITA.

Novel mathematical algorithm for pupillometric data analysis.

Pupillometry is used clinically to evaluate retinal and optic nerve function by measuring pupillary response to light stimuli. We have developed a mathematical algorithm to automate and expedite the analysis of non-filtered, non-calculated pupillometric data obtained from mouse pupillary light reflex recordings, obtained from dynamic pupillary diameter recordings following exposure of varying light intensities. The non-filtered, non-calculated pupillometric data is filtered through a low pass finite impulse response (FIR) filter. Thresholding is used to remove data caused by eye blinking, loss of pupil tracking, and/or head movement. Twelve physiologically relevant parameters were extracted from the collected data: (1) baseline diameter, (2) minimum diameter, (3) response amplitude, (4) re-dilation amplitude, (5) percent of baseline diameter, (6) response time, (7) re-dilation time, (8) average constriction velocity, (9) average re-dilation velocity, (10) maximum constriction velocity, (11) maximum re-dilation velocity, and (12) onset latency. No significant differences were noted between parameters derived from algorithm calculated values and manually derived results (p ≥ 0.05). This mathematical algorithm will expedite endpoint data derivation and eliminate human error in the manual calculation of pupillometric parameters from non-filtered, non-calculated pupillometric values. Subsequently, these values can be used as reference metrics for characterizing the natural history of retinal disease. Furthermore, it will be instrumental in the assessment of functional visual recovery in humans and pre-clinical models of retinal degeneration and optic nerve disease following pharmacological or gene-based therapies.