Elastin is a versatile elastic protein that dominates flexible tissues capable of recoil, and facilitates commensurate cell interactions in these tissues in all higher vertebrates. Elastin's persistence and insolubility hampered early efforts to construct versatile biomaterials. Subsequently the field has progressed substantially through the adapted use of solubilized elastin, elastin-based peptides and the increasing availability of recombinant forms of the natural soluble elastin precursor, tropoelastin. These interactions allow for the formation of a sophisticated range of biomaterial constructs and composites that benefit from elastin's physical properties of innate assembly and elasticity, and cell interactive properties as discussed in this tutorial review.

Surprisingly little is known about the effects of the physical microenvironment on hemopoietic stem and progenitor cells. To explore the physical effects of matrix elasticity on well-characterized primitive hemopoietic cells, we made use of a uniquely elastic biomaterial, tropoelastin. Culturing mouse or human hemopoietic cells on a tropoelastin substrate led to a two- to threefold expansion of undifferentiated cells, including progenitors and mouse stem cells. Treatment with cytokines in the presence of tropoelastin had an additive effect on this expansion. These biological effects required substrate elasticity, as neither truncated nor cross-linked tropoelastin reproduced the phenomenon, and inhibition of mechanotransduction abrogated the effects. Our data suggest that substrate elasticity and tensegrity are important mechanisms influencing hemopoietic stem and progenitor cell subsets and could be exploited to facilitate cell culture.

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PurposeTo characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease.MethodsSingle eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort.ResultsPattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm).ConclusionsPattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease.

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PurposeTo determine the locus of test locations that exhibit statistically similar age-related decline in sensitivity to light increments and age-corrected contrast sensitivity isocontours (CSIs) across the central visual field (VF). We compared these CSIs with test point clusters used by the Glaucoma Hemifield Test (GHT).MethodsSixty healthy observers underwent testing on the Humphrey Field Analyzer 30-2 test grid using Goldmann (G) stimulus sizes I-V. Age-correction factors for GI-V were determined using linear regression analysis. Pattern recognition analysis was used to cluster test locations across the VF exhibiting equal age-related sensitivity decline (age-related CSIs), and points of equal age-corrected sensitivity (age-corrected CSIs) for GI-V.ResultsThere was a small but significant test size–dependent sensitivity decline with age, with smaller stimuli declining more rapidly. Age-related decline in sensitivity was more rapid in the periphery. A greater number of unique age-related CSIs was revealed when using smaller stimuli, particularly in the mid-periphery. Cluster analysis of age-corrected sensitivity thresholds revealed unique CSIs for GI-V, with smaller stimuli having a greater number of unique clusters. Zones examined by the GHT consisted of test locations that did not necessarily belong to the same CSI, particularly in the periphery.ConclusionsCluster analysis reveals statistically significant groups of test locations within the 30-2 test grid exhibiting the same age-related decline. CSIs facilitate pooling of sensitivities to reduce the variability of individual test locations. These CSIs could guide future structure-function and alternate hemifield asymmetry analyses by comparing matched areas of similar sensitivity signatures.

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PurposeRecent studies propose that the use of target stimuli within or close to complete spatial summation reveal larger threshold elevation in ocular disease. The Humphrey Visual Field Analyzer (HFA) is used to assess visual function yet the spatial summation characteristics are unexplored for the central macular region. We therefore wanted to establish the relationship between contrast sensitivity and stimulus size (spatial summation) within the central 20° visual field using the high sampling density of the 10–2 test grid.MethodsThresholds were measured for one eye from 37 normal subjects using the HFA 10–2 test grid with all five Goldmann (G) targets (GI to GV). Subject data were converted to 50-year-old equivalent using published and calculated location-specific decade correction factors. Spatial summation curves were fitted for all data at all locations. The size of Ricco’s critical area (Ac) within which complete spatial summation operates (k = 1), and the slope of partial summation (k < 1: to characterize partial summation), was established.ResultsThe 50-year-old age normative data were determined for all Goldmann stimulus sizes for the 10–2 HFA test grid and showed a marked change in contrast sensitivity for small test stimuli (e.g. GI) and little change in larger test stimuli (e.g. GV). Both the Ac and k values did not vary with age allowing for the application of the age correction factors. Ac and k values increased with eccentricity with GI remaining within complete spatial summation and GII was close or within complete spatial summation. GIII or larger test sizes were always outside complete spatial summation operating within various levels of partial summation.ConclusionsThe developed normative data now allows comparisons of data sets with high sampling density using the 10–2 grid irrespective of subject age. Test size is important when assessing ocular disease yet only GI or GII stimuli operate close to or within complete spatial summation in the macula. Current visual field testing protocols employ GIII which is always outside complete spatial summation and operates under various values of partial summation: GIII may not be the most suitable test size to assess ocular disease affecting the macula.