Corneal recovery in a rabbit limbal stem cell deficiency model by autologous grafts of tertiary outgrowths from cultivated limbal biopsy explants

PubMed ID: 26937166Purpose: To determine the corneal regenerative capacity of sequentially generated primary, secondary, and tertiary limbal explant outgrowths in a limbal stem cell deficiency (LSCD) surgical model. Methods: Two-millimeter-long limbal shallow biopsies were surgically excised from the upper quadrant of the right eye of rabbits and set on preserved amniotic membrane for explant culture. After the generation of primary outgrowth, the biopsies were sequentially transferred to new amniotic membrane to generate secondary and then tertiary outgrowths. Eighteen rabbits were subjected to a 360° limbal peritomy extending into the scleral zone and combined with superficial keratectomy of the corneal periphery and thorough mechanical debridement of the central cornea in their left eye. Right eye outgrowths, six of each generation, were engrafted on the ocular surface. Clinical outcomes (neovascularization, corneal clarity, and corneal fluorescein staining) were graded after 6 months. Post-mortem corneas were compared with histology, immunochemistry for p63 and Krt3, ABCG2-dependent dye exclusion, and capacity for outgrowths in explant culture. Results: Immunohistology and western blot of the outgrowths for p63 and Krt3 indicated no differences in expression between the primary and tertiary outgrowths for these two markers of growth and differentiation. Clinically, all rabbits treated with amniotic membrane alone developed severe LSCD. Most rabbits grafted with cell outgrowths from all three outgrowth generations achieved stable (>6 months) recovery of the ocular surface. There were partial failures of grafts performed with two secondary and tertiary outgrowths. However, Kruskal-Wallis statistical analysis of the clinical scores yielded no significant difference between the three groups (p=0.524). Histology showed full anatomic recovery of grafts made with primary and tertiary outgrowths. Krt3 and p63 expression throughout the whole limbal corneal epithelium with primary or tertiary outgrowths was not distinguishable from each other. The percentage of dye-excluding cells present within this zone and the capacity of the explant epithelial outgrowth of the regenerated peripheral corneal zone were also on par with those of the donor corneas. The Krt3-negative cells that characterize the basal epithelial layer of the normal limbus could not be found in any regenerated cornea from the primary to tertiary outgrowths. Conclusions: Our results demonstrate that in rabbits post-primary explant outgrowths retain the capacity for LSCD recovery found in primary explants. © 2016, Molecular Vision.National Institutes of Health, NIH: K08EY02399

Overconfidence and trading volume

Theoretical models predict that overconfident investors will trade more than rational investors. We directly test this hypothesis by correlating individual overconfidence scores with several measures of trading volume of individual investors. Approximately 3,000 online broker investors were asked to answer an internet questionnaire which was designed to measure various facets of overconfidence (miscalibration, volatility estimates, better than average effect). The measures of trading volume were calculated by the trades of 215 individual investors who answered the questionnaire. We find that investors who think that they are above average in terms of investment skills or past performance (but who did not have above average performance in the past) trade more. Measures of miscalibration are, contrary to theory, unrelated to measures of trading volume. This result is striking as theoretical models that incorporate overconfident investors mainly motivate this assumption by the calibration literature and model overconfidence as underestimation of the variance of signals. In connection with other recent findings, we conclude that the usual way of motivating and modeling overconfidence which is mainly based on the calibration literature has to be treated with caution. Moreover, our way of empirically evaluating behavioral finance models—the correlation of economic and psychological variables and the combination of psychometric measures of judgment biases (such as overconfidence scores) and field data—seems to be a promising way to better understand which psychological phenomena actually drive economic behavior. Copyright The Geneva Association 2007Overconfidence, Differences of opinion, Trading volume, Individual investors, Investor behavior, Correlation of economic and psychological variables, Combination of psychometric measures of judgment biases and field data, D8, G1,