Schlemm's canal is an important structure of the conventional aqueous humor outflow pathway and is critically involved in regulating the intraocular pressure. In this study, we report a novel finding that prospero homeobox protein 1 (Prox-1), the master control gene for lymphatic development, is expressed in Schlemm's canal. Moreover, we provide a novel in vivo method of visualizing Schlemm's canal using a transgenic mouse model of Prox-1-green fluorescent protein (GFP). The anatomical location of Prox-1+ Schlemm's canal was further confirmed by in vivo gonioscopic examination and ex vivo immunohistochemical analysis. Additionally, we show that the Schlemm's canal is distinguishable from typical lymphatic vessels by lack of lymphatic vessel endothelial hyaluronan receptor (LYVE-1) expression and absence of apparent sprouting reaction when inflammatory lymphangiogenesis occurred in the cornea. Taken together, our findings offer new insights into Schlemm's canal and provide a new experimental model for live imaging of this critical structure to help further our understanding of the aqueous humor outflow. This may lead to new avenues toward the development of novel therapeutic intervention for relevant diseases, most notably glaucoma.

We develop an analytical framework to study experimental design in two-sided marketplaces. Many of these experiments exhibit interference, where an intervention applied to one market participant influences the behavior of another participant. This interference leads to biased estimates of the treatment effect of the intervention. We develop a stochastic market model and associated mean field limit to capture dynamics in such experiments and use our model to investigate how the performance of different designs and estimators is affected by marketplace interference effects. Platforms typically use two common experimental designs: demand-side “customer” randomization ([Formula: see text]) and supply-side “listing” randomization ([Formula: see text]), along with their associated estimators. We show that good experimental design depends on market balance; in highly demand-constrained markets, [Formula: see text] is unbiased, whereas [Formula: see text] is biased; conversely, in highly supply-constrained markets, [Formula: see text] is unbiased, whereas [Formula: see text] is biased. We also introduce and study a novel experimental design based on two-sided randomization ([Formula: see text]) where both customers and listings are randomized to treatment and control. We show that appropriate choices of [Formula: see text] designs can be unbiased in both extremes of market balance while yielding relatively low bias in intermediate regimes of market balance. This paper was accepted by David Simchi-Levi, revenue management and market analytics.

The University of California recently suspended through 2024 the requirement that California applicants submit SAT scores, upending the major role standardized testing has played in college admissions. We study the impact of this decision and its interplay with other policies-such as affirmative action-on admitted class composition.We develop a market model with schools and students. Students have an unobserved true skill level, a potentially observed demographic group membership, and an observed application with both test scores and other features. Bayesian schools optimize the dual-objectives of admitting (1) the "most qualified" and (2) a "diverse" cohort. They estimate each applicant's true skill level using the observed features and potentially their group membership, and then admit students with or without affirmative action.We show that dropping test scores may exacerbate disparities by decreasing the amount of information available for each applicant. However, if there are substantial barriers to testing, removing the test improves both academic merit and diversity by increasing the size of the applicant pool. We also find that affirmative action alongside using group membership in skill estimation is an effective strategy with respect to the dual-objective. Findings are validated with calibrated simulations using cross-national testing data.

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