Open Access
Physiology and Pharmacology  |   June 2017
A Compact Whole-Eye Perfusion System to Evaluate Pharmacologic Responses of Outflow Facility
Author Affiliations & Notes
  • Enhua H. Zhou
    Department of Ophthalmology, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States
  • Michael Paolucci
    Department of Informatics, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States
  • Thaddeus P. Dryja
    Department of Ophthalmology, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States
  • Ted Manley
    Department of Informatics, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States
  • Chuanxi Xiang
    Department of Ophthalmology, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States
  • Dennis S. Rice
    Department of Ophthalmology, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States
  • Ganesh Prasanna
    Department of Ophthalmology, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States
  • Amy Chen
    Department of Ophthalmology, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, United States
  • Correspondence: Enhua H. Zhou, Department of Ophthalmology, Novartis Institutes for BioMedical Research, 22 Windsor Street, Cambridge, MA 02139, USA; enhua.zhou@novartis.com
  • Amy Chen, Department of Ophthalmology, Novartis Institutes for BioMedical Research, 22 Windsor Street, Cambridge, MA 02139, USA; amy1.chen@novartis.com
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 2991-3003. doi:10.1167/iovs.16-20974
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Enhua H. Zhou, Michael Paolucci, Thaddeus P. Dryja, Ted Manley, Chuanxi Xiang, Dennis S. Rice, Ganesh Prasanna, Amy Chen; A Compact Whole-Eye Perfusion System to Evaluate Pharmacologic Responses of Outflow Facility. Invest. Ophthalmol. Vis. Sci. 2017;58(7):2991-3003. doi: 10.1167/iovs.16-20974.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose: To discover novel therapies that lower IOP by increasing aqueous humor outflow facility, ex vivo ocular perfusion systems provide a valuable tool. However, currently available designs are limited by their throughput. Here we report the development of a compact, scalable perfusion system with improved throughput and its validation using bovine and porcine eyes.

Methods: At a fixed IOP of 6 mm Hg, flow rate was measured by flow sensors. We validated the system by measuring the outflow responses to Y-39983 (a Rho kinase inhibitor), endothelin-1 (ET-1), ambrisentan (an antagonist for endothelin receptor A [ETA]), sphigosine-1-phosphate (S1P), JTE-013 (antagonist for S1P receptor 2 [S1P2]), S-nitroso-N-acetylpenicillamine (SNAP, a nitric oxide [NO] donor), and 3-Morpholino-sydnonimine (SIN-1, another NO donor).

Results: The instrument design enabled simultaneous measurements of 20 eyes with a footprint of 1 m2. Relative to vehicle control, Y-39983 increased outflow by up to 31% in calf eyes. On the contrary, ET-1 decreased outflow by up to 79%, a response that could be blocked by pretreatment with ambrisentan, indicating a role for ETA receptors. Interestingly, the effect of ET-1 was also inhibited by up to 70% to 80% by pretreatment with NO donors, SNAP and SIN-1. In addition to testing in calf eyes, similar effects of ET-1 and ambrisentan were observed in adult bovine and porcine eyes.

Conclusions: The compact eye perfusion platform provides an opportunity to efficiently identify compounds that influence outflow facility and may lead to the discovery of new glaucoma therapies.

Primary open-angle glaucoma (POAG) affects approximately 60 million people worldwide, including 2.2% of those older than 40.1 Although no cure exists for glaucoma, reduction in IOP is a proven therapy, with each mm Hg of reduction associated with approximately 10% reduction in disease progression.2,3 IOP reduction can be achieved by reducing aqueous humor secretion or facilitating aqueous humor outflow. The former mechanism explains the efficacy of medications, such as β-blockers, carbonic anhydrase inhibitors, and α2-agonists. In the latter category, cholinergics induce ciliary muscle contraction to facilitate outflow through the trabecular meshwork (TM) and prostaglandin analogs facilitate outflow mainly through the unconventional uveoscleral outflow tract by which aqueous exits the eye through the ciliary muscle and suprachoroidal space.4 However, these drugs do not directly target the TM, the dysfunction of which is believed to be the root cause of the elevated IOP seen in POAG.5 More recently, several compounds that target the TM have been shown to reduce pressure in glaucoma patients.68 These include latrunculin,9 Rho kinase inhibitors,10,11 and adenosine A1 agonists.12,13 Their IOP-lowering effects were not superior to prostaglandin analogs, and ocular hyperemia was a common side effect. As such, a major thrust for glaucoma drug discovery is to identify more effective and better tolerated therapies targeting the conventional outflow tract. 
Ex vivo perfusion of whole eyes or the anterior segment has long been proven a valid model for studying outflow facility.7,1416 They fall into either pump-driven systems1719 or gravity-driven systems2025 (Table). In pump-driven systems, IOP is monitored by pressure transducers while flow rate is specified.1719 A key limitation for these systems is the relatively large footprint of the pumps. In gravity-driven systems, IOP is also monitored by pressure transducers while flow rate is deduced from the rate of changes in reservoir weight,20,21 the rate of changes in reservoir height,22 or the pressure drop through a tubing of known resistance.7,24 A key challenge for such systems is accurate quantification of flow rate, which was recently addressed by Sherwood et al.23 using a commercially available, compact, flow sensor. Although the systems reviewed above have facilitated the understanding of several molecular targets and mechanisms that modulate outflow facility,5 the relatively large footprint and low throughput limit their use in drug discovery. 
Table
 
Summary of Ex Vivo Perfusion Systems for Studying Outflow Facility
Table
 
Summary of Ex Vivo Perfusion Systems for Studying Outflow Facility
In this work, we developed an ex vivo eye perfusion system with reduced footprint, improved throughput, and the ability to resolve time-dependent pharmacologic response. We first validated the system using Y-39983 (a Rho kinase inhibitor) and sphigosine-1-phosphate (S1P), two molecules known to increase26,27 and decrease28,29 outflow facility, respectively. We also discovered novel interactions between endothelin-1 (ET-1) and nitric oxide (NO) in the whole eye that have only been demonstrated before in cell-based assays. This system may serve to evaluate candidate drugs before in vivo testing. Its application may reduce animal use and facilitate more efficient discovery of therapies targeting the outflow pathway. 
Materials and Methods
Perfusion Setup
Similar to other gravity-driven perfusion systems,2024,30 our system measures the flow rate at controlled IOP (Figs. 1A, 1B). To control IOP, a reservoir traveled vertically on a motorized stage (Zaber Technologies, Inc., Vancouver, British Columbia, Canada). IOP is computed as the hydrostatic pressure, Display Formula
\(\def\upalpha{\unicode[Times]{x3B1}}\)\(\def\upbeta{\unicode[Times]{x3B2}}\)\(\def\upgamma{\unicode[Times]{x3B3}}\)\(\def\updelta{\unicode[Times]{x3B4}}\)\(\def\upvarepsilon{\unicode[Times]{x3B5}}\)\(\def\upzeta{\unicode[Times]{x3B6}}\)\(\def\upeta{\unicode[Times]{x3B7}}\)\(\def\uptheta{\unicode[Times]{x3B8}}\)\(\def\upiota{\unicode[Times]{x3B9}}\)\(\def\upkappa{\unicode[Times]{x3BA}}\)\(\def\uplambda{\unicode[Times]{x3BB}}\)\(\def\upmu{\unicode[Times]{x3BC}}\)\(\def\upnu{\unicode[Times]{x3BD}}\)\(\def\upxi{\unicode[Times]{x3BE}}\)\(\def\upomicron{\unicode[Times]{x3BF}}\)\(\def\uppi{\unicode[Times]{x3C0}}\)\(\def\uprho{\unicode[Times]{x3C1}}\)\(\def\upsigma{\unicodeTimes]{x3C3}}\)\(\def\uptau{\unicode[Times]{x3C4}}\)\(\def\upupsilon{\unicode[Times]{x3C5}}\)\(\def\upphi{\unicode[Times]{x3C6}}\)\(\def\upchi{\unicode[Times]{x3C7}}\)\(\def\uppsy{\unicode[Times]{x3C8}}\)\(\def\upomega{\unicode[Times]{x3C9}}\)\(\def\bialpha{\boldsymbol{\alpha}}\)\(\def\bibeta{\boldsymbol{\beta}}\)\(\def\bigamma{\boldsymbol{\gamma}}\)\(\def\bidelta{\boldsymbol{\delta}}\)\(\def\bivarepsilon{\boldsymbol{\varepsilon}}\)\(\def\bizeta{\boldsymbol{\zeta}}\)\(\def\bieta{\boldsymbol{\eta}}\)\(\def\bitheta{\boldsymbol{\theta}}\)\(\def\biiota{\boldsymbol{\iota}}\)\(\def\bikappa{\boldsymbol{\kappa}}\)\(\def\bilambda{\boldsymbol{\lambda}}\)\(\def\bimu{\boldsymbol{\mu}}\)\(\def\binu{\boldsymbol{\nu}}\)\(\def\bixi{\boldsymbol{\xi}}\)\(\def\biomicron{\boldsymbol{\micron}}\)\(\def\bipi{\boldsymbol{\pi}}\)\(\def\birho{\boldsymbol{\rho}}\)\(\def\bisigma{\boldsymbol{\sigma}}\)\(\def\bitau{\boldsymbol{\tau}}\)\(\def\biupsilon{\boldsymbol{\upsilon}}\)\(\def\biphi{\boldsymbol{\phi}}\)\(\def\bichi{\boldsymbol{\chi}}\)\(\def\bipsy{\boldsymbol{\psy}}\)\(\def\biomega{\boldsymbol{\omega}}\)\(\rho gH\)
, where ρ is the density of water, g is the gravity on earth, and H is the difference in water levels between the reservoir and the eye container (see Perfusion Protocol). To measure the flow, we used compact liquid flow sensors that are in turn based on thermal sensors (LG16–0430A; Sensirion AG, Stafa, Switzerland), similar to that used by Sherwood et al.23 A computer controls the motorized stage and collects signal from the flow sensors through a data acquisition board (National Instruments, Austin, TX, USA). Data communication, processing, and user interface were implemented using custom software written in Matlab (Mathworks, Natick, MA, USA). Data were acquired once every minute. 
Figure 1
 
The setup and calibration of the perfusion system. (A) A schematic showing the working principle. DAQ, data acquisition. (B) A drawing of the system. (C) To calibrate the system in the absence of any eye, we varied pressure as a function of time (gray trace) by moving the reservoir vertically (pressure was set to zero where flow rate was zero and calculated from ρgH [see Methods]). The resultant changes in flow rate (blue trace) were measured using the flow sensor. For clarity, only one representative example is shown. (D) Flow rate was proportional to pressure, the slope being the intrinsic facility in the absence of any eye. Each set of unique markers, fitted with a straight line, represents raw data points for one sensor (n = 20 sensors). Note that when pressure goes negative, so does flow rate.
Figure 1
 
The setup and calibration of the perfusion system. (A) A schematic showing the working principle. DAQ, data acquisition. (B) A drawing of the system. (C) To calibrate the system in the absence of any eye, we varied pressure as a function of time (gray trace) by moving the reservoir vertically (pressure was set to zero where flow rate was zero and calculated from ρgH [see Methods]). The resultant changes in flow rate (blue trace) were measured using the flow sensor. For clarity, only one representative example is shown. (D) Flow rate was proportional to pressure, the slope being the intrinsic facility in the absence of any eye. Each set of unique markers, fitted with a straight line, represents raw data points for one sensor (n = 20 sensors). Note that when pressure goes negative, so does flow rate.
To control temperature, an aluminum block with recesses for glass beakers was heated from underneath using a silicone rubber heating blanket (Briskheat, Columbus, OH, USA) and housed in an environmental chamber made of polycarbonate sheets (Fig. 1B). The temperature inside the chamber was set to 24°C and the beakers were bathed in water to maintain humidity. This temperature was used for perfusion experiments because higher temperatures not only caused outgassing of perfusion media to block tubing but also increased the extent of bacterial contamination. Bacterial contamination was rarely noted in previous studies on bovine eye perfusion,17,18,31 which lasted for only a few hours; it is possible that bacterial outgrowth takes longer time to become noticeable. 
Computer-Aided Design and Three-Dimensional Printing
The media reservoir, environmental chambers, syringe holders, the platform for the valves, and flow sensors were designed using SolidWorks (Dassault Systèmes SolidWorks Corporation, Waltham, MA, USA) and printed using Polyjet technology on Objet Connex 350, or FDM technology on Fortus 360mc and Dimension Elite (Stratasys Ltd., Billerica, MA, USA). The drawing of the whole system is shown in Figure 1B. 
Animal Eyes, Solutions, and Compounds
Calf (2–14 days old), cattle (1–4 years old), and porcine (4–6 months old) eyes were obtained from a local abattoir and shipped at room temperature so they arrived in the laboratory approximately 4 hours postmortem (Research 87, Inc., Boylston, MA, USA). 
For both shipment and perfusion studies, eyes were immersed in the bathing solution: Hank's balanced salt solution supplemented with 1× antibiotic-antimycotic (100 U/mL penicillin, 100 U/mL streptomycin, 0.25 μg/mL amphotericin B; Thermo Fisher Scientific, Inc., Waltham, MA, USA) and 15 μg/mL ofloxacin (Sigma-Aldrich Corp., St. Louis, MO, USA). Eyes were perfused with the perfusion solution: CO2-independent medium that contains 0.7 g/L glucose (CIM, cat# 18045088; Thermo Fisher Scientific, Inc.) supplemented with 0.1% BSA (fraction V with low endotoxin; from Gemini Bio-Products, West Sacramento, CA, USA), 100 μg/mL ascorbate (Sigma-Aldrich Corp.), 1× Glutamax (Thermo Fisher Scientific, Inc.), 1× antibiotic-antimycotic, and 15 μg/mL ofloxacin (Sigma-Aldrich Corp.). The following molecules were prepared in stock solutions and evaluated in perfusion experiments: Y-39983, ambrisentan, and JTE-013 (antagonist for S1P receptor 2 [S1P2]) (10 mM in dimethyl sulfoxide [DMSO], synthesized by Novartis Institutes for BioMedical Research, Cambridge, MA, USA); ET-1 (0.4 mg/mL in PBS with 1% BSA; Enzo Life Sciences, Inc., Farmingdale, NY, USA); 3-Morpholino-sydnonimine (SIN-1) (100 mM in water) and S1P (1 mM in PBS with 1% BSA) (Cayman Chemical Company, Ann Arbor, MI, USA); and S-nitroso-N-acetylpenicillamine (SNAP) (250 mM in DMSO, Sigma-Aldrich Corp.). 
Perfusion Protocol
Before loading eyes, we filled the perfusion system with perfusion solution and examined the fluid path to ensure the absence of bubbles. To characterize the intrinsic flow resistance of the system, we varied the reservoir height while recording the flow rate; an example calibration result is shown in Figures 1C and 1D. To identify the reference reservoir height with a pressure gradient of zero, the reservoir height was adjusted to achieve a zero flow. Finally, the reservoir was raised to achieve a pressure gradient of 6 mm Hg, the perfusion pressure used throughout this article. (In calf eyes, this perfusion pressure has been reported to elicit slower washout, which is the increase in outflow facility over time in animal eyes perfused ex vivo,32 than do higher pressures.17) We chose to report the flow rate (or flow) in this article; outflow facility can be calculated by dividing the flow rate by 6 mm Hg. 
Each eye was cleared of extraocular tissue, washed in fresh PBS, and set in a 50 mL beaker (14000–50; Kimbal Chase, Rockwood, TN, USA) padded with surgical gauze and filled with the bathing solution up to the limbus. The eye was then cannulated with two 27-gauge butterfly needles (SAI Infusion Technologies, Lake Villa, IL, USA) and covered with surgical gauze to prevent drying. One needle was connected to the reservoir through tubing and an in-line flow sensor and the other was connected to a 1-mL syringe, which was used to withdraw or inject solutions. Once the flow became stabilized, usually within 1 to 2 hours after cannulation, the data recording began. To introduce a treatment into the anterior chamber, a fixed volume of perfusate was withdrawn and subsequently the same volume of the test compound in fresh perfusion solution was injected; both withdrawal and injection were by hand and took approximately 5 to 10 seconds. The injection volume was 300 μL for calf and cattle eyes and 150 μL for porcine eyes. 
To evaluate physiological responses following a treatment, we used protocols we termed the agonist mode or antagonist mode. In the agonist mode, we added vehicle or test compound only once after recording the baseline for 10 to 20 minutes. In antagonist mode, the first test compound or solution was followed by addition of ET-1 or S1P an hour later without completely removing the first treatment. 
The vehicle group and treatment groups were always tested in parallel. When testing eyes in a paired manner, we subjected one eye to vehicle and the fellow eye to treatment. When testing eyes in a randomized manner, we subjected three to four eyes to vehicle each day and the other eyes to various treatments. On a given day, a single perfusion set up could perfuse a maximum of 20 eyes. 
Data Normalization and Calculation of the Rate of Washout
For the agonist mode, the flow rate was first normalized to baseline: Display Formula
\({F_N}(t) = F(t)/{F_B}\)
, where Display Formula
\(F(t)\)
was the recorded flow as a function of time (t), and Display Formula
\({F_B}\)
was the pretreatment baseline flow rate. This normalization removed the eye-to-eye variations in baseline flow rate (Figs. 2A, 2B). For each experiment, Display Formula
\({F_N}(t)\)
is further normalized by the averaged vehicle flow rate: Display Formula
\({F_{NN}}(t) = {F_N}(t)/F_N^V(t)\)
, where Display Formula
\(F_N^V\left( t \right) = mean({F_N}(t))\)
for all vehicle-treated eyes (n = 3–4 for each experiment; Figs. 2C, 2E). This normalization attempts to account for the day-to-day variations in vehicle responses as well as time-dependent flow changes, known as the washout phenomenon.17,18,21,32,33 In several experiments, we perfused paired eyes, with one receiving vehicle and the other receiving drug. To analyze drug response, the first normalization is same as above, but the second normalization is performed against the paired vehicle eye: Display Formula
\(F_N^{paired}(t) = {F_N}(t)/F_N^{pairedV}(t)\)
, where Display Formula
\(F_N^{pairedV}(t)\)
is Display Formula
\({F_N}(t)\)
for the paired eye receiving vehicle (Figs. 2D, 2F). 
Figure 2
 
The process of data normalization is illustrated using three pairs of eyes treated with 0.1 μM ET-1 or vehicle as examples. In (AD), each pair of eyes shares one color; the solid lines are for the vehicle-treated eyes and the dashed lines for ET-1-treated eyes. For each eye, raw flow rates (A) were first normalized to pretreatment baselines to yield baseline-normalized flow (B). In an unpaired paradigm assuming each eye is independent, a second normalization to the average of vehicle control was carried out (C, E). By contrast, in a paired paradigm, a second normalization to paired vehicle control was carried out (D, F). Both paradigms yielded nearly identical treatment responses (E, F; mean ± SD). n = 7 pairs of eyes.
Figure 2
 
The process of data normalization is illustrated using three pairs of eyes treated with 0.1 μM ET-1 or vehicle as examples. In (AD), each pair of eyes shares one color; the solid lines are for the vehicle-treated eyes and the dashed lines for ET-1-treated eyes. For each eye, raw flow rates (A) were first normalized to pretreatment baselines to yield baseline-normalized flow (B). In an unpaired paradigm assuming each eye is independent, a second normalization to the average of vehicle control was carried out (C, E). By contrast, in a paired paradigm, a second normalization to paired vehicle control was carried out (D, F). Both paradigms yielded nearly identical treatment responses (E, F; mean ± SD). n = 7 pairs of eyes.
For antagonist mode, we tested if the treatment modifies the response of an eye to a challenge (e.g., ET-1). Hence, the flow rate is normalized to the baseline before the challenge (Display Formula
\({F_{B2}}\)
): Display Formula
\({F_{N2}}(t) = F(t)/{F_{B2}}\)
. When using 0.1 μM ET-1 as the challenge, we computed the maximal ET-1 response as the maximal fractional reduction in flow rate within 20 to 200 minutes after ET-1 challenge: Display Formula
\(R = 1 - {\rm{min}}({F_{N2}}\left( t \right))\)
. For each experiment, the average ET-1 response for all vehicle-treated eyes (n = 3–4) is Display Formula
\({R^V} = mean(R)\)
. To account for the day-to-day variation in ET-1 response of vehicle-treated eyes, we computed the percent inhibition of maximum ET-1 response as Display Formula
\(I = 1 - R/{R^V}\)
To determine the rate of washout for each eye at a given time point, we computed the slope of flow rate versus time using a time span of up to 30 minutes centered at that time point. This slope was then normalized by IOP (6 mm Hg) to obtain the rate of washout. As a solution exchange typically induced artificial changes in flow rate, we did not compute the rate of washout from 0 to 20 minutes following a solution exchange. If a time span contained the time of a solution exchange, we excluded all time points at and after that solution exchange. Data analysis was implemented using custom code written in Matlab. 
Histology, Live-Dead Staining, and Fluorescent Imaging
For histology, bovine eyes were fixed either without perfusion (“fresh”) or at 18 hours postperfusion in 10% neutral buffered formalin for 4 days, dehydrated with graded ethanol, and embedded in paraffin by Tissue-Tek VIP processor (Sakura Finetek, Torrance, CA, USA). Sections of 5-μm thickness were stained with hematoxylin-eosin (H&E) in Tissue-Tek Prisma (Sakura Finetek), mounted in Tissue-Tek GlasTM (Sakura Finetek), and scanned in Aperio AT2 scanner using a ×40 objective (Leica, Wetzlar, Germany). Histologic images were viewed in Aperio eSlide Manager (Leica). For live-dead staining, calf eyes were perfused at 6 mm Hg for approximately 18 hours with the perfusion solution. A total of 300 μL was withdrawn from each eye, followed by the injection of 300 μL perfusion solution containing ethidium homodimer-1 (EthD1; 4 μM), calcein AM (8 μM), and Hoechst 33342 (20 μg/mL), all from Thermo Fisher Scientific, Inc., and incubated for 15 minutes without continued perfusion. The anterior segment, which contains cornea, a ring of sclera, and the TM, was subsequently dissected out as described in Reference 15. After rinsing in PBS, the anterior segment was imaged using a Nikon (Tokyo, Japan) microscope using ×10 and ×20 objectives (Eclipse TE2000-U). 
Dye Clearance During Perfusion of Calf Eyes
To assess the clearance of dye molecules from the anterior chamber following a bolus injection, we introduced 300 μL perfusion solution containing either vehicle or a mixture of fluorescent dyes into calf eyes perfused at 6 mm Hg. The mixture contained fluorescein sodium (32 μg/mL, molecular weight [MW] = 376.27 Da; Altaire Pharmaceuticals, Inc., Riverhead, NY, USA) and Texas Red–labeled dextran (200 μg/mL, MW = 40 kDa; Thermo Fisher Scientific, Inc.). The flow rates were continuously monitored to assess whether injected dyes changed flow rates. A 40-μL sample was collected, without replenishment, from the anterior chamber at each of the five time points (0, 40, 118, 208, and 290 minutes). The fluorescence was read at excitation/emission wavelengths of 488/521 nm and 595/615 nm for fluorescein and Texas Red–labeled dextran, respectively, using a fluorophotometer (infinite M1000; Tecan, Mannedorf, Switzerland). Serial dilutions of the stock solution were measured to generate standard curves. Calculation of dye concentrations in the samples and data processing were implemented using custom code written in Matlab. 
Dye clearance also can be estimated assuming a uniform concentration of Display Formula
\(C\left( t \right)\)
, where t is time, in a chamber with fixed volume (V), and that the dye only leaves via outflow at a constant rate (F). The dye concentration at time t can be derived as Display Formula
\(C\left( t \right) = C\left( 0 \right){e^{ - tF/V}}\)
. The time it takes for C(t) to become C(0)/2 is therefore  
\begin{equation}\tag{1}{t_{1/2}} = - \ln \left( {0.5} \right)V/F\end{equation}
 
Statistical Methods
For comparing the rate of washout with zero, the one-sample t-test was used. For analyzing eyes in a paired manner, the paired Student's t-test (1-tailed, assuming equal variance) was used. For all other cases, unpaired Student's t-test (2-tailed, assuming unequal variance) was used. A difference is considered significant if P ≤ 0.05. Data are presented as mean ± SD. 
Results
Calibration
The setup for measuring 20 eyes in parallel is shown in Figures 1A through 1B. At the beginning of each experiment, the sensors were calibrated by determining the pressure-flow relationship in the absence of any eyes. We varied the reservoir height using the motorized stage while measuring the flow rate using the flow sensors (Figs. 1A–C). The hydrostatic pressure was computed from the difference between reservoir height and reference height (see Methods). Flow rate varied linearly with pressure, yielding a nominal outflow facility of 14.36 ± 1.56 μL/min/mm Hg for the instrument alone, which far exceeded that of a bovine eye (see below). Calibration was carried out once a week with consistent results. 
Baseline Outflow Characteristics
When perfused at 6 mm Hg, the baseline flow rate of calf eyes of mixed strains was 6.48 ± 1.91 μL/min (mean ± SD, n = 377), which was indistinguishable from that of the Jersey strain (6.29 ± 1.74, n = 42) or the Holstein strain (6.64 ± 2.77, n = 26). There was no significant difference between calf eyes and cattle eyes (6.07 ± 3.15, n = 33, Fig. 3). However, the baseline flow rate in these eyes was significantly higher than that in porcine eyes (1.96 ± 0.79, n = 51) (Fig. 3). In calf eyes, the flow rate increased over time (Figs. 3D, 3E), similar to that reported by others.17,18,32 Interestingly, despite a transient increase in the rate of washout associated with the introduction of 300 μL vehicle-containing perfusion solution, the rate of washout generally declined over time. The flow rate approached a steady state (Fig. 3D) and the washout rate approached zero after roughly 10 hours of perfusion (Fig. 3E). Qualitatively similar findings were made on cattle eyes, although the rate of washout appeared lower in cattle eyes. 
Figure 3
 
Outflow characteristics of calf, cattle, and pig eyes perfused at 6 mm Hg. (A, B) The distribution of baseline flow rate was shown for calf (A) and pig eyes (B). (C) The average baseline flow rate was shown for calf (n = 377), cattle (n = 33; including adult cows and bulls), and pig eyes (n = 51). (D) The washout phenomenon is present in calf eyes (n = 67) and cattle eyes (n = 6) that received a vehicle treatment at time 0 (indicated by an arrow). Data are shown as mean ± SD; ns, P > 0.05; **P < 0.01. (E) The rate of washout was computed as the slope of flow rate against time, divided by the pressure (6 mm Hg). It exhibited a transient elevation after vehicle treatment, followed by a gradual reduction over time. In (D, E), data are shown as mean ± SD. In (E), only open symbols represent statistical difference from 0 (P < 0.05).
Figure 3
 
Outflow characteristics of calf, cattle, and pig eyes perfused at 6 mm Hg. (A, B) The distribution of baseline flow rate was shown for calf (A) and pig eyes (B). (C) The average baseline flow rate was shown for calf (n = 377), cattle (n = 33; including adult cows and bulls), and pig eyes (n = 51). (D) The washout phenomenon is present in calf eyes (n = 67) and cattle eyes (n = 6) that received a vehicle treatment at time 0 (indicated by an arrow). Data are shown as mean ± SD; ns, P > 0.05; **P < 0.01. (E) The rate of washout was computed as the slope of flow rate against time, divided by the pressure (6 mm Hg). It exhibited a transient elevation after vehicle treatment, followed by a gradual reduction over time. In (D, E), data are shown as mean ± SD. In (E), only open symbols represent statistical difference from 0 (P < 0.05).
Effect of Perfusion Culture on Tissue Morphology
After perfusing calf eyes for 18 hours at the culture condition described in Methods, we assessed the morphology of the anterior segment by histologic methods using an H&E stain and a live-dead stain. The TM in eyes perfused overnight (Fig. 4B) appeared very similar to that in freshly received eyes (Fig. 4A) and showed very little evidence of cell damage. The live-dead stain further confirmed good cell viability and little cell death at the TM (Fig. 4C). All the perfusion data reported here were completed within 10 hours of perfusion. 
Figure 4
 
Tissue remained healthy after 18 hours of perfusion (approximately 24 hours postmortem). Calf eyes were received approximately 4 hours postmortem and perfusion was started within 2 hours. (A, B) H&E staining is shown for a newly received eye without any perfusion (A) and an eye perfused for 18 hours (B). (C) Live-dead staining of the TM is shown for an eye perfused for 18 hours. Individual fluorescence channels are shown for EthD-1 (indicating dead cells, C1), calcein AM (indicating live cells, C2), and Hoechst 33342 (all cells, C3). The arrowheads point to aqueous plexus and the arrows point to TM. Images are representative of n = 2 eyes for (A, C), and n = 4 eyes for (B).
Figure 4
 
Tissue remained healthy after 18 hours of perfusion (approximately 24 hours postmortem). Calf eyes were received approximately 4 hours postmortem and perfusion was started within 2 hours. (A, B) H&E staining is shown for a newly received eye without any perfusion (A) and an eye perfused for 18 hours (B). (C) Live-dead staining of the TM is shown for an eye perfused for 18 hours. Individual fluorescence channels are shown for EthD-1 (indicating dead cells, C1), calcein AM (indicating live cells, C2), and Hoechst 33342 (all cells, C3). The arrowheads point to aqueous plexus and the arrows point to TM. Images are representative of n = 2 eyes for (A, C), and n = 4 eyes for (B).
Assessment of Dye Clearance From Anterior Chamber
To estimate the clearance rate of treatment from perfusion, we introduced 300 μL perfusion solution containing both sodium fluorescein and Texas Red–labeled dextran (40 kDa) into calf eyes perfused at 6 mm Hg. Flow rate was 5.6 ± 2.4 μL/min (mean ± SD, n = 8) at baseline and gradually increased with time due to washout (Supplementary Fig. S1C); relative to vehicle-treated eyes, the dyes did not alter flow (Supplementary Fig. S1C, P > 0.05, n = 4 for vehicle and 8 for dyes). Samples were withdrawn from the anterior chamber at multiple time points and measured using a fluorophotometer (Tecan) (see Methods). The anterior chamber volume was calculated as 1073 ± 197 μL and 1118 ± 175 μL (mean ± SD, n = 8) based on the level of immediate dilution of dyes after injection of fluorescein and Texas Red–labeled dextran, respectively; hence a drug solution injected at 300 μL is subjected to an immediate dilution of approximately 3.7-fold. The concentrations for both dyes decreased with time exponentially (Supplementary Figs. S1A, S1B) with a half-life (t1/2) of 101.3 ± 12.8 and 138.5 ± 29.3 minutes for fluorescein and dextran, respectively (mean ± SD, n = 8); t1/2 was shorter for fluorescein than for dextran (P < 0.001, paired t-test). The theoretical t1/2 is also calculated based on the average baseline flow rate and anterior chamber volume using Equation 1. The t1/2 is estimated as 132.8 and 138.4 minutes for fluorescein and dextran, respectively. These theoretical estimates compare favorably with the t1/2 for dextran but less so with that for fluorescein. Although providing no information about the local tissue concentration, these data do provide a rough estimate of the clearance dynamics of injected molecules from the anterior chamber. 
Similar Drug Responses Were Seen in Eyes Studied in a Paired or Unpaired Manner
We first evaluated the effect of 0.1 μM ET-1 on outflow in calf eyes. For each pair of eyes from a single animal, one was subjected to ET-1 treatment and the other to vehicle. Using the paired and unpaired data analysis, described in Methods, nearly identical ET-1 responses were seen, revealing a dramatic reduction in outflow followed by a gradual recovery to baseline (Figs. 2E, 2F). We then used the same protocol to evaluate the effect of 10 μM Y-39983, a Rho kinase inhibitor. Y-39983 caused a time-dependent increase in outflow (Supplementary Fig. S2). Similarly, the paired and unpaired data analysis yielded nearly identical results (Supplementary Figs. S2E, S2F). These data suggested that testing eyes in a paired manner was not critical for our experiment design and hence experimental and control eyes were assigned randomly for all other studies. 
We did find that it was, however, necessary to normalize flow according to the pretreatment baseline flow. The baseline flow rates were positively correlated but substantially different between paired eyes (Supplementary Fig. S3). On average, the baseline flow rate in one eye differed from that in the fellow eye by 23.7% ± 20.2% (mean ± SD; n = 17); such differences could obscure drug responses when paired eye comparisons were made. Indeed, in our experiments using paired eyes treated with vehicle or Y-39983 for 3 hours, the absolute flow rates did not indicate any effect of Y-39983 (Supplementary Fig. S4A). By contrast, when data were normalized to pretreatment (baseline) flow rates, the results indicated that Y-39983 increased outflow above vehicle by 35% ± 18% (paired analysis, P = 0.012) or by 34% ± 13% (unpaired analysis, P = 0.002) (Supplementary Figs. S4B, S4C). As such, we reported our data after normalization to baseline. 
S1P Decreased Outflow and Its Effect Was Blocked by an S1P2 Receptor Antagonist
Calf eyes responded to 100 μM S1P by reducing outflow with a maximum inhibition of 21%, which occurred after approximately 3 hours of treatment (crimson circles in Fig. 5). This reduction could be blocked by pretreatment of the eyes with 100 μM JTE-013, an S1P2 receptor antagonist (blue triangles in Fig. 5). Thus, in a different species, these data replicated previous findings that S1P reduced outflow facility in porcine or human eyes and that this effect was blocked by JTE-013.28,29 
Figure 5
 
A bolus injection of 100 μM S1P reduced outflow facility in calf eyes pretreated with vehicle but not in those pretreated with 100 μM JTE-013, an S1P2 antagonist. The left arrow indicates the injection of vehicle or JTE-013, and the right arrow indicates the injection of S1P. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; P < 0.01 comparing the normalized flow rates when S1P response was maximum (t = 180 minutes).
Figure 5
 
A bolus injection of 100 μM S1P reduced outflow facility in calf eyes pretreated with vehicle but not in those pretreated with 100 μM JTE-013, an S1P2 antagonist. The left arrow indicates the injection of vehicle or JTE-013, and the right arrow indicates the injection of S1P. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; P < 0.01 comparing the normalized flow rates when S1P response was maximum (t = 180 minutes).
Y-39983 Dose-Dependently Increased Outflow
To further validate the system and assess its sensitivity, we treated calf eyes with six different concentrations of Rho kinase inhibitor Y-39983 (0.3–10 μM). Y-39983 induced a time- and dose-dependent elevation in outflow (Fig. 6A). The outflow elevation took 2 to 3 hours to peak and remained fairly stable thereafter (Fig. 6A). When assessed at 3 hours posttreatment, the dose-response curve exhibited an EC50 (half maximal effective concentration) of 0.85 μM and a maximum of 31% increase above vehicle control (Fig. 6B). 
Figure 6
 
A bolus injection of Y-39983 (a ROCK inhibitor) at time 0 induced time- and dose-dependent increase in outflow in calf eyes perfused at 6 mm Hg. (A) For each eye, the flow rate was first normalized to the baseline before treatment, and second normalized to the average time-matched vehicle controls tested on the same day. For clarity, not all error bars are shown. (B) Dose response of Y-39983 in increasing outflow facility at 180 minutes of treatment. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; *P < 0.05; **P < 0.01.
Figure 6
 
A bolus injection of Y-39983 (a ROCK inhibitor) at time 0 induced time- and dose-dependent increase in outflow in calf eyes perfused at 6 mm Hg. (A) For each eye, the flow rate was first normalized to the baseline before treatment, and second normalized to the average time-matched vehicle controls tested on the same day. For clarity, not all error bars are shown. (B) Dose response of Y-39983 in increasing outflow facility at 180 minutes of treatment. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; *P < 0.05; **P < 0.01.
ET-1 Dose-Dependently Decreased Outflow
We treated calf eyes with a bolus of ET-1 at five different concentrations (0.0064–0.25 μM). ET-1 induced a time- and dose-dependent reduction in outflow (Fig. 7A). At all doses, outflow rate reached a minimum at approximately 1 hour posttreatment before gradually returning toward baseline (Fig. 7A). The fact that 0.25 μM did not produce a longer-lasting response than 0.1 μM or 0.04 μM indicates that the temporal dynamics were not driven by dilution of ET-1 over time during perfusion. When assessed at 1 hour posttreatment, the dose-response curve exhibited an EC50 of 0.02 μM and a maximum asymptote of 79% decrease relative to vehicle control (Fig. 7B). 
Figure 7
 
A bolus injection of ET-1 induced time- and dose-dependent decrease in outflow in calf eyes perfused at 6 mm Hg. (A) For each eye, the flow rate was first normalized to the baseline before treatment, and second normalized to the average time-matched vehicle controls tested on the same day. (B) Dose response of ET-1 in reducing outflow facility at 60 minutes of treatment. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; *P < 0.05; **P < 0.01.
Figure 7
 
A bolus injection of ET-1 induced time- and dose-dependent decrease in outflow in calf eyes perfused at 6 mm Hg. (A) For each eye, the flow rate was first normalized to the baseline before treatment, and second normalized to the average time-matched vehicle controls tested on the same day. (B) Dose response of ET-1 in reducing outflow facility at 60 minutes of treatment. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; *P < 0.05; **P < 0.01.
ET-1 Response Was Blocked by Endothelin Receptor A (ETA) Receptor Antagonist in Eyes From Different Species
ET-1 response was further tested in calf, cattle, and pig eyes. In these experiments, we used the antagonist mode and the corresponding normalization method (see Methods). All animal eyes pretreated with vehicle responded to 0.1 μM ET-1 with a profound outflow reduction before gradually returning to baseline (crimson circles in Figs. 8A–C). The average time it took to reach the maximum reduction was approximately 50, 60, and 40 minutes for calf, cattle, and porcine eyes, respectively. In both species, ambrisentan, an ETA receptor antagonist, blocked ET-1 response, confirming the role of ETA receptor in mediating ET-1 response. 
Figure 8
 
A bolus injection of 0.1 μM ET-1 induced transient decrease in outflow facility in calf (A), adult bovine (B), and porcine eyes (C). In all cases, the decrease could be inhibited by pretreatment of the eye with 10 μM ambrisentan. In each panel, the left arrow indicates the injection of vehicle or ambrisentan, and the right arrow indicates the injection of ET-1. Data are shown as mean ± SD; sample sizes (n) are indicated as the numbers in parentheses; P < 0.01 comparing the normalized flow between ambrisentan-treated eyes and vehicle-treated eyes at the time of peak ET-1 response.
Figure 8
 
A bolus injection of 0.1 μM ET-1 induced transient decrease in outflow facility in calf (A), adult bovine (B), and porcine eyes (C). In all cases, the decrease could be inhibited by pretreatment of the eye with 10 μM ambrisentan. In each panel, the left arrow indicates the injection of vehicle or ambrisentan, and the right arrow indicates the injection of ET-1. Data are shown as mean ± SD; sample sizes (n) are indicated as the numbers in parentheses; P < 0.01 comparing the normalized flow between ambrisentan-treated eyes and vehicle-treated eyes at the time of peak ET-1 response.
Blockade of ET-1 Response by NO Donors
NO signaling has been reported to lower IOP in vivo,34 increase outflow facility in ex vivo cultured mouse eyes16 and anterior segments,35 relax precontracted TM and ciliary muscle,36 and reverse ET-1–elicited contraction of TM cells.37 The effect of NO donors on ET-1 response has not been evaluated in ex vivo eye perfusion before. We first tested SIN-1 and SNAP, two NO donors, in ex vivo perfused calf eyes using the agonist mode. At 1000 μM, neither molecule increased flow rate for the test duration of 10 hours (Supplementary Fig. S5). In separate experiments using the antagonist mode, we injected calf eyes with vehicle or SIN-1, at four doses (100–3000 μM), waited for 1 hour, and then injected ET-1 (0.1 μM). Vehicle-treated eyes responded to ET-1 as reported above, showing approximately 70% inhibition of outflow (crimson circles in Fig. 9A), whereas pretreatment with SIN-1 significantly inhibited the ET-1 response in a dose-dependent manner (Fig. 9A). Similar findings were observed for SNAP. We quantified the percent inhibition of maximum ET-1 response (see Methods) as a function of the dose for each NO donor (Fig. 9B). The EC50 was 1288 and 513 μM for SIN-1 and SNAP, respectively, and the maximum response was 94% and 78% inhibition for SIN-1 and SNAP, respectively (Fig. 9B). 
Figure 9
 
Pretreatment of calf eyes with SIN-1 or SNAP dose-dependently inhibited ET-1 response. (A) Flow rate in each eye was normalized to that before ET-1 injection. Similar observation was made with another NO donor, SNAP. (B) Dose response for SIN-1 and SNAP in inhibiting ET-1 response. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend for SIN-1; n = 11, 4, 3, 7, and 3 eyes for SNAP at five ascending doses, respectively; * or #P < 0.05; ** or ##P < 0.01; the number signs and the asterisks indicate comparisons made to vehicle for SIN-1 and SNAP, respectively.
Figure 9
 
Pretreatment of calf eyes with SIN-1 or SNAP dose-dependently inhibited ET-1 response. (A) Flow rate in each eye was normalized to that before ET-1 injection. Similar observation was made with another NO donor, SNAP. (B) Dose response for SIN-1 and SNAP in inhibiting ET-1 response. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend for SIN-1; n = 11, 4, 3, 7, and 3 eyes for SNAP at five ascending doses, respectively; * or #P < 0.05; ** or ##P < 0.01; the number signs and the asterisks indicate comparisons made to vehicle for SIN-1 and SNAP, respectively.
Discussion
We have developed a platform to evaluate outflow facility and its time- and dose-dependent responses to pharmacologic interventions. Our platform covers a footprint of 1 m2 and has the capacity to evaluate 20 eyes simultaneously. Its compactness and throughput represent improvements over the available technologies to evaluate outflow facility in an ex vivo perfusion system. 
The technologies for ex vivo eye perfusion systems have been reviewed elsewhere23,38 and are summarized in the Table. A key recent advancement was the introduction of a commercial flow sensor by Sherwood et al.23; this flow sensor derives the flow rate by monitoring the temperature distribution around a heat source and along the flow path. Focusing on mouse eyes, the authors optimized their system for multilevel perfusion. Subjecting one eye to vehicle and the fellow eye to a prostaglandin EP4 agonist, they showed the drug increased outflow facility by an average of 56%. It is worth noting that the baseline outflow facility was not reported for each eye before treatment; nor was the time course of drug response reported in the publication.23 
Focusing on larger animal eyes, we optimized our system for time course measurements using each eye as its own pretreatment control. We used a flow sensor of the same class as Sherwood et al.,23 but with three orders of magnitude lower hydraulic resistance. Due to the insignificant pressure drop between the reservoir and the eye, a pressure transducer, as used by Sherwood et al.,23 was not used in our system. This further simplified the setup and reduced its footprint. For calf eyes, our data indicate that normalizing results with baseline flow rate increases the power to reveal drug effects (Supplementary Fig. S4). Also, measuring flow rate continuously before and after drug treatment yielded information on the time dependence of drug responses. 
Washout Phenomenon
The outflow facility in ex vivo perfused eyes is known to increase over time, with the exception of mouse and human eyes.17,18,21,32,33 In our perfusion studies, this washout phenomenon were also observed. Furthermore, we also observed eye-to-eye and day-to-day variations in the rate of washout. We quantified the influence of washout by computing the average time course of baseline-normalized flow rate from three to four vehicle-treated eyes in each experiment. The averaged time course for vehicle-treated eyes formed the basis for further normalization to reveal the effects of drugs. With this approach, we were able to resolve the time- and/or dose-dependent changes in outflow induced by Y-39983, S1P, JTE-013, ET-1, ambrisentan, SNAP, and SIN-1. Future work is needed to optimize the culture conditions to reduce washout in ex vivo perfused eyes. 
Outflow Facility Compared With Literature
For bovine eye perfusion, Johnson et al.17 reported baseline outflow facility of 1.2 ± 0.08 and 1.3 ± 0.1 μL/min/mm Hg from the same eye when perfused at 6 mm Hg and 15 mm Hg, respectively. Overby et al.18 reported 1.16 ± 0.08 μL/min/mm Hg when perfused at 15 mm Hg. Using a similar setup, Zhu et al.31 reported 2.16 ± 0.44 μL/min/mm Hg at 7 mm Hg and 0.90 ± 0.19 μL/min/mm Hg at 30 mm Hg from the same eyes. At 6 mm Hg, we measured 1.08 ± 0.32 and 1.01 ± 0.52 μL/min/mm Hg for calf and cattle eyes, respectively, which is comparable to the first two studies and lower than the third. For porcine eyes perfused at 10 and 15 mm Hg, the outflow facility was reported at 0.28 ± 0.0939 and 1.09 ± 0.007 μL/min/mm Hg,27 respectively. For porcine anterior chambers, the outflow facility has been reported as 0.128 ± 0.041.40 Our measurement of 0.33 ± 0.13 μL/min/mm Hg at 6 mm Hg is comparable to the first but different than the other two studies. 
The Effect of ET-1 on IOP In Vivo
Published results indicate that ET-1, when injected into monkey eyes, caused a prolonged reduction in IOP,41 although this was not reproduced in a subsequent study.42 In rabbit eyes, ET-1 was reported to cause a biphasic IOP response: an initial rise (0.5–2.0 hours) and a subsequent reduction that lasted for at least 5 days.43,44 The mechanism by which ET-1 induced a transient rise in IOP in rabbit eyes mainly involved ETA receptor activation.4547 Moreover, topically delivered ETA antagonist lowered IOP in monkey eyes with laser-induced ocular hypertension.48 Nevertheless, in healthy volunteers or glaucoma patients, intravenously delivered BQ-123 (ETA antagonist) or orally delivered bosentan (dual antagonist for ETA and ETB) had no effect on IOP.4951 The mechanism by which ET-1 induced a prolonged reduction in IOP is not completely understood, but may involve activation of the ETB receptor,45 reduction of aqueous humor secretion,44 increase in outflow facility,44 contraction of the ciliary muscle,41 the breakdown of the blood-aqueous barrier,43 and/or prostaglandin release.45 Despite the prevalence of in vivo data, studies are scarce using ex vivo organ perfusion. 
The Effect of ET-1 on Outflow Facility Ex Vivo
In perfusion studies using anterior segments of bovine eyes, ET-1 reduced outflow facility at 1 or 2 hours posttreatment by up to 57%.30 When applied to isolated tissue or cells from the TM or ciliary muscle, it induced a dose-dependent contraction.37,5254 However, the effects of ET-1 on ex vivo perfused whole eyes have not been previously reported to our knowledge. In our whole-eye perfusion studies, ET-1 induced a time-dependent reduction in outflow facility in three species by up to 80%. Similarly, S1P, which is known to increase cell stiffness and contraction,55 also reduced outflow facility in calf eyes, although it was much less in magnitude compared with that observed with ET-1. These data are consistent with the notion that increased contractility of cells in the outflow tract can reduce outflow facility.27,30,55,56 Nevertheless, we did not observe the phase of outflow facility increase following ET-1 treatment, as was seen in vivo in monkeys41 or rabbits.43,44 One potential explanation could be the duration of our studies were too short. 
Inhibition of ET-1 Response by NO Donors
Our data revealed that NO donors, SIN-1 and SNAP, inhibited the ocular hypertensive response induced by ET-1. This finding provides one potential mechanism for the IOP-lowering effect of NO donors.34 NO donors with various half-lives have been previously used to lower IOP in both in vivo and ex vivo perfusion models.34,35,5759 It is thought that the reductions in IOP or increases in outflow facility induced by NO donors are mainly due to the relaxation of TM/Schlemms's canal tissues. NO can activate soluble guanylate cyclase, resulting in the production of cGMP. Elevated cGMP can cause the activation of protein kinase G, which in turn can phosphorylate several key proteins, including those involved in ion channel regulation and smooth muscle tone regulation.60 NO can also nitrosylate proteins61 to directly modify cytoskeleton.62 Nevertheless, we found little effect of SIN-1 and SNAP on baseline flow rate in untreated eyes. This could suggest that the basal tone attributable to ET-1 signaling is minimal in enucleated eyes. Detailed understanding of the mechanism by which NO blocked ET-1 response and lowers IOP awaits further investigation. 
Limitations
First, in our perfusion system, the TM, aqueous plexus (porcine/bovine equivalent of Schlemm's canal), collector channels, and episcleral veins are intact, forming a functional conventional outflow system.63 However, it is devoid of blood circulation, aqueous humor secretion, episcleral venous pressure, and neuronal input from the central nervous system. Hence, the whole-eye perfusion system is perhaps limited to studying the conventional outflow tract. Second, the duration of culture of the whole eyes ex vivo was short. Based on histologic assessments, we have currently limited our study to within 18 hours of perfusion. For the evaluation of molecular mechanisms that act chronically or for long-term assessment of changes in outflow pathway, anterior segment culture may be an alternative.30 Third, the eyes were cultured at 24°C and at a single perfusion pressure of 6 mm Hg. Future work will improve temperature control and evaluate the effect of perfusion pressure on drug responses. 
In summary, we have engineered a compact and scalable ocular perfusion system. Using this system, we were able to shed light on the regulation of outflow facility by endothelin, NO, and S1P signaling pathways. We have demonstrated that this system is well suited for identification of drug targets that increase outflow facility. 
Acknowledgments
The authors thank Dan Stamer for technical suggestions, and Sam Shrestha, Christopher W. Wilson, Tom Vollmer, Ernie Hixon, Andrew Brady, and Aaron Bickel for technical assistance. 
Disclosure: E.H. Zhou, Novartis Institutes for BioMedical Research (E); M. Paolucci, Novartis Institutes for BioMedical Research (E); T.P. Dryja, Novartis Institutes for BioMedical Research (E); T. Manley, Novartis Institutes for BioMedical Research (E); C. Xiang, Novartis Institutes for BioMedical Research (E); D.S. Rice, Novartis Institutes for BioMedical Research (E); G. Prasanna, Novartis Institutes for BioMedical Research (E); A. Chen, Novartis Institutes for BioMedical Research (E) 
References
Kapetanakis VV, Chan MPY, Foster PJ, Cook DG, Owen CG, Rudnicka AR. Global variations and time trends in the prevalence of primary open angle glaucoma (POAG): a systematic review and meta-analysis. Br J Ophthalmol. 2016; 100: 86–93.
Heijl A, Leske MC, Bengtsson B, Hyman L, Bengtsson B, Hussein M; for the Early Manifest Glaucoma Trial Group. Reduction of intraocular pressure and glaucoma progression: results from the Early Manifest Glaucoma Trial. Arch Ophthalmol. 2002; 120: 1268–1279.
Leske MC, Heijl A, Hussein M, Bengtsson B, Hyman L, Komaroff E; for the Early Manifest Glaucoma Trial Group. Factors for glaucoma progression and the effect of treatment: the early manifest glaucoma trial. Arch Ophthalmol. 2003; 121: 48–56.
Pang IH, Clark AF. Outflow signaling mechanisms and new therapeutic strategies for the control of intraocular pressure. The Eye's Aqueous Humor. 2008; 62: 427.
Stamer WD, Acott TS. Current understanding of conventional outflow dysfunction in glaucoma. Curr Opin Ophthalmol. 2012; 23: 135–143.
Grant WM. Clinical measurements of aqueous outflow. AMA Arch Ophthalmol. 1951; 46: 113–131.
Grant WM. Experimental aqueous perfusion in enucleated human eyes. Arch Ophthalmol. 1963; 69: 783–801.
Prasanna G, Li B, Mogi M, Rice DS. Pharmacology of novel intraocular pressure-lowering targets that enhance conventional outflow facility: pitfalls, promises and what lies ahead? Eur J Pharmacol. 2016; 787: 47–56.
Rasmussen CA, Kaufman PL, Ritch R, Haque R, Brazzell RK, Vittitow JL. Latrunculin B reduces intraocular pressure in human ocular hypertension and primary open-angle glaucoma. Trans Vis Sci Tech. 2014; 3 (5): 1.
Garnock-Jones KP. Ripasudil: first global approval. Drugs. 2014; 74: 2211–2215.
Williams RD, Novack GD, Van Haarlem T, Kopczynski C. Ocular hypotensive effect of the rho kinase inhibitor AR-12286 in patients with glaucoma and ocular hypertension. Am J Ophthalmol. 2011; 152: 834–841.e1.
Tian B, Gabelt BT, Crosson CE, Kaufman PL. Effects of adenosine agonists on intraocular pressure and aqueous humor dynamics in cynomolgus monkeys. Exp Eye Res. 1997; 64: 979–989.
Myers JS, Sall KN, DuBiner H, et al. A dose-escalation study to evaluate the safety, tolerability, pharmacokinetics, and efficacy of 2 and 4 weeks of twice-daily ocular trabodenoson in adults with ocular hypertension or primary open-angle glaucoma. J Ocul Pharmacol Ther. 2016; 32: 555–562.
Bahler CK, Howell KG, Hann CR, Fautsch MP, Johnson DH. Prostaglandins increase trabecular meshwork outflow facility in cultured human anterior segments. Am J Ophthalmol. 2008; 145: 114–119.
Mao W, Tovar-Vidales T, Yorio T, Wordinger RJ, Clark AF. Perfusion-cultured bovine anterior segments as an ex vivo model for studying glucocorticoid-induced ocular hypertension and glaucoma. Invest Ophthalmol Vis Sci. 2011; 52: 8068–8075.
Chang JY, Stamer WD, Bertrand J, et al. Role of nitric oxide in murine conventional outflow physiology. Am J Physiol Cell Physiol. 2015; 309: C205–C214.
Johnson M, Chen A, Epstein DL, Kamm RD. The pressure and volume dependence of the rate of wash-out in the bovine eye. Curr Eye Res. 1991; 10: 373–375.
Overby D, Gong H, Qiu G, Freddo TF, Johnson M. The mechanism of increasing outflow facility during washout in the bovine eye. Invest Ophthalmol Vis Sci. 2002; 43: 3455–3464.
Millar JC, Clark AF, Pang IH. Assessment of aqueous humor dynamics in the mouse by a novel method of constant-flow infusion. Invest Ophthalmol Vis Sci. 2011; 52: 685–694.
Brubaker RF. The effect of intraocular pressure on conventional outflow resistance in the enucleated human eye. Invest Ophthalmol. 1975; 14: 286–292.
Erickson-Lamy K, Schroeder AM, Bassett-Chu S, Epstein DL. Absence of time-dependent facility increase (“washout”) in the perfused enucleated human eye. Invest Ophthalmol Vis Sci. 1990; 31: 2384–2388.
Camras LJ, Sufficool KE, Camras CB, Fan S, Liu H, Toris CB. Duration of anesthesia affects intraocular pressure, but not outflow facility in mice. Curr Eye Res. 2010; 35: 819–827.
Sherwood JM, Reina-Torres E, Bertrand JA, Rowe B, Overby DR. Measurement of outflow facility using iPerfusion. PLoS One. 2016; 11: e0150694.
Ethier CR, Ajersch P, Pirog R. An improved ocular perfusion system. Curr Eye Res. 1993; 12: 765–770.
Grant WM, Trotter RR. Tonographic measurements in enucleated eyes. AMA Arch Ophthalmol. 1955; 53: 191–200.
Honjo M, Tanihara H, Inatani M, et al. Effects of rho-associated protein kinase inhibitor Y-27632 on intraocular pressure and outflow facility. Invest Ophthalmol Vis Sci. 2001; 42: 137–144.
Rao PV, Deng PF, Kumar J, Epstein DL. Modulation of aqueous humor outflow facility by the Rho kinase-specific inhibitor Y-27632. Invest Ophthalmol Vis Sci. 2001; 42: 1029–1037.
Sumida GM, Stamer WD. S1P(2) receptor regulation of sphingosine-1-phosphate effects on conventional outflow physiology. Am J Physiol Cell Physiol. 2011; 300: C1164–C1171.
Mettu PS, Deng PF, Misra UK, Gawdi G, Epstein DL, Rao PV. Role of lysophospholipid growth factors in the modulation of aqueous humor outflow facility. Invest Ophthalmol Vis Sci. 2004; 45: 2263–2271.
Wiederholt M, Bielka S, Schweig F, Lutjen-Drecoll E, Lepple-Wienhues A. Regulation of outflow rate and resistance in the perfused anterior segment of the bovine eye. Exp Eye Res. 1995; 61: 223–234.
Zhu JY, Ye W, Wang T, Gong HY. Reversible changes in aqueous outflow facility, hydrodynamics, and morphology following acute intraocular pressure variation in bovine eyes. Chinese Med J (Engl). 2013; 126: 1451–1457.
Gong H, Freddo TF. The washout phenomenon in aqueous outflow—why does it matter? Exp Eye Res. 2009; 88: 729–737.
Lei Y, Overby DR, Boussommier-Calleja A, Stamer WD, Ethier CR. Outflow physiology of the mouse eye: pressure dependence and washout. Invest Ophthalmol Vis Sci. 2011; 52: 1865–1871.
Carreiro S, Anderson S, Gukasyan HJ, Krauss A, Prasanna G. Correlation of in vitro and in vivo kinetics of nitric oxide donors in ocular tissues. J Ocul Pharmacol Ther. 2009; 25: 105–112.
Ellis DZ, Dismuke WM, Chokshi BM. Characterization of soluble guanylate cyclase in NO-induced increases in aqueous humor outflow facility and in the trabecular meshwork. Invest Ophthalmol Vis Sci. 2009; 50: 1808–1813.
Wiederholt M, Sturm A, Lepple-Wienhues A. Relaxation of trabecular meshwork and ciliary muscle by release of nitric oxide. Invest Ophthalmol Vis Sci. 1994; 35: 2515–2520.
Dismuke WM, Liang J, Overby DR, Stamer WD. Concentration-related effects of nitric oxide and endothelin-1 on human trabecular meshwork cell contractility. Exp Eye Res. 2014; 120: 28–35.
Johnson M. What controls aqueous humour outflow resistance? Exp Eye Res. 2006; 82: 545–557.
Wagner JA, Edwards A, Schuman JS. Characterization of uveoscleral outflow in enucleated porcine eyes perfused under constant pressure. Invest Ophthalmol Vis Sci. 2004; 45: 3203–3206.
Jacobi PC, Dietlein TS, Krieglstein GK. Effects of Er:YAG laser trabecular ablation on outflow facility in cadaver porcine eyes. Graefes Arch Clin Exp Ophthalmol. 1996; 234: S204–S208.
Erickson-Lamy K, Korbmacher C, Schuman JS, Nathanson JA. Effect of endothelin on outflow facility and accommodation in the monkey eye in vivo. Invest Ophthalmol Vis Sci. 1991; 32: 492–495.
Millar JC, Gabelt BT, Hubbard WC, Kiland JA, Kaufman PL. Endothelin-1 effects on aqueous humor dynamics in monkeys. Acta Ophthalmol Scand 1998; 76: 663–667.
MacCumber MW, Jampel HD, Snyder SH. Ocular effects of the endothelins. Abundant peptides in the eye. Arch Ophthalmol. 1991; 109: 705–709.
Taniguchi T, Okada K, Haque MS, Sugiyama K, Kitazawa Y. Effects of endothelin-1 on intraocular pressure and aqueous humor dynamics in the rabbit eye. Curr Eye Res. 1994; 13: 461–464.
Sugiyama K, Haque MS, Okada K, Taniguchi T, Kitazawa Y. Intraocular pressure response to intravitreal injection of endothelin-1 and the mediatory role of ETA receptor, ETB receptor, and cyclooxygenase products in rabbits. Curr Eye Res. 1995; 14: 479–486.
Hollo G, Lakatos P, Vargha P. Immediate increase in aqueous humour endothelin 1 concentration and intra-ocular pressure after argon laser trabeculoplasty in the rabbit. Ophthalmologica. 2000; 214: 292–295.
Hollo G, Kothy P, Lakatos P, Vargha P. Endothelin-A receptor antagonist BQ-485 protects against intraocular pressure spike induced by laser trabeculoplasty in the rabbit. Ophthalmologica. 2002; 216: 459–462.
Wang RF, Podos SM, Serle JB, Baltatu OC. Effect of SPP 301, an endothelin antagonist, on intraocular pressure in glaucomatous monkey eyes. Curr Eye Res. 2011; 36: 41–46.
Fuchsjager-Mayrl G, Luksch A, Malec M, Polska E, Wolzt M, Schmetterer L. Role of endothelin-1 in choroidal blood flow regulation during isometric exercise in healthy humans. Invest Ophthalmol Vis Sci. 2003; 44: 728–733.
Polak K, Luksch A, Frank B, Jandrasits K, Polska E, Schmetterer L. Regulation of human retinal blood flow by endothelin-1. Exp Eye Res. 2003; 76: 633–640.
Resch H, Karl K, Weigert G, et al. Effect of dual endothelin receptor blockade on ocular blood flow in patients with glaucoma and healthy subjects. Invest Ophthalmol Vis Sci. 2009; 50: 358–363.
Cellini M, Versura P, Trere D, Campos EC. Effects of endothelin-1 on human trabecular meshwork cell contraction. an in vitro cell culture model. Ophthalmic Res. 2005; 37: 43–49.
Cellini M, Versura P, Zamparini E, Bendo E, Campos EC. Effects of endothelin-1 and flunarizine on human trabecular meshwork cell contraction. Exp Biol Med (Maywood). 2006; 231: 1081–1084.
Rosenthal R, Choritz L, Zorn R, et al. Endothelin receptor B in trabecular meshwork. Exp Eye Res. 2007; 85: 482–491.
Zhou EH, Krishnan R, Stamer WD, et al. Mechanical responsiveness of the endothelial cell of Schlemm's canal: scope, variability and its potential role in controlling aqueous humour outflow. J R Soc Interface. 2012; 9: 1144–1155.
Overby DR, Zhou EH, Vargas-Pinto R, et al. Altered mechanobiology of Schlemm's canal endothelial cells in glaucoma. Proc Natl Acad Sci U S A. 2014; 111: 13876–13881.
Cavet ME, Vollmer TR, Harrington KL, VanDerMeid K, Richardson ME. Regulation of endothelin-1-induced trabecular meshwork cell contractility by latanoprostene bunod. Invest Ophthalmol Vis Sci. 2015; 56: 4108–4116.
Krauss AH, Impagnatiello F, Toris CB, et al. Ocular hypotensive activity of BOL-303259-X, a nitric oxide donating prostaglandin F2alpha agonist, in preclinical models. Exp Eye Res. 2011; 93: 250–255.
Heyne GW, Kiland JA, Kaufman PL, Gabelt BT. Effect of nitric oxide on anterior segment physiology in monkeys. Invest Ophthalmol Vis Sci. 2013; 54: 5103–5110.
Lincoln TM, Dey N, Sellak H. Invited review: cGMP-dependent protein kinase signaling mechanisms in smooth muscle: from the regulation of tone to gene expression. J Appl Physiol (1985). 2001; 91: 1421–1430.
Hess DT, Matsumoto A, Kim SO, Marshall HE, Stamler JS. Protein S-nitrosylation: purview and parameters. Nat Rev Mol Cell Biol. 2005; 6: 150–166.
Dalle-Donne I, Milzani A, Giustarini D, Di Simplicio P, Colombo R, Rossi R. S-NO-actin: S-nitrosylation kinetics and the effect on isolated vascular smooth muscle. J Muscle Res Cell Motil. 2000; 21: 171–181.
Pizzirani S, Gong H. Functional anatomy of the outflow facilities. Vet Clin North Am Small Anim Pract. 2015; 45: 1101–1126, v.
Figure 1
 
The setup and calibration of the perfusion system. (A) A schematic showing the working principle. DAQ, data acquisition. (B) A drawing of the system. (C) To calibrate the system in the absence of any eye, we varied pressure as a function of time (gray trace) by moving the reservoir vertically (pressure was set to zero where flow rate was zero and calculated from ρgH [see Methods]). The resultant changes in flow rate (blue trace) were measured using the flow sensor. For clarity, only one representative example is shown. (D) Flow rate was proportional to pressure, the slope being the intrinsic facility in the absence of any eye. Each set of unique markers, fitted with a straight line, represents raw data points for one sensor (n = 20 sensors). Note that when pressure goes negative, so does flow rate.
Figure 1
 
The setup and calibration of the perfusion system. (A) A schematic showing the working principle. DAQ, data acquisition. (B) A drawing of the system. (C) To calibrate the system in the absence of any eye, we varied pressure as a function of time (gray trace) by moving the reservoir vertically (pressure was set to zero where flow rate was zero and calculated from ρgH [see Methods]). The resultant changes in flow rate (blue trace) were measured using the flow sensor. For clarity, only one representative example is shown. (D) Flow rate was proportional to pressure, the slope being the intrinsic facility in the absence of any eye. Each set of unique markers, fitted with a straight line, represents raw data points for one sensor (n = 20 sensors). Note that when pressure goes negative, so does flow rate.
Figure 2
 
The process of data normalization is illustrated using three pairs of eyes treated with 0.1 μM ET-1 or vehicle as examples. In (AD), each pair of eyes shares one color; the solid lines are for the vehicle-treated eyes and the dashed lines for ET-1-treated eyes. For each eye, raw flow rates (A) were first normalized to pretreatment baselines to yield baseline-normalized flow (B). In an unpaired paradigm assuming each eye is independent, a second normalization to the average of vehicle control was carried out (C, E). By contrast, in a paired paradigm, a second normalization to paired vehicle control was carried out (D, F). Both paradigms yielded nearly identical treatment responses (E, F; mean ± SD). n = 7 pairs of eyes.
Figure 2
 
The process of data normalization is illustrated using three pairs of eyes treated with 0.1 μM ET-1 or vehicle as examples. In (AD), each pair of eyes shares one color; the solid lines are for the vehicle-treated eyes and the dashed lines for ET-1-treated eyes. For each eye, raw flow rates (A) were first normalized to pretreatment baselines to yield baseline-normalized flow (B). In an unpaired paradigm assuming each eye is independent, a second normalization to the average of vehicle control was carried out (C, E). By contrast, in a paired paradigm, a second normalization to paired vehicle control was carried out (D, F). Both paradigms yielded nearly identical treatment responses (E, F; mean ± SD). n = 7 pairs of eyes.
Figure 3
 
Outflow characteristics of calf, cattle, and pig eyes perfused at 6 mm Hg. (A, B) The distribution of baseline flow rate was shown for calf (A) and pig eyes (B). (C) The average baseline flow rate was shown for calf (n = 377), cattle (n = 33; including adult cows and bulls), and pig eyes (n = 51). (D) The washout phenomenon is present in calf eyes (n = 67) and cattle eyes (n = 6) that received a vehicle treatment at time 0 (indicated by an arrow). Data are shown as mean ± SD; ns, P > 0.05; **P < 0.01. (E) The rate of washout was computed as the slope of flow rate against time, divided by the pressure (6 mm Hg). It exhibited a transient elevation after vehicle treatment, followed by a gradual reduction over time. In (D, E), data are shown as mean ± SD. In (E), only open symbols represent statistical difference from 0 (P < 0.05).
Figure 3
 
Outflow characteristics of calf, cattle, and pig eyes perfused at 6 mm Hg. (A, B) The distribution of baseline flow rate was shown for calf (A) and pig eyes (B). (C) The average baseline flow rate was shown for calf (n = 377), cattle (n = 33; including adult cows and bulls), and pig eyes (n = 51). (D) The washout phenomenon is present in calf eyes (n = 67) and cattle eyes (n = 6) that received a vehicle treatment at time 0 (indicated by an arrow). Data are shown as mean ± SD; ns, P > 0.05; **P < 0.01. (E) The rate of washout was computed as the slope of flow rate against time, divided by the pressure (6 mm Hg). It exhibited a transient elevation after vehicle treatment, followed by a gradual reduction over time. In (D, E), data are shown as mean ± SD. In (E), only open symbols represent statistical difference from 0 (P < 0.05).
Figure 4
 
Tissue remained healthy after 18 hours of perfusion (approximately 24 hours postmortem). Calf eyes were received approximately 4 hours postmortem and perfusion was started within 2 hours. (A, B) H&E staining is shown for a newly received eye without any perfusion (A) and an eye perfused for 18 hours (B). (C) Live-dead staining of the TM is shown for an eye perfused for 18 hours. Individual fluorescence channels are shown for EthD-1 (indicating dead cells, C1), calcein AM (indicating live cells, C2), and Hoechst 33342 (all cells, C3). The arrowheads point to aqueous plexus and the arrows point to TM. Images are representative of n = 2 eyes for (A, C), and n = 4 eyes for (B).
Figure 4
 
Tissue remained healthy after 18 hours of perfusion (approximately 24 hours postmortem). Calf eyes were received approximately 4 hours postmortem and perfusion was started within 2 hours. (A, B) H&E staining is shown for a newly received eye without any perfusion (A) and an eye perfused for 18 hours (B). (C) Live-dead staining of the TM is shown for an eye perfused for 18 hours. Individual fluorescence channels are shown for EthD-1 (indicating dead cells, C1), calcein AM (indicating live cells, C2), and Hoechst 33342 (all cells, C3). The arrowheads point to aqueous plexus and the arrows point to TM. Images are representative of n = 2 eyes for (A, C), and n = 4 eyes for (B).
Figure 5
 
A bolus injection of 100 μM S1P reduced outflow facility in calf eyes pretreated with vehicle but not in those pretreated with 100 μM JTE-013, an S1P2 antagonist. The left arrow indicates the injection of vehicle or JTE-013, and the right arrow indicates the injection of S1P. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; P < 0.01 comparing the normalized flow rates when S1P response was maximum (t = 180 minutes).
Figure 5
 
A bolus injection of 100 μM S1P reduced outflow facility in calf eyes pretreated with vehicle but not in those pretreated with 100 μM JTE-013, an S1P2 antagonist. The left arrow indicates the injection of vehicle or JTE-013, and the right arrow indicates the injection of S1P. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; P < 0.01 comparing the normalized flow rates when S1P response was maximum (t = 180 minutes).
Figure 6
 
A bolus injection of Y-39983 (a ROCK inhibitor) at time 0 induced time- and dose-dependent increase in outflow in calf eyes perfused at 6 mm Hg. (A) For each eye, the flow rate was first normalized to the baseline before treatment, and second normalized to the average time-matched vehicle controls tested on the same day. For clarity, not all error bars are shown. (B) Dose response of Y-39983 in increasing outflow facility at 180 minutes of treatment. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; *P < 0.05; **P < 0.01.
Figure 6
 
A bolus injection of Y-39983 (a ROCK inhibitor) at time 0 induced time- and dose-dependent increase in outflow in calf eyes perfused at 6 mm Hg. (A) For each eye, the flow rate was first normalized to the baseline before treatment, and second normalized to the average time-matched vehicle controls tested on the same day. For clarity, not all error bars are shown. (B) Dose response of Y-39983 in increasing outflow facility at 180 minutes of treatment. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; *P < 0.05; **P < 0.01.
Figure 7
 
A bolus injection of ET-1 induced time- and dose-dependent decrease in outflow in calf eyes perfused at 6 mm Hg. (A) For each eye, the flow rate was first normalized to the baseline before treatment, and second normalized to the average time-matched vehicle controls tested on the same day. (B) Dose response of ET-1 in reducing outflow facility at 60 minutes of treatment. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; *P < 0.05; **P < 0.01.
Figure 7
 
A bolus injection of ET-1 induced time- and dose-dependent decrease in outflow in calf eyes perfused at 6 mm Hg. (A) For each eye, the flow rate was first normalized to the baseline before treatment, and second normalized to the average time-matched vehicle controls tested on the same day. (B) Dose response of ET-1 in reducing outflow facility at 60 minutes of treatment. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend; *P < 0.05; **P < 0.01.
Figure 8
 
A bolus injection of 0.1 μM ET-1 induced transient decrease in outflow facility in calf (A), adult bovine (B), and porcine eyes (C). In all cases, the decrease could be inhibited by pretreatment of the eye with 10 μM ambrisentan. In each panel, the left arrow indicates the injection of vehicle or ambrisentan, and the right arrow indicates the injection of ET-1. Data are shown as mean ± SD; sample sizes (n) are indicated as the numbers in parentheses; P < 0.01 comparing the normalized flow between ambrisentan-treated eyes and vehicle-treated eyes at the time of peak ET-1 response.
Figure 8
 
A bolus injection of 0.1 μM ET-1 induced transient decrease in outflow facility in calf (A), adult bovine (B), and porcine eyes (C). In all cases, the decrease could be inhibited by pretreatment of the eye with 10 μM ambrisentan. In each panel, the left arrow indicates the injection of vehicle or ambrisentan, and the right arrow indicates the injection of ET-1. Data are shown as mean ± SD; sample sizes (n) are indicated as the numbers in parentheses; P < 0.01 comparing the normalized flow between ambrisentan-treated eyes and vehicle-treated eyes at the time of peak ET-1 response.
Figure 9
 
Pretreatment of calf eyes with SIN-1 or SNAP dose-dependently inhibited ET-1 response. (A) Flow rate in each eye was normalized to that before ET-1 injection. Similar observation was made with another NO donor, SNAP. (B) Dose response for SIN-1 and SNAP in inhibiting ET-1 response. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend for SIN-1; n = 11, 4, 3, 7, and 3 eyes for SNAP at five ascending doses, respectively; * or #P < 0.05; ** or ##P < 0.01; the number signs and the asterisks indicate comparisons made to vehicle for SIN-1 and SNAP, respectively.
Figure 9
 
Pretreatment of calf eyes with SIN-1 or SNAP dose-dependently inhibited ET-1 response. (A) Flow rate in each eye was normalized to that before ET-1 injection. Similar observation was made with another NO donor, SNAP. (B) Dose response for SIN-1 and SNAP in inhibiting ET-1 response. Data are shown as mean ± SD; sample sizes (n) are indicated in the legend for SIN-1; n = 11, 4, 3, 7, and 3 eyes for SNAP at five ascending doses, respectively; * or #P < 0.05; ** or ##P < 0.01; the number signs and the asterisks indicate comparisons made to vehicle for SIN-1 and SNAP, respectively.
Table
 
Summary of Ex Vivo Perfusion Systems for Studying Outflow Facility
Table
 
Summary of Ex Vivo Perfusion Systems for Studying Outflow Facility
Supplement 1
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×