variations in instrument orientation means that extensive practice and operator experience are needed to use the Tono-Pen in rats. Even with experience, and with light general anesthesia, some individuals have reported that many individual measurement attempts are still required to get IOP readings (Pease et al., 2006). While it is possible that a smaller post and tip might make this instrument easier to use, this modification has not yet been successfully achieved.

Other researchers have adapted the Goldmann tonometer for measuring IOP in rats. This is done by increasing the angle of the prisms within the tip to account for the increased curvature of the cornea and modifying the tonometer strain gauge to accommodate the reduced corneal rigidity (Cohan and Bohr, 2001a, b; Grozdanic et al., 2003a). With the tonometer mounted on a clinical biomicroscope, one investigator holds the animal while another obtains the pressure readings. Calibration studies in cannulated eyes have indicated a good correlation of readings with this modified instrument against actual transducer pressures. Disadvantages include the necessity of obtaining a modified instrument from the manufacturer and the fact that more than one person is required to measure IOP.

The pneumatonometer has also been used for monitoring IOP in rats (Shareef et al., 1995; Sawada and Neufeld, 1999). Although one can obtain recordable pressure readings in rat eyes with this instrument, it is difficult to calibrate in these small eyes, and it must be used with a general anesthetic.

Over the past several years, a new device for measuring IOP in rats has gradually become available based on the principle of rebound tonometry (Kontiola, 1996, 2000; Kontiola et al., 2001). With this, activation of a solenoid propels a lightweight magnetized probe against the cornea, and IOP is then determined by the rate of its deceleration. Prototype instruments have been used to measure IOP in rats (Kontiola et al., 2001; Goldblum et al., 2002), mice (Danias et al., 2003; Filippopoulos et al., 2006; Kim et al., 2007; Morris et al., 2006; Nissirios et al., 2007), and humans (Kontiola and Puska, 2004; Sahin et al., 2007a, b; Chui et al., 2008).

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This instrument is now available commercially as the TonoLab (Colonial Medical Supply, Franconia, NH), designed specifically for rodents. Two studies have reported a good correlation of readings with this instrument against a pressure transducer in rat and mouse eyes (Wang et al., 2005; Pease et al., 2006). One of these reports also demonstrated methods for using it in awake animals (Wang et al., 2005) while the other showed that calibration of the TonoLab compared favorably with that of the Tono-Pen in rat eyes with elevated IOP as well as in eyes with experimental glaucoma (Pease et al., 2006).

We have found that the advantages of this instrument are that it is relatively easy to use and can detect circadian fluctuation of IOP in awake rats (Jia et al., 2006). However, we noted that readings with this instrument over time were more variable than with the Tono-Pen. In addition, our calibrations indicate that, in Brown Norway rats, readings with the TonoLab tend to underestimate the actual IOP and flatten out below an actual IOP of 20 mmHg, suggesting that instrument readings below 10 mmHg will be difficult to interpret (Fig. 3b). In rat eyes with experimental glaucoma, we found that the TonoLab, unlike the Tono-Pen, was not able to detect significant pressure elevations in eyes with minimal optic nerve damage, most likely due to the greater variability of readings with this instrument (Jia et al., 2006).

The Tono-Pen and the TonoLab are currently the most popular tonometers used in rat models. However, both require experience, and researchers are strongly encouraged to calibrate the instrument in their animals of interest to understand its behavior prior to using it in experimental studies. We still need an instrument that allows sensitive, accurate measurement of mild pressure elevations but does not require extensive training, experience, and practice.

General considerations for measuring IOP in rats

A reliable, unbiased method of measuring IOP is indispensable for working with any glaucoma model. Because IOP fluctuation is common in glaucoma and animal models of glaucoma,

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pressure measurements must be noninvasive and repeatable to provide sufficient documentation of the IOP that the eye (and the ONH) experiences during the experimental period.

While it is possible to monitor IOP repeatedly over time using a general anesthetic, measurements performed on a daily basis can result in progressive weight loss and even a reduction in IOP, presumably due to cumulative side effects of the general anesthetics (Moore et al., 1995). More importantly, general anesthetics will cause variable lowering of IOP while active, resulting in IOP measurements that are artifactually low and not reflective of the IOP actually experienced by the eye (Jia et al., 2000a). Because of these problems, and because the animal will be awake for nearly all chronic experiments, we advocate measuring IOP in awake animals, using only topical anesthesia. Fortunately, the Brown Norway rat has proven to be docile and easy to handle, and it is possible to obtain meaningful IOP measurements in these awake animals.

Obtaining an accurate assessment of IOP also requires understanding the normal, daily circadian fluctuations of IOP. When housed in a standard 12-h light:dark cycle, IOP is significantly lower in the light phase and higher in the dark (Moore et al., 1996). This appears to be a true circadian phenomenon since the IOP cycle can be reversed by inverting the light and dark phases and probably results from fluctuations in the rate of aqueous humor production (Gregory et al., 1985; Mclaren et al., 1996).

When superimposed on experimental obstruction of aqueous outflow, this circadian fluctuation can become greatly exaggerated. Over 30% of eyes with experimental outflow obstruction develop a significant IOP elevation over the fellow control eyes only in the dark phase, all of which have significant optic nerve injury (Jia et al., 2000b). In this situation, if pressure were measured only in the light phase, this nerve injury would not be explained by the recorded IOP history.

Simply measuring IOP at the same time of day does not adequately account for these problems. Using pressures measured in the nonaffected fellow eyes as a way of accounting for fluctuations is also not sufficient since IOP fluctuations

following outflow obstruction can be random and highly variable.

These results suggest that, when animals with experimental outflow obstruction are housed in standard lighting conditions, IOP must be monitored in both the dark and light phases. This approach is cumbersome, and the resulting large IOP fluctuations may make it difficult to correlate pressure history with optic nerve damage. For these reasons, we feel that it is important to minimize these underlying circadian IOP fluctuations.

We have accomplished this by placing animals in a low-level constant light environment, which Rowland, studying rabbits, previously found reduces circadian IOP fluctuation (Rowland et al., 1981). We, and other laboratories, have found that, when animals are housed in constant fluorescent light conditions (40–90 lux), IOP in normal eyes will consistently measure between 27 and 28 mmHg by the Tono-Pen, regardless of the time of day. This is in contrast to light and dark pressures of 19–21 and 28–30 mmHg, when in standard lighting conditions (Moore et al., 1996; Morrison et al., 2005; Pang et al., 2005b).

In eyes with experimental aqueous outflow obstruction, IOP in constant light becomes significantly elevated over that in the fellow eyes. However, unlike a standard light:dark cycle, where the fluctuation between light and dark phases in some animals can be markedly accentuated (Jia et al., 2000b), circadian variation is not observed when animals are placed in constant light (Morrison et al., 2005). It should be emphasized that the constant light paradigm described here does not eliminate all IOP fluctuations since significant pressure variation is common to human glaucoma and glaucoma models that rely on aqueous humor outflow obstruction (Piltz et al., 1985; Asrani et al., 2000; Pena et al., 2001; Nouri-Mahdavi et al., 2004a). It reduces the overall extent of pressure fluctuation by limiting circadian variations in aqueous humor production, a significant source of marked, dark-cycle pressure elevations (Smith and Gregory, 1989). It also frees the experimenter of the need to measure IOP by a rigid schedule and monitor both lightand dark-phase pressures. The reliability of this approach has been repeatedly

demonstrated by the close correlations it provides between mean IOP measurements and many different measures of injury, such as extent of optic nerve damage, RGC loss, and measures of altered cellular function in both tissues (Jia et al., 2000b; Johnson et al., 2000, 2006, 2007; Schlamp et al., 2001; Ahmed et al., 2004; Fortune et al., 2004; Morrison et al., 2005; Pang et al., 2005a).

We have observed normal Brown Norway rats in constant light for as long as 12 months and found that the pressure effects are maintained throughout the entire period. Importantly, the retinas were histologically normal, and retinal nuclear layer thickness measurements performed in collaboration with Dr. Matt LaVail were indistinguishable from retinas of age-matched animals simultaneously housed under standard light:dark conditions for the same time period (Morrison et al., 2005). It thus appears that the low level of constant light in our model does not induce photoreceptor toxicity in these pigmented rats (LaVail, 1980).

Assessing optic nerve and retina damage

Assessing damage in any glaucoma model can be done by examining either the optic nerve or the retina. It is critical that this provides an objective picture of either injury or cellular dropout in order to understand the effects of elevated IOP. This is also critical for performing reliable testing of potential neuroprotective compounds, which depend on careful documentation of IOP and damage in both experimental and control groups.

Nerve damage can be measured by evaluating a single cross section of the optic nerve, which contains the entire output of the RGCs. At the light microscopic (LM) level, standard staining of plastic-embedded sections readily allows identification of normal axons by staining the myelin sheaths. Semiautomated image analysis methods can count and determine axon density within specified areas (Quigley et al., 1987). These are then used to calculate entire nerve counts by measuring the total area of the nerve cross section. In experimental models, damage can be determined by comparing these nerve counts to

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counts in the normal, fellow optic nerves. Although some researchers will determine injury by comparing axon density alone, this is subject to error since nerve damage in these models is not uniform and the individual nerve areas used to count axons may not faithfully capture the true extent of axon loss.

An advantage of this semiautomated optic nerve analysis is that it requires relatively few manipulations and is objective. A disadvantage of this method is that it depends heavily on the quality of tissue fixation and, as discussed below, can produce an underestimate of actual axon counts.

Optic nerve axon counts can also be determined in cross sections by transmission electron microscopy (TEM) (Chauhan et al., 2002; Cepurna et al., 2005). Here, tissue sections from experimental and control nerves are photographed in a random, standardized fashion, and axon counts are performed manually. At this level, the axons can be readily identified by their myelin sheaths and contained microtubules.

Relatively few comparisons of this TEM method with the semiautomated LM approach detailed above have been performed, but available evidence suggests that they do not supply identical results. Two reports using the LM method in Wistar rats found total counts between 79.8 and 87.3 thousand axons (Ricci et al., 1988; Levkovitch-Verbin et al., 2002b). In contrast, studies in the same species of similar age using TEM counting methods reported 102.2 and 105.8 thousand axons (Fukuda et al., 1982; Sugimoto et al., 1984).

A direct comparison of these counting methods in the same optic nerves has provided a similar result (Cepurna et al., 2005; Morrison et al., 2005). Manual axon counts of TEM photographs encompassing approximately 65% of the optic nerve cross section in normal Brown Norway rat eyes resulted in a mean total of 126.477.8 (7SD) thousand axons. By contrast, an LM method using an IBAS image analysis system resulted in a mean total of 86.8711.5 thousand axons. This difference was statistically significant, with the LM method undercounting axons by a mean of 39.6719.4 thousand axons, or 31715% of the TEM count. These underestimates ranged from 19 to 43%.

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The precise reasons for this discrepancy are unknown. However, because TEM allows positive identification of all myelinated axons and nearly 65% of all axons were manually counted, there is a relatively less chance that the TEM method either overor undercounted axons. By contrast, the large underestimate of axons by the LM method could have resulted from axons that were just at or smaller than the limit of resolution for the light microscope and got ignored by the software of the image analysis system.

Unfortunately, the extent of this underestimation by the LM method was variable as well as large, and one cannot simply extrapolate between these methods. This means that the difference was due to nonuniform errors, such as tissue fixation and staining, despite the use of perfusion fixation and obtaining sections for each technique from the same block of tissue. These uncertainties and potential problems must always be kept in mind whenever using the LM method for axonal counting to determine optic nerve damage.

Another way to assess optic nerve damage is to develop a qualitative LM grading scale for optic nerve degeneration (Jia et al., 2000b). This avoids the potential pitfalls of LM axon counting noted above and is more rapid than the TEM method. This approach depends on recognizing axonal degeneration at the LM level by the appearance of swollen axons that lack apparent axoplasm and dark axons due to collapsed myelin sheaths. The extent of injury is then graded, based on a stereotypical pattern of injury that we have observed in rats with elevated IOP due to aqueous humor outflow obstruction (Table 1). In this system, each optic nerve cross section is assigned a grade, based on a 5-point scale, ranging from

Table 1. LM grading system for optic nerve damage due to elevated IOP due to aqueous humor outflow obstruction

grade 1 (normal) to 5 (degeneration involving the entire nerve cross section).

Other investigators, working with albino animals and another method of aqueous outflow obstruction, have developed and used similar qualitative damage scales (Levkovitch-Verbin et al., 2002a, b). Another group, working with chronic ischemia from endothelin administration, has described another grading scale (Chauhan et al., 2006), although it differs considerably from ours due to the different pattern of injury produced by endothelin.

To support the reliability of our grading system, a comparison to actual nerve counts by TEM in the same nerves reveals a linear relationship between the two methods, representing approximately 12,000 axons per grade (Morrison et al., 2005). This comparison also showed that some eyes with mild nerve injury (grade 2–2.5) had axon counts that were within the normal range of variation in total axons, which can be as high as 20%. This suggests that this grading system is more sensitive to mild damage than either TEM or LM counting methods.

Other investigators choose to evaluate damage by documenting loss of RGCs. This usually involves placing a tracer, such as fluorogold, into the superior colliculus or on the stump of a severed optic nerve. The tracer, which is then transported by retrograde axoplasmic flow, will accumulate in RGCs, which can then be counted, usually in flat mount preparations. Generally, these counts are performed systematically in representative regions of the retina and RGC losses determined as a reduction of RGC density or by calculating total RGCs based on the total retinal area.

Because this technique relies on axonal transport, it allows the examiner to assess viable cells. On the other hand, it depends on uniform uptake of the tracer by axons, which may not always happen and can result in an underestimate of actual RGC. It also relies on sampling several regions of the retina, which must be standardized and consistent, since RGC density varies with different regions of the retina in normal eyes. This increases the chance that regional injury may not be adequately or reproducibly detected. Automated methods of counting all labeled RGCs over