Open Access
Glaucoma  |   July 2018
Influence of the Water-Drinking Test on Intraocular Pressure, Schlemm's Canal, and Autonomic Nervous System Activity
Author Affiliations & Notes
  • Wei Chen
    Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • Liugui Chen
    Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • Zhiqi Chen
    Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • Yan Xiang
    Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • Shiliang Liu
    Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • Hong Zhang
    Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • Junming Wang
    Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
  • Correspondence: Junming Wang, Department of Ophthalmology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, Hubei 430030; China; eyedrwjm@163.com
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 3232-3238. doi:10.1167/iovs.18-23909
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      Wei Chen, Liugui Chen, Zhiqi Chen, Yan Xiang, Shiliang Liu, Hong Zhang, Junming Wang; Influence of the Water-Drinking Test on Intraocular Pressure, Schlemm's Canal, and Autonomic Nervous System Activity. Invest. Ophthalmol. Vis. Sci. 2018;59(8):3232-3238. doi: 10.1167/iovs.18-23909.

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

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Abstract

Purpose: To assess changes in Schlemm's canal (SC), intraocular pressure (IOP), and autonomic nervous system activity in healthy individuals after performing the water-drinking test (WDT).

Methods: The SC area (SCAR), trabecular meshwork (TM) thickness, IOP, high frequency (HF) of heart rate variability (HRV), heart rate (HR), and systolic (SBP) and diastolic blood pressure (DBP) were measured in 22 young healthy participants before and after the WDT, which involved drinking a 1-liter water load in 5 minutes.The SC and TM profiles were captured using a Spectralis optical coherence tomography device (anterior segment module). HF was recorded using Kubios HRV Premium software to evaluate parasympathetic nervous system activity.

Results: Compared with baseline values, IOP increased significantly (14.9 ± 2.7 mm Hg vs. 18.4 ± 3.3 mm Hg; P < 0.001), whereas HF (1587 ± 930 ms2 vs. 2193 ± 863 ms2; P < 0.001), mean SCAR (6521 ± 1360 μm2 vs. 5180 ± 1455 μm2; P < 0.001), and HR (69 ± 9.7 beats/min vs. 63 ± 8.9 beats/min; P < 0.001) values decreased significantly by 15 minutes after water-loading. Least significant difference pairwise comparison revealed significant fluctuations of all parameters (SCAR, IOP, HF, and HR) at 15 minutes and their recovery at 30-minutes post-WDT. TM thickness, SBP, and DBP post-WDT did not differ significantly. The increase in IOP (r = −0.4047; P = 0.010) and HF (r = −0.386; P = 0.014) correlated significantly with the decrease in SCAR.

Conclusions: The WDT may cause parasympathetic nervous system stimulation, leading to the collapse of SC, which leads to increased IOP.

Achieving target intraocular pressure (IOP) is reported to assist in halting the progression of glaucoma optic neuropathy.1,2 Hitherto, glaucoma management has mostly been based on single IOP measurements obtained during routine office visits, even though IOP measurements of most glaucoma patients are higher during the nocturnal period, according to 24-hour diurnal tension curves. The diurnal tension curve is useful for discovering the IOP peak, but it is not always feasible to implement in routine practice.3 
The water-drinking test (WDT) was first described as a provocation test for glaucoma in the 1960s.4 However, it was associated with markedly unacceptable false-positive and false-negative results.5 In the 1980s, Armaly et al.6 found a good correlation between the IOP in the WDT and that in the 24-hour IOP curve. Consequently, the concepts about the WDT have changed; it is no longer used as a diagnostic test but rather as a useful tool to assess IOP peaks. 
A markedly increased IOP after the WDT has been described in many studies of glaucoma patients and normal controls, but the underlying mechanism remains unclear.710 We have previously shown that an IOP decrease was accompanied by enlargement of Schlemm's canal (SC) and enhancement of sympathetic nervous system activity after aerobic exercise.11 In this study, we therefore investigated whether changes in SC and autonomic nervous system activity occur after the WDT, in an exploration of the physiologic basis of peri-WDT IOP fluctuations. 
Materials and Methods
Subjects
A total of 25 healthy staff members of the Tongji Hospital in Wuhan, Hubei Province, China, were enrolled in this study from June to December 2017. All the participants underwent an ophthalmic examination. Either of their eyes was randomly included in the study. 
Inclusion criteria were as follows: IOP <21 mm Hg and normal ophthalmoscopic appearance of the optic nerve (cup-to-disc ratio, <0.5 in both eyes; cup-to disc ratio asymmetry, <0.2; absence of hemorrhage; and of localized or diffuse rim thinning). Furthermore, subjects had to be over 18 years old, should not have received any medicines affecting the circulatory system in the month preceding their enrollment, and should not have ingested caffeine for at least 24 hours before the investigations commenced. 
Exclusion criteria were as follows: (1) best corrected visual acuity <0.5 (to ensure that the subjects had good central fixation); (2) refractive error (RE) ≤−6.0 D and RE ≥3.0 D; (3) serious cataract and other ocular diseases that hamper enhanced depth imaging optical coherence tomography (EDI-OCT); (4) presence of other eye diseases, such as age-related macular degeneration, retinal detachment, or previous eye operations; and (5) a history of or current hypertension or diabetes, or a family history of these conditions. 
Written informed consent was obtained from all the study participants prior to enrollment in the study. The study adhered to the tenets of the Declaration of Helsinki. 
Measurement of IOP, Systolic Blood Pressure, Diastolic Blood Pressure, Heart Rate, and High Frequency Heart Rate Variability
Patients fasted for at least 4 hours, after which four assessment time-points (baseline, 15, 30, and 60 minutes after drinking 1 liter of water within a 5-minute period) were scheduled. The IOP was measured using an iCare rebound tonometer (iCare Finland Oy, Vantaa, Finland). The iCare tonometer was chosen because of its portability, noninvasive characteristics, and good correlation with the Goldmann applanation tonometer.12 No anesthesia or calibration was required during the procedure.13 The iCare tonometer uses a P value to indicate the quality of the measurement taken, and we discarded any iCare reading with an error bar.14 Three measurements (six readings per measurement) were obtained, and if the difference value was within ±1 mm Hg, the average value was calculated as the result of this IOP measurement.15 All IOP measurements were taken by the same experienced examiner (CLG). A different observer (CW) read and recorded the IOP readings to minimize biases. 
Systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were recorded using an automatic sphygmomanometer (OmronHEM-7201; Omron, Dalian, Liaoning, China). The mean arterial pressure (MAP) was calculated using the equation MAP = [(2 × DBP) + SBP]/3. 
Five-minute dynamic electrocardiograms (ECGs) were recorded at each time-point after the participants had rested in a supine position on a firm bed for 5 minutes. The high frequency (HF; 0.15−0.4 Hz) indices of heart rate variability (HRV), determined by using Kubios HRV Premium software (version 2.2; University of Eastern Finland), were transformed into their natural logarithm (ln, milliseconds2) and analyzed using parametric tests (Fig. 1). 
Figure 1
 
The HRV results obtained from a 5-minute ECG recording. The frequency domains are generated using Fourier transform from the recorded R–R intervals. (A) The R–R interval curve from the 5-minute recording. (B) The frequency domain result before the WDT. (C) The frequency domain result at 15 minutes after the WDT. The HF of the HRV increased markedly after the water-loading (Fig. 1C). HF is shown between the two arrows in B and C.
Figure 1
 
The HRV results obtained from a 5-minute ECG recording. The frequency domains are generated using Fourier transform from the recorded R–R intervals. (A) The R–R interval curve from the 5-minute recording. (B) The frequency domain result before the WDT. (C) The frequency domain result at 15 minutes after the WDT. The HF of the HRV increased markedly after the water-loading (Fig. 1C). HF is shown between the two arrows in B and C.
Imaging Processing
SC and the trabecular meshwork (TM) were imaged at four time-points by using enhanced depth imaging optical coherence tomography (EDI-OCT; Spectralis; Heidelberg Engineering GmbH, Dossenheim, Germany), after 5 minutes of rest. 
Rectangle EDI-OCT scans were used to assess eight regions (at the 12:00, 1:30, 3:00, 4:30, 6:00, 7:30, 9:00, and 10:30 o'clock positions) of the randomly selected eye of each participant by using the anterior segment module of the Spectralis OCT (Fig. 2). For a rectangular area of 15 × 5°, 21 serial EDI-OCT B-scans were obtained (20 frames were stacked to generate one EDI OCT B-scan). All OCT tests were performed under standardized darkroom photopic conditions (ca. 3.5 lux). 
Figure 2
 
Rectangle EDI-OCT scan of eight different regions of the right eye.
Figure 2
 
Rectangle EDI-OCT scan of eight different regions of the right eye.
Measurement of SC and TM
The SC area (SCAR; μm2) in the same location and the TM thickness (TMTH) of eight regions at different time-points were measured using Image J software (version 1.45S; National Institutes of Health, Bethesda, MD, USA). SC was defined as being observable when a black, lucent space was detected (Fig. 3). The TMTH was calculated as the average of measurements acquired at the anterior endpoint and the middle portion of SC, as reported in our previous study.11 
Figure 3
 
The profile of SC. The yellow curve indicates the SC section.
Figure 3
 
The profile of SC. The yellow curve indicates the SC section.
The measurements were performed by two observers; cases of discrepancy >15% were resolved by consulting the senior author. The data were recorded and stored for later statistical analysis. 
Statistical Analysis
All statistical analyses were performed using the SPSS software package (version 16.0; SPSS, Inc., Chicago, IL, USA). The data are presented as the mean values ± standard deviations. Mauchly's sphericity and the Greenhouse−Geisser test were used to validate a repeated measures ANOVA of parameters. Fisher's least significant difference test was adopted to compare the differences in the average of eight SCAR regions [SCAR(mean)]: the superior, inferior, nasal, and temporal SCAR, as well as TMTH, HF, HR, and MAP at the different time-points. Pearson's correlation and univariate linear regression analysis were adopted to examine the relationship between SCAR(mean) and HF, HR, and IOP. All tests were two-tailed. Statistical significance was defined as a P value less than 0.05. 
Results
Twenty-five participants (25 eyes) were enrolled in this study. Three participants were excluded because of unsatisfactory image quality. A total of 22 participants (22 eyes; 7 males; 15 females) were thus eventually included in the analyses. The mean patient age was 27.32 ± 3.30 years, the mean best corrected visual acuity was 1.004 ± 0.120, the mean RE was −2.28 ± 2.01 D, and the mean body mass index was 20.79. 
SCAR(mean) decreased from 6521 ± 1360 μm2 at baseline to 5180 ± 1455 μm2 at 15-minutes post-WDT (Figs. 4A, 4B) and increased from 6289 ± 1876 μm2 at 30-minutes post-WDT to 6526 ± 1565 μm2 at 60-minutes post-WDT. IOP increased from 14.9 ± 2.7 mm Hg at baseline to 18.4 ± 3.3 mm Hg at 15-minutes post-WDT and decreased from 16.2 ± 3.1 mm Hg at 30-minutes post-WDT to 14.5 ± 2.7 mm Hg at 60-minutes post-WDT. HF indices increased from 1587 ± 930 ms2 at baseline to 2193 ± 863 ms2 at 15-minutes post-WDT and returned from 1844 ± 653 ms2 at 30-minutes post-WDT to 1715 ± 584 at 60-minutes post-WDT. HR decreased from 69 ± 9.7 beats/min (bpm) at baseline to 63 ± 8.9 bpm at 15-minutes post-WDT and was 64 ± 7.1 bpm at 30 minutes and 63 ± 10.1 bpm at 60-minutes post-WDT (Figs. 5A, 5B). 
Figure 4
 
Morphology of SC (white arrow). Before (left panel) and after (right panel) the WDT.
Figure 4
 
Morphology of SC (white arrow). Before (left panel) and after (right panel) the WDT.
Figure 5
 
The variations in SC, IOP, HF HRV, and HR across four time-points after water-loading. (A) IOP and SC varied significantly by 15 minutes and returned to baseline at 60 minutes after water-loading. (B) HF and HR varied significantly by 15 minutes and returned to baseline at 60 minutes after water-loading.
Figure 5
 
The variations in SC, IOP, HF HRV, and HR across four time-points after water-loading. (A) IOP and SC varied significantly by 15 minutes and returned to baseline at 60 minutes after water-loading. (B) HF and HR varied significantly by 15 minutes and returned to baseline at 60 minutes after water-loading.
Significant differences were found by Mauchly's sphericity and the within-subjects effect test (Greenhouse−Geisser test and Sphericity assumed test). At least one of the time-points for SCAR(mean), SCAR(inferior), SCAR(nasal), SCAR(temporal) (see Fig. 2), IOP, HF, and HR tested different from the other time-points. There was no significant difference in SCAR (superior), TMTH, and MAP after water-loading (Table). 
Table
 
Repeated Measures of Parameters at the Four Time-Points
Table
 
Repeated Measures of Parameters at the Four Time-Points
The least significant difference test for pairwise comparisons was adopted to compare the parameters (SCAR, IOP, HF, and HR) at different time-points after the WDT (Figs. 6A−E). There were significant fluctuations of all these parameters at 15 minutes, with recovery at 30 minutes after the WDT (P > 0.05). 
Figure 6
 
(A−D) Changes in SCAR(mean), IOP, HF, and HR at different time-points after water-loading. (E) Four quadrants of SCAR at different time-points after water-loading. The asterisk indicates statistically significant differences.
Figure 6
 
(A−D) Changes in SCAR(mean), IOP, HF, and HR at different time-points after water-loading. (E) Four quadrants of SCAR at different time-points after water-loading. The asterisk indicates statistically significant differences.
When plotting SCAR(mean) against the IOP and HF from baseline to the maximum change after the WDT, significant correlations were found (Figs. 7A, 7B). Figure 7C shows the associations between HF and HR from baseline to maximum change. 
Figure 7
 
(A, B) The univariate regression analysis shows significant correlations of IOP and HF with SCAR(mean). (C) Significant associations between HF and HR from baseline to maximum change.
Figure 7
 
(A, B) The univariate regression analysis shows significant correlations of IOP and HF with SCAR(mean). (C) Significant associations between HF and HR from baseline to maximum change.
Discussion
SC was discovered by the anatomist Friedrich Schlemm as a vein located at the chamber angle that collects aqueous humor from the anterior chamber and delivers it into the bloodstream.16 As pathologic changes in SC can result in significant resistance to aqueous humor outflow,1721 SC has attracted considerable interest as a target for glaucoma therapy in recent years (e.g., canaloplasty, viscocanalostomy, and SC scaffolding).16 Given the superb images obtained with the EDI-OCT's anterior segment module, we were able to describe the details of SC in vivo.22 
The increased IOP elicited by the WDT has been reported by numerous studies; in this study, we also found that IOP increased significantly by 15 minutes after water-loading (14.9 ± 2.7 mm Hg vs. 18.4 ± 3.3 mm Hg; P < 0.05). However, the physiologic basis of this IOP fluctuation is not yet clear.23 Secretion of aqueous humor and resistance to its outflow are important processes for maintaining stable IOP. It has been speculated that water-loading changes the plasma osmotic pressure gradient and causes an influx of water into the eye. However, neither change in plasma osmolality nor colloid osmotic pressure was confirmed during the WDT.24 Greenfield et al.25 proposed that the WDT raises IOP by increasing episcleral venous pressure, but a reduced aqueous flow could result from venous obstructive eye disease, such as thyroid ophthalmopathy, superior vena cava syndrome, thrombosis of the cavernous sinus or orbital veins, and Sturge−Weber syndrome. Another proposed mechanism for IOP elevation is decreased aqueous flow after the WDT.26,27 After an oral water-loading test, Diestelhorst and Krieglstein28 found that the aqueous flow (μl/min) decreased significantly in 10 minutes and was gradually restored to baseline within 90 minutes after the WDT. That result was similar to the SCAR(mean) results in this study: a significant collapse of SC occurred by 15 minutes after the WDT, but was restored to baseline values by 60 minutes after water-loading (Fig. 2A). 
Mathematical modeling showed that the dilation of SC increased the outflow facility and the subsequent IOP reduction.29 Increasing the length of the dilated portion of SC improves outflow, as observed with treatment using SC scaffolds.19,20 Genaidy et al.30 showed that canaloplasty successfully reduced the IOP from 25.2 ± 1.009 mm Hg before surgery to 15.9 ± 0.7 mm Hg at 1 year after surgery in eyes with primary open angle glaucoma. In our study, both SCAR(mean) and IOP changed synchronously in the first 15-minutes post-WDT and returned to baseline by 60-minutes post-WDT. Regression analysis showed a significant correlation between SCAR and IOP. Thus, the IOP peak after the WDT could be explained by the collapse of SC. 
Many studies have shown that when an IOP of 30 to 50 mm Hg is achieved, the trabecular sheets become markedly more mechanically distended into SC, reducing the SC lumen.31,32 However, in our study, there was no significant difference in the TMTH post-WDT; thus, the mechanical stress of the small IOP elevation (below 20 mm Hg) in our study was not likely to be involved in the variations of the TM after water-loading. Then, what might regulate the lumen of SC during the WDT? 
HRV has become a point of interest in recent years, as it allows for the noninvasive monitoring of autonomic nervous system regulation and is highly reproducible.33 HRV is the variation in the time interval between each heartbeat, recorded as the R–R interval. The recorded R−R intervals are transformed to generate time and frequency domains. The frequency domains are generated using Fourier transform and are then separated into 3 basic components: very-low-frequency (0−0.04 Hz), low-frequency (0.04−0.15 Hz), and HF (0.15−0.4 Hz). HF specifically reflects parasympathetic nervous system activity, whereas very-low-frequency and low-frequency are attributed to the combined sympathetic and parasympathetic influence, although this interpretation is widely debated.34 A recent study has demonstrated that a shorter recording period (5 minutes) can provide equally reliable information as 24-hour R−R interval recordings. Therefore, we used short ECG segments lasting 5 minutes in our research.35 
The autonomic nervous system is thought to be involved in IOP regulation. In our prior study, we showed that aerobic exercise causes sympathetic nervous system stimulation, consequently causing the expansion of SC.11 Sasamoto et al.36 observed many unmyelinated nerves containing substance P in the inner wall of SC, which indicates that parasympathetic nerves may be involved in SC regulation. It has been proven repeatedly that water intake accelerates parasympathetic activation.37,38 HF specifically reflects parasympathetic nervous system activity, which was found to increase significantly post-WDT in this study. There was also significant correlation between SCAR and HF; HF increased and HR decreased concurrently at 15-minutes post-WDT, and there was a negative correlation between HF and HR (r = −0.6115; P = 0.0002), which indicated that activation of parasympathetic nerves might be involved in the collapse of SC during the WDT. 
This study design did not allow an exploration of the mechanisms underlying parasympathetic nervous system activation post-WDT. However, Peçanha et al.37 and Kawano et al.38 found a positive effect of water consumption on vagal activity after moderate-to-high intensity exercise. These authors have suggested that a vagal activity increase post-WDT occurs to counterbalance a potential sympathetic pressor effect evoked by exercise. Hence, the parasympathetic−sympathetic counterbalance hypothesis has been proposed in recent years, which may explain the results of some other studies. For instance, Jordan et al.39 found that drinking water raises resting plasma norepinephrine levels in young individuals but observed no fluctuations of SBP and DBP after 30 minutes of water intake. We observed similar hemodynamic effects. Increased parasympathetic activation was seen at 15-minutes post-WDT and had returned to normal levels at 30-minutes post-WDT. Therefore, activation of sympathetic nerves may be countered by compensatory vagal activation. 
This study had limitations. First, the correlation coefficients were below 0.45, except for HF and HR. That means that the strength of association was not very strong for SCAR and IOP, and SCAR and HF. The results may be influenced by the narrow age range of the participants we adopted and the lack of samples in this study (mean age, 27.32 ± 3.30 years; 23 eyes). Next, it is unclear whether similar effects of water-loading would be observed in elderly individuals or in patients with primary open angle glaucoma. Lastly, we found significant differences in SCAR, except for the superior quadrant, but data of only one of the quadrants that showed a difference (12:00, 3:00, 6:00, and 9:00 sectors) were used in the analysis. It is necessary to acquire a more detailed data set involving different quadrants in a future study. 
In conclusion, the WDT could cause parasympathetic nervous system stimulation, which may cause the collapse of SC, leading to increased IOP post-WDT. 
Acknowledgments
Supported by National Natural Science Foundation of China (81470632; China). 
Disclosure: W. Chen, None; L. Chen, None; Y. Xiang, None; S. Liu, None; H. Zhang, None; J. Wang, None 
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Figure 1
 
The HRV results obtained from a 5-minute ECG recording. The frequency domains are generated using Fourier transform from the recorded R–R intervals. (A) The R–R interval curve from the 5-minute recording. (B) The frequency domain result before the WDT. (C) The frequency domain result at 15 minutes after the WDT. The HF of the HRV increased markedly after the water-loading (Fig. 1C). HF is shown between the two arrows in B and C.
Figure 1
 
The HRV results obtained from a 5-minute ECG recording. The frequency domains are generated using Fourier transform from the recorded R–R intervals. (A) The R–R interval curve from the 5-minute recording. (B) The frequency domain result before the WDT. (C) The frequency domain result at 15 minutes after the WDT. The HF of the HRV increased markedly after the water-loading (Fig. 1C). HF is shown between the two arrows in B and C.
Figure 2
 
Rectangle EDI-OCT scan of eight different regions of the right eye.
Figure 2
 
Rectangle EDI-OCT scan of eight different regions of the right eye.
Figure 3
 
The profile of SC. The yellow curve indicates the SC section.
Figure 3
 
The profile of SC. The yellow curve indicates the SC section.
Figure 4
 
Morphology of SC (white arrow). Before (left panel) and after (right panel) the WDT.
Figure 4
 
Morphology of SC (white arrow). Before (left panel) and after (right panel) the WDT.
Figure 5
 
The variations in SC, IOP, HF HRV, and HR across four time-points after water-loading. (A) IOP and SC varied significantly by 15 minutes and returned to baseline at 60 minutes after water-loading. (B) HF and HR varied significantly by 15 minutes and returned to baseline at 60 minutes after water-loading.
Figure 5
 
The variations in SC, IOP, HF HRV, and HR across four time-points after water-loading. (A) IOP and SC varied significantly by 15 minutes and returned to baseline at 60 minutes after water-loading. (B) HF and HR varied significantly by 15 minutes and returned to baseline at 60 minutes after water-loading.
Figure 6
 
(A−D) Changes in SCAR(mean), IOP, HF, and HR at different time-points after water-loading. (E) Four quadrants of SCAR at different time-points after water-loading. The asterisk indicates statistically significant differences.
Figure 6
 
(A−D) Changes in SCAR(mean), IOP, HF, and HR at different time-points after water-loading. (E) Four quadrants of SCAR at different time-points after water-loading. The asterisk indicates statistically significant differences.
Figure 7
 
(A, B) The univariate regression analysis shows significant correlations of IOP and HF with SCAR(mean). (C) Significant associations between HF and HR from baseline to maximum change.
Figure 7
 
(A, B) The univariate regression analysis shows significant correlations of IOP and HF with SCAR(mean). (C) Significant associations between HF and HR from baseline to maximum change.
Table
 
Repeated Measures of Parameters at the Four Time-Points
Table
 
Repeated Measures of Parameters at the Four Time-Points
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