Light and Exercise and Melatonin Production in Women

Julia A. Knight1, Suzanne Thompson1, Janet M. Raboud1 and Barry R. Hoffman2

1 Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
2 Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada

Correspondence to Dr. Julia A. Knight, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, 60 Murray Street, Fifth Floor, Toronto, ON, Canada M5G 1X5 (e-mail: knight{at}mshri.on.ca).

Received for publication April 4, 2005. Accepted for publication June 27, 2005.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Melatonin may protect against breast cancer. Light and other factors influence melatonin, but the evidence is limited. The authors conducted a study to determine factors related to melatonin. Women volunteers recruited in Toronto, Canada, from 2002 to 2004 collected urine for three nights (winter and summer), took periodic light measurements, and recorded exposures in a diary. The relation of each variable to log-transformed creatinine-corrected 6-sulfatoxymelatonin in overnight urine was determined by use of generalized estimating equation linear regression. The final model was based on 1,054 measurement days from 213 participating women. None of the light variables was related to the log of 6-sulfatoxymelatonin. A significant interaction between season and day length was included in the final model. The most significant factor was duration of exercise (ß = 0.072; p = 0.004, two-tailed), which increased the amount of melatonin produced. Exercise duration later in the day was more significant (ß = 0.108; p = 0.0009, two-tailed). There was no difference between moderate or strenuous exercise. The failure to find a relation between light brightness and melatonin may be due to the difficulty of measuring this, as well as the importance of the light spectrum, which could not be measured. It is possible that the protective effect of exercise with respect to breast cancer may operate in part through an effect on melatonin.

breast neoplasms; exercise; light; melatonin; women


Abbreviations: NSAID, nonsteroidal antiinflammatory drug


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Melatonin is synthesized in the pineal gland in a series of steps, but the rate-limiting step is directly influenced by the light-dark cycle. Synthesis occurs during the night and is suppressed by bright light (1Go, 2Go). The primary metabolite of melatonin is 6-sulfatoxymelatonin, and overnight urine levels of this metabolite are highly correlated with overnight plasma levels (3Go, 4Go). Experimental studies suggest that the administration of melatonin reduces the incidence and increases the latency of breast tumor development in rodents exposed to chemical carcinogens (1Go, 5Go, 6Go). Susceptibility to breast tumors may also be increased by melatonin suppression from exposure to constant light. Human breast cancer cells implanted into rats exhibited much greater growth rates when the rats were melatonin suppressed (7Go). The question of whether melatonin is involved in breast cancer etiology in humans is largely supported by indirect evidence. Shift work, with increased exposure to light during melatonin production, has been consistently associated with an increased risk of breast cancer (8Go–11Go). A reduced risk of breast cancer in blind women has been cited as supporting evidence for the melatonin hypothesis, as these women would be unaffected by the potentially suppressing effect of light at night (5Go). However, it is not clear whether blind individuals actually do secrete more melatonin than the sighted (12Go). There has been only one study to directly address whether melatonin is related to breast cancer risk in humans (13Go). Although the study found no evidence of a relation, the power to detect a moderate effect was low.

Although there is concern about artificial light exposure in the general population, the extent of exposure in non-shift workers is unclear as is the relation of artificial light to variation in melatonin production in a free-living (i.e., not in controlled laboratory conditions) population. To date, the majority of studies relating light to melatonin synthesis in humans have been conducted in controlled laboratory conditions, where subjects lacking any temporal information and where their activity, sleep, and eating schedules are strictly regulated are exposed to light over a defined interval and at a specific brightness at a particular point in their sleep-wake cycle (14Go–16Go). Other factors have also been linked to melatonin including a variety of medications, weight or body mass index, and alcohol (13Go, 17Go–21Go). Acute effects of exercise on melatonin production have been observed, but inconsistently (22Go). Other variables such as age, sex, and timing of exercise may affect the relation. Menopausal status (18Go) and menstrual cycle phase appear to have no effect on melatonin (3Go).

We conducted a cross-sectional study of healthy female volunteers recruited from Toronto, Canada, from 2002 to 2004 to examine the relation of light and other factors to melatonin production in a free-living population.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Data and sample collection
Female volunteers were recruited by advertising at local hospitals and universities. They were considered eligible if they had no prior cancer or kidney or liver disease, had not traveled across time zones in the previous month, and were not currently working night shifts. An initial appointment was scheduled either from November through February or from May through August. At this time, the participants were asked to complete a questionnaire that requested information on height, weight, and hormone use and incorporated the Horne-Östberg assessment of morning-evening preference (23Go). They were also instructed in the use of a "datalogging" portable light meter (model 401036; Extech Instruments Corporation, Waltham, Massachusetts) and in the collection of overnight urine in the containers provided.

For a 3-day period, the women were asked to take light meter readings every 2 hours from waking to 6 p.m. and every hour from 6 p.m. to bedtime, as well as any time they woke up in the night. As readings were highly variable, they were asked to record in two standard positions, with the sensor at eye level and also pointed toward the brightest light source. The latter usually was either a window or an artificial light source representing the maximum possible light exposure, but the eye level measurement capturing the light in the direction where the participant was looking (often a computer or television) likely better represented actual light exposure. In a darkened room, the brightest light source could have been the same as the eye level source. Urine collection began at 8 p.m. and continued up to and including the first morning void. A diary was provided in which the light meter readings were recorded as a backup to the meter recording and in which each participant was to note if and when any alcohol was consumed or medication taken, as well as any moderate or strenuous physical activity they did. The women were asked to return and repeat the procedure in the opposite season. Compensation of Can $50 (US $43) for time and inconvenience was provided for each completed 3-day session. The study was approved by the Research Ethics Board of Mount Sinai Hospital, Toronto, Canada, and all participants signed a consent form before participating.

Laboratory assay
The volume of each overnight urine collection was measured, and two 1-ml aliquots were stored at –20°C for later analysis of 6-sulfatoxymelatonin, the primary metabolite of melatonin. Urine creatinine was determined on the automated Roche Cobas Integra 700 analyzer (F. Hoffmann-La Roche, Ltd., Basel, Switzerland) using an enzymatic creatinase-based method supplied by the manufacturer. Analytical imprecision was less than 3 percent. Following collection of all urine specimens in the study, one of the two frozen stored urine aliquots was thawed, manually diluted, and assayed for 6-sulfatoxymelatonin using a single-epitope competitive enzyme-linked immunoassay kit commercially available from IBL Gesellschaft für Immunochimie und Immunobiologie mbH, Hamburg, Germany (catalog number RE54031). The assay, which did not require prior extraction of the urine, was adapted to an automated robotic system that carried out the pipeting, shaking, incubation, washing, and reading steps of the test protocol. All assays were completed over a 2-day period using the same lot of test kit. Specimens were tested in singleton in the titer plate formatted assay. The three urine specimens provided by each study participant over each collection period were assayed back to back on the titer plate. Standards and controls provided with the kit were included in each titer plate. Total imprecision across all the assay runs as judged from the controls was 25 percent at a level of 13 µg/liter and 17 percent at a level of 63 µg/liter. Urine specimens containing 6-sulfatoxymelatonin at a concentration in excess of the second highest standard (140 µg/liter) were diluted further and assayed again.

Analysis
Light readings recorded by the meter were compared with those recorded in the diary, and periods where no concordance could be found were excluded. For analysis, summary measures of light exposure were constructed as follows. "Day" exposures were defined as those occurring from 5 a.m. up to 6 p.m., and "night" exposures were defined as those from 6 p.m. up to 5 a.m. An indicator of whether light was recorded above a specific threshold was created for both day and night and for both eye-level and brightest-light readings for three thresholds, 100, 500, and 1,000 lux. Other variables that were tested included bedtime, wake time, time between wake time and bedtime, day length, season, morning-evening preference score, age, height, weight, oral contraceptive use, alcohol use, nonsteroidal antiinflammatory drug (NSAID) use, and exercise. Exercise was defined as moderate or strenuous, and both any exercise and duration in minutes were tested. The time of day of exercise was also examined, with separate variables constructed for exercise in the morning (from 4 a.m. up to noon), afternoon (from noon up to 4 p.m.), evening (from 4 p.m. up to 8 p.m.), and night (from 8 p.m. up to 4 a.m.). The primary outcome variable was the creatinine-corrected 6-sulfatoxymelatonin (µg/mmol of creatinine), which was natural log transformed.

The contributions of variation between days within individuals, between individuals, and between seasons to the total variation in melatonin were determined using components of variance analysis. Correlation between measurements on separate days from the same individual was measured with Spearman's rank correlation. Relations between the log of 6-sulfatoxymelatonin and various continuous covariates were examined using scatterplots. Locally weighted scatterplot smoothers were used to summarize trends in the relation. The relation of each variable with the log of 6-sulfatoxymelatonin was determined using generalized estimating equation linear regression models to account for the repeated measures (3 days in each of two seasons). Each variable was first examined in a univariate model before multivariable modeling. A two-tailed p value of 0.05 was used to determine significance. Analyses were conducted using SAS, version 8.2, software (SAS Institute, Inc., Cary, North Carolina).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
We recruited 213 women to participate in at least one 3-day session, and 161 (76 percent) also completed a second session in the opposite season. In total, there were 200 completed winter sessions and 174 completed summer sessions or 374 sessions (1,119 measurement days) in total. Of the 1,119 measurement days, 13 (1 percent) were excluded because no urine sample was available, leaving 1,106 measurement days. The final model was based on 1,054 measurement days, as data were missing on 52 (5 percent) measurement days. Table 1 shows the age distribution of the participants, as well as the average height and weight, the proportion using oral contraceptives, NSAIDs, and alcohol, and the proportion exercising. The women were relatively young with 83 percent under the age of 40 years. Many were students with a variable lifestyle and schedule. There were 67 women (31 percent) using oral contraceptives and 34 (16 percent) used NSAIDs at some point during the study. The number who consumed alcohol during at least one measurement day was 69 (32 percent), and 154 (72 percent) reported doing some form of exercise on at least 1 measurement day. Figure 1 shows the overall distribution of log-transformed creatinine-corrected 6-sulfatoxymelatonin over all measurement days.


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TABLE 1. Characteristics of the 213 study participants recruited in Toronto, Canada, from 2002 to 2004, as well as the mean and standard deviation of log-transformed creatinine-corrected 6-sulfatoxymelatonin by characteristic

 


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FIGURE 1. A histogram of the frequency distribution of natural log-transformed creatinine-corrected 6-sulfatoxymelatonin (6-OHMS) measured in overnight urine collected over 1,054 measurement days from 213 women study participants recruited in Toronto, Canada, from 2002 to 2004.

 
From the components-of-variance analysis for the log of 6-sulfatoxymelatonin, between-person variance and within-person variance were approximately equal (41 percent and 45 percent, respectively). Any measurement error would be included in the within-person variation. Seasonal differences contributed relatively little (14 percent) to the total variation. The day-to-day Spearman rank correlations (comparing day 1 with day 2 and day 2 with day 3, within session) were 0.55 and 0.62.

The relations between individual variables and creatinine-corrected 6-sulfatoxymelatonin are shown in table 2. Individual variables significantly related to melatonin were height, season, day length, NSAID use, and duration of exercise. Age was marginally insignificant (p = 0.08). None of the light measures was significantly related to melatonin and neither were any exercise versus no exercise, alcohol use, weight, morning-evening preference score, oral contraceptive use, time of going to bed or waking, or total hours in bed. We also examined body mass index, but found the relation (p = 0.12) weaker than the relation between height and 6-sulfatoxymelatonin, and therefore we incorporated height and weight separately in subsequent modeling.


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TABLE 2. Relation of characteristics of study participants recruited in Toronto, Canada, from 2002 to 2004 to log-transformed creatinine-corrected 6-sulfatoxymelatonin (µg/mmol) from generalized estimating equation linear regression models

 
As some initial analysis by season appeared to indicate that the effect of some variables varied by season, interaction by season was tested for all the variables included in the modeling (both main effect variables and the interaction were included in the test model). Significant interactions were found for height (pinteraction = 0.02), day length (pinteraction = 0.04), night eye-level light of >1,000 lux (pinteraction = 0.03), day eye-level light of >1,000 lux (pinteraction = 0.03), and day brightest light of >500 lux (pinteraction = 0.006). However, upon further investigation, the R2 contribution of each interaction was very small, that is, less than 0.005, except for day length by season (R2 = 0.02). Therefore, only the latter interaction was retained in the multivariable modeling.

Table 3 shows the final multivariable model results. By far the most significant variable was duration of exercise with increasing 6-sulfatoxymelatonin production occurring along with increasing duration of exercise. Although the model had an R2 of only 0.09, most of this variation was accounted for by duration of exercise (R2 = 0.05). Season and day length also contributed to melatonin in this model, but the effect of day length varied by season. In the summer, increasing day length was associated with decreasing 6-sulfatoxymelatonin as expected, but there was a weak effect in the opposite direction in the winter. Taller women tended to excrete more 6-sulfatoxymelatonin, while women taking NSAIDs excreted less, although the latter effect was marginally insignificant. Older women tended to excrete less 6-sulfatoxymelatonin, but we had relatively few older women in our study sample and the relation was not statistically significant. Figure 2 shows the relation between log-transformed 6-sulfatoxymelatonin and exercise duration, height, age, and also day length by season.


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TABLE 3. Relation of characteristics of study participants recruited in Toronto, Canada, from 2002 to 2004 to log-transformed creatinine-corrected 6-sulfatoxymelatonin (µg/mmol) using generalized estimating equations for linear regression after multivariable modeling

 


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FIGURE 2. Scatterplots of age (years), height (cm), duration of exercise (hours), summer day length (hours), and winter day length (hours) versus log-transformed creatinine-corrected 6-sulfatoxymelatonin (6-OHMS) in overnight urine collected over 1,054 measurement days from 213 women study participants recruited in Toronto, Canada, from 2002 to 2004. The curve on each plot is based on a locally weighted scatterplot smoother.

 
As there appeared to be two outlier points in exercise duration, we explored whether they were exerting undue influence on the results. Removing these two points made little difference to either the regression coefficient estimate (0.081 vs. 0.080, univariate) or the p value (0.002 vs. 0.005, univariate). We also tested a natural log-transformed duration of exercise variable to see whether any conclusions would be altered. As there was now a greater separation between exercisers and nonexercisers, a term adjusting for exercise (yes/no) also had to be included in the model. Log-transformed duration of exercise remained significant (p = 0.004).

We also investigated whether the timing of the exercise made a difference, and the results are also shown in table 3. The effect of exercise duration appeared to be stronger in the evening and night (from 4 p.m. up to 4 a.m.) compared with the morning (from 4 a.m. up to noon) or afternoon (from noon up to 4 p.m.). When the duration of moderate exercise was considered separately from more strenuous exercise, there was little difference in the effect (table 3). Moderate exercise included activities such as walking, gardening, baseball, and golfing, while strenuous exercise included activities such as running, biking, swimming, and aerobics.


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
There has been interest in the potential relation between melatonin and breast cancer in the search for potentially modifiable risk factors for breast cancer since Stevens (24Go) proposed a relation between electrical power use and breast cancer. Exposure to artificial light is ubiquitous in developed countries, but brightness can vary considerably and there is growing evidence that a number of factors may affect melatonin production. We wished to address whether variation in light and other exposures in a free-living population not working night shifts can account for variation in melatonin, which in turn could be contributing to variation in breast cancer risk.

There were considerable variation between individuals and also day-to-day variation within individuals. Levallois et al. (19Go) previously reported a high Spearman rank correlation of 0.92 between days over a 2-day measurement period. The day-to-day Spearman rank correlation in our study was considerably lower, ranging from 0.55 to 0.62. In the previous study, urine was collected beginning only after the last void before bed, whereas we instructed women to collect all urine beginning at 8 p.m. It is possible that there is greater variability in melatonin produced earlier in the evening that was not captured previously. Both light exposure and exercise, which can vary day-to-day, may have an influence here. Our study sample was also younger compared with that of the previous study, which may also influence day-to-day variability.

The primary exposure of interest was light, but we were unable to observe any relation between light brightness and 6-sulfatoxymelatonin in a free-living population. However, light brightness was extremely variable and difficult to measure. Slight movement of, or even near, the light meter sensor could alter readings, and the readings also depended on how the sensor was oriented in a room. The readings depended on not only lighting sources but also light reflections. Light sources such as computer or television screens are also variable themselves. Therefore, the light received by the retina will vary even within one location. Even attempting to account for this variation by considering brightness thresholds, that is, whether there was any light exposure above a certain level, did not yield any associations with melatonin. The thresholds were selected to reflect common exposures: 100 lux would be the brightest light likely experienced at home, while levels of approximately 500 lux could be experienced in a bright office environment with artificial lighting. Sunlight, even on a cloudy day, was generally brighter than most artificial light sources and yielded readings of 1,000 lux or more. Bright light experienced in a work environment during normal melatonin production could still act to suppress melatonin in shift workers, but we did not address that question in this study. Our focus was on light exposures in the majority of the population who do not work night shifts. In general, any light readings after bedtime were very low. It should also be noted that bright light does not suppress melatonin when the eyes are closed (25Go).

Another potential explanation for our failure to find a relation between light brightness and melatonin in our study is that the light spectrum is likely important. It is becoming apparent that the circadian system is more sensitive to shorter wavelengths of light (26Go–28Go). Unlike our visual system, which has a peak sensitivity at wavelengths of approximately 505 nm in low light and 555 nm in brighter light, our circadian system has a peak sensitivity at wavelengths of approximately 460 nm (blue) (26Go, 27Go). In future studies, it would be useful to attempt to consider light spectrum as well as brightness. Spectral differences may also account for differences in the effect of day length by season. Longer days in the summer reduced the amount of melatonin produced at night as expected (29Go) and as previously observed in one study (18Go), but not in another (19Go). However, not only was the effect weaker in the winter, it appeared to be in the opposite direction (figure 2). Attenuation of effect in the winter could be accounted for by the fact that, in Toronto from November to February, most people spend the majority of their time indoors and may be less influenced by external day length. Lack of exposure to outdoor lighting conditions can diminish a relation between day length and melatonin (29Go). Both the brightness and the spectrum of sunlight also vary by season. The latter is due to increased scattering of shorter wavelengths when the sun is lower in the sky (30Go). Therefore, the influence of artificial light and other factors influencing melatonin is likely to be greater in the winter. This seasonal effect may also have obscured any relation between day length and melatonin in a previous study (19Go).

Height appeared to be more strongly related to 6-sulfatoxymelatonin than either weight or body mass index. Taller women tended to excrete more 6-sulfatoxymelatonin than did shorter women. As taller women have a greater risk of developing breast cancer (31Go), the direction of the relation is opposite to what might be expected if melatonin reduces breast cancer risk. However, the relation between height and 6-sulfatoxymelatonin was not as significant as the relation between exercise duration and 6-sulfatoxymelatonin, and other studies have also found that taller women have reduced risk if they are physically active (31Go).

Among the factors that we measured, duration of exercise clearly had the strongest effect on melatonin. Several studies have considered the short-term effects of exercise on melatonin production, but the results have been mixed, as discussed in a recent review (22Go). However, there are many potentially modifying factors influencing this relation, including sex, age, fitness, time of day, and lighting conditions. In general, the data are too sparse to draw conclusions about any of these potential modifiers. Studies that specifically examined girls and women have generally found that exercise increased melatonin (22Go, 32Go, 33Go), consistent with our results. The majority of studies measured melatonin in either plasma or saliva. Those that reported an increase in melatonin found that the effect was short lived, with melatonin levels falling once the activity stopped (22Go). As we were measuring metabolized and excreted melatonin, it is not surprising that exercise in the evening, prior to urine collection, still contributed to the overall 6-sulfatoxymelatonin. The temporary effect could explain the reduced effect of morning and afternoon exercise compared with evening and nighttime exercise, as any early temporary increase may not have been captured. However, a recent study in young men found that exercise increased melatonin only in the evening or night (34Go).

Using our subjective assignment of activities into categories of moderate or strenuous exercise, we did not see any apparent differences between the categories. The effect of exercise did not vary by season and therefore cannot be explained by increased exposure to sunlight in the summer. It is also clear that the effect of exercise is dependent on the duration, also not surprising if the effect on melatonin production continues only as long as the activity is being carried out.

Despite the short-lived nature of the effect, exercise duration contributed significantly to the overall melatonin excreted throughout the night, implying that even an hour of moderate exercise contributes significantly to the total amount of melatonin produced in a day. Participants were asked simply to report the approximate duration and type of physical activity in the appropriate time slot of their diary. Even with this relatively crude level of detail, exercise duration contributed an R2 of 0.05 in a model where the total R2 was 0.09. Therefore, the majority of the variation that we could explain was accounted for by exercise duration. Physical activity is becoming increasingly established as being protective against breast cancer (35Go–37Go). However, the biologic mechanism explaining the effect is still unclear (31Go, 38Go). It is intriguing to consider that this protective effect may be at least partially accounted for by an effect on melatonin.

As is evident for the total R2 reported above, our model accounted for only a small proportion of the overall variation in melatonin. There are several possible reasons for the modest R2 estimate. One consideration is that our outcome variable, creatinine-corrected 6-sulfatoxymelatonin, is actually based on three separate measurements, urine volume, creatinine, and 6-sulfatoxymelatonin. Even a small amount of measurement error in each of these will contribute to a larger overall error when they are combined. The potential pitfalls of the light measurements have already been discussed, but there is also likely some error in the other variables that we considered, and some were only crude indicators. There are also many factors that we were unable to consider. Although a variety of medications were taken by our participants, in most cases the number taking any particular class of drugs was too small to evaluate. Others have shown that medications could influence melatonin, although combining unrelated medications may not be meaningful. The class of drugs we could evaluate, NSAIDs, did have a marginal effect. Further work in this area is needed. Our participants did not consume much alcohol over the study, and it is still possible that higher intakes affect melatonin in some populations. It is likely that there is a genetic contribution to melatonin (21Go), but we did not evaluate this aspect, and there may also be a dietary contribution to melatonin as tryptophan depletion can reduce melatonin levels (39Go). It is possible that increased tryptophan intake could increase melatonin, but we did not measure this. Finally, light likely does contribute to melatonin in some way, but further studies are needed to address issues in light measurement including spectrum. It is possible that much of the artificial light we are exposed to is too dim to have a strong biologic effect, but this question needs further consideration.

Overall, although we were unable to clearly link variation in exposure to bright light to variation in melatonin in a free-living population, we did find a clear effect of exercise. As we were looking at a number of variables in this exploratory analysis, it is possible that some significant associations occurred by chance. However, longer duration of either moderate or strenuous activity was highly significantly related to the amount of melatonin produced based on measurement of 6-sulfatoxymelatonin in overnight urine. The potential for melatonin to mediate the protective effect of physical activity on breast cancer risk could be exploited in the development and evaluation of physical activity interventions.


    ACKNOWLEDGMENTS
 
This work was supported by the Canadian Breast Cancer Research Alliance.

The authors would like to thank Dr. Azar Azad for overseeing all the biochemical assays.

Conflict of interest: none declared.


    References
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 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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