1 Department of Urology, North Staffordshire Hospital, Staffordshire
2 Clinical Biochemistry Research Laboratory, Keele University School of Medicine, North Staffordshire Hospital, Staffordshire ST4 7PA
3 Department of Mathematics, Keele University, Staffordshire
4 Department of Biochemistry, Good Hope Hospital, Sutton Coldfield, Birmingham B75 7RR, UK
5 To whom correspondence should be addressed Email: paa00{at}keele.ac.uk
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Abstract |
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Abbreviations: BPH, benign prostatic hypertrophy; OR, odds ratio; UVR, ultraviolet radiation.
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Introduction |
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The mechanism for this effect is unclear although vitamin D is implicated (1,2,610). The vitamin affects proliferation and differentiation of many cell types including prostate and may act as a UVR-dependent serum factor that prevents development of this cancer (1,2,11). Indeed, links between vitamin D status and cancer incidence or mortality have been reported. For example, reduced colorectal cancer risk has been related to higher serum 25-hydroxyvitamin D3 concentrations (12), and women with high vitamin D3 intake or dermatological evidence of high sun exposure have a lower breast cancer risk (13). The serum vitamin D concentration depends on cutaneous synthesis, which is influenced by skin colour. Increased pigmentation results in reduced vitamin D synthesis (1416). Thus, ability to initiate pigmentation after exposure may influence cancer risk via effects on vitamin D synthesis (11,17). This view is supported by studies showing allelism in genes that mediate melanin synthesis, a major determinant of skin colour, is associated with prostate cancer risk. Thus, allelic variants in exon 1 (TYR*A2) of tyrosinase (TYR), a gene whose product catalyses rate-limiting steps in melanin synthesis, are associated with reduced risk of prostate cancer (11,17). We speculated that TYR*A2 is associated with less efficient melanin production and reduced pigmentation (11).
These findings suggest prostate cancer risk is partly determined by interaction between exposure and pigmentation. In this context, skin type is putatively important as it describes the tanning and burning reaction of the skin to sunlight by considering past reaction to UVR (18). In the commonly used Fitzpatrick system (18), skin type 1 describes Caucasians who cannot tan and whose skin burns easily. Skin types 2 and 3 describe increasing ability to tan and decreasing tendency to burn while subjects with skin type 4 tan easily and rarely burn. However, the effect of skin type on prostate cancer risk is difficult to predict. Men with skin type 1 would be expected to be at reduced risk because their failure to pigment allows increased vitamin D synthesis even after modest exposure (15). However, men with skin type 1 could be at increased risk because studies examining the effect of skin type on skin cancer risk show that these subjects often avoid exposure because of their propensity to burning (19,20). It is possible that both these contrasting effects occur in different subgroups of men.
We now describe studies to determine if the link between UVR exposure and prostate cancer risk is mediated by skin type. We assessed exposure, using data on cumulative exposure per year and adult sunbathing score derived from a validated questionnaire. These parameters were studied because they are associated with prostate cancer risk, they reflect exposure during adult life and, they are variables that allow examination of the possibility that thresholds of exposure mediate risk (8). The parameters were compared in prostate cancer and BPH patients. The BPH comparison group was chosen because this diagnosis largely allows exclusion of concurrent prostate cancer (21). Our aims were first, to determine if extent of UVR exposure in cancer and BPH patients is influenced by skin type. Secondly, we determined if skin type mediates cancer risk. We particularly wished to determine if the association between risk and exposure is found in all men or, only those with particular skin types or patterns of exposure. Prostate cancer patients have developed the disease because of different combinations of characteristics and exposures. These patients therefore, comprise subgroups defined by different combinations of risk variables (22,23). Recursive partitioning approaches are useful in identifying combinations of variables that affect risk in some but not other subgroups (23). The approach is based on classification trees that result from partitioning the data repeatedly in splits using variables such as cumulative exposure or sunbathing score. We describe its use in identifying how skin type affects prostate cancer risk in the cancer and BPH groups and, in subgroups of men with particular exposures to UVR.
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Materials and methods |
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The diagnosis of prostate adenocarcinoma was made on the basis of histological evidence. In 32 men with advanced cancers, it was considered unethical to biopsy the prostate and histology was not available. These patients were included as they had a malignant prostate gland on digital rectal examination (DRE), positive bone scan and prostatic specific antigen (PSA) level >30 ng/ml (age-related reference range; up to 06.5 ng/ml). The diagnosis of BPH was made using histology. All the BPH patients had a serum PSA level in the age-related reference range and benign DRE. We excluded cancer or BPH patients with two or more first-degree relatives with prostate cancer or one first-degree relative diagnosed with prostate cancer before 55 years. Our aim was to recruit all men who fulfilled our inclusion criteria and the few suitable patients not included were missed at random. Two BPH patients (none with cancer) declined participation. The North Staffordshire Hospital Ethics Committee approved the study and written, informed consent was obtained from all subjects.
Assessment of UVR exposure and skin type
All the men completed, before leaving the urology clinic, a validated questionnaire (11,24,25) that recorded: (i) cumulative exposure in months during adult life per year: this parameter was determined by adding hours of exposure to sunshine on each weekday and during weekends (considered separately) during adult life (age 20 years to age at diagnosis). Subjects were asked to assess such exposures during three age categories: 2039, 4059 and after 60 years. The data were combined to give total cumulative exposure in months per year between 20 years of age and age at diagnosis (first quartile 1.1, second quartile 1.21.7, third quartile 1.82.4, fourth quartile >2.5 months). The parameter, exposure per year therefore, allows for the broad range of ages at diagnosis in men in both the cancer and BPH groups. (ii) Adult sunbathing score; subjects were asked to assess the extent of sunbathing during the age bands, 2039, 4059 and after 60 years using the categories never, rarely, occasionally and frequently (scored 1, 2, 3 and 4 units, respectively). Sunbathing score was obtained by adding the units from the three age categories (maximum score 12, minimum score 2 as some subjects were aged <60 years at diagnosis). As this score is ordinal, it is not appropriate to calculate sunbathing score per year. (iii) Skin type. This was determined using the Fitzpatrick system (18,19) as categorized as; type 1 always burn/never tan, type 2 usually burn/tan with difficulty, type 3 sometimes mild burn/average tanning ability, type 4 rarely burn/easily tan. We attempted to eliminate researcher bias by allowing self-administration of the questionnaire although
25% of men required assistance. Accordingly, the interviewer used a neutral script to guide the questions.
The questionnaire also assesses the following parameters of exposure although they were not considered in the present study. (iv) Childhood sunburning, defined as erythema for >48 h or blistering was scored yes/no. (v) Foreign holidays, recorded as at least one holiday each year in a sunny country over the last 10 years (scored yes/no). (vi) Living abroad in a hot climate for >6 months (scored yes/no). (vii) Proportion of occupational time spent outdoors. (viii) Use of sunbeds (scored yes/no). (ix) Sunscreen use scored (yes/no).
Statistical analysis
As mean age at diagnosis of BPH patients (67.2 ± 8.5 SD years) was younger (MannWhitney test, P < 0.0001) than that of cancer patients (70.4 ± 7.9 SD years), we adjusted for this difference by including age at diagnosis as a main effect in logistic regression models. To ensure the associations between prostate cancer risk and UVR exposure parameters were not influenced by imbalances in age and proportions of subjects with particular skin types, we also studied the effect of exposure per year and sunbathing in pairs of men matched for age (cancer cases 68.2 years, BPH 68.2 years), and age and skin type (cancer cases 68.4 years, BPH 68.3 years) using conditional logistic regression (Stata release 7 for Windows, Stata Corporation, College Station, TX).
Two-way analysis of variance (ANOVA) without interactions was used to compare exposure in the four skin type groups (NCSS 2001, Kaysville, UT). Analysis of covariance (ANCOVA) was used to adjust for imbalances in age at diagnosis between prostate cancer and BPH patients. For ANOVA and ANCOVA, exposure data were log-transformed giving approximate normality. To assess the relationship between exposure and skin type, linear regression models, with inclusion of age at diagnosis as a main effect, were applied separately in cancer and BPH patients. Association of skin type with prostate cancer was studied by fitting logistic regression (corrected for age) and conditional logistic regression models (matched 1:1 for age at diagnosis).
To determine the joint effect of skin type and UVR exposure, a recursive partitioning approach (HelixTree software from Golden Helix, www. goldenhelix.com) was used. This allows prediction of a dependent variable on the basis of a number of predictors. The software is based on a Formal Inference-based Recursive Model (http://www.stat.umn.edu/users/FIRM/firm-info.html). The HelixTree algorithm partitions continuous (cumulative exposure per year) and ordinal (sunbathing score, skin type) predictors in an optimal manner such that more homogeneous groups, with respect to status of individuals (prostate cancer or BPH), were produced. The algorithm uses an appropriate significance test (t-test, F-test, 2-test) to select groups that are most significantly different from each other (highest proportion of cancer or BPH patients). Thus, in the first partition, the algorithm lists the predictors in the order of their P values. Partitioning is based on the value of the Bonferroni-corrected P value. We selected the most significant predictor to partition our subjects into nodes comprising an increasing proportion of either cancer or BPH patients. The algorithm was then used to effect further partitioning of the subjects in each of the nodes. At each level of partitioning, we selected to use the most significant predictor although any of the other variables may be selected. An age-corrected odds ratio was calculated, using logistic regression analysis, to determine cancer risk in subgroups identified from recursive partitioning.
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Results |
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Skin type and extent of UVR exposure: BPH patients
Table I shows numbers of BPH patients with skin types 14 and mean months of cumulative exposure per year in these subjects. While exposure in men with skin type 1 was lower than in those with skin type 4, this association was not significant (two-way ANOVA, P = 0.18). The linear relationship between exposure per year (using log transformed data) and skin type was assessed using linear regression models with inclusion of age at diagnosis as a main effect. This analysis showed no significant association between exposure per year and increasing skin type (P = 0.281).
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Skin type and UVR exposure: cancer patients
Table I shows the numbers of prostate cancer patients with skin types 14. Cumulative exposure per year significantly increased (two-way ANOVA, P = 0.022) with increasing skin type. Cumulative exposure per year in cancer patients with skin type 1 and 4 were significantly different (MannWhitney test P = 0.014) although there were no significant differences in exposure between men with skin type 1 and type 2 (P = 0.17), types 2 and 3 (P = 0.96). Exposure was significantly lower in men with skin type 3 than in those with skin type 4 (P = 0.048). A highly significant positive relationship between increasing exposure per year and skin type (P < 0.001) was also identified.
Skin type was also associated with sunbathing score in cancer cases (two-way ANOVA, P < 0.0001). Thus, the score increased with skin type; sunbathing score in men with skin type 1 was significantly lower than that in patients with skin type 2 (MannWhitney test, P = 0.009), in type 2 than type 3 (P = 0.001) but not in patients with skin types 3 and 4 (P = 0.36). Sunbathing score was significantly lower in men with skin type 1 than in those with skin type 4 (P = 0.0005). We found a significant positive relationship between increasing sunbathing score and skin type (P < 0.001).
Comparison of exposure per year and sunbathing score in cancer and BPH patients
Inspection of the data in Table I shows that both cumulative exposure per year and adult sunbathing score were lower in cancer than BPH patients in each of the skin type categories.
In the combined group of 765 cancer and BPH patients, skin type and being a cancer or BPH patient were both individually associated with exposure per year (two-way ANOVA; P = 0.008 and P < 0.001, respectively) and sunbathing score (both P < 0.001) (Table I). To assess the possible confounding effect of age at diagnosis, we repeated the analysis with inclusion of age as a continuous variable (analysis of covariance; ANCOVA). Table I shows that skin type and being a cancer case, but not age at diagnosis, were significantly associated with exposure/year and sunbathing score.
Skin type and prostate cancer risk
The data in Table I show that relative to BPH patients, the proportions of cancer cases with skin types 1 and 2 were lower while the proportion with skin types 3 and 4 were greater. We used logistic regression analysis (with inclusion of age at diagnosis as a main effect) to determine whether skin type was significantly associated with prostate cancer risk. The proportions of cancer and BPH patients in each skin type group were not significantly different although the difference between skin types 1 and 4 approached significance (P = 0.11, Table I). We obtained similar results when we used conditional logistic regression to study the association of skin type with risk in 290 age-matched pairs of men with cancer or BPH; relative to type 1, types 3 and 4 were associated with increased risk although the association was not significant (Table I).
Recursive partitioning to identify associations of skin type with prostate cancer risk
We used recursive partitioning to determine if skin type influenced prostate cancer risk in subgroups created by stratifying the total group of 765 cancer and BPH patients by parameters of exposure. The model comprised adult sunbathing score (minimum 2, maximum 12, mean 6.5), cumulative exposure per year (minimum 0.14 months, maximum 4.6 months, mean 1.3 months) and skin type. Figure 1 shows a classification tree with a parent node that contains all the observations in the 765 patients.
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The partitioning algorithm further stratified subjects in node 1 by skin type (Figure 1). Thus, 99/119 (83.9%) of men with an adult sunbathing score 3 who were skin types 2, 3 or 4 were cancer cases (node 1.2). Neither adult sunbathing score nor cumulative exposure per year significantly discriminated between cancer cases and BPH patients in node 1. Subjects in node 2 were stratified by skin types 1 and 2 (node 2.1) and 3 and 4 (node 2.2), no other parameter allowed significant stratification. Subjects in node 3 were stratified by cumulative exposure per year (>0.78 months). Partitioning by skin type did not allow significant discrimination of cases and controls in node 3 (P = 0.27).
Logistic regression analysis was used to determine the values of the age-corrected odds ratios describing the risks of prostate cancer for subjects with the different combinations of UVR-related parameters and skin type identified by recursive partitioning. In men with a sunbathing score 3, relative to those with skin type 1 (node 1.2), those with skin types 2, 3 and 4 (node 1.1) had a 4.78 times risk of prostate cancer (Figure 1). Similarly, in men with a sunbathing score >3
8, relative to those with skin type 1 or 2 (node 2.1), men with skin types 3 or 4 (node 2.2) had a 1.73 times risk of prostate cancer (Figure 1).
We performed further analyses to first, determine if partitions in Figure 1 were influenced by age and secondly, to assess their reproducibility. First, we studied a partitioning model that included exposure per year, sunbathing score, skin type and age at diagnosis. We obtained the same partitions as those in Figure 1; skin type 1 was associated with reduced risk relative to types 24, in men with sunbathing scores 3 (Bonferroni-corrected P = 0.006) and skin types 1 and 2 conferred reduced risk relative to types 3 and 4 in men with scores >3
8 (Bonferroni-corrected P = 0.05). Secondly, we used the facility in HelixTree software to effect random splitting of the 765 men into two groups of 382 and 383 men each comprising the same proportion of cancer and BPH patients. We repeated partitioning in each of these groups and found that relative to skin types 24, type 1 was associated with reduced risk in men with sunbathing scores
3 (group 1 P = 0.057, group 2 P = 0.003). In men with sunbathing scores >3
8, skin types 1 and 2 were associated with reduced risk of cancer compared with types 3 or 4 (group 1 P = 0.039, group 2 P = 0.061). We report uncorrected P values for these analyses, as significance was lost after Bonferroni correction.
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Discussion |
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We examined the role of skin type in determining prostate cancer risk by comparing its association with exposure in cancer and BPH patients. The BPH group was chosen because the diagnosis largely excludes concurrent prostate cancer. Both diseases are common and while they may coexist, data showing no increase in cancer risk in patients treated for BPH indicates their independence (21). Indeed, BPH originates in the transition zone of the gland while only 1020% of cancers develop in this region (26). BPH may be viewed as part of normal ageing as necropsy studies show that 50% of men aged 5160 years and >90% of men aged 80 years have the condition (26).
Response to UVR varies markedly and in the context of skin cancer risk there has been much interest in defining host characteristics that protect against the adverse effects of exposure (27). Ability to tan and susceptibility to burning have attracted particular attention. In Caucasians, the widely used Fitzpatrick scale combines assessment of these characteristics (18) although it can be criticized because there is no simple inverse correlation between burning and tanning (20). Individuals who never burn do not necessarily tan easily (20,27). Indeed, Harrison and Young (28) recently showed that while there was a trend between skin type and the lowest UVR dose that effects skin redness (minimal erythema dose, MED), there was considerable overlap. They concluded that skin type was a poor indicator of MED. However, the Fitzpatrick scale is useful as it also classifies individuals by ability to tan. In particular, subjects with skin type 1 are important as uniquely, they cannot tan effectively. Classifying individuals as skin types 1 or 4 is straightforward (19,20). Classifying subjects as types 2 or 3 is more problematical as individuals must compare their response to UVR with that of other individuals, and assess the responses of their skin to previous exposures (19,20). Skin type is a polygenic trait and studies showing associations with polymorphisms in the melanocortin 1 receptor (29) and p53 (30) genes suggest prostate cancer risk will be mediated by allelism in genes that determine this phenotype. Indeed, we found that polymorphic variants in the pigmentation-associated melanocortin 1 receptor and tyrosinase genes are linked with prostate cancer risk (11).
While many individuals with sun-sensitive skin will avoid UVR, Kricker et al. (19) found that 22% of subjects with highly sensitive skin who were outdoors on the preceding weekend reported being sunburnt. The relationship between prostate cancer risk, exposure and ability to tan is likely to be complex and it is not clear if skin type 1 confers increased risk because of sun avoidance or decreased risk because of more effective vitamin D synthesis.
We collected exposure data using a questionnaire. While exposure may be assessed by dosimetry using a device worn on an exposed part of the body, this method can only be used for short periods of time and recalled data must still be used to estimate lifetime exposure. Various questionnaires have been used to assess UVR exposure but none has gained universal acceptance implying it is a difficult parameter to measure. Our validated questionnaire has been used to show that high UVR exposure is linked with firstly, risk of non-melanoma skin cancer and solar keratoses and secondly, development of cutaneous squamous cell carcinoma in renal transplant patients (8,24,25). Nonetheless, we recognize that the exposure data is dependent on recall bias in often, elderly men.
The questionnaire records various aspects of exposure. We selected to use adult cumulative exposure per year and sunbathing score. Adult cumulative exposure per year is a marker of chronic UV exposure that provides a measure of occupational and recreational exposure. This continuous variable allows the possibility of thresholds to be investigated. Virtually all the men with very high levels of cumulative exposure had outdoor occupations. As holidays abroad are of relatively short duration they do not generally affect adult cumulative exposure. Time lived abroad in a sunny country may affect total exposure although in this study it was not a good indicator as all the men who had lived abroad, except for one, did so in the army. However, as it was a disciplinary offence to become sunburnt, there was an incentive to avoid exposure. Adult sunbathing was also selected as previous step-wise analysis (9), supported by the recursive partitioning analysis, showed that of the parameters recorded in the questionnaire, it is the best discriminator of cancer and BPH patients. This may reflect the large area exposed, some of which, such as the trunk, will generally be less pigmented than the face. Indeed, exposure of the trunk and legs results in greater increases in serum vitamin D than does exposure of the head, neck or arms (16). Importantly, cumulative exposure per year and sunbathing score assess distinct aspects of exposure; men with high levels of exposure may not sunbathe. Indeed, these parameters were not significantly correlated. There was no demonstrable effect on prostate cancer risk from sunscreen use although few men reported using them particularly when young. It was not possible to determine the effects of sun beds, as only one man (BPH patient) regularly used one.
We first determined whether exposure to UVR is linked with skin type. While studies on skin cancer risk predict that skin type 1 will be associated with less exposure than other types (19), this possibility needed to be examined in prostate cancer patients. In BPH patients, exposure per year and skin type were not linearly related although exposure in men with type 1 was lower than in those with type 4. Lower levels of exposure were more evident in BPH patients when sunbathing was considered. Thus, this score progressively increased with skin type. In cancer cases, there was a significant relationship between skin type and both cumulative exposure per year and adult sunbathing score. These findings are compatible with studies in skin cancer risk that suggest that subjects with skin types 1 and 2 adopt sun avoidance strategies compared with those with types 3 and 4. Importantly, in each of the skin type groups, values of the exposure parameters were higher in BPH than cancer patients. These findings support our previous studies showing that UVR confers protection against development of this cancer (8). The data also indicate that it is difficult to define a universal safe level of exposure. Thus, sunbathing score in BPH patients with skin type 1 was lower than in cancer cases with type 4. This finding suggests that host characteristics, possibly related to efficiency of vitamin D synthesis, determine the level of UVR needed to prevent cancer development.
In the second analysis we determined whether skin type was associated with prostate cancer risk. In the total cancer and BPH groups, we found that relative to skin type 1, men with type 4 were at increased risk (OR = 1.70) although the difference was not statistically significant. However, given the relatively low proportion of men with skin type 1, we accept that our study may lack power and that this phenotype should not be discounted as a marker of prostate cancer risk.
We used recursive partitioning to examine the hypothesis that the association of skin type with risk is more evident in men grouped by levels of exposure. In particular, we wished to determine the influence of the phenotype on risk in men with low levels of cumulative exposure per year or sunbathing (8,9). While HelixTree software permits operator-selection of the levels of parameters used to effect partitioning, we allowed the partitioning algorithm to select on the basis of P values, low, intermediate and high sunbathing scores, as the partition that best separated cancer from BPH patients. Thus, while it was possible to choose particular values of variables for partitioning, we used the data-driven values selected by the algorithm as they were compatible with our a priori hypothesis. We recognize that partitions other than that shown in Figure 1 can be obtained by selecting different values or order of the selected variables. Accordingly, the resulting age-corrected odds ratios must be considered descriptive and interpreted with caution. However, we believe the approach is valid as results of these analyses support previous studies showing that low levels of UVR increase prostate cancer risk (8,9). Further, the robustness of the approach is indicated by analyses in which partitioning was repeated in two randomly selected sets of cancer and BPH patients. These analyses showed that in men with low adult sunbathing scores (3), those with skin types 2, 3 and 4 were at increased risk relative to those with type 1. The increased risk associated with skin types that confer effective pigmentation was also observed in men with intermediate levels of sunbathing (score >3
8), although their impact was less than in men with lower levels of sunbathing. In men with higher levels of sunbathing (score>8), skin type did not allow significant partitioning.
These findings suggest that at low levels of exposure, an inability to pigment is advantageous because it allows some UVR-initiated, cutaneous vitamin D synthesis. They are also compatible with the view that case groups are heterogeneous and variables are likely to exert an effect only in subgroups (22,23,31). The data also support our suggestion that moderate exposure to UVR is sufficient to reduce prostate cancer risk (8). This conclusion is compatible with data showing that cutaneous vitamin D synthesis does not increase linearly with duration of exposure. Indeed, continued irradiation results in conversion of pre-vitamin D3 and vitamin D3 into steroids with no vitamin D activity (14,15). These findings together with data showing that in Caucasians, exposure for periods as short as 15 min will allow adequate vitamin D synthesis indicate that regular short-term exposure may be sufficient for reduction of cancer risk. Thus, excess exposure, particularly the burning linked with skin cancer risk can be avoided (27). More deeply pigmented individuals require more exposure to ensure synthesis of sufficient vitamin D. Skin type and extent of pigmentation are important adaptive traits that mediate UVR penetration in the integument. Skin colour is a compromise between latitude, extent of exposure and conflicting requirements of photoprotection against UVR-induced photolysis of key chemicals such as folate and adequate synthesis of vitamin D (32). It is possible therefore, that the associations we have observed between exposure, skin type and risk of prostate cancer are found only in men from northerly latitudes with relatively restricted exposure to UVR.
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Acknowledgments |
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References |
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