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ORIGINAL ARTICLE
Year : 2018  |  Volume : 14  |  Issue : 12  |  Page : 1152-1157

Detection of urinary trace elements and pattern recognition analysis in patients with renal cell carcinoma by inductively coupled plasma mass spectrometry


1 Department of Urology and Center of Urology, The First Affiliated Hospital of Xiamen University, Xiamen, China
2 Department of Chemistry, Key Laboratoryof Analytical Sciences, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China

Date of Web Publication11-Dec-2018

Correspondence Address:
Jinchun Xing
Department of Urology and Center of Urology, The First Affiliated Hospital of Xiamen University, No. 55 Zhenhai Road, Xiamen 361003
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0973-1482.204902

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 > Abstract 


Objective: This study aims to observe the changes and diagnostic values of urinary trace elements in patients with renal cell carcinoma (RCC).
Methods: A total of 28 RCC patients that had been performed radical surgery for more than 3 years were included into this case–control study; meanwhile, thirty healthy volunteers without kidney diseases were set as the control group over the same period. The levels of various urinary trace elements in both groups were measured, and the results were performed the significance analysis and pattern recognition analysis using with partial least square discriminant analysis and Fisher analysis.
Results: The significance analysis showed that compared with the control group, the case group exhibited significantly reduced levels of Mg (26.3 mg/L for the case group vs. 52.1 mg/L for the control group, P < 0.05), V (72.9 μg/L for the case group vs. 110.1 μg/L for the control group, P < 0.05), Mo (59.6 μg/L for the case group vs. 261.7 μg/L for the control group, P < 0.05), and Sn (4.5 μg/L for the case group vs. 27.3 μg/L for the control group, P < 0.05) while significantly increased Cd (25.0 μg/L for the case group vs. 15.5 μg/L for the control group, P < 0.05). The accuracy of the discriminant function established by the Fisher analysis was 91.4%.
Conclusions: Patients with RCC exhibit differences in such urinary trace elements as Mg, V, Mo, Sn, and Cd with healthy populations, and the discriminant accuracy is high.

Keywords: Discriminant analysis, kidney neoplasms, mass, spectral analysis, trace elements


How to cite this article:
Zheng J, Chen B, Liu R, Wang H, Xing J, Hang W. Detection of urinary trace elements and pattern recognition analysis in patients with renal cell carcinoma by inductively coupled plasma mass spectrometry. J Can Res Ther 2018;14, Suppl S5:1152-7

How to cite this URL:
Zheng J, Chen B, Liu R, Wang H, Xing J, Hang W. Detection of urinary trace elements and pattern recognition analysis in patients with renal cell carcinoma by inductively coupled plasma mass spectrometry. J Can Res Ther [serial online] 2018 [cited 2019 Apr 19];14:1152-7. Available from: http://www.cancerjournal.net/text.asp?2018/14/12/1152/204902




 > Introduction Top


Excessive exposure to or insufficiency of trace elements, which have known physiological functions in humans, may lead to pathological conditions.[1],[2] Among these trace elements, such essential elements as Cr, Mg, Mn, and Zn are necessary for many metabolic processes, and their homeostasis is crucial for life, but toxic metals, such as Cd and Pb, have no beneficial roles in human metabolism or even can be harmful.[3] Hence, any disorders of these elements will affect the organs and result in damages.[4],[5] Usually, As, Cd, and Ni are defined as carcinogenic trace elements while Se and Zn are defined as anticarcinogenic trace elements.[6],[7]

Bivalent metal cations are key components in DNA synthesis, which are necessary for all DNA polymerases and involved in DNA damage.[8] If metal cation unbalance occurs, DNA damages, as well as replication disturbance and mutations, will happen, and sometimes even lead to cancer and other diseases,[9] such as diabetes,[10] cardiovascular disease,[11] or Alzheimer disease.[12]

The roles of trace elements in the occurrence, development, and prevention of malignant cancers have attracted Chinese and foreign researchers' attention. Since aging is associated with an increasing incidence of cancer, one study analyzed elementary in animal furs, and the results showed that aging reduces the content levels of Co, K, and Se; meanwhile, the content levels of Al, As, B, Hg, Mo, and Ti are elevated.[13]

So far, however, studies about the relationships between trace elements and tumors have quite inconsistent conclusions, and though International Agency for Research on Cancer and the National Toxicology Program both agreed that Cr, Ni, and As are category 1 carcinogens that can increase cancer risks, whereas recent research thinks that exposing to Ni and As is not positively correlated with lung cancer.[14],[15] It was considered traditionally that Se and Zn have anticancer effects, but it has been challenged now, and some scholars believe Se and Zn have no significant correlation with the occurrence of tumors, and some scholars even believe that Zn supplementation can increase the incidence of prostate cancer by 2.9 times.[16],[17] This suggests the complexity of the relationships between cancer and trace elements; therefore, experiments need to further optimized and designed so as to study the relationships between trace elements and tumors. The etiology of renal cell carcinoma (RCC) is still not fully understood, which may be related to age, smoking, drugs, hormones, coffee, viral infection, radiation exposure, heredity, or trace elements. This study used inductively coupled plasma mass spectrometry (ICP-MS) to detect the urinary trace elements in RCC patients and healthy controls, and pattern recognition analysis was also performed toward trace elements, aiming to explore the relationships between trace elements and RCC and to analyze their clinical significance.


 > Methods Top


Clinical data

A total of 28 RCC patients resided locally for more than 3 years and treated in our hospital from 2007 to 2010 were selected, including 17 males and 11 females, aging 33–72 years, with the mean age as 53.5 years. All the patients had received RCC radical surgery, and their pathological results revealed 25 cases of RCC, 1 case of renal granular cell carcinoma, and 2 cases of renal papillary cell carcinoma. Pathological grading: 22 cases in Farhinan Grade I, 4 cases in Grade II, and 2 cases in Grade III–IV. All the patients were excluded other liver or renal chronic diseases as well as cardiovascular and endocrine diseases.

Thirty healthy volunteers underwent health inspection in the same period were selected as the control group, aging 30–70 years, with the mean age as 51.4 years. All the volunteers had lived locally for more than 3 years, without history of metal exposure, liver, kidney, or endocrine diseases and did not take steroids within the past 3 years.

Urine sampling

To reduce pollution, fresh morning urine was collected into 5% (v/v) HNO3-washed polypropylene bottles and stored at −80°C.

Sample preparation

Before the detection, the urine samples were thawed at room temperature, and centrifuged for 5 min (8000 rpm, 4°C); 400 μl of the supernatant was then added with 20 μl of 1 mg/L Rh internal standard solution, and then the volume was made up to 2.0 ml with 2% HNO3.

Graphing of standard curve

According to the approximate contents of the trace elements in human urine, standard stock solutions were used to prepare a series of mixed standard solutions so as to graph the made the standard curve.

Instrument coordination and interference elimination

To ensure the accuracy and stability of the measurements, the instrument was optimized using the 10 μg/L mixed standard solution of Li, Y, Ce, and Tl. The blank and the samples were then continuously detected. The optimized instrument conditions and the appropriate interference correction equations were then used to correct the interferences due to oxides, dual-charged substances, or mass discrimination.

Determination of samples

HP 4500 ICP-MS Analyzer (Agilent, USA) was used to detect the samples with the internal standard method.

Statistical analysis

SPSS 15.0 (SPSS Inc., Chicago, IL, USA) statistical software was used for the data processing. The Shapiro–Wilk test was first performed to test the data's normality, and those normally distributed were compared with the t-test, otherwise used the nonparametric Mann–Whitney U-test for the comparison, with P < 0.05 considered as statistically significant. SIMCA-P v11 (Umetrics Inc., San Jose, CA, USA) and SPSS 15.0 were used for further multivariate analysis, and the partial least square discriminant analysis (PLS-DA) and the Fisher discriminant analysis were used to perform pattern recognition analysis toward the detection results of urinary trace elements.


 > Results Top


The limits of detection and stability

Under the optimized instrument conditions, the blank solution was tested 10 times repeatedly, with the element concentration corresponding to the three times (3σ) of standard deviation as limit of detection (LOD); the detection ranges were 0.003 μg/L (Li)–2.986 μg/L (Ti).

The detection was repeated once every 1 h within 10 h at room temperature, and the measurement values obtained at 20 min and 4 h were used to represent the short-term and long-term stabilities; the relative standard deviation of 20 min was 0.80%–4.66% and that of 4 h was 0.35%–6.68%.

Precision and accuracy

The precision and accuracy of the detection were verified by the quality control methods. The intraday coefficient of variation, based on the continuous 10-time detections of the same sample, ranged within 0.76%–4.69%, and the interday coefficient of variation, based on the 10-time detections of ten different samples in different days, ranged within 1.08%–14.18%; the recovery rate ranged within 89.00%–113.00%.

To further verify the accuracy and precision of method, this study analyzed the standard reference of urine (Billingstad Company, LOT 0511545, Norway), and the results were in good agreement with the reference values [Table 1], indicating that the LOD, stability, precision, accuracy, etc., of the instruments and detection method, were suitable for the rapid high-throughput detection of trace elements in clinical urine.
Table 1: Analytical results and reference values of trace element content in urine nominal sample (LOT 0511545)

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Determination of trace elements

Among these urinary samples, only Cu, Cr, Mn, and V exhibited normal distribution, but As, Ca, Cd, Co, Cr, Fe, Li, Mg, Ni, Mo, Se, Sn, and Zn exhibited skewed distribution, which was consistent with the distributions of most biological indexes in vivo.[18]

The contents of Mg, V, Li, Cr, As, Se, Mo, and Sn in the RCC patients were lower than those in the control group (P < 0.05), but the Cd content was significantly higher (P < 0.05) [Table 2], [Table 3] and [Figure 1].
Table 2: Determination of trace elements in the two groups (skewed distribution)

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Table 3: Determination of trace elements in the two groups (normal distribution)

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Figure 1: Box plots of urine concentration distributions of Mg (a), V (b), Mo (c), Li (d), Cr (e), Cd (f), As (g), Se (h) and Sn (i) in renal cell carcinoma patients and controls. Note: the ordinate represents the element concentration, and the abscissa represents the comparison between the control and the renal cell carcinoma patients, controls: healthy volunteers, patients: renal cell carcinoma patients, 1 ppm = 1 mg/L; 1 ppb = 1 μg/L; 1 ppt = 1 ng/L

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Pattern recognition analysis of urinary trace elements

The PLS-DA results obtained from the SIMCA-P software were shown in [Figure 2]. [Figure 2] shows that the contents of urinary trace elements in the RCC patients were significantly different from those in the control group, and most points of these two parts can be separated in the graph, with R2Y (cum) = 0.76 and Q2 (cum) = 0.64, which are both ideal. The samples obtained from normal populations and RCC patients were grouped into two categories, and those of the RC patients significantly deviate from the control group.
Figure 2: Partial least square discriminant analysis results of urinary trace elements in the two groups. The rhombus is renal cell carcinoma patient and square is control group

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In SPSS 15.0, the Fish discriminant analysis found that Ca, Fe, Cu, Li, As, and Sn exhibited significant discriminant abilities, and their standard coefficients were −2.124, 2.388, −0.625, 0.381, 0.422, and 0.853, respectively, which represented the impacts of these six elements toward the function; their standardized discriminant functions (canonical correlation coefficient = 0.847, Wilks' Lambda test, P < 0.001) were as follows: D = −2.124 Ca + 2.388 Fe − 0.625 Cu + 0.381 Li + 0.422 As + 0.853 Sn.

The discriminant function was then transferred to nonstandardized canonical discriminant function: D = −0.103 Ca + 0.004 Fe − 0.003 Cu + 0.012 Li + 0.004 As + 0.069 Sn − 1.432.

According to this equation, the center scoring point of the RC group was −1.622, but that in the control group was 1.514. Because this study was two-category discrimination with 0 as the cutoff point, if certain person's serum Ca, Fe, Cu, Li, As, and Sn values were input into the function, and the discriminant score obtained was <0, this person had greater likelihood of being one RCC patient, otherwise this person can be determined to be healthy. The further interactive verification of this discriminant function revealed the total discriminant accuracy as 91.4%, sensitivity as 96.4%, and specificity as 86.6%.


 > Discussion Top


Trace elements play important roles in metabolic processes and growth processes of organisms. Trace elements with appropriate amounts are necessary for human health, participate in biosynthesis in vivo, and directly affect the synthesis of nucleic acids and proteins; furthermore, they can also enhance immunity. Too much or too little trace elements in vivo can cause diseases and even cancers.[19]

In this study, the univariate significance test revealed that the urinary amounts of Mg, V, Li, Cr, As, Se, Mo, and Sn in the RCC patients were significantly lower than the control group. Mg, V, Li, Se, Mo, and Sn are important trace elements in vivo, and experimental studies have clinically demonstrated their in vivo anticancer effects, consistent with the results of this study. Geographical research also confirms the Se concentration in vivo is negatively correlated with cancer mortalities;[20] the subsequent studies confirm that Se is one powerful inhibitor toward breast cancer, liver cancer, skin cancer, colon cancer, lung cancer, bladder cancer, and prostate cancer.[21],[22],[23],[24],[25],[26] Mg is a necessary trace element in vivo and acting as an auxiliary ion; it plays key roles in many essential enzyme reactions, such as participating in the synthesis and degradation of DNA and participating in the synthesis of proteins. Li is a necessary trace element in vivo, plays important roles through participating in many biochemical reactions in vivo; furthermore, it can enhance the body's immune system by stimulating the proliferation of lymphocytes;[27] meanwhile, it can inhibit the cell line proliferation of esophageal cancer and thyroid follicular cell carcinoma.[28] V compound can fight against toxic metabolites produced by carcinogens in vivo so as to achieve the anti-cancer effects.[29] Mo is an important component of the three enzyme systems in human and can catalyze reactions, thus being closely related to the formation of uric acid, iron usage, carbohydrate metabolism, and sulfite detoxification. Epidemiological surveys have shown that low-Mo geological environment is associated with the incidence of esophageal cancer.[30] The deficiency of such anti-cancer elements as Mg, V, Li, Se, Mo, and Sn in RCC patients may promote the development and progression of tumors.

Cd, Cr, and As have long been considered to have significant carcinogenic effects, if more Cd accumulates in RCC patients, it may have some correlations with the occurrence of cancer. Experimental studies and epidemiological studies have confirmed that as a carcinogen, Cd can act on human bodies through the genetic toxicity mechanism, which included inducting oxidative stress, breaking DNA single strand, or activating oncogenes. Studies have confirmed that Cd has impacts on liver, lung, prostate, and reproductive system.[31] Cd can activate the signaling pathways in breast cancer cells, such as activating the protein kinase C, thereby stimulating the growth of cancer cells. This study revealed that the urinary contents of Cr and As were reduced, contrast to most studies, and it cannot rule out such reasons as small sample size, diet, or environmental impacts, so this requires further experiments to confirm the in vivo metabolic pathways of Cr and As, and further expand the sample size for the analysis.

Trace elements have synergistic and antagonistic effects among them. Therefore, the conclusions obtained through the single-factor significant test cannot explain the relationships between trace elements and RCC, and this study used the pattern recognition method to categorize and study the RCC patients and normal controls. The PLS-DA and Fisher discriminant analysis can successfully distinguish the urine samples of RCC patients and controls, indicating that the in vivo metabolic patterns of trace elements between the two groups have significant differences; therefore, detecting the in vivo levels of trace elements can discriminate RCC patients from normal healthy populations, and thus providing the basis for the early diagnosis of RC. However, it should also be noted that the contents of urinary trace elements are related to a variety of factors, such as gender, perimenopause status in women, age, or different levels and types of tumors. This study failed further stratification study due to the small sample size and evaluating the authenticity of diagnostic test also requires larger sample sizes; therefore, we will expand the sample size in our next step as well as optimizing the experimental designs.

This study used ICP-MS as a detection means, together with pattern recognition analysis, to study the differences of trace elements between RCC patients and normal controls, and successfully distinguished the urine samples of RCC patients from healthy controls, thus realizing the discriminant analysis of RCC and providing some basic theoretical research for the early diagnosis, prevention, and pathogenic mechanism research of RCC. The diversities of trace elements and their multiple relations with tumors indicate the complexity between trace elements and tumors, which still needs to increase the sample size in future studies, and optimize experimental designs so as to reveal the relationships between trace elements and cancers.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
 > References Top

1.
Farina M, Avila DS, da Rocha JB, Aschner M. Metals, oxidative stress and neurodegeneration: A focus on iron, manganese and mercury. Neurochem Int 2013;62:575-94.  Back to cited text no. 1
    
2.
Gee JB 2nd, Corbett RJ, Perlman JM, Laptook AR. Hypermagnesemia does not increase brain intracellular magnesium in newborn swine. Pediatr Neurol 2001;25:304-8.  Back to cited text no. 2
    
3.
Afridi HI, Kazi TG, Brabazon D, Naher S, Talpur FN. Comparative metal distribution in scalp hair of Pakistani and Irish referents and diabetes mellitus patients. Clin Chim Acta 2013;415:207-14.  Back to cited text no. 3
    
4.
Fairweather-Tait SJ, Cashman K. Minerals and trace elements. World Rev Nutr Diet 2015;111:45-52.  Back to cited text no. 4
    
5.
Lind PM, Olsén L, Lind L. Circulating levels of metals are related to carotid atherosclerosis in elderly. Sci Total Environ 2012;416:80-8.  Back to cited text no. 5
    
6.
Wadhwa SK, Kazi TG, Afridi HI, Talpur FN, Naeemullah. Interaction between carcinogenic and anti-carcinogenic trace elements in the scalp hair samples of different types of Pakistani female cancer patients. Clin Chim Acta 2015;439:178-84.  Back to cited text no. 6
    
7.
Kazi TG, Wadhwa SK, Afridi HI, Talpur FN, Tuzen M, Baig JA. Comparison of essential and toxic elements in esophagus, lung, mouth and urinary bladder male cancer patients with related to controls. Environ Sci Pollut Res 2015;22:7705-15.  Back to cited text no. 7
    
8.
Gening LV, Lakhin AV, Stelmashook EV, Isaev NK, Tarantul VZ. Inhibition of Mn(2+)-induced error-prone DNA synthesis with Cd(2+) and Zn(2+). Biochemistry (Mosc) 2013;78:1137-45.  Back to cited text no. 8
    
9.
Liu B, Xue Q, Tang Y, Cao J, Guengerich FP, Zhang H. Mechanisms of mutagenesis: DNA replication in the presence of DNA damage. Mutat Res Rev Mutat Res 2016;768:53-67.  Back to cited text no. 9
    
10.
Gouaref I, Bellahsene Z, Zekri S, Alamir B, Koceir EA. The link between trace elements and metabolic syndrome/oxidative stress in essential hypertension with or without type 2 diabetes. Ann Biol Clin (Paris) 2016;74:233-43.  Back to cited text no. 10
    
11.
Mordukhovich I, Wright RO, Hu H, Amarasiriwardena C, Baccarelli A, Litonjua A, et al. Associations of toenail arsenic, cadmium, mercury, manganese, and lead with blood pressure in the normative aging study. Environ Health Perspect 2012;120:98-104.  Back to cited text no. 11
    
12.
Walton JR. Aluminum involvement in the progression of Alzheimer's disease. J Alzheimers Dis 2013;35:7-43.  Back to cited text no. 12
    
13.
Ambeskovic M, Fuchs E, Beaumier P, Gerken M, Metz GA. Hair trace elementary profiles in aging rodents and primates: Links to altered cell homeodynamics and disease. Biogerontology 2013;14:557-67.  Back to cited text no. 13
    
14.
Sivulka DJ, Seilkop SK. Reconstruction of historical exposures in the US nickel alloy industry and the implications for carcinogenic hazard and risk assessments. Regul Toxicol Pharmacol 2009;53:174-85.  Back to cited text no. 14
    
15.
Chen Y, Ahsan H. Cancer burden from arsenic in drinking water in Bangladesh. Am J Public Health 2004;94:741-4.  Back to cited text no. 15
    
16.
Lipsky K, Zigeuner R, Zischka M, Schips L, Pummer K, Rehak P, et al. Selenium levels of patients with newly diagnosed prostate cancer compared with control group. Urology 2004;63:912-6.  Back to cited text no. 16
    
17.
Wong PF, Abubakar S. LNCaP prostate cancer cells are insensitive to zinc-induced senescence. J Trace Elem Med Biol 2008;22:242-7.  Back to cited text no. 17
    
18.
Silva MP, Tomal A, Pérez CA, Ribeiro-Silva A, Poletti ME. Determination of Ca, Fe, Cu and Zn and their correlations in breast cancer and normal adjacent tissues. Xray Spectrom 2009;38:103-11.  Back to cited text no. 18
    
19.
Sarmiento-González A, Marchante-Gayón JM, Tejerina-Lobo JM, Paz-Jiménez J, Sanz-Medel A. ICP-MS multielemental determination of metals potentially released from dental implants and articular prostheses in human biological fluids. Anal Bioanal Chem 2005;382:1001-9.  Back to cited text no. 19
    
20.
Kieliszek M, Blazejak S. Current knowledge on the importance of selenium in food for living organisms: A review. Molecules 2016;21. pii: E609.  Back to cited text no. 20
    
21.
Singh P, Kapil U, Shukla NK, Deo S, Dwivedi SN. Association between breast cancer and Vitamin C, Vitamin E and selenium levels: Results of a case-control study in India. Asian Pac J Cancer Prev 2005;6:177-80.  Back to cited text no. 21
    
22.
Huff J. Selenium supplementation and secondary prevention of nonmelanoma skin cancer in a randomized trial. J Natl Cancer Inst 2004;96:333-4.  Back to cited text no. 22
    
23.
Combs GF Jr. Status of selenium in prostate cancer prevention. Br J Cancer 2004;91:195-9.  Back to cited text no. 23
    
24.
Kellen E, Zeegers M, Buntinx F. Selenium is inversely associated with bladder cancer risk: A report from the Belgian case-control study on bladder cancer. Int J Urol 2006;13:1180-4.  Back to cited text no. 24
    
25.
Majewska U, Banas D, Braziewicz J, Gózdz S, Kubala-Kukus A, Kucharzewski M. Trace element concentration distributions in breast, lung and colon tissues. Phys Med Biol 2007;52:3895-911.  Back to cited text no. 25
    
26.
Kubala-Kukuś A, Banaś D, Braziewicz J, Góźdź S, Majewska U, Pajek M. Analysis of elemental concentration censored distributions in breast malignant and breast benign neoplasm tissues. Spectrochim Acta B 2007;62:695-701.  Back to cited text no. 26
    
27.
Wang JS, Wang CL, Wen JF, Wang YJ, Hu YB, Ren HZ. Lithium inhibits proliferation of human esophageal cancer cell line Eca-109 by inducing a G2/M cell cycle arrest. World J Gastroenterol 2008;14:3982-9.  Back to cited text no. 27
    
28.
Camacho CP, Latini FR, Oler G, Hojaij FC, Maciel RM, Riggins GJ, et al. Down-regulation of NR4A1 in follicular thyroid carcinomas is restored following lithium treatment. Clin Endocrinol (Oxf) 2009;70:475-83.  Back to cited text no. 28
    
29.
Kostova I. Titanium and vanadium complexes as anticancer agents. Anticancer Agents Med Chem 2009;9:827-42.  Back to cited text no. 29
    
30.
Farzin L, Moassesi ME, Amiri M, Shams H. Spectroscopic studies on molybdenum and zinc levels in fingernails of patients with esophagus cancer. J Biol Res (Thessalon) 2008;9:107-11.  Back to cited text no. 30
    
31.
Thompson J, Bannigan J. Cadmium: Toxic effects on the reproductive system and the embryo. Reprod Toxicol 2008;25:304-15.  Back to cited text no. 31
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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