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Residue Content of Organophosphorus Pesticides and their Toxic Metabolites in Greenhouse-Grown Tomatoes during Pre-Harvest Interval and Post-Harvest Processing: A Kinetic Study

Reza Shokoohi1, Mohammad Taghi Samadi1, Manoochehr Karami2, Ali Heshmati3, Mostafa Leili4 and Samira Khamutian4,*

  1. Department of Environmental Health Engineering, Research Center for Health Sciences, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran
  2. Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
  3. Department of Nutrition and Food Hygiene, School of Medicine, Nutrition Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
  4. Department of Environmental Health Engineering, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran

 

* Corresponding author: Samira Khamutian, Department of Environmental Health Engineering, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran. Email: skhamutian@yahoo.com

 

Received 2020 October 29; Revised 2020 November 27; Accepted 2020 December 14.

 

Abstract

Background: Organophosphorus pesticides (OPPs) have a wide application throughout the world and exert adverse effects on human health. Moreover, these chemical compounds are responsible for thousands of deaths per year worldwide. Kinetic and mathematical models could be used to optimize the application of pesticides on fruits and vegetables and monitor their residues.  

Objectives: The present study aimed to model the dissipation of diazinon and chlorpyrifos in different conditions, such as household conditions (e.g., storage at room and refrigerator temperatures, as well as cooking) and field condition for greenhouse tomatoes.

Methods: A multi-residue analysis of diazinon, chlorpyrifos, and their oxon derivatives was established by gas chromatography-tandem mass spectrometry. The limit of quantification (LOQ), recovery, precision, linearity, and the limit of detection (LOD) were evaluated to ensure that the method was able to effectively determine the studied pesticides in the tomato samples. The linear and nonlinear kinetic models were presented for chlorpyrifos and diazinon residues in tomato using zero-order, first-order, and second-order equations.

Results: Based on the best fitting models for diazinon in the case of laboratory treatment at the refrigerator, room, and boiling temperatures, the half-lives were calculated as 18.79 days, 11.41 days, and 45.39 min, respectively. The half-life of diazinon was lower than that of chlorpyrifos in both field and laboratory treatments.

Conclusion: Modeling the removal of the pesticides indicated that the nonlinear first- and second-order models were the best fitted models for the dissipation of both pesticides in field and post-harvest conditions.

 

Keywords: Chlorpyrifos oxon, Dissipation kinetic, Nonlinear model


1. Background

Organophosphorus pesticides (OPPs) have a wide application across the globe. These compounds inhibit acetylcholine esterase which results in the uncontrolled firing of neurons, the loss of asphyxiation respiratory control, and finally death (1,2). Moreover, they exert other adverse effects on human health due to their immunosuppressive, cytotoxicity, mutagenicity, and endocrine-disrupting properties. They are also associated with decreased average birth weight. These chemical compounds are responsible for thousands of deaths per year worldwide (3,4). 

The degradation, transformation, and dissipation of insecticide residues in stored foods considerably depend on light, temperature, food type, and moisture content. OPPs, including diazinon and chlorpyrifos, reach their greatest toxicity by oxidative desulfurization (4,5). Among their metabolite components, chlorpyrifos oxon has been shown to be 100 times more toxic than chlorpyrifos, whereas diazoxon is 10 times more lethal than diazinon (6,7). As reported by the World Health Organization (WHO), dietary exposure to insecticide residues is almost five times higher, compared to exposure through air or drinking water (8). Lycopersicon esculentum (tomato) as one of the widely consumed fruits in the world is among the 10 most pesticide-contaminated fruits and vegetables. The consumption of tomatoes varies across different countries. For instance, the annual tomato consumption per capita in the USA, Sweden, Germany, and Iran were recorded as 9.5, 10, 25, and 62.2 kg, respectively (9,10).

Kinetic and mathematical models could be used to optimize the application of pesticides on fruits and vegetables and monitor their residues. A kinetic model of pesticide dissipation can help predict the half-lives of pesticides for the estimation of their final residue levels in different conditions, including pre-and post-harvesting. 'Half-life' is described as the time it takes to remove 50% of a substance and demonstrates the persistence of a pesticide (11-14). The validation of the methods (including the assessment of the linearity of the analytical curve, accuracy, precision, the limits of detection and quantification, and recovery) perform a peculiar role in trace analysis. Therefore, a preliminary phase of contamination monitoring in fruits and vegetables should be designed for the validity of the method (15,16).

The previously conducted studies have mainly focused on primary compounds, and only a few of them have addressed their metabolites.


2.Objectives

The present study aimed to model the dissipation of diazinon, chlorpyrifos, and their oxon derivatives in different conditions (including pre-and post-harvest conditions) and assess the interactions among the independent variables.


3.Methods

3.1. Reagents and materials

Chlorpyrifos (diethoxy-sulfanylidene-(3, 5, 6-trichloropyridin-2-yl) oxy-λ5-phosphane) and diazinon (diethoxy-(6-methyl-2-propan-2-ylpyrimidin-4-yl) oxy-sulfanylidene-λ5-phosphane) were purchased from Sigma-Aldrich. Chlorpyrifos oxon (diethyl (3, 5, 6-trichloropyridin-2-yl) phosphate) was provided by Dr. Ehrenstorfer (Augsburg, Germany). Diazoxon (diethyl (6-methyl-2-propan-2-ylpyrimidin-4-yl) phosphate) was obtained from Toronto Research Chemicals (Toronto, Canada). Sodium chloride, trisodium citrate dihydrate, disodium hydrogen citrate, magnesium sulfate, PSA (primary-secondary amine), formic acid, acetonitrile, ethyl acetate, methane, and TPM (Triphenylmethane ) were of analytical and HPLC (high-performance liquid chromatography) grade and were acquired from Sigma-Aldrich (Switzerland).

3.2. Standard and working solutions

About 10 mg chlorpyrifos, diazinon, chlorpyrifos oxon, and diazoxon were dissolved with ethyl acetate in a 10 mL volumetric balloon in order to reach the concentration of 1000 mg/L. The stock solution was kept at -20°C. The working solutions were made by diluting 250 µL of the standard solution with ethyl acetate in a 25 mL volumetric balloon in order to obtain a concentration of 10 ppm. Appropriate dilutions were used to prepare the calibration curves for the gas chromatography-mass spectrometry (GC/MS) analysis.

3.3. Sample collection

The experiments were conducted in Amzajerd greenhouses located in Hamadan from November-December 2018. The field trials were performed on experimental plots of tomato plants. Two treatments with chlorpyrifos (40.8% EC) and diazinon (60% EC) at the recommended dosages of 2/1000 and 1/1000 were applied to determine the dissipation kinetics under laboratory and greenhouse conditions. The tomato samples were randomly picked 2 hours, as well as 1, 3, 7, 10, and 21 days after pesticide application. After being harvested, the tomato samples were transported to the laboratory for further analyses.

In addition, to investigate the dissipation pattern of the pesticides for the post-harvested tomatoes, the harvested samples were separately collected and stored in the laboratory for different analyses 2 h after spraying. The tomato samples were analyzed for diazinon, chlorpyrifos, and their oxon derivatives at room temperature on days 1, 2, 3, and 5, at refrigerator temperature on days 1, 3, 5, and 7, and at boiling temperature after 5, 30, and 45 min, as well as 1 and 2 h.

3.4. Sample preparation

The extraction of the samples was performed by a modified QuEChERS method (17).  The top layers of the samples were transferred to 5 mL centrifuge tubes and were acidified with 10 µL formic acid (5%). The solution was evaporated to dryness and dissolved with methane to 1 mL. Finally, the methane solution was analyzed by GC-MS/MS.

3.5. Instrumentation

The qualification analyses of both pesticides and their degradation products were performed using a gas chromatograph (Agilent 7890, UK) coupled with a tandem mass spectrometer. An autosampler (Shimadzu, Japan) was utilized to inject the sample solution (1 µL) in the splitless mode. A silica capillary column coated with diphenyl-methyl polysiloxane was used as the stationary phase for separation in GC. Perfluoro tributylamine (PFTBA) was employed for the calibration of the MS spectrometer. The temperature program of GC was set in the following way: the initial temperature of 75oC was kept for 4 min and increased up to 120oC with the time rate of 25oC/min. Thereafter, it increased up to 300oC with the time rate of 50oC/min and was kept for 7 min. The inlet temperature, the flow gas, and the interface temperature were 250oC, 3 mL/min, and 280oC, respectively. The multi-reaction monitoring mode was applied for all of the compounds (diazinon, chlorpyrifos, and their oxon derivatives).

3.6. Validation study

The European Health and Consumer Guidelines were employed for the validation study (18).  The limit of quantification (LOQ), recovery, precision, linearity, the limit of detection (LOD), and specificity of these compounds were evaluated to ensure that the method was able to effectively determine chlorpyrifos, diazinon, and their oxon derivatives in the tomato samples. The absolute recovery and relative standard deviations (RSD) of chlorpyrifos, diazinon, chlorpyrifos oxon, and diazoxon were obtained by investigating the spiked samples at three

 

Table 1. Limit of quantification, limit of detection, and regression equation for the studied pesticides

MRL

mg/kg

R2

Regression equation

LOD

mg/kg

LOQ

mg/kg

Insecticide

0.5

0.9965

y=47.377x+758.56

0.0277

0.083

Chlorpyrifos

0.05

0.9955

y=31.169x+10.198

0.015

0.0478

Chlorpyrifos oxon

0.05

0.9934

y=11.626x+70.742

0.00308

0.0103

Diazinon

0.05

0.9936

y=244.88x-615.3

0.01226

0.039

Diazoxon

 

Figure 1. Standard calibration curves for the analyses

 

different levels (75, 100, and 125 μg/kg) on three different days.

The LOD and LOQ were calculated at the lowest concentrations of the analysis and yielded peaks with the signal/noise ratios of 3 and 10, respectively. The LOQ is the lowest concentration and has an acceptable precision (RSD≤ 20%) and recovery (70%-120%). The LOQs determined for this method were lower than those set by Iranian national standards for the above-mentioned pesticides in tomato (Table 1). The calibration curves of the peak area versus the concentrations of diazinon, chlorpyrifos, diazoxon, and chlorpyrifos-oxon were constructed using eight concentration levels (5, 10, 25, 50, 75, 100, 125, and 200 µg/kg) (Figure 1). The typical chromatograms of these pesticides are displayed in Figure 2.

3.7. Modeling the chlorpyrifos and diazinon residues

3.7.1. Linear kinetic modeling

The linear kinetic models were presented for chlorpyrifos and diazinon residues in tomato using zero-order, first-order, and second-order equations (19).

Zero-order model

The following equation was considered for zero-order kinetic (Equation 1):

Ct = C0 - k0t                                                                               (1)

where Ct (µg/kg) signifies the residue concentration after the application of pesticide at time t, C0 (µg/kg) is the initial concentration at time 0 which dissipates through kinetic processes, and k0 indicates the reaction rate constant (1/day).

The half-life (t1/2) for the zero-order model was determined by Equation 2:

t1/2 = C0/2k0.                                                                            (2)

First-order model

First-order kinetic can be expressed as follows (Equation 3):

Ln Ct = -k1t + LnC0                                                                  (3)

where k1 is the rate constant (1/day), and Ct and C0 (µg/kg) are the residue concentration at time t and the initial concentration at time 0, respectively. Equation 4 was used to determine half-life (t1/2)

 

Figure 2. Chromatographic profiles of spiked tomato samples with the target analyses under established GC/MS2 conditions. The retention time of every insecticide is as follows: (a) diazoxon: 17.1 min, diazinon: 17.53 min, chlorpyrifos oxon: 21.048 min; (b) chlorpyrifos: 21.04 min

 

for the first-order model

t1/2 = C0/2k0                                                                             (4)

The half-life (t1/2) for the zero-order model was determined from the equation t1/2=Ln2/k1.

Second-order model

The second-order form of the linear kinetic model is as follows (Equation 5):

1/Ct =1/C0+k2t                                                                       (5)

Where k2 is the rate constant (1/day), and Ct and C0 (µg/kg) are the residue concentration after the application of pesticide at time t and the initial concentration at time 0, respectively.

The half-life (t1/2) for the second-order model was calculated using Equation 6:

t1/2 =1/k2C0                                                                              (6)

3.7.2. Nonlinear kinetic modeling

The nonlinear chi-square test is a statistical tool obtained by dividing the sum squared difference by its corresponding value. The Solver Add-in as part of Microsoft Excel was employed for fitting the nonlinear first- and second-order equations to the experimental data and determining the kinetic parameters, such as the rate constant (1) and t1/2 (20,21).


4.Results

4.1. The dissipation dynamics of chlorpyrifos and diazinon and the production of oxon derivatives

The chlorpyrifos and diazinon residues in the greenhouse were reduced from 2.01-0.09 µg/g and from 1.92-0.01 µg/g, respectively. In field conditions, the 5-day residual values of chlorpyrifos were less than the maximum residue levels of the Iranian national and the European Union standards (0.1 µg/g), whereas the required time for diazinon to reach the maximum residue limit (MRL) accepted by the European Union (EU) (0.01 µg/g) was 10 days.

At room and refrigerator temperatures, the final residual concentrations of both diazinon and chlorpyrifos were higher than the MRL after 5 days. In room conditions, the reductions of chlorpyrifos and diazinon were 27.17% and 32.8%, respectively, whereas in refrigerator conditions, they were calculated at 23.11% and 17.29%, respectively.

At boiling temperature, the residue levels of chlorpyrifos and diazinon decreased from 2.77- 1.21 µg/g and from 2.92-0.19 µg/g within 2 h, respectively, and the dissipation rates were obtained at 56.3% and 93.4%, respectively.

In the present study, the residue of the oxon derivative of chlorpyrifos (chlorpyrifos oxon) was positive after the application of chlorpyrifos (40.8% EC) at the recommended dosages of 2/1000. On the contrary, diazinon oxon was found to be below the detection limit in all of the analyzed samples. The residue levels of chlorpyrifos oxon fluctuated during field conditions and reached a maximum of 7 days after spraying. At boiling temperature for 2 h, chlorpyrifos oxon varied from 224.8-170.59 µg/kg, while at room and refrigerator temperatures, it ranged from 147.9-180.34 µg/kg and 53.07-202.6 µg/kg, respectively (Figure 3).

 

4.2. Modeling pesticide dissipation in tomatoes

The kinetic parameters, including the half-lives

 

Figure 3. Dissipation of chlorpyrifos and its metabolite chlorpyrifos oxon in the tomato samples in: (a) greenhouse, (b) boiling, (c) refrigerator, and (d) room conditions

 

Table 2. Regression equation, correlation coefficient, and half-life of diazinon in tomato

R2

t  1/2 (day)

k

Dynamic equation

Model

Condition

0.9287

2.83

316.11

ct= -316.11t + 1791.9

Zero-order model

Greenhouse

0.981

1.15

0.6017

lnct= -0.6017t + 7.7929

First-order model

0.8384

0.68

0.0029

1/ct= 0.0029t - 0.002

Second-order model

0.990

1.48

0.465

ct =1919.7e- 0.465t

Nonlinear first-order model

0.932

2.70

2E-04

1/ct= 5.2E-04+2E-04t

Nonlinear second-order model

0.9664

13.78

74.299

ct  = -74.299t+ 2047.8

Zero-order model

Refrigerator

0.971

17.45

0.0397

lnct  = -0.0397t + 7.6258

First-order model

0.9752

19.01

2E-05

1/ct  = 2E-05t+ 0.0005

Second-order model

0.976

11.84

0.058

ct =2056.8e- 0.058t

Nonlinear first-order model

0.979

18.79

2.58E-05

1/ct= 4.8E-04+2.58E-05t

Nonlinear second-order model

0.9487

7.03

168.79

ct  = -168.79t+ 2375.9

Zero-order model

Room

0.9564

8.03

0.0863

lnct  = -0.0863t + 7.7789

First-order model

0.9641

10

4E-05

1/ct  = 4E-05t + 0.0004

Second-order model

0.960

8.88

0.078

ct =2371.3e- 0.078 t

Nonlinear first-order model

0.965

11.41

3.69E-05

1/ct= 4.2E-04+3.69E-05t

Nonlinear second-order model

0.9365

45.59 (min)

0.0292

ct = -0.0292t+ 2.6626

Zero-order model

Boiling

0.914

42.786

0.0162

lnct = -0.0162t + 7.9145

First-order model

0.967

30.99

0.0107

1/ct  = 0.0107t + 0.3316

Second-order model

0.964

43.32

0.016

ct =2920.5e- 0.016t

Nonlinear first-order model

0.975

45.39

7.54E-06

1/ct= 3.4E-04+7.54E-06t

Nonlinear second-order model

 

Table 3. Regression equation, correlation coefficient, and half-life of chlorpyrifos in tomato

R2

t  1/2 (day)

k

Dynamic equation

Model

Condition

0.884

1.24

839.33

ct = -839.33x + 2082.1

Zero-order model

Greenhouse

0.905

0.78

0.88

lnct  = -0.8885t + 7.7768

First-order model

0.822

0.41

0.001

1/ct  = 0.0012t + 0.0002

Second-order model

0.914

1.51

0.458

ct =2020.3e -0.4583t

Nonlinear first-order model

0.809

2.04

2.4E-04

1/ct= 4.9E-04+2.4E-04t

Nonlinear second-order model

0.949

9.11

111.37

ct  = -111.37t+ 2029.4

Zero-order model

Room

0.982

10.72

0.064

lnct  = -0.0646t+ 7.6215

First-order model

0.971

10

4E-05

1/ct  = 4E-05t + 0.0005

Second-order model

0.986

12.44

0.055

ct =2001.9e-  0.0557t

Nonlinear first-order model

0.875

16.77

2.98E-05

1/ct= 5E-04+2.98E-05t

Nonlinear second-order model

0.846

13.64

78.451

ct  = -78.451t + 2141.2

Zero-order model

Refrigerator

0.859

17.50

0.0396

lnct  = -0.0396t + 7.6687

First-order model

0.870

20

2E-05

1/ct  = 2E-05t+ 0.0005

Second-order model

0.866

14.77

0.0469

ct =2211.07e-  0.0469 t

Nonlinear first-order model

0.887

19.739

2.29 E-05

1/ct= 4.5E-04+ 2.29 E-05 t

Nonlinear second-order model

0.939

78.94 (min)

17.291

ct = -17.291t+ 2730

Zero-order model

Boiling

0.940

92.41

0.0075

lnct  = -0.0075t+ 7.9178

First-order model

0.940

100

3E-06

1/ct  = 3E-06t + 0.0004

Second-order model

0.945

108.3

0.0064

ct =2689.3e- 0.0064t

Nonlinear first-order model

0.945

145.3

2.56E-06

1/ct= 3.7E-04+2.56E-06t

Nonlinear second-order model

 

and the rate constants of the pesticides, were calculated by modeling pesticide removal from tomatoes with four procedures (laboratory (e.g., boiling, refrigerator, and room temperatures) and field treatments).

The nonlinear first-order model gave more accurate fits to the field data (greenhouse) for both diazinon and chlorpyrifos, compared to other models and yielded the correlation coefficient (R2) values of 0.990 and 0.914, respectively (tables 2 and 3). On the contrary, the nonlinear second-order model provided a better pattern of dissipation at the refrigerator, room, and boiling temperatures, except for chlorpyrifos at room temperature whose variation was best described by the nonlinear first-order model (tables 2 and 3). Figures 4 and 5 display the best fitting models for the kinetic behaviors of chlorpyrifos and diazinon in all conditions. The half-lives of diazinon and chlorpyrifos were estimated from the best fitting models.

Based on the best fitting models for diazinon in the case of laboratory treatment at the refrigerator, room, and boiling temperatures, the half-lives were calculated as 18.79 days, 11.41 days, and 45.39 min, respectively, while the half-life of chlorpyrifos was estimated at 12.44 days-145.3 min.


5.Discussion

In the current research, a significant reduction was detected in chlorpyrifos and diazinon residues in field conditions during various time periods. The dissipation rates of chlorpyrifos and diazinon in field conditions were obtained at 95.5% and 99.4%, respectively. In one study,3 days after the application of pesticides on cucumbers, the decline of chlorpyrifos residues exceeded 70% and reached 98.67% after 10 days (22). As illustrated by another study,21 days

 

Figure 4. Best-fitting models for the kinetic behaviors of diazinon during field treatment and household conditions (e.g., storage at refrigerator and room temperatures, as well as boiling)

 

Figure 5. Best-fitting models for the kinetic behaviors of chlorpyrifos during field treatment and household conditions (e.g., storage at room and refrigerator temperatures, as well as boiling)

 

after spraying at the recommended dose, 98% of chlorpyrifos residues in the sweet corn samples and 91.2% of chlorpyrifos residues in the soil samples were removed. All final residues were lower than the MRL (0.1 µg/g), and the half-life of chlorpyrifos degradation was calculated at 4.02 days (6).

Chlorpyrifos and diazinon were less persistent in field conditions, including room and refrigerator temperatures, compared to laboratory conditions. It can be ascribed to the higher temperature, humidity, and photodecomposition, in the greenhouse, in comparison to other storage conditions, except for the boiling temperature (23). According to the results, temperature plays a crucial role in the degradation of pesticides. In one study,after boiling the samples for 5 min, the reduction percentage of the pesticides ranged from 42.8% (in cyprodinil) to  92.9 (in pyraclostrobin) (24).

The oxon derivatives of chlorpyrifos and diazinon demonstrated a peak at a retention time similar to that of their parent compounds. Therefore, they might not be detected in the samples by conventional methods (GC-MS and HPLC), and their detection is difficult and time-consuming (2). It was observed that the concentration of chlorpyrifos oxon was higher than the MRLs established by the European Union and the national standards. In two previously conducted studies, the formation of chlorpyrifos oxon was detected and increased toxicity after photodeg-radation and ultrasonic irradiation; nonetheless, the oxidation of diazinon was not the predominant reaction (25,26).

Using the nonlinear first-order model in the case of the field treatment, the half-life was determined at 1.48 days for diazinon and 1.51 days for chlorpyrifos. The half-life of chlorpyrifos was almost the same as that observed by Liang et al. who reported that the decline time of chlorpyrifos in cucumber samples was 1.60 days at the recommended dose (22). The half-lives of both pesticides decreased by increasing the temperature in laboratory studies from 4°C-100°C. Therefore, boiling proved to be more effective in the dissipation of pesticides, compared to storage at refrigerator and room temperatures.

The effective decline of pesticide residues based on the level of heat treatments may be attributed to the increased volatilization and accelerated degradation of these compounds as a result of elevated temperature. These findings were consistent with those suggested by previous studies which indicated that organophosphorus pesticides in foods were effectively decreased by increasing temperature in heat treatments (27,28).

According to the results, it can be observed that the half-life of diazinon was lower than that of chlorpyrifos in both field and lab treatments. It can be ascribed to the physical-chemical characteristics of diazinon, such as its high-pressure volatility, solubility in water, and photolysis, which lead to a more effective dissipation of diazinon residues, compared to chlorpyrifos residues (29,30).


6.Conclusion

In the current research, a significant reduction was observed in chlorpyrifos and diazinon residues in various time periods. The dissipation rates of these pesticides in field conditions after 5 days were reported as 90.3% and 95.8%, respectively. Modeling the removal of the pesticides indicated that the nonlinear first- and second-order models were the best fitted models for the dissipation of both pesticides in field and post-harvest conditions. The half-life of diazinon was lower than that of chlorpyrifos in both field and laboratory treatments. Moreover, the half-lives of the pesticides significantly decreased in boiling conditions. Chlorpyrifos oxon was found in the samples as an intermediate product of chlorpyrifos, and its concentrations were higher than the recommended MRLs in all household conditions (e.g., at room, refrigerator, and boiling temperatures).


Acknowledgments

This study was extracted from a Ph.D. dissertation at Hamadan University of Medical Sciences and was supported by the Vice-Chancellor for Research and Technology, Hamadan University of Medical Sciences (9704262384).


Footnotes

Authors’ Contribution: Study concept and design: R.Sh., M.T.S., S.K. ; analysis and interpretation of data: R.Sh., M.T.S., M.K., A.H., M.L. S.K.; drafting of the manuscript: R.Sh., M.T.S., S.K.; critical revision of the manuscript for important intellectual content: R.Sh., M.T.S., S.K. M.K., A.H., M.L.; statistical analysis: R.Sh., M.T.S., M.K., A.H., M.L. S.K.

Conflict of Interests: The authors declare that they have no conflict of interest regarding the publication of the current study.

Ethical Approval: This research project was approved by the Ethics Committee of Hamadan University of Medical Sciences (IR.UMSHA.REC. 1397.291).


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