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					<li><a href="#articleinfo">Article Info</a></li>
					<li><a href="#abstract">Abstract</a></li>
					<li><a href="#intro">Introduction</a></li>
					<li><a href="#method">Materials and Methods</a></li>
					<li><a href="#analysis">Statistical Analysis</a></li>
					<li><a href="#result">Results</a></li>
					<li><a href="#discussion">Discussion</a></li>
					<li><a href="#conclusion">Conclusion</a></li>
					<li><a href="#ack">Acknowledgement</a></li>
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			<li><a href="#intro">Introduction</a></li>
			<li><a href="#method">Materials and Methods</a></li>
			<li><a href="#analysis">Statistical Analysis</a></li>
			<li><a href="#result">Results</a></li>
			<li><a href="#discussion">Discussion</a>
			<li><a href="#conclusion">Conclusion</a>
			<li><a href="#ack">Acknowledgement</a></li>
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                    <p class="art-type" id="articleinfo">Research Article</p>
		    <p class="art-title">Serum Uric Acid to Creatinine Ratio as a Marker of Estimated Glomerular Filtration Rate in Type 2 Diabetes Patients</p>
		    <p class="art-author"><?php $authors="Sengsuk J<sup>1</sup>, Tangvarasittichai O<sup>2</sup> and Surapon Tangvarasittichai<sup>2*</sup>"; echo (stristr($authors,$coauthor))?str_replace($coauthor,"<a href='".$extpath."authors/".$courl."' target='_blank'>".$coauthor."</a>",$authors):$authors; ?></p>
<p class="art-affl"><sup>1</sup>Clinical Laboratory Unit, Ladyao Hospital, Nakhonsawan, Thailand<br/>
			<sup>2</sup>Chronic Diseases Research Unit, Department of Medical Technology, Faculty of Allied Health Sciences, Naresuan University, Phitsanulok 65000, Thailand</p>
		    <p class="art-aff"><b>*Corresponding author: <?php $corresponding_author="Surapon Tangvarasittichai"; echo ($coauthor!="" && $coauthor==$corresponding_author)?"<a href='".$extpath."authors/".$courl."' target='_blank'>".$coauthor."</a>":$corresponding_author;?></b>,
Associate Professor,
Department of Medical Technology,
Faculty of Allied Health Sciences,
Naresuan University,
Phitsanulok, 65000,
Thailand,
Tel: +66055966276,
Fax: +66-0-5596-6300,
E-mail: <a href="mailto:surapon14t@yahoo.com">surapon14t@yahoo.com</a></p>
<p class="art-aff"><b>Received:</b>  April 3, 2018
<b>Accepted:</b>    April 20, 2018
<b>Published:</b> April 26, 2018</p>
<p class="art-aff"><b>Citation:</b> Sengsuk J, Tangvarasittichai O, Tangvarasittichai S. Serum Uric Acid to Creatinine Ratio as a Marker of Estimated Glomerular Filtration Rate in Type 2 Diabetes Patients. <i>Madridge J Diabetes</i>. 2018; 2(1): 36-41. doi: <a href="https://doi.org/10.18689/mjd-1000107">10.18689/mjd-1000107</a></p>
<p class="art-aff"><b>Copyright:</b> &copy;   2018 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
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<div class="articlecontent">
<p class="art-subhead" id="abstract">Abstract</p>
<p class="art-para">Chronic kidney disease (CKD) is a global health care problem; Serum creatinine
(SCr), Serum uric acid (SUA) levels has shown to be the markers of renal disease
progression. We aim to test renal function-normalized serum uric acid (SUA/SCr ratio
and SUA*GFR/100; corresponding with their eGFR equation) as biomarkers of estimated
glomerular filtration rate (eGFR) and CKD identification in type 2 diabetes mellitus
(T2DM) patients. A total of 446 T2DM patients were included. Three eGFR equations
were used as: Cockroft-Gault (eGFR1), the modification of diet in renal disease (MDRD)
(eGFR2) and CKD-epidemiology collaboration (eGFR3) equation. Kruskal-Wallis test and
Mann-Whitney <i>U</i>-test were used to compare the differences all groups and intergroup.
ROC curve was used to indicate better marker, discrimination, and cut-off values
generation. SUA*eGFR/100 and eGFR were significantly different in eGFR3 and caused
the different values of SUA*eGFR/100 in total T2DM patients. The number of CKD
patients (eGFR 30-59.9 ml/min/1.73 m<sup>2</sup>
) was different according to their eGFR equations
and found significantly different in eGFR of each group and SCr, SUA, SUA/SCr ratio, and
SUA*eGFR/100 in eGFR3 group. Bivariate correlation of SUA/SCr ratio, SUA*GFR/100
were significantly correlated with eGFR1, eGFR2, eGFR3 and the other variables both in
total and in CKD group. SUA/SCr ratio, SUA*eGFR/100 with each eGFR equations cut-off
values for CKD identification were generated.</p>
<p class="art-para"><b>Conclusion:</b> SUA/SCr ratio can be used as a biomarker of GFR estimation and CKD identification, likely with eGFR but easier calculation. SUA/SCr ratio cut-off values were provided corresponding with their eGFR equations for selection.</p>
<p class="art-para"><b>Keywords:</b> Serum creatinine; Serum uric acid; Estimated glomerular filtration rate; Cockroft-Gault; The modification of diet in renal disease; CKD-epidemiology collaboration.</p>

<p class="art-subhead" id="intro">Introduction</p>
<p class="art-para">Kidney dysfunction and albuminuria are determinants as independent risk factors
for chronic kidney disease (CKD) and cardiovascular disease (CVD) <a href="#1" id="ref1">[1</a>, <a href="#2" id="ref2">2]</a>. Chronic kidney
disease is a global health care problem; hyperglycemia and hypertension are the
modifiable risk factors to control these factors are important for CKD prevention <a href="#3" id="ref3">[3]</a>.
Patients with CKD may have one or more of these following, pathologic abnormalities,
markers of kidney injury or damage (imaging, serum or urine sediment abnormalities
and albuminuria), or GFR <60 mL per minute per 1.73 m<sup>2</sup> for at least three months <a href="#4" id="ref4">[4]</a>.
Diabetes mellitus is the major and leading cause of CKD globally <a href="#5" id="ref5">[5]</a>.</p>

<p class="art-para">Serum creatinine (SCr), blood urea nitrogen (BUN) and
serum uric acid (SUA) levels and urine analysis were commonly
used for kidney function estimation <a href="#6" id="ref6">[6]</a>. However more evidences
are demonstrated these biomarkers are not reach the optimal
detection of the early stages of kidney disease <a href="#7" id="ref7">[7</a>-<a href="#10" id="ref10">10]</a>. The Kidney
Disease Improving Global Outcomes recommends that glomerular
filtration rate (GFR) is a determinant for diagnosis, classification
and staging CKD <a href="#11" id="ref11">[11]</a>. GFR is the volume of body fluid filtered
through the glomerular capillaries of the Bowman's capsule per
unit time <a href="#12" id="ref12">[12</a>, <a href="#13" id="ref13">13]</a>. GFR was usually used in clinical practice for
drug dosing, diagnosis, prognosis and management in addition
with public health and research works <a href="#14" id="ref14">[14</a>-<a href="#16" id="ref16">16]</a>.</p>
<p class="art-para">Serum creatinine (SCr) is a common marker for detecting
the GFR changing and CKD stage, elevated SCr as a marker of
renal disease and decreased renal function <a href="#17" id="ref17">[17]</a>. Similarly,
elevated SUA level is also commonly observed in CKD patients.
It is a simple biochemical marker for impaired or pathogenic
role of kidney function <a href="#18" id="ref18">[18</a>, <a href="#19" id="ref19">19]</a>. An elevated SUA was also
associated with impaired renal function in type 2 diabetes
mellitus (T2DM) patients <a href="#20" id="ref20">[20]</a>, and used as predictor of
development and progression of CKD in T2DM patients. <a href="#20" id="ref20">[20</a>,
<a href="#21" id="ref21">21]</a> In general physiological, renal clearance of SUA is often
impaired during kidney injury or dysfunction, renal function is
the major confounder in studies of the association between
SUA with CKD progression <a href="#22" id="ref22">[22]</a>.</p>
<p class="art-para">The renal function-normalized SUA (SUA/SCr ratio and
SUA*GFR/100) is studied before as the biomarker of the
chronic obstructive pulmonary disease, metabolic syndrome
and higher in the population with high prevalence of
metabolic syndrome and T2DM <a href="#23" id="ref23">[23</a>, <a href="#24" id="ref24">24</a>-<a href="#26" id="ref26">26]</a>. Because of the
many formulas of the eGFR including sex, weight, race and
many mathematic numbers were used in the clinical practice
and provided the different results. But the SUA/SCr ratio is
easier calculation by using the general biochemical markers
no any additions. In the present study, we aim to demonstrate
the renal function-normalized SUA (SUA/SCr ratio and
SUA*GFR/100) <a href="#23" id="ref23">[23]</a> as the biomarkers for eGFR and CKD
detection in T2DM patients.</p>

<p class="art-subhead" id="method">Materials and Methods</p>
<p class="art-para"><b>Subjects</b><br/>
A total of 446 T2DM patients (overt diabetes more than 5
years) were randomized from the Diabetes Care Clinic of Ladyao
Hospital during January 2015 to December 2016. All T2DM
patients were receiving regular treatment with glycemic lowering,
lipid lowering, and anti-hypertensive medication. The exclusion
criteria were sustained heart failure, peripheral vascular disease,
recent myocardial infarction, unstable angina, stroke, acute or
chronic infection, cancer, hepatic disease, acute illness in the year
of recruitment. All participants gave written informed consent.
Our study protocol was approved by the Ethic committees of
Naresuan University.</p>
<p class="art-para"><b>Physical and Biochemical Examination</b><br/>
All T2DM underwent anthropometry, blood pressure
measurement and physical examination. Body mass index (BMI)
was calculated and waist circumference (WC) was measured at
the midpoint between the rib cage and the top of lateral border
of iliac crest at minimum respiration. BP was measured after the
participants had been seated and rested for 5 minutes, as the
mean value of at least two measurements for these participants
on the same day with calibrated desktop sphygmomanometers.
Venous blood samples were collected from all participants
without stasis after 8-12 hour fast in a seated position. Blood
specimens were processed and assayed in the clinical laboratory
of Ladyao Hospital, Nakhonsawan, Thailand. Plasma glucose
(Glu), blood urea nitrogen (BUN), serum uric acid (SUA), total
cholesterol (TC), triglyceride (TG), high density lipoprotein-cholesterol (HDL-C) were measured by enzymatic method.
Serum creatinine (SCr) and urine creatinine (UCr) concentrations
were determined based on the Jaffe reaction. Low density
lipoprotein-cholesterol (LDL-C) concentrations were calculated
with Friedewald's formula in specimens with TG levels <400 mg/
dl. Urine samples were collected in polyethylene bottles after
physical examination and blood taken for N-acetyl-&beta;-Dglucosaminidase (NAG) and UCr determination. SUA/SCr ratio
and SUA*GFR/100 were calculated according to their formula.</p>
<p class="art-para"><b>Hemoglobin A1C Measurement</b><br/>
HbA1c levels were assayed by using turbidimetric
inhibition immunoassay (TINIA) on hemolyzed whole blood
(standardized according to the International Federation of
Clinical Chemistry) by use of a Hitachi 912 auto-analyzer
(Roche Diagnostic, Switzerland)</p>
<p class="art-para"><b>High sensitivity-C-reactive protein (hs-CRP) Measurement</b><br/>
The hs-CRP levels were assayed by using latex-enhanced
immunoneplelometric method on the Hitachi 912 auto-analyzer (Roche Diagnostic, Switzerland) that has been
standardized against the World Health Organization
reference.</p>
<p class="art-para"><b>Urinary NAG (UNAG) Measurement</b><br/>
The assay is based on NAG in urine reacting with the
substrate of p-nitrophenyl-N-acetyl- &beta; -D-glucosaminide in
sodium citrate buffer (pH 4.4) at 37 &deg;C to liberate
p-nitrophenylate ion, then adding 2-amino-2-methyl-1-
propanol (AMP) buffer (pH 10.25) to the reaction and
measuring the color reaction with spectrophotometer at 405
nm <a href="#27" id="ref27">[27]</a> The within-run and between-run coefficient of
variation in control material were 3.14% and 4.11% (n=10).</p>
<p class="art-para"><b>Estimated Glomerular Filtration Rate (eGFR)</b><br/>
The eGFR of each method was calculated by as follow:</p>
<p class="art-para"><b>The Cockroft-Gault Equation (eGFR1)</b><br/>
The Cockroft-Gault formula which incorporates age, body
weight, and sex <a href="#28" id="ref28">[28]</a>. The formula is: eGFR1 = [(140 - age) *
weight (kg) *constant]/[serum creatinine (&mu;mol/L)] where 1.23
and 1.04 are constants for men and women, respectively.</p>
<p class="art-para"><b>The Modification of Diet in Renal Disease (MDRD)
Equation (eGFR2)</b><br/>
The formula is: eGFR2 = 175 * (SCr) -1.154 * (age) -0.203
* 0.742 (If female) or 0.212 (If Black); SCr in mg/dl <a href="#29" id="ref29">[29]</a>.</p>

<p class="art-para"><b>CKD-Epidemiology Collaboration Equation (eGFR3)</b><br/>
The formula is: eGFR3=141 <sup>*</sup> min (SCr/k, 1)<sup>&#945; *</sup> max (SCr/k, 1) <sup>-1.209 *</sup>  0.993 <sup>(age) *</sup>  1.018 (If female) or 1.159 (If Black) <a href="#30" id="ref30">[30]</a>.
Five eGFR stages according to clinical guidelines for chronic
kidney disease of The Kidney disease outcome quality
initiative advisory board were used: Stage I was normal eGFR
(&ge;90ml/min/1.73 m<sup>2</sup>
); Stage II was mildly eGFR (60-89 mL/min/1.73 m<sup>2</sup>
); Stage III was moderately eGFR (30-59 ml/min/1.73 m<sup>2</sup>
); Stage IV was severely eGFR (<30 ml/min/ 1.73
m<sup>2</sup>
), and Stage V was end-stage renal disease: eGFR (<15 ml/min/1.73 m<sup>2</sup>
). An eGFR lower than 60 ml/min/1.73 m<sup>2</sup>
(moderately eGFR) was defined as chronic kidney disease
(CKD) <a href="#31" id="ref31">[31]</a>.</p>


<p class="art-subhead" id="analysis">Statistical Analysis</p>
<p class="art-para">All data are presented as median and interquartile range
for non-normally distributed data, tested by using Shapiro-Wilk test. All clinical characteristics, eGFR,SUA/SCr ratio,
SUA*eGFR/100; corresponding with their eGFR equations
were compared and CKD of these T2DM patients were
identified (eGFR 30-59 ml/min/1.73 m<sup>2</sup>
) and compared clinical
characteristics, number of patients according to each equation
of eGFR calculation by using Kruskal-Wallis test, and compared
the differences of intergroup by using Mann-Whitney <i>U</i>-test.
Bivariate correlation between SUA/SCr ratio, SUA*eGFR/100,
NAG, hs-CRP and with the other variables was assessed by
using Spearman rank correlation test. A comparison of SUA/
SCr ratio and SUA*eGFR/100 in CKD and non-CKD group of
each eGFR equation were analyzed in terms of a receiver
operating characteristic (ROC) curve. A ROC curve is a plot
between sensitivity (Y-axis) versus false positive (X-axis),
obtained for different cutoff points. Areas under the curve
(AUC) of the ROC curves and their 95 per cent confidence
intervals (CI) were evaluated as a measure of diagnostic
accuracy. A discriminate analysis was performed to identify a
combination of these parameters that provided the best
differentiation between CKD and non-CKD individuals.
Greater AUC of the ROC curve indicated better markers of the
study. In general, an AUC of a ROC of 0.5 suggests no
discrimination, whereas a maximal AUC of a ROC of 1 suggests
outstanding discrimination and also generate the cut-off
values of SUA/SCr ratio and SUA*eGFR/100 according to each
equation of eGFR calculation <a href="#32" id="ref32">[32]</a>. All tests were two tailed,
and <i>p</i>-values less than 0.05 were regarded as statistically
significant. All analysis was performed by SPSS version 13.0
(SPSS, Chicago, IL, USA).</p>


<p class="art-subhead" id="result">Results</p>
<p class="art-para">The comparison of all clinical characteristics, SUA/SCr ratio,
SUA*eGFR/100; corresponding with their eGFR equations of 446
T2DM patients by using the Kruskal-Wallis test and MannWhitney <i>U</i>-test were demonstrated in Table 1.</p>

<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t001a.gif" class="img-responsive center-block"/></div>
<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t001b.gif" class="img-responsive center-block"/></div>

<p class="art-para">SUA*eGFR/100 and eGFR are significantly different in
eGFR3 Gr. These suggest that eGFR3 was significantly
difference from the others and also caused the different
values of SUA*eGFR/100 in total T2DM patients.</p>
<p class="art-para">We found the difference number of subjects with eGFR
30-59.9 ml/min/1.73 m2 or CKD patients according to their
eGFR equations. We also found significantly different in each
eGFR group and significantly different in SCr, SUA, SUA/SCr
ratio, and SUA*eGFR/100 in eGFR3 group as shown in Table 2.</p>

<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t002a.gif" class="img-responsive center-block"/></div>
<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t002b.gif" class="img-responsive center-block"/></div>

<p class="art-para">Bivariate correlation, SUA/SCr ratio was significantly
correlated with the other variables and significantly correlated
with eGFR1, eGFR2, eGFR3 both in total patients and CKD
patients (eGFR 30-59.9 ml/min/1.73 m2) as shown in Table 3.</p>

<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t003a.gif" class="img-responsive center-block"/></div>
<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t003b.gif" class="img-responsive center-block"/></div>

<p class="art-para">We plotted the ROC curves for SUA/SCr ratio and
SUA*eGFR/100; corresponding with their eGFR equations.
The results of SUA/SCr ratio and SUA*eGFR/100; corresponding
with their eGFR equations ROC curve analysis showed that
each marker is a significant discriminator for eGFR in CKD
patients. The area under the curve (AUC) of the ROC curve
was used for prediction of better markers for each eGFR in
CKD patients. The AUC results were obtained with 0.877 of
SUA/SCr ratio and 0.928 of SUA*eGFR1/100 (Figure 1A), 0.944
of SUA/SCr ratio and 0.958 of SUA*eGFR2/100 (Figure 1B),
and 0.928 of SUA/SCr ratio and 0.974 of SUA*eGFR3/100
(Figure 1C), indicating that these models with these ratios can
be used for estimating the glomerular filtration rate of T2DM
patients in this study (Table 4, Figure 1).</p>

<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t004.gif" class="img-responsive center-block"/></div>
<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-f001.gif" class="img-responsive center-block"/></div>

<p class="art-para">The optimal cut-off values of SUA/SCr ratio, SUA*eGFR/100;
corresponding with their eGFR equations, for prediction of
CKD in present study were 3.60 with sensitivity and specificity
of 90.8%, and 73.0%; 220 with sensitivity and specificity of
90.8% and 79.9%, corresponding with their eGFR1 equations,
3.19 with sensitivity and specificity of 89.6%, and 86.9%; 175.0
with sensitivity and specificity of 85.1.8% and 93.9%,
corresponding with their eGFR2 equations, and 3.18 with
sensitivity and specificity of 90.9%, and 80.4%; 175 with
sensitivity and specificity of 91.4% and 90.4%, corresponding
with their eGFR3 equations, respectively (Table 5).</p>
<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t005.gif" class="img-responsive center-block"/></div>
<p class="art-para">The different number of individual having lower cut-off
value of SUA/SCr ratio and eGFR<60.0 ml/min/1.73 m<sup>2</sup> (CKD)
were identified by using their SUA/SCr ratio values and their
eGFR equation as shown in the Table 6.</p>
<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t006a.gif" class="img-responsive center-block"/></div>
<div class="art-img">
<img src="<?php echo $imgpath;?>images/mjd-107-t006b.gif" class="img-responsive center-block"/></div>

<p class="art-subhead" id="discussion">Discussion</p>
<p class="art-para">Estimating GFR was very important and usually used in
clinical practice for drug dosing, diagnosis, prognosis and
management in addition with public health and renal research
works <a href="#14" id="ref14">[14</a>-<a href="#16" id="ref16">16]</a>. The most commonly used equations including
Cockroft-Gault (eGFR1) <a href="#28" id="ref28">[28]</a>, MDRD (eGFR2) <a href="#29" id="ref29">[29</a>, <a href="#33" id="ref33">33]</a>, CKD-EPI
(eGFR3) <a href="#30" id="ref30">[30]</a> and more equations that combines creatinine
and CysC <a href="#34" id="ref34">[34]</a>. The results of CKD-EPI were significantly lower
estimated CKD than the MDRD equation <a href="#33" id="ref33">[33]</a>. While the MDRD
equation underestimates GFR in healthy individuals resulting
in false negative diagnosis of CKD in this population <a href="#35" id="ref35">[35]</a>.</p>
<p class="art-para">The present study demonstrated that MDRD equation
(eGFR2) resulted in higher eGFR and gave lower in number of
CKD patients, and CKD-EPI equation (eGFR3) resulted in lower
eGFR and gave higher in number of CKD patients, while
Cockroft-Gault equation (eGFR1) resulted in the middle of
these 2 equations. Our results demonstrated the same cut-off
values (<3.19 and <3.18) of SUA/SCr ratio according to eGFR2
and eGFR3 and also identified the same number of CKD
patients, while the SUA/SCr ratio cut-off value = <3.60
according to eGFR1 and also identified the higher number of
CKD patients.</p>
<p class="art-para">Only SUA has been shown a predictor for the progression
of renal disease caused from the association of SUA and
eGFR, but not all studies <a href="#36" id="ref36">[36</a>, <a href="#37" id="ref37">37]</a>. In impaired renal function,
increasing of SUA was occurred as a consequence of CKD as
a strong predictor for renal disease progression. Patients with
lower eGFR were higher in SUA levels and higher risks in
progression of renal disease. Then, baseline renal function-normalized SUA (SUA/SCr ratio, SUA*eGFR/100), which may
reflect the net production of SUA, will be better than only SUA
value as the predictor of incident CKD. The Modification of
Diet in Renal Disease (MDRD) Study also failed to demonstrate
SUA as the predictor for progression of chronic renal failure
after a 10-year follow-up in 840 individuals with CKD <a href="#20" id="ref20">[20</a>, <a href="#38" id="ref38">38</a>,
<a href="#39" id="ref39">39]</a>. SUA/SCr ratio is studied before as the biomarker of the
chronic obstructive pulmonary disease, metabolic syndrome
and higher in the population with high prevalence of
metabolic syndrome and T2DM <a href="#24" id="ref24">[24</a>-<a href="#27" id="ref27">27]</a>.</p>

<p class="art-subhead" id="conclusion">Conclusion</p>
<p class="art-para">The present study demonstrated SUA/SCr ratio and
SUA*eGFR/100 was significantly correlated with each eGFR
equations.SUA/SCr ratio can be used as a biomarker of GFR
estimation in the same as eGFR but easier calculation by using
the general biochemical markers no any additions. We also
provide the SUA/SCr ratio cut-off value according to eGFR
equations for selection.</p>

<p class="art-subhead" id="ack">Acknowledgement</p>
<p class="art-para">We sincerely thank Ladyao Hospital and all co-workers of Clinical
Laboratory, Ladyao Hospital for their technical assistance and
supporting. We sincerely thank Asst. Prof. Dr. Ronald A. Markwardt,
Burapha University, for his reading and correcting of the manuscript.</p>

<p class="art-subhead" id="conflict">Conflict of interest</p>
<p class="art-para">The authors declare that they have no competing interests.</p>

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