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Fluctuating asymmetry and developmental instability in the wings of Neurothemis terminata as bioindicator of stress.

INTRODUCTION

Fluctuating asymmetry is characterized by small random deviation from perfect bilateral symmetry [1,2]. FA is commonly seen as a departure from ideal development process thus it is often used as an indicator for developmental instability (DI). DI is defined as a suite of processes that tend to disrupt the precise development of bilateral traits in organisms and is believed to stem from various exogenous and endogenous stresses that collectively referred to as developmental noise or perturbations [3,4]. Hence, developmental instability happens when an organism fails to buffer disturbances resulting to fluctuating asymmetry and the ability of resisting effects from stressors is generally linked to organism's fitness [5].

Nowadays, there is the incessant search for easily measured bioindicators which resulted in the investigation of asymmetry of morphological characters as a possible bioindicator for stress and the most widely used measure of asymmetry is Fluctuating Asymmetry (FA). Levels of FA have been studied as a measure of genetic and environmental stress. FA has been used as a measurement in many areas of animal behavior research [6] and has been applied as well to conservation problems [7,8]. The ubiquity of symmetry is a major advantage of fluctuating asymmetry over other measures of developmental instability. One could actually compare developmental instabilities of organisms and decipher the underlying causal stress [9]. Symmetry is a major trait of life and it has been suggested that more symmetrical individuals have higher developmental stability (DS), reproductive success and survival rate. Herewith, FA is then said to be a measure of viable genes and is therefore considered intricate or impossible to mask. An increase of chance in variation in the development is probably the result of general destabilized individual development. The use of FA as an indicator of developmental stability and a measure of ecological stress is based on the assumption that a stressful environment would result in higher FA levels than those observed in optimum environments [10,11,12,13,2,14,15]. Hence, the relationship between FA and exogenous or endogenous stresses could be utilized especially in solving practical tasks such as biomonitoring purposes [16].

Moreover, much interest has been devoted to the observation and examination of FA as an indicator of individual quality in relation to stress. Thus, in this study, fluctuating asymmetry (FA) in the wings of Libellulid eurotopic dragonfly, Neurothemis terminata have been analyzed. This species is widely distributed and often adapted to different environment. They are commonly found in several man-made habitats (terrestrial and freshwater) in Peninsular Malaysia, Japan, Philippines and in some parts of Asia and also occurring on lakes, marshes and in rice fields, but is absent from well-developed forest [17]. Accordingly, this study determined developmental stability via fluctuating asymmetry of dragonfly populations from three different areas (Tibanga, Tominobo and Tipanoy) in Iligan City that serve as sampling sites representing different environmental conditions. It is perceived that significant FA and increase FA may present inability of species to buffer stress in its developmental pathways hence, would mean developmental instability and have implications on species fitness. Hypothesis assumes that FA has costs, reflects the quality of individuals and the level of genetic and environmental stress experienced by individuals or populations during development.

MATERIALS AND METHODS

Collection of Samples:

Dragonflies had been considered as bioindicator species. In this study, eurytopic species Neurothemis terminata, were chosen since they were widely distributed and adapted to different environment. Samples were collected in Iligan City from three different sites: Tibanga, Tominobo and Tipanoy respectively, with N=90 per site. Adult specimens were identified as Neurothemis terminata, using existing illustrated keys and guides. The wings (fore- and hind wings) were removed and placed in clear glass slides for scanning. Digital images were acquired from both sides of fore-and hind wings using a HP 2400 scanner at 1200 dpi.

Landmark assignment:

Building TPS files and landmark assignment were done using tpsUtil and tpsDig2 software. Descriptions of landmark locations were shown in Table 1 and 2 and a total of 29 landmarks in the fore- wing and 35 landmarks in the hind wing were digitized using tpsDig2 software (see Fig. 1 and Fig. 2). Landmarking per specimen was done in triplicates to quantify and minimize measurement error.

Fluctuating Asymmetry Analysis (FA) and Principle Component Analysis (PCA):

Individual levels of FA of dragonflies were obtained using the SAGE (Symmetry and Asymmetry in Geometric Data) program. This software analyzed the x- and y-coordinates, using a configuration protocol that corresponds to both sides of the fore- and hind wings of the dragonfly. Matching symmetry protocol was applied in this case for both the left and right fore- and hind wings. Procrustes methods were used to analyze shape by superimposing configurations of landmarks into two or more specimens to achieve an overall best fit. Procrustes superimposition analysis was performed with the original and mirrored configurations simultaneously.

The squared average of Procrustes distances for all specimens is the individual contribution to the FA component of variation within a sample. To detect the components of variances and deviations, a two-way, mixed model ANOVA with three replicates was used [18,19,20]. The effect called 'sides' is the variation between the two sides; it is a measure of directional asymmetry (DA). The effect called 'individuals' is the variation among individual genotypes (size and shape variation). The individual's mean square is a measure of total phenotypic variation and it is random. The 'individual by sides' interaction is the failure of the effect of individuals to be the same from side to side; it is a measure of fluctuating asymmetry and antisymmetry; variations could be dependent to both environmental and genetic conditions [9].

Moreover, PCAs of the covariance matrix associated with the component of FA variation were performed, to carry out an interpolation based on a thin-plate spline to visualize shape changes as landmark displacement in deformation grids [18].

RESULTS AND DISCUSSION

Fluctuating asymmetry (FA) is defined as small random deviations from the ideal bilateral symmetry and it has been hypothesized to increase in response to both genetic and environmental stress experienced by a population [21]. An underlying hypothesis behind FA analysis is that the development of the two sides of a bilaterally symmetrical organism is often influenced by identical genes and thus, non-directional differences between the sides must be environmental in origin and reflect accidents occurring during development [3,2,22]. FA is directly related to developmental instability (DI), hence, a tool in investigating DI. Developmental instability is said to be the departure from perfect symmetry [2]. Meanwhile, the converse of which is known as developmental stability (DS) which pertains to the ability of organisms to maintain a stable state despite different environmental conditions and stressors. This assumes that the more perfectly symmetrical an individual, the more robust the organism is in the face of environmental or genetic stress during development. Herewith, the FA level was assessed for the three populations to determine developmental stability. FA of the right and left fore- and hind wings of N. terminata collected from three different sites: Tibanga, Tominobo and Tipanoy, Iligan City respectively were assessed through Procrustes method using SAGE software.

FA level was determined using the coordinates of the tangential space including the product of the coordinates of the left and right homologous points in formula which provided the final result of the Procrustes ANOVA (Table 3 and 4). The mean square of the interaction of "sides" and "individuals x sides" effects revealed a high value compared to the low value of mean square measurement error which indicates a significant result. F values for "individuals x sides'" effect for the three sites were all significant thus, significant FA value. However, Tibanga has relatively higher F value for both fore- and hind wings (F=10.2272; F=5.6378) compared to Tominobo and Tipanoy populations. A higher F value would mean smaller P value (*P<0.001 is significant) thus, more significant. Only individual x sides interaction denotes fluctuating asymmetry (FA). Directional asymmetry (DA) ('sides') was not significant in all samples.

The higher the F value the more highly significant the FA level, the greater the stress is. It was noted that sampling areas in Tibanga were open grass fields exposed to intense heat from the sun, near a dumpsite and characterized by the relative presence of small shallow water pools that serve as laying ground for eggs and breeding sites. Thus, the area was quite stressful for the species though, they have become somehow, adapted and thrived but not suitable for them. In Tominobo, they also thrived in open fields with tall grasses, bushes and some trees covering the area. Small shallow water pools and canals serve as breeding sites. Meanwhile, in Tipanoy, they were found inhabiting varied environment such as along canals, small brooks and streams covered with vegetation but the areas were quite disturbed due to anthropogenic activities. The results possibly imply that populations experienced high developmental perturbations and increased stress [23]. According to Badyaev, 2000 [24]if an organism could not attain a normal developmental process it would result to fluctuating asymmetry or an increase in the frequency of phenotypic deviants. Thus, the environment may contribute to ecological stress and could be responsible for elevated levels in FA. Moreover, Graham et al., 2010, said that FA is thought to increase under both environment and genetic stress [2].

In this regard, stress in this field can be clearly manifested as high levels of asymmetry. High FA would mean high developmental instability, the inverse of developmental stability. FA might have resulted from enumerable sources of stress. A possible explanation for high levels of FA detected may rise from the differences in genetic composition of the populations resulting in different tolerance to stress. Also individuals in their respective locations might have experienced developmental perturbations/noise early in life (exogenous and endogenous stresses such as low habitat quality to low genetic heterozygosity) which resulted to the observed deviations from bilateral symmetry based on the trait examined [25]. Endogenous stress are those brought about by inbreeding, hybridization and novel mutants while, exogenous stress were environmental stress such as pollution, alteration to organisms habitat, food deficiency, parasitism, deviant climatic conditions and other physicochemical factors. Thus, increased levels of FA, could also be a result of the interplay of developmental "noise" and stabilizing processes, which is associated by extreme conditions of environment such as high levels of pollutants or disturbances [26]. In addition, as odonata were considered as agile organisms and generally spent most of their time in the air, it is also deduced that asymmetry observed in their wings can be caused by disturbing effects and perturbations during growth and mating in the air [3]. Individuals defend their territory by flying above it, and sometimes stand on a stick to see intruders. Herewith, most likely, wing asymmetry has a major impact on species fitness and success. Hence, FA can be used as a bioindicator of individual quality and adaptation thereby, also demonstrating the potential for FA as a biomarker of stress and developmental instability of populations of odonata [27,28].

Moreover, Principal Component Analysis (PCA) was also performed in order to visualize the covariance shape change for each principal component and to see the general direction and magnitude of the fluctuation for each landmark. The red dots represent the morphological landmarks used in the study while the blue arrows indicate the direction as well as the magnitude of the fluctuation. The percentage values of PCA represent the level of variability in the data. Here, the amount of overall variation exhibited by PC1 and PC2 of samples from Tibanga (68.6811% and 64.4132%) were relatively higher than the percentage of variation of samples from Tominobo and Tipanoy (Table 5 and 6; Figure 3 and 4) for both fore- and hind wings. It was noted that Tibanga site was the most disturbed among the three locations due to anthropogenic activities in the area and having a dumpsite could also be a factor. Also, higher FA were exhibited by the samples from Tibanga.

Conclusion:

The results of this study demonstrate the potential of FA as a bioindicator of stress and its efficacy in measuring developmental instability in N. terminata. Results yield significant FA for all populations examined however, species from Tibanga have higher FA than species from Tominobo and Tipanoy respectively. The amount of overall variation exhibited by PC1 and PC2 of samples for both fore- and hind wings from Tibanga (68.6811% and 64.4132%) was relatively higher also compared to Tominobo and Tipanoy based on the Principal Component Analysis. A higher FA would mean lower developmental stability, meaning more stress experienced by the populations. Moreover, stress present could be attributed to pollution in general, and/or declination of habitat quality for all sampling sites or a result of the interplay of developmental "noise" and stabilizing processes, which is associated by extreme conditions of environment such as high levels of pollutants or disturbances. Thus, FA could be a good indicator of levels of developmental instability as well as a useful tool in detecting ecological stress in organisms/populations. An increase level of FA, have possible implications on species fitness and adaptation. The knowledge gained from this species and their population dynamics is vital in developing programs for biomonitoring purposes.

REFERENCES

[1] Palmer, AR, C. Strobeck and AK. Chippindale, 1993. Bilateral variation and the evolution of macroscopic asymmetries. Gelletica, 89: 201-18.

[2] Van Valen, L., 1962. A study of fluctuating asymmetry. Evolution, 16: 1-7.

[3] Palmer, AR., 1994. Fluctuating asymmetry analysis: a primer. In Developmental Instability: Its Origins and Evolutionary Implications, [Markow, TA (ed.)]. London: Kluwer Academic.

[4] Reimchen, TE. and P. Nosil, 2001 Lateral plate asymmetry, diet and parasitism in three spine Stickleback. J. Evol., 14: 632-645.

[5] Markow, T.A., 1999. Evolutionary ecology and developmental instability. AmlU. Rev. Entomol., 40: 105-20.

[6] Hovorka, MD. and RJ. Robertson, 2000. Food stress, nestling growth and fluctuating asymmetry. Can. J. Zool, 78: 28-35.

[7] Lens, L., VS. Dongen, CM. Wilder, TM. Brooks and E. Matthysen, 1999. Fluctuating Asymmetry increases with habitat disturbance in seven bird species of a fragmented afrotropical forest. Proc. R. Soc. B, 266: 1241-1246.

[8] Anciaes, M. and MA. Marini, 2000. The effects of fragmentation on fluctuating asymmetry in passerine birds of Brazilian tropical forests. J. Appl. Ecol., 37: 1013-1028.

[9] Graham, JH., S. Raz, H. Hagit and E. Nevo, 2010. Fluctuating Asymmetry: Methods, Theory and Applications. Symmetry, 2: 466-495.

[10] Parsons, PA., 1961. Fly size, emergence time and sternopleural chaeta number in Drosophila. Heredity, 16: 455-47.

[11] Parsons, PA., 1962. Maternal age and developmental variability. J. Exp. Biol., 39: 251-260.

[12] Parsons, PA., 1990. Fluctuating asymmetry: an epigenetic measure of stress. Biol. Rev., 65: 131-145.

[13] Parsons, PA., 1992. Fluctuating asymmetry: a biological monitor of environmental and genomic stress. Heredity, 68: 361-364.

[14] Palmer, AR. and C. Strobeck, 1986. Fluctuating asymmetry--measurement, analysis, patterns. Annu. Rev. Ecol. Syst., 17:391-421.

[15] Leary, RF. and FW. Allendorf, 1989. Fluctuating asymmetry as an indicator of stress: implications for conservation biology. Trends Ecol. Evol., 4: 214-217.

[16] Ryazanova, GI. and AS. Polygalov, 2013. Vestnik Moskovskogo Universiteta. Biologiya, 3: 27-32.

[17] Kalkman, V., 2009. Neurothemis terminata. In: IUCN 2013. IUCN Red List of Threatened Species. Version 2013.2. <www.iucnredlist.org>.

[18] Marquez, E., 2006. Sage: symmetry and asymmetry in geometric data. Ver 1.0. http://www.personal.umich.edu/~emarquez/morph/.

[19] Klingenberg, CP., M. Barluenga and A. Meyer, 2002. Shape analysis of symmetric structures: quantifying variation among individuals and asymmetry. Evolution, 56: 1909-1920.

[20] Klingenberg, CP. and GS. McIntyre, 1998. Geometric morphometrics of developmental instability: analyzing patterns of fluctuating asymmetry with Procrustes methods. Evolution, 52: 1363-1375.

[21] Trokovic, N., G. Herczeg, NI. Ab Ghani, T. Shikano and J. Merila, 2012. High levels of fluctuating asymmetry in isolated stickleback populations. BMC Evolutionary Biology, 12: 115.

[22] Gangestad, SW. and R. Thornhill, 1999. Individual differences in developmental precision and fluctuating asymmetry: a model and its implications. Journal of Evolutionary Biology, 12: 402-416.

[23] Hermita, JM., JC. Gorospe, MA. Torres, JL. Lumasag and CG. Demayo, 2013. Fluctuating asymmetry in the body shape of the mottled spinefoot fish, siganus fuscescens (houttuyn, 1782) collected from different bays in mindanao island, Philippines. Sci.Int.(Lahore), 25(4): 857-861.

[24] Badyaek, AV., KR. Foresman and MV. Fernandes, 2000. Stress and Deveopmental Stability: Vegetation Removal Caused Increased in Fluctuating Asymmetry in Shrews. Ecology, 81(2): 336-345.

[25] Utayopas, P., 2001. Fluctuating Asymmetry in Fishes inhabiting polluted and unpolluted Bodies of water in Thailand. Thammasat Int. J. Sc. Tech., 6(2): 10-20.

[26] Graham, JH., DC. Freeman and JC. Emlem, 1993. Antisymmetry, Directional Symmetry and Dynamic Morphogenesis. Genetics, 89: 173-293.

[27] Ducos, MB. and SR. Tabugo, 2014. Fluctuating asymmetry as an indicator of ecological stress and developmental instability of Gafrarium tumidum (ribbed venus clam) from Maak and Lagoon Camiguin Island, Philipines. AACL Bioflux, 7(6): 516-523.

[28] Mpho, M., GJ. Holloway and A. Callaghan, 2000. The effect of larval density on life history and wing asymmetry in the mosquito Culexpipiens. Bulletin of Entomological Research, 90: 279-283.

Sharon Rose Tabugo, Princess Angelie Casas, Ma. Theresa Pareno, Myrtle Ayn Penaredondo

Department of Biological Sciences, MSU-Iligan Institute of Technology, Tibanga, Iligan City, Lanao del Norte, Mindanao, Philippines

ARTICLE INFO

Article history:

Received 23 June 2015

Accepted 25 July 2015

Available online 30 August 2015

Corresponding Author: Sharon Rose Tabugo, Faculty, Department of Biological Sciences, College of Science and Mathematics, MSU-Iligan Institute of Technology, Tibanga, Iligan City, Lanao del Norte, Philippines.

E-mail: sharonrose0297@gmail.com

Table 1: Description of assigned landmarks on both left and
right fore-wing respectively.

Landmark #                     Descriptive location

1                         Proximal End of the Costa (C)
2                       Proximal End of the Subcosta (Sc)
3                    Proximal End of the Radius + Media (R+M)
4                        Proximal End of the Cubitus (Cu)
5                    Proximal End of the 1st Anal Vein (A/IA)
6                         Basal End of the Arculus (Arc)
7            Proximal End of the Anterior Margin of the Triangle (T)
8             Distal End of the Anterior Margin of the Triangle (T)
9                          Midpoint of the Triangle (T)
10                         Midpoint of the Triangle (T)
11                      Posterior End of the Triangle (T)
12                    Origin of Radial Branches (R2 and R4)
13                       Origin of Intercalary Vein (IR3)
14                                   Nodus(N)
15                       Distal End of the Subcosta (Sc)
16                         Distal End of the Radius (R)
17                  Origin of the Radial Branches (R2 and R3)
18                      Anterior End of the 2nd Crossvein
                       between Radial Branches (R2 and R3)
19                  Posterior End of the 2nd Crossvein between
                      Radial Branches (R2 and R3); Origin of
                             Radial Supplement (Rspl)
20                   Proximal End of Radial Supplement (Rspl)
21                       Distal End of Radial Supplement
22                      Distal End of Anterior Media (MA)
23                       Distal End of Radial Branch (R4)
24                 Distal End of Intercalary Radial Vein (IR2)
25                       Distal End of Radial Branch (R2)
26               Antero-lateral and Distal End of the Pterostigma
27              Postero-lateral and Distal End of the Pterostigma
28              Antero-lateral and Proximal End of the Pterostigma
29             Postero-lateral and Proximal End of the Pterostigma

Table 2: Description of assigned landmarks on both left
and right hind wing respectively.

Landmark #                    Descriptive location

1                         Proximal End of the Costa (C)
2                       Proximal End of the Subcosta (Sc)
3                         Proximal End of the Media (m)
4                       Proximal End of the Cubitus (Cu)
5                    Posterior End of the Anal Crossing (Ac)
6                        Basal End of the Arculus (Arc)
7            Posterior and Proximal Vertex of the Hypertrigone (ht)
8              Anterior and Proximal Vertex of the Subtrigone (t)
9             Anterior and Proximal Vertex of the Hypertrigone (ht)
10             Posterior and Proximal Vertex of the Subtrigone (t)
11                                 (Cu2 + A2)
12                     Distal Vertex of the Subtrigone (t)
13                           Anal Supplement (Aspl)
14                       Basal end of the Anal Vein (A3)
15                     Second Branch of Cubital Vein (Cu2)
16                  Distal End of the Cubito-anal Vein (Cu2)
17                  Distal End of the Posterior Cubital Vein
18                      Origin of the Radial Branch (R4)
19                 Origin of the Intercalary Radial Vein (IR3)
20                                  Nodus (n)
21                       Distal End of the Subcosta (Sc)
22                        Distal End of the Radius (R)
23                  Origin of the Radial Branches (R2 and R3)
24                       Distal End of Radial Supplement
25              Posterior End of the 2nd Crossvein between Radial
                Branches (R2 and R3); Origin of Radial Supplement
                                     (Rspl)
26                    Distal End of the Anterior Media (AM)
27                    Distal End of the Radial Branch (R4)
28               Distal End of the Intercalary Radial Vein (IR3)
29                    Distal End of the Radial Branch (R3)
30                 Distal End of Intercalary Radial Vein (IR2)
31                      Distal End of Radial Branch (R2)
32              Antero-lateral and Distal end of the Pterostigma
33             Postero- lateral and Distal end of the Pterostigma
34             Antero-lateral and Proximal end of the Pterostigma
35             Postero-lateral and Proximal End of the Pterostigma

Table 3: Procrustes ANOVA results of the fore-wings of
Neurothemis terminata from three different locations in Iligan
City.

Effect           SS        dF         MS

TIBANGA
Sides         0.010907     54     0.00020198
Individual    0.035352    1566     2.2575 x
  x Sides                        [10.sup.-005]
Measurement   0.014304    6480     2.2073 x
  error                          [10.sup.-006]

TOMINOBO

Sides         0.0013953    54      2.5839 x
                                 [10.sup.-005]
Individual     0.01792    1566     1.1443 x
  x Sides                        [10.sup.-005]
Measurement   0.019841    6480     3.0619 x
  error                          [10.sup.-006]

TIPANOY

Sides         0.0019132    54       3.543 x
                                 [10.sup.-005]
Individual    0.026833    1566     1.7135 x
  x Sides                        [10.sup.-005]
Measurement   0.039503    6480     6.0961 x
  error                          [10.sup.-006]

Effect           F        P       Remarks

TIBANGA
Sides         8.9472
Individual    10.2272   *****     Highly
  x Sides                       Significant
Measurement     --
  error

TOMINOBO

Sides         2.2579

Individual    3.7374     ***    Significant
  x Sides
Measurement     --
  error

TIPANOY

Sides         2.0677

Individual    2.8108     ***    Significant
  x Sides
Measurement     --
  error

Note: side = directional asymmetry; individual x sides
interaction = fluctuating asymmetry; * P < 0.001,
ns--statistically insignificant (P>0.05); significance was
tested with 99 permutations

Table 4: Procrustes ANOVA results of the hind wings of Neurothemis
terminata from three different locations in Iligan City.

Effect           SS        dF         MS

TIBANGA

Sides         0.0052929    66      8.0195 x
                                 [10.sup.-005]
Individual     0.0437     1914     2.2832 x
  x Sides                        [10.sup.-005]
Measurement   0.032074    6480     4.0498 x
  error                          [10.sup.-006]

TOMINOBO

Sides         0.0010483    66      1.5884 x
                                 [10.sup.-005]
Individual    0.027979    1914     1.4618 x
  x Sides                        [10.sup.-005]
Measurement   0.030422    6480     3.8411 x
  error                          [10.sup.-006]

TIPANOY

Sides         0.0026996    66      4.0904 x
                                 [10.sup.-005]
Individual    0.028775    1914     1.5034 x
  x Sides                        [10.sup.-005]
Measurement   0.026682    6480     3.3689 x
  error                          [10.sup.-006]

Effect          F       P       Remarks

TIBANGA

Sides         3.5124

Individual    5.6378   ****     Highly
  x Sides                     Significant
Measurement     --
  error

TOMINOBO

Sides         1.0866

Individual    3.8057   ***    Significant
  x Sides
Measurement     --
  error

TIPANOY

Sides         2.7207

Individual    4.4626   ****   Significant
  x Sides
Measurement     --
  error

Note: side = directional asymmetry; individual x sides interaction =
fluctuating asymmetry; * P < 0.001, ns -- statistically insignificant
(P > 0.05); significance was tested with 99 permutations

Table 5: Variance explained by first two principal components
of Neurothemis terminata fore- wings from three different
locations in Iligan City.

Site       PC 1 (%)   PC 2 (%)   Overall (%)

Tibanga    46.4537    22.2274      68.6811
Tominobo   24.1912    15.4944      39.6856
Tipanoy    22.8296    19.5316      42.3612

Table 6: Variance explained by first two principal components
of Neurothemis terminata hind wings from three different
locations in Iligan City.

Site       PC 1 (%)   PC 2 (%)   Overall (%)

Tibanga    51.7307    12.6825      64.4132
Tominobo   26.3198    21.2012      47.521
Tipanoy    22.3794    18.6449      41.0243
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Author:Tabugo, Sharon Rose; Casas, Princess Angelie; Pareno, Ma. Theresa; Penaredondo, Myrtle Ayn
Publication:Advances in Environmental Biology
Article Type:Report
Date:Aug 1, 2015
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