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<Part>
<H1>ORTHODONTICS </H1>

<Link>
<P>STUDY REGARDING THE INFLUENCE OF VARIOUS MODELING AGENTS ON SURFACE MICROHARDNESS ROUGHNESS OF NANOHYBRID COMPOSITE RESINS </P>

<P>Simona Stoleriu1a* 
<Link><Figure>

<ImageData src="images/Article_11_1-2_4_img_0.jpg"/>
</Figure>
</Link>
    , Gianina Iovan1b 
<Link><Figure>

<ImageData src="images/Article_11_1-2_4_img_0.jpg"/>
</Figure>
</Link>
, Irina Nica1c 
<Link><Figure>

<ImageData src="images/Article_11_1-2_4_img_0.jpg"/>
</Figure>
</Link>
, Galina Pancu1d 
<Link><Figure>

<ImageData src="images/Article_11_1-2_4_img_0.jpg"/>
</Figure>
</Link>
, Andrei Georgescu1e 
<Link><Figure>

<ImageData src="images/Article_11_1-2_4_img_0.jpg"/>
</Figure>
</Link>
, Alice Murariu2f*     
<Link><Figure>

<ImageData src="images/Article_11_1-2_4_img_0.jpg"/>
</Figure>
</Link>
, Sorin Andrian
<Link>1g <Figure>

<ImageData src="images/Article_11_1-2_4_img_0.jpg"/>
</Figure>
, Ionuț Tărăboanță</Link>
1h </P>

<Link>
<Sect><Figure>

<ImageData src="images/Article_11_1-2_4_img_0.jpg"/>
</Figure>
</Sect>
</Link>

<P>1Department of Odontology, Periodontology and Fixed Prosthodontics, “Grigore T. Popa” University of Medicine and Pharmacy, Iasi, Romania 2Department of Surgery, Faculty of Dental Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, Iasi, Romania </P>

<P>aDMD, PhD, Associate Professor; e-mail: 
<Link>simona.stoleriu@umfiasi.ro</Link>
; ORCID-iD: 
<Link>https://orcid.org/0000-0001-5427-6027 </Link>
bDMD, PhD, Professor; e-mail: 
<Link>gianina.iovan@umfiasi.ro</Link>
; ORCID-iD: 
<Link>https://orcid.org/0000-0001-7255-4406 </Link>
cDMD, PhD, Lecturer; e-mail: 
<Link>irina.nica@umfiasi.ro</Link>
; ORCID-iD: 
<Link>https://orcid.org/0000-0003-1189-0785 </Link>
dDMD, PhD, Lecturer; e-mail: 
<Link>galina.pancu@umfiasi.ro</Link>
; ORCID-iD: 
<Link>https://orcid.org/0000-0001-5427-6027 </Link>
eDMD, PhD, Professor assistant; e-mail: 
<Link>andrei.georgescu@umfiasi.ro</Link>
; ORCID-iD: 
<Link>https://orcid.org/0000-0001-7407-844X </Link>
fDMD, PhD, Professor; e-mail: 
<Link>alice.murariu@umfiasi.ro</Link>
; ORCID-iD: 
<Link>https://orcid.org/0000-0003-4526- 3878 </Link>
gDMD, PhD, Professor; e-mail: 
<Link>sorin.andrian@umfiasi.ro</Link>
; ORCID-iD: 
<Link>https://orcid.org/0000-0002-9271-6123 </Link>
hDMD, PhD, Professor assistant; e-mail: 
<Link>ionut.taraboanta@umfiasi.ro</Link>
; ORCID-iD: 
<Link>https://orcid.org/0000-0001-5452-916X </Link>
</P>
</Link>

<P><Figure>

<ImageData src="images/Article_11_1-2_4_img_1.jpg"/>
</Figure>

<Link>https://doi.org/10.25241/stomaeduj.2024.11(1-2).art.</Link>
4</P>

<P>ABSTRACT </P>

<P>Objective The purpose of this study was to investigate the effects of different modeling agents on surface hardness and on surface roughness of some conventional nanohybrid composite resins. Metodology Samples of two nanohybrid composite resins: Essentia - group I (n=40) and Neo Spectra ST HV - group II (n=40) were included in this study. Three modeling agents were applied on top of the last composite layer before light curing: Modeling Liquid - subgroup 2 (n=10), 7th generation of bonding system-G-Bond </P>

<P>- subgroup 3 (n=10), and a universal bonding system G-Premio Bond - subgroup 4 (n=10). In subgroup 1 (n=10) no modeling agent was applied. Half of the samples in subgroups 1, 2, 3 and 4 from each group were subjected to surface hardness determination using a digital electronic hardness tester (Vickers Hardness Number (VHN) mean value was reported) and half of them to surface roughness evaluation by Atomic Force Microscopy (AFM) analysis (AFM analysis) (root mean square parameter (Rq) was reported). Results In group I and II statistically significant results were obtained when comparing the surface microhardness in subgroups 2, 3 and 4 with subgroup 1, the microhardness in subgroups 2 and 3 and in subgroup 2 and 4 (Wilcoxon test, p&lt;0.05). In both groups, no statistically significant differences were obtained when comparing the mean  Rq values among all subgroups (ANOVA and post hoc Bonferroni tests, p&lt;0.05). 3 (p=.1520). The difference on the left side was insignificant (0.81, p=0.9933). The total volume removed did not differ significantly between the two methods (p=0.88851) or on the side (p=0.7582). Conclusion All evaluated modeling agents decreased the surface microhardness of the tested nanohybrid composite resins. None of the modeling agents influenced the surface roughness of the composites. </P>

<P>KEYWORDS </P>

<P>Original Articles </P>

<P>Atomic Force Microscopy (AFM); Composite Resins; Microhardness; Modeling Agents; Roughness. </P>

<P>1. INTRODUCTION </P>

<P>Due to technological progress in material science composite resins have become the most commonly used direct restorative materials both on anterior and posterior area of the arches [1]. The main advantages are represented by their use in minimally invasive techniques, esthetic aspect, good mechanical properties, good handling properties (some composite resins having easy transportation, insertion and modeling characteristics) [2]. Rebuilding tooth anatomy is a mandatory step when restoring a tooth and due to the viscosity of resin monomers sometimes it is difficult to shape the composite in order to fit the natural anatomical aspect of the tooth. To prevent the adhesiveness of the composite to the instruments used for transportation, insertion or modeling, different resin monomers or substances were used to lubricate the tools or the brushes. In time practitioners started to use alcohol, acetone and isopropyl acid to control the handling and modeling characteristics of the composites, but they were considered inappropriate for the purpose. Alcohol used as a modeling agent can have detrimental effects on the resin matrix and can decrease the mechanical properties of composites [3]. Some producers introduced wetting agents </P>

<P><Figure>

<ImageData src="images/Article_11_1-2_4_img_2.jpg"/>
</Figure>
OPEN ACCESS This is an Open Access article under the CC BY-NC 4.0 license. </P>

<P>Peer-Reviewed Article Citation: Stoleriu S, Iovan G, Nica I, Pancu G, Georgescu A, Murariu A, Andrian S, Tărăboanță I. Study regarding the influence of various modeling agents on surface microhardness and on surface roughness of nanohybrid composite resins. Stoma Edu J. 2024;11(1-2):51-57. Received: March 21, 2024;  Revised: April 21, 2024;  Accepted: May 02, 2024;  Published: May 15, 2024. *Corresponding author: Simona Stoleriu; Address: Universității Street No.16, Iași, Romania; Tel.: +40-745-106-066; e-mail: 
<Link>simona.stoleriu@e-mail. </Link>

<Link>com</Link>
; Alice Murariu; Address: Universității Street No.16, Iași, Romania; Tel.: +40-745-106-066; e-mail: 
<Link>alice.murariu@umfiasi.ro</Link>
. Copyright: © 2022 the Editorial Council for the Stomatology Edu Journal. </P>

<Sect>
<P>51-57 </P>
</Sect>

<P>51 </P>

<Sect>
<P>Stoleriu S, et al. </P>
</Sect>

<P>Original Articles </P>

<P>(modeling liquids) for better handling. The lubricants can be applied in the layering process of composite application to minimize adhesiveness by wiping the instrument with modeling agents [4,5]. This approach facilitated the improvement of handling and insertion, but also simplified the modeling process of composite resins and improved the surface characteristics by smoothening the surface [6]. Most of the modeling agents are resin-based materials that include little or no filler [7]. Modeling liquids generally contain methacrylates such as urethane dimethacrylate (UDMA), bisphenol A-glycidyl methacrylate (Bis-GMA), and triethylene glycol dimethacrylate (TEGDMA). They are also composed of hydrophobic non-solvated resins and they have low or no organic fillers [8]. Chemical, structural and mechanical alterations have been reported in composite materials after being modeled with the instrument lubricated with modeling agent even when the chemical composition of the agent was similar to that of the composite resin [9]. As an alternative to modeling liquids dental clinicians have used bonding systems to improve composite handling properties, even if this use is not included in the manufacturers' specifications. Some studies have pointed that these techniques can negatively affect the physical properties and surface characteristics of composite resins [10-12]. Significantly higher decrease of composite surface micro-hardness was reported when a non-solvated adhesive (the 3rd step of etch and rinse bonding system) [10] or the self-etch primer (the 1st liquid of the 2-step self-etch bonding system) [11] were used as lubricants. On the contrary, other studies concluded that some modeling agents can preserve the surface hardness [13]. Only a few articles reported data regarding the influence of modeling agents on composite surface roughness and these data are controversial. Some of the studies pointed that the modeling liquid, the universal bonding agent or the 2nd step of a self-etch bonding system have no effect on the surface roughness of the investigated composite resins [10,11]. On the other hand, in other studies the application of a modeling liquid determined an increased surface roughness of the composite resins [13]. The purpose of this study was to investigate the effects of various agents (modeling substances or adhesive systems) on the surface hardness and surface roughness of some conventional nanohybrid composite resins. The null hypotheses were: </P>

<L>
<LI>
<Lbl>1.</Lbl>

<LBody> the use of different modeling agents has no effect on the surface microhardness of nanohybrid composite resins; </LBody>
</LI>

<LI>
<Lbl>2.</Lbl>

<LBody> the use of different modeling agents has no effect on the surface roughness of nanohybrid composite resins. </LBody>
</LI>
</L>

<Sect>
<P>2. METHODS AND MATERIALS </P>

<P>Study design is presented in Fig. 1.roughly in the canine location (Fig. 1). </P>
<Figure>

<ImageData src="images/Article_11_1-2_4_img_3.jpg"/>
</Figure>

<P>Figure 1. Study design. </P>

<P>2.1. Sample preparation </P>

<P>Two nanohybrid composite resins were included in this study: Essentia - group I (GC Corp., Tokyo, Japan) (light enamel shade) and Neo Spectra ST HV- group II (Dentsly Sirona, Konstanz, Germany) (A1 shade). Forty samples of each material were obtained by condensing the resin into the plastic cylinders 6 mm in diameter and 4 mm in height. The molds were placed on a glass plate in contact with a transparent matrix to ensure a smooth surface of the sample. Two layers of each material were inserted, each layer being individually cured for 40 seconds using a LED lamp (Woodpecker Med. Instrument, Guilin, China) with the intensity of 1.200 mW/cm2. Before light-curing the last layer, three different modeling agents were applied on the surface of 30 samples from each group using a brush. Modeling Liquid (GC Corp., Tokyo, Japan) was applied on 10 samples from each group (subgroup 2), G-Bond bonding system (GC Corp., Tokyo, Japan) on 10 samples (subgroup 3) and universal bonding system G-Premio Bond (GC Corp., Tokyo, Japan) were applied in self-etch technique on 10 samples (subgroup 4). Different brushes were used for each modeling agent and for a specific type of agent the brush was replaced by a new one after 10 applications. The same quantity of the liquid (one drop) was placed in a plastic box, the brush was submersed one time in the liquid and the excess was removed by touching a paper towel with the brush. For the rest of 10 samples in each group no modeling agent or bonding system was applied before light-curing the last layer of composite resin (subgroup 1). Details related to the chemical composition of the two composite resins and modeling agents are presented in Table 1. </P>
</Sect>

<P>52 51-57 </P>

<P>The effect of modeling agents on nanohybrid composite resins surface properties </P>

<P>Table 1. Chemical composition of the tested materials. </P>

<Table>
<TR>
<TD/>

<TD>Material type </TD>

<TD>Composition </TD>

<TD>The manufacturing company </TD>
</TR>

<TR>
<TD>Essentia </TD>

<TD>Nanohybrid composite resin </TD>

<TD>Matrix: UDMA, Bis-MEPP, Bis-EMA, Bis-GMA, TEGDMA Filler: prepolymerized silicon particles, barium glass (81% by weight and 65% by volume) </TD>

<TD>GC Corp., Tokyo, Japan </TD>
</TR>

<TR>
<TD>Neo Spectra ST HV</TD>

<TD> Nanohybrid composite resin </TD>

<TD>Matrix: Methacrylate modified polysiloxane (organically modified ceramic), Bis-EMA, TEGDMAFiller: prepolymerized spherical particles (15 µm) and 0.6 µm barium glass and 0.6 µm ytterbium fluoride particles, silicon dioxide nanoparticles (10 nm), (77–79% by weight and 59–61% by volume) </TD>

<TD>Dentsly Sirona, Konstanz, Germany </TD>
</TR>

<TR>
<TD>Modeling Liquid </TD>

<TD>Modeling agent </TD>

<TD>UDMA, 2-HEMA, TEGDME </TD>

<TD>GC Corp., To-kyo, Japan </TD>
</TR>

<TR>
<TD>G-Bond </TD>

<TD>adhesive system (7th generation) </TD>

<TD>Phosphoric acid ester monomers, 4-MET monomer, nanoparticles </TD>

<TD>GC Corp., To-kyo, Japan </TD>
</TR>

<TR>
<TD>G-Premio Bond </TD>

<TD>Universal adhe-sive system </TD>

<TD>4-MET, MDP and MDTP </TD>

<TD>GC Corp., To-kyo, Japan </TD>
</TR>

<TR>
<TD>UDMA- urethane dimethacrylate; Bis-MEPP- bisphenol-A ethoxylate dimethacrylate; Bis-EMA- ethoxylated bisphenol-A dimethacrylate; Bis-GMA-bisphenolglycidyl methacrylate; TEGDMA- triethylene glycol dimethacrylate; UDMA- urethane dimethacrylate; 2-HEMA- 2 hydroxyethyl methacrylate, TEGDME- trimethylene glycol dimethyl ether; 4-MET- 4-[2-(methacryloyloxy)ethoxycarbonyl]phathalic acid;MDP- 10-Methacryloyloxydecyl dihydrogen phosphate; MDTP- 4,4',4&quot;- [(methanetriyltris (benzene-4,1-diyl)) tris (oxy)] triphthalonitrile. </TD>
</TR>
</Table>

<P>The samples were then removed from the plastic mold, the lower surfaces were marked and the upper surfaces of the samples were finished with medium, fine and extra fine abrasive discs (Sof-LexTM, 3M ESPE) under water cooling, for 20 seconds for each grit. The samples were then submersed for 24 hours in a container with distilled water. Half of the samples in subgroups 1, 2, 3 and 4 from each group were subsequently subjected to surface hardness determination and half of them to surface roughness evaluation. </P>

<P>2.2. Determination of surface microhardness </P>

<P>On the unmarked surfaces of the samples Vickers hardness was determined using a digital electronic hardness tester (Micro-Vickers Hardness System CV400 DMTM, CV Instruments Namicon). CV-400 mico/ macrohardness tester is a solid and accurate hardness tester used on an industrial and laboratory scale. It is equipped with an automatic Vickers indentation head and a special indentation measurement and evaluation software. In this study a load of 200 g with a 10-second dwell time was applied on Vickers hardness head, according to the International Organization for Standardization (ISO) 6507/ASTM E 384 standards. For each sample 2 indentations were made, the distance between the indentations being of 1 mm. The surface hardness was determined by measuring the indentation diagonal and was expressed as Vickers Hardness Number (VHN). The final surface hardness of a sample was calculated as the average value of the two determinations. </P>

<P>2.2. Determination of surface microroughness </P>

<P>Half of the samples in each group were analyzed for surface roughness using atomic force microscopy (SOLVER PRO-M scanning probe microscope, NTMDT, Russia). The measurements were performed in air environment and in static force operating mode. 2D and 3D images were obtained on sample area of 20 × 20 µm. On 3D images the surface roughness was reported as the root mean square roughness </P>

<P>parameter (Rq). Two hundred fifty-six linear scans were performed on each section and the final Rq value of the sample was reported as the mean value of all scans. </P>

<P>2.3. Statistical analyses </P>

<P>The data were analyzed using IBM SPSS Statistics </P>

<P>28.0.1 program (SPSS Inc., Chicago, IL, USA). The effects of modeling agents on hardness were analyzed using the Wilcoxon test (at p&lt;0.05 significance level) and the effects on surface roughness using ANOVA and post hoc Bonferroni tests (at p&lt;0.05 significance level). </P>

<P>3. RESULTS </P>

<P>The mean values and standard deviation of surface microhardness (VHN) in groups and subgroups are presented in Table 2. </P>

<P>Table 2. Mean VHN values and standard deviations of surface microhardness (VHN) in groups and subgroups. </P>

<Table>
<TR>
<TH/>

<TH>Subgroup 1 </TH>

<TH>Subgroup 2 </TH>

<TH>Subgroup 3 </TH>

<TH>Subgroup 4 </TH>
</TR>

<TR>
<TH>Group I </TH>

<TD>68.04 ± 0.45 </TD>

<TD>63.58 ± 0.77 </TD>

<TD>54.25 ± 1.34* </TD>

<TD>56.02 ± 0.48* </TD>
</TR>

<TR>
<TH>Group II </TH>

<TD>66.05 ± 0.67 </TD>

<TD>58.23 ± 0.70 </TD>

<TD>44.93 ± 0.99* </TD>

<TD>46.05 ± 0.60* </TD>
</TR>
</Table>

<P>* represent no statistical differences among the subgroups in group (p&gt;0.05) </P>

<P>In group I and II statistically significant results were obtained when comparing the surface microhardness values of the samples in subgroups 2, 3 and 4 with subgroup 1 of the samples in subgroups 2 and subgroup 3 and of subgroup 2 with subgroup 4 (Table 2). </P>

<P>3.2. Surface roughness evaluation </P>

<P>3D and 2D aspects of some samples in group I subgroups 1-4 and group II subgroups 1-4 are presented in Figs. 2, 3, respectively. </P>

<P>Original Articles </P>

<Sect>
<P>51-57 </P>
</Sect>

<P>53 </P>

<Sect>
<P>Stoleriu S, et al. </P>
</Sect>

<P>Original Articles </P>

<Table>
<TR>
<TH>Group I </TH>

<TH>3D aspect of the sample </TH>

<TH>2D aspect of the sample </TH>
</TR>

<TR>
<TD>Subgroup 1 </TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_4.jpg"/>
</Figure>
</TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_5.jpg"/>
</Figure>
</TD>
</TR>

<TR>
<TD>Subgroup 2 </TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_6.jpg"/>
</Figure>
</TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_5.jpg"/>
</Figure>
</TD>
</TR>

<TR>
<TD>Subgroup 3 </TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_7.jpg"/>
</Figure>
</TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_7.jpg"/>
</Figure>
</TD>
</TR>

<TR>
<TD>Subgroup 4 </TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_8.jpg"/>
</Figure>
</TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_9.jpg"/>
</Figure>
</TD>
</TR>
</Table>

<P>Figure 2. 3D and 2D aspect of Essentia samples when using no modeling agent (subgroup 1), Modeling Liquid (subgroup 2), G-Bond (subgroup 3), G-Premio Bond (subgroup 3).. </P>

<Table>
<TR>
<TH>Group II </TH>

<TH>3D aspect of the sample </TH>

<TH>2D aspect of the sample </TH>
</TR>

<TR>
<TD>Subgroup 1 </TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_10.jpg"/>
</Figure>
</TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_11.jpg"/>
</Figure>
</TD>
</TR>

<TR>
<TD>Subgroup 2 </TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_12.jpg"/>
</Figure>
</TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_13.jpg"/>
</Figure>
</TD>
</TR>

<TR>
<TD>Subgroup 3 </TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_14.jpg"/>
</Figure>
</TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_13.jpg"/>
</Figure>
</TD>
</TR>

<TR>
<TD>Subgroup 4 </TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_15.jpg"/>
</Figure>
</TD>

<TD><Figure>

<ImageData src="images/Article_11_1-2_4_img_16.jpg"/>
</Figure>
</TD>
</TR>
</Table>

<P>Figure 3. 3D and 2D aspect of NeoSpectra ST samples when using no modeling agent (subgroup 1), Modeling Liquid (subgroup 2), G-Bond (subgroup 3), G-Premio Bond (subgroup 3). </P>

<P>54 51-57 </P>

<P>The effect of modeling agents on nanohybrid composite resins surface properties </P>

<P>The mean Rq values and standard deviation in subgroups 1-4 of groups I and II are presented in table 3. In both groups, no statistically significant differences were obtained when comparing the surface roughness among subgroups 1, 2, 3 and 4. </P>

<P>Table 3. </P>

<Table>
<TR>
<TH/>

<TH>Subgroup 1 </TH>

<TH>Subgroup 2 </TH>

<TH>Subgroup 3 </TH>

<TH>Subgroup 4 </TH>
</TR>

<TR>
<TH>Group I </TH>

<TD>0.051±0.003 </TD>

<TD>0.067±0.002 </TD>

<TD>0.055±0.003 </TD>

<TD>0.064±0.003 </TD>
</TR>

<TR>
<TH>Group II </TH>

<TD>0.052±0.002 </TD>

<TD>0.064±0.003 </TD>

<TD>0.057±0.004 </TD>

<TD>0.065±0.002 </TD>
</TR>
</Table>

<P>4. DISCUSSION </P>

<P>The first null hypothesis of the study was rejected, all the agents used for modeling the composite resin decreasing the composite surface hardness. This might be determined by the filler content in the final composite layer after using modeling agents [7]. All modeling agents have a low filler percentage, so their application on the last composite layer lead to a resin-rich layer formation on the surface [14]. As a result, lower VHN values are obtained after modeling agent application. Generally, this extern layer having high resin content is removed by the finishing procedure. Although all the samples in this study were finished, VHN values were still lower in the groups where modeling agents were used when comparing to the control group (Table 2). Even if the external resin-reach layer was removed by finishing, it seems that wetting agents can diffuse in the deeper layers of the material, changing their chemical composition and hardness [15]. Another explanation for decreasing the surface hardness as a result of modeling agents application is the presence of 2-HEMA molecule in the composition of the Modeling Liquid, a hydrophilic monomer which can cause water absorption due to a hydroxyl and carbonyl group [16]. Therefore, as it was reported even in previous studies, HEMA can reduce the hardness of composite resin [17]. The 2021 study conducted by Ezgi T. Bayraktar also focused on the effects of modeling agents on mechanical properties of composites when using modeling agents on composite top layer [8]. Their study reported the reduction of surface microhardness as a result of modeling agents application in the last material layer, similar to the results of the present study. Also, Tuncer et al. evaluated the effects of a modeling agent (Modeling Resin, Bisco, IL, USA) on the surface microhardness of different composite resins and they reported decreased surface microhardness when using a modeling agent for two of the tested composite resin [7]. In our study the group in which the Modeling Liquid was used recorded highest hardness value when comparing to the 7th generation of adhesive system and to the universal bonding system. That aspect might be correlated to the presence of UDMA molecule in the composition. This molecule consists of two urethane bonds and a flexible aliphatic core and forms double hydrogen bonds [18]. It has been </P>

<P>reported that resins containing UDMA have superior polymerization rates and a high degree of conversion [18]. Consequently, the degree of conversion and polymerization rate can affect the surface hardness of the samples. However, Tuncer et al. pointed  that differences in microhardness between different composites may not be attributed to the degree of conversion [7]. Also Kutuk et al tested Modeling Liquid and two universal adhesive agents (G-Premio Bond, GC Corp.; OptiBond XTR, KavoKerr, Orange, CA, United States) as modeling agents in combination with nanohybrid composite resins [11]. The study found the lowest microhardness values when OptiBond XTR was used. Contradictory to the findings of this study, in our research the 7th generation of bonding agent determined lower microhardness of the tested materials when comparing to the Modeling Liquid group and control group and the same effect as the universal bonding resin. The composite resins hardness is also determined by the characteristics of filler particles and their interaction with the polymers [19,20]. It was reported that nanofilled composite resins exhibit improved hardness and abrasion resistance when comparing to other categories of composite resins [21]. That was the reason for including nanohybrid composites as testing materials in our study. The low-viscosity agents used to improve composites handling characteristics act by reducing the surface tension [22], but also by filling the defects in the material by diffusing through the pores resulted during layering procedure, making the material more resistant to degradation [5,23]. The final layer of restorative material has a decisive effect on aesthetics, color stability, and surface roughness [24]. Smooth and well-polished surfaces decrease plaque retention and consequently lower the risk of secondary caries and staining. In our study, the roughness values of both tested composite resins were lower than the plaque accumulation threshold of 20 µm [25]. Adequate finished and polished surfaces are mandatory to achieve long-lasting clinical restorations. Composites having nanoparticles present high polishability when using tools containing Al2O3 or diamond particles [26,27]. In our study, the specimens were polished using Sof-Lex aluminum oxide discs to achieve optimal surface smoothness. Following the polishing procedure, in our study the samples were submersed in distilled water for 24 hours to remove unreacted monomers and to allow post-polymerization process. It has been suggested that some liquid agents can be used to achieve smooth composite resin surface [28,29]. However, it has been proved to be very difficult to obtain a regular surface when using liquid resins [30]. All tested modeling agents in the present study had no effect on surface roughness of composite resins (Tab. 3), so the second null hypotesis was accepted]. </P>

<P>Original Articles </P>

<Sect>
<P>51-57 </P>
</Sect>

<P>55 </P>

<Sect>
<P>Stoleriu S, et al. </P>
</Sect>

<P>Original Articles </P>

<Sect>
<P>5. CONCLUSION </P>
</Sect>

<P>Within the limitations of this study, all evaluated modeling agents decreased the surface microhardness of the tested nanohybrid composite resins. None of the modeling agents influenced the surface roughness of the composites. Further clinical studies should be performed for more accurate understanding of the effects of modeling agents on the mechanical properties and surface condition of composite resins. </P>

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</P>

<P>AUTHOR CONTRIBUTIONS </P>

<P>SS, GP, GI: concept; SS, IN, AM: protocol; SS, IT, AG: data gathering and analysis; SS, GP: data interpretation; SA, GI: revising the manuscript. </P>

<P>CONFLICT OF INTEREST </P>

<P>Authors declare that there is no conflict of interests. </P>

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</Sect>

<P>56 51-57 </P>

<P>The effect of modeling agents on nanohybrid composite resins surface properties </P>

<Sect>
<P>Simona STOLERIU </P>
</Sect>

<P>DMD, PhD, Associate Professor Department of Odontology Periodontology and Fixed Prosthodontics “Grigore T. Popa” University of Medicine and Pharmacy Iasi, Romania </P>

<Sect><Figure>

<ImageData src="images/Article_11_1-2_4_img_17.jpg"/>
</Figure>
</Sect>

<P>Simona Stoleriu is an educationist, researcher, and specialist in cariology and operative dentistry. Since 2018 she is associate professor on the Faculty of Dental Medicine, “Grigore T. Popa” University of Medicine and Pharmacy Iaşi, Romania in 2018. She received PhD in Medical Dentistry in 2009 and she became senior specialist in General Dentistry in 2006. The research activity focused on early diagnosis of dental caries, non-operative and restorative treatment of caries lesion, diagnosis and treatment of wear lesions, the behavior of restorative materials in oral environment, factors which can influence the surface condition and mechanical properties of direct restorative materials, and remineralization of dental hard tissues. She was also being invited as a speaker on many national and international congresses and he received 10 awards for the scientific activity. </P>

<P>Questions </P>

<P>1. Different tools have been developed to improve the fit and the configuration of composite resins: </P>

<L>
<LI>
<Lbl>qa. </Lbl>

<LBody>Titanium coated instruments; </LBody>
</LI>

<LI>
<Lbl>qb.</Lbl>

<LBody> Aluminum coated instruments; </LBody>
</LI>

<LI>
<Lbl>qc.</Lbl>

<LBody> Resin knives; </LBody>
</LI>

<LI>
<Lbl>qd.</Lbl>

<LBody> Brushes. </LBody>
</LI>
</L>

<P>2. Practitioners have used multiple lubricants in layering process of composite application to minimize adhesiveness of the material to the instrument: </P>

<L>
<LI>
<Lbl>qa.</Lbl>

<LBody> Acetone; </LBody>
</LI>

<LI>
<Lbl>qb.</Lbl>

<LBody> Glycerine; </LBody>
</LI>

<LI>
<Lbl>qc.</Lbl>

<LBody> Modeling liquid; </LBody>
</LI>

<LI>
<Lbl>qd.</Lbl>

<LBody> Bonding system. </LBody>
</LI>
</L>

<P>3. The followings are true regarding the conclusions of the present study: </P>

<L>
<LI>
<Lbl>qa.</Lbl>

<LBody> Modeling liquid had no effect on surface hardness; </LBody>
</LI>

<LI>
<Lbl>qb. </Lbl>

<LBody>The use of 7th generation of adhesive system increased surface roughness of composite resin; </LBody>
</LI>

<LI>
<Lbl>qc. </Lbl>

<LBody>The use of universal bonding system had no effect on surface roughness of composite resin; </LBody>
</LI>

<LI>
<Lbl>qd.</Lbl>

<LBody> Modeling liquid increased composite surface roughness. </LBody>
</LI>
</L>

<P>4. Some studies have pointed that adhesive agent used on the extern layer of the restoration may lead to: </P>

<L>
<LI>
<Lbl>qa.</Lbl>

<LBody> Changes of composite color; </LBody>
</LI>

<LI>
<Lbl>qb.</Lbl>

<LBody> Changes of composite physical properties; </LBody>
</LI>

<LI>
<Lbl>qc.</Lbl>

<LBody> Changes of composite chemical properties; </LBody>
</LI>

<LI>
<Lbl>qd.</Lbl>

<LBody> Increased viscosity of the composite resin. </LBody>
</LI>
</L>

<P>Original Articles </P>

<Sect>
<P>51-57 </P>
</Sect>

<P>57 </P>
</Part>
</TaggedPDF-doc>
