Abstract
The objective of this study was to evaluate microbial leakage by means of genome counts, through the implant–abutment interface in dental implants with different Morse taper abutments. Fifty-six samples were prepared and divided in four groups: CMC TB (14 Cylindrical Implants–14 TiBase Abutments), CMX TB (14 Conical Implants–14 TiBase Abutments), CMX PU (14 Conical Implants–14 Universal Abutment) and CMX U (14 Tapered Implants–14 UCLA Abutments). Assemblies had their interface submerged in saliva as the contaminant. Samples were subjected either to thermomechanical cycling (2 × 106 mechanical cycles with frequency of 5 Hz and load of 120 N simultaneously with thermal cycles of 5–55 °C) or thermal cycling (5–55 °C). After cycling, the contents from the inner parts of assemblies were collected and analyzed using the Checkerboard DNA–DNA hybridization technique. Significant differences in the total genome counts were found after both thermomechanical or thermal cycling: CMX U > CMX PU > CMX TB > CMC TB. There were also significant differences in individual bacterial counts in each of the groups (p < 0.05). Irrespective of mechanical cycling, the type of abutment seems to influence not only the total microbial leakage through the interface, but also seems to significantly reflect differences considering individual target species.
Keywords: dental implants, dental implant–abutment design, microbiological phenomena
1. Introduction
With the continuous advancement of rehabilitation materials and techniques, implant-supported restorations have been extensively used in dentistry with a very high predictability rate of both success and survival [1]. Although the use of osseointegrable implants can be considered safe and predictable, the oral environment presents itself as one of the most challenging places in the human body, bringing mechanical, thermal and acidity variations and, mainly, microbial challenges. The use of two-part dental implants presents as advantages the reliable standard protocol and easy handling of peri-implant tissues, providing several possibilities of the transmucosal area, prosthetic heights, diameters and angulation. However, these systems still have a major concern related to the implant–abutment interface; to date, it has not been possible to make it impervious to the passage of microorganisms, including those that may cause peri-implant diseases [2].
The presence of microorganisms at this interface, if not controlled, can result in inflammatory processes and cause damage to peri-implant tissues as the bacterial presence activates inflammatory cells, inducing osteoclastic action and consequent bone loss [3]. Scanning electron microscopy images demonstrate the presence of bacteria at the implant–abutment interface in failed implants, suggesting that these bacteria might be part of the factors causing inflammation and consequent bone loss in the region [4].
It already seems clear from the literature that Morse taper connections tend to present a lower amount of bacterial penetration through the interface region, resulting in the reduced contamination of the inner parts of the implant components. Most of these studies have compared conical and external hexagon connections, but also often include an internal hexagon [2]. The ostensible comparison between these three renowned interfaces and the considerable number of works demonstrating the superiority of conical connections in the reduction of bacterial infiltrate can lead the reader, clinician or even researcher to the erroneous understanding that all conical connections behave in the same way. In a study, Bella et al. compared indexed (two-piece) and non-indexed (solid one-piece) conical connection abutments and found a statistical difference in the bacterial infiltrate between them [5]. Among conical connections, we can find numerous differences; the angulation of the cone in relation to the long axis of the implant, the fixation of the implant using a through screw (two-piece) or a solid abutment and the material that the abutment is made of. The macrogeometry of implants can also play a relevant role in the passage of microorganisms and other substances into the implants, since the distribution of forces throughout the systems can alter the micro-movements of the components and influence the microgaps into the interface.
Therefore, it is important to have knowledge about how the connections of three different abutments that are widely used in dental clinics behave: Universal abutment, widely used due to its simplicity, reliability and good adaptation; UCLA-type abutments, which, due to their low cost and because they represent a direct connection from the implant platform, are widely used in cases of reduced transmucosal tissue, but may represent a potential risk for the passage of microorganisms due to the finishing process and polishing, as seen in a study by Rismanchian et al. [6]; and the TiBase abutments that are gaining strength nowadays due to their versatility and the possibility of inserting oral rehabilitation through implants in the digital dentistry world, but their use on a large scale must be carried out with caution, since the literature shows differences in the misadaptation gap between different manufacturers of TiBase abutments [7]. Also, how the shape of the implants can influence the adaptation of the components and the passage of microorganisms after loading should be investigated.
The specificities of each system or components, such as changes in the insertion torque, through screw and composition of the implant alloys can generate different types of bacterial infiltrates and these can be associated with the inflammatory processes that give rise to peri-implantitis. Socransky et al. demonstrated that different bacteria are related to different clinical parameters, which allows us to relate certain bacterial complexes to different clinical situations [8]. The Checkerboard DNA–DNA hybridization detection methodology used in this study allows the simultaneous identification and quantitation of up to 45 different species of microorganisms in the same sample [9].
Knowledge of the behavior of different implants and components in the face of the passage of microorganisms can provide relevant information not only to encourage new research in this area of knowledge, but also help the rehabilitation dentist when making decisions in the phase of choosing implants and prosthetic components aiming for the greater predictability of long-term treatment success. In this context, the objective of this study was to evaluate the bacterial infiltrate recovered from three different conical connections (universal abutment, Co-Cr UCLA and TiBase 4CAD) after thermomechanical cycling. The hypotheses tested were that there would be differences in the bacterial quantitation between conical and cylindrical implants with different connections and both thermal and thermomechanical simulations would influence the results.
2. Materials and Methods
2.1. Experimental Design
This is a randomized in vitro experimental study, with parallel groups, investigating the leakage of microorganisms through the implant–abutment interface of a system with cylindrical and conical implants, with Morse taper connection and different prosthetic abutments. The research was carried out at the Molecular Dental Diagnostic Laboratory of the School of Dentistry of Ribeirão Preto, University of São Paulo. Human saliva was used as contaminant media, the study protocol was approved by the Local Ethics Committee under the number CAAE: 25836819.2.0000.5419 and all experiments were carried out with the participants’ written consent.
2.2. Implant and Abutment Selection and Constitution of Study Groups
This research involved the use of grade 4 titanium dental implants (n = 56) with Morse taper connection (Singular Implants, Natal, RN, Brazil), of which 42 had a conical shape (CMX; 4.0 × 13—Ref: 100.194) and 14 cylindrical (CMC; 4.0 × 13—Ref: 100.124). All implants used in the study are indicated for intraosseous use, with an internal cone angulation measuring 11.5°. The abutments investigated were as follows: (TB) Tibase 4 CAD CM N—1.5 mm (n = 28; Ref: 126.125; Figure 1), (PU) Universal abutment CM—3.3 × 4–1.5 mm (n = 14; Ref: 119.014; Figure 2) and (U) UCLA Co-Cr CM—1.5 mm (n = 14; Ref: 103.120; Figure 3). Among the 14 samples in each group, we separated 10 samples for the thermomechanical cycle and 4 samples we removed from the mechanical challenge, which then underwent solely thermal cycling.
Figure 1.
Tibase 4 CAD abutment.
Figure 2.
Universal Abutment.
Figure 3.
UCLA abutment.
2.3. Collecting Negative Control and Abutment Fixation
All the implants and components used were previously sterilized by gamma ray; however, to ensure that there were no pre-existing bacteria, before implant–abutment assembly, samples from the inner parts of the implants and the surfaces of the screws from all samples were collected with the aid of sterilized microbrushes serving as negative control for contamination, with a total of 56 samples obtained. Samples were stored individually in microtubes with 80 μL of TE buffer solution (10 Mm Tris-HCl, 1 Mm EDTA pH 7.6; Figure 4).
Figure 4.
Sample taken from the inner part of the implants and components before thermocycling.
The implant–abutment set was connected using a digital torquemeter (Torque Meter TQ 8800, Instrutherm, São Paulo, Brazil) which was fitted to a delineator created in the Department of Dental Materials and Prosthetics of the School of Dentistry of Ribeirão Preto-USP to maintain standardized positioning of the prosthetic key for applying force (torque). The abutments were connected to the implants applying the torque load Ncm recommended by the manufacturer and experimental groups were as follows: CMC TB (32 Ncm), CMX TB (32 Ncm), CMX PU (32 Ncm) and CMX U (20 Ncm).
As recommended in the literature, after 10 min of applying the load recommended by the manufacturer, the retaining screw was retorqued applying the same load, aiming to avoid loss of torque resulting from the deformation and flow of the components [10,11].
All component attachment steps took place using a laminar flow, with the work surface disinfected with 70% alcohol and previously sterilized for 30 min by ultraviolet light. The glassware, tweezers and keys for applying force were previously sterilized in an autoclave and the researchers were equipped with personal protective equipment.
2.4. Polyurethane Bases and Sample Positioning
The 56 implant–abutment sets were embedded in polyurethane to be subjected to thermocycling and cyclic loading prior to the microbial contamination test. A silicone base was used as a mold to construct the test specimens. On a precision scale, 7.5 g of Polyol + 7.5 g of Isocyanate (Isocyanate F 160, Sika Axson, Madison Heights, MI, USA) were weighed, manipulated for 30 s, poured onto the silicone base and awaited the polymerization process, as recommended by the manufacturer.
To standardize the implants positioning on polyurethane base, an adjustable base parallelometer was used. The silicone base was positioned on the parallelometer base and the implant–prosthetic abutment set was connected to the mobile rod, ensuring the same position in all sets.
The positioning of the implants was carried out so that the prosthetic platform was at the level of the polyurethane surface, simulating an implant at bone level.
2.5. The 3D Crowns
Three-dimensional resin crowns in the shape of a maxillary canine were fabricated using the Autodesk MeshMixer version 3.5 software (Autodesk Inc., San Rafael, CA, USA) for the cyclic load simulation on the assemblies. A profile projector (Profile Projector Model 6C, Nikon, Tokyo, Japan) was used to standardize the crown dimensions for the different abutments. The crowns (Figure 5) were printed on the Phrozen Sonic 4K 3D printer [Phrozen Tech. Co., Hsinchu City, Taiwan (R.O.C.)] with 3D temporary resin (Printax, Phrozen Tech. Co.). The loading applicators, 15 mm in diameter × 15 mm in width and with an angulation in the internal region of 10° that were coupled to the fatigue machine, were also manufactured in printed 3D resin, following the same protocol as the crowns.
Figure 5.
Three-dimensional resin-printed crowns in the shape of a maxillary canine.
2.6. Saliva Collecting
To collect the unstimulated human saliva used as a contaminant media for the implant assemblies, 20 healthy adults were selected among students and employees of the university itself. Participants of both genders with no signs and symptoms of systemic diseases or infections in the oral cavity were included. Furthermore, a group of participants with similar ages and environmental conditions was sought, aiming for uniform saliva samples. Collections were always carried out at the same time and place.
Each participant contributed 6 mL of saliva. After individual collecting, samples from the 20 participants were pooled and homogenized for 3 min and transferred to a single tube constituting the contaminant media and stored in a bacteriological oven at 37 °C throughout the cyclic loading and thermocycling test (Figure 6).
Figure 6.
Tube with saliva collected from participants that served as a contaminant for the samples.
2.7. Final Preparation of Specimens and Contamination Test
After re-torque, the screw access channel was sealed with Teflon tape and light-polymerizable microhybrid composite resin (Applic Flow-Maquira), then the crown was cemented onto the components with Polyether (Impregum soft—3M).
Rubber tubes were fixed to the polyurethane with water-based silicone and, in this way, the implant–abutment assembly was isolated from the external environment in a reservoir for placing saliva during the cyclic load application test. Next, 3 mL of saliva was inserted into each of the reservoirs (Figure 7). The volume of saliva added was sufficient to cover the implant–prosthetic abutment connection interface without reaching the access hole of the abutment fixation screw, in order to minimize the passage of microorganisms from saliva through any route other than the implant–abutment interface. At the end of the cyclic loading test, samples (n = 10) from the tube containing the human saliva used as contaminant media were collected and used as positive control to verify the microbial profile of the saliva before and after the loading test period.
Figure 7.
Pipette inserting the collected saliva into the implant–abutment interface before the thermomechanical test.
2.8. Thermomechanical Cycling
Ten implant–abutment sets from each group were subjected to the cyclic load test. The chewing mechanical fatigue machine (BIOPDI—Equipment for research into medical and dental materials, São Carlos, Brazil) was used to simulate human chewing, which is in the Biomechanics Laboratory of the School of Dentistry of Ribeirão Preto. This machine made it possible to conduct dynamic tests on 10 specimens simultaneously. Force applicators were made on the 10 pistons using a 3D resin printer. The 10 pistons used to apply load acted independently on each specimen.
The loading of each specimen during the simulation of chewing cycles occurred through a system of springs. The load was applied during thermal cycles of 5–55 °C (25 s of filling, 5 min of residence and 35 s of emptying). This loading application process was carried out automatically.
The test specimens’ sets, as seen in Figure 8, immersed in saliva were fixed to the base of the testing machine, remaining juxtaposed, since their polyurethane bases were built with the same dimensions as the machine’s fixing niches. The specimens were positioned and the load was applied incisally from the prosthetic crown to the long axis of the implant. The entire system was sealed with flexible adhesive film (Parafilm, Neehan, WI, USA), which allowed its isolation from the external environment.
Figure 8.
Thermomechanical cycling test machine with the specimens fixed and the load applicators.
The machine was programmed for the controlled application of a load of 120 N through the loading applicators in the incisal region of each crown. The 2 × 106 cycles were performed, with a frequency of 5 Hz. Simultaneously, the base to which each specimen was fixed performed horizontal movements of 1 mm to the right side and 1 mm to the left side, replicating the excursive mandible movements.
2.9. Thermocycling Test
The specimens were also tested for the passage of microorganisms when subjected to thermal cycling only, without cyclic loading. Four implant–prosthetic abutment sets from each of the 4 groups analyzed were fixed to polyurethane and submerged in 3 mL of human saliva and coupled to the base of the fatigue machine, undergoing only thermocycling, without applying force.
2.10. Assessment of Microbial Leakage Using Checkerboard DNA–DNA Hybridization Method
Samples from the inner part of the implant–abutment assemblies subjected to either thermocycling tests with cyclic load or thermocycling were collected to identify and quantify the microorganisms that penetrate through the interface. For this, the Checkerboard DNA–DNA hybridization method was used according to Socransky et al. with a modification by do Nascimento et al. [9,12].
Before collecting, the rubber tubes were removed from the polyurethane base of assemblies and all the external surfaces of experimental and control sets were carefully washed with 70% alcohol and dried with sterilized gauze pads. The crowns were then removed from the prosthetic abutment with the aid of hemostatic forceps. The sets were reopened to collect content from the inside of the implants and fixation screw threads using sterile microbrushes. The samples were individually inserted in microtubes containing 150 μL of TE buffer solution and stored at 4 °C until laboratorial processing.
For this study, 40 different microbial species were selected, ranging from the initial colonizers of the microbial biofilm to species considered pathogenic for the development of periodontal and peri-implant diseases. Four species of Candida, commonly detected in the oral cavity, were included: Candida tropicalis, Candida glabrata, Candida dubliniensis, Candida albicans, Streptococcus pneumoniae, Streptococcus gallolyticus, Veillonella parvula, Treponema denticola, Tannerella forsythia, Streptococcus sobrinus, Streptococcus sanguinis, Streptococcus salivarius, Staphylococcus pasteuri, Streptococcus parasanguinis, Streptococcus oralis, Streptococcus mutans, Solobacterium moorei, Streptococcus mitis, Streptococcus constellatus, Staphylococcus aureus, Pseudomonas putida, Prevotella nigrescens, Parvimona micra, Prevotella melaninogenica, Prevotella inter media, Porphyromonas gingivalis, Porphyromonas endodontalis, Peptostreptococcus anaerobius, Pseudomonas aeruginosa, Mycoplasma salivarium, Lactobacillus casei, Klebsiella pneumoniae, Fusobacterium nucleatum, Enterococcus faecalis, Eikenella corrodens, Escherichia coli, Campylobacter rectus, Capnocytophaga gingivalis, Bacteroides fragilis and Aggregatibacter actinomycetemcomitans.
2.11. Data Analysis
Data from Checkerboard DNA–DNA hybridization were analyzed using the CLIQS 1D software (Totallab, Newcastle, UK). The approximate number of microbial cells (genome counts) present in each investigated sample was estimated by comparing the intensity of the hybridization signals obtained by the intersection of the samples against the labeled probes in relation to the intensity of the standards containing 105 and 106 cells from each of the 40 target species.
Descriptive analysis of the data was performed, including point estimators such as means, medians and quartiles (first quartile—Q1—and third quartile—Q3), according to their distribution and variance of experimental errors. Data normality was verified by visual inspection of density graphs, histograms and Q-Q plots and confirmed by the Shapiro–Wilk significance test. Homoscedasticity was verified by Levene’s test. The analysis of the effect of the abutments and thermocycling or cyclic load tests on the count of microorganisms was carried out using the non-parametric and multifactorial Brunner–Langer method with Bonferroni adjustment. Considering the multifactorial and correlational nature of microbiological data, the Generalized Estimating Equations—GEE—model was used to compare the microbial profile between groups. Data were processed using the statistical software R (R software, version 4.1.0; R Foundation for Statistical Computing, Vienna, Austria) and differences were considered significant at p value < 0.05.
3. Results
None of the negative control samples from all of the evaluated groups, collected from inside the implants prior to the thermocycling and cyclic loading test, showed positive results for microbial presence, ensuring the sterilization effectiveness carried out by the manufacturer.
After the thermocycling and cyclic loading test, all implant–abutment sets of all abutments investigated showed the presence of microorganisms, totaling 2,041,551 recorded genomes. A similar result was observed for the abutments that were subjected only to the thermal test, with a total of 1,997,290 genomes. Among the groups subjected to thermocycling and cyclic loading, the median total genome count, in order from highest to lowest, was CMC TB (627,805), CMX TB (572,820), CMX PU (519,282) and CMX U (321,644). Among the groups subjected only to thermal cycling, the medians were CMC TB (617,112), CMX TB (550,809), CMX PU (513,847) and CMX U (315,522).
The groups investigated showed significant differences in the genome counts (WTS and ATS; p < 0.005). Figure 9 illustrates the median, maximum and minimum values and interquartile range of the total genome counts of microbial cells from samples collected inside the implants and fixation screws subjected or not to cyclic loading, while in Table 1, Table 2, Table 3 and Table 4, the values referring to the individual count of each of the 40 target species evaluated in the study are described. The lowest values recorded between the thermocycling and cyclic load groups were the CMX U group, while the CMC TB and CMX TB groups presented the highest values (Tukey; p < 0.005). Among the thermocycling groups, the one that presented the best results was also the CMX U group.
Figure 9.
Box Plot with median, maximum and minimum values and interquartile range of quantification of total genomes of the 40 target species identified in the screw threads and inside the implant of the groups subjected to cyclic loading (C) and thermocycling (T).
Table 1.
CMC TB Group. Minimum (Min), 1st Quartile, median, mean, 3rd Quartile and maximum (Max) of the 40 target species detected in the screw threads and inside the implant.
| Thermomechanical Loading | Thermocycling | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min | 1st Quartile | Median | Mean | 3rd Quartile | Max | Min | 1st Quartile | Median | Mean | 3rd Quartile | Max | |
| Candida tropicalis | 499,465 | 516,712 | 534,038 | 547,554 | 557,708 | 651,489 | 400,259 | 523,034 | 537,468 | 527,930 | 542,365 | 556,524 |
| Candida glabrata | 471,179 | 544,496 | 602,260 | 599,857 | 615,837 | 811,410 | 431,936 | 503,807 | 561,537 | 563,680 | 621,410 | 699,708 |
| Candida dubliniensis | 475,402 | 504,454 | 539,168 | 544,929 | 567,558 | 683,705 | 512,943 | 573,779 | 595,362 | 583,010 | 604,592 | 628,377 |
| Candida albicans | 503,754 | 514,799 | 534,297 | 552,731 | 584,323 | 649,825 | 480,652 | 512,195 | 523,533 | 551,795 | 563,133 | 679,463 |
| S. pneumoniae | 504,896 | 567,937 | 597,443 | 587,463 | 621,210 | 642,731 | 595,870 | 598,772 | 612,444 | 625,121 | 638,792 | 679,728 |
| S. gallolyticus | 507,870 | 546,434 | 579,044 | 587,641 | 615,521 | 697,752 | 589,889 | 638,313 | 655,077 | 644,569 | 661,366 | 678,234 |
| V. parvula | 539,243 | 590,354 | 597,497 | 606,167 | 635,940 | 658,358 | 567,120 | 585,344 | 593,449 | 588,217 | 596,322 | 598,849 |
| T. denticola | 483,362 | 578,609 | 656,805 | 660,446 | 763,000 | 828,167 | 561,773 | 586,472 | 647,304 | 653,646 | 714,479 | 758,203 |
| T. forsythia | 558,789 | 611,798 | 683,665 | 746,543 | 755,839 | 134,4715 | 659,659 | 704,875 | 722,092 | 723,360 | 740,576 | 789,596 |
| S. sobrinus | 661,538 | 699,976 | 726,574 | 750,250 | 806,908 | 895,655 | 691,838 | 786,421 | 844,923 | 820,197 | 878,699 | 899,104 |
| S. sanguinis | 530,248 | 594,529 | 638,470 | 651,256 | 652,013 | 819,170 | 504,070 | 633,840 | 691,386 | 651,957 | 709,502 | 720,986 |
| S. salivarius | 542,248 | 568,458 | 622,717 | 622,594 | 704,591 | 816,027 | 583,503 | 600,370 | 649,205 | 659,604 | 708,438 | 756,500 |
| S. pasteuri | 480,058 | 558,181 | 602,310 | 622,594 | 704,591 | 816,027 | 587,990 | 600,285 | 619,728 | 628,646 | 648,089 | 687,136 |
| S. parasanguinis | 536,446 | 5,707,749 | 629,047 | 630,151 | 667,066 | 757,201 | 550,919 | 605,175 | 636,416 | 640,084 | 671,325 | 736,586 |
| S. oralis | 474,413 | 568,393 | 652,822 | 634,822 | 704,656 | 762,701 | 530,628 | 543,113 | 591,199 | 604,967 | 653,053 | 706,844 |
| S. mutans | 487,655 | 546,186 | 620,196 | 603,589 | 658,292 | 703,153 | 457,503 | 467,810 | 509,795 | 538,970 | 580,955 | 678,787 |
| S. moorei | 567,414 | 624,352 | 644,285 | 655,223 | 660,830 | 787,577 | 566,710 | 577,428 | 638,138 | 642,531 | 703,241 | 727,137 |
| S. mitis | 479,870 | 570,950 | 608,519 | 613,243 | 623,248 | 858,306 | 574,245 | 607,696 | 630,267 | 632,519 | 655,090 | 699,222 |
| S. constellatus | 545,565 | 555,355 | 610,398 | 637,886 | 684,581 | 885,305 | 511,381 | 556,467 | 588,400 | 574,351 | 606,284 | 609,222 |
| S. aureus | 487,191 | 540,175 | 675,949 | 635,201 | 702,206 | 769,954 | 587,478 | 594,220 | 612,905 | 652,605 | 671,291 | 797,133 |
| P. putida | 516,300 | 619,464 | 650,428 | 647,966 | 698,450 | 786,884 | 558,804 | 586,594 | 633,324 | 624,951 | 671,681 | 674,352 |
| P. nigrescens | 501,925 | 574,848 | 610,700 | 608,865 | 637,100 | 707,094 | 587,177 | 632,085 | 655,643 | 640,732 | 664,291 | 664,466 |
| P. micra | 481,842 | 597,128 | 614,948 | 614,355 | 662,351 | 635,758 | 560,538 | 605,321 | 649,838 | 638,953 | 683,470 | 695,596 |
| P. melaninogenica | 581,484 | 642,451 | 656,114 | 658,453 | 679,316 | 748,853 | 525,768 | 573,214 | 651,422 | 659,362 | 737,570 | 808,836 |
| P. intermedia | 515,419 | 567,509 | 622,782 | 613,075 | 654,738 | 692,820 | 422,016 | 459,808 | 558,247 | 563,794 | 66,223 | 716,664 |
| P. gingivalis | 537,493 | 574,899 | 620,351 | 613,752 | 651,885 | 690,923 | 583,254 | 612,617 | 648,828 | 643,132 | 679,342 | 691,620 |
| P. endodontalis | 509,354 | 575,225 | 616,594 | 608,420 | 649,087 | 685,654 | 565,105 | 566,852 | 577,432 | 577,239 | 587,819 | 588,988 |
| P. anaerobius | 537,745 | 568,076 | 600,039 | 607,396 | 624,819 | 715,654 | 598,955 | 599,954 | 610,824 | 613,199 | 624,069 | 632,193 |
| P. aeruginosa | 481,647 | 582,853 | 640,709 | 624,453 | 681,893 | 751,444 | 565,730 | 591,237 | 599,990 | 606,724 | 615,477 | 661,188 |
| M. salivarium | 514,754 | 551,419 | 610,696 | 594,794 | 631,804 | 662,789 | 537,426 | 538,582 | 555,831 | 577,334 | 594,583 | 660,247 |
| K. pneumoniae | 478,531 | 542,816 | 599,017 | 589,771 | 634,740 | 681,970 | 511,323 | 573,528 | 616,948 | 618,669 | 662,088 | 729,458 |
| F. nucleatum | 390,358 | 509,930 | 539,019 | 552,677 | 624,528 | 662,581 | 629,171 | 632,180 | 655,032 | 657,829 | 680,680 | 692,081 |
| E. faecalis | 449,873 | 524,863 | 540,289 | 551,201 | 589,501 | 656,899 | 615,639 | 663,619 | 684,774 | 675,718 | 696,873 | 717,685 |
| E. corrodens | 392,714 | 578,014 | 610,590 | 580,026 | 627,132 | 684,806 | 567,392 | 586,274 | 666,448 | 662,937 | 743,111 | 751,458 |
| C. rectus | 423,191 | 526,447 | 663,110 | 615,102 | 676,448 | 752,398 | 612,597 | 633,473 | 640,603 | 647,565 | 654,695 | 696,458 |
| C. gengivalis | 474,206 | 591,170 | 650,446 | 641,002 | 674,923 | 787,770 | 608,877 | 628,253 | 668,521 | 667,024 | 707,292 | 722,178 |
| B. fragilis | 508,267 | 546,144 | 620,278 | 609,245 | 668,141 | 693,737 | 560,138 | 637,204 | 666,793 | 647,105 | 676,692 | 694,699 |
| Aaa | 476,387 | 569,010 | 612,387 | 615,976 | 632,509 | 521,162 | 521,162 | 571,564 | 633,465 | 622,224 | 685,226 | 698,605 |
| C. coli | 451,384 | 571,859 | 626,636 | 607,283 | 672,237 | 707,912 | 602,417 | 614,768 | 632,057 | 635,732 | 653,021 | 676,396 |
| L. casei | 565,001 | 581,528 | 646,157 | 638,162 | 683,994 | 724,165 | 479,441 | 588,346 | 646,438 | 624,235 | 682,327 | 724,623 |
Table 2.
CMX TB Group. Minimum (Min), 1st Quartile, median, mean, 3rd Quartile and maximum (Max) of the 40 target species detected in the screw threads and inside the implant.
| Thermomechanical Loading | Thermocycling | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min | 1st Quartile | Median | Mean | 3rd Quartile | Max | Min | 1st Quartile | Median | Mean | 3rd Quartile | Max | |
| Candida tropicalis | 496,592 | 515,731 | 526,960 | 525,193 | 53,851º | 548,276 | 489,379 | 506,751 | 512,887 | 516,540 | 522,676 | 551,008 |
| Candida glabrata | 518,446 | 527,305 | 534,480 | 538,439 | 542,217 | 582,655 | 501,586 | 508,209 | 515,254 | 527,091 | 534,136 | 576,270 |
| Candida dubliniensis | 477,982 | 517,257 | 529,519 | 525,692 | 545,424 | 565,209 | 470,631 | 490,024 | 512,224 | 506,412 | 528,612 | 530,569 |
| Candida albicans | 473,474 | 494,370 | 523,611 | 516,886 | 529,699 | 572,128 | 492,392 | 499,021 | 510,583 | 517,413 | 528,993 | 556,093 |
| S. pneumoniae | 482,061 | 508,639 | 522,327 | 518,340 | 537,917 | 544,420 | 487,890 | 500,679 | 533,283 | 531,922 | 564,526 | 573,230 |
| S. gallolyticus | 399,066 | 507,491 | 528,371 | 520,918 | 554,330 | 565,274 | 489,946 | 498,905 | 521,177 | 525,008 | 547,280 | 567,733 |
| V. parvula | 512,181 | 526,347 | 536,916 | 531,959 | 540,894 | 542,268 | 386,188 | 452,881 | 487,084 | 477,951 | 512,154 | 551,449 |
| T. denticola | 543,743 | 558,818 | 563,354 | 568,994 | 572,934 | 613,872 | 542,853 | 560,909 | 569,516 | 565,391 | 573,999 | 579,678 |
| T. forsythia | 532,057 | 543,820 | 560,373 | 561,235 | 580,801 | 585,616 | 507,034 | 530,541 | 550,539 | 552,844 | 572,841 | 603,264 |
| S. sobrinus | 519,783 | 537,888 | 549,026 | 551,081 | 557,541 | 610,955 | 569,753 | 573,052 | 577,485 | 580,099 | 584,533 | 595,673 |
| S. sanguinis | 473,787 | 514,390 | 533,482 | 531,100 | 554,510 | 580,375 | 329,607 | 416,505 | 477,452 | 468,591 | 529,538 | 589,852 |
| S. salivarius | 475,515 | 525,172 | 534,335 | 530,916 | 544,926 | 559,998 | 515,742 | 518,324 | 531,689 | 533,916 | 547,281 | 556,545 |
| S. pasteuri | 459,655 | 494,762 | 521,916 | 516,966 | 540,400 | 560,938 | 481,242 | 485,587 | 491,090 | 489,862 | 495,364 | 496,024 |
| S. parasanguinis | 551,532 | 555,873 | 560,776 | 562,206 | 564,969 | 583,635 | 522,089 | 535,622 | 548,198 | 544,030 | 556,606 | 557,635 |
| S. oralis | 547,741 | 547,741 | 557,186 | 566,023 | 570,717 | 583,620 | 561,110 | 569,979 | 578,776 | 580,457 | 588,353 | 604,966 |
| S. mutans | 521,082 | 545,371 | 571,449 | 563,677 | 582,176 | 597,851 | 548,784 | 551,513 | 561,157 | 565,602 | 575,245 | 591,308 |
| S. moorei | 506,457 | 554,874 | 565,164 | 560,009 | 573,283 | 599,603 | 544,476 | 549,398 | 560,877 | 564,643 | 576,123 | 592,343 |
| S. mitis | 526,259 | 533,981 | 548,766 | 555,798 | 574,910 | 595,837 | 100,000 | 426,065 | 535,121 | 428,344 | 537,400 | 543,136 |
| S. constellatus | 527,892 | 560,203 | 569,269 | 566,945 | 574,598 | 592,919 | 547,831 | 562,346 | 567,613 | 563,918 | 569,184 | 572,616 |
| S. aureus | 548,861 | 556,266 | 563,362 | 564,513 | 574,890 | 578,580 | 526,178 | 569,788 | 584,634 | 571,746 | 586,592 | 591,541 |
| P. putida | 500,590 | 541,112 | 549,882 | 547,336 | 560,674 | 585,879 | 503,974 | 527,182 | 537,623 | 537,638 | 548,080 | 571,334 |
| P. nigrescens | 532,600 | 545,662 | 557,655 | 564,862 | 588,724 | 594,985 | 555,658 | 556,225 | 561,188 | 566,100 | 566,562 | 568,365 |
| P. micra | 402,709 | 550,502 | 561,360 | 543,071 | 568,187 | 622,768 | 307,382 | 493,785 | 557,719 | 501,157 | 565,090 | 581,808 |
| P. melaninogenica | 495,919 | 555,366 | 562,177 | 563,158 | 575,509 | 613,968 | 534,323 | 539,015 | 545,649 | 549,336 | 555,970 | 571,724 |
| P. intermedia | 544,669 | 557,460 | 569,073 | 571,801 | 580,986 | 613,662 | 564,974 | 569,463 | 571,896 | 572,860 | 575,293 | 582,673 |
| P. gingivalis | 489,725 | 504,471 | 535,813 | 527,119 | 546,902 | 554,464 | 507,347 | 518,645 | 536,165 | 538,127 | 555,646 | 572,833 |
| P. endodontalis | 441,086 | 486,754 | 502,020 | 496,015 | 507,733 | 529,601 | 407,109 | 447,178 | 468,629 | 476,382 | 497,832 | 561,159 |
| P. anaerobius | 479,681 | 521,592 | 532,805 | 539,360 | 537,340 | 573,804 | 529,878 | 549,986 | 559,938 | 553,762 | 563,714 | 565,295 |
| P. aeruginosa | 503,678 | 522,435 | 562,092 | 553,281 | 578,722 | 601,961 | 556,387 | 557,108 | 557,552 | 563,401 | 563,845 | 582,113 |
| M. salivarium | 521,811 | 535,519 | 565,304 | 558,432 | 574,149 | 591,321 | 541,602 | 559,289 | 572,156 | 567,911 | 580,778 | 585,729 |
| K. pneumoniae | 542,472 | 568,314 | 577,548 | 581,477 | 595,568 | 617,113 | 559,294 | 566,629 | 570,637 | 578,279 | 582,288 | 612,548 |
| F. nucleatum | 560,132 | 564,347 | 570,906 | 575,682 | 581,220 | 619,010 | 543,114 | 547,686 | 557,899 | 559,287 | 569,501 | 578,237 |
| E.faecalis | 545,878 | 564,308 | 576,484 | 573,064 | 581,512 | 603,714 | 557,411 | 560,442 | 562,146 | 569,102 | 570,806 | 594,704 |
| E. corrodens | 552,590 | 568,619 | 579,075 | 578,317 | 587,834 | 608,508 | 567,342 | 567,979 | 578,663 | 578,561 | 589,245 | 589,577 |
| C. rectus | 532,558 | 561,741 | 575,519 | 577,864 | 593,144 | 615,889 | 544,577 | 565,388 | 572,980 | 569,702 | 577,294 | 588,274 |
| C. gengivalis | 537,625 | 545,711 | 556,653 | 559,280 | 571,189 | 583,272 | 521,654 | 542,848 | 556,176 | 553,238 | 566,565 | 578,945 |
| B. fragilis | 514,676 | 553,184 | 567,165 | 562,438 | 573,858 | 600,250 | 558,006 | 567,206 | 572,172 | 575,094 | 580,060 | 597,996 |
| Aaa | 520,565 | 531,841 | 549,008 | 548,850 | 565,558 | 580,608 | 534,334 | 535,150 | 540,761 | 547,236 | 552,847 | 573,088 |
| C. coli | 528,294 | 553,992 | 561,322 | 558,542 | 572,180 | 575,593 | 553,865 | 565,098 | 575,156 | 571,711 | 581,769 | 582,669 |
| L. casei | 531,608 | 573,140 | 583,355 | 580,824 | 595,654 | 604,658 | 551,711 | 557,724 | 57,660 | 576,619 | 596,555 | 599,446 |
Table 3.
CMX PU. Minimum (Min), 1st Quartile, median, mean, 3rd Quartile and maximum (Max) of the 40 target species detected in the screw threads and inside the implant.
| Thermomechanical Loading | Thermocycling | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min | 1st Quartile | Median | Mean | 3rd Quartile | Max | Min | 1st Quartile | Median | Mean | 3rd Quartile | Max | |
| Candida tropicalis | 521,879 | 526,899 | 532,735 | 535,348 | 540,132 | 568,524 | 532,127 | 544,172 | 550,925 | 546,923 | 553,676 | 553,717 |
| Candida glabrata | 509,069 | 519,093 | 521,232 | 524,599 | 531,062 | 547,197 | 523,553 | 523,558 | 527,277 | 528,696 | 532,414 | 536,675 |
| Candida dubliniensis | 502,067 | 511,557 | 515,934 | 516,141 | 522,602 | 525,501 | 523,273 | 524,197 | 524,826 | 525,243 | 525,872 | 528,050 |
| Candida albicans | 505,054 | 517,696 | 520,209 | 519,744 | 524,708 | 529,092 | 518,324 | 519,122 | 521,380 | 521,729 | 523,987 | 525,834 |
| S. pneumoniae | 508,163 | 509,542 | 517,133 | 518,351 | 524,156 | 535,767 | 505,438 | 512,514 | 516,580 | 517,004 | 521,070 | 529,418 |
| S. gallolyticus | 508,370 | 511,941 | 512,435 | 514,700 | 515,767 | 524,863 | 512,751 | 517,757 | 520,574 | 519,627 | 522,444 | 524,608 |
| V. parvula | 498,994 | 505,425 | 510,424 | 509,845 | 514,491 | 519,270 | 509,489 | 511,837 | 512,774 | 515,817 | 516,755 | 528,232 |
| T. denticola | 492,806 | 510,774 | 518,132 | 517,028 | 525,095 | 540,757 | 509,681 | 510,765 | 526,990 | 524,016 | 530,242 | 532,403 |
| T. forsythia | 505,347 | 519,426 | 522,475 | 524,148 | 529,123 | 547,926 | 510,002 | 515,201 | 521,239 | 525,246 | 531,285 | 548,505 |
| S. sobrinus | 595,786 | 510,908 | 515,635 | 520,340 | 535,644 | 541,346 | 516,657 | 519,578 | 522,600 | 526,706 | 529,727 | 544,967 |
| S. sanguinis | 499,460 | 506,609 | 509,465 | 511,159 | 514,431 | 525,458 | 511,951 | 514,355 | 515,938 | 525,292 | 526,876 | 557,342 |
| S. salivarius | 499,330 | 507,500 | 512,509 | 511,075 | 515,363 | 519,720 | 506,010 | 507,446 | 500,883 | 508,136 | 509,200 | 509,516 |
| S. pasteuri | 502,444 | 507,500 | 512,509 | 511,075 | 515,363 | 519,720 | 506,276 | 513,591 | 516,103 | 519,186 | 521,698 | 538,260 |
| S. parasanguinis | 506,311 | 506,901 | 507,235 | 510,155 | 510,431 | 523,784 | 509,446 | 512,415 | 516,258 | 521,968 | 525,811 | 545,913 |
| S. oralis | 502,672 | 503,168 | 507,264 | 513,903 | 516,239 | 556,053 | 509,773 | 512,126 | 519,338 | 519,623 | 526,834 | 530,043 |
| S. mutans | 502,274 | 506,689 | 509,707 | 509,551 | 510,936 | 518,002 | 510,262 | 511,036 | 513,776 | 523,327 | 526,067 | 555,495 |
| S. moorei | 502,459 | 506,118 | 508,818 | 509,641 | 512,814 | 521,343 | 495,690 | 504,196 | 512,701 | 514,469 | 523,858 | 535,015 |
| S. mitis | 496,140 | 508,397 | 512,622 | 510,891 | 516,285 | 521,740 | 509,202 | 512,173 | 515,134 | 515,491 | 518,452 | 522,494 |
| S. constellatus | 499,229 | 504,608 | 513,249 | 510,944 | 515,374 | 520,901 | 502,799 | 507,690 | 510,825 | 517,339 | 520,474 | 544,905 |
| S. aureus | 502,340 | 506,297 | 513,276 | 512,750 | 516,756 | 524,366 | 503,241 | 510,870 | 515,086 | 518,742 | 522,958 | 541,558 |
| P. putida | 502,727 | 509,252 | 512,796 | 516,473 | 520,938 | 540,759 | 513,027 | 515,250 | 519,531 | 525,870 | 530,151 | 551,392 |
| P. nigrescens | 499,713 | 505,889 | 514,311 | 513,822 | 521,081 | 526,972 | 508,985 | 509,206 | 512,414 | 515,173 | 518,382 | 526,878 |
| P. micra | 499,866 | 509,486 | 514,798 | 513,336 | 518,662 | 519,904 | 495,886 | 505,933 | 514,731 | 514,545 | 523,343 | 532,833 |
| P. melaninogenica | 516,074 | 519,036 | 521,372 | 520,954 | 522,910 | 526,552 | 515,292 | 524,258 | 528,527 | 527,933 | 532,202 | 539,287 |
| P. intermedia | 492,805 | 510,600 | 512,890 | 512,164 | 518,208 | 520,554 | 502,698 | 512,800 | 516,485 | 522,552 | 525,937 | 553,340 |
| P. gingivalis | 496,318 | 510,253 | 513,687 | 514,056 | 519,108 | 525,049 | 506,885 | 508,754 | 511,323 | 521,321 | 523,890 | 555,753 |
| P. endodontalis | 500,108 | 507,253 | 510,450 | 510,585 | 513,594 | 522,991 | 510,414 | 512,129 | 514,838 | 518,472 | 521,181 | 533,797 |
| P. anareobius | 499,789 | 508,881 | 513,569 | 512,332 | 518,974 | 521,314 | 510,178 | 512,684 | 513,693 | 521,200 | 522,209 | 547,236 |
| P. aeruginosa | 502,333 | 504,190 | 506,289 | 508,465 | 512,226 | 517,909 | 499,685 | 504,556 | 515,162 | 514,296 | 524,903 | 527,176 |
| M. salivarium | 502,480 | 503,394 | 508,459 | 508,819 | 513,308 | 517,638 | 505,885 | 509,168 | 512,009 | 513,433 | 516,273 | 523,829 |
| K. pneumoniae | 503,118 | 507,107 | 509,697 | 510,426 | 514,686 | 517,074 | 512,896 | 515,614 | 516,578 | 517,487 | 518,450 | 523,895 |
| F. nucleatum | 496,246 | 509,891 | 513,442 | 512,987 | 517,171 | 529,364 | 506,459 | 506,717 | 511,210 | 512,268 | 516,762 | 520,195 |
| E.faecalis | 502,648 | 509,671 | 516,600 | 513,598 | 517,098 | 523,633 | 503,046 | 508,314 | 511,641 | 510,392 | 513,718 | 515,240 |
| E. corrodens | 499,102 | 507,130 | 511,786 | 510,290 | 514,304 | 517,051 | 502,761 | 507,881 | 511,606 | 513,627 | 517,352 | 528,535 |
| C. rectus | 503,240 | 504,524 | 508,209 | 509,771 | 513,324 | 521,964 | 503,162 | 506,076 | 508,482 | 511,234 | 513,640 | 524,809 |
| C. gengivalis | 496,277 | 509,774 | 508,597 | 511,429 | 518,305 | 525,247 | 500,159 | 502,528 | 510,465 | 512,300 | 520,237 | 528,113 |
| B. fragilis | 500,472 | 506,942 | 508,975 | 508,685 | 511,356 | 515,116 | 507,329 | 509,377 | 514,210 | 515,172 | 520,005 | 524,938 |
| Aaa | 500,329 | 504,265 | 510,794 | 510,960 | 513,583 | 530,871 | 503,189 | 506,050 | 510,544 | 512,296 | 516,790 | 524,905 |
| C. coli | 499,754 | 506,396 | 513,786 | 511,665 | 516,312 | 521,797 | 510,199 | 510,906 | 513,822 | 515,704 | 518,620 | 528,620 |
| L. casei | 496,075 | 507,173 | 509,809 | 510,831 | 515,268 | 523,264 | 502,363 | 508,030 | 511,699 | 513,208 | 516,876 | 527,070 |
Table 4.
CMX U. Minimum (Min), 1st Quartile, median, mean, 3rd Quartile and maximum (Max) of the 40 target species detected in the screw threads and inside the implant.
| Thermomechanical Loading | Thermocycling | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min | 1st Quartile | Median | Mean | 3rd Quartile | Max | Min | 1st Quartile | Median | Mean | 3rd Quartile | Max | |
| Candida tropicalis | 217,282 | 341,234 | 385,222 | 378,850 | 439,730 | 465,562 | 219,254 | 254,462 | 352,510 | 348,994 | 447,041 | 471,700 |
| Candida glabrata | 225,313 | 246,065 | 262,678 | 268,364 | 290,845 | 327,597 | 184,674 | 227,776 | 250,716 | 242,263 | 265,203 | 282,946 |
| Candida dubliniensis | 285,913 | 327,206 | 331,453 | 348,002 | 345,835 | 478,154 | 327,498 | 385,702 | 411,369 | 434,964 | 460,630 | 589,619 |
| Candida albicans | 110,375 | 224,104 | 288,444 | 272,661 | 316,789 | 380,726 | 301,789 | 358,219 | 384,111 | 378,853 | 404,745 | 445,398 |
| S. pneumoniae | 109,486 | 143,622 | 259,004 | 233,199 | 287,371 | 383,126 | 100,000 | 212,150 | 365,828 | 359,290 | 512,968 | 605,506 |
| S. gallolyticus | 217,038 | 233,505 | 290,082 | 313,556 | 333,302 | 586,911 | 141,288 | 193,417 | 258,145 | 260,751 | 325,479 | 385,428 |
| V. parvula | 143,606 | 278,304 | 338,548 | 309,169 | 369,346 | 383,873 | 124,813 | 209,168 | 261,543 | 248,175 | 300,550 | 344,799 |
| T. denticola | 109,853 | 224,276 | 271,285 | 260,355 | 327,284 | 362,279 | 192,606 | 202,036 | 221,284 | 223,541 | 242,789 | 258,989 |
| T. forsythia | 116,516 | 228,361 | 263,827 | 262,679 | 296,038 | 402,735 | 193,887 | 202,409 | 235,870 | 239,400 | 272,860 | 291,973 |
| S. sobrinus | 110,479 | 228,074 | 277,931 | 275,089 | 336,756 | 397,246 | 262,909 | 288,476 | 299,820 | 301,256 | 312,601 | 342,476 |
| S. sanguinis | 186,712 | 260,753 | 319,200 | 311,340 | 372,454 | 413,536 | 158,952 | 265,727 | 369,944 | 424,695 | 439,865 | 439,895 |
| S. salivarius | 183,190 | 261,160 | 289,836 | 281,151 | 298,268 | 368,143 | 220,188 | 250,046 | 279,214 | 274,872 | 304,040 | 320,874 |
| S. pasteuri | 252,142 | 287,569 | 293,603 | 301,347 | 300,692 | 396,385 | 144,374 | 170,950 | 199,114 | 230,808 | 258,973 | 380,631 |
| S. parasanguinis | 112,858 | 210,692 | 301,458 | 281,694 | 341,119 | 399,906 | 243,447 | 275,141 | 303,708 | 295,559 | 324,126 | 331,372 |
| S. oralis | 280,561 | 351,924 | 391,391 | 390,849 | 409,087 | 528,500 | 297,603 | 305,743 | 328,975 | 360,780 | 384,012 | 487,569 |
| S. mutans | 227,850 | 290,089 | 313,220 | 311,207 | 376,317 | 407,205 | 188,905 | 277,723 | 322,566 | 301,035 | 345,877 | 370,103 |
| S. moorei | 109,937 | 189,142 | 243,573 | 228,104 | 268,104 | 306,521 | 223,630 | 258,245 | 289,429 | 283,920 | 315,104 | 333,192 |
| S. mitis | 150,640 | 185,939 | 215,018 | 243,150 | 313,548 | 376,590 | 154,386 | 206,231 | 262,503 | 252,076 | 308,348 | 328,913 |
| S. constellatus | 145,954 | 188,560 | 226,072 | 250,585 | 328,127 | 365,342 | 193,170 | 216,380 | 225,202 | 227,024 | 235,847 | 264,521 |
| S. aureus | 187,880 | 262,263 | 280,057 | 291,265 | 302,379 | 408,494 | 226,065 | 308,542 | 370,618 | 363,374 | 425,451 | 486,196 |
| P. putida | 143,161 | 253,023 | 322,618 | 309,755 | 368,265 | 455,233 | 297,895 | 306,702 | 363,186 | 366,827 | 423,311 | 443,041 |
| P. nigrescens | 177,730 | 207,023 | 266,496 | 277,380 | 353,889 | 397,399 | 321,529 | 362,934 | 386,017 | 442,321 | 465,404 | 675,723 |
| P. micra | 189,217 | 190,844 | 207,689 | 224,872 | 243,638 | 334,089 | 185,569 | 265,603 | 299,005 | 277,407 | 310,809 | 326,048 |
| P. melaninogenica | 448,694 | 514,857 | 561,123 | 591,295 | 652,611 | 880,154 | 566,416 | 582,489 | 605,760 | 632,014 | 655,285 | 750,119 |
| P. intermedia | 156,879 | 225,608 | 287,838 | 340,493 | 383,084 | 812,934 | 207,091 | 244,818 | 320,549 | 314,632 | 390,363 | 410,339 |
| P. gingivalis | 117,124 | 264,842 | 272,863 | 298,062 | 369,196 | 496,776 | 263,035 | 268,326 | 281,348 | 302,660 | 315,681 | 384,908 |
| P. endodontalis | 110,453 | 233,541 | 284,995 | 268,700 | 331,040 | 345,795 | 147,782 | 176,117 | 204,091 | 242,392 | 270,366 | 413,606 |
| P. anareobius | 151,960 | 225,042 | 265,177 | 263,778 | 293,364 | 405,937 | 146,384 | 230,859 | 280,924 | 279,409 | 329,475 | 409,404 |
| P. aeruginosa | 227,437 | 239,907 | 290,105 | 308,114 | 377,696 | 413,180 | 225,416 | 225,727 | 246,442 | 273,559 | 294,274 | 375,936 |
| M. salivarium | 187,273 | 247,973 | 341,173 | 333,144 | 415,076 | 469,885 | 309,088 | 333,366 | 364,032 | 365,248 | 395,914 | 423,843 |
| K. pneumoniae | 195,112 | 282,004 | 404,784 | 402,078 | 450,658 | 783,747 | 232,059 | 260,969 | 348,822 | 358,690 | 446,544 | 505,059 |
| F. nucleatum | 150,975 | 272,399 | 305,683 | 303,963 | 341,448 | 454,396 | 235,202 | 263,872 | 306,925 | 317,749 | 368,002 | 421,946 |
| E.faecalis | 186,020 | 274,720 | 341,316 | 325,884 | 396,734 | 420,810 | 309,552 | 331,993 | 360,781 | 353,452 | 382,240 | 382,694 |
| E. corrodens | 231,374 | 281,719 | 336,372 | 366,000 | 409,572 | 574,781 | 230,021 | 282,075 | 343,949 | 333,581 | 395,455 | 416,406 |
| C. rectus | 328,256 | 351,452 | 426,916 | 477,979 | 581,944 | 767,913 | 115,174 | 209,127 | 361,902 | 343,182 | 495,957 | 533,751 |
| C. gengivalis | 233,038 | 310,492 | 342,198 | 425,489 | 541,128 | 748,697 | 236,263 | 260,985 | 287,295 | 320,936 | 347,246 | 472,891 |
| B. fragilis | 277,918 | 292,194 | 355,0285 | 408,566 | 432,525 | 792,708 | 348,069 | 370,687 | 402,494 | 470,874 | 502,680 | 730,439 |
| Aaa | 110,516 | 268,966 | 287,284 | 296,592 | 338,523 | 427,716 | 148,299 | 178,126 | 229,103 | 244,087 | 295,064 | 369,845 |
| C. coli | 147,005 | 230,240 | 268,391 | 279,505 | 346,504 | 389,418 | 268,353 | 293,782 | 306,211 | 329,242 | 335,372 | 410,996 |
| L. casei | 147,514 | 282,125 | 345,747 | 319,614 | 377,600 | 387,103 | 147,246 | 233,982 | 322,463 | 322,463 | 346,930 | 595,550 |
The Generalized Estimation Equations (GEE) method showed that there were significant differences in the counts of the different target species of the study between the groups after the cyclic load test (p < 0.05). As shown in Table 1, the microorganisms with the highest counts found in the CMC TB group subjected to thermal cycling and cyclic loading were S. sobrinus (750,250), T. forsythia (746,543), T. denticola (660,446), P. melaninogenica (658,453), S. moorei (655,223) and S. sanguinis (651,256). Among the groups subjected to thermal cycling, the highest counts were for S. sobrinus (820,197), T. forsythia (723,360), E. faecalis (675,718), C. gingalis (667,024), E. corrodens (662,937) and melaninogeneca (659,362).
As displayed in Table 2, the microorganisms with the highest counts found in the CMX TB group subjected to thermal cycling and cyclic loading were K. pneumoniae (581,477), L. casei (580,824), E. corrodens (578,317), C. rectus (577,864), F. nucleatum (575,682) and E. faecalis (573,064). Among the groups subjected to thermal cycling, the highest counts were for S. oralis (580,457), S. sobrinus (580,099), E. corrodens (578,561), K. pneumoniae (578,279), L. casei (576,619) and B. fragilis (575,094).
As presented in Table 3, the microorganisms with the highest counts found in the CMX PU group subjected to thermal cycling and cyclic loading were C. tropicalis (535,348), C. Glabrata (524,599), T. forsythia (524,148), P. melanogenica (520,954), S. sobrinus (520,340) and C. albicans (519,744). Among the groups subjected to thermal cycling, the highest counts were for C. tropicalis (546,923), C. Glabrata (528,696), S. sobrinus (526,706), P. putida (525,870), T. forsythia (525,246) and C. dubliniensis (525,243).
As shown in Table 4, the microorganisms with the highest counts found in the CMX U group subjected to thermal cycling and cyclic loading were P. melaninogenica (591,295), C. rectus (477,979), C. gingivalis (425,489), B. fragilis (408,566), K. pneumoniae (402,078) and S. oralis (390,849). Among the groups subjected to thermal cycling, the microorganisms with the highest counts were P. melaninogenica (632,014), B. fragilis (470,874), P. nigrescens (442,321), Candida dubliniensis (434,964), Candida albicans (378,853) and P. putida (366,827)
Figure 10 and Figure 11 illustrate the distribution of bacterial species according to the Socransky red and orange complexes, respectively, in the investigated groups subjected or not to cyclic loading [13].
Figure 10.
Bacterial count (total genomes) after the thermomechanical loading assay.
Figure 11.
Bacterial count (total genomes) after the thermal cycling assay.
The results indicate that the amount of red complex bacterial genomes detected in the groups after the cyclic loading test was much higher than the amount observed in the groups subjected only to the thermocycling test. However, the distribution pattern of genomes in the groups is similar, with the highest values being observed for the CMC TB group and the lowest for the CMX U groups.
For microorganisms belonging to the orange complex, the number of genomes observed in the two experimental situations, with or without charge, was similar. However, the distribution profile between the groups was different in both situations; for the groups subjected to the cyclic load test, the pattern was similar to that of the red complex, with the highest counts observed for the CMC TB group, followed by CMX TB, CMX PU and CMX U. For the groups subjected only to the cyclic load test, thermocycling, the pattern was very different, with the CMX TB group presenting a much higher count of total genomes when compared to the other groups that were similar.
4. Discussion
The present study evaluated the microbial leakage through the implant–abutment interface in conical connection implants with different prosthetic abutment designs after thermal cycling associated or not with cyclic loading. To achieve this, the assemblies were subjected to a cyclic load test simulating human chewing and the Checkerboard DNA–DNA hybridization technique was used to identify and quantify the presence of up to 40 microbial species that commonly colonize the oral cavity, including bacteria and fungi that are associated with the inflammatory processes that may cause periodontal and peri-implant diseases.
Dental implant systems are conventionally used in two parts: the implant and the prosthetic component (abutment) that adapts to the implant and receives prosthetic rehabilitation. Studies point to the conical connection as having the best mechanical/biological performance when compared to others existing connection designs. The junction between these two pieces, even if very well adapted, results in spaces that can favor the colonization and multiplication of microorganisms present in the oral cavity [14,15,16]. The hypothesis tested in this study was confirmed since the results demonstrate that all types of abutments and implants investigated have not avoided the passage of microorganisms through the interface, even when not subjected to the cyclic load test. Despite advances with dental implants and their connections, the occurrence of microbial infiltration through this interface is expected, since the size of the spaces reported in the literature can vary between 0.1 and 10 µm and the average diameter of the smallest bacteria present in the oral cavity varies between 0.2 and 1.5 μm in width and 2 and 10 μm in length [15,16,17,18]. Additionally, the micro-movements that occur between the components favor the opening of existing spaces [19,20]. Therefore, the null hypothesis established for this study was not confirmed, since there were significant differences in the microbial profile for the different groups investigated.
Although Morse cone connections are considered the most stable and have the least infiltration potential between implant components, the presence of microorganisms colonizing the interior of implants has been frequently reported in the literature, even in experimental tests with the absence of load application [3,14,21,22]. The implant–abutment interface in this connection design has friction adjustment and when this assembly is subjected to load, the spaces present can also be enlarged as a result of micro-movements, resulting in the infiltration of microorganisms and their fluids into the implant and vice versa [2,23,24,25]. Furthermore, the imprecise machining of the internal parts of the implant and the prosthetic abutment does not allow a sufficient contact area between the surfaces to provide an effective seal and may contribute to the occurrence of micro-leakage [26,27].
Teixeira et al. [28] found a percentage of S. aureus infiltration in 77% of implants with morse cone connections and 100% in internal hexagon-type connections. The results described in the literature showed that the Morse cone-type connection, when compared to the internal hexagon, presented a greater sealing capacity; however, it was not able to prevent the passage of bacteria and fluids through the connection interface [28,29,30].
Studies in the literature have already demonstrated the presence of more than 700 different species of microorganisms colonizing the tissues of the oral cavity, including viruses, protozoa, fungi and bacteria that cohabit in homeostasis [31]. When the biological balance is disrupted, inflammatory processes can occur with the consequent development of oral diseases [32]. Socransky et al. classified the various microorganisms into distinct microbial complexes, namely purple, green, orange, yellow and red, associated according to the bacterial virulence for periodontal disease. The purple, green and yellow complexes showed strong associations with each other and were less associated with the red and orange complexes, which present the bacterial species most closely related to disease conditions [13,33,34].
All target species proposed to be investigated in this study were found inside the implants of the different groups studied, both in situations involving the application of the cyclic load and in groups subjected only to thermocycling. The species T. denticola, T. forshytia and P. gingivalis, which are part of the red complex, and the species S. constellatus, P. nigrescens, P. intermedia and C. rectus, from the orange complex, are directly related to periodontal and peri-implant disease and were detected in moderate quantities inside the implants. Microorganisms from the red complex are almost always found in the presence of the orange complex, as they precede colonization by species from the red complex [13].
Comparing the count of red and orange complex microorganisms inside the implants, the thermal group with the cyclic load presented the highest values of bacterial genomes. However, the distribution pattern of genomes in the groups is similar, with the highest values being observed for the CMC TB group and the lowest for the CMX U groups. The cyclic loading condition may have caused micro-movements of the components during mechanical loading which facilitated the microbial passage at the implant–prosthetic abutment interface into the implant, as demonstrated in other studies [16,26].
Despite the lower microbial count, the condition of the group without the load simulation did not prevent infiltration at the implant–prosthetic component interface and, consequently, colonization inside the implant. Among the abutments of the static group, the CMC TB group also presented the highest count of genomes of bacteria from the red group (T. denticola, T. forshytia and P. gingivalis), while for microorganisms belonging to the orange complex (S. constellatus, P. nigrescens, P. intermedia and C. rectus), the CMX TB group presented a higher total genome count than the other groups, which in turn had a similar count. Other studies also detected the presence of microorganisms, even in conditions without a load simulation [14,22].
In general, the prevalence of microbial species between the different abutments was different; the CMC TB group had the most prevalent species: S. sobrinus, T. forsythia, T. denticola, E. faecalis and C. gingivalis. In the CMX TB group, the most common species found were K. pneumoniae, L. casei, E. corrodens, S. oralis and S. sobrinus. In the CMX PU group, the most prevalent were C. tropicalis, C. Glabrata, T. forsythia, P. melanogenica and S. sobrinus. In the CMX U group, the species P. melaninogenica, C. rectus, C. gingivalis, B. fragilis and P. nigrescens prevailed. The amount of microorganisms between the groups also showed significant differences in the contamination values (p < 0.005), in addition to the aforementioned factors that lead to screw loosening which may have contributed in different ways between the groups to the microbial passage into the interior of the implants. Other factors such as the microorganism size, microgap size, surface topography, atomic interactions and surface free energy of the pillars can also justify the different quantities and species detected between the groups [15,16,17,18,35,36,37,38,39,40]. Works using similar methodologies to the present study have also demonstrated the passage of microorganisms from the external environment to the interior of implants [9,14,21,41,42].
Overall, periodontopathogenic species belonging to the genera Porphyromonas, Tannerella and Treponema were found at moderate levels in the thermal cycling and cyclic loading groups. The presence of these pathogenic species is threatening when a microbial imbalance occurs or the host presents susceptibility, as proposed by the “ecological plaque theory”, which presents biofilm-mediated diseases as a result of an imbalance in the host’s microbiota [43,44,45].
In addition to bacteria, the presence of some fungi was also found inside the implants. The literature shows that the species C. topicalis, C. albicans, C. glabata and C. dubliniensis, identified in the groups studied, play a fundamental role, as opportunists in the constitution of biofilm in association with bacteria, playing a relevant role in the pathogenesis of peri-implantitis [46,47]. The most prevalent fungal species in the group subjected only to thermal cycling was C. dubliniensis and in the thermal group with a cyclic load, C. glabata. The species of fungi investigated in this study belong to the same genus, Candida, and, therefore, have many similarities in the constitution of their genetic material, mainly regarding their size and diameter. The differences in prevalence found for these species in the different groups in our study, as well as the differences observed for bacteria belonging to the same genus, need to be better investigated in future studies. One possibility could be the differences in the electrostatic potential and atomic interactions that occur between different microorganisms and substrates.
It is important to highlight that detecting microorganisms inside implants is not the confirmation of peri-implant disease, but rather a situation that can substantially increase the risk, since several other factors are necessary for the onset of the disease, with its etiology being multifactorial [48,49,50].
The method used to investigate the presence of micro-leakage in this study was Checkerboard DNA–DNA Hybridization, which has been widely used to detect and quantify species that harbor different sites in the oral cavity [51,52]. As it is a method based on identifying the genetic material of target species, it allows detecting viable or non-viable species within a biofilm. The detection of non-viable species is a very important factor, since just the presence of the bacterial cellular structure and its degradation products already pose a risk to peri-implant structures, as they serve as a substrate for other bacteria [41,53]. This method’s main characteristic is the speed and simultaneous identification of several species of microorganisms. Despite the excellent results provided, this detection method also has limitations such as reduced sensitivity, since the presence of microorganisms in concentrations lower than 104 cells does not result in detectable or reproducible signals and only detects species that had the probes prepared from the DNA of the species defined as targets in the study [8]. Therefore, non-cultivable species or those that have not yet had their genome determined are not detected by this method. Furthermore, there is the possibility of the nonspecific binding of the probe labeling reagent with other macromolecules when the proportion of DNA is low [8]. Despite this, several studies have used this methodology to prove the micro-infiltration of microorganisms through the implant–prosthetic abutment interface [8,14,26,54].
The results of this study and many others, including literature reviews, demonstrate that despite presenting fewer occurrences of bacterial infiltration, conical connections are not capable of completely sealing the implant–abutment interface, making it vulnerable to the consequences of allowing a bacterial presence near this region. This finding leads us to question whether we should seek a different clinical approach, which seeks to learn how to deal with bacterial infiltration. In other words, we should seek a maintenance protocol that aims to control bacteria in the interface region. Sinjari et al., in 2018, published a study that provides important information about the implant–abutment interface. In the double-blind, controlled, randomized and prospective study Sinjari et al., with the objective of evaluating marginal bone loss, selected patients with prosthetic rehabilitation needs of a single element and separated the treatment times in five phases: t0—Implant placement surgery, t1—Reopening of the surgical room after 8 weeks, t2—Temporary placement after 12 weeks, t3—placement of final restoration after 14 weeks, t4—follow-up after 1 year. During the surgical procedure phases, however, one group (B) received cleaning of the interface region, carried out with gel 0.20% chlorhexidine, and the other group (A) received cleansing with placebo gel, without the inclusion of an antimicrobial agent. Bone loss analyses were performed during each phase of the study and the results demonstrate statistical differences in all surgical phases with greater bone loss for the group that received cleansing with the placebo gel. At t0, bone growth was observed in the test group and bone loss in the control group. In the subsequent periods, bone losses were observed for both groups, but always with statistical differences for lower loss in the test group [55,56,57,58,59].
Therefore, it can be understood that microbial infiltration through the implant–abutment interface is a problem still present in implant-supported rehabilitations, even when associated with implants with Morse cone connections, and this infiltration, if not minimized or controlled, can, in the long term, result in compromising the clinical success of the treatment if an imbalance of the associated oral microbiota occurs. More studies need to be conducted in order to clarify the relationship between the type of bacteria that develops and the clinical consequences, as well as studies that aim to develop interfaces that avoid, minimize or control the effects of the bacterial leakage.
5. Conclusions
Based on the results obtained in the present study, we can conclude that none of the implant–abutment combinations were able to prevent the microbial leakage through the interface. Mechanical cycling appears to play an important role in increasing the number of microbial counts. The design of the implant–abutment interface seems to be relevant to the type of microorganisms that penetrate and grow inside the implant.
Acknowledgments
The authors give thanks to Singular Implants (Natal, Brazil) for donating the implants and prosthetic components and Viviane de Cássia Oliveira (Dept. of Dental Materials and Prosthodontics, School of Dentistry of Ribeirao Preto, University of Sao Paulo) for technical support.
Author Contributions
Conceptualization, R.F.R., R.C.S.R. and C.d.N.; methodology, A.C.L.F., C.d.N., E.d.S.S., R.C.S.R. and R.F.R.; validation, V.B.d.M., L.d.O.T., A.A.S., A.C.L.F. and E.d.S.S.; formal analysis, E.d.S.S., A.C.L.F., C.d.N. and R.F.R.; investigation, V.B.d.M., L.d.O.T. and A.A.S.; resources, C.d.N., R.C.S.R. and R.F.R.; data curation, V.B.d.M., L.d.O.T., A.A.S., E.d.S.S. and A.C.L.F.; writing—original draft preparation, V.B.d.M., L.d.O.T. and E.d.S.S.; writing—review and editing, C.d.N., R.C.S.R. and R.F.R.; funding acquisition, R.F.R. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of the School of Dentistry of Ribeirao Preto, University of Sao Paulo (CAAE: 25836819.2.0000.5419 on 10 December 2019).
Informed Consent Statement
Not applicable.
Data Availability Statement
The data that support the findings of this study are available from the corresponding authors upon reasonable request.
Conflicts of Interest
The authors declare no conflicts of interest in relation to this study.
Funding Statement
This research was funded by Sao Paulo Research Foundation—FAPESP, grant number 2019/25405-0; R.F.R. received from National Council for Scientific and Technological Development—CNPq, a personal grant number 307944/2019-0; V.B.M. and A.A.S. received a Master and PhD scholarships, respectively, from Agency for the High-Standard Promotion of Graduate Courses—CAPES, which also support the Oral Rehabilitation Graduate Program—code 001.
Footnotes
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding authors upon reasonable request.