Assessment of Microgap and Microbial Leakage of Two Different Implant-abutment Interfaces: An In Vitro Study.

AIM: The purpose of the current study was to evaluate Titanium and Bioneck TRI implant-abutment interfaces for microgaps and microbiological leakage. MATERIALS AND METHODS: In this in vitro experiment, 40 dental implants were split into two groups, each of which had 20 samples. Group I: Titanium dental implant, group II: Bioneck TRI. E. coli strain was cultivated in MacConkey media for 24 hours at 37°C. To achieve a bacterial concentration of 1 × 108 colony-forming units per mL at 0.5 scale of MacFarland, the brain-heart infusion (BHI) broth was injected. The CFU count was done to evaluate the microbial leakage. The parts were first submerged, carefully cleaned in an ultrasonic bath, and then installed using a digital torque meter with a 20 N/cm preload. These were attached to a stub of approximately 13 mm using carbon tape, and the microgap evaluation was performed using a scanning electron microscope at a magnification of x1000. Unpaired t-test was used for the calculated data's statistical analysis. The p-value less than 0.05 was considered as statistically significant. RESULTS: The maximum microbial leakage was in Bioneck TRI implants (10000 ± 0.01) followed by Titanium dental implants (8.60 ± 3.16). The mean difference was 9991.40 and there was a statistically significant difference found between the two different groups. The maximum microgap was found in the Bioneck TRI implants (9.72 ± 0.96), followed by Titanium dental implant (6.82 ± 1.10) and there was a statistically significant difference was found between the groups (p < 0.001). CONCLUSION: The present study concluded that the microorganisms can infiltrate the microgap between the implant and abutment interface. When compared with Titanium dental implants, Bioneck TRI implants showed significantly higher levels of microbial leakage. CLINICAL SIGNIFICANCE: A microgap between the implant and abutment connection might operate as a bacterial source, may produce inflammation, even osseointegration in danger, and subsequently alter clinical and histological parameters. Therefore, having an understanding of the compatible components aids in overcoming treatment planning challenges.

Dynamics of capillary blood flow responses to acute local changes in oxygen and carbon dioxide concentrations.

Objectives: We aimed to quantify the magnitude and time transients of capillary blood flow responses to acute changes in local oxygen concentration ([O2]), and carbon dioxide concentration ([CO2]) in skeletal muscle. Additionally, we sought to quantify the combined response to both low [O2] and high [CO2] to mimic muscle microenvironment changes at the onset of exercise. Methods: 13 Sprague Dawley rats were anaesthetized, mechanically ventilated, and instrumented with indwelling catheters for systemic monitoring. The extensor digitorum longus muscle was blunt dissected, and reflected over a microfluidic gas exchange chamber in the stage of an inverted microscope. Four O2 challenges, four CO2 challenges, and a combined low O2 (7-2%) and high CO2 (5-10%) challenges were delivered to the surface with simultaneous visualization of capillary blood flow responses. Recordings were made for each challenge over a 1-min baseline period followed by a 2-min step change. The combined challenge employed a 1-min [O2] challenge followed by a 2-min change in [CO2]. Mean data for each sequence were fit using least-squared non-linear exponential models to determine the dynamics of each response. Results: 7-2% [O2] challenges decreased capillary RBC saturation within 2 s following the step change (46.53 ± 19.56% vs. 48.51 ± 19.02%, p < 0.0001, τ = 1.44 s), increased RBC velocity within 3 s (228.53 ± 190.39 µm/s vs. 235.74 ± 193.52 µm/s, p < 0.0003, τ = 35.54 s) with a 52% peak increase by the end of the challenge, hematocrit and supply rate show similar dynamics. 5-10% [CO2] challenges increased RBC velocity within 2 s following the step change (273.40 ± 218.06 µm/s vs. 276.75 ± 215.94 µm/s, p = 0.007, τ = 79.34s), with a 58% peak increase by the end of the challenge, supply rate and hematocrit show similar dynamics. Combined [O2] and [CO2] challenges resulted in additive responses to all microvascular hemodynamic measures with a 103% peak velocity increase by the end of the collection period. Data for mean responses and exponential fitting parameters are reported for all challenges. Conclusion: Microvascular level changes in muscle [O2] and [CO2] provoked capillary hemodynamic responses with differing time transients. Simulating exercise via combined [O2] and [CO2] challenges demonstrated the independent and additive nature of local blood flow responses to these agents.