Characteristics of Particles and Debris Released after Implantoplasty: A Comparative Study

Titanium particles embedded on peri-implant tissues are associated with a variety of detrimental effects. Given that the characteristics of these detached fragments (size, concentration, etc.) dictate the potential cytotoxicity and biological repercussions exerted, it is of paramount importance to investigate the properties of these debris. This study compares the characteristics of particles released among different implant systems (Group A: Straumann, Group B: BioHorizons and Group C: Zimmer) during implantoplasty. A novel experimental system was utilized for measuring and collecting particles generated from implantoplasty. A scanning mobility particle sizer, aerodynamic particle sizer, nano micro-orifice uniform deposit impactor, and scanning electron microscope were used to collect and analyze the particles by size. The chemical composition of the particles was analyzed by highly sensitive microanalysis, microstructures by scanning electron microscope and the mechanical properties by nanoindentation equipment. Particles released by implantoplasty showed bimodal size distributions, with the majority of particles in the ultrafine size range (<100 nm) for all groups. Statistical analysis indicated a significant difference among all implant systems in terms of the particle number size distribution (p < 0.0001), with the highest concentration in Group B and lowest in Group C, in both fine and ultrafine modes. Significant differences among all groups (p < 0.0001) were also observed for the other two metrics, with the highest concentration of particle mass and surface area in Group B and lowest in Group C, in both fine and ultrafine modes. For coarse particles (>1 µm), no significant difference was detected among groups in terms of particle number or mass, but a significantly smaller surface area was found in Group A as compared to Group B (p = 0.02) and Group C (p = 0.005). The 1 first minute of procedures had a higher number concentration compared to the second and third minutes. SEM-EDS analysis showed different morphologies for various implant systems. These results can be explained by the differences in the chemical composition and microstructures of the different dental implants. Group B is softer than Groups A and C due to the laser treatment in the neck producing an increase of the grain size. The hardest implants were those of Group C due to the cold-strained titanium alloy, and consequently they displayed lower release than Groups A and B. Implantoplasty was associated with debris particle release, with the majority of particles at nanometric dimensions. BioHorizons implants released more particles compared to Straumann and Zimmer. Due to the widespread use of implantoplasty, it is of key importance to understand the characteristics of the generated debris. This is the first study to detect, quantify and analyze the debris/particles released from dental implants during implantoplasty including the full range of particle sizes, including both micro- and nano-scales.

Assessing the Accuracy of Estimated Lipoprotein(a) Cholesterol and Lipoprotein(a)‐Free Low‐Density Lipoprotein Cholesterol

Background Accurate measurement of the cholesterol within lipoprotein(a) (Lp[a]‐C) and its contribution to low‐density lipoprotein cholesterol (LDL‐C) has important implications for risk assessment, diagnosis, and treatment of atherosclerotic cardiovascular disease, as well as in familial hypercholesterolemia. A method for estimating Lp(a)‐C from particle number using fixed conversion factors has been proposed (Lp[a]‐C from particle number divided by 2.4 for Lp(a) mass, multiplied by 30% for Lp[a]‐C). The accuracy of this method, which theoretically can isolate “Lp(a)‐free LDL‐C,” has not been validated. Methods and Results In 177 875 patients from the VLDbL (Very Large Database of Lipids), we compared estimated Lp(a)‐C and Lp(a)‐free LDL‐C with measured values and quantified absolute and percent error. We compared findings with an analogous data set from the Mayo Clinic Laboratory. Error in estimated Lp(a)‐C and Lp(a)‐free LDL‐C increased with higher Lp(a)‐C values. Median error for estimated Lp(a)‐C <10 mg/dL was −1.9 mg/dL (interquartile range, −4.0 to 0.2); this error increased linearly, overestimating by +30.8 mg/dL (interquartile range, 26.1–36.5) for estimated Lp(a)‐C ≥50 mg/dL. This error relationship persisted after stratification by overall high‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol subtypes. Similar findings were observed in the Mayo cohort. Absolute error for Lp(a)‐free LDL‐C was +2.4 (interquartile range, −0.6 to 5.3) for Lp(a)‐C<10 mg/dL and −31.8 (interquartile range, −37.8 to −26.5) mg/dL for Lp(a)‐C≥50 mg/dL. Conclusions Lp(a)‐C estimations using fixed conversion factors overestimated Lp(a)‐C and subsequently underestimated Lp(a)‐free LDL‐C, especially at clinically relevant Lp(a) values. Application of inaccurate Lp(a)‐C estimations to correct LDL‐C may lead to undertreatment of high‐risk patients.

Analysis of Low and High Temperature Heat Release in Dual-Fuel RCCI Engine and its Relationship with Particle Emissions

This study presents the influence of low-temperature heat release (LTHR) and high-temperature heat release (HTHR) on the combustion and particle number characteristics of the RCCI engine. The study investigates the relationship between the amount of LTHR, HTHR, and particle number emission characteristics. In this study, gasoline and methanol are used as low reactivity fuel (LRF), and diesel is used as a high reactivity fuel (HRF). The LRF is injected into the intake manifold using a port-fuel injection (PFI) strategy, and HRF is directly injected into the cylinder using a direct injection strategy. A particle sizer is used to measure particle emission in size ranging from 5 to 1000 nm. Firstly, the LTHR and HTHR are analyzed for different diesel injection timing (SOI) for RCCI operation. Later, the variation of particle emissions with LTHR and HTHR is characterized. Additionally, empirical correlations are developed to understand the relation between the LTHR and HTHR with particle emission. Two-staged auto-ignition of charge has been observed in RCCI combustion. Results depict that LTHR varies with diesel injection timing and the phasing of HTHR depends on the amount and location of LTHR. Results also showed that HTHR and LTHR significantly influence the formation of particle number concentration in RCCI combustion. The developed empirical correlation depicts a good correlation between diesel SOI and the ratio of HTHR to LTHR to estimate total particle number concentration.

Entropies and IPR as Markers for a Phase Transition in a Two-Level Model for Atom–Diatomic Molecule Coexistence

A quantum phase transition (QPT) in a simple model that describes the coexistence of atoms and diatomic molecules is studied. The model, which is briefly discussed, presents a second-order ground state phase transition in the thermodynamic (or large particle number) limit, changing from a molecular condensate in one phase to an equilibrium of diatomic molecules–atoms in coexistence in the other one. The usual markers for this phase transition are the ground state energy and the expected value of the number of atoms (alternatively, the number of molecules) in the ground state. In this work, other markers for the QPT, such as the inverse participation ratio (IPR), and particularly, the Rényi entropy, are analyzed and proposed as QPT markers. Both magnitudes present abrupt changes at the critical point of the QPT.

Number concentration dependence of ultrasonic disruption ratio of diameter-sorted microcapsules

The use of ultrasound to destroy microcapsules in microbubble-assisted drug delivery systems (DDS) is of great interest. In the present study, the disruption ratios of capsule clusters were measured by observing and experimentally analyzing microcapsules with polymer shells undergoing disruption by ultrasound. The microcapsules were dispersed in a planar microchamber filled with a gelatin gel and sonicated using 1 MHz focused ultrasound. Different capsule populations were obtained using a filtration technique to modify and control the capsule sizes. The disruption ratio as a function of the concentration of capsules was obtained through image processing of the recorded photomicrographs. We found that the disruption ratio for each population exponentially decreases as the particle number concentration (PNC) increases. The maximum disruption ratio of the diameter-sorted capsules was larger than that of polydispersed capsules. Particularly, for resonant capsule populations, the ratio was more than twice that of polydispersed capsules. Furthermore, the maximum disruption ratio occurred at higher concentrations as the mean particle diameter of the capsule cluster decreased.

The Impact of Traffic and Meteorology on Urban Particle Mass and Particle Number Concentrations: Student-Led Studies Using Mobile Measurements before, during, and after the COVID-19 Pandemic Lockdowns

A series of student-led research activities were performed using a cargo bicycle equipped with air chemistry instrumentation to study the dynamics of aerosol particles in urban air before, during, and after the COVID-19 lockdown periods. The studies examined a high-traffic route and a low-traffic route around the city center of Münster, Germany. A complex picture emerged for how the particle number concentrations (PN) and particle mass concentrations (PM, specifically PM10) were affected by the day of the week, the route selected, the meteorological conditions, and the traffic intensity. Traffic had the most impact on PN through the multitude of exhaust plumes from motorized vehicles. The impact of traffic on PM10 was rather low, which is also mirrored in the general pattern of the low response of PM10 to the pandemic lockdown in Germany. Instead, PM10 responded more to the day of the week. Presumably, PM10 responds either to a specific traffic component, such as commercial low-duty vehicles, or to other business, such as construction activity. Meteorological conditions exert their impact mostly through the relative humidity, which affects particle growth. As such, future research could examine PN and PM10 responses over all seasons of the year. In any case, this student-led study in which high-resolution data were acquired deepened our understanding and broadened our view on particle dynamics in urban air. Well-trained university graduates will contribute to meeting further challenges in studying and combatting air pollution.