Comparison of Bond Failure and Accuracy of Two Indirect Bonding Techniques and Materials: An In-Vivo Study

The purpose of this study was to compare and evaluate the clinical bond failure rate and accuracy of bracket placement of two indirect bonding materials and transfer trays. A split mouth technique was used in this study in which twenty patients were randomly divided into four groups: Group A – Polyvinyl siloxane / Sondhi™ Rapid-Set (3M unitek), Group B - Polyvinyl siloxane / custom IQ (Reliance orthodontics), Group C - Thermal glue / Sondhi™ Rapid-Set (3M unitek) & Group D - Thermal glue / custom IQ ( Reliance orthodontics). A total of 326 brackets were bonded and bond failure of brackets involved only first time failures during the tray removal, initial arch wire placement and thereafter three consecutive appointments (30,60 and 90 days). Accuracy of bracket placement was measured with modified digital/vernier caliper. Vertical and horizontal measurements were taken both on the models and intraorally in the patients and were evaluated for accuracy. CONCLUSION: The findings of the study showed Polyvinyl Siloxane / Sondhi Rapid Set had maximum bond failure rate (25.4%) when compared with other groups. The bond failure rate was higher during the transfer tray removal (7.6%) which gradually declined in consecutive appointments. Thermal glue transfer tray and Custom IQ (Reliance orthodontics) resin proved to be superior with minimum bond failure. Mandibular second premolars (22.2%) and lower incisors (17.7%) showed increased bond failure rates. Indirect bonding was accurate in vertical dimension and fourth quadrant showed least accuracy. Thermal glue / Sondhi Rapid set (3M unitek) group was efficient in accurate transfer of the brackets. Thermal Glue found to be an inexpensive and a better transfer tray material when compared to Polyvinyl Siloxane. Thermal Glue tray reinforced with 19 gauge wire proved to be more effective. In case of malocclusions it was recommended to section the tray to minimize bond failure. Modified Digital vernier caliper can be a reproducible and convenient method for measuring bracket placement accuracy. These findings need to be confirmed in future studies with larger samples over a longer period of time

Elevated Tumor Lactate and Efflux in High-grade Prostate Cancer demonstrated by Hyperpolarized 13C Magnetic Resonance Spectroscopy of Prostate Tissue Slice Cultures.

Non-invasive assessment of the biological aggressiveness of prostate cancer (PCa) is needed for men with localized disease. Hyperpolarized (HP) 13C magnetic resonance (MR) spectroscopy is a powerful approach to image metabolism, specifically the conversion of HP [1-13C]pyruvate to [1-13C]lactate, catalyzed by lactate dehydrogenase (LDH). Significant increase in tumor lactate was measured in high-grade PCa relative to benign and low-grade cancer, suggesting that HP 13C MR could distinguish low-risk (Gleason score ≤3 + 4) from high-risk (Gleason score ≥4 + 3) PCa. To test this and the ability of HP 13C MR to detect these metabolic changes, we cultured prostate tissues in an MR-compatible bioreactor under continuous perfusion. 31P spectra demonstrated good viability and dynamic HP 13C-pyruvate MR demonstrated that high-grade PCa had significantly increased lactate efflux compared to low-grade PCa and benign prostate tissue. These metabolic differences are attributed to significantly increased LDHA expression and LDH activity, as well as significantly increased monocarboxylate transporter 4 (MCT4) expression in high- versus low- grade PCa. Moreover, lactate efflux, LDH activity, and MCT4 expression were not different between low-grade PCa and benign prostate tissues, indicating that these metabolic alterations are specific for high-grade disease. These distinctive metabolic alterations can be used to differentiate high-grade PCa from low-grade PCa and benign prostate tissues using clinically translatable HP [1-13C]pyruvate MR

Modeling hyperpolarized lactate signal dynamics in cells, patient-derived tissue slice cultures and murine models.

Determining the aggressiveness of renal cell carcinoma (RCC) noninvasively is a critical part of the diagnostic workup for treating this disease that kills more than 15,000 people annually in the USA. Recently, we have shown that not only the amount of lactate produced, as a consequence of the Warburg effect, but also its efflux out of the cell, is a critical marker of RCC aggressiveness and differentiating RCCs from benign renal tumors. Enzymatic conversions can now be measured in situ with hyperpolarized (HP) 13 C magnetic resonance (MR) on a sub-minute time scale. Using RCC models, we have shown that this technology can interrogate in real time both lactate production and compartmentalization, which are associated with tumor aggressiveness. The dynamic HP MR data have enabled us to robustly characterize parameters that have been elusive to measure directly in intact living cells and murine tumors thus far. Specifically, we were able to measure the same intracellular lactate longitudinal relaxation time in three RCC cell lines of 16.42 s, and lactate efflux rate ranging from 0.14 to 0.8 s-1 in the least to the most aggressive RCC cell lines and correlate it to monocarboxylate transporter isoform 4 expression. We also analyzed dynamic HP lactate and pyruvate data from orthotopic murine RCC tumors using a simplified one-compartment model, and showed comparable apparent pyruvate to lactate conversion rate (kPL ) values with those measured in vitro. This kinetic modeling was then extended to characterize the lactate dynamics in patient-derived living RCC tissue slices; and even without direct measurement of the extracellular lactate signal the efflux parameter was still assessed and was distinct between the benign renal tumors and RCCs. Across all these preclinical models, the rate parameters of kPL and lactate efflux correlated to cancer aggressiveness, demonstrating the validity of our modeling approach for noninvasive assessment of RCC aggressiveness

A comprehensive study on the performance and emission analysis in diesel engine via optimization of novel ternary fuel blends: Diesel, manganese, and diethyl ether

Ecosystem degradation and fossil fuel depletion are the two foremost concerns to look for alternative fuels. Rapid population growth is primarily accountable for higher consumption of fossil fuel sources, although engine technology is achieving milestones in terms of fuel efficiency and lower exhaust emissions in order to contribute towards a sustainable environment. The main root cause of global warming is carbon dioxide emissions; therefore, it is imperative to assess the impact of alternative fuels in diesel engines with an aim to minimize carbon emissions. A current study deals with the reduction of carbon emissions and improvement of efficiency through addition of manganese nano-additive to di-ethyl ether and diesel fuel blend in particulate form. Fuel blends were formed by adding various proportions of manganese to high-speed diesel fuel and stirring the mixture while heating it for 10 min. The blends were then tested in diesel engines at two distinct loads and five engine speed ranges. Emission analyzer was used to ascertain the CO2 output of engine. At higher loads for 10 % diethyl ether in diesel, the increase in brake thermal efficiency was 24.19, 28.17 and 26.86 % when the manganese amount in blend was changed as 250 mg, 375 mg and 500 mg respectively. On the other side CO2 emissions increase by 11.57, 30.52 and 20.33 % for manganese concentrations of 250 mg, 375 mg and 500 mg respectively. Analysis performed with Design Expert 13 showed that the desirability was 0.796 for a blend of 375 mg manganese at 1300 rpm and 4500 W load with 33.0611 % BTE, 334.011kg/kWh BSFC, 67.8821Nm torque, and 6.072 % CO2. Therefore, it can be deduced that manganese nanoparticle blends improved engine performance but CO2 emissions also increase which can be responsible for global warming and it should be reduced through catalytic converters

Point-of-care motion capture and biomechanical assessment improve clinical utility of dynamic balance testing for lower extremity osteoarthritis.

Musculoskeletal conditions impede patient biomechanical function. However, clinicians rely on subjective functional assessments with poor test characteristics for biomechanical outcomes because more advanced assessments are impractical in the ambulatory care setting. Using markerless motion capture (MMC) in clinic to record time-series joint position data, we implemented a spatiotemporal assessment of patient kinematics during lower extremity functional testing to evaluate whether kinematic models could identify disease states beyond conventional clinical scoring. 213 trials of the star excursion balance test (SEBT) were recorded by 36 subjects during routine ambulatory clinic visits using both MMC technology and conventional clinician scoring. Conventional clinical scoring failed to distinguish patients with symptomatic lower extremity osteoarthritis (OA) from healthy controls in each component of the assessment. However, principal component analysis of shape models generated from MMC recordings revealed significant differences in subject posture between the OA and control cohorts for six of the eight components. Additionally, time-series models of subject posture change over time revealed distinct movement patterns and reduced overall postural change in the OA cohort compared to the controls. Finally, a novel metric quantifying postural control was derived from subject specific kinematic models and was shown to distinguish OA (1.69), asymptomatic postoperative (1.27), and control (1.23) cohorts (p = 0.0025) and to correlate with patient-reported OA symptom severity (R = -0.72, p = 0.018). Time series motion data have superior discriminative validity and clinical utility than conventional functional assessments in the case of the SEBT. Novel spatiotemporal assessment approaches can enable routine in-clinic collection of objective patient-specific biomechanical data for clinical decision-making and monitoring recovery