Robotic Arthroplasty Clinical and cost Effectiveness Randomised controlled trial (RACER-knee): a study protocol.

INTRODUCTION: Robotic-assisted knee replacement systems have been introduced to healthcare services worldwide in an effort to improve clinical outcomes for people, although high-quality evidence that they are clinically, or cost-effective remains sparse. Robotic-arm systems may improve surgical accuracy and could contribute to reduced pain, improved function and lower overall cost of total knee replacement (TKR) surgery. However, TKR with conventional instruments may be just as effective and may be quicker and cheaper. There is a need for a robust evaluation of this technology, including cost-effectiveness analyses using both within-trial and modelling approaches. This trial will compare robotic-assisted against conventional TKR to provide high-quality evidence on whether robotic-assisted knee replacement is beneficial to patients and cost-effective for healthcare systems. METHODS AND ANALYSIS: The Robotic Arthroplasty Clinical and cost Effectiveness Randomised controlled trial-Knee is a multicentre, participant-assessor blinded, randomised controlled trial to evaluate the clinical and cost-effectiveness of robotic-assisted TKR compared with TKR using conventional instruments. A total of 332 participants will be randomised (1:1) to provide 90% power for a 12-point difference in the primary outcome measure; the Forgotten Joint Score at 12 months postrandomisation. Allocation concealment will be achieved using computer-based randomisation performed on the day of surgery and methods for blinding will include sham incisions for marker clusters and blinded operation notes. The primary analysis will adhere to the intention-to-treat principle. Results will be reported in line with the Consolidated Standards of Reporting Trials statement. A parallel study will collect data on the learning effects associated with robotic-arm systems. ETHICS AND DISSEMINATION: The trial has been approved by an ethics committee for patient participation (East Midlands-Nottingham 2 Research Ethics Committee, 29 July 2020. NRES number: 20/EM/0159). All results from the study will be disseminated using peer-reviewed publications, presentations at international conferences, lay summaries and social media as appropriate. TRIAL REGISTRATION NUMBER: ISRCTN27624068.

Biophysical evaluation of milk-clotting enzymes processed by high pressure.

High pressure processing (HPP) is able to promote changes in enzymes structure. This study evaluated the effect of HP on the structural changes in milk-clotting enzymes processed under activation conditions for recombinant camel chymosin (212MPa/5min/10°C), calf rennet (280MPa/20min/25°C), bovine rennet (222MPa/5min/23°C), and porcine pepsin (50MPa/5min/20°C) and under inactivation conditions for all enzymes (600MPa/10min/25°C) including the protease from Rhizomucor miehei. In general, it was found that the HPP at activation conditions was able to increase the intrinsic fluorescence of samples with high pepsin concentration (porcine pepsin and bovine rennet), increase significantly the surface hydrophobicity and induce changes in secondary structure of all enzymes. Under inactivation conditions, increases in surface hydrophobicity and a reduction of intrinsic fluorescence were observed, suggesting a higher exposure of hydrophobic sites followed by water quenching of Trp residues. Moreover, changes in secondary structure were observed (with minor changes seen in Rhizomucor miehei protease). In conclusion, HPP was able to unfold milk-clotting enzymes even under activation conditions, and the porcine pepsin and bovine rennet were more sensitive to HPP.

Application of biochar and nitrogen influences fluxes of CO2, CH4 and N2O in a forest soil.

Nitrogen (N) fertilization of forests for increasing carbon sequestration and wood volume is expected to influence soil greenhouse gas (GHG) emissions, especially to increase N2O emissions. As biochar application is known to affect soil GHG emissions, we investigated the effect of biochar application, with and without N fertilization, to a forest soil on GHG emissions in a controlled laboratory study. We found that biochar application at high (10%) application rates increased CO2 and N2O emissions when applied without urea-N fertilizer. At both low (1%) and high biochar (10%) application rates CH4 consumption was reduced when applied without urea-N fertilizer. Biochar application with urea-N fertilization did not increase CO2 emissions compared to biochar amended soil without fertilizer. In terms of CO2-eq, the net change in GHG emissions was mainly controlled by CO2 emissions, regardless of treatment, with CH4 and N2O together accounting for less than 1.5% of the total emissions.