Novel minimally invasive treatments for lower urinary tract symptoms: a systematic review and network meta-analysis

ABSTRACT Purpose: To review and compare the effectivity of novel minimally invasive treatments (MITs) to transurethral resection of the prostate (TURP) for the treatment of lower urinary tract symptoms (LUTS) in men. Methods: Medline, Embase, and Cochrane databases were searched from January 2010 to December 2022 for randomized controlled trials (RCTs) evaluating MITs, compared to TURP or sham, in men with LUTS. Studies were assessed by risk of bias tool, and evidence by GRADE. Functional outcomes by means of uroflowmetry and IPSS were the primary outcomes, safety and sexual function were secondary outcomes. As part of this review, a network meta-analysis (NMA) was conducted. MITs were ranked based on functional outcome improvement probability. Results: In total, 10 RCTs were included, evaluating aquablation, prostatic urethral lift, prostatic artery embolization (PAE), convective water vapor thermal treatment or temporary implantable nitinol device. All MITs showed a better safety profile compared to TURP. Functional outcome improvement following aquablation were comparable to TURP. In the NMA, aquablation was ranked highest, PAE followed with the second highest probability to improve functional outcomes. Other novel MITs resulted in worse functional outcomes compared to TURP. Level of evidence was low to very low. Conclusions: Five MITs for treatment of LUTS were identified. Aquablation is likely to result in functional outcomes most comparable to TURP. Second in ranking was PAE, a technique that does not require general or spinal anesthesia. MITs have a better safety profile compared to TURP. However, due to high study heterogeneity, results should be interpreted with caution

Screening Methodology for the Efficient Pairing of Ionic Liquids and Carbonaceous Electrodes Applied to Electric Energy Storage

A model is presented that correlates the measured electric capacitance with the energy that comprises the desolvation, dissociation and adsorption energy of an ionic liquid into carbonaceous electrode (represented by single-wall carbon nanotubes). An original methodology is presented that allows for the calculation of the adsorption energy of ions in a host system that does not necessarily compensate the total charge of the adsorbed ions, leaving an overall net charge. To obtain overall negative (favorable) energies, adsorption energies need to overcome the energy cost for desolvation of the ion pair and its dissociation into individual ions. Smaller ions, such as BF4 −, generally show larger dissociation energies than anions such as PF6 − or TFSI−. Adsorption energies gradually increase with decreasing pore size of the CNT and show a maximum when the pore size is slightly greater than the dimensions of the adsorbed ion and the attractive van der Waals forces dominate the interaction. At smaller pore diameters, the adsorption energy sharply declines and becomes repulsive as a result of geometry deformations of the ion. Only for those diameters where the adsorption reaches maximum values is the adsorption energy sufficiently negative to balance the positive dissociation and desolvation energies. We present for each ion (and ionic liquid) what the most adequate electrode pore size should be for maximum capacitance

Density Functional Theory Study of Monoethanolamine Adsorption on Hydroxylated Cr2O3 Surfaces

International audienceThe adsorption of monoethanolamine (MEA), a well-known CO2 capture amine, on the hydroxylated (0001)-Cr2O3 surface was investigated by periodic density functional theory calculations and complementary ab initio molecular dynamics. Two different adsorption modes were investigated: adsorption of MEA above the hydroxylated surface and substitution of a surface water molecule by MEA. Several MEA coverages were studied from 0.25 to 1 monolayer. An atomistic thermodynamic approach was used to take into account the effects of temperature and solvation on the MEA adsorption process in aqueous solution. MEA can adsorb on the surface in a parallel orientation, and H-bonds are formed between amine and alcohol groups and different (H)OH groups at the surface. In the gas phase at 0 K, the formation of a monolayer (ML) of MEA above the surface is the most favorable adsorption mode. In aqueous solution at 298.15K, calculations have suggested that MEA adsorbs above the hydroxylated Cr2O3 surface with a density of 2.37 MEA/nm2 (0.5 ML). However, the substitution process was found to be endothermic at temperatures above 298.15 K

First-Principles Chemical Kinetic Modeling of Methyl trans -3-Hexenoate Epoxidation by HO 2

International audienceThe design of innovative combustion processes relies on a comprehensive understanding of biodiesel oxidation kinetics. The present study aims at unraveling the reaction mechanism involved in the epoxidation of a realistic biodiesel surrogate, methyl trans-3-hexenoate, by hydroperoxy radicals using a bottom-up theoretical kinetics methodology. The obtained rate constants are in good agreement with experimental data for alkene epoxidation by HO2. The impact of temperature and pressure on epoxidation pathways involving H-bonded and non-H-bonded conformers was assessed. The obtained rate constant was finally implemented into a state-of-the-art detailed combustion mechanism, resulting in fairly good agreement with engine experiments

ReaxFF Alumina Parametrization Data Set

ReaxFF Alumina Parametrization Data Set This dataset contains all the data needed to reproduce the Alumina Parametrization of ReaxFF, see bibliographic reference in the metadata. All AMS calculations are performed using AMS2023.101. Whenever possible, Python scripts are written so that they do not require AMS, making a large portion of the scripts reproducible with open-source software. The instructions below assume that the archive is unpacked on a Linux system, as follows: unzip dataset-parametrization.zip This will preserve file permissions upon extraction. Do not transfer the files to a Linux system after unpacking this archive on Windows, as this will remove the file permission flags. Data descriptor *** How the data were generated *** The following steps summarize how to reproduce the results in this dataset. It is assumed that you have a Linux system with AMS 2023.101 installed. Copy the file amsenv.sh.example to amsenv.sh and change the variables in this copy to match the location of your AMS installation. For all non-AMS scripts, a Micromamba environment is used, which can be created with ./setup-env-micromamba.sh. After installation, you either manually activate the environment with source env/bin/activate or use direnv. The VASP calculations for the training and validation sets are converted into files for ParAMS by running the following scripts: (cd training-set/conversion; ./job.sh) (cd validation-set/conversion; ./job.sh) The job scripts can also be submitted with sbatch on a cluster. (You may need to modify them to work on your system.) This will produce several files for each set, of which the following are relevant: chemformula.json: names and chemical formulas of all structures counts.json: counts of data set items in each category, per structure energies.json: electronic energies of all structures and chemical equations ics_phase1.json: internal coordinates in phase 1, see article for details ics_phase2.json: internal coordinates in phase 2, see article for details job_collection_{name}.yaml: Job collections for ParAMS {name}_set.yaml: Dataset entries for ParAMS These output files are already included in this archive. Only the .yaml files are used by ParAMS. The JSON files are used by some of the scripts in this archive, and were also used to generate tables and figures in the article. The parameter selection can be reproduced as follows: (cd parameter-selection; ./parameter_selection_ams.py) This will produce a parameter_interface.yaml file that can be used as input to ParAMS. It contains the selection of parameters, the bounds and the historical values taken from Joshi et al. The parameter_interface.yaml file is already included in the archive. At this stage, all inputs for the parametrization are available. The actual parametrization workflow is implemented in the opt-*-p28 directories. Note that the inputs to ParAMS and some configuration files for the workflow are stored in opt-*-p28/results/given. To repeat the parametrization workflow, remove the existing outputs (all directories under opt-*-p28/results/ except given). If some directories still exist, these steps will not be repeated. After removing existing outputs, enter one of the opt-*-p28 directories and run ../opt/workflow.py This will coordinate the submission of various jobs to Slurm including: 40 CMA optimizations, the recomputation of the loss for a range geometryoptimization.MaxIterations values, for all 40 optimized force fields, and the evaluation of the data sets, using the best result from the 40 CMA runs. Again, you may need to modify the job scripts in opt/templates/*/ to make them work on your system. *** Software that was used *** AMS 2023.101. Python 3.11 and all packages listed in environment.yaml. (These are installed with the command ./setup-env-micromamba.sh.) The custom ParAMS extractors defined in ./extractors/. These extractors are a workaround for efficiency issues in ParAMS. Instead of listing each angle or distance as a separate dataset item, these extractors group such quantities into arrays, which speeds up the training and increases parallel efficiency. At the time of writing, there is still a bug in AMS 2023.101, which requires one to manually edit singleton arrays that lack square brackets in a dataset.yaml file. The Python scripts under scripts/ are used to generate the training and validation sets. The Balanced Loss function is implemented in a module site-packages/balanced_loss_ams.py. *** Directory and file organization *** Most directories have already been defined in the previous two sections. This section only discusses some points not mentioned above. The parametrization workflow consists of three different types of jobs, whose implementation can be found in opt/templates. Running ./setup-env-micromamba.sh installs the Python environment in a subdirectory env. The VASP outputs can be found in training-set/vasp-calculations and validation-set/vasp-calculations. Note that POTCAR files are not included due to restrictions imposed by the VASP license. Python scripts ending with _ams.py should be executed (or imported) with amspython. The distinction is necessary because AMS2023.101 includes Python 3.8, while the rest of the Python scripts may benefit from new features in Python 3.11. By using this filename convention, we can apply pyupgrade selectively for different Python versions. The MANIFEST.sha256sum file can be used to check the archive for corrupted files, e.g. due to bit rot. The following command will verify all files after unpacking the archive: cut -c 17- MANIFEST.sha256 | sha256sum -c *** File content details *** All .json files in this archive contain custom data structures specific to this project. To understand their contents, please refer to the source code of the scripts that generate and use these files. All other file formats are defined in the context of external software packages (VASP, AMS, …) and these formats will not be explained here

Impact of Associated Gases on Equilibrium and Transport Properties of a CO2 Stream: Molecular Simulation and Experimental Studies

International audienceDuring the various carbon dioxide capture and storage (CCS) stages, an accurate knowledge of thermodynamic properties of CO2 streams is required for the correct sizing of plant units. The injected CO2 streams are not pure and often contain small amounts of associated gaseous components such as O2,N2, SOx ,NOx , noble gases, etc. In this work, the thermodynamic behavior and transport properties of some CO2-rich mixtures have been investigated using both experimental approaches and molecular simulation techniques such as Monte Carlo and molecular dynamics simulations.Using force fields available in the literature,we have validated the capability of molecular simulation techniques in predicting properties for pure compounds, binary mixtures, as well as multicomponent mixtures. These validations were performed on the basis of experimental data taken from the literature and the acquisition of new experimental data. As experimental data and simulation results were in good agreement, we proposed the use of simulation techniques to generate new pseudoexperimental data and to study the impact of associated gases on the properties of CO2 streams. For instance, for a mixture containing 92.0mol% of CO2, 4.0mol% of O2, 3.7mol% of Ar, and 0.3mol% of N2, we have shown that the presence of associated gases leads to a decrease of 14% and 21% of the dense phase density and viscosity, respectively, as compared to pure CO2 properties

Reaction Kinetics of a Selected Number of Elementary Processes Involved in the Thermal Decomposition of 9-Methylphenanthrene Using Density Functional Theory

With the use of general transition state theory and density functional theory, six reference reactions that are thought to play an essential role in the thermal cracking process of 9-methylphenanthrene have been studied. At the uB3LYP/6-31G(d,p) level, the transition state structures could be located on the 0 K potential energy surface for the three propagation reactions which induce no net creation/annihilation of radicals, and the calculated activation energies and preexponential frequency factor generally correspond well to experimental values. The transition states for two termination reactions were determined by replacement of a phenanthrenic by a phenylic aromatic moiety; it followed that such model reactions represent well systems with larger aromatic units. Only for the initiation reaction the transition state could not be located; in this case the activation energy was approximated by the change in overall enthalpy