Impact of drainage catheter material, size, and anti-dislodgement mechanism on percutaneous nephrostomy exchange intervals: a systematic review protocol [version 1; peer review: 2 approved]

Background: Percutaneous nephrostomy (PCN) is a commonly performed procedure by interventional radiology and urology to treat urinary obstruction. In this procedure, a catheter is percutaneously placed into the renal pelvis for urinary diversion or hemorrhagic cystitis. Material type, catheter size, and catheter shape (anti-dislodgement feature) ultimately contribute to the inherent traits of longevity in drainage catheter device. Reviewing the relative strengths or weaknesses of products in the existing clinical market may help clinicians critically appraise the devices they use with evidence-based findings from this review. Furthermore, a deeper understanding of the relative strengths and weaknesses of existing devices may help inform the next generation of drainage catheter devices to prolong the interval between exchanges without detriment to patient safety. Methods: The following electronic databases will be queried: PubMed, Web of Science, Cochrane from their inception to January 2023 to identify randomized controlled trials (RCTs) and cohort studies to investigate the differences that our interventions of catheter material, size, and dislodgement mechanism will have on the exchange interval (standard of care 90 days vs. 60 days vs. 45 days vs. 30 days). The primary outcomes will be the drainage catheter exchange frequency. Ethics and dissemination: We aim to share our findings through high-impact peer reviewed journals. As drainage catheters and minimally invasive interventional radiology procedures become more popular, it is important for healthcare providers taking case of these populations to understand which variables might optimize patient care and minimize emergent exchanges. Data will be made available to readers. Registration: PROSPERO (CRD42023432788, 16 June 2023)

ExoMars Raman Laser Spectrometer (RLS): development of chemometric tools to classify ultramafic igneous rocks on Mars

Producción CientíficaThis work aims to evaluate whether the multi-point analysis the ExoMars Raman Laser Spectrometer (RLS) will perform on powdered samples could serve to classify ultramafc rocks on Mars. To do so, the RLS ExoMars Simulator was used to study terrestrial analogues of Martian peridotites and pyroxenites by applying the operational constraints of the Raman spectrometer onboard the Rosalind Franklin rover. Besides qualitative analysis, RLS-dedicated calibration curves have been built to estimate the relative content of olivine and pyroxenes in the samples. These semi-quantitative results, combined with a rough estimate of the concentration ratio between clino- and ortho-pyroxene mineral phases, were used to classify the terrestrial analogues. XRD data were fnally employed as reference to validate Raman results. As this preliminary work suggests, ultramafc rocks on Mars could be efectively classifed through the chemometric analysis of RLS data sets. After optimization, the proposed chemometric tools could be applied to the study of the volcanic geological areas detected at the ExoMars landing site (Oxia Planum), whose mineralogical composition and geological evolution have not been fully understoodProyecto MINECO Retos de la Sociedad. Ref. ESP2017-87690-C3-1-RProyecto MINECO Retos de la Sociedad. Ref. ESP2017-87690-C3-1-

Raman semi-quantification on Mars: ExoMars RLS system as a tool to better comprehend the geological evolution of martian crust

Producción CientíficaThis work presents the latest chemometric tools developed by the RLS science team to optimize the scientific outcome of the Raman system onboard the ExoMars 2022 rover. Feldspar, pyroxene and olivine samples were first analyzed through the RLS ExoMars Simulator to determine the spectroscopic indicators to be used for a proper discrimination of mineral phases on Mars. Being the main components of Martian basaltic rocks, lepidocrocite, augite and forsterite were then used as mineral proxies to prepare binary mixtures. By emulating the operational constraints of the RLS, Raman datasets gathered from laboratory mixtures were used to build external calibration curves. Providing excellent coefficients of determination (R2 0.9942÷0.9997), binary curves were finally used to semi-quantify ternary mixtures of feldspar, pyroxene and olivine minerals. As Raman results are in good agreement with real concentration values, this work suggests the RLS could be effectively used to perform semi-quantitative mineralogical studies of the basaltic geological units found at Oxia Planum. As such, crucial information about the geological evolution of Martian Crust could be extrapolated. In light of the outstanding scientific impact this analytical method could have for the ExoMars mission, further methodological improvements to be discussed in a dedicated work are finally proposed.Consejo Europeo de Investigación (grant 687302)Ministerio de Economía, Industria y Competitividad (grants PID2019-107442RB-C31 and RDE2018-102600-T

Non‐steroidal anti‐inflammatory drugs (NSAIDs) for acute sore throat

This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To assess the effects of non‐steroidal anti‐inflammatory drugs (NSAIDs) for acute sore throat in children and adults

Application of chemometrics on Raman spectra from Mars: Recent advances and future perspectives

Producción CientíficaThe SuperCam and SHERLOC instruments onboard the NASA/Perseverancerover are returning the first Raman spectra to be ever collected from anotherplanet. Similarly, the RLS instrument onboard the ESA/Rosalind Franklinrover will collect Raman spectra from powdered rocks sampled from thesubsurface of Mars. To optimize the scientific exploitation of Raman spectrareturned from planetary exploration missions, tailored chemometric tools arebeing developed that take into account the analytical capability of the men-tioned Raman spectrometers. In this framework, the ERICA research groupis using laboratory simulators of SuperCam and RLS to perform representa-tive laboratory studies that will enhance the scientific outcome of bothMars2020 and ExoMars missions. On one hand, preliminary studies provedthe chemometric analysis of RLS datasets could be used to obtain a reliablesemi-quantitative estimation of the main mineral phases composing Martiangeological samples. On the other hand, it was proved the data fusion ofRaman and LIBS spectra gathered by SuperCam could be used to enhancethe discrimination of mineral phases from remote geological targets. Besidesdescribing the models developed by the ERICA group, this work presents anoverview of the complementary chemometric approaches so far tested in thisfield of study and propose further improvements to be addressed in thefuture.Ministerio de Economía y Competitividad, Beca/Concesión Número:PID2019-107442RBC31European Union’s Horizon 2020 research and innovation program. grant agreement no. 68730

Laboratory analysis of returned samples from the AMADEE-18 Mars analog mission

Between 01-28. February 2018, the Austrian Space Forum, in cooperation with the Oman Astronomical Society and research teams from 25 nations conducted the AMADEE-18 mission, a human-robotic Mars expedition simulation in the Dhofar region in the Sultanate of Oman As a part of the AMADEE-18 simulated Mars human exploration mission, the Remote Science Support team performed analysis of the Dhofar area, (Oman) in order to characterize it as a potential Mars analog site. The main motivation of this research was to study and register selected samples collected by the analog astronauts during the AMADEE-18 mission with laboratory analytical methods and techniques comparable to the techniques that will be used on Mars in the future. The 25 samples representing unconsolidated sediments obtained during the simulated mission were studied by using optical microscopy, Raman spectroscopy, X-ray diffraction, laser-induced breakdown spectroscopy, and laser-induced fluorescence. The principal results showed the existence of minerals and the detection of alteration processes related to volcanism, hydrothermalism, and weathering. The analogy between the Dhofar region and the Eridana Basin region of Mars is clearly noticeable, particularly as an analog for secondary minerals formed in a hydrothermal seafloor volcanic-sedimentary environment. The synergy between the techniques used in the present work provides a solid basis for the geochemical analyses and organic detection in the context of future human-robotic Mars expeditions. AMADEE-18 has been a prime test bed for geoscientific workflows with astrobiological relevance and has provided valuable insights for future space missions

Machine learning methods applied to combined Raman and LIBS spectra: Implications for mineral discrimination in planetary missions

Producción CientíficaThe combined analysis of geological targets by complementary spectroscopic techniques could enhance the characterization of the mineral phases found on Mars. This is indeed the case with the SuperCam instrument onboard the Perseverance rover. In this framework, the present study seeks to evaluate and compare multiple machine learning techniques for the characterization of carbonate minerals based on Raman-LIBS (Laser-Induced Breakdown Spectroscopy) spectroscopic data. To do so, a Ca-Mg prediction curve was created by mixing hydromagnesite and calcite at different concentration ratios. After their characterization by Raman and LIBS spectroscopy, different multivariable machine learning (Gaussian process regression, support vector machines, ensembles of trees, and artificial neural networks) were used to predict the concentration ratio of each sample from their respective datasets. The results obtained by separately analyzing Raman and LIBS data were then compared to those obtained by combining them. By comparing their performance, this work demonstrates that mineral discrimination based on Gaussian and ensemble methods optimized the combine of Raman-LIBS dataset outperformed those ensured by Raman and LIBS data alone. This demonstrated that the fusion of data combination and machine learning is a promising approach to optimize the analysis of spectroscopic data returned from Mars.Agencia Estatal de Investigación, grant (PID2022-142490OB-C32)Ministerio de Economía y Competitividad (MINECO),Grant/Award Number (RDE2018-102600-T

The Raman laser spectrometer ExoMars simulator (RLS Sim): A heavy‐duty Raman tool for ground testing on ExoMars

Producción CientíficaThe Raman laser spectrometer (RLS) instrument onboard the Rosalind Franklin rover of the ExoMars 2022 mission will analyze powdered samples on Mars to search for traces of life. To prepare for the mission, the RLS scientific team has developed the RLS ExoMars Simulator (RLS Sim), a flexible model of RLS that operates similarly to the actual instrument, both in laboratory and field conditions, while also emulating the rover operational constraints in terms of sample distribution that are relevant to the Raman analysis. This system can operate autonomously to perform RLS-representative analysis in one or several samples, making it very useful to perform heavy experimental tasks that would otherwise be impossible using a flight-representative model of the instrument. In this work, we introduce the current configuration of the RLS Sim that has incorporated new hardware elements such as the RAman Demonstrator 1 (RAD1) spectrometer with the objective of approaching its performance to that of the actual RLS instrument. To evaluate the scientific capability of the RLS Sim, we have compared it with a replica model of RLS, the RLS Flight Spare (FS). Several acquisition aspects have been evaluated based on the analysis of select samples, assessing the performance in terms of spectral range and resolution and also studying several issues related to the evolution of signal-to-noise ratio (SNR) with different acquisition parameters, especially the number of accumulations. This performance analysis has shown that the RLS Sim in its updated configuration will be a key model to perform support science for the ExoMars mission and the RLS instrument on the Rosalind Franklin rover. Designed to work intensively, the use of the RLS Sim in combination with the RLS FS will facilitate maximizing the scientific return of the RLS spectrometer during Martian operations.Secretaría de Estado de Investigación, Desarrollo e Innovación (grant PID2019-107442RBC31)European Union’s Horizon 2020 research and innovation program (grant 687302

Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN

An Empirical Comparative Assessment of Inter-Rater Agreement of Binary Outcomes and Multiple Raters

Background: Many methods under the umbrella of inter-rater agreement (IRA) have been proposed to evaluate how well two or more medical experts agree on a set of outcomes. The objective of this work was to assess key IRA statistics in the context of multiple raters with binary outcomes. Methods: We simulated the responses of several raters (2–5) with 20, 50, 300, and 500 observations. For each combination of raters and observations, we estimated the expected value and variance of four commonly used inter-rater agreement statistics (Fleiss’ Kappa, Light’s Kappa, Conger’s Kappa, and Gwet’s AC1). Results: In the case of equal outcome prevalence (symmetric), the estimated expected values of all four statistics were equal. In the asymmetric case, only the estimated expected values of the three Kappa statistics were equal. In the symmetric case, Fleiss’ Kappa yielded a higher estimated variance than the other three statistics. In the asymmetric case, Gwet’s AC1 yielded a lower estimated variance than the three Kappa statistics for each scenario. Conclusion: Since the population-level prevalence of a set of outcomes may not be known a priori, Gwet’s AC1 statistic should be favored over the three Kappa statistics. For meaningful direct comparisons between IRA measures, transformations between statistics should be conducted