Artificial Intelligence for the Advancement of Lunar and Planetary Science and Exploration

AI-driven methods have potential to minimise manual labour during planetary data processing and aid ongoing missions with real-time data analysis. This white paper focuses on key areas of AI-driven research, the need for open source training data, and the importance of collaboration between academia and industries to advance AI-driven research

Dynamics of Adrenal Steroids Are Related to Variations in Th1 and Treg Populations during Mycobacterium tuberculosis Infection in HIV Positive Persons

Tuberculosis (TB) remains the most frequent cause of illness and death from an infectious agent, and its interaction with HIV has devastating effects. We determined plasma levels of dehydroepiandrosterone (DHEA), its circulating form DHEA-suphate (DHEA-s) and cortisol in different stages of M. tuberculosis infection, and explored their role on the Th1 and Treg populations during different scenarios of HIV-TB coinfection, including the immune reconstitution inflammatory syndrome (IRIS), a condition related to antiretroviral treatment. DHEA levels were diminished in HIV-TB and HIV-TB IRIS patients compared to healthy donors (HD), HIV+ individuals and HIV+ individuals with latent TB (HIV-LTB), whereas dehydroepiandrosterone sulfate (DHEA-s) levels were markedly diminished in HIV-TB IRIS individuals. HIV-TB and IRIS patients presented a cortisol/DHEA ratio significantly higher than HIV+, HIV-LTB and HD individuals. A positive correlation was observed between DHEA-s and CD4 count among HIV-TB individuals. Conversely, cortisol plasma level inversely correlated with CD4 count within HIV-TB individuals. M. tuberculosis-specific Th1 lymphocyte count was increased after culturing PBMC from HIV-TB individuals in presence of DHEA. We observed an inverse correlation between DHEA-s plasma level and Treg frequency in co-infected individuals, and CD4+FoxP3+ Treg frequency was increased in HIV-TB and IRIS patients compared to other groups. Strikingly, we observed a prominent CD4+CD25-FoxP3+ population across HIV-TB and HIV-TB IRIS patients, which frequency correlated with DHEA plasma level. Finally, DHEA treatment negatively regulated FoxP3 expression without altering Treg frequency in co-infected patients. These data suggest an enhancing role for DHEA in the immune response against M. tuberculosis during HIV-TB coinfection and IRIS

Optimisation of Perioperative Cardiovascular Management to Improve Surgical Outcome II (OPTIMISE II) trial: study protocol for a multicentre international trial of cardiac output-guided fluid therapy with low-dose inotrope infusion compared with usual care in patients undergoing major elective gastrointestinal surgery.

INTRODUCTION: Postoperative morbidity and mortality in older patients with comorbidities undergoing gastrointestinal surgery are a major burden on healthcare systems. Infections after surgery are common in such patients, prolonging hospitalisation and reducing postoperative short-term and long-term survival. Optimal management of perioperative intravenous fluids and inotropic drugs may reduce infection rates and improve outcomes from surgery. Previous small trials of cardiac-output-guided haemodynamic therapy algorithms suggested a modest reduction in postoperative morbidity. A large definitive trial is needed to confirm or refute this and inform widespread clinical practice. METHODS: The Optimisation of Perioperative Cardiovascular Management to Improve Surgical Outcome II (OPTIMISE II) trial is a multicentre, international, parallel group, open, randomised controlled trial. 2502 high-risk patients undergoing major elective gastrointestinal surgery will be randomly allocated in a 1:1 ratio using minimisation to minimally invasive cardiac output monitoring to guide protocolised administration of intravenous fluid combined with low-dose inotrope infusion, or usual care. The trial intervention will be carried out during and for 4 hours after surgery. The primary outcome is postoperative infection of Clavien-Dindo grade II or higher within 30 days of randomisation. Participants and those delivering the intervention will not be blinded to treatment allocation; however, outcome assessors will be blinded when feasible. Participant recruitment started in January 2017 and is scheduled to last 3 years, within 50 hospitals worldwide. ETHICS/DISSEMINATION: The OPTIMISE II trial has been approved by the UK National Research Ethics Service and has been approved by responsible ethics committees in all participating countries. The findings will be disseminated through publication in a widely accessible peer-reviewed scientific journal. TRIAL REGISTRATION NUMBER: ISRCTN39653756.The OPTIMISE II trial is supported by Edwards Lifesciences (Irvine, CA) and the UK National Institute for Health Research through RMP’s NIHR Professorship

Editorial: Wildfire severity and forest soils: impacts and post-fire restoration strategies to mitigate climate change

3 páginas.- 10 referenciasEditorial on the Research Topic Wildfire severity and forest soils: impacts and post-fire restoration strategies to mitigate climate change Impacts of fire on forest soils have been widely studied in the last decades. Early studies compared burned and unburned areas, revealing that soil properties and dynamics are significantly affected by fire. Moreover, the advancements in soil and fire sciences revealed the importance of considering the variety of fire characteristics, ecosystem types and environmental pre- and post-fire conditions when studying fire effects on soils (Certini, 2005; Pereira et al., 2018; Fernández-García et al., 2020). Previous research has shown that the temperature reached in the soil and the residence time are critical factors that determine the effects of fire on soil properties. Biological and biochemical properties are generally altered at low temperatures (Fernández-García et al., 2020), while moderate temperatures cause shifts in soil organic matter and several nutrients (Marcos et al., 2007). High temperatures, on the other hand, can impact other chemical properties as well as ecologically relevant physical properties, such as soil structure and mineralogy (Santín and Doerr, 2016; Alcañiz et al., 2018; Fernández-García et al., 2019).VF-G was supported by a Margarita Salas fellowship from the Ministry of Universities of Spain, financed by European Union Next-Generation EU funds and granted by the University of León to conduct his postdoctoral research at the University of Lausanne. NJ-M was supported by a Ramón y Cajal contract (ref. RYC2021-031253-I) funded by MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTRPeer reviewe

A nearest neighbour approach to the simulation of spread of barley yellow dwarf virus

The spread of insect vectored plant virus diseases such as barley yellow dwarf virus has traditionally been depicted as disease progress curves which represent an integration of the interactions between virus, host plant and vector. In this paper, virus spread is described by the probability of a plant becoming infected conditioned on the number of infected plants neighbouring it. This has the advantage that the influence of aphid movement can be incorporated into the definition of the probability of a neighbour becoming infected. Data were collected from an experimental field of barley (cv. Alexis) sown at a row spacing of 12 cm on 29 March 1993 at Rothamsted Experimental Station. Twelve plots, each approximately 84×70 cm were divided into a 7×7 grid of cells. The plots were arranged in four blocks, each with two treatments T1) and an untreated control. The probabilities of a plant, or rather a cell which is a group of plants, becoming infected conditioned on the number of its infected neighbours was estimated from this experiment considering various neighbourhoods. These probability estimates were then used to develop visual interactive simulation models of spread on a 51×51 grid of cells. In all simulation models, the central cell was set as infected at the start of the simulation to match the experimental design for treatments T1 and T2. The simulations were run for a 15-week period, replicated 50 times, and the resulting infection counts were averaged. These simulations were used to estimate the rate of spread of BYDV and to perform a range of sensitivity analyses

A Geostatistical Approach to Map Near-Surface Soil Moisture through Hyperspatial Resolution Thermal Inertia

Thermal inertia has been applied to map soil water content exploiting remote sensing data in the short and long wave regions of the electromagnetic spectrum. Over the last years, optical and thermal cameras were sufficiently miniaturized to be loaded onboard of unmanned aerial systems (UASs), which provide unprecedented potentials to derive hyperspatial resolution thermal inertia for soil water content mapping. In this study, we apply a simplification of thermal inertia, the apparent thermal inertia (ATI), over pixels where underlying thermal inertia hypotheses are fulfilled (unshaded bare soil). Then, a kriging algorithm is used to spatialize the ATI to get a soil water content map. The proposed method was applied to an experimental area of the Alento River catchment, in southern Italy. Daytime radiometric optical multispectral and day and nighttime radiometric thermal images were acquired via a UAS, while $in ,,situ$ soil water content was measured through the thermo-gravimetric and time domain reflectometry (TDR) methods. The determination coefficient between ATI and soil water content measured over unshaded bare soil was 0.67 for the gravimetric method and 0.73 for the TDR. After interpolation, the correlation slightly decreased due to the introduction of measurements on vegetated or shadowed positions ( $r^{2} = 0.59$ for gravimetric method; $r^{2} = 0.65$ for TDR). The proposed method shows promising results to map the soil water content even over vegetated or shadowed areas by exploiting hyperspatial resolution data and geostatistical analysis