SARS-CoV-2 infection induces a dual response in liver function tests: Association with mortality during hospitalization

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with abnormal liver function tests. We hypothesized that early altered liver biochemistries at admission might have different clinical relevance than subsequent changes during hospitalization. A single-center retrospective study was conducted on 540 consecutive hospitalized patients, PCR-diagnosed with SARS-CoV-2. Liver test abnormalities were defined as the elevation of either gamma-glutamyltransferase (GGT), alanine aminotransferase (ALT), or aspartate aminotransferase (AST), above the upper limit of normality set by our laboratory. Linear mixed models (LMM) evaluated longitudinal associations, incorporating all available follow-up laboratory chemistries. By the end of the follow-up period, 502 patients (94.5%) were discharged (109 (20.5%) died). A total of 319 (64.3%) had at least one abnormal liver test result at admission. More prevalent were elevated AST (40.9%) and GGT (47.3%). Abnormalities were not associated with survival but with respiratory complications at admission. Conversely, LMM models adjusted for age and sex showed that longitudinal increases during hospitalization in ferritin, GGT, and alkaline phosphatase (ALP), as well as a decreased albumin levels, were associated with reduced survival. This dual pattern of liver damage might reconcile previous conflicting reports. GGT and ALP trajectories could be useful to determine who might need more surveillance and intensive care

Long term measurement of the 222Rn concentration in the Canfranc Underground Laboratory

We report the results of 6 years (2013–2018) of measurements of 222Rn air concentration, relative humidity, atmospheric pressure and temperature in the halls A, B and C of the Canfranc Underground Laboratory (LSC). We have calculated all the Pearson correlation coefficients among these parameters and we have found a positive correlation between the 222Rn concentration and the relative humidity. Both correlated variables show a seasonal periodicity. The joint analysis of laboratory data and 4 years (2015– 2018) of the meteorological variables outside the laboratory shows the correlation between the 222Rn concentration and the outside temperature. The collected information stresses the relevance of designing good Rn-mitigation strategies in current and future experiments at LSC; in particular, we have checked for two years (2017–2018) the good performance of the mitigation procedure of the ANAIS-112 experiment. Finally, we have monitored (2019–2021) for 2 years of live time, the radon-free air provided by the radon abatement system installed in the laboratory.This research was funded by MCIN/AEI/10.13039/501100011033 under Grant PID2019-104374GB-I00; by MINECO-FEDER under Grants FPA2017-83133-P, and FPA2014-55986-P; by MICINN-FEDER under Grants FPA2011-23749; by CONSOLIDER-Ingenio 2010 Programme under Grants MultiDark CSD2009-00064 and CPAN CSD2007-00042; by the University of Zaragoza under Grant UZ2017-CIE-09; by the Spanish Meteorological Agency (AEMET), the Gobierno de Aragón (Group in Nuclear and Astroparticle Physics, ARAID Foundation and I. Coarasa predoctoral grant), the European Social Fund and by the LSC consortium

Diet quality index as a predictor of treatment efficacy in overweight and obese adolescents: The EVASYON study

Background & aim: A diet quality index (DQI) is a tool that provides an overall score of an individual''s dietary intake when assessing compliance with food-based dietary guidelines. A number of DQIs have emerged, albeit their associations with health-related outcomes are debated. The aim of the present study was to assess whether adherence to dietary intervention, and the overall quality of the diet, can predict body composition changes. Methods: To this purpose, overweight/obese adolescents (n = 117, aged: 13–16 years; 51 males, 66 females) were recruited into a multi-component (diet, physical activity and psychological support) family-based group treatment programme. We measured the adolescents’ compliance and body composition at baseline and after 2 months (intensive phase) and 13 months (extensive phase) of follow-up. Also, at baseline, after 6 months, and at the end of follow-up we calculated the DQI. Results: Global compliance with the dietary intervention was 37.4% during the intensive phase, and 14.3% during the extensive phase. Physical activity compliance was 94.1% at 2-months and 34.7% at 13months and psychological support compliance were growing over the intervention period (10.3% intensive phase and 45.3% during extensive phase). Adolescents complying with the meal frequency criteria at the end of the extensive phase had greater reductions in FMI z-scores than those did not complying (Cohen''s d = 0.53). A statistically significant association was observed with the diet quality index. DQI-A variation explained 98.1% of BMI z-score changes and 95.1% of FMI changes. Conclusions: We conclude that assessment of changes in diet quality could be a useful tool in predicting body composition changes in obese adolescents involved in a diet and physical activity intervention programme backed-up by psychological and family support

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Global urban environmental change drives adaptation in white clover.

Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale

Global urban environmental change drives adaptation in white clover

Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale

COALAS

We report a detailed CO(1−0) survey of a galaxy protocluster field at z = 2.16, based on 475 h of observations with the Australia Telescope Compact Array. We constructed a large mosaic of 13 individual pointings, covering an area of 21 arcmin2 and ±6500 km s−1 range in velocity. We obtained a robust sample of 46 CO(1−0) detections spanning z = 2.09 − 2.22, constituting the largest sample of molecular gas measurements in protoclusters to date. The CO emitters show an overdensity at z = 2.12 − 2.21, suggesting a galaxy super-protocluster or a protocluster connected to large-scale filaments of ∼120 cMpc in size. We find that 90% of CO emitters have distances ${ > }0{{\overset{\prime}{.}}}5{-}4{\prime}$ to the center galaxy, indicating that small area surveys would miss the majority of gas reservoirs in similar structures. Half of the CO emitters have velocities larger than escape velocities, which appears gravitationally unbound to the cluster core. These unbound sources are barely found within the R200 radius around the center, which is consistent with a picture in which the cluster core is collapsed while outer regions are still in formation. Compared to other protoclusters, this structure contains a relatively higher number of CO emitters with relatively narrow line widths and high luminosities, indicating galaxy mergers. We used these CO emitters to place the first constraint on the CO luminosity function and molecular gas density in an overdense environment. The amplitude of the CO luminosity function is 1.6 ± 0.5 orders of magnitude higher than that observed for field galaxy samples at z ∼ 2, and one order of magnitude higher than predictions for galaxy protoclusters from semi-analytical SHARK models. We derive a high molecular gas density of 0.6 − 1.3 × 109 M⊙ cMpc−3 for this structure, which is consistent with predictions for cold gas density of massive structures from hydro-dynamical DIANOGA simulations