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Abstract This study evaluates the impact of the COVID-19 pandemic on healthcare workers in Argentina, during the second wave in 2021. The aim is to assess stress and burnout, incorporating the assessment of hair cortisol levels as a biomarker of chronic stress. A total of 496 healthcare workers from three different hospitals were included in this study. Two of these hospitals depend on the Buenos Aires City Ministry of Health and the third hospital belongs to Buenos Aires University. Hair samples were obtained using scissors from the posterior vertex, as close to the scalp as possible. Each sample was weighed, and cortisol was extracted and then measured using an automated chemiluminescent method. Notably, 10% of the population exhibited hair cortisol levels above 128 pg/mg. Associations were found between high hair cortisol levels and age, workload, emotional exhaustion, and depersonalization. In addition, burnout, identified in 11% of participants, correlated with higher perceived stress and lower social support. Binary logistic regression revealed associations between burnout and perceived stress, and age. Finally, mediation analysis showed depersonalization as a mediating variable in the relationship between hair cortisol concentration and emotional exhaustion. In conclusion, this study highlights the complex relationships between stress, cortisol levels, and burnout. Prioritizing interventions and research is essential to support the well-being of frontline healthcare professionals, ensuring their resilience during challenging times.

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at $g-i\ge 0.60$ and $g-i< 0.60$, respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be $\log(M_{\rm host}/M_{\odot}) = 12.98 ^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at $\log(M_{\rm sub}/M_{\odot})

We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 < z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality z > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω _M = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration ( q _0 < 0 in ΛCDM) with over 5 σ confidence. We find $({{\rm{\Omega }}}_{{\rm{M}}},w)=({0.264}_{-0.096}^{+0.074},-{0.80}_{-0.16}^{+0.14})$ in flat w CDM. For flat w _0 w _a CDM, we find $({{\rm{\Omega }}}_{{\rm{M}}},{w}_{0},{w}_{a})=({0.495}_{-0.043}^{+0.033},-{0.36}_{-0.30}^{+0.36},-{8.8}_{-4.5}^{+3.7})$ , consistent with a constant equation of state to within ∼2 σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω _M , w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2 σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.

Alcoholic liver disease (ALD) is a clinical-pathologic entity caused by the chronic excessive consumption of alcohol. The disease includes a broad spectrum of anomalies at the cellular and tissual level that can cause acute-on-chronic (alcoholic hepatitis) or chronic (fibrosis, cirrhosis, hepatocellular cancer) injury, having a great impact on morbidity and mortality worldwide. Alcohol is metabolized mainly in the liver. During alcohol metabolism, toxic metabolites, such as acetaldehyde and oxygen reactive species, are produced. At the intestinal level, alcohol consumption can cause dysbiosis and alter intestinal permeability, promoting the translocation of bacterial products and causing the production of inflammatory cytokines in the liver, perpetuating local inflammation during the progression of ALD. Different study groups have reported systemic inflammatory response disturbances, but reports containing a compendium of the cytokines and cells involved in the pathophysiology of the disease, from the early stages, are difficult to find. In the present review article, the role of the inflammatory mediators involved in ALD progression are described, from risky patterns of alcohol consumption to advanced stages of the disease, with the aim of understanding the involvement of immune dysregulation in the pathophysiology of ALD. Resumen: La enfermedad hepática alcohólica (EHA) es una entidad clínico-patológica, ocasionada por el consumo excesivo y crónico de alcohol. La enfermedad incluye un amplio espectro de anomalías a nivel celular y tisular que pueden causar daño agudo sobre crónico (hepatitis alcohólica) o crónico (fibrosis, cirrosis, cáncer hepatocelular), teniendo un gran impacto en la morbilidad y mortalidad a nivel mundial. El alcohol es metabolizado principalmente en el hígado. Durante el metabolismo del alcohol son generados metabolitos tóxicos como el acetaldehído y las especies reactivas de oxígeno. A nivel intestinal, el consumo de alcohol puede producir disbiosis y alteración de la permeabilidad intestinal, promoviendo la translocación de productos bacterianos, y provocando la producción de citocinas proinflamatorias en el hígado, lo cual perpetua la inflamación local durante la evolución de la EHA. Diferentes grupos de estudio han reportado alteraciones de la respuesta inflamatoria a nivel sistémico, sin embargo, es difícil encontrar reportes que contengan un compendio de las células y citocinas involucradas en la fisiopatología de la enfermedad desde sus etapas tempranas. En este trabajo de revisión se describe el papel de los mediadores inflamatorios involucrados en la progresión de la EHA, desde los patrones de consumo de riesgo hasta etapas avanzadas de la enfermedad, con la finalidad de comprender la implicación de la desregulación inmunológica en la fisiopatología de esta enfermedad.

Resumen: La enfermedad hepática alcohólica (EHA) es una entidad clinicopatológica ocasionada por el consumo excesivo y crónico de alcohol. La enfermedad incluye un amplio espectro de anomalías celulares y tisulares que pueden causar daño agudo sobre crónico (hepatitis alcohólica) o crónico (fibrosis, cirrosis, cáncer hepatocelular), teniendo un gran impacto en la morbimortalidad en todo el mundo. El alcohol es metabolizado principalmente en el hígado. Durante el metabolismo del alcohol son generados metabolitos tóxicos como el acetaldehído y las especies reactivas de oxígeno. En el intestino el consumo de alcohol puede producir disbiosis y alteración de la permeabilidad intestinal, promoviendo la translocación de productos bacterianos y provocando la producción de citocinas proinflamatorias en el hígado, lo cual perpetúa la inflamación local durante la evolución de la EHA. Diferentes grupos de estudio han reportado alteraciones de la respuesta inflamatoria a nivel sistémico, sin embargo es difícil encontrar reportes que contengan un compendio de las células y citocinas involucradas en la fisiopatología de la enfermedad desde sus etapas tempranas. En este trabajo de revisión se describe el papel de los mediadores inflamatorios involucrados en la progresión de la EHA, desde los patrones de consumo de riesgo hasta etapas avanzadas de la enfermedad, con la finalidad de comprender la implicación de la desregulación inmunológica en la fisiopatología de esta enfermedad. Abstract: Alcoholic liver disease (ALD) is a clinical-pathologic entity caused by the chronic excessive consumption of alcohol. The disease includes a broad spectrum of anomalies at the cellular and tissual level that can cause acute-on-chronic (alcoholic hepatitis) or chronic (fibrosis, cirrhosis, hepatocellular cancer) injury, having a great impact on morbidity and mortality worldwide. Alcohol is metabolized mainly in the liver. During alcohol metabolism, toxic metabolites, such as acetaldehyde and oxygen reactive species, are produced. At the intestinal level, alcohol consumption can cause dysbiosis and alter intestinal permeability, promoting the translocation of bacterial products and causing the production of inflammatory cytokines in the liver, perpetuating local inflammation during the progression of ALD. Different study groups have reported systemic inflammatory response disturbances, but reports containing a compendium of the cytokines and cells involved in the pathophysiology of the disease, from the early stages, are difficult to find. In the present review article, the role of the inflammatory mediators involved in ALD progression are described, from risky patterns of alcohol consumption to advanced stages of the disease, with the aim of understanding the involvement of immune dysregulation in the pathophysiology of ALD.

We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$ with a mean value of $0.790^{+0.018}_{-0.014}$. The mean marginal is lower than the maximum a posteriori estimate, $S_8=0.801$, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with $S_8$ constraints from observations of the cosmic microwave background by Planck, with agreement at the $1.7\sigma$ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum. Supplementary information: you can download the chains here or create your own chains with CosmoSIS here.

We present the Ly α Continuum Analysis Network (LyCAN), a convolutional neural network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of 1040–1600 Å based on the red side of the Ly α emission line (1216–1600 Å). We developed synthetic spectra based on a Gaussian mixture model representation of nonnegative matrix factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift ( z < 0.2) Hubble Space Telescope/Cosmic Origins Spectrograph (COS) quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms principal component analysis (PCA) and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of 2.1 ≤ z ≤ 4.2 and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power law of the form $\tau {(z)={\tau }_{0}(1+z)}^{\gamma }$ to our measurements and find τ _0 = (2.46 ± 0.14) × 10 ^−3 and γ = 3.62 ± 0.04. Our results show particular agreement with high-resolution, ground-based observations around z = 2, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest.

Highly multiplexed, robotic, fiber-fed spectroscopic surveys are observing tens of millions of stars and galaxies. For many systems, accurate positioning relies on imaging the fibers in the focal plane and feeding that information back to the robotic positioners to correct their positions. Inhomogeneities and turbulence in the air between the focal plane and the imaging camera can affect the measured positions of fibers, limiting the accuracy with which fibers can be placed on targets. For the Dark Energy Spectroscopic Instrument, we dramatically reduced the effect of turbulence on measurements of positioner locations in the focal plane by taking advantage of stationary positioners and the correlation function of the turbulence. We were able to reduce positioning errors from 7.3 to 3.5 μ m, speeding the survey by 1.6% under typical conditions.

We present griz photometric light curves for the full 5 yr of the Dark Energy Survey Supernova (DES-SN) program, obtained with both forced point-spread function photometry on difference images ( DiffImg ) performed during survey operations, and scene modelling photometry (SMP) on search images processed after the survey. This release contains 31,636 DiffImg and 19,706 high-quality SMP light curves, the latter of which contain 1635 photometrically classified SNe that pass cosmology quality cuts. This sample spans the largest redshift ( z ) range ever covered by a single SN survey (0.1 < z < 1.13) and is the largest single sample from a single instrument of SNe ever used for cosmological constraints. We describe in detail the improvements made to obtain the final DES-SN photometry and provide a comparison to what was used in the 3 yr DES-SN spectroscopically confirmed Type Ia SN sample. We also include a comparative analysis of the performance of the SMP photometry with respect to the real-time DiffImg forced photometry and find that SMP photometry is more precise, more accurate, and less sensitive to the host-galaxy surface brightness anomaly. The public release of the light curves and ancillary data can be found at http://github.com/des-science/DES-SN5YR and doi:10.5281/zenodo.12720777.

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of principal component analysis–derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive data set derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by 10%–30%. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates (0.5%–0.8% higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false-positive redshift estimation by 5%−40% for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is nontrivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmological parameters from simulations modeled after the Dark Energy Survey 5 Yr (DES-SN5YR) photometric sample. For both DES-SN5YR data and simulations, we employ the directional light radius method for host galaxy matching. In our SN Ia simulations, we find that 1.7% of SNe are matched to the wrong host galaxy, with redshift differences between the true and matched hosts of up to 0.6. Using our analysis pipeline, we determine the shift in the dark energy equation of state parameter (Δ w ) due to including SNe with incorrect host galaxy matches. For SN Ia–only simulations, we find Δ w = 0.0013 ± 0.0026 with constraints from the cosmic microwave background. Including core-collapse SNe and peculiar SNe Ia in the simulation, we find that Δ w ranges from 0.0009 to 0.0032, depending on the photometric classifier used. This bias is an order of magnitude smaller than the expected total uncertainty on w from the DES-SN5YR sample of ∼0.03. We conclude that the bias on w from host galaxy mismatch is much smaller than the uncertainties expected from the DES-SN5YR sample, but we encourage further studies to reduce this bias through better host-matching algorithms or selection cuts.

We report results from a systematic wide-area search for faint dwarf galaxies at heliocentric distances from 0.3 to 2 Mpc using the full 6 yr of data from the Dark Energy Survey (DES). Unlike previous searches over the DES data, this search specifically targeted a field population of faint galaxies located beyond the Milky Way virial radius. We derive our detection efficiency for faint, resolved dwarf galaxies in the Local Volume with a set of synthetic galaxies and expect our search to be complete to M _V ∼ (−7, −10) mag for galaxies at D = (0.3, 2.0) Mpc. We find no new field dwarfs in the DES footprint, but we report the discovery of one high-significance candidate dwarf galaxy at a distance of ${2.2}_{-0.12}^{+0.05}\,\mathrm{Mpc}$ , a potential satellite of the Local Volume galaxy NGC 55, separated by 47′ (physical separation as small as 30 kpc). We estimate this dwarf galaxy to have an absolute V -band magnitude of $-{8.0}_{-0.3}^{+0.5}\,\mathrm{mag}$ and an azimuthally averaged physical half-light radius of ${2.2}_{-0.4}^{+0.5}\,\mathrm{kpc}$ , making this one of the lowest surface brightness galaxies ever found with $\mu =32.3\,\mathrm{mag}\,{\mathrm{arcsec}}^{-2}$ . This is the largest, most diffuse galaxy known at this luminosity, suggesting possible tidal interactions with its host.

We address the problem of optimally identifying all kilonovae detected via gravitational-wave emission in the upcoming LIGO/Virgo/KAGRA observing run, O4, which is expected to be sensitive to a factor of ∼7 more binary neutron star (BNS) alerts than previously. Electromagnetic follow-up of all but the brightest of these new events will require >1 m telescopes, for which limited time is available. We present an optimized observing strategy for the DECam during O4. We base our study on simulations of gravitational-wave events expected for O4 and wide-prior kilonova simulations. We derive the detectabilities of events for realistic observing conditions. We optimize our strategy for confirming a kilonova while minimizing telescope time. For a wide range of kilonova parameters, corresponding to a fainter kilonova compared to GW170817/AT 2017gfo, we find that, with this optimal strategy, the discovery probability for electromagnetic counterparts with the DECam is ∼80% at the nominal BNS gravitational-wave detection limit for O4 (190 Mpc), which corresponds to an ∼30% improvement compared to the strategy adopted during the previous observing run. For more distant events (∼330 Mpc), we reach an ∼60% probability of detection, a factor of ∼2 increase. For a brighter kilonova model dominated by the blue component that reproduces the observations of GW170817/AT 2017gfo, we find that we can reach ∼90% probability of detection out to 330 Mpc, representing an increase of ∼20%, while also reducing the total telescope time required to follow up events by ∼20%.

Introduction: We analysed the neurological complications of patients with severe SARS-CoV-2 infection who required intensive care unit (ICU) admission. Patients and methods: We conducted a retrospective, observational, descriptive study of consecutive patients admitted to the ICU due to severe respiratory symptoms secondary to SARS-CoV-2 infection between 1 April and 1 June 2020. Results: We included 30 patients with neurological symptoms; 21 were men (72.40%), and mean age (standard deviation [SD]) was 57.41 years (11.61). The mean duration of ICU stay was 18.83 days (14.33). The neurological conditions recorded were acute confusional syndrome in 28 patients (93.33%), neuromuscular disease in 15 (50%), headache in 5 (16.66%), cerebrovascular disease in 4 (13.33%), and encephalopathies/encephalitis in 4 (13.33%). CSF analysis results were normal in 6 patients (20%). Brain MRI or head CT showed alterations in 20 patients (66.6%). EEG was performed in all patients (100%), with 8 (26.66%) showing abnormal findings. In 5 of the 15 patients with clinical myopathy, diagnosis was confirmed with electroneuromyography. We found a correlation between older age and duration of ICU stay (P = 0.002; 95% CI, 4.032–6.022; OR). Conclusions: Severe COVID-19 mainly affects men, as observed in other series. Half of our patients presented acute myopathy, and almost all patients left the ICU with acute confusional syndrome, which fully resolved; no correlation was found with EEG or neuroimaging findings. Older age is associated with longer ICU stay. Resumen: Introducción: Nos proponemos analizar las complicaciones neurológicas de los pacientes con infección grave por SARS-CoV2, que han requerido ingreso en Unidad de Cuidados Intensivos (UCI). Pacientes y métodos: Estudio descriptivo retrospectivo, observacional, de pacientes consecutivos ingresado en UCI por infección respiratoria grave por SARS-CoV-2, desde el 1 de Abril hasta el 1 de Junio de 2020. Resultados: Registramos 30 pacientes con síntomas neurológicos, 21 hombres (72,40%), edad media: 57,41 años ± 11,61 desviación estándar (DE). Estancia media en UCI: 18,83 ± 14,33 DE. A nivel sindrómico: 28 pacientes (93,33%) con síndrome confusional agudo, 15 pacientes (50%) con patología neuromuscular, 5 (16,66%) cefalea, 4 (13,33%) con patología cerebrovascular, y 4 (13,33%) con encefalopatías/encefalitis. Punción lumbar normal en 6 pacientes (20%). La RMN craneal o TAC craneal mostró alteraciones en 20 casos (66,6%). Se realizó EEG en todos los pacientes (100%), alterado en 8 pacientes (26,66%). En 5 de los 15 pacientes con miopatía clínica se ha podido confirmar con ENMG. Hemos encontrado relación entre la mayor edad y los días de ingreso en UCI (P = 0,002, IC 95% 4,032-6,022; OR:). Conclusiones: La infección grave por COVID-19 afecta mayoritariamente a hombres, similar a lo descrito en otras series. La mitad de nuestros pacientes presentan una miopatía aguda, y casi la totalidad de los pacientes salen de la UCI con sindromes confusionales agudos, que evolucionan a la resolución completa, sin correlacionarse con los resultados del EEG o de pruebas de neuroimagen. La mayor edad sí se asocia con un mayor número de días de estancia en UCI.

Resumen: Introducción: Nos proponemos analizar las complicaciones neurológicas de los pacientes con infección grave por SARS-CoV-2 que han requerido ingreso en unidad de cuidados intensivos (UCI). Pacientes y métodos: Estudio descriptivo retrospectivo, observacional, de pacientes consecutivos ingresados en UCI por infección respiratoria grave por SARS-CoV-2 desde el 1 de abril hasta el 1 de junio de 2020. Resultados: Registramos 30 pacientes con síntomas neurológicos, 21 hombres (72,40%), edad media: 57,41 años ± 11,61 desviación estándar (DE). Estancia media en UCI: 18,83 ± 14,33 DE. A nivel sindrómico: 28 pacientes (93,33%) con síndrome confusional agudo, 15 (50%) con patología neuromuscular, 5 (16,66%) con cefalea, 4 (13,33%) con patología cerebrovascular y 4 (13,33%) con encefalopatías/encefalitis. Punción lumbar normal en 6 pacientes (20%). La RMN craneal o TAC craneal mostró alteraciones en 20 casos (66,6%). Se realizó EEG en todos los pacientes (100%), alterado en 8 pacientes (26,66%). En 5 de los 15 pacientes con miopatía clínica se ha podido confirmar con ENMG. Hemos encontrado relación entre la mayor edad y los días de ingreso en UCI (p = 0,002; IC 95%: 4,032-6,022; OR: 3,594). Conclusiones: La infección grave por COVID-19 afecta mayoritariamente a hombres, similar a lo descrito en otras series. La mitad de nuestros pacientes presenta una miopatía aguda, y casi la totalidad de los pacientes salen de la UCI con síndromes confusionales agudos que evolucionan a una resolución completa, sin correlacionarse con los resultados del EEG o de pruebas de neuroimagen. La mayor edad se asocia con un mayor número de días de estancia en UCI. Abstract: Introduction: We analysed the neurological complications of patients with severe SARS-CoV-2 infection who required intensive care unit (ICU) admission. Patients and methods: We conducted a retrospective, observational, descriptive study of consecutive patients admitted to the ICU due to severe respiratory symptoms secondary to SARS-CoV-2 infection between 1 April and 1 June 2020. Results: We included 30 patients with neurological symptoms; 21 were men (72.40%), and mean age (standard deviation [SD]) was 57.41 years (11.61). The mean duration of ICU stay was 18.83 days (14.33). The neurological conditions recorded were acute confusional syndrome in 28 patients (93.33%), neuromuscular disease in 15 (50%), headache in 5 (16.66%), cerebrovascular disease in 4 (13.33%), and encephalopathies/encephalitis in 4 (13.33%). CSF analysis results were normal in 6 patients (20%). Brain MRI or head CT showed alterations in 20 patients (66.6%). EEG was performed in all patients (100%), with 8 (26.66%) showing abnormal findings. In 5 of the 15 patients with clinical myopathy, diagnosis was confirmed with electroneuromyography. We found a correlation between older age and duration of ICU stay (P = .002; 95% CI: 4.032-6.022; OR: 3,594). Conclusions: Severe COVID-19 mainly affects men, as observed in other series. Half of our patients presented acute myopathy, and almost all patients left the ICU with acute confusional syndrome, which fully resolved; no correlation was found with EEG or neuroimaging findings. Older age is associated with longer ICU stay.

We perform a search for galaxy–galaxy strong lens systems using a convolutional neural network (CNN) applied to imaging data from the first public data release of the DECam Local Volume Exploration Survey, which contains ∼520 million astronomical sources covering ∼4000 deg ^2 of the southern sky to a 5 σ point–source depth of g = 24.3, r = 23.9, i = 23.3, and z = 22.8 mag. Following the methodology of similar searches using Dark Energy Camera data, we apply color and magnitude cuts to select a catalog of ∼11 million extended astronomical sources. After scoring with our CNN, the highest-scoring 50,000 images were visually inspected and assigned a score on a scale from 0 (not a lens) to 3 (very probable lens). We present a list of 581 strong lens candidates, 562 of which are previously unreported. We categorize our candidates using their human-assigned scores, resulting in 55 Grade A candidates, 149 Grade B candidates, and 377 Grade C candidates. We additionally highlight eight potential quadruply lensed quasars from this sample. Due to the location of our search footprint in the northern Galactic cap ( b > 10 deg) and southern celestial hemisphere (decl. < 0 deg), our candidate list has little overlap with other existing ground-based searches. Where our search footprint does overlap with other searches, we find a significant number of high-quality candidates that were previously unidentified, indicating a degree of orthogonality in our methodology. We report properties of our candidates including apparent magnitude and Einstein radius estimated from the image separation.

We combine photometry of Eris from a 6 month campaign on the Palomar 60 inch telescope in 2015, a 1 month Hubble Space Telescope WFC3 campaign in 2018, and Dark Energy Survey data spanning 2013–2018 to determine a light curve of definitive period 15.771 ± 0.008 days (1 σ formal uncertainties), with nearly sinusoidal shape and peak-to-peak flux variation of 3%. This is consistent at part-per-thousand precision with the P = 15.785 90 ± 0.00005 day sidereal period of Dysnomia’s orbit around Eris, strengthening the recent detection of synchronous rotation of Eris by Szakáts et al. with independent data. Photometry from Gaia are consistent with the same light curve. We detect a slope of 0.05 ± 0.01 mag per degree of Eris’s brightness with respect to illumination phase averaged across g , V , and r bands, intermediate between Pluto’s and Charon’s values. Variations of 0.3 mag are detected in Dysnomia’s brightness, plausibly consistent with a double-peaked light curve at the synchronous period. The synchronous rotation of Eris is consistent with simple tidal models initiated with a giant-impact origin of the binary, but is difficult to reconcile with gravitational capture of Dysnomia by Eris. The high albedo contrast between Eris and Dysnomia remains unexplained in the giant-impact scenario.

Wavelength-dependent atmospheric effects impact photometric supernova flux measurements for ground-based observations. We present corrections on supernova flux measurements from the Dark Energy Survey Supernova Program’s 5YR sample (DES-SN5YR) for differential chromatic refraction (DCR) and wavelength-dependent seeing, and we show their impact on the cosmological parameters w and Ω _m . We use g − i colors of Type Ia supernovae to quantify astrometric offsets caused by DCR and simulate point-spread functions (PSFs) using the GalSIM package to predict the shapes of the PSFs with DCR and wavelength-dependent seeing. We calculate the magnitude corrections and apply them to the magnitudes computed by the DES-SN5YR photometric pipeline. We find that for the DES-SN5YR analysis, not accounting for the astrometric offsets and changes in the PSF shape cause an average bias of +0.2 mmag and −0.3 mmag, respectively, with standard deviations of 0.7 mmag and 2.7 mmag across all DES observing bands ( griz ) throughout all redshifts. When the DCR and seeing effects are not accounted for, we find that w and Ω _m are lower by less than 0.004 ± 0.02 and 0.001 ± 0.01, respectively, with 0.02 and 0.01 being the 1 σ statistical uncertainties. Although we find that these biases do not limit the constraints of the DES-SN5YR sample, future surveys with much higher statistics, lower systematics, and especially those that observe in the u band will require these corrections as wavelength-dependent atmospheric effects are larger at shorter wavelengths. We also discuss limitations of our method and how they can be better accounted for in future surveys.

The ultra-faint dwarf galaxy Reticulum II (Ret II) exhibits a unique chemical evolution history, with ${72}_{-12}^{+10}$ % of its stars strongly enhanced in r -process elements. We present deep Hubble Space Telescope photometry of Ret II and analyze its star formation history. As in other ultra-faint dwarfs, the color–magnitude diagram is best fit by a model consisting of two bursts of star formation. If we assume that the bursts were instantaneous, then the older burst occurred around the epoch of reionization, forming ∼80% of the stars in the galaxy, while the remainder of the stars formed ∼3 Gyr later. When the bursts are allowed to have nonzero durations, we obtain slightly better fits. The best-fitting model in this case consists of two bursts beginning before reionization, with approximately half the stars formed in a short (100 Myr) burst and the other half in a more extended period lasting 2.6 Gyr. Considering the full set of viable star formation history models, we find that 28% of the stars formed within 500 ± 200 Myr of the onset of star formation. The combination of the star formation history and the prevalence of r -process-enhanced stars demonstrates that the r -process elements in Ret II must have been synthesized early in its initial star-forming phase. We therefore constrain the delay time between the formation of the first stars in Ret II and the r -process nucleosynthesis to be less than 500 Myr. This measurement rules out an r -process source with a delay time of several Gyr or more, such as GW170817.

Gravitationally lensed supernovae (LSNe) are important probes of cosmic expansion, but they remain rare and difficult to find. Current cosmic surveys likely contain 5–10 LSNe in total while next-generation experiments are expected to contain several hundred to a few thousand of these systems. We search for these systems in observed Dark Energy Survey (DES) five year SN fields—10 3 sq. deg. regions of sky imaged in the griz bands approximately every six nights over five years. To perform the search, we utilize the DeepZipper approach: a multi-branch deep learning architecture trained on image-level simulations of LSNe that simultaneously learns spatial and temporal relationships from time series of images. We find that our method obtains an LSN recall of 61.13% and a false-positive rate of 0.02% on the DES SN field data. DeepZipper selected 2245 candidates from a magnitude-limited ( m _i < 22.5) catalog of 3,459,186 systems. We employ human visual inspection to review systems selected by the network and find three candidate LSNe in the DES SN fields.

Introduction Psychosis are complex disorders due to their symptomatic and evolutionary heterogeneity. The genetic-environmental interaction model is the most accepted etiopathogenic model, in which neurobiological processes (genetic factors, connectivity and brain structure) and environmental factors (for example: childhood trauma) are studied. The association between suffering traumatic events in childhood and the subsequent development of a Mental Disorder is of increasing interest. Objectives Analyze if a childhood trauma is a modulating factor of psychotic symptoms in patients with Mental Disorder. Analyze the implication of childhood trauma in long-term functionality. Methods The sample is made up of 37 patients with psychosis and their healthy brothers. Different sociodemographic, clinical and evolutionary variables were collected in all groups. The sample was evaluated using the semi-structured interview CASH, the WHODAS scale and the self-applied questionnaire CTQ. Results We did not find significant differences between the scores of CTQ between patients with psychosis and their healthy brothers. Sexual abuse is significantly correlated with the presence of hallucinations, inappropriate affect, formal thought disorders and catatonic symptoms. Emotional neglect is significantly correlated with the presence of hallucinations, inappropriate affect, affective blunting, and anhedonia. Physical neglect is significantly correlated with flattery and blunt affection. Sexual abuse is correlated with poorer personal care. Emotional neglect is correlated with poorer personal care, poorer family functioning, and worse overall functioning in the last year. Conclusions The intensity of traumatic experiences throughout childhood could be considered a modulating factor of psychotic symptoms (positive, negative, disorganized and catatonic) and overall functioning (occupational, family, social and personal care).

The Dark Energy Spectroscopic Instrument (DESI) embarked on an ambitious 5 yr survey in 2021 May to explore the nature of dark energy with spectroscopic measurements of 40 million galaxies and quasars. DESI will determine precise redshifts and employ the baryon acoustic oscillation method to measure distances from the nearby universe to beyond redshift z > 3.5, and employ redshift space distortions to measure the growth of structure and probe potential modifications to general relativity. We describe the significant instrumentation we developed to conduct the DESI survey. This includes: a wide-field, 3.°2 diameter prime-focus corrector; a focal plane system with 5020 fiber positioners on the 0.812 m diameter, aspheric focal surface; 10 continuous, high-efficiency fiber cable bundles that connect the focal plane to the spectrographs; and 10 identical spectrographs. Each spectrograph employs a pair of dichroics to split the light into three channels that together record the light from 360–980 nm with a spectral resolution that ranges from 2000–5000. We describe the science requirements, their connection to the technical requirements, the management of the project, and interfaces between subsystems. DESI was installed at the 4 m Mayall Telescope at Kitt Peak National Observatory and has achieved all of its performance goals. Some performance highlights include an rms positioner accuracy of better than 0.″1 and a median signal-to-noise ratio of 7 of the [O ii ] doublet at 8 × 10 ^−17 erg s ^−1 cm ^−2 in 1000 s for galaxies at z = 1.4–1.6. We conclude with additional highlights from the on-sky validation and commissioning, key successes, and lessons learned.

We measure the top quark mass in dilepton final states of tt¯ events in pp¯ collisions at s=1.96 TeV, using data corresponding to an integrated luminosity of 9.7 fb−1 at the Fermilab Tevatron Collider. The analysis features a comprehensive optimization of the neutrino weighting method to minimize the statistical uncertainties. We also improve the calibration of jet energies using the calibration determined in tt¯→lepton+jets events, which reduces the otherwise limiting systematic uncertainty from the jet energy scale. The measured top quark mass is mt=173.32±1.36(stat)±0.85(syst) GeV.

We present a measurement of the cross sections for the associated production of a W boson with at least one heavy quark jet, b or c, in proton–antiproton collisions. Data corresponding to an integrated luminosity of 8.7 fb−1 recorded with the D0 detector at the Fermilab Tevatron pp¯ Collider at s=1.96 TeV are used to measure the cross sections differentially as a function of the jet transverse momenta in the range 20 to 150 GeV. These results are compared to calculations of perturbative QCD theory as well as predictions from Monte Carlo generators.

We present the first measurements of the differential cross section dσ/dpTγ for the production of an isolated photon in association with at least two b-quark jets. The measurements consider photons with rapidities |yγ|15 GeV and |yjet|

Objective: To evaluate the prevalence of and the associated factors for metabolic syndrome (MS) among Latin American HIV-infected patients receiving antiretroviral therapy (ART) using baseline data from the RAPID II study. Methods: A longitudinal study to evaluate the metabolic profile, cardiovascular disease (CVD) risk and associated treatment practices to reduce this risk has been conducted in seven Latin American countries (the RAPID II study). Adult HIV patients with at least six months of RT were enrolled. MS was defined following ATP-III criteria. Demographic and anthropometric data, serum biochemical and clinical parameters were compared in patients with and without MS using bivariate and multivariate analysis. Results: A total of 4,010 patients were enrolled, 2,963 (74%) were males. Mean age (SD) was 41.9 (10.0) years. The prevalence of MS was 20.2%. Females had higher prevalence of MS than males (22.7% vs. 19.4%, p = 0.02). MS was driven by high triglycerides, low HDL-cholesterol and high blood pressure (HBP). Patients with MS had higher 10- year CVD risk: 22.2% vs. 7.4%, p < 0.001. Age (OR: 1.05 per year), female gender (OR: 1.29), family history of CVD (OR: 1.28), CD4 cell count (OR: 1.09 per 100 cell increase), and protease inhibitor based-ART (OR: 1.33) correlated with MS in the multivariate analysis. Conclusions: Prevalence of MS in this setting was similar to that reported from developed countries. MS was driven by high triglycerides, low-HDL and HBP, and it was associated with higher risk of CVD. Traditional risk factors, female gender, immune reconstitution, and protease inhibitor based-ART correlated with MS. Keywords: metabolic syndrome (MS), HIV, ART, Latin America

En el presente estudio se resume e interpreta la información disponible de niveles del mar para el Golfo de California. Las series de marea de 33 localidades del Golfo se analizaron mediante los métodos de análisis armónico y de admitancia. Los resultados se presentan bajo la forma de mapas cotidales para las principales componentes semidiurnas, diurnas y de período largo. doi: https://doi.org/10.22201/igeof.00167169p.1989.28.1.1015