Can Phlorotannins Purified Extracts Constitute a Novel Pharmacological Alternative for Microbial Infections with Associated Inflammatory Conditions?

Bacterial and fungal infections and the emerging multidrug resistance are driving interest in fighting these microorganisms with natural products, which have generally been considered complementary to pharmacological therapies. Phlorotannins are polyphenols restricted to brown seaweeds, recognized for their biological capacity. This study represents the first research on the antibacterial, antifungal, anti-inflammatory and antioxidant activity of phlorotannins purified extracts, which were obtained from ten dominant brown seaweeds of the occidental Portuguese coast

A composite transcriptional signature differentiates responses towards closely related herbicides in Arabidopsis thaliana and Brassica napus

In this study, genome-wide expression profiling based on Affymetrix ATH1 arrays was used to identify discriminating responses of Arabidopsis thaliana to five herbicides, which contain active ingredients targeting two different branches of amino acid biosynthesis. One herbicide contained glyphosate, which targets 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS), while the other four herbicides contain different acetolactate synthase (ALS) inhibiting compounds. In contrast to the herbicide containing glyphosate, which affected only a few transcripts, many effects of the ALS inhibiting herbicides were revealed based on transcriptional changes related to ribosome biogenesis and translation, secondary metabolism, cell wall modification and growth. The expression pattern of a set of 101 genes provided a specific, composite signature that was distinct from other major stress responses and differentiated among herbicides targeting the same enzyme (ALS) or containing the same chemical class of active ingredient (sulfonylurea). A set of homologous genes could be identified in Brassica napus that exhibited a similar expression pattern and correctly distinguished exposure to the five herbicides. Our results show the ability of a limited number of genes to classify and differentiate responses to closely related herbicides in A. thaliana and B. napus and the transferability of a complex transcriptional signature across species

Exploring deep microbial life in coal-bearing sediment down to ~2.5 km below the ocean floor

Peer reviewedPostprin

Event-by-event reconstruction of the shower maximum Xmax with the Surface Detector of the Pierre Auger Observatory using deep learning

The measurement of the mass composition of ultra-high energy cosmic rays constitutes a prime challenge in astroparticle physics. Most detailed information on the composition can be obtained from measurements of the depth of maximum of air showers, Xmax, with the use of fluorescence telescopes, which can be operated only during clear and moonless nights. Using deep neural networks, it is now possible for the first time to perform an event-by-event reconstruction of Xmax with the Surface Detector (SD) of the Pierre Auger Observatory. Therefore, previously recorded data can be analyzed for information on Xmax, and thus, the cosmic-ray composition. Since the SD operates with a duty cycle of almost 100% and its event selection is less strict than for the Fluorescence Detector (FD), the gain in statistics with respect to the FD is almost a factor of 15 for energies above 1019.5 eV. In this contribution, we introduce the neural network particularly designed for the SD of the Pierre Auger Observatory. We evaluate its performance using three different hadronic interaction models, verify its functionality using Auger hybrid measurements, and find that the method can extract mass information on an event level

The depth of the shower maximum of air showers measured with AERA

The Auger Engineering Radio Array (AERA) is currently the largest array of radio antennas for the detection of cosmic rays, spanning an area of 17 km2 with 153 radio antennas, measuring in the energy range from 1017.0 to 1019.0 eV. It detects the radio emission of extensive air showers produced by cosmic rays in the 30 − 80 MHz band. The cosmic-ray mass composition is a crucial piece of information in determining the sources of cosmic rays and their acceleration mechanisms. The depth of the shower maximum, Xmax, a probe for mass composition can be determined with a likelihood analysis that compares the measured radio-emission footprint on the ground to an ensemble of footprints from CORSIKA/CoREAS Monte-Carlo air shower simulations. These simulations are also used to determine the resolution of the method and to validate the reconstruction by identifying and correcting for systematic uncertainties. We will present the method for the reconstruction of the depth of the shower maximum, achieving a resolution of up to 15 g/cm2, show compatibility with the independent fluorescence detector reconstruction measured on an event-by-event basis, and show that the data taken over the past seven years with AERA shows a light cosmic-ray mass composition reconstruction in the energy range from 1017.5 to 1018.8 eV

The Pierre Auger Observatory Open Data

The Pierre Auger Collaboration has embraced the concept of open access to their research data since its foundation, with the aim of giving access to the widest possible community. A gradual process of release began as early as 2007 when 1% of the cosmic-ray data was made public, along with 100% of the space-weather information. In February 2021, a portal was released containing 10% of cosmic-ray data collected from 2004 to 2018, during Phase I of the Observatory. The Portal included detailed documentation about the detection and reconstruction procedures, analysis codes that can be easily used and modified and, additionally, visualization tools. Since then the Portal has been updated and extended. In 2023, a catalog of the 100 highest-energy cosmic-ray events examined in depth has been included. A specific section dedicated to educational use has been developed with the expectation that these data will be explored by a wide and diverse community including professional and citizen-scientists, and used for educational and outreach initiatives. This paper describes the context, the spirit and the technical implementation of the release of data by the largest cosmic-ray detector ever built, and anticipates its future developments.Comment: 19 pages, 8 figure

Radio Measurements of the Depth of Air-Shower Maximum at the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA), part of the Pierre Auger Observatory, is currently the largest array of radio antenna stations deployed for the detection of cosmic rays, spanning an area of $17$ km$^2$ with 153 radio stations. It detects the radio emission of extensive air showers produced by cosmic rays in the $30-80$ MHz band. Here, we report the AERA measurements of the depth of the shower maximum ($X_\text{max}$), a probe for mass composition, at cosmic-ray energies between $10^{17.5}$ to $10^{18.8}$ eV, which show agreement with earlier measurements with the fluorescence technique at the Pierre Auger Observatory. We show advancements in the method for radio $X_\text{max}$ reconstruction by comparison to dedicated sets of CORSIKA/CoREAS air-shower simulations, including steps of reconstruction-bias identification and correction, which is of particular importance for irregular or sparse radio arrays. Using the largest set of radio air-shower measurements to date, we show the radio $X_\text{max}$ resolution as a function of energy, reaching a resolution better than $15$ g cm$^{-2}$ at the highest energies, demonstrating that radio $X_\text{max}$ measurements are competitive with the established high-precision fluorescence technique. In addition, we developed a procedure for performing an extensive data-driven study of systematic uncertainties, including the effects of acceptance bias, reconstruction bias, and the investigation of possible residual biases. These results have been cross-checked with air showers measured independently with both the radio and fluorescence techniques, a setup unique to the Pierre Auger Observatory.Comment: Submitted to Phys. Rev.

Ground observations of a space laser for the assessment of its in-orbit performance

The wind mission Aeolus of the European Space Agency was a groundbreaking achievement for Earth observation. Between 2018 and 2023, the space-borne lidar instrument ALADIN onboard the Aeolus satellite measured atmospheric wind profiles with global coverage which contributed to improving the accuracy of numerical weather prediction. The precision of the wind observations, however, declined over the course of the mission due to a progressive loss of the atmospheric backscatter signal. The analysis of the root cause was supported by the Pierre Auger Observatory in Argentina whose fluorescence detector registered the ultraviolet laser pulses emitted from the instrument in space, thereby offering an estimation of the laser energy at the exit of the instrument for several days in 2019, 2020 and 2021. The reconstruction of the laser beam not only allowed for an independent assessment of the Aeolus performance, but also helped to improve the accuracy in the determination of the laser beam's ground track on single pulse level. The results presented in this paper set a precedent for the monitoring of space lasers by ground-based telescopes and open new possibilities for the calibration of cosmic-ray observatories.Comment: 10 pages, 10 figure

Deep-learning based reconstruction of the shower maximum Xmax using the water-Cherenkov detectors of the Pierre Auger Observatory

The atmospheric depth of the air shower maximum Xmax is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of Xmax are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of Xmax from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of Xmax. The reconstruction relies on the signals induced by shower particles in the ground based water-Cherenkov detectors of the Pierre Auger Observatory. The network architecture features recurrent long short-term memory layers to process the temporal structure of signals and hexagonal convolutions to exploit the symmetry of the surface detector array. We evaluate the performance of the network using air showers simulated with three different hadronic interaction models. Thereafter, we account for long-term detector effects and calibrate the reconstructed Xmax using fluorescence measurements. Finally, we show that the event-by-event resolution in the reconstruction of the shower maximum improves with increasing shower energy and reaches less than 25 g/cm2 at energies above 2×1019 eV