An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides. Part 2: impacts on organisms and ecosystems

New information on the lethal and sublethal effects of neonicotinoids and fipronil on organisms is presented in this review, complementing the previous WIA in 2015. The high toxicity of these systemic insecticides to invertebrates has been confirmed and expanded to include more species and compounds. Most of the recent research has focused on bees and the sublethal and ecological impacts these insecticides have on pollinators. Toxic effects on other invertebrate taxa also covered predatory and parasitoid natural enemies and aquatic arthropods. Little, while not much new information has been gathered on soil organisms. The impact on marine coastal ecosystems is still largely uncharted. The chronic lethality of neonicotinoids to insects and crustaceans, and the strengthened evidence that these chemicals also impair the immune system and reproduction, highlights the dangers of this particular insecticidal classneonicotinoids and fipronil. , withContinued large scale – mostly prophylactic – use of these persistent organochlorine pesticides has the potential to greatly decreasecompletely eliminate populations of arthropods in both terrestrial and aquatic environments. Sublethal effects on fish, reptiles, frogs, birds and mammals are also reported, showing a better understanding of the mechanisms of toxicity of these insecticides in vertebrates, and their deleterious impacts on growth, reproduction and neurobehaviour of most of the species tested. This review concludes with a summary of impacts on the ecosystem services and functioning, particularly on pollination, soil biota and aquatic invertebrate communities, thus reinforcing the previous WIA conclusions (van der Sluijs et al. 2015)

Gender-related differences in physiologic color space: a functional transcranial Doppler (fTCD) study

Simultaneous color contrast and color constancy are memory processes associated with color vision, however, the gender-related differences of 'physiologic color space' remains unknown. Color processing was studied in 16 (8 men and 8 women) right-handed healthy subjects using functional transcranial Doppler (fTCD) technique. Mean flow velocity (MFV) was recorded in both right (RMCA) and left (LMCA) middle cerebral arteries in dark and white light conditions, and during color (blue and yellow) stimulations. The data was plotted in a 3D quadratic curve fit to derive a 'physiologic color space' showing the effects of luminance and chromatic contrasts. In men, wavelength-differencing of opponent pairs (yellow-blue) was adjudged by changes in the RMCA MFV for Yellow plotted on the Y-axis, and the RMCA MFV for Blue plotted on the X-axis. In women, frequency-differencing for opponent pairs (blue-yellow) was adjudged by changes in the LMCA MFV for Yellow plotted on the Y-axis, and the LMCA MFV for Blue plotted on the X-axis. The luminance effect on the LMCA MFV in response to white light with the highest luminous flux, was plotted on the (Z - axis), in both men and women. The 3D-color space for women was a mirror-image of that for men, and showed enhanced color constancy. The exponential function model was applied to the data in men, while the logarithmic function model was applied to the data in women. Color space determination may be useful in the study of color memory, adaptive neuroplasticity, cognitive impairment in stroke and neurodegenerative diseases

Euclid preparation: LXVIII. Extracting physical parameters from galaxies with machine learning

\ua9 The Authors 2025.The Euclid mission is generating a vast amount of imaging data in four broadband filters at a high angular resolution. This data will allow for the detailed study of mass, metallicity, and stellar populations across galaxies that will constrain their formation and evolutionary pathways. Transforming the Euclid imaging for large samples of galaxies into maps of physical parameters in an efficient and reliable manner is an outstanding challenge. Here, we investigate the power and reliability of machine learning techniques to extract the distribution of physical parameters within well-resolved galaxies. We focus on estimating stellar mass surface density, mass-averaged stellar metallicity, and age. We generated noise-free synthetic high-resolution (100 pc 7 100 pc) imaging data in the Euclid photometric bands for a set of 1154 galaxies from the TNG50 cosmological simulation. The images were generated with the SKIRT radiative transfer code, taking into account the complex 3D distribution of stellar populations and interstellar dust attenuation. We used a machine learning framework to map the idealised mock observational data to the physical parameters on a pixel-by-pixel basis. We find that stellar mass surface density can be accurately recovered with a ≤0.130 dex scatter. Conversely, stellar metallicity and age estimates are, as expected, less robust, but they still contain significant information that originates from underlying correlations at a sub-kiloparsec scales between stellar mass surface density and stellar population properties. As a corollary, we show that TNG50 follows a spatially resolved mass-metallicity relation that is consistent with observations. Due to its relatively low computational and time requirements, which has a time-frame of minutes without dedicated high performance computing infrastructure once it has been trained, our method allows for fast and robust estimates of the stellar mass surface density distributions of nearby galaxies from four-filter Euclid imaging data. Equivalent estimates of stellar population properties (stellar metallicity and age) are less robust but still hold value as first-order approximations across large samples

Euclid: Early Release Observations of ram-pressure stripping in the Perseus cluster: Detection of parsec-scale star formation within the low surface brightness stripped tails of UGC 2665 and MCG +07-07-070

\ua9 2025 EDP Sciences. All rights reserved.Euclid is delivering optical and near-infrared imaging data over 14 000 deg2 on the sky at spatial resolution and surface brightness levels that can be used to understand the morphological transformation of galaxies within groups and clusters. Using the Early Release Observations (ERO) of the Perseus cluster, we demonstrate the capability offered by Euclid in studying the nature of perturbations for galaxies in clusters. Filamentary structures are observed along the discs of two spiral galaxies, UGC 2665 and MCG +07-07-070, with no extended diffuse emission expected from tidal interactions at surface brightness levels of a30 mag arcseca 2. The detected features exhibit a good correspondence in morphology between optical and near-infrared wavelengths, with a surface brightness of a25 mag arcseca 2, and the knots within the features have sizes of a 100 pc, as observed through IE imaging. Using the Euclid, CFHT, UVIT, and LOFAR 144 MHz radio continuum observations, we conducted a detailed analysis to understand the origin of the detected features. We constructed the Euclid IEaYE, YEaHE, and CFHT u ar, g ai colour-colour plane and show that these features contain recent star formation events, which are also indicated by their Hα and NUV emissions. Euclid colours alone are insufficient for studying stellar population ages in unresolved star-forming regions, which require multi-wavelength optical imaging data. There are features with red colours that can be explained by dust being stripped along with the gas in these regions. The morphological shape, orientation, and mean age of the stellar population, combined with the presence of extended radio continuum cometary tails can be consistently explained if these features formed during a recent ram-pressure stripping event. This result further confirms the exceptional qualities of Euclid in the study of galaxy evolution in dense environments

<em>Euclid </em>preparation LXXIII. Spatially resolved stellar populations of local galaxies with <em>Euclid</em>: A proof of concept using synthetic images with the TNG50 simulation

\ua9 The Authors 2025.The European Space Agency’s Euclid mission will observe approximately 14 000 deg2 of the extragalactic sky and deliver high-quality imaging of a large number of galaxies. The depth and high spatial resolution of the data will enable a detailed analysis of the stellar population properties of local galaxies through spatially resolved spectral energy distribution (SED) fitting. In this study, we test our pipeline for spatially resolved SED fitting using synthetic images of Euclid, LSST, and GALEX generated from the TNG50 simulation using the SKIRT 3D radiative transfer code. Our pipeline uses functionalities in piXedfit for processing the simulated data cubes and carrying out SED fitting. We apply our pipeline to 25 simulated galaxies at z ∼ 0 to recover their resolved stellar population properties. For each galaxy, we produce three types of data cubes: GALEX + LSST + Euclid, LSST + Euclid, and Euclid-only. We performed the SED fitting tests with two stellar population synthesis (SPS) models in a Bayesian framework. Because the age, metallicity (Z), and dust attenuation estimates are biased when applying only classical formulations of flat priors (even with the combined GALEX + LSST + Euclid data), we examined the effects of additional physically motivated priors in the forms of mass-age and mass-metallicity relations, constructed using a combination of empirical and simulated data. Stellar-mass surface densities can be recovered well using any of the three data cubes, regardless of the SPS model and prior variations. The new priors then significantly improve the measurements of mass-weighted age and Z compared to results obtained without priors, but they may play an excessive role compared to the data in determining the outcome when no ultraviolet (UV) data is available. Compared to varying the spectral extent of the data cube or including and discarding the additional priors, replacing one SPS model family with the other has little effect on the results. The spatially resolved SED fitting method is powerful for mapping the stellar population properties of many galaxies with the current abundance of high-quality imaging data. Our study re-emphasizes the gain added by including multi-wavelength data from ancillary surveys and the roles of priors in Bayesian SED fitting. With the Euclid data alone, we will be able to generate complete and deep stellar mass maps of galaxies in the local Universe (z . 0.1), exploiting the telescope’s wide field, near-infrared sensitivity, and high spatial resolution