Plausibility of a Neural Network Classifier-Based Neuroprosthesis for Depression Detection via Laughter Records

The present work explores the diagnostic performance for depression of neural network classifiers analyzing the sound structures of laughter as registered from clinical patients and healthy controls. The main methodological novelty of this work is that simple sound variables of laughter are used as inputs, instead of electrophysiological signals or local field potentials (LFPs) or spoken language utterances, which are the usual protocols up-to-date. In the present study, involving 934 laughs from 30 patients and 20 controls, four different neural networks models were tested for sensitivity analysis, and were additionally trained for depression detection. Some elementary sound variables were extracted from the records: timing, fundamental frequency mean, first three formants, average power, and the Shannon-Wiener entropy. In the results obtained, two of the neural networks show a diagnostic discrimination capability of 93.02 and 91.15% respectively, while the third and fourth ones have an 87.96 and 82.40% percentage of success. Remarkably, entropy turns out to be a fundamental variable to distinguish between patients and controls, and this is a significant factor which becomes essential to understand the deep neurocognitive relationships between laughter and depression. In biomedical terms, our neural network classifier-based neuroprosthesis opens up the possibility of applying the same methodology to other mental-health and neuropsychiatric pathologies. Indeed, exploring the application of laughter in the early detection and prognosis of Alzheimer and Parkinson would represent an enticing possibility, both from the biomedical and the computational points of view

Repurposing Disulfiram as an Antimicrobial Agent in Topical Infections

Antimicrobial drugs applied topically offer several advantages. However, the widespread use of antibiotics has led to increasing antimicrobial resistance. One interesting approach in the drug discovery process is drug repurposing. Disulfiram, which was originally approved as an anti-alcoholism drug, offers an attractive alternative to treat topical multidrug resistance bacteria in skin human infections. This study aimed to evaluate the biopharmaceutical characteristics of the drug and the effects arising from its topical application in detail. Microdilution susceptibility testing showed antibacterial activity against Gram-positive bacteria Staphylococcus aureus and Streptococcus pyogenes. Dermal absorption revealed no permeation in pig skin. The quantification of the drug retained in pig skin demonstrated concentrations in the stratum corneum and epidermis, enough to treat skin infections. Moreover, in vitro cytotoxicity and micro-array analyses were performed to better understand the mechanism of action and revealed the importance of the drug as a metal ion chelator. Together, our findings suggest that disulfiram has the potential to be repurposed as an effective antibiotic to treat superficial human skin infections

Astrometric calibration and performance of the Dark Energy Camera

We characterize the ability of the Dark Energy Camera (DECam) to perform relative astrometry across its 500~Mpix, 3 deg^2 science field of view, and across 4 years of operation. This is done using internal comparisons of ~4x10^7 measurements of high-S/N stellar images obtained in repeat visits to fields of moderate stellar density, with the telescope dithered to move the sources around the array. An empirical astrometric model includes terms for: optical distortions; stray electric fields in the CCD detectors; chromatic terms in the instrumental and atmospheric optics; shifts in CCD relative positions of up to ~10 um when the DECam temperature cycles; and low-order distortions to each exposure from changes in atmospheric refraction and telescope alignment. Errors in this astrometric model are dominated by stochastic variations with typical amplitudes of 10-30 mas (in a 30 s exposure) and 5-10 arcmin coherence length, plausibly attributed to Kolmogorov-spectrum atmospheric turbulence. The size of these atmospheric distortions is not closely related to the seeing. Given an astrometric reference catalog at density ~0.7 arcmin^{-2}, e.g. from Gaia, the typical atmospheric distortions can be interpolated to 7 mas RMS accuracy (for 30 s exposures) with 1 arcmin coherence length for residual errors. Remaining detectable error contributors are 2-4 mas RMS from unmodelled stray electric fields in the devices, and another 2-4 mas RMS from focal plane shifts between camera thermal cycles. Thus the astrometric solution for a single DECam exposure is accurate to 3-6 mas (0.02 pixels, or 300 nm) on the focal plane, plus the stochastic atmospheric distortion.Comment: Submitted to PAS

Altered methylation pattern in EXOC4 is associated with stroke outcome: an epigenome-wide association study

Background and purpose: The neurological course after stroke is highly variable and is determined by demographic, clinical and genetic factors. However, other heritable factors such as epigenetic DNA methylation could play a role in neurological changes after stroke. Methods: We performed a three-stage epigenome-wide association study to evaluate DNA methylation associated with the difference between the National Institutes of Health Stroke Scale (NIHSS) at baseline and at discharge (Delta NIHSS) in ischaemic stroke patients. DNA methylation data in the Discovery (n = 643) and Replication (n = 62) Cohorts were interrogated with the 450 K and EPIC BeadChip. Nominal CpG sites from the Discovery (p value < 10(-06)) were also evaluated in a meta-analysis of the Discovery and Replication cohorts, using a random-fixed effect model. Metabolic pathway enrichment was calculated with methylGSA. We integrated the methylation data with 1305 plasma protein expression levels measured by SOMAscan in 46 subjects and measured RNA expression with RT-PCR in a subgroup of 13 subjects. Specific cell-type methylation was assessed using EpiDISH. Results: The meta-analysis revealed an epigenome-wide significant association in EXOC4 (p value = 8.4 x 10(-08)) and in MERTK (p value = 1.56 x 10(-07)). Only the methylation in EXOC4 was also associated in the Discovery and in the Replication Cohorts (p value = 1.14 x 10(-06) and p value = 1.3 x 10(-02), respectively). EXOC4 methylation negatively correlated with the long-term outcome (coefficient = - 4.91) and showed a tendency towards a decrease in EXOC4 expression (rho = - 0.469, p value = 0.091). Pathway enrichment from the meta-analysis revealed significant associations related to the endocytosis and deubiquitination processes. Seventy-nine plasma proteins were differentially expressed in association with EXOC4 methylation. Pathway analysis of these proteins showed an enrichment in natural killer (NK) cell activation. The cell-type methylation analysis in blood also revealed a differential methylation in NK cells. Conclusions: DNA methylation of EXOC4 is associated with a worse neurological course after stroke. The results indicate a potential modulation of pathways involving endocytosis and NK cells regulation

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Dark Energy Survey Year 1 Results: A Precise H0 Measurement from DES Y1, BAO, and D/H Data

We combine Dark Energy Survey Year 1 clustering and weak lensing data with baryon acoustic oscillations and Big Bang nucleosynthesis experiments to constrain the Hubble constant. Assuming a flat ΛCDM model with minimal neutrino mass (Σm υ = 0.06 eV), we find H 0 = 67.4 -1.2+1.1 km s -1 Mpc -1 (68 per cent CL). This result is completely independent of Hubble constant measurements based on the distance ladder, cosmic microwave background anisotropies (both temperature and polarization), and strong lensing constraints. There are now five data sets that: (a) have no shared observational systematics; and (b) each constrains the Hubble constant with fractional uncertainty at the few percent level. We compare these five independent estimates, and find that, as a set, the differences between them are significant at the 2.5σ level (χ 2 /dof = 24/11, probability to exceed = 1.1 per cent). Having set the threshold for consistency at 3σ, we combine all five data sets to arrive at H 0 = 69.3 -0.6+0.4 km s -1 Mpc -

Characterizing the intracluster light over the redshift range 0.2 < z < 0.8 in the DES-ACT overlap

We characterize the properties and evolution of bright central galaxies (BCGs) and the surrounding intracluster light (ICL) in galaxy clusters identified in the Dark Energy Survey and Atacama Cosmology Telescope Survey (DES-ACT) overlapping regions, covering the redshift range 0.20 14.4. We also measure the stellar mass–halo mass (SMHM) relation for the BCG+ICL system and find that the slope, β, which characterizes the dependence of M200m,SZ on the BCG+ICL stellar mass, increases with radius. The outskirts are more strongly correlated with the halo than the core, which supports that the BCG+ICL system follows a two-phase growth, where recent growth (z < 2) occurs beyond the BCG’s core. Additionally, we compare our observed SMHM relation results to the IllustrisTNG300-1 cosmological hydrodynamic simulations and find moderate qualitative agreement in the amount of diffuse light. However, the SMHM relation’s slope is steeper in TNG300-1 and the intrinsic scatter is lower, likely from the absence of projection effects in TNG300-1. Additionally, we find that the ICL exhibits a colour gradient such that the outskirts are bluer than the core. Moreover, for the lower halo mass clusters (log10(M200m,SZ/M⊙) < 14.59), we detect a modest change in the colour gradient’s slope with lookback time, which combined with the absence of stellar mass growth may suggest that lower mass clusters have been involved in growth via tidal stripping more recently than their higher mass counterparts

Observation and confirmation of nine strong-lensing systems in Dark Energy Survey Year 1 data

We describe the observation and confirmation of nine new strong gravitational lenses discovered in Year 1 data from the Dark Energy Survey (DES). We created candidate lists based on (i) galaxy group and cluster samples, and (ii) photometrically selected galaxy samples. We selected 46 candidates through visual inspection and then used the Gemini Multi-Object Spectrograph(GMOS) at the Gemini South telescope to acquire a spectroscopic follow-up of 21 of these candidates. Through an analysis of these spectroscopic follow-up data, we confirmed nine new lensing systems and rejected two candidates, and the analysis was inconclusive on 10 candidates. For each of the confirmed systems, our report measured spectroscopic properties, estimated source image–lens separations, and estimated enclosed masses as well. The sources that we targeted have an i-band surface brightness range of iSB∼22−24magarcsec−2 and a spectroscopic redshift range of zspec ∼ 0.8−2.6. The lens galaxies have a photometric redshift range of zlens ∼ 0.3−0.7. The lensing systems range in source image–lens separation from 2 to 9 arcsec and in enclosed mass from 1012 to 1013 M⊙