Recombinant lipid transfer protein Tri a 14: a novel heat and proteolytic resistant tool for the diagnosis of baker's asthma

BACKGROUND Baker's asthma is an important occupational allergic disease. Wheat lipid transfer protein (LTP) Tri a 14 is a major allergen associated with wheat allergy. No panel of wheat recombinant allergens for component-resolved diagnosis of baker's asthma is currently available. OBJECTIVE To evaluate the potential role of recombinant Tri a 14 as a novel tool for the diagnosis of baker's asthma, and to test the heat and proteolytic resistance of the wheat LTP allergen. METHODS A cDNA encoding Tri a 14 was isolated and sequenced, the recombinant allergen produced in Pichia pastoris and purified by chromatographic methods. Physicochemical and immunological comparison of the natural and recombinant forms of Tri a 14 was carried out by N-terminal amino acid sequencing, matrix-assisted laser desorption/ionization mass spectrometry, circular dichroism (CD) analysis, IgE immunodetection, and specific IgE determination and ELISA-inhibition assays using a pool or individual sera from 26 patients with baker's asthma. Thermal denaturation and simulated gastrointestinal digestion of both Tri a 14 forms were checked by spectroscopic and electrophoretic methods, respectively, and biological activity by basophil activation test (BAT). RESULTS Natural and recombinant Tri a 14 were similarly folded, as indicated by their nearly identical CD spectra and heat denaturation profiles. A high interclass correlation coefficient (0.882) was found between specific IgE levels to both Tri a 14 proteins in individual sera from baker's asthma patients, but a slightly lower IgE-binding potency of rTri a 14 was detected by ELISA-inhibition assays. Natural and recombinant Tri a 14 elicited positive BAT in two and one out of three patients, respectively. Heat denaturation profiles and simulated gastrointestinal digestion assays indicated that Tri a 14 displayed a high heat and digestive proteolytic resistance, comparable to those of peach Pru p 3, the model food allergen of the LTP family. CONCLUSIONS Recombinant Tri a 14 is a potential tool for baker's asthma diagnosis, based on its physicochemical and immunological similarity with its natural counterpart. Wheat Tri a 14 shows a high thermal stability and resistance to gastrointestinal digestion

Novel tools for the diagnosis of baker's asthma: wheat lipid transfer protein Tri a 14

Background: Baker’s asthma is among the most important occupational allergic diseases. Wheat lipid transfer protein (LTP) Tri a 14 has been reported as a major allergen associated with wheat allergy. No panel of wheat recombinant allergens for component-resolved diagnosis of baker’s asthma is currently performed. We sought to evaluate the potential role of recombinant Tri a 14 as a novel tool for the diagnosis of baker’s asthma, and to test the heat and proteolytic resistance of this wheat LTP allergen

The ALHAMBRA survey: Accurate merger fractions by PDF analysis of photometric close pairs

Our goal is to develop and test a novel methodology to compute accurate close pair fractions with photometric redshifts. We improve the current methodologies to estimate the merger fraction f_m from photometric redshifts by (i) using the full probability distribution functions (PDFs) of the sources in redshift space, (ii) including the variation in the luminosity of the sources with z in both the selection of the samples and in the luminosity ratio constrain, and (iii) splitting individual PDFs into red and blue spectral templates to deal robustly with colour selections. We test the performance of our new methodology with the PDFs provided by the ALHAMBRA photometric survey. The merger fractions and rates from the ALHAMBRA survey are in excellent agreement with those from spectroscopic work, both for the general population and for red and blue galaxies. With the merger rate of bright (M_B <= -20 - 1.1z) galaxies evolving as (1+z)^n, the power-law index n is larger for blue galaxies (n = 2.7 +- 0.5) than for red galaxies (n = 1.3 +- 0.4), confirming previous results. Integrating the merger rate over cosmic time, we find that the average number of mergers per galaxy since z = 1 is N_m = 0.57 +- 0.05 for red galaxies and N_m = 0.26 +- 0.02 for blue galaxies. Our new methodology exploits statistically all the available information provided by photometric redshift codes and provides accurate measurements of the merger fraction by close pairs only using photometric redshifts. Current and future photometric surveys will benefit of this new methodology.Comment: Submitted to A&A, 15 pages, 15 figures, 6 tables. Comments are welcome. Close pair systems available at https://cloud.iaa.csic.es/alhambra/catalogues/ClosePairs

The ALHAMBRA Survey: Bayesian Photometric Redshifts with 23 bands for 3 squared degrees

The ALHAMBRA (Advance Large Homogeneous Area Medium Band Redshift Astronomical) survey has observed 8 different regions of the sky, including sections of the COSMOS, DEEP2, ELAIS, GOODS-N, SDSS and Groth fields using a new photometric system with 20 contiguous ~ $300\AA$ filters covering the optical range, combining them with deep $JHKs$ imaging. The observations, carried out with the Calar Alto 3.5m telescope using the wide field (0.25 sq. deg FOV) optical camera LAICA and the NIR instrument Omega-2000, correspond to ~700hrs on-target science images. The photometric system was designed to maximize the effective depth of the survey in terms of accurate spectral-type and photo-zs estimation along with the capability of identification of relatively faint emission lines. Here we present multicolor photometry and photo-zs for ~438k galaxies, detected in synthetic F814W images, complete down to I~24.5 AB, taking into account realistic noise estimates, and correcting by PSF and aperture effects with the ColorPro software. The photometric ZP have been calibrated using stellar transformation equations and refined internally, using a new technique based on the highly robust photometric redshifts measured for emission line galaxies. We calculate photometric redshifts with the BPZ2 code, which includes new empirically calibrated templates and priors. Our photo-zs have a precision of $dz/(1+z_s)=1$ for I<22.5 and 1.4% for 22.5<I<24.5. Precisions of less than 0.5% are reached for the brighter spectroscopic sample, showing the potential of medium-band photometric surveys. The global $P(z)$ shows a mean redshift =0.56 for I=0.86 for I<24.5 AB. The data presented here covers an effective area of 2.79 sq. deg, split into 14 strips of 58.5'x15.5' and represents ~32 hrs of on-target.Comment: The catalog data and a full resolution version of this paper is available at https://cloud.iaa.csic.es/alhambra

The ALHAMBRA survey : Estimation of the clustering signal encoded in the cosmic variance

The relative cosmic variance ($\sigma_v$) is a fundamental source of uncertainty in pencil-beam surveys and, as a particular case of count-in-cell statistics, can be used to estimate the bias between galaxies and their underlying dark-matter distribution. Our goal is to test the significance of the clustering information encoded in the $\sigma_v$ measured in the ALHAMBRA survey. We measure the cosmic variance of several galaxy populations selected with $B-$band luminosity at $0.35 \leq z < 1.05$ as the intrinsic dispersion in the number density distribution derived from the 48 ALHAMBRA subfields. We compare the observational $\sigma_v$ with the cosmic variance of the dark matter expected from the theory, $\sigma_{v,{\rm dm}}$. This provides an estimation of the galaxy bias $b$. The galaxy bias from the cosmic variance is in excellent agreement with the bias estimated by two-point correlation function analysis in ALHAMBRA. This holds for different redshift bins, for red and blue subsamples, and for several $B-$band luminosity selections. We find that $b$ increases with the $B-$band luminosity and the redshift, as expected from previous work. Moreover, red galaxies have a larger bias than blue galaxies, with a relative bias of $b_{\rm rel} = 1.4 \pm 0.2$. Our results demonstrate that the cosmic variance measured in ALHAMBRA is due to the clustering of galaxies and can be used to characterise the $\sigma_v$ affecting pencil-beam surveys. In addition, it can also be used to estimate the galaxy bias $b$ from a method independent of correlation functions.Comment: Astronomy and Astrophysics, in press. 9 pages, 4 figures, 3 table

Stellar populations of galaxies in the ALHAMBRA survey up to z∼1z \sim 1. I. MUFFIT: A Multi-Filter Fitting code for stellar population diagnostics

We present MUFFIT, a new generic code optimized to retrieve the main stellar population parameters of galaxies in photometric multi-filter surveys, and we check its reliability and feasibility with real galaxy data from the ALHAMBRA survey. Making use of an error-weighted $\chi^2$-test, we compare the multi-filter fluxes of galaxies with the synthetic photometry of mixtures of two single stellar populations at different redshifts and extinctions, to provide through a Monte Carlo method the most likely range of stellar population parameters (mainly ages and metallicities), extinctions, redshifts, and stellar masses. To improve the diagnostic reliability, MUFFIT identifies and removes from the analysis those bands that are significantly affected by emission lines. We highlight that the retrieved age-metallicity locus for a sample of $z \le 0.22$ early-type galaxies in ALHAMBRA at different stellar mass bins are in very good agreement with the ones from SDSS spectroscopic diagnostics. Moreover, a one-to-one comparison between the redshifts, ages, metallicities, and stellar masses derived spectroscopically for SDSS and by MUFFIT for ALHAMBRA reveals good qualitative agreements in all the parameters. In addition, and using as input the results from photometric-redshift codes, MUFFIT improves the photometric-redshift accuracy by $\sim 10$-$20\%$, and it also detects nebular emissions in galaxies, providing physical information about their strengths. Our results show the potential of multi-filter galaxy data to conduct reliable stellar population studies with the appropiate analysis techniques, as MUFFIT.Comment: 31 pages, 18 figures, accepted for publication in A&

The ALHAMBRA survey : B−B-band luminosity function of quiescent and star-forming galaxies at 0.2≤z<10.2 \leq z < 1 by PDF analysis

Our goal is to study the evolution of the $B-$band luminosity function (LF) since $z=1$ using ALHAMBRA data. We used the photometric redshift and the $I-$band selection magnitude probability distribution functions (PDFs) of those ALHAMBRA galaxies with $I\leq24$ mag to compute the posterior LF. We statistically studied quiescent and star-forming galaxies using the template information encoded in the PDFs. The LF covariance matrix in redshift-magnitude-galaxy type space was computed, including the cosmic variance. That was estimated from the intrinsic dispersion of the LF measurements in the 48 ALHAMBRA sub-fields. The uncertainty due to the photometric redshift prior is also included in our analysis. We modelled the LF with a redshift-dependent Schechter function affected by the same selection effects than the data. The measured ALHAMBRA LF at $0.2\leq z<1$ and the evolving Schechter parameters both for quiescent and star-forming galaxies agree with previous results in the literature. The estimated redshift evolution of $M_B^* \propto Qz$ is $Q_{\rm SF}=-1.03\pm0.08$ and $Q_{\rm Q}=-0.80\pm0.08$, and of $\log \phi^* \propto Pz$ is $P_{\rm SF}=-0.01\pm0.03$ and $P_{\rm Q}=-0.41\pm0.05$. The measured faint-end slopes are $\alpha_{\rm SF}=-1.29\pm0.02$ and $\alpha_{\rm Q}=-0.53\pm0.04$. We find a significant population of faint quiescent galaxies, modelled by a second Schechter function with slope $\beta=-1.31\pm0.11$. We find a factor $2.55\pm0.14$ decrease in the luminosity density $j_B$ of star-forming galaxies, and a factor $1.25\pm0.16$ increase in the $j_B$ of quiescent ones since $z=1$, confirming the continuous build-up of the quiescent population with cosmic time. The contribution of the faint quiescent population to $j_B$ increases from 3% at $z=1$ to 6% at $z=0$. The developed methodology will be applied to future multi-filter surveys such as J-PAS.Comment: Accepted for publication in Astronomy and Astrophysics. 25 pages, 20 figures, 7 table

Type Ia Supernova host galaxies as seen with IFU spectroscopy

(abridged) We used the wide-field IFU spectrograph PMAS/PPAK at the 3.5m telescope of Calar Alto Observatory to observe six nearby spiral galaxies that hosted SNe Ia. Spatially resolved 2D maps of the properties of the ionized gas and the stellar populations were derived. Five of the observed galaxies have an ongoing star formation rate of 1-5 M_sun/yr and mean stellar population ages ~5 Gyr. The sixth galaxy shows no star formation and has an about 12 Gyr old stellar population. All galaxies have stellar masses larger than 2E+10 M_sun and metallicities above solar. Four galaxies show negative radial metallicity gradients of the ionized gas up to -0.058 dex/kpc and one has nearly uniform metallicity with a possible shallow positive slope. The stellar components show shallower negative metallicity gradients up to -0.03 dex/kpc. We find no clear correlation between the properties of the galaxy and those of the supernovae, which may be because of the small ranges spanned by the galaxy parameters. However, we note that the Hubble residuals are on average positive while negative Hubble residuals are expected for SNe Ia in massive hosts such as the galaxies in our sample. In conclusion, IFU spectroscopy on 4-m telescopes is a viable technique for studying host galaxies of nearby SNe Ia. It allows one to correlate the supernova properties with the properties of their host galaxies at the projected positions of the supernovae. Our current sample of six galaxies is too small to draw conclusions about the SN Ia progenitors or correlations with the galaxy properties, but the ongoing CALIFA IFU survey will provide a solid basis to exploit this technique more and improve our understanding of SNe Ia as cosmological standard candles.Comment: accepted by A&A, final language-edited version, layout change

The miniJPAS survey:star-galaxy classification using machine learning

Future astrophysical surveys such as J-PAS will produce very large datasets, which will require the deployment of accurate and efficient Machine Learning (ML) methods. In this work, we analyze the miniJPAS survey, which observed about 1 deg2 of the AEGIS field with 56 narrow-band filters and 4 ugri broad-band filters. We discuss the classification of miniJPAS sources into extended (galaxies) and point-like (e.g. stars) objects, a necessary step for the subsequent scientific analyses. We aim at developing an ML classifier that is complementary to traditional tools based on explicit modeling. In order to train and test our classifiers, we crossmatched the miniJPAS dataset with SDSS and HSC-SSP data. We trained and tested 6 different ML algorithms on the two crossmatched catalogs. As input for the ML algorithms we use the magnitudes from the 60 filters together with their errors, with and without the morphological parameters. We also use the mean PSF in the r detection band for each pointing. We find that the RF and ERT algorithms perform best in all scenarios. When analyzing the full magnitude range of 1521). We use our best classifiers, with and without morphology, in order to produce a value added catalog available at https://j-pas.org/datareleases