Water extract of Cryphaea heteromalla (Hedw.) D. Mohr bryophyte as a natural powerful source of biologically active compounds

Bryophytes comprise of the mosses, liverworts, and hornworts. Cryphaea heteromalla, (Hedw.) D. Mohr, is a non-vascular lower plant belonging to mosses group. To the date, the most chemically characterized species belong to the liverworts, while only 3.2% and 8.8% of the species belonging to the mosses and hornworts, respectively, have been investigated. In this work, we present Folin–Ciocalteu and oxygen radical absorbance capacity (ORAC) data related to crude extracts of C. heteromalla obtained by three different extraction solvents: pure water (WT), methanol:water (80:20 v/v) (MET), and ethanol:water (80:20 v/v) (ETH). The water extract proved to be the best solvent showing the highest content of biophenols and the highest ORAC value. The C. heteromalla-WT extract was investigated by HPLC-TOF/MS (High Performance Liquid Chromatography-Time of Flight/Mass Spectrometry) allowing for the detection of 14 compounds, five of which were phenolic compounds, derivatives of benzoic, caffeic, and coumaric acids. Moreover, the C. heteromalla WT extract showed a protective effect against reactive oxygen species (ROS) generation induced by tert-butyl hydroperoxide (TBH) on the murine NIH-3T3 fibroblast cell line

Novel and natural knockout lung cancer cell lines for the LKB1/STK11 tumor suppressor gene

Germline mutations of the LKB1 gene are responsible for Peutz-Jeghers syndrome (PJS), an autosomal dominant inherited disorder bestowing an increased risk of cancer. We have recently demonstrated that LKB1 inactivating mutations are not confined to PJS, but also appear in lung adenocarcinomas of sporadic origin, including primary tumors and lung cancer cell lines. To accurately determine the frequency of inactivating LKB1 gene mutations in lung tumors we have sequenced the complete coding region of LKB1 in 21 additional lung cancer cell lines. Here we describe the mutational status of LKB1 gene in 30 lung cancer cell lines from different histopathological types, including 11 lung adenocarcinomas (LADs) and 11 small cell lung cancers (SCLCs). LKB1 gene alterations were present in six (54%) of the LAD cell lines tested but in none of the other histological types. Similar to our previous observations in primary tumors, all point mutations were of the nonsense or frameshift type, leading to an abnormal, truncated protein. Moreover, 2 cell lines (A427 and H2126) harbored large gene deletions that spanned several exons. Hence, we have identified additional lung cancer cell lines carrying inactivating mutations of the LKB1 tumor suppressor gene, further attesting to the significance of this gene in the development of LADs and providing new natural LKB1 knockouts for studies of the biological function of the LKB1 protein

The stellar content of low redshift radio galaxies from near-infrared spectroscopy

We present medium spectral resolution near-infrared (NIR) HK-band spectra for 8 low redshift (z<0.06) radio galaxies to study the NIR stellar properties of their host galaxies. As a homogeneous comparison sample, we used 9 inactive elliptical galaxies that were observed with similar resolution and wavelength range. The aim of the study is to compare the NIR spectral properties of radio galaxies to those of inactive early-type galaxies and, furthermore, produce the first NIR HK-band spectra for low redshift radio galaxies. For both samples spectral indices of several diagnostic absorption features, SiI(1.589microns), CO(1.619microns), NaI(2.207microns), CaI(2.263microns), CO(>2.29microns), were measured. To characterize the age of the populations, the measured EWs of the absorption features were fitted with the corresponding theoretical evolutionary curves of the EWs calculated by the stellar synthesis model. On average, EW(CO 2.29) of radio galaxies is somewhat greater than that of inactive ellipticals. Most likely, EW(CO 2.29) is not significantly affected by dilution, and thus indicating that elliptical galaxies containing AGN are in a different stage in their evolution than inactive ellipticals. This is also supported by comparing other NIR features, such as CaI and NaI, with each other. Absorption features are consistent with the intermediate age stellar population, suggesting that host galaxies contain both an old and intermediate age components. It is consistent with previous optical spectroscopy studies which have shown evidence on the intermediate age (~2 Gyr) stellar population of radio galaxies, and also in some of the early-type galaxies. The existence of intermediate age population is a link between the star formation episode, possibly induced by interaction or merging event, and the triggering of the nuclear activity.Comment: 10 pages, 7 figure

The PAU Survey: Photometric redshifts using transfer learning from simulations

In this paper we introduce the \textsc{Deepz} deep learning photometric redshift (photo-$z$) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. \textsc{Deepz} reduces the $\sigma_{68}$ scatter statistic by 50\% at $i_{\rm AB}=22.5$ compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-$z$ scatter by 10 percent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys.Comment: Accepted versio

Brown dwarf census with the Dark Energy Survey year 3 data and the thin disc scale height of early L types

27 pages, 18 figuresIn this paper we present a catalogue of 11 745 brown dwarfs with spectral types ranging from L0 to T9, photometrically classified using data from the Dark Energy Survey (DES) year 3 release matched to the Vista Hemisphere Survey (VHS) DR3 and Wide-field Infrared Survey Explorer (WISE) data, covering ≈2400 deg2 up to iAB = 22. The classification method follows the same phototype method previously applied to SDSS-UKIDSS-WISE data. The most significant difference comes from the use of DES data instead of SDSS, which allow us to classify almost an order of magnitude more brown dwarfs than any previous search and reaching distances beyond 400 pc for the earliest types. Next, we also present and validate the GalmodBD simulation, which produces brown dwarf number counts as a function of structural parameters with realistic photometric properties of a given survey. We use this simulation to estimate the completeness and purity of our photometric LT catalogue down to iAB = 22, as well as to compare to the observed number of LT types. We put constraints on the thin disc scale height for the early L (L0–L3) population to be around 450 pc, in agreement with previous findings. For completeness, we also publish in a separate table a catalogue of 20 863 M dwarfs that passed our colour cut with spectral types greater than M6. Both the LT and the late M catalogues are found at DES release page https://des.ncsa.illinois.edu/releases/other/y3-mlt.Peer reviewedFinal Published versio

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

Forward Global Photometric Calibration of the Dark Energy Survey

Many scientific goals for the Dark Energy Survey (DES) require calibration of optical/NIR broadband $b = grizY$ photometry that is stable in time and uniform over the celestial sky to one percent or better. It is also necessary to limit to similar accuracy systematic uncertainty in the calibrated broadband magnitudes due to uncertainty in the spectrum of the source. Here we present a "Forward Global Calibration Method (FGCM)" for photometric calibration of the DES, and we present results of its application to the first three years of the survey (Y3A1). The FGCM combines data taken with auxiliary instrumentation at the observatory with data from the broad-band survey imaging itself and models of the instrument and atmosphere to estimate the spatial- and time-dependence of the passbands of individual DES survey exposures. "Standard" passbands are chosen that are typical of the passbands encountered during the survey. The passband of any individual observation is combined with an estimate of the source spectral shape to yield a magnitude $m_b^{\mathrm{std}}$ in the standard system. This "chromatic correction" to the standard system is necessary to achieve sub-percent calibrations. The FGCM achieves reproducible and stable photometric calibration of standard magnitudes $m_b^{\mathrm{std}}$ of stellar sources over the multi-year Y3A1 data sample with residual random calibration errors of $\sigma=5-6\,\mathrm{mmag}$ per exposure. The accuracy of the calibration is uniform across the $5000\,\mathrm{deg}^2$ DES footprint to within $\sigma=7\,\mathrm{mmag}$. The systematic uncertainties of magnitudes in the standard system due to the spectra of sources are less than $5\,\mathrm{mmag}$ for main sequence stars with $0.5<g-i<3.0$.Comment: 25 pages, submitted to A

Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogs from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multi-band deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalog created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of $\sigma_{\Delta z} = 0.007$, which is a 60% improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.Comment: 24 pages, 11 figures; matches version accepted to MNRA