Insulin-like growth factor I sensitization rejuvenates sleep patterns in old mice

Sleep disturbances are common during aging. Compared to young animals, old mice show altered sleep structure, with changes in both slow and fast electrocorticographic (ECoG) activity and fewer transitions between sleep and wake stages. Insulin-like growth factor I (IGF-I), which is involved in adaptive changes during aging, was previously shown to increase ECoG activity in young mice and monkeys. Furthermore, IGF-I shapes sleep architecture by modulating the activity of mouse orexin neurons in the lateral hypothalamus (LH). We now report that both ECoG activation and excitation of orexin neurons by systemic IGF-I are abrogated in old mice. Moreover, orthodromical responses of LH neurons are facilitated by either systemic or local IGF-I in young mice, but not in old ones. As orexin neurons of old mice show dysregulated IGF-I receptor (IGF-IR) expression, suggesting disturbed IGF-I sensitivity, we treated old mice with AIK3a305, a novel IGF-IR sensitizer, and observed restored responses to IGF-I and rejuvenation of sleep patterns. Thus, disturbed sleep structure in aging mice may be related to impaired IGF-I signaling onto orexin neurons, reflecting a broader loss of IGF-I activity in the aged mouse brain.This work was funded by a grant from Ciberned and is part of the project SAF2016-76462 funded by MCIN/AEI/https://doi.org/10.13039/501100011033. J.A. ZegarraValdivia acknowledges the fnancial support of the National Council of Science, Technology and Technological Innovation (CONCYTEC, Perú) through the National Fund for Scientifc and Technological Development (FONDECYT, Perú). J. Fernandes received a post-doc fellowship from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP: # 2017/14742–0; # 2019/03368–5)

Astrocytic IGF-IRs induce adenosine-mediated inhibitory downregulation and improve sensory discrimination

Insulin-like growth factor-I (IGF-I) signaling plays a key role in learning and memory processes. While the effects of IGF-I on neurons have been studied extensively, the involvement of astrocytes in IGF-I signaling and the consequences on synaptic plasticity and animal behavior remain unknown. We have found that IGF-I induces long-term potentiation (LTPIGFI) of the postsynaptic potentials that is caused by a long-term depression of inhibitory synaptic transmission in mice. We have demonstrated that this long-lasting decrease in the inhibitory synaptic transmission is evoked by astrocytic activation through its IGF-I receptors (IGF-IRs). We show that LTPIGFI not only increases the output of pyramidal neurons, but also favors the NMDAR-dependent LTP, resulting in the crucial information processing at the barrel cortex since specific deletion of IGF-IR in cortical astrocytes impairs the whisker discrimination task. Our work reveals a novel mechanism and functional consequences of IGF-I signaling on cortical inhibitory synaptic plasticity and animal behavior, revealing that astrocytes are key elements in these processesThis work was supported by Grants BFU2016-80802-P from Agencia Estatal de Investigación Spain/Fondo Europeo de Desarrollo Regional, and from the European Union [Ministerio de Economía y Competitividad (MINECO)] to D.F.d.S.; Grants R01-NS-097312 and R01-DA-048822 from National Institutes of Health/National Institute of Neurological Disorders and Stroke to A.A.; and grants from Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED) and Grant SAF2016-76462-C2-1-P from MINECO to I.T.-A. J.A.Z.-V. was supported by the National Council of Science, Technology and Technological Innovation (CONCYTEC, Perú) through the National Fund for Scientific and Technological Development (FONDECYT, Perú). J.F. received a postdoctoral fellowship from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP; Grants #2017/ 14742-0 and #2019/03368-5). We thank the University of Minnesota Viral Vector and Cloning Core for production of some of the viral vectors used in this study; and Dr. G. Perea and Dr. Washington Buño for helpful comment

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

The adjusted International Prognostic Index and beta-2-microglobulin predict the outcome after autologous stem cell transplantation in relapsing/refractory peripheral T-cell lymphoma

BACKGROUND AND OBJECTIVES: Preliminary data on the use of autologous stem cell transplantation (ASCT) as a salvage therapy for peripheral T-cell lymphoma (PTCL) indicate that the results are similar to those obtained in aggressive B-cell lymphomas. The aim of our study was to analyze outcomes of a large series of patients with PTCL with a prolonged follow-up who received ASCT as salvage therapy. DESIGN AND METHODS: Between 1990 and 2004, 123 patients in this situation were registered in the GELTAMO database. The median age at transplantation was 43.5 years; in 91% of patients the disease was chemosensitive. RESULTS: Seventy-three percent of the patients achieved complete remission, 11% partial remission and the procedure failed in 16%. At a median follow-up of 61 months, the 5-year overall and progression-free survival rates were 45% and 34%, respectively. The presence of more than one factor of the adjusted International Prognostic Index (a-IPI) and a high beta2-microglobulin at transplantation were identified as adverse prognostic factors for both overall and progression-free survival and allowed the population to be stratified into three distinct risk groups. INTERPRETATION AND CONCLUSIONS: Our data show that approximately one third of patients with PTCL in the salvage setting may enjoy prolonged survival following ASCT, provided they are transplanted in a chemosensitive disease state. The a-IPI and beta2-microglobulin level predict the outcome after ASCT in relapsing/refractory PTCL

The Positive Rhinovirus/Enterovirus Detection and SARS-CoV-2 Persistence beyond the Acute Infection Phase: An Intra-Household Surveillance Study.

We aimed to assess the duration of nasopharyngeal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA persistence in adults self-confined at home after acute infection; and to identify the associations of SARS-CoV-2 persistence with respiratory virus co-detection and infection transmission. A cross-sectional intra-household study was conducted in metropolitan Barcelona (Spain) during the time period of April to June 2020. Every adult who was the first family member reported as SARS-CoV-2-positive by reverse transcription polymerase chain reaction (RT-PCR) as well as their household child contacts had nasopharyngeal swabs tested by a targeted SARS-CoV-2 RT-PCR and a multiplex viral respiratory panel after a 15 day minimum time lag. Four-hundred and four households (404 adults and 708 children) were enrolled. SARS-CoV-2 RNA was detected in 137 (33.9%) adults and 84 (11.9%) children. Rhinovirus/Enterovirus (RV/EV) was commonly found (83.3%) in co-infection with SARS-CoV-2 in adults. The mean duration of SARS-CoV-2 RNA presence in adults' nasopharynx was 52 days (range 26-83 days). The persistence of SARS-CoV-2 was significantly associated with RV/EV co-infection (adjusted odds ratio (aOR) 9.31; 95% CI 2.57-33.80) and SARS-CoV-2 detection in child contacts (aOR 2.08; 95% CI 1.24-3.51). Prolonged nasopharyngeal SARS-CoV-2 RNA persistence beyond the acute infection phase was frequent in adults quarantined at home during the first epidemic wave; which was associated with RV/EV co-infection and could enhance intra-household infection transmission

The PAU Survey: Photometric redshift estimation in deep wide fields

We present photometric redshifts (photo-$z$) for the deep wide fields of the Physics of the Accelerating Universe Survey (PAUS), covering an area of $\sim$50 deg$^{2}$, for $\sim$1.8 million objects up to $i_{\textrm{AB}}<23$. The PAUS deep wide fields overlap with the W1 and W3 fields from CFHTLenS and the G09 field from KiDS/GAMA. Photo-$z$ are estimated using the 40 narrow bands (NB) of PAUS and the broad bands (BB) of CFHTLenS and KiDS. We compute the redshifts with the SED template-fitting code BCNZ, with a modification in the calibration technique of the zero-point between the observed and the modelled fluxes, that removes any dependence on spectroscopic redshift samples. We enhance the redshift accuracy by introducing an additional photo-$z$ estimate ($z_{\textrm{b}}$), obtained through the combination of the BCNZ and the BB-only photo-$z$. Comparing with spectroscopic redshifts estimates ($z_{\textrm{s}}$), we obtain a $\sigma_{68} \simeq 0.019$ for all galaxies with $i_{\textrm{AB}}<23$ and a typical bias $|z_{\textrm{b}}-z_{\textrm{s}}|$ smaller than 0.01. For $z_{\textrm{b}} \sim (0.10-0.75)$ we find $\sigma_{68} \simeq (0.003-0.02)$, this is a factor of $10-2$ higher accuracy than the corresponding BB-only results. We obtain similar performance when we split the samples into red (passive) and blue (active) galaxies. We validate the redshift probability $p(z)$ obtained by BCNZ and compare its performance with that of $z_{\textrm{b}}$. These photo-$z$ catalogues will facilitate important science cases, such as the study of galaxy clustering and intrinsic alignment at high redshifts ($z \lesssim 1$) and faint magnitudes.Comment: 24 pages, 26 figures, submitted to MNRA

The PAU survey: classifying low-z SEDs using Machine Learning clustering

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record Monthly Notices of the Royal Astronomical Society 524.3 (2023): 3569-3581 is available online at: https://academic.oup.com/mnras/article-abstract/524/3/3569/7225529?redirectedFrom=fulltextWe present an application of unsupervised Machine Learning clustering to the PAU survey of galaxy spectral energy distribution (SED) within the COSMOS field. The clustering algorithm is implemented and optimized to get the relevant groups in the data SEDs. We find 12 groups from a total number of 5234 targets in the survey at 0.01 < z < 0.28. Among the groups, 3545 galaxies (68 per cent) show emission lines in the SEDs. These groups also include 1689 old galaxies with no active star formation. We have fitted the SED to every single galaxy in each group with CIGALE. The mass, age, and specific star formation rates (sSFR) of the galaxies range from 0.15 < age/Gyr <11; 6 < log (M/M⊙) <11.26, and -14.67 < log (sSFR/yr-1) <-8. The groups are well-defined in their properties with galaxies having clear emission lines also having lower mass, are younger and have higher sSFR than those with elliptical like patterns. The characteristic values of galaxies showing clear emission lines are in agreement with the literature for starburst galaxies in COSMOS and GOODS-N fields at low redshift. The star-forming main sequence, sSFR versus stellar mass and UVJ diagram show clearly that different groups fall into different regions with some overlap among groups. Our main result is that the joint of low- resolution (R ∼50) photometric spectra provided by the PAU survey together with the unsupervised classification provides an excellent way to classify galaxies. Moreover, it helps to find and extend the analysis of extreme ELGs to lower masses and lower SFRs in the local UniverseThis work has been supported by the Ministry of Science and Innovation of Spain, project PID2019-107408GB-C43 (ESTALLIDOS), and the Government of the Canary Islands through EU FEDER funding, projects PID2020010050 and PID2021010077. This article is based on observations made in the Observatorios de Canarias of the Instituto de Astrofísica de Canarias (IAC) with the WHT operated on the island of La Palma by the Isaac Newton Group of Telescopes (ING) in the Observatorio del Roque de los Muchachos. The PAU Survey is partially supported by MINECO under grants CSD2007-00060, AYA2015-71825, ESP2017-89838, PGC2018-094773, PGC2018-102021, PID2019-111317GB, SEV-2016-0588, SEV-2016-0597, MDM-2015-0509 and Juan de la Cierva fellowship and LACEGAL and EWC Marie Sklodowska-Curie grant No 734374 and no.776247 with ERDF funds from the EU Horizon 2020 Programme, some of which include ERDF funds from the European Union. IEEC and IFAE are partially funded by the CERCA and Beatriu de Pinos program of the Generalitat de Catalunya. Funding for PAUS has also been provided by Durham Univer sity (via the ERC StG DEGAS-259586), ETH Zurich, Leiden University (via ERC StG ADULT-279396 and Netherlands Organisation for Scientific Research (NWO) Vici grant 639.043.512), University College London and from the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 776247 EWC. The PAU data center is hosted by the Port d’Información Científica (PIC), maintained through a collaboration of CIEMAT and IFAE, with additional support from Universitat Autónoma de Barcelona and ERDF. We acknowledge the PIC services department team for their support and fruitful discussion

The Physics of the Accelerating Universe Survey: narrow-band image photometry

PAUCam is an innovative optical narrow-band imager mounted at the William Herschel Telescope built for the Physics of the Accelerating Universe Survey (PAUS). Its set of 40 filters results in images that are complex to calibrate, with specific instrumental signatures that cannot be processed with traditional data reduction techniques. In this paper, we present two pipelines developed by the PAUS data management team with the objective of producing science-ready catalogues from the uncalibrated raw images. The NIGHTLY pipeline takes care of entire image processing, with bespoke algorithms for photometric calibration and scatter-light correction. The Multi-Epoch and Multi-Band Analysis pipeline performs forced photometry over a reference catalogue to optimize the photometric redshift (photo-z) performance. We verify against spectroscopic observations that the current approach delivers an inter-band photometric calibration of 0.8 per cent across the 40 narrow-band set. The large volume of data produced every night and the rapid survey strategy feedback constraints require operating both pipelines in the Port d’Informació Cientifica data centre with intense parallelization. While alternative algorithms for further improvements in photo-z performance are under investigation, the image calibration and photometry presented in this work already enable state-of-the-art photo-z down to iAB = 23.0

The PAU Survey: Narrow-band image photometry

PAUCam is an innovative optical narrow-band imager mounted at the William Herschel Telescope built for the Physics of the Accelerating Universe Survey (PAUS). Its set of 40 filters results in images that are complex to calibrate, with specific instrumental signatures that cannot be processed with traditional data reduction techniques. In this paper we present two pipelines developed by the PAUS data management team with the objective of producing science-ready catalogues from the uncalibrated raw images. The Nightly pipeline takes care of all image processing, with bespoke algorithms for photometric calibration and scatter-light correction. The Multi-Epoch and Multi-Band Analysis (MEMBA) pipeline performs forced photometry over a reference catalogue to optimize the photometric redshift performance. We verify against spectroscopic observations that the current approach delivers an inter-band photometric calibration of 0.8% across the 40 narrow-band set. The large volume of data produced every night and the rapid survey strategy feedback constraints require operating both pipelines in the Port d'Informaci\'o Cientifica data centre with intense parallelization. While alternative algorithms for further improvements in photo-z performance are under investigation, the image calibration and photometry presented in this work already enable state-of-the-art photometric redshifts down to iAB=23.0.Comment: 32 pages, 26 figures, MNRAS in pres