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Galaxy–galaxy lensing (GGL) and clustering measurements from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) data set promise to yield unprecedented combined-probe tests of cosmology and the galaxy–halo connection. In such analyses, it is essential to identify and characterize all relevant statistical and systematic errors. We forecast the covariances of DESI Y1 GGL + clustering measurements and the systematic bias due to redshift evolution in the lens samples. Focusing on the projected clustering and GGL correlations, we compute a Gaussian analytical covariance, using a suite of N -body and lognormal simulations to characterize the effect of the survey footprint. Using the DESI one percent survey data, we measure the evolution of galaxy bias parameters for the DESI luminous red galaxy (LRG) and bright galaxy survey (BGS) samples. We find mild evolution in the LRGs in |$0.4 < z < 0.8$|⁠ , subdominant to the expected statistical errors. For BGS, we find less evolution for brighter absolute magnitude cuts, at the cost of reduced sample size. We find that for a redshift bin width |$\Delta z = 0.1$|⁠ , evolution effects on DESI Y1 GGL is negligible across all scales, all fiducial selection cuts, all fiducial redshift bins. Galaxy clustering is more sensitive to evolution due to the bias squared scaling. Nevertheless the redshift evolution effect is insignificant for clustering above the 1-halo scale of |$0.1h^{-1}$|  Mpc. For studies that wish to reliably access smaller scales, additional treatment of redshift evolution is likely needed. This study serves as a reference for GGL and clustering studies using the DESI Y1 sample. [ABSTRACT FROM AUTHOR]

We use angular clustering of luminous red galaxies from the Dark Energy Spectroscopic Instrument (DESI) imaging surveys to constrain the local primordial non-Gaussianity parameter f NL. Our sample comprises over 12 million targets, covering 14 000 deg2 of the sky, with redshifts in the range 0.2 < z < 1.35. We identify Galactic extinction, survey depth, and astronomical seeing as the primary sources of systematic error, and employ linear regression and artificial neural networks to alleviate non-cosmological excess clustering on large scales. Our methods are tested against simulations with and without f NL and systematics, showing superior performance of the neural network treatment. The neural network with a set of nine imaging property maps passes our systematic null test criteria, and is chosen as the fiducial treatment. Assuming the universality relation, we find |$f_{\rm NL} = 34^{+24(+50)}_{-44(-73)}$| at 68 per cent (95 per cent) confidence. We apply a series of robustness tests (e.g. cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. We study how the regression method biases the measured angular power spectrum and degrades the f NL constraining power. The use of the nine maps more than doubles the uncertainty compared to using only the three primary maps in the regression. Our results thus motivate the development of more efficient methods that avoid overcorrection, protect large-scale clustering information, and preserve constraining power. Additionally, our results encourage further studies of f NL with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics and lessen the degradation in the f NL uncertainty. [ABSTRACT FROM AUTHOR]

The Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) will explore the assembly history of the Milky Way by characterizing remnants of ancient dwarf galaxy accretion events and improving constraints on the distribution of dark matter in the outer halo. We present mock catalogues that reproduce the selection criteria of MWS and the format of the final MWS data set. These catalogues can be used to test methods for quantifying the properties of stellar halo substructure and reconstructing the Milky Way's accretion history with the MWS data, including the effects of halo-to-halo variance. The mock catalogues are based on a phase-space kernel expansion technique applied to star particles in the Auriga suite of six high-resolution lambda-cold dark matter magnetohydrodynamic zoom-in simulations. They include photometric properties (and associated errors) used in DESI target selection and the outputs of the MWS spectral analysis pipeline (radial velocity, metallicity, surface gravity, and temperature). They also include information from the underlying simulation, such as the total gravitational potential and information on the progenitors of accreted halo stars. We discuss how the subset of halo stars observable by MWS in these simulations corresponds to their true content and properties. These mock Milky Ways have rich accretion histories, resulting in a large number of substructures that span the whole stellar halo out to large distances and have substantial overlap in the space of orbital energy and angular momentum. [ABSTRACT FROM AUTHOR]

We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H α, H β, [O ii ], and [O iii ]) from a galaxy's rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman's rank correlation coefficient ρ s > 0.87 between predictions and observations for most lines. Using a non-linear dimensionality reduction technique, we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterize and account for biases in the spectroscopic training sets used for training and calibration of photo- z 's, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys. [ABSTRACT FROM AUTHOR]

We present the first comprehensive halo occupation distribution (HOD) analysis of the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey luminous red galaxy (LRG) and Quasi Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32  h −1 Mpc in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of |$f_\mathrm{sat} = 11\pm 1~{y{\ \mathrm{per\,cent}}}$|⁠ , a mean halo mass of |$\log _{10}\overline{M}_h/M_\odot =13.40^{+0.02}_{-0.02}$|⁠ , and a linear bias of |$b_\mathrm{lin} = 1.93_{-0.04}^{+0.06}$|⁠. For LRGs in 0.6 < z < 0.8, we find |$f_\mathrm{sat}=14\pm 1~{{\ \mathrm{per\,cent}}}$|⁠ , |$\log _{10}\overline{M}_h/M_\odot =13.24^{+0.02}_{-0.02}$|⁠ , and |$b_\mathrm{lin}=2.08_{-0.03}^{+0.03}$|⁠. For QSOs, we infer |$f_\mathrm{sat}=3^{+8}_{-2}\mathrm{per\,cent}$|⁠ , |$\log _{10}\overline{M}_h/M_\odot = 12.65^{+0.09}_{-0.04}$|⁠ , and |$b_\mathrm{lin} = 2.63_{-0.26}^{+0.37}$| in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high fidelity galaxy mocks, forming the basis of systematic tests for DESI Y1 cosmological analyses. We also study the redshift-evolution of the DESI LRG sample from z  = 0.4 up to z  = 1.1, revealling significant and interesting trends in mean halo mass, linear bias, and satellite fraction. [ABSTRACT FROM AUTHOR]

We present new spectroscopic and photometric follow-up observations of the known sample of extreme coronal line-emitting galaxies (ECLEs) identified in the Sloan Digital Sky Survey (SDSS). With these new data, observations of the ECLE sample now span a period of two decades following their initial SDSS detections. We confirm the non-recurrence of the iron coronal line signatures in five of the seven objects, further supporting their identification as the transient light echoes of tidal disruption events (TDEs). Photometric observations of these objects in optical bands show little overall evolution. In contrast, mid-infrared (MIR) observations show ongoing long-term declines consistent with power-law decay. The remaining two objects had been classified as active galactic nuclei (AGNs) with unusually strong coronal lines rather than being TDE related, given the persistence of the coronal lines in earlier follow-up spectra. We confirm this classification, with our spectra continuing to show the presence of strong, unchanged coronal line features and AGN-like MIR colours and behaviour. We have constructed spectral templates of both subtypes of ECLE to aid in distinguishing the likely origin of newly discovered ECLEs. We highlight the need for higher cadence, and more rapid, follow-up observations of such objects to better constrain their properties and evolution. We also discuss the relationships between ECLEs, TDEs, and other identified transients having significant MIR variability. [ABSTRACT FROM AUTHOR]

We estimate the redshift-dependent, anisotropic clustering signal in the Dark Energy Spectroscopic Instrument (DESI) Year 1 Survey created by tidal alignments of Luminous Red Galaxies (LRGs) and a selection-induced galaxy orientation bias. To this end, we measured the correlation between LRG shapes and the tidal field with DESI's Year 1 redshifts, as traced by LRGs and Emission-Line Galaxies. We also estimate the galaxy orientation bias of LRGs caused by DESI's aperture-based selection, and find it to increase by a factor of seven between redshifts 0.4−1.1 due to redder, fainter galaxies falling closer to DESI's imaging selection cuts. These effects combine to dampen measurements of the quadrupole of the correlation function (ξ2) caused by structure growth on scales of 10–80 h −1 Mpc by about 0.15 per cent for low redshifts (0.4 < z < 0.6) and 0.8 per cent for high (0.8 < z < 1.1), a significant fraction of DESI's error budget. We provide estimates of the ξ2 signal created by intrinsic alignments that can be used to correct this effect, which is necessary to meet DESI's forecasted precision on measuring the growth rate of structure. While imaging quality varies across DESI's footprint, we find no significant difference in this effect between imaging regions in the Legacy Imaging Survey. [ABSTRACT FROM AUTHOR]

Together with larger spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI), the precision of large-scale structure studies and thus the constraints on the cosmological parameters are rapidly improving. Therefore, one must build realistic simulations and robust covariance matrices. We build galaxy catalogues by applying a halo occupation distribution (HOD) model upon the FastPM simulations, such that the resulting galaxy clustering reproduces high-resolution N -body simulations. While the resolution and halo finder are different from the reference simulations, we reproduce the reference galaxy two-point clustering measurements – monopole and quadrupole – to a precision required by the DESI Year 1 emission line galaxy sample down to non-linear scales, i.e. |$k\lt 0.5\, h\, \mathrm{Mpc}^{-1}$| or |$s\gt 10\, \mathrm{Mpc}\, h^{-1}$|⁠. Furthermore, we compute covariance matrices based on the resulting FastPM galaxy clustering – monopole and quadrupole. We study for the first time the effect of fitting on Fourier conjugate (e.g. power spectrum) on the covariance matrix of the Fourier counterpart (e.g. correlation function). We estimate the uncertainties of the two parameters of a simple clustering model and observe a maximum variation of 20 per cent for the different covariance matrices. Nevertheless, for most studied scales the scatter is between 2 and 10  per cent. Consequently, using the current pipeline we can precisely reproduce the clustering of N -body simulations and the resulting covariance matrices provide robust uncertainty estimations against HOD fitting scenarios. We expect our methodology will be useful for the coming DESI data analyses and their extension for other studies. [ABSTRACT FROM AUTHOR]

We present fitcov an approach for accurate estimation of the covariance of two-point correlation functions that requires fewer mocks than the standard mock-based covariance. This can be achieved by dividing a set of mocks into jackknife regions and fitting the correction term first introduced in Mohammad & Percival (2022), such that the mean of the jackknife covariances corresponds to the one from the mocks. This extends the model beyond the shot-noise limited regime, allowing it to be used for denser samples of galaxies. We test the performance of our fitted jackknife approach, both in terms of accuracy and precision, using lognormal mocks with varying densities and approximate EZmocks mimicking the Dark Energy Spectroscopic Instrument LRG and ELG samples in the redshift range of z  = [0.8, 1.1]. We find that the Mohammad–Percival correction produces a bias in the two-point correlation function covariance matrix that grows with number density and that our fitted jackknife approach does not. We also study the effect of the covariance on the uncertainty of cosmological parameters by performing a full-shape analysis. We demonstrate that our fitted jackknife approach based on 25 mocks can recover unbiased and as precise cosmological parameters as the ones obtained from a covariance matrix based on 1000 or 1500 mocks, while the Mohammad–Percival correction produces uncertainties that are twice as large. The number of mocks required to obtain an accurate estimation of the covariance for the two-point correlation function is therefore reduced by a factor of 40–60. The fitcov code that accompanies this paper is available at this GitHub repository. [ABSTRACT FROM AUTHOR]

We perform SubHalo Abundance Matching (SHAM) studies on UNIT simulations with {σ, V ceil, v smear}-SHAM and {σ, V ceil, f sat}-SHAM. They are designed to reproduce the clustering on 5–30  |$\, {\, h^{-1}\, {\rm Mpc}}$| of luminous red galaxies (LRGs), emission-line galaxies (ELGs), and quasi-stellar objects (QSOs) at 0.4 < z < 3.5 from DESI (Dark Energy Spectroscopic Instrument) One Percent Survey. V ceil is the incompleteness of the massive host (sub)haloes and is the key to the generalized SHAM. v smear models the clustering effect of redshift uncertainties, providing measurements consistent with those from repeat observations. A free satellite fraction f sat is necessary to reproduce the clustering of ELGs. We find ELGs present a more complex galaxy–halo mass relation than LRGs reflected in their weak constraints on σ. LRGs, QSOs, and ELGs show increasing V ceil values, corresponding to the massive galaxy incompleteness of LRGs, the quenched star formation of ELGs and the quenched black hole accretion of QSOs. For LRGs, a Gaussian v smear presents a better profile for subsamples at redshift bins than a Lorentzian profile used for other tracers. The impact of the statistical redshift uncertainty on ELG clustering is negligible. The best-fitting satellite fraction for DESI ELGs is around 4 per cent, lower than previous estimations for ELGs. The mean halo mass log10(〈 M vir〉) in |${{\, h^{-1}\, \mbox{M}_\odot }}{}$| for LRGs, ELGs, and QSOs are 13.16 ± 0.01, 11.90 ± 0.06, and 12.66 ± 0.45, respectively. Our generalized SHAM algorithms facilitate the production of multitracer galaxy mocks for cosmological tests. [ABSTRACT FROM AUTHOR]

We present the one-dimensional Ly α forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises 26 330 quasar spectra, at redshift z > 2.1, contained in the DESI Early Data Release and the first 2 months of the main survey. We employ a Fast Fourier Transform (FFT) estimator and compare the resulting power spectrum to an alternative likelihood-based method in a companion paper. We investigate methodological and instrumental contaminants associated with the new DESI instrument, applying techniques similar to previous Sloan Digital Sky Survey (SDSS) measurements. We use synthetic data based on lognormal approximation to validate and correct our measurement. We compare our resulting power spectrum with previous SDSS and high-resolution measurements. With relatively small number statistics, we successfully perform the FFT measurement, which is already competitive in terms of the scale range. At the end of the DESI survey, we expect a five times larger Ly α forest sample than SDSS, providing an unprecedented precise one-dimensional power spectrum measurement. [ABSTRACT FROM AUTHOR]

Accurate quasar classifications and redshift measurements are increasingly important to precision cosmology experiments. Broad absorption line (BAL) features are present in 15–20 per cent of all quasars, and these features can introduce systematic redshift errors, and in extreme cases produce misclassifications. We quantitatively investigate the impact of BAL features on quasar classifications and redshift measurements with synthetic spectra that were designed to match observations by the Dark Energy Spectroscopic Instrument (DESI) survey. Over the course of 5 yr, DESI aims to measure spectra for 40 million galaxies and quasars, including nearly three million quasars. Our synthetic quasar spectra match the signal-to-noise ratio and redshift distributions of the first year of DESI observations, and include the same synthetic quasar spectra both with and without BAL features. We demonstrate that masking the locations of the BAL features decreases the redshift errors by about 1 per cent and reduces the number of catastrophic redshift errors by about 80 per cent. We conclude that identifying and masking BAL troughs should be a standard part of the redshift determination step for DESI and other large-scale spectroscopic surveys of quasars. [ABSTRACT FROM AUTHOR]

We present the first detection of the baryon acoustic oscillations (BAOs) signal obtained using unblinded data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). From a selected sample of 261 291 luminous red galaxies spanning the redshift interval 0.4 < z < 1.1 and covering 1651 square degrees with a 57.9  per cent completeness level, we report a ∼5σ level BAO detection and the measurement of the BAO location at a precision of 1.7  per cent. Using a bright galaxy sample of 109 523 galaxies in the redshift range 0.1 < z < 0.5, over 3677 square degrees with a 50.0  per cent completeness, we also detect the BAO feature at ∼3σ significance with a 2.6  per cent precision. These first BAO measurements represent an important milestone, acting as a quality control on the optimal performance of the complex robotically actuated, fibre-fed DESI spectrograph, as well as an early validation of the DESI spectroscopic pipeline and data management system. Based on these first promising results, we forecast that DESI is on target to achieve a high-significance BAO detection at sub-per cent precision with the completed 5-yr survey data, meeting the top-level science requirements on BAO measurements. This exquisite level of precision will set new standards in cosmology and confirm DESI as the most competitive BAO experiment for the remainder of this decade. [ABSTRACT FROM AUTHOR]

Phosphorylation reactions performed by protein kinases are one of the most studied post-translational modifications within cells. Much is understood about conserved residues within protein kinase domains that perform catalysis of the phosphotransfer reaction, yet the identity of the target substrates and downstream biological effects vary widely among cells, tissues, and organisms. Here, we characterize key residues essential for NUAK kinase activity in Drosophila melanogaster myogenesis and homeostasis. Creation of a NUAK kinase-dead mutation using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 results in lethality at the embryo to larval transition, while loss of NUAK catalytic function later in development produces aggregation of the chaperone protein αB-crystallin/CryAB in muscle tissue. Yeast 2-hybrid assays demonstrate a physical interaction between NUAK and CryAB. We further show that a phosphomimetic version of NUAK promotes the phosphorylation of CryAB and this post-translational modification occurs at 2 previously unidentified phosphosites that are conserved in the primary sequence of human CryAB. Mutation of these serine residues in D. melanogaster NUAK abolishes CryAB phosphorylation, thus, proving their necessity at the biochemical level. These studies together highlight the importance of kinase activity regulation and provide a platform to further explore muscle tissue proteostasis. [ABSTRACT FROM AUTHOR]

We describe the target selection and characteristics of the DESI Peculiar Velocity Survey, the largest survey of peculiar velocities (PVs) using both the fundamental plane (FP) and the Tully–Fisher (TF) relationship planned to date. We detail how we identify suitable early-type galaxies (ETGs) for the FP and suitable late-type galaxies (LTGs) for the TF relation using the photometric data provided by the DESI Legacy Imaging Survey DR9. Subsequently, we provide targets for 373 533 ETGs and 118 637 LTGs within the Dark Energy Spectroscopic Instrument (DESI) 5-yr footprint. We validate these photometric selections using existing morphological classifications. Furthermore, we demonstrate using survey validation data that DESI is able to measure the spectroscopic properties to sufficient precision to obtain PVs for our targets. Based on realistic DESI fibre assignment simulations and spectroscopic success rates, we predict the final DESI PV Survey will obtain ∼133 000 FP-based and ∼53 000 TF-based PV measurements over an area of 14 000 deg2. We forecast the ability of using these data to measure the clustering of galaxy positions and PVs from the combined DESI PV and Bright Galaxy Surveys (BGS), which allows for cancellation of cosmic variance at low redshifts. With these forecasts, we anticipate a 4 per cent statistical measurement on the growth rate of structure at z < 0.15. This is over two times better than achievable with redshifts from the BGS alone. The combined DESI PV and BGS will enable the most precise tests to date of the time and scale dependence of large-scale structure growth at z < 0.15. [ABSTRACT FROM AUTHOR]

The shear measurement from the Dark Energy Camera Legacy Survey (DECaLS) provides an excellent opportunity for galaxy–galaxy lensing study with the Dark Energy Spectroscopic Instrument (DESI) galaxies, given the large (∼9000 deg2) sky overlap. We explore this potential by combining the DESI 1 per cent survey and DECaLS Data Release 8 (DR8). With ∼106 deg2 sky overlap, we achieve significant detection of galaxy–galaxy lensing for Bright Galaxy Survey (BGS) and luminous red galaxy (LRG) as lenses. Scaled to the full BGS sample, we expect the statistical errors to improve from |$18(12)\,{\rm per \ cent}$| to a promising level of |$2(1.3)\,{\rm per \ cent}$| at |$\theta \gt 8\,\mathrm{ arcmin} \, (\lt 8\,\mathrm{ arcmin})$|⁠. This brings stronger requirements for future systematics control. To fully realize such potential, we need to control the residual multiplicative shear bias | m | < 0.006 and the bias in the mean redshift |Δ z | < 0.008, requiring the introduced bias in the measurement is <0.31σ. We also expect significant detection of galaxy–galaxy lensing with DESI LRG/emission line galaxy (ELG) full samples as lenses, and cosmic magnification of ELG through cross-correlation with low-redshift DECaLS shear. If such systematical error control can be achieved, we find the advantages of DECaLS, comparing with the Kilo Degree Survey (KiDS) and the Hyper Suprime-Cam (HSC), are at low redshift, large scale, and in measuring the shear ratio (to σ R ∼ 0.04) and cosmic magnification. [ABSTRACT FROM AUTHOR]

We present an extended validation of semi-analytical, semi-empirical covariance matrices for the two-point correlation function (2PCF) on simulated catalogs representative of luminous red galaxies (LRGs) data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). We run the pipeline on multiple effective Zel'dovich (EZ) mock galaxy catalogs with the corresponding cuts applied and compare the results with the mock sample covariance to assess the accuracy and its fluctuations. We propose an extension of the previously developed formalism for catalogs processed with standard reconstruction algorithms. We consider methods for comparing covariance matrices in detail, highlighting their interpretation and statistical properties caused by sample variance, in particular, non-trivial expectation values of certain metrics even when the external covariance estimate is perfect. With improved mocks and validation techniques, we confirm a good agreement between our predictions and sample covariance. This allows one to generate covariance matrices for comparable data sets without the need to create numerous mock galaxy catalogs with matching clustering, only requiring 2PCF measurements from the data itself. The code used in this paper is publicly available at https://github.com/oliverphilcox/RascalC. [ABSTRACT FROM AUTHOR]

We measure the tidal alignment of the major axes of luminous red galaxies (LRGs) from the Legacy Imaging Survey and use it to infer the artificial redshift-space distortion signature that will arise from an orientation-dependent, surface-brightness selection in the Dark Energy Spectroscopic Instrument (DESI) survey. Using photometric redshifts to downweight the shape–density correlations due to weak lensing, we measure the intrinsic tidal alignment of LRGs. Separately, we estimate the net polarization of LRG orientations from DESI's fibre-magnitude target selection to be of order 10−2 along the line of sight. Using these measurements and a linear tidal model, we forecast a 0.5 per cent fractional decrease on the quadrupole of the two-point correlation function for projected separations of 40–80 h −1 Mpc. We also use a halo catalogue from the Abacussummit cosmological simulation suite to reproduce this false quadrupole. [ABSTRACT FROM AUTHOR]

We present the VST ATLAS Quasar Survey, consisting of ∼1229 000 quasar (QSO) candidates with 16 < g < 22.5 over ∼4700 deg2. The catalogue is based on VST ATLAS+NEOWISE imaging surveys and aims to reach a QSO sky density of 130 deg−2 for |$z$| < 2.2 and ∼30 deg−2 for |$z$| > 2.2. To guide our selection, we use X-ray/UV/optical/MIR data in the extended William Herschel Deep Field (WHDF) where we find a g < 22.5 broad-line QSO density of 269 ± 67 deg−2, roughly consistent with the expected ∼196 deg−2. We find that ∼25 per cent of our QSOs are morphologically classed as optically extended. Overall, we find that in these deep data, MIR, UV, and X-ray selections are ∼70–90 per cent complete while X-ray suffers less contamination than MIR and UV. MIR is however more sensitive than X-ray or UV to |$z$| > 2.2 QSOs at g < 22.5 and the |$S_X(0.5-10\, {\rm keV})\gt 1\times 10^{-14}$| ergs cm−2 s−1 limit of eROSITA. We adjust the selection criteria from our previous 2QDES pilot survey and prioritize VST ATLAS candidates that show both UV and MIR excess, also selecting candidates initially classified as extended. We test our selections using data from DESI (which will be released in DR1) and 2dF to estimate the efficiency and completeness, and we use ANNz2 to determine photometric redshifts. Applying over the ∼4700 deg2 ATLAS area gives us |$\sim 917\,000\, z\lt 2.2$| QSO candidates of which 472 000 are likely to be |$z$| < 2.2 QSOs, implying a sky density of ∼100 deg−2, which our WHDF analysis suggests will rise to at least 130 deg−2 when eROSITA X-ray candidates are included. At |$z$| > 2.2, we find ∼310() 000 candidates, of which 169 000 are likely to be QSOs for a sky density of ∼36 deg−2. [ABSTRACT FROM AUTHOR]

We investigate using three-point statistics in constraining the galaxy–halo connection. We show that for some galaxy samples, the constraints on the halo occupation distribution parameters are dominated by the three-point function signal (over its two-point counterpart). We demonstrate this on mock catalogues corresponding to the Luminous red galaxies (LRGs), Emission-line galaxies (ELGs), and quasars (QSOs) targeted by the Dark Energy Spectroscopic Instrument (DESI) Survey. The projected three-point function for triangle sides less up to 20  h −1 Mpc measured from a cubic Gpc of data can constrain the characteristic minimum mass of the LRGs with a preci sion of 0.46 per cent. For comparison, similar constraints from the projected two-point function are 1.55 per cent. The improvements for the ELGs and QSOs targets are more modest. In the case of the QSOs, it is caused by the high shot-noise of the sample, and in the case of the ELGs, it is caused by the range of halo masses of the host haloes. The most time-consuming part of our pipeline is the measurement of the three-point functions. We adopt a tabulation method, proposed in earlier works for the two-point function, to significantly reduce the required compute time for the three-point analysis. [ABSTRACT FROM AUTHOR]

Analysis of large galaxy surveys requires confidence in the robustness of numerical simulation methods. The simulations are used to construct mock galaxy catalogues to validate data analysis pipelines and identify potential systematics. We compare three N -body simulation codes, abacus , gadget-2 , and swift , to investigate the regimes in which their results agree. We run N -body simulations at three different mass resolutions, 6.25 × 108, 2.11 × 109, and 5.00 × 109  h −1 M⊙, matching phases to reduce the noise within the comparisons. We find systematic errors in the halo clustering between different codes are smaller than the Dark Energy Spectroscopic Instrument (DESI) statistical error for |$s\ \gt\ 20\ h^{-1}$|  Mpc in the correlation function in redshift space. Through the resolution comparison we find that simulations run with a mass resolution of 2.1 × 109  h −1 M⊙ are sufficiently converged for systematic effects in the halo clustering to be smaller than the DESI statistical error at scales larger than |$20\ h^{-1}$|  Mpc. These findings show that the simulations are robust for extracting cosmological information from large scales which is the key goal of the DESI survey. Comparing matter power spectra, we find the codes agree to within 1 per cent for k ≤ 10  h  Mpc−1. We also run a comparison of three initial condition generation codes and find good agreement. In addition, we include a quasi- N -body code, FastPM, since we plan use it for certain DESI analyses. The impact of the halo definition and galaxy–halo relation will be presented in a follow-up study. [ABSTRACT FROM AUTHOR]

Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches |$\sim 20\, h^{-3}\, \mathrm{Gpc}^{3}$|⁠. It is a great challenge to prepare high-resolution simulations with a much larger volume for validating the DESI analysis pipelines. AbacusSummit is a suite of high-resolution dark-matter-only simulations designed for this purpose, with |$200\, h^{-3}\, \mathrm{Gpc}^{3}$| (10 times DESI volume) for the base cosmology. However, further efforts need to be done to provide a more precise analysis of the data and to cover also other cosmologies. Recently, the CARPool method was proposed to use paired accurate and approximate simulations to achieve high statistical precision with a limited number of high-resolution simulations. Relying on this technique, we propose to use fast quasi- N -body solvers combined with accurate simulations to produce accurate summary statistics. This enables us to obtain 100 times smaller variance than the expected DESI statistical variance at the scales we are interested in, e.g. |$k \lt 0.3\, h\, \mathrm{Mpc}^{-1}$| for the halo power spectrum. In addition, it can significantly suppress the sample variance of the halo bispectrum. We further generalize the method for other cosmologies with only one realization in AbacusSummit suite to extend the effective volume ∼20 times. In summary, our proposed strategy of combining high-fidelity simulations with fast approximate gravity solvers and a series of variance suppression techniques sets the path for a robust cosmological analysis of galaxy survey data. [ABSTRACT FROM AUTHOR]

We characterize the selection cuts and clustering properties of a magnitude-limited sample of bright galaxies that is part of the Bright Galaxy Survey (BGS) of the Dark Energy Spectroscopic Instrument (DESI) using the ninth data release of the Legacy Imaging Surveys (DR9). We describe changes in the DR9 selection compared to the DR8 one and we also compare the DR9 selection in three distinct regions: BASS/MzLS in the north Galactic Cap (NGC), DECaLS in the NGC, and DECaLS in the south Galactic Cap (SGC). We investigate the systematics associated with the selection and assess its completeness by matching the BGS targets with the Galaxy and Mass Assembly (GAMA) survey. We measure the angular clustering for the overall bright sample (r mag ≤ 19.5) and as function of apparent magnitude and colour. This enables to determine the clustering strength r 0 and slope γ by fitting a power-law model that can be used to generate accurate mock catalogues for this tracer. We use a counts-in-cells technique to explore higher order statistics and cross-correlations with external spectroscopic data sets in order to check the evolution of the clustering with redshift and the redshift distribution of the BGS targets using clustering redshifts. While this work validates the properties of the BGS bright targets, the final target selection pipeline and clustering properties of the entire DESI BGS will be fully characterized and validated with the spectroscopic data of Survey Validation. [ABSTRACT FROM AUTHOR]

Accurate forecasting of space weather requires knowledge of the source regions where solar energetic particles (SEP) and eruptive events originate. Recent work has linked several major SEP events in 2014, January, to specific features in the host active region (AR 11944). In particular, plasma composition measurements in and around the footpoints of hot, coronal loops in the core of the active region were able to explain the values later measured in situ by the Wind spacecraft. Due to important differences in elemental composition between SEPs and the solar wind, the magnitude of the Si/S elemental abundance ratio emerged as a key diagnostic of SEP seed population and solar wind source locations. We seek to understand if the results are typical of other active regions, even if they are not solar wind sources or SEP productive. In this paper, we use a novel composition analysis technique, together with an evolutionary magnetic field model, in a new approach to investigate a typical solar active region (AR 11150), and identify the locations of highly fractionated (high Si/S abundance ratio) plasma. Material confined near the footpoints of coronal loops, as in AR 11944, that in this case have expanded to the AR periphery, show the signature, and can be released from magnetic field opened by reconnection at the AR boundary. Since the fundamental characteristics of closed field loops being opened at the AR boundary is typical of active regions, this process is likely to be general. [ABSTRACT FROM AUTHOR]

Previous studies have reported substantial involvement of the noradrenergic system in Parkinson's disease. Neuromelanin-sensitive MRI sequences and PET tracers have become available to visualize the cell bodies in the locus coeruleus and the density of noradrenergic terminal transporters. Combining these methods, we investigated the relationship of neurodegeneration in these distinct compartments in Parkinson's disease. We examined 93 subjects (40 healthy controls and 53 Parkinson's disease patients) with neuromelanin-sensitive turbo spin-echo MRI and calculated locus coeruleus-to-pons signal contrasts. Voxels with the highest intensities were extracted from published locus coeruleus coordinates transformed to individual MRI. To also investigate a potential spatial pattern of locus coeruleus degeneration, we extracted the highest signal intensities from the rostral, middle, and caudal third of the locus coeruleus. Additionally, a study-specific probabilistic map of the locus coeruleus was created and used to extract mean MRI contrast from the entire locus coeruleus and each rostro-caudal subdivision. Locus coeruleus volumes were measured using manual segmentations. A subset of 73 subjects had 11C-MeNER PET to determine noradrenaline transporter density, and distribution volume ratios of noradrenaline transporter-rich regions were computed. Patients with Parkinson's disease showed reduced locus coeruleus MRI contrast independently of the selected method (voxel approaches: P < 0.0001, P < 0.001; probabilistic map: P < 0.05), specifically on the clinically-defined most affected side (P < 0.05), and reduced locus coeruleus volume (P < 0.0001). Reduced MRI contrast was confined to the middle and caudal locus coeruleus (voxel approach, rostral: P = 0.48, middle: P < 0.0001, and caudal: P < 0.05; probabilistic map, rostral: P = 0.90, middle: P < 0.01, and caudal: P < 0.05). The noradrenaline transporter density was lower in patients with Parkinson's diseasein all examined regions (group effect P < 0.0001). No significant correlation was observed between locus coeruleus MRI contrast and noradrenaline transporter density. In contrast, the individual ratios of noradrenaline transporter density and locus coeruleus MRI contrast were lower in Parkinson's disease patients in all examined regions (group effect P < 0.001). Our multimodal imaging approach revealed pronounced noradrenergic terminal loss relative to cellular locus coeruleus degeneration in Parkinson's disease; the latter followed a distinct spatial pattern with the middle-caudal portion being more affected than the rostral part. The data shed first light on the interaction between the axonal and cell body compartments and their differential susceptibility to neurodegeneration in Parkinson's disease, which may eventually direct research towards potential novel treatment approaches. [ABSTRACT FROM AUTHOR]

During the prodromal period of Parkinson's disease and other α-synucleinopathy-related parkinsonisms, neurodegeneration is thought to progressively affect deep brain nuclei, such as the locus coeruleus, caudal raphe nucleus, substantia nigra, and the forebrain nucleus basalis of Meynert. Besides their involvement in the regulation of mood, sleep, behaviour, and memory functions, these nuclei also innervate parenchymal arterioles and capillaries throughout the cortex, possibly to ensure that oxygen supplies are adjusted according to the needs of neural activity. The aim of this study was to examine whether patients with isolated REM sleep behaviour disorder, a parasomnia considered to be a prodromal phenotype of α-synucleinopathies, reveal microvascular flow disturbances consistent with disrupted central blood flow control. We applied dynamic susceptibility contrast MRI to characterize the microscopic distribution of cerebral blood flow in the cortex of 20 polysomnographic-confirmed patients with isolated REM sleep behaviour disorder (17 males, age range: 54-77 years) and 25 healthy matched controls (25 males, age range: 58-76 years). Patients and controls were cognitively tested by Montreal Cognitive Assessment and Mini Mental State Examination. Results revealed profound hypoperfusion and microvascular flow disturbances throughout the cortex in patients compared to controls. In patients, the microvascular flow disturbances were seen in cortical areas associated with language comprehension, visual processing and recognition and were associated with impaired cognitive performance. We conclude that cortical blood flow abnormalities, possibly related to impaired neurogenic control, are present in patients with isolated REM sleep behaviour disorder and associated with cognitive dysfunction. We hypothesize that pharmacological restoration of perivascular neurotransmitter levels could help maintain cognitive function in patients with this prodromal phenotype of parkinsonism. [ABSTRACT FROM AUTHOR]

We present measurements of the redshift-dependent clustering of a DESI-like luminous red galaxy (LRG) sample selected from the Legacy Survey imaging data set, and use the halo occupation distribution (HOD) framework to fit the clustering signal. The photometric LRG sample in this study contains 2.7 million objects over the redshift range of 0.4 < z < 0.9 over 5655 deg2. We have developed new photometric redshift (photo- z) estimates using the Legacy Survey DECam and WISE photometry, with σNMAD = 0.02 precision for LRGs. We compute the projected correlation function using new methods that maximize signal-to-noise ratio while incorporating redshift uncertainties. We present a novel algorithm for dividing irregular survey geometries into equal-area patches for jackknife resampling. For a five-parameter HOD model fit using the MultiDark halo catalogue, we find that there is little evolution in HOD parameters except at the highest redshifts. The inferred large-scale structure bias is largely consistent with constant clustering amplitude over time. In an appendix, we explore limitations of Markov chain Monte Carlo fitting using stochastic likelihood estimates resulting from applying HOD methods to N -body catalogues, and present a new technique for finding best-fitting parameters in this situation. Accompanying this paper, we have released the Photometric Redshifts for the Legacy Surveys catalogue of photo- z 's obtained by applying the methods used in this work to the full Legacy Survey Data Release 8 data set. This catalogue provides accurate photometric redshifts for objects with z < 21 over more than 16 000 deg2 of sky. [ABSTRACT FROM AUTHOR]

Periodically variable quasars have been suggested as close binary supermassive black holes. We present a systematic search for periodic light curves in 625 spectroscopically confirmed quasars with a median redshift of 1.8 in a 4.6 deg2 overlapping region of the Dark Energy Survey Supernova (DES-SN) fields and the Sloan Digital Sky Survey Stripe 82 (SDSS-S82). Our sample has a unique 20-yr long multicolour (griz) light curve enabled by combining DES-SN Y6 observations with archival SDSS-S82 data. The deep imaging allows us to search for periodic light curves in less luminous quasars (down to r ∼23.5 mag) powered by less massive black holes (with masses ≳ 108.5 M ⊙) at high redshift for the first time. We find five candidates with significant (at >99.74 per cent single-frequency significance in at least two bands with a global p-value of ∼7 × 10−4–3 × 10−3 accounting for the look-elsewhere effect) periodicity with observed periods of ∼3–5 yr (i.e. 1–2 yr in rest frame) having ∼4–6 cycles spanned by the observations. If all five candidates are periodically variable quasars, this translates into a detection rate of |${\sim }0.8^{+0.5}_{-0.3}$|  per cent or |${\sim }1.1^{+0.7}_{-0.5}$| quasar per deg2. Our detection rate is 4–80 times larger than those found by previous searches using shallower surveys over larger areas. This discrepancy is likely caused by differences in the quasar populations probed and the survey data qualities. We discuss implications on the future direct detection of low-frequency gravitational waves. Continued photometric monitoring will further assess the robustness and characteristics of these candidate periodic quasars to determine their physical origins. [ABSTRACT FROM AUTHOR]

Parkinson's disease is characterized by the presence of abnormal, intraneuronal α-synuclein aggregates, which may propagate from cell-to-cell in a prion-like manner. However, it remains uncertain where the initial α-synuclein aggregates originate. We have hypothesized that Parkinson's disease comprises two subtypes. A brain-first (top-down) type, where α-synuclein pathology initially arises in the brain with secondary spreading to the peripheral autonomic nervous system; and a body-first (bottom-up) type, where the pathology originates in the enteric or peripheral autonomic nervous system and then spreads to the brain. We also hypothesized that isolated REM sleep behaviour disorder (iRBD) is a prodromal phenotype for the body-first type. Using multimodal imaging, we tested the hypothesis by quantifying neuronal dysfunction in structures corresponding to Braak stages I, II and III involvement in three distinct patient groups. We included 37 consecutive de novo patients with Parkinson's disease into this case-control PET study. Patients with Parkinson's disease were divided into 24 RBD-negative (PDRBD-) and 13 RBD-positive cases (PDRBD+) and a comparator group of 22 iRBD patients. We used 11C-donepezil PET/CT to assess cholinergic (parasympathetic) innervation, 123I-metaiodobenzylguanidine (MIBG) scintigraphy to measure cardiac sympathetic innervation, neuromelanin-sensitive MRI to measure the integrity of locus coeruleus pigmented neurons, and 18F-dihydroxyphenylalanine (FDOPA) PET to assess putaminal dopamine storage capacity. Colon volume and transit times were assessed with CT scans and radiopaque markers. Imaging data from the three groups were interrogated with ANOVA and Kruskal-Wallis tests corrected for multiple comparisons. The PDRBD- and PDRBD+ groups showed similar marked reductions in putaminal FDOPA-specific uptake, whereas two-thirds of iRBD patients had normal scans (P < 10-13, ANOVA). When compared to the PDRBD- patients, the PDRBD+ and iRBD patients showed reduced mean MIBG heart:mediastinum ratios (P < 10-5, ANOVA) and colon 11C-donepezil standard uptake values (P = 0.008, ANOVA). The PDRBD+ group trended towards a reduced mean MRI locus coeruleus: pons ratio compared to PDRBD- (P = 0.07, t-test). In comparison to the other groups, the PDRBD+ group also had enlarged colon volumes (P < 0.001, ANOVA) and delayed colonic transit times (P = 0.01, Kruskal-Wallis). The combined iRBD and PDRBD+ patient data were compatible with a body-first trajectory, characterized by initial loss of cardiac MIBG signal and 11C-colonic donepezil signal followed by loss of putaminal FDOPA uptake. In contrast, the PDRBD- data were compatible with a brain-first trajectory, characterized by primary loss of putaminal FDOPA uptake followed by a secondary loss of cardiac MIBG signal and 11C-donepezil signal. These findings support the existence of brain-first and body-first subtypes of Parkinson's disease. [ABSTRACT FROM AUTHOR]

The biologically active estrogen estradiol has important roles in adult brain physiology and sexual behavior. A single gene, Cyp19a1 , encodes aromatase, the enzyme that catalyzes the conversion of testosterone to estradiol in the testis and brain of male mice. Estradiol formation was shown to regulate sexual activity in various species, but the relative contributions to sexual behavior of estrogen that arises in the brain versus from the gonads remained unclear. To determine the role of brain aromatase in regulating male sexual activity, we generated a brain-specific aromatase knockout (bArKO) mouse. A newly generated whole-body total aromatase knockout mouse of the same genetic background served as a positive control. Here we demonstrate that local aromatase expression and estrogen production in the brain is partially required for male sexual behavior and sex hormone homeostasis. Male bArKO mice exhibited decreased sexual activity in the presence of strikingly elevated circulating testosterone. In castrated adult bArKO mice, administration of testosterone only partially restored sexual behavior; full sexual behavior, however, was achieved only when both estradiol and testosterone were administered together. Thus, aromatase in the brain is, in part, necessary for testosterone-dependent male sexual activity. We also found that brain aromatase is required for negative feedback regulation of circulating testosterone of testicular origin. Our findings suggest testosterone activates male sexual behavior in part via conversion to estradiol in the brain. These studies provide foundational evidence that sexual behavior may be modified through inhibition or enhancement of brain aromatase enzyme activity and/or utilization of selective estrogen receptor modulators. [ABSTRACT FROM AUTHOR]

We report the identification of a low-mass active galactic nucleus (AGN), DES J0218−0430, in a redshift z  = 0.823 galaxy in the Dark Energy Survey (DES) Supernova field. We select DES J0218−0430 as an AGN candidate by characterizing its long-term optical variability alone based on DES optical broad-band light curves spanning over 6 yr. An archival optical spectrum from the fourth phase of the Sloan Digital Sky Survey shows both broad Mg  ii and broad H β lines, confirming its nature as a broad-line AGN. Archival XMM–Newton X-ray observations suggest an intrinsic hard X-ray luminosity of |$L_{{\rm 2-12\, keV}}\approx 7.6\pm 0.4\times 10^{43}$| erg s−1, which exceeds those of the most X-ray luminous starburst galaxies, in support of an AGN driving the optical variability. Based on the broad H β from SDSS spectrum, we estimate a virial black hole (BH) mass of M • ≈ 106.43–106.72 M⊙ (with the error denoting the systematic uncertainty from different calibrations), consistent with the estimation from OzDES, making it the lowest mass AGN with redshift > 0.4 detected in optical. We estimate the host galaxy stellar mass to be M * ≈ 1010.5 ± 0.3 M⊙ based on modelling the multiwavelength spectral energy distribution. DES J0218−0430 extends the M •– M * relation observed in luminous AGNs at z  ∼ 1 to masses lower than being probed by previous work. Our work demonstrates the feasibility of using optical variability to identify low-mass AGNs at higher redshift in deeper synoptic surveys with direct implications for the upcoming Legacy Survey of Space and Time at Vera C. Rubin Observatory. [ABSTRACT FROM AUTHOR]

We evaluate the impact of imaging systematics on the clustering of luminous red galaxies (LRG), emission-line galaxies (ELG), and quasars (QSO) targeted for the upcoming Dark Energy Spectroscopic Instrument (DESI) survey. Using Data Release 7 of the DECam Legacy Survey, we study the effects of astrophysical foregrounds, stellar contamination, differences between north galactic cap and south galactic cap measurements, and variations in imaging depth, stellar density, galactic extinction, seeing, airmass, sky brightness, and exposure time before presenting survey masks and weights to mitigate these effects. With our sanitized samples in hand, we conduct a preliminary analysis of the clustering amplitude and evolution of the DESI main targets. From measurements of the angular correlation functions, we determine power law fits |$r_0 = 7.78 \pm 0.26\, h^{-1}$| Mpc, γ  = 1.98 ± 0.02 for LRGs and |$r_0 = 5.45 \pm 0.1\, h^{-1}$| Mpc, γ  = 1.54 ± 0.01 for ELGs. Additionally, from the angular power spectra, we measure the linear biases and model the scale-dependent biases in the weakly non-linear regime. Both sets of clustering measurements show good agreement with survey requirements for LRGs and ELGs, attesting that these samples will enable DESI to achieve precise cosmological constraints. We also present clustering as a function of magnitude, use cross-correlations with external spectroscopy to infer dN/dz and measure clustering as a function of luminosity, and probe higher order clustering statistics through counts-in-cells moments. [ABSTRACT FROM AUTHOR]

We present new Gemini/GMOS optical spectroscopy of 16 extreme variability quasars (EVQs) that dimmed by more than 1.5 mag in the g band between the Sloan Digital Sky Survey (SDSS) and the Dark Energy Survey epochs (separated by a few years in the quasar rest frame). These EVQs are selected from quasars in the SDSS Stripe 82 region, covering a redshift range of 0.5 < z < 2.1. Nearly half of these EVQs brightened significantly (by more than 0.5 mag in the g band) in a few years after reaching their previous faintest state, and some EVQs showed rapid (non-blazar) variations of greater than 1–2 mag on time-scales of only months. To increase sample statistics, we use a supplemental sample of 33 EVQs with multi-epoch spectra from SDSS that cover the broad Mg  ii  λ2798 line. Leveraging on the large dynamic range in continuum variability between the multi-epoch spectra, we explore the associated variations in the broad Mg  ii line, whose variability properties have not been well studied before. The broad Mg  ii flux varies in the same direction as the continuum flux, albeit with a smaller amplitude, which indicates at least some portion of Mg  ii is reverberating to continuum changes. However, the full width at half-maximum (FWHM) of Mg  ii does not vary accordingly as continuum changes for most objects in the sample, in contrast to the case of the broad Balmer lines. Using the width of broad Mg  ii to estimate the black hole mass with single epoch spectra therefore introduces a luminosity-dependent bias. [ABSTRACT FROM AUTHOR]

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or an investigation for maximizing their effectiveness. We carry out a comparison between several common machine learning methods for galaxy classification [Convolutional Neural Network (CNN), K-nearest neighbour, logistic regression, Support Vector Machine, Random Forest, and Neural Networks] by using Dark Energy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project (GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of ∼2800 galaxies with visual classification from GZ1, we reach an accuracy of ∼0.99 for the morphological classification of ellipticals and spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both ellipticals and spirals. We confirm that ∼2.5 per cent galaxies are misclassified by GZ1 in our study. After correcting these galaxies' labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result). [ABSTRACT FROM AUTHOR]

Introduction: Live attenuated zoster vaccine (Zostavax) was used to test the hypothesis that constitutive level of interleukin 10 (IL-10), which may be high in elderly subjects, impairs vaccine efficacy. If constitutive IL-10 impairs vaccine efficacy, the effectiveness of viral vaccines might be improved by transient inhibition of IL-10 before vaccination.Methods: Zostavax was given to 26 patients (age, 60-80 years). IL-10 and immunity to varicella zoster virus (VZV) were measured at baseline and after vaccination. Fluorescent antibody to membrane antigen (FAMA) assays and glycoprotein enzyme-linked immunosorbent assays (gpELISAs) were used to assess humoral immunity; anti-varicella virus T-cell responses were studied in a subset of subjects. In a prospective animal model, T-cell responses to chimeric vaccines against lymphocytic choriomeningitis virus (LCMV) were assessed in mice that express or lack IL-10.Results: FAMA assays revealed significant boosting (by 4-fold) of humoral immunity, which occurred only in subjects (10 of 26) with a low constitutive IL-10 level (ie, <20 pg/mL); moreover, the Zostavax-induced FAMA and gpELISA responses were inversely related to the constitutive IL-10 level. Significant VZV-specific T-cell responses followed vaccination only in subjects with a low constitutive IL-10 level. Vaccine-induced LCMV-specific T-cell responses in mice lacking IL-10 were greater than in wild-type animals.Conclusions: A high constitutive IL-10 level adversely affects vaccine efficacy. [ABSTRACT FROM AUTHOR]

The Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) will be a survey of bright, low-redshift galaxies, which is planned to cover an area of |${\sim } 14\, 000$| square degrees in three passes. Each pass will cover the survey area with ∼2000 pointings, each of area ∼8 square degrees. The BGS is currently proposed to consist of a bright high priority sample to an r -band magnitude limit r  ∼ 19.5, with a fainter low priority sample to r  ∼ 20. The geometry of the DESI fibre positioners in the focal plane of the telescope affects the completeness of the survey and has a non-trivial impact on clustering measurements. Using a BGS mock catalogue, we show that completeness due to fibre assignment primarily depends on the surface density of galaxies. Completeness is high (>95 per cent) in low-density regions, but very low (<10 per cent) in the centre of massive clusters. We apply the pair inverse probability (PIP) weighting correction to clustering measurements from a BGS mock which has been through the fibre assignment algorithm. This method is only unbiased if it is possible to observe every galaxy pair. To facilitate this, we randomly promote a small fraction of the fainter sample to be high priority, and dither the set of tile positions by a small angle. We show that inverse pair weighting combined with angular upweighting provides an unbiased correction to galaxy clustering measurements for the complete three pass survey, and also after one pass, which is highly incomplete. [ABSTRACT FROM AUTHOR]

Using stellar population models, we predicted that the Dark Energy Survey (DES) – due to its special combination of area (5000 deg2) and depth (i  = 24.3) – would be in the position to detect massive (≳1011 M⊙) galaxies at |$z$|  ∼ 4. We confront those theoretical calculations with the first ∼150 deg2 of DES data reaching nominal depth. From a catalogue containing ∼5 million sources, ∼26 000 were found to have observed-frame g − r versus  r − i colours within the locus predicted for |$z$|  ∼ 4 massive galaxies. We further removed contamination by stars and artefacts, obtaining 606 galaxies lining up by the model selection box. We obtained their photometric redshifts and physical properties by fitting model templates spanning a wide range of star formation histories, reddening and redshift. Key to constrain the models is the addition, to the optical DES bands g, r, i, |$z$|⁠, and Y, of near-IR J, H, Ks data from the Vista Hemisphere Survey. We further applied several quality cuts to the fitting results, including goodness of fit and a unimodal redshift probability distribution. We finally select 233 candidates whose photometric redshift probability distribution function peaks around |$z$|  ∼ 4, have high stellar masses [log (M */M⊙) ∼ 11.7 for a Salpeter IMF] and ages around 0.1 Gyr, i.e. formation redshift around 5. These properties match those of the progenitors of the most massive galaxies in the local Universe. This is an ideal sample for spectroscopic follow-up to select the fraction of galaxies which are truly at high redshift. These initial results and those at the survey completion, which we shall push to higher redshifts, will set unprecedented constraints on galaxy formation, evolution, and the re-ionization epoch. [ABSTRACT FROM AUTHOR]

The Emission Line Galaxy survey made by the Dark Energy Spectroscopic Instrument (DESI) survey will be created from five passes of the instrument on the sky. On each pass, the constrained mobility of the ends of the fibres in the DESI focal plane means that the angular distribution of targets that can be observed is limited. Thus, the clustering of samples constructed using a limited number of passes will be strongly affected by missing targets. In two recent papers, we showed how the effect of missing galaxies can be corrected when calculating the correlation function using a weighting scheme for pairs. Using mock galaxy catalogues we now show that this method provides an unbiased estimator of the true correlation function for the DESI survey after any number of passes. We use multiple mocks to determine the expected errors given one to four passes, compared to an idealized survey observing an equivalent number of randomly selected targets. On BAO scales, we find that the error is a factor of 2 worse after one pass, but that after three or more passes, the errors are very similar. Thus, we find that the fibre assignment strategy enforced by the design of DESI will not affect the cosmological measurements to be made by the survey, and can be removed as a potential risk for this experiment. [ABSTRACT FROM AUTHOR]

Alzheimer's disease is characterized by the histopathological presence of amyloid-β plaques and tau-containing neurofibrillary tangles. Microglial activation is also a recognized pathological component. The relationship between microglial activation and protein aggregation is still debated. We investigated the relationship between amyloid plaques, tau tangles and activated microglia using PET imaging. Fifty-one subjects (19 healthy controls, 16 mild cognitive impairment and 16 Alzheimer's disease subjects) participated in the study. All subjects had neuropsychometric testing, MRI, amyloid (18F-flutemetamol), and microglial (11C-PBR28) PET. All subjects with mild cognitive impairment and Alzheimer's disease and eight of the controls had tau (18F-AV1451) PET. 11C-PBR28 PET was analysed using Logan graphical analysis with an arterial plasma input function, while 18F-flutemetamol and 18F-AV1451 PET were analysed as target:cerebellar ratios to create parametric standardized uptake value ratio maps. Biological parametric mapping in the Statistical Parametric Mapping platform was used to examine correlations between uptake of tracers at a voxel-level. There were significant widespread clusters of positive correlation between levels of microglial activation and tau aggregation in both the mild cognitive impairment (amyloid-positive and amyloid-negative) and Alzheimer's disease subjects. The correlations were stronger in Alzheimer's disease than in mild cognitive impairment, suggesting that these pathologies increase together as disease progresses. Levels of microglial activation and amyloid deposition were also correlated, although in a different spatial distribution; correlations were stronger in mild cognitive impairment than Alzheimer's subjects, in line with a plateauing of amyloid load with disease progression. Clusters of positive correlations between microglial activation and protein aggregation often targeted similar areas of association cortex, indicating that all three processes are present in specific vulnerable brain areas. For the first time using PET imaging, we show that microglial activation can correlate with both tau aggregation and amyloid deposition. This confirms the complex relationship between these processes. These results suggest that preventative treatment for Alzheimer's disease should target all three processes. [ABSTRACT FROM AUTHOR]

Rest tremor is one of the cardinal signs of Parkinson's disease. Kinetic and postural tremors may also occur. The coexistence of these three types of tremor at disease onset and their subsequent progression could have important clinical and therapeutic implications but remain to be fully elucidated. We aimed to: (i) evaluate prevalence and progression of these three types of tremor in early stages of the disease; and (ii) investigate longitudinally the relationship between dopaminergic and serotonergic terminal dysfunction, rest tremor severity and its response to dopaminergic therapy. The Parkinson's Progressive Markers Initiative database provided the baseline and 2-year follow-up clinical ratings and 123ioflupane-fluoropropyl-carbomethoxy-3-beta-4-iodophenyltropane (123I-FP-CIT) single photon emission computed tomography images for this study. 123I-FP-CIT measured putamen dopamine transporter and median raphe serotonin transporter availability. A raphe/putamen uptake ratio was calculated for each patient as an index of relative involvement of these structures. Clinical analysis of tremor was conducted on 378 patients: 87.8% presented with tremor at baseline; rest tremor occurred in 69.6% of patients at baseline; and 67.9% at follow-up. Postural and kinetic tremors occurred in about 50% of patients at both baseline and follow-up. Over 20% of patients presenting with tremor did not exhibit a rest component at baseline. The number of patients with isolated rest tremor was halved at follow-up. In tremor predominant patients, rest tremor severity was inversely correlated with raphe serotonin transporter availability both at baseline and follow-up (baseline: constancy P < 0.05, tremor index P < 0.05; follow-up: amplitude P < 0.05, constancy P < 0.05, tremor index P < 0.05). In the entire cohort, more severe tremor scores correlated with lower raphe/putamen uptake ratio values, indicative of more severe raphe dysfunction (baseline: constancy P < 0.01, tremor index P < 0.05; follow-up: amplitude P < 0.01, constancy P < 0.001, tremor index P < 0.001). The percentage of improvement in rest tremor amplitude after acute dopaminergic therapy was smaller in patients with lower raphe/putamen uptake ratio values (P < 0.01). Rest tremor is the most represented type of tremor in early Parkinson's disease. However, postural and kinetic tremor can affect approximately half of these patients and can occur in absence of resting tremor. As disease progresses, both raphe serotonergic dysfunction and putamen dopamine depletion could contribute to the occurrence of rest tremor. The former is linked to more severe tremor scores and poorer response to dopaminergic therapy. Non-dopaminergic treatments might be beneficial for patients whose tremor is associated with a raphe-predominant dysfunction. [ABSTRACT FROM AUTHOR]

Pathological involvement of the noradrenergic locus coeruleus occurs early in Parkinson's disease, and widespread noradrenaline reductions are found at post-mortem. Rapid eye movement sleep behaviour disorder (RBD) accompanies Parkinson's disease and its presence predicts an unfavourable disease course with a higher propensity to cognitive impairment and orthostatic hypotension. MRI can detect neuromelanin in the locus coeruleus while 11C-MeNER PET is a marker of noradrenaline transporter availability. Here, we use both imaging modalities to study the association of RBD, cognition and autonomic dysfunction in Parkinson's disease with loss of noradrenergic function. Thirty non-demented Parkinson's disease patients [16 patients with RBD and 14 without RBD, comparable across age (66.6 ± 6.7 years), sex (22 males), and disease stage (Hoehn and Yahr, 2.3 ± 0.5)], had imaging of the locus coeruleus with neuromelanin sensitive MRI and brain noradrenaline transporter availability with 11C-MeNER PET. RBD was confirmed with polysomnography; cognitive function was assessed with a neuropsychological test battery, and blood pressure changes on tilting were documented; results were compared to 12 matched control subjects. We found that Parkinson's disease patients with RBD showed decreased locus coeruleus neuromelanin signal on MRI (P < 0.001) and widespread reduced binding of 11C-MeNER (P < 0.001), which correlated with amount of REM sleep without atonia. Parkinson's disease with RBD was also associated with a higher incidence of cognitive impairment, slowed EEG activity, and orthostatic hypotension. Reduced 11C-MeNER binding correlated with EEG slowing, cognitive performance, and orthostatic hypotension. In conclusion, reduced noradrenergic function in Parkinson's disease was linked to the presence of RBD and associated with cognitive deterioration and orthostatic hypotension. Noradrenergic impairment may contribute to the high prevalence of these non-motor symptoms in Parkinson's disease, and may be of relevance when treating these conditions in Parkinson's disease. [ABSTRACT FROM AUTHOR]

We present the discovery of a z = 0.65 low-ionization broad absorption line (LoBAL) quasar in a post-starburst galaxy in data from the Dark Energy Survey (DES) and spectroscopy from the Australian Dark Energy Survey (OzDES). LoBAL quasars are a minority of all BALs, and rarer still is that this object also exhibits broad Fe II (an FeLoBAL) and Balmer absorption. This is the first BAL quasar that has signatures of recently truncated star formation, which we estimate ended about 40 Myr ago. The characteristic signatures of an FeLoBAL require high column densities, which could be explained by the emergence of a young quasar from an early, dust-enshrouded phase, or by clouds compressed by a blast wave. The age of the starburst component is comparable to estimates of the lifetime of quasars, so if we assume the quasar activity is related to the truncation of the star formation, this object is better explained by the blast wave scenario. [ABSTRACT FROM AUTHOR]

See Kreisl (doi:10.1093/awx151) for a scientific commentary on this article.Subjects with mild cognitive impairment associated with cortical amyloid-β have a greatly increased risk of progressing to Alzheimer's disease. We hypothesized that neuroinflammation occurs early in Alzheimer's disease and would be present in most amyloid-positive mild cognitive impairment cases. 11C-Pittsburgh compound B and 11C-(R)-PK11195 positron emission tomography was used to determine the amyloid load and detect the extent of neuroinflammation (microglial activation) in 42 mild cognitive impairment cases. Twelve age-matched healthy control subjects had 11C-Pittsburgh compound B and 10 healthy control subjects had 11C-(R)-PK11195 positron emission tomography for comparison. Amyloid-positivity was defined as 11C-Pittsburgh compound B target-to-cerebellar ratio above 1.5 within a composite cortical volume of interest. Supervised cluster analysis was used to generate parametric maps of 11C-(R)-PK11195 binding potential. Levels of 11C-(R)-PK11195 binding potential were measured in a selection of cortical volumes of interest and at a voxel level. Twenty-six (62%) of 42 mild cognitive impairment cases showed a raised cortical amyloid load compared to healthy controls. Twenty-two (85%) of the 26 amyloid-positive mild cognitive impairment cases showed clusters of increased cortical microglial activation accompanying the amyloid. There was a positive correlation between levels of amyloid load and 11C-(R)-PK11195 binding potentials at a voxel level within subregions of frontal, parietal and temporal cortices. 11C-(R)-PK11195 positron emission tomography reveals increased inflammation in a majority of amyloid positive mild cognitive impairment cases, its cortical distribution overlapping that of amyloid deposition. [ABSTRACT FROM AUTHOR]

Adult muscle precursor (AMP) cells located in the notum of the larval wing disc undergo rapid amplification and eventual fusion to generate the Drosophila melanogaster indirect flight muscles (IFMs). Here we find that loss of Moleskin (Msk) function in these wing disc-associated myoblasts reduces the overall AMP pool size, resulting in the absence of IFM formation. This myoblast loss is due to a decrease in the AMP proliferative capacity and is independent of cell death. In contrast, disruption of Msk during pupal myoblast proliferation does not alter the AMP number, suggesting that Msk is specifically required for larval AMP proliferation. It has been previously shown that Wingless (Wg) signaling maintains expression of the Vestigial (Vg) transcription factor in proliferating myoblasts. However, other factors that influence Wg-mediated myoblast proliferation are largely unknown. Here we examine the interactions between Msk and the Wg pathway in regulation of the AMP pool size. We find that a myoblast-specific reduction of Msk results in the absence of Vg expression and a complete loss of the Wg pathway readout b-catenin/Armadillo (Arm). Moreover, msk RNA interference knockdown abolishes expression of the Wg target Ladybird (Lbe) in leg disc myoblasts. Collectively, our results provide strong evidence that Msk acts through the Wg signaling pathway to control myoblast pool size and muscle formation by regulating Arm stability or nuclear transport. [ABSTRACT FROM AUTHOR]

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars show the lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES), near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with iAB = 18.61 and iAB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002. We model the system as a single isothermal ellipsoid and find the Einstein radius θE ~ 1.47 arcsec, enclosed mass Menc ~ 4 x 1011 Mʘ and a time delay of ~52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1. [ABSTRACT FROM AUTHOR]

Amyloid-β deposition, neuroinflammation and tau tangle formation all play a significant role in Alzheimer's disease. We hypothesized that there is microglial activation early on in Alzheimer's disease trajectory, where in the initial phase, microglia may be trying to repair the damage, while later on in the disease these microglia could be ineffective and produce proinflammatory cytokines leading to progressive neuronal damage. In this longitudinal study, we have evaluated the temporal profile of microglial activation and its relationship between fibrillar amyloid load at baseline and follow-up in subjects with mild cognitive impairment, and this was compared with subjects with Alzheimer's disease. Thirty subjects (eight mild cognitive impairment, eight Alzheimer's disease and 14 controls) aged between 54 and 77 years underwent 11C-(R)PK11195, 11C-PIB positron emission tomography and magnetic resonance imaging scans. Patients were followed-up after 14 ± 4 months. Region of interest and Statistical Parametric Mapping analysis were used to determine longitudinal alterations. Single subject analysis was performed to evaluate the individualized pathological changes over time. Correlations between levels of microglial activation and amyloid deposition at a voxel level were assessed using Biological Parametric Mapping. We demonstrated that both baseline and follow-up microglial activation in the mild cognitive impairment cohort compared to controls were increased by 41% and 21%, respectively. There was a longitudinal reduction of 18% in microglial activation in mild cognitive impairment cohort over 14 months, which was associated with a mild elevation in fibrillar amyloid load. Cortical clusters of microglial activation and amyloid deposition spatially overlapped in the subjects with mild cognitive impairment. Baseline microglial activation was increased by 36% in Alzheimer's disease subjects compared with controls. Longitudinally, Alzheimer's disease subjects showed an increase in microglial activation. In conclusion, this is one of the first longitudinal positron emission tomography studies evaluating longitudinal changes in microglial activation in mild cognitive impairment and Alzheimer's disease subjects. We found there is an initial longitudinal reduction in microglial activation in subjects with mild cognitive impairment, while subjects with Alzheimer's disease showed an increase in microglial activation. This could reflect that activated microglia in mild cognitive impairment initially may adopt a protective activation phenotype, which later change to a cidal pro-inflammatory phenotype as disease progresses and amyloid clearance fails. Thus, we speculate that there might be two peaks of microglial activation in the Alzheimer's disease trajectory; an early protective peak and a later pro-inflammatory peak. If so, anti-microglial agents targeting the pro-inflammatory phenotype would be most beneficial in the later stages of the disease. [ABSTRACT FROM AUTHOR]

The tau tangle ligand (18)F-AV-1451 ((18)F-T807) binds to neuromelanin in the midbrain, and may therefore be a measure of the pigmented dopaminergic neuronal count in the substantia nigra. Parkinson's disease is characterized by progressive loss of dopaminergic neurons. Extrapolation of post-mortem data predicts that a ∼30% decline of nigral dopamine neurons is necessary to cause motor symptoms in Parkinson's disease. Putamen dopamine terminal loss at disease onset most likely exceeds that of the nigral cell bodies and has been estimated to be of the order of 50-70%. We investigated the utility of (18)F-AV-1451 positron emission tomography to visualize the concentration of nigral neuromelanin in Parkinson's disease and correlated the findings to dopamine transporter density, measured by (123)I-FP-CIT single photon emission computed tomography. A total of 17 patients with idiopathic Parkinson's disease and 16 age- and sex-matched control subjects had (18)F-AV-1451 positron emission tomography using a Siemens high-resolution research tomograph. Twelve patients with Parkinson's disease also received a standardized (123)I-FP-CIT single photon emission computed tomography scan at our imaging facility. Many of the patients with Parkinson's disease displayed visually apparent decreased (18)F-AV-1451 signal in the midbrain. On quantitation, patients showed a 30% mean decrease in total nigral (18)F-AV-1451 volume of distribution compared with controls (P = 0.004), but there was an overlap of the individual ranges. We saw no significant correlation between symptom dominant side and contralateral nigral volume of distribution. There was no correlation between nigral (18)F-AV-1451 volume of distribution and age or time since diagnosis. In the subset of 12 patients, who also had a (123)I-FP-CIT scan, the mean total striatal dopamine transporter signal was decreased by 45% and the mean total (18)F-AV-1451 substantia nigra volume of distribution was decreased by 33% after median disease duration of 4.7 years (0.5-12.4 years). (18)F-AV-1451 positron emission tomography may be the first radiotracer to reflect the loss of pigmented neurons in the substantia nigra of parkinsonian patients. The magnitude of the nigral signal loss was smaller than the decrease in striatal dopamine transporter signal measured by dopamine transporter single photon emission computed tomography. These findings suggest a more severe loss of striatal nerve terminal function compared with neuronal cell bodies, in accordance with the post-mortem literature. [ABSTRACT FROM AUTHOR]

Amyloid deposition, tangle formation, neuroinflammation and neuronal dysfunction are pathological processes involved in Alzheimer's disease. However, the relative role of these processes in driving disease progression is still unclear. The aim of this positron emission tomography study was to: (i) investigate longitudinal changes of microglial activation, amyloid and glucose metabolism; and (ii) assess the temporospatial relationship between these three processes in Alzheimer's disease. A group of eight patients with a diagnosis of Alzheimer's disease (66 ± 4.8 years) and 14 healthy controls (65 ± 5.5 years) underwent T1 and T2 magnetic resonance imaging, along with (11)C-(R)-PK11195, (11)C-Pittsburgh compound B and (18)F-fluorodeoxyglucose positron emission tomography scans for microglial activation, amyloid deposition and glucose metabolism. All patients were followed-up with repeated magnetic resonance imaging and three positron emission tomography scans after 16 months. Parametric maps were interrogated using region of interest analysis, Statistical Parametric Mapping, and between-group correlation analysis at voxel-level using Biological Parametric Mapping. At baseline, patients with Alzheimer's disease showed significantly increased microglial activation compared to the control subjects. During follow-up, for the first time, we found that while there is a progressive reduction of glucose metabolism, there was a longitudinal increase of microglial activation in the majority of the patients with Alzheimer's disease. Voxel-wise correlation analysis revealed that microglial activation in patients with Alzheimer's disease was positively correlated with amyloid deposition and inversely correlated with regional cerebral metabolic rate at voxel level over time. Even though one of the limitations of this study is the lack of longitudinal follow-up of healthy control subjects, this study demonstrates that there is persistent neuroinflammation throughout the Alzheimer's disease process with associated synaptic dysfunction and reduced glucose metabolism. Voxel-wise correlation analysis suggests that neuroinflammation is associated with localized amyloid deposition and glucose metabolism over time, however, the level of inflammation could also occur independently of amyloid pathology, especially in the later stages of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Post-mortem and neuroimaging studies suggest that the serotonergic system, which originates from the brainstem raphe nuclei, is disrupted in Parkinson's disease. This could contribute to the occurrence of non-motor symptoms and tremor, which are only partially explained by dopamine loss. However, the level of involvement of the serotonergic raphe nuclei in early Parkinson's disease is still debated. (123)I-FP-CIT single photon emission computed tomography is a marker of dopamine and serotonin transporter availability. While (123)I-FP-CIT binds primarily to dopamine transporters in the striatum, its binding in the brainstem raphe nuclei reflects serotonin transporter availability. We interrogated baseline single photon emission computed tomography scans of subjects recruited by the Parkinson's Progression Markers Initiative to determine: (i) the integrity of the brainstem raphe nuclei in early Parkinson's disease; and (ii) whether raphe serotonin transporter levels correlate with severity of tremor and symptoms of fatigue, depression, and sleep disturbance. Three hundred and forty-five patients with early drug-naïve Parkinson's disease, 185 healthy controls, and 56 subjects with possible Parkinson's disease without evidence of dopaminergic deficit were included. In the Parkinson's disease cohort, 37 patients had a tremulous, 106 patients had a pure akinetic-rigid, and 202 had a mixed phenotype. Patients with Parkinson's disease had significantly lower serotonin transporter availability in the brainstem raphe nuclei compared to controls (P < 0.01) and subjects without evidence of dopaminergic deficit (P < 0.05). However, only 13% of patients with Parkinson's disease individually had reduced signals. Raphe serotonin transporter availability over the entire Parkinson's disease cohort were associated with rest tremor amplitude (β = -0.106, P < 0.05), rest tremor constancy (β = -0.109, P < 0.05), and index of rest tremor severity (β = -0.104, P < 0.05). The tremulous Parkinson's disease subgroup had significantly lower raphe serotonin transporter availability but less severe striatal dopaminergic deficits compared to akinetic-rigid patients with no resting tremor (P < 0.05). In tremulous patients, raphe serotonin transporter availability was also associated with rest tremor constancy (β = -0.380, P < 0.05) and index of rest tremor severity (β = -0.322, P < 0.05). There was no association between raphe serotonin transporter availability and fatigue, depression, excessive daytime sleepiness, or rapid eye movement sleep behaviour disorder in early Parkinson's disease. We conclude that the raphe nuclei are affected in a subgroup of early drug-naïve Parkinson's disease patients and that reduced raphe serotonin transporter availability is associated with the severity of resting tremor but not non-motor symptoms. [ABSTRACT FROM AUTHOR]