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We have conducted a widefield, wideband, snapshot survey using the Australian SKA Pathfinder (ASKAP) referred to as the Rapid ASKAP Continuum Survey (RACS). RACS covers 
$\approx 90$% of the sky, with multiple observing epochs in three frequency bands sampling the ASKAP frequency range of 700–1 800 MHz. This paper describes the third major epoch at 1 655.5 MHz, RACS-high, and the subsequent imaging and catalogue data release. The RACS-high observations at 1 655.5 MHz are otherwise similar to the previously released RACS-mid (at 1 367.5 MHz) and were calibrated and imaged with minimal changes. From the 1 493 images covering the sky up to declination 
$\approx +48^\circ$, we present a catalogue of 2 677 509 radio sources. The catalogue is constructed from images with a median root-mean-square noise of 
$\approx 195$ 
$\unicode{x03BC}$Jy PSF
$^{-1}$ (point-spread function) and a median angular resolution of 
$11{\stackrel{\prime\prime}{\raise-0pt\hbox{.}}}8 \times 8{\stackrel{\prime\prime}{\raise-0pt\hbox{.}}}1$. The overall reliability of the catalogue is estimated to be 99.18%, and we find a decrease in reliability as angular resolution improves. We estimate the brightness scale to be accurate to 10%, and the astrometric accuracy to be within 
$\approx 0{\stackrel{\prime\prime}{\raise-0pt\hbox{.}}}6$ in right ascension and 
$\approx 0{\stackrel{\prime\prime}{\raise-0pt\hbox{.}}}7$ in declination after correction of a systematic declination-dependent offset. All data products from RACS-high, including calibrated visibility datasets, images from individual observations, full-sensitivity mosaics, and the all-sky catalogue are available at the CSIRO ASKAP Science Data Archive.
Major Depressive Disorder (MDD) is a complex mental health condition characterized by a wide spectrum of symptoms. According to the Diagnostic Statistical Manual 5 (DSM-5) criteria, patients can present with up to 1,497 different symptom combinations, yet all receive the same MDD diagnosis. This diversity in symptom presentation poses a significant challenge to understanding the disorder in the wider population. Subtyping offers a way to unpick this phenotypic diversity and enable improved characterization of the disorder. According to reviews, MDD subtyping work to date has lacked consistency in results due to inadequate statistics, non-transparent reporting, or inappropriate sample choice. By addressing these limitations, the current study aims to extend past phenotypic subtyping studies in MDD.
(1) To investigate phenotypic subtypes at baseline in a sample of people with MDD;
(2) To determine if subtypes are consistent between baseline 6- and 12-month follow-ups; and
(3) To examine how participants move between subtypes over time.
This was a secondary analysis of a one-year longitudinal observational cohort study. We collected data from individuals with a history of recurrent MDD in the United Kingdom, the Netherlands and Spain (N=619). The presence or absence of symptoms was tracked at three-month intervals through the Inventory of Depressive Symptomatology: Self-Report (IDS-SR) assessment. We used latent class and three-step latent transition analysis to identify subtypes at baseline, determined their consistency at 6- and 12-month follow-ups, and examined participants’ transitions over time.
We identified a 4-class solution based on model fit and interpretability, including (Class 1) severe with appetite increase, (Class 2), severe with appetite decrease, (Class 3) moderate, and (Class 4) low severity. The classes mainly differed in terms of severity (the varying likelihood of symptom endorsement) and, for the two more severe classes, the type of neurovegetative symptoms reported (Figure 1). The four classes were stable over time (measurement invariant) and participants tended to remain in the same class over baseline and follow-up (Figure 2).
Image:
Image 2:
We identified four stable subtypes of depression, with individuals most likely to remain in their same class over 1-year follow-up. This suggests a chronic nature of depression, with (for example) individuals in severe classes more likely to remain in the same class throughout follow-up. Despite the vast heterogeneous symptom combinations possible in MDD, our results emphasize differences across severity rather than symptom type. This raises questions about the meaningfulness of these subtypes beyond established measures of depression severity. Implications of these findings and recommendations for future research are made.
C. Oetzmann Grant / Research support from: C.O. is supported by the UK Medical Research Council (MR/N013700/1) and King’s College London member of the MRC Doctoral Training Partnership in Biomedical Sciences., N. Cummins: None Declared, F. Lamers: None Declared, F. Matcham: None Declared, K. White: None Declared, J. Haro: None Declared, S. Siddi: None Declared, S. Vairavan Employee of: S.V is an employee of Janssen Research & Development, LLC and hold company stocks/stock options., B. Penninx : None Declared, V. Narayan: None Declared, M. Hotopf Grant / Research support from: M.H. is the principal investigator of the RADAR-CNS programme, a precompetitive public–private partnership funded by the Innovative Medicines Initiative and the European Federation of Pharmaceutical Industries and Associations. The programme received support from Janssen, Biogen, MSD, UCB and Lundbeck., E. Carr: None Declared
The Australian SKA Pathfinder (ASKAP) is being used to undertake a campaign to rapidly survey the sky in three frequency bands across its operational spectral range. The first pass of the Rapid ASKAP Continuum Survey (RACS) at 887.5 MHz in the low band has already been completed, with images, visibility datasets, and catalogues made available to the wider astronomical community through the CSIRO ASKAP Science Data Archive (CASDA). This work presents details of the second observing pass in the mid band at 1367.5 MHz, RACS-mid, and associated data release comprising images and visibility datasets covering the whole sky south of 
$\delta_{\text{J2000}}=+49^\circ$. This data release incorporates selective peeling to reduce artefacts around bright sources, as well as accurately modelled primary beam responses. The Stokes I images reach a median noise of 198 
$\mu$Jy PSF
$^{-1}$ with a declination-dependent angular resolution of 8.1–47.5 arcsec that fills a niche in the existing ecosystem of large-area astronomical surveys. We also supply Stokes V images after application of a widefield leakage correction, with a median noise of 165 
$\mu$Jy PSF
$^{-1}$. We find the residual leakage of Stokes I into V to be 
$\lesssim 0.9$–
$2.4$% over the survey. This initial RACS-mid data release will be complemented by a future release comprising catalogues of the survey region. As with other RACS data releases, data products from this release will be made available through CASDA.
We present a comparison between the performance of a selection of source finders (SFs) using a new software tool called Hydra. The companion paper, Paper I, introduced the Hydra tool and demonstrated its performance using simulated data. Here we apply Hydra to assess the performance of different source finders by analysing real observational data taken from the Evolutionary Map of the Universe (EMU) Pilot Survey. EMU is a wide-field radio continuum survey whose primary goal is to make a deep (
$20\mu$Jy/beam RMS noise), intermediate angular resolution (
$15^{\prime\prime}$), 1 GHz survey of the entire sky south of 
$+30^{\circ}$ declination, and expecting to detect and catalogue up to 40 million sources. With the main EMU survey it is highly desirable to understand the performance of radio image SF software and to identify an approach that optimises source detection capabilities. Hydra has been developed to refine this process, as well as to deliver a range of metrics and source finding data products from multiple SFs. We present the performance of the five SFs tested here in terms of their completeness and reliability statistics, their flux density and source size measurements, and an exploration of case studies to highlight finder-specific limitations.
The latest generation of radio surveys are now producing sky survey images containing many millions of radio sources. In this context it is highly desirable to understand the performance of radio image source finder (SF) software and to identify an approach that optimises source detection capabilities. We have created Hydra to be an extensible multi-SF and cataloguing tool that can be used to compare and evaluate different SFs. Hydra, which currently includes the SFs Aegean, Caesar, ProFound, PyBDSF, and Selavy, provides for the addition of new SFs through containerisation and configuration files. The SF input RMS noise and island parameters are optimised to a 90% ‘percentage real detections’ threshold (calculated from the difference between detections in the real and inverted images), to enable comparison between SFs. Hydra provides completeness and reliability diagnostics through observed-deep (
$\mathcal{D}$) and generated-shallow (
$\mathcal{S}$) images, as well as other statistics. In addition, it has a visual inspection tool for comparing residual images through various selection filters, such as S/N bins in completeness or reliability. The tool allows the user to easily compare and evaluate different SFs in order to choose their desired SF, or a combination thereof. This paper is part one of a two part series. In this paper we introduce the Hydra software suite and validate its 
$\mathcal{D/S}$ metrics using simulated data. The companion paper demonstrates the utility of Hydra by comparing the performance of SFs using both simulated and real images.
