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Functional impairment in daily activities, such as work and socializing, is part of the diagnostic criteria for major depressive disorder and most anxiety disorders. Despite evidence that symptom severity and functional impairment are partially distinct, functional impairment is often overlooked. To assess whether functional impairment captures diagnostically relevant genetic liability beyond that of symptoms, we aimed to estimate the heritability of, and genetic correlations between, key measures of current depression symptoms, anxiety symptoms, and functional impairment.
Methods
In 17,130 individuals with lifetime depression or anxiety from the Genetic Links to Anxiety and Depression (GLAD) Study, we analyzed total scores from the Patient Health Questionnaire-9 (depression symptoms), Generalized Anxiety Disorder-7 (anxiety symptoms), and Work and Social Adjustment Scale (functional impairment). Genome-wide association analyses were performed with REGENIE. Heritability was estimated using GCTA-GREML and genetic correlations with bivariate-GREML.
Results
The phenotypic correlations were moderate across the three measures (Pearson’s r = 0.50–0.69). All three scales were found to be under low but significant genetic influence (single-nucleotide polymorphism-based heritability [h2SNP] = 0.11–0.19) with high genetic correlations between them (rg = 0.79–0.87).
Conclusions
Among individuals with lifetime depression or anxiety from the GLAD Study, the genetic variants that underlie symptom severity largely overlap with those influencing functional impairment. This suggests that self-reported functional impairment, while clinically relevant for diagnosis and treatment outcomes, does not reflect substantial additional genetic liability beyond that captured by symptom-based measures of depression or anxiety.
Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.
Methods
T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).
Results
PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).
Conclusions
PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.
Objectives/Goals: The never in mitosis kinase (NEK) family regulates vital processes, namely cell cycle progression, but their potential as therapeutic targets in TNBC has not been fully explored. Our studies aim to develop a toolkit to investigate the functional roles of NEKs in pathologies including carcinogenesis. Methods/Study Population: To assess differential NEK expression in normal and tumor tissues and correlation of gene expression with patient survival, we used Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier Plotter (KMPlot) pan-cancer analysis, respectively. Basal NEK protein levels were determined by immunoblot across a panel of cell lines, including breast cancer, osteosarcoma, hepatocellular carcinoma, and non-cancerous cells, to identify appropriate systems for evaluation of NEK function. Doxycycline-inducible cell lines were generated by transduction with lentiviral stocks of NEK shRNA and overexpression constructs and antibiotic selection. Expression was analyzed by qPCR and immunoblot. Results/Anticipated Results: Expression of NEK2, 4, 5, 6, 8, and 11 was higher in breast tumors compared to normal tissue by GEPIA analysis. Further examination using KMPlot showed a correlation between elevated NEK6 expression and decreased overall survival in patients with aggressive cancers. As an initial proof-of-concept study, we analyzed NEK6 protein expression in breast cancer cells. Levels of NEK6 were elevated in TNBC cells (MDA-MB-231) compared to hormone receptor positive (HR+) breast cancer cells (MCF7). Using complementary approaches to investigate the functional role of NEK6 in breast cancer, we depleted NEK6 expression using shRNAs in TNBC cells and expressed NEK6 in HR+ cells Discussion/Significance of Impact: Because kinase dysregulation promotes oncogenesis and metastasis, targeting kinases is a key strategy in therapeutic development. A NEK-specific molecular toolkit allows researchers to elucidate NEK functions and contributions to carcinogenesis, promoting advancement of novel therapies.
Objectives/Goals: Team science (TS) competency is important for translational science team collaboration. However, there are few educators available to assist teams. Asynchronous learning is an effective strategy for delivering TS content. The goal of this project is to expand TS education by providing online access to our learners using online modules. Methods/Study Population: The Collaboration and Team Science (CaTS) team at the University of Cincinnati provides a robust TS education and training program. As the need for team science gains recognition, CaTS has received increased requests for services, leading to a need to broaden TS offerings. To address this demand, the CaTS team created “Team Science 101,” an online, asynchronous, series of 15 modules covering basic team science concepts. Each module consists of an educational recording lasting an average of 20 minutes, optional topic resources, pre- and post-module surveys assessing learners’ confidence and satisfaction, post-module knowledge checks, and evaluation questions. Upon completing all modules, participants receive a completion certificate. Results/Anticipated Results: TS 101 will be piloted with a group of participants who expressed interest in asynchronous TS content and will be adjusted based on the feedback received. The associated pre- and post-module survey, post-module knowledge check, and evaluation questions will be monitored to determine learning levels and improve TS 101 overall. Canvas is the educational platform that houses these modules, allowing for participant follow-up and scalable dissemination. The CaTS team plans to disseminate TS 101 nationally and internationally for anyone interested in this resource. Discussion/Significance of Impact: There is a national effort to collect and curate TS education, training, and toolkits. TS 101 will be a useful educational tool that will expand the reach of team science educators, provide the foundation for educators to explore topics more deeply by building on the module topics, and provide education to broader audiences who lack access to TS experts.
We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and searches for dispersed fast transient signals including fast radio bursts (FRB), pulsars, and ultra-long period objects (ULPO). With the visibility data, CRACO can localise the transient events to arcsecond-level precision after the detection. Here, we describe the CRACO system and report the result from a sky survey carried out by CRACO at 110-ms resolution during its commissioning phase. During the survey, CRACO detected two FRBs (including one discovered solely with CRACO, FRB 20231027A), reported more precise localisations for four pulsars, discovered two new RRATs, and detected one known ULPO, GPM J1839 $-$10, through its sub-pulse structure. We present a sensitivity calibration of CRACO, finding that it achieves the expected sensitivity of 11.6 Jy ms to bursts of 110 ms duration or less. CRACO is currently running at a 13.8 ms time resolution and aims at a 1.7 ms time resolution before the end of 2024. The planned CRACO has an expected sensitivity of 1.5 Jy ms to bursts of 1.7 ms duration or less and can detect $10\times$ more FRBs than the current CRAFT incoherent sum system (i.e. 0.5 $-$2 localised FRBs per day), enabling us to better constrain the models for FRBs and use them as cosmological probes.
We present the Pilot Survey Phase 2 data release for the Wide-field ASKAP L-band Legacy All-sky Blind surveY (WALLABY), carried-out using the Australian SKA Pathfinder (ASKAP). We present 1760 H i detections (with a default spatial resolution of 30′′) from three pilot fields including the NGC 5044 and NGC 4808 groups as well as the Vela field, covering a total of $\sim 180$ deg$^2$ of the sky and spanning a redshift up to $z \simeq 0.09$. This release also includes kinematic models for over 126 spatially resolved galaxies. The observed median rms noise in the image cubes is 1.7 mJy per 30′′ beam and 18.5 kHz channel. This corresponds to a 5$\sigma$ H i column density sensitivity of $\sim 9.1\times10^{19}(1 + z)^4$ cm$^{-2}$ per 30′′ beam and $\sim 20$ km s$^{-1}$ channel and a 5$\sigma$ H i mass sensitivity of $\sim 5.5\times10^8 (D/100$ Mpc)$^{2}$ M$_{\odot}$ for point sources. Furthermore, we also present for the first time 12′′ high-resolution images (“cut-outs”) and catalogues for a sub-sample of 80 sources from the Pilot Survey Phase 2 fields. While we are able to recover sources with lower signal-to-noise ratio compared to sources in the Public Data Release 1, we do note that some data quality issues still persist, notably, flux discrepancies that are linked to the impact of side lobes associated with the dirty beams due to inadequate deconvolution. However, in spite of these limitations, the WALLABY Pilot Survey Phase 2 has already produced roughly a third of the number of HIPASS sources, making this the largest spatially resolved H i sample from a single survey to date.
Stenotrophomonas maltophilia is a multidrug-resistant gram-negative bacillus that can cause serious infections but has limited treatment options. This study aims to establish trends in the treatment of S. maltophilia bloodstream infections (BSI) across the United States in Department of Veterans Affairs (VA) facilities.
Methods:
Data was evaluated over a 10-year timeframe (2012 to 2021) in this retrospective cohort study. Veterans with ≥ 1 blood culture with S. maltophilia within a VA medical encounter were included. Microbiology, pharmacy, and patient information were collected through national VA data sources and chart review. Descriptive statistics and Poisson regression were used to summarize patient demographics, facility characteristics, microbiologic data, and treatment trends.
Results:
A total of 374 blood cultures positive for S. maltophilia were identified across 75 VA facilities. Of 282 unique patients with BSI, the majority were male (93.6%), white (67.4%), with a mean age of 64 ± 13.1 years. Of those patients, 78% received treatment, 12.8% had a polymicrobial blood culture, and 5.3% had a documented sulfa allergy. Susceptibility results were most reported for trimethoprim-sulfamethoxazole (TMP-SMX), levofloxacin, and ceftazidime, with 4.5%, 4.3%, and 44.4% resistant isolates, respectively. Antibiotics most prescribed included TMP-SMX (41.5%) and levofloxacin (39.4%), followed by ciprofloxacin (13.8%) and ceftazidime (12.4%). Combination therapy was prescribed in 33% of patients. No significant trends were found with antibiotic utilization over time.
Conclusions:
TMP-SMX and levofloxacin were the most prescribed antibiotics for S. maltophilia BSI treatment. No significant changes were seen with antibiotic prescribing trends in Veterans from 2012 to 2021.
Gaming disorder has become a global concern and it could have a variety of health and social consequences. The trauma model has been applied to the understanding of different types of addictions as behavioral addictions can sometimes be conceptualized as self-soothing strategies to avoid trauma-related stressors or triggers. However, much less is known about the relationship between trauma exposure and gaming disorder.
Objectives
To inform prevention and intervention strategies and to facilitate further research, we conducted the first scoping review to explore and summarize the literature on the relationship between trauma and gaming disorder.
Methods
A systematic search was conducted on the Web of Science, Scopus and ProQuest. We looked for original studies published in English that included a measure of trauma exposure and a measure of gaming disorder symptoms, as well as quantitative data regarding the relationship between trauma exposure and gaming disorder.
Results
The initial search generated 412 articles, of which 15 met the inclusion criteria. All of them were cross-sectional studies, recruiting participants from both clinical and non-clinical populations. Twelve of them (80%) reported significant correlations between trauma exposure and the severity of gaming disorder symptoms (r = 0.18 to 0.46, p < 0.010). Several potential mediators, including depressive symptoms and dissociative experiences, have been identified. One study found that parental monitoring moderated the relationship between trauma and gaming disorder symptoms. No studies reported the prevalence of trauma or trauma-related symptoms among people with gaming disorder.
Conclusions
There is some evidence supporting the association between trauma and gaming disorder, at small to medium effect sizes. Future studies should investigate the mediators and moderators underlying the relationship between trauma and gaming disorder. The longitudinal relationship between trauma exposure and the development of gaming disorder should be clarified. A trauma-informed approach may be a helpful strategy to alleviate gaming disorder symptoms.
Background: Hyperacute stroke care demands rapid, coordinated care. Traditional metrics like Door-to-Needle time are pivotal but insufficient for capturing the complexity of endovascular stroke interventions. The SMILES collaboration aims to standardize and optimize protocols for door-to-intervention times, incorporating Crew Resource Management (CRM). Methods: The multidisciplinary initiative integrates both hospitals, ED, neurology, and QI teams. We employed a comprehensive approach: stakeholder engagement, simulation-based learning, process mapping, and literature review. Emphasis was placed on enhancing situational awareness, triage and prioritization, cognitive load management, role clarity, effective communication, and debriefing. Results: The collaboration led to PDSA cycles and development of refined stroke protocols. Interventions included: 1) A ’zero point survey’ for team pre-arrival briefings, enhancing situational awareness and role clarity; 2) Streamlined patient registration to reduce cognitive load and improve triage efficiency; 3) Direct transfer of patients to imaging. Additionally, digital tools were implemented to facilitate communication. Simulation sessions reinforced CRM principles, leading to improved team cohesion and operational performance. Conclusions: The SMILES initiative is grounded in CRM principles by standardizing protocols and emphasizing non-technical skills crucial for high-stakes environments. This improves outcomes but also fosters a culture of safety and efficiency. Future directions include an evaluation of these protocols’ impact on patient factors.
Understanding characteristics of healthcare personnel (HCP) with SARS-CoV-2 infection supports the development and prioritization of interventions to protect this important workforce. We report detailed characteristics of HCP who tested positive for SARS-CoV-2 from April 20, 2020 through December 31, 2021.
Methods:
CDC collaborated with Emerging Infections Program sites in 10 states to interview HCP with SARS-CoV-2 infection (case-HCP) about their demographics, underlying medical conditions, healthcare roles, exposures, personal protective equipment (PPE) use, and COVID-19 vaccination status. We grouped case-HCP by healthcare role. To describe residential social vulnerability, we merged geocoded HCP residential addresses with CDC/ATSDR Social Vulnerability Index (SVI) values at the census tract level. We defined highest and lowest SVI quartiles as high and low social vulnerability, respectively.
Results:
Our analysis included 7,531 case-HCP. Most case-HCP with roles as certified nursing assistant (CNA) (444, 61.3%), medical assistant (252, 65.3%), or home healthcare worker (HHW) (225, 59.5%) reported their race and ethnicity as either non-Hispanic Black or Hispanic. More than one third of HHWs (166, 45.2%), CNAs (283, 41.7%), and medical assistants (138, 37.9%) reported a residential address in the high social vulnerability category. The proportion of case-HCP who reported using recommended PPE at all times when caring for patients with COVID-19 was lowest among HHWs compared with other roles.
Conclusions:
To mitigate SARS-CoV-2 infection risk in healthcare settings, infection prevention, and control interventions should be specific to HCP roles and educational backgrounds. Additional interventions are needed to address high social vulnerability among HHWs, CNAs, and medical assistants.
We investigate the diversity in the sizes and average surface densities of the neutral atomic hydrogen (H i) gas discs in $\sim$280 nearby galaxies detected by the Widefield ASKAP L-band Legacy All-sky Blind Survey (WALLABY). We combine the uniformly observed, interferometric H i data from pilot observations of the Hydra cluster and NGC 4636 group fields with photometry measured from ultraviolet, optical, and near-infrared imaging surveys to investigate the interplay between stellar structure, star formation, and H i structural parameters. We quantify the H i structure by the size of the H i relative to the optical disc and the average H i surface density measured using effective and isodensity radii. For galaxies resolved by $>$$1.3$ beams, we find that galaxies with higher stellar masses and stellar surface densities tend to have less extended H i discs and lower H i surface densities: the isodensity H i structural parameters show a weak negative dependence on stellar mass and stellar mass surface density. These trends strengthen when we limit our sample to galaxies resolved by $>$2 beams. We find that galaxies with higher H i surface densities and more extended H i discs tend to be more star forming: the isodensity H i structural parameters have stronger correlations with star formation. Normalising the H i disc size by the optical effective radius (instead of the isophotal radius) produces positive correlations with stellar masses and stellar surface densities and removes the correlations with star formation. This is due to the effective and isodensity H i radii increasing with mass at similar rates while, in the optical, the effective radius increases slower than the isophotal radius. Our results are in qualitative agreement with previous studies and demonstrate that with WALLABY we can begin to bridge the gap between small galaxy samples with high spatial resolution H i data and large, statistical studies using spatially unresolved, single-dish data.
To describe patterns of inappropriate antibiotic prescribing at US children’s hospitals and how these patterns vary by clinical service.
Design:
Serial, cross-sectional study using quarterly surveys.
Setting:
Surveys were completed in quarter 1 2019–quarter 3 2020 across 28 children’s hospitals in the United States.
Participants:
Patients at children’s hospitals with ≥1 antibiotic order at 8:00 a.m. on institution-selected quarterly survey days.
Methods:
Antimicrobial stewardship physicians and pharmacists collected data on antibiotic orders and evaluated appropriateness of prescribing. The primary outcome was percentage of inappropriate antibiotics, stratified by clinical service and antibiotic class. Secondary outcomes included reasons for inappropriate use and association of infectious diseases (ID) consultation with appropriateness.
Results:
Of 13,344 orders, 1,847 (13.8%) were inappropriate; 17.5% of patients receiving antibiotics had ≥1 inappropriate order. Pediatric intensive care units (PICU) and hospitalists contributed the most inappropriate orders (n = 384 and n = 314, respectively). Surgical subspecialists had the highest percentage of inappropriate orders (22.5%), and 56.8% of these were for prolonged or unnecessary surgical prophylaxis. ID consultation in the previous 7 days was associated with fewer inappropriate orders (15% vs 10%; P < .001); this association was most pronounced for hospitalist, PICU, and surgical and medical subspecialty services.
Conclusions:
Inappropriate antibiotic use for hospitalized children persists and varies by clinical service. Across 28 children’s hospitals, PICUs and hospitalists contributed the most inappropriate antibiotic orders, and surgical subspecialists’ orders were most often judged inappropriate. Understanding service-specific prescribing patterns will enable antimicrobial stewardship programs to better design interventions to optimize antibiotic use.
We present the highest resolution and sensitivity $\sim$$1.4\,$GHz continuum observations of the Eridanus supergroup obtained as a part of the Widefield Australian Square Kilometer Array Pathfinder (ASKAP) L-band Legacy All-sky Blind surveY (WALLABY) pre-pilot observations using the ASKAP. We detect 9461 sources at 1.37 GHz down to a flux density limit of $\sim$$0.1$ mJy at $6.1''\times 7.9''$ resolution with a median root mean square of 0.05 mJy beam$^{-1}$. We find that the flux scale is accurate to within 5 % (compared to NVSS at 1.4 GHz). We then determine the global properties of eight Eridanus supergroup members, which are detected in both radio continuum and neutral hydrogen (HI) emission, and find that the radio-derived star formation rates (SFRs) agree well with previous literature. Using our global and resolved radio continuum properties of the nearby Eridanus galaxies, we measure and extend the infrared-radio correlation (IRRC) to lower stellar masses and inferred SFRs than before. We find the resolved IRRC to be useful for: (1) discriminating between active galactic nuclei and star-forming galaxies; (2) identifying background radio sources; and (3) tracing the effects of group environment pre-processing in NGC 1385. We find evidence for tidal interactions and ram-pressure stripping in the HI, resolved spectral index and IRRC morphologies of NGC 1385. There appears to be a spatial coincidence (in projection) of double-lobed radio jets with the central HI hole of NGC 1367. The destruction of polycyclic aromatic hydrocarbons by merger-induced shocks may be driving the observed WISE W3 deficit observed in NGC 1359. Our results suggest that resolved radio continuum and IRRC studies are excellent tracers of the physical processes that drive galaxy evolution and will be possible on larger sample of sources with upcoming ASKAP radio continuum surveys.
Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions.
Methods
Data came from n = 999 patients ages 18–75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models.
Results
Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31–1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65–2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43–2.87) and bullying (RR = 1.44; 95% CI = 0.99–2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE.
Conclusions
Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.
A survey of attitudes towards the welfare and rights of animals was conducted in universities in 11 European and Asian countries, to improve understanding of cultural differences that might impact on trade and international relations. Collaborators’ universities were recruited in each country to assist in the design, translation and administration of the survey via the internet in a convenient selection of the country's universities, providing 3,433 student responses from at least 103 universities. Respondents rated the acceptability of 43 major concerns about animals (focused on type of use, animal integrity, killing animals, animal welfare, experimentation on animals, changes in animal genotypes, the environment for animals and societal attitudes towards animals). Students from European countries had more concern for animal welfare than students from Asian countries, which may be partly explained by increased affluence of European students as there was a positive correlation between student expenditure and concern for animal welfare and rights. Southern and central European countries had most concern for animal rights and unnatural practices. Those in communist or former communist countries in Asia and Europe had most concern about killing animals and those in northern European countries the least. Regional similarities between neighbouring countries were evident in responses to animal issues and there were no differences between ethnic groups within a country. Thus, there were national and continental differences in European and Asian students’ attitudes to animals’ welfare and rights, which appear to arise as a result of the socio-political situation in regions rather than religious or other differences.
We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I Hi kinematic models. This first data release consists of Hi observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group. In this paper, we describe how we generate and publicly release flat-disk tilted-ring kinematic models for 109/592 unique Hi detections in these fields. The modelling method adopted here—which we call the WALLABY Kinematic Analysis Proto-Pipeline (WKAPP) and for which the corresponding scripts are also publicly available—consists of combining results from the homogeneous application of the FAT and 3DBarolo algorithms to the subset of 209 detections with sufficient resolution and $S/N$ in order to generate optimised model parameters and uncertainties. The 109 models presented here tend to be gas rich detections resolved by at least 3–4 synthesised beams across their major axes, but there is no obvious environmental bias in the modelling. The data release described here is the first step towards the derivation of similar products for thousands of spatially resolved WALLABY detections via a dedicated kinematic pipeline. Such a large publicly available and homogeneously analysed dataset will be a powerful legacy product that that will enable a wide range of scientific studies.
We present WALLABY pilot data release 1, the first public release of H i pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder. Phase 1 of the WALLABY pilot survey targeted three $60\,\mathrm{deg}^{2}$ regions on the sky in the direction of the Hydra and Norma galaxy clusters and the NGC 4636 galaxy group, covering the redshift range of $z \lesssim 0.08$. The source catalogue, images and spectra of nearly 600 extragalactic H i detections and kinematic models for 109 spatially resolved galaxies are available. As the pilot survey targeted regions containing nearby group and cluster environments, the median redshift of the sample of $z \approx 0.014$ is relatively low compared to the full WALLABY survey. The median galaxy H i mass is $2.3 \times 10^{9}\,{\rm M}_{{\odot}}$. The target noise level of $1.6\,\mathrm{mJy}$ per 30′′ beam and $18.5\,\mathrm{kHz}$ channel translates into a $5 \sigma$ H i mass sensitivity for point sources of about $5.2 \times 10^{8} \, (D_{\rm L} / \mathrm{100\,Mpc})^{2} \, {\rm M}_{{\odot}}$ across 50 spectral channels (${\approx} 200\,\mathrm{km \, s}^{-1}$) and a $5 \sigma$ H i column density sensitivity of about $8.6 \times 10^{19} \, (1 + z)^{4}\,\mathrm{cm}^{-2}$ across 5 channels (${\approx} 20\,\mathrm{km \, s}^{-1}$) for emission filling the 30′′ beam. As expected for a pilot survey, several technical issues and artefacts are still affecting the data quality. Most notably, there are systematic flux errors of up to several 10% caused by uncertainties about the exact size and shape of each of the primary beams as well as the presence of sidelobes due to the finite deconvolution threshold. In addition, artefacts such as residual continuum emission and bandpass ripples have affected some of the data. The pilot survey has been highly successful in uncovering such technical problems, most of which are expected to be addressed and rectified before the start of the full WALLABY survey.
Social anxiety disorder (SAD) can accompany emotional symptoms as well as physical reactions. The assessment and real-time measurement of SAD is difficult in real-world.
Objectives
This study aims to predict the severity of specific anxiety states and virtual reality (VR) sickness in SAD patients by a machine learning model based on only quantitative measuring of autonomic physiologic signals during VR therapy sessions.
Methods
In total, 32 individuals with SAD symptoms were enrolled in VR participatory sessions. We assessed patients’ specific anxiety symptoms through Internalized Shame Scale (ISS) and Post-Event Rumination Scale (PERS), and VR sickness through Simulator Sickness Questionnaire (SSQ). Specific anxiety symptoms and VR sickness were divided into severe and non-severe states based on the total score of each scale by K-means clustering. Logistic regression, Random Forest, Naïve Bayes classifier, and Support Vector Machine were used based on the physiological signal data to predict the severity group in subdomains of ISS, PERS, and SSQ.
Results
Prediction performance (F1 score) for the severity of the ISS mistake anxiety subdomain was higher than other scales with 0.8421. For VR sickness, prediction performance for the severity of the physical subdomain was higher than the non-physical subdomain with 0.7692.
Conclusions
The study findings present that mistake anxiety and physical sickness could be predicted more accurately by only autonomic physiological signals, suggesting these features are probably associated with autonomic responses. Based on the present study results, we could provide the evidence for predicting the severity of specific anxiety or VR adverse effects only based on in-situ physiological signals.
This study aimed to investigate the use of the head and neck cancer risk calculator version 2 in a primary care setting and to evaluate the impact of the risk calculator on the number of referrals stratified by urgency and cancer yield.
Method
Referrals between April 2019 and August 2019, April 2020 and July 2020 (pre-risk calculator) and August 2020 and July 2021 (post-risk calculator) were analysed. Referral urgency, head and neck cancer risk calculator version 2 score, cancer diagnosis, cancer type and further investigations were recorded.
Results
The 2023 patient encounters were analysed; there were 1110 (55 per cent) referrals before head and neck cancer risk calculator version 2 use and 913 (45 per cent) after head and neck cancer risk calculator version 2 use. A higher proportion of older (p < 0.001) and male (p < 0.013) patients were seen post-head and neck cancer risk calculator version 2 use. All cancer cases were seen on the urgent suspicion of cancer pathway post-head and neck cancer risk calculator version 2 use; however, a higher proportion of patients were seen as urgent suspicion of cancer (51.1 vs 83.5 per cent; p < 0.001). Overall, the cancer diagnosis rate increased from 2.7 to 4.1 per cent.
Conclusion
The head and neck cancer risk calculator version 2 had high sensitivity in cancer diagnosis. More studies are required to optimise the predicted versus actual cancer probability gap.
The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors.
Method
Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change.
Results
Prospective symptom analyses showed small decreases in depression (PHQ-9: −0.43 points) and anxiety [generalised anxiety disorder scale – 7 items (GAD)-7: −0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status.
Conclusions
We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity.