Recent changes to US research funding are having far-reaching consequences that imperil the integrity of science and the provision of care to vulnerable populations. Resisting these changes, the BJPsych Portfolio reaffirms its commitment to publishing mental science and advancing psychiatric knowledge that improves the mental health of one and all.

The First Large Absorption Survey in H i (FLASH) is a large-area radio survey for neutral hydrogen in and around galaxies in the intermediate redshift range 0.4 < z < 1.0, using the 21-cm H i absorption line as a probe of cold neutral gas. The survey uses the ASKAP radio telescope and will cover 24,000 deg2 of sky over the next five years. FLASH breaks new ground in two ways – it is the first large H i absorption survey to be carried out without any optical preselection of targets, and we use an automated Bayesian line-finding tool to search through large datasets and assign a statistical significance to potential line detections. Two Pilot Surveys, covering around 3000 deg2 of sky, were carried out in 2019-22 to test and verify the strategy for the full FLASH survey. The processed data products from these Pilot Surveys (spectral-line cubes, continuum images, and catalogues) are public and available online. In this paper, we describe the FLASH spectral-line and continuum data products and discuss the quality of the H i spectra and the completeness of our automated line search. Finally, we present a set of 30 new H i absorption lines that were robustly detected in the Pilot Surveys, almost doubling the number of known H i absorption systems at 0.4 < z < 1. The detected lines span a wide range in H i optical depth, including three lines with a peak optical depth τ > 1, and appear to be a mixture of intervening and associated systems. Interestingly, around two-thirds of the lines found in this untargeted sample are detected against sources with a peaked-spectrum radio continuum, which are only a minor (5-20%) fraction of the overall radio-source population. The detection rate for H i absorption lines in the Pilot Surveys (0.3 to 0.5 lines per 40 deg2 ASKAP field) is a factor of two below the expected value. One possible reason for this is the presence of a range of spectral-line artefacts in the Pilot Survey data that have now been mitigated and are not expected to recur in the full FLASH survey. A future paper in this series will discuss the host galaxies of the H i absorption systems identified here.

This paper reports an expansion of the English as a second language (L2) component of the Multilingual Eye Movement Corpus (MECO L2), an international database of eye movements during text reading. While the previous Wave 1 of the MECO project (Kuperman et al., 2023) contained English as a L2 reading data from readers with 12 different first language (L1) backgrounds, the newly collected dataset adds eye-tracking data on English text reading from 13 distinct L1 backgrounds (N = 660) as well as participants’ scores on component skills of English proficiency and information about their demographics and language background and use. The paper reports reliability estimates, descriptive statistics, and correlational analyses as means to validate the expansion dataset. Consistent with prior literature and the MECO Wave 1, trends in the MECO Wave 2 data include a weak correlation between reading comprehension and oculomotor measures of reading fluency and a greater L1-L2 contrast in reading fluency than reading comprehension. Jointly with Wave 1, the MECO project includes English reading data from more than 1,200 readers representing a diversity of native writing systems (logographic, abjad, abugida, and alphabetic) and 19 distinct L1 backgrounds. We provide multiple pointers to new venues of how L2 reading researchers can mine this rich publicly available dataset.

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.

Two studies were conducted in 2022 and 2023 near Rocky Mount and Clayton, NC, to determine the optimal granular ammonium sulfate (AMS) rate and application timing for pyroxasulfone-coated AMS. In the rate study, AMS rates included 161, 214, 267, 321, 374, 428, and 481 kg ha−1, equivalent to 34, 45, 56, 67, 79, 90, and 101 kg N ha−1, respectively. All rates were coated with pyroxasulfone at 118 g ai ha−1 and topdressed onto 5- to 7-leaf cotton. In the timing study, pyroxasulfone (118 g ai ha−1) was coated on AMS and topdressed at 321 kg ha−1 (67 kg N ha−1) onto 5- to 7-leaf, 9- to 11-leaf, and first bloom cotton. In both studies, weed control and cotton tolerance to pyroxasulfone-coated AMS were compared to pyroxasulfone applied POST and POST-directed. The check in both studies received non-herbicide-treated AMS (321 kg ha−1). Before treatment applications, all plots (including the check) were maintained weed-free with glyphosate and glufosinate. In both studies, pyroxasulfone applied POST was most injurious (8% to 16%), while pyroxasulfone-coated AMS resulted in ≤4% injury. Additionally, no differences in cotton lint yield were observed in either study. With the exception of the lowest rate of AMS (161 kg ha−1; 79%), all AMS rates coated with pyroxasulfone controlled Palmer amaranth ≥83%, comparably to pyroxasulfone applied POST (92%) and POST-directed (89%). In the timing study, the application method did not affect Palmer amaranth control; however, applications made at the mid- and late timings outperformed early applications. These results indicate that pyroxasulfone-coated AMS can control Palmer amaranth comparably to pyroxasulfone applied POST and POST-directed, with minimal risk of cotton injury. However, the application timing could warrant additional treatment to achieve adequate late-season weed control.

Several algorithms for covariance structure analysis are considered in addition to the Fletcher-Powell algorithm. These include the Gauss-Newton, Newton-Raphson, Fisher Scoring, and Fletcher-Reeves algorithms. Two methods of estimation are considered, maximum likelihood and weighted least squares. It is shown that the Gauss-Newton algorithm which in standard form produces weighted least squares estimates can, in iteratively reweighted form, produce maximum likelihood estimates as well. Previously unavailable standard error estimates to be used in conjunction with the Fletcher-Reeves algorithm are derived. Finally all the algorithms are applied to a number of maximum likelihood and weighted least squares factor analysis problems to compare the estimates and the standard errors produced. The algorithms appear to give satisfactory estimates but there are serious discrepancies in the standard errors. Because it is robust to poor starting values, converges rapidly and conveniently produces consistent standard errors for both maximum likelihood and weighted least squares problems, the Gauss-Newton algorithm represents an attractive alternative for at least some covariance structure analyses.

An experiment was conducted in 2022 and 2023 near Rocky Mount and Clayton, NC, to evaluate residual herbicide-coated fertilizer for cotton tolerance and Palmer amaranth control. Treatments included acetochlor, atrazine, dimethenamid-P, diuron, flumioxazin, fluometuron, fluridone, fomesafen, linuron, metribuzin, pendimethalin, pyroxasulfone, pyroxasulfone + carfentrazone, S-metolachlor, and sulfentrazone. Each herbicide was individually coated on granular ammonium sulfate (AMS) and top-dressed at 321 kg ha−1 (67 kg N ha−1) onto 5- to 7-leaf cotton. The check plots received the equivalent rate of nonherbicide-treated AMS. Before top-dress, all plots (including the check) were treated with glyphosate and glufosinate to control previously emerged weeds. All herbicides except metribuzin resulted in transient cotton injury. Cotton response to metribuzin varied by year and location. In 2022, metribuzin caused 11% to 39% and 8% to 17% injury at the Clayton and Rocky Mount locations, respectively. In 2023, metribuzin caused 13% to 32% injury at Clayton and 73% to 84% injury at Rocky Mount. Pyroxasulfone (91%), pyroxasulfone + carfentrazone (89%), fomesafen (87%), fluridone (86%), flumioxazin (86%), and atrazine (85%) controlled Palmer amaranth ≥85%. Pendimethalin and fluometuron were the least effective treatments, resulting in 58% and 62% control, respectively. As anticipated, early season metribuzin injury translated into yield loss; plots treated with metribuzin yielded 640 kg ha−1 and were comparable to yields after linuron (790 kg ha−1) was used. These findings suggest that with the exception of metribuzin, residual herbicides coated onto AMS may be suitable and effective in cotton production, providing growers with additional modes of action for late-season control of multiple herbicide–resistant Palmer amaranth.

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.

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.

Background: Circadian rhythms are implicated in timing of stroke onset and infarct progression in adults, but this has not been studied in pediatric/young adult populations. Methods: We queried the RAPID Insights database from centers in USA for unique patients <25 years with a CTP (10/05/2018-09/29/2023) and a minimum ischemic core volume (defined as relative cerebral blood flow (rCBF) reduction of <30%) of >0 cc and minimum mismatch of >0 cc. Imaging time was subdivided into three epochs: Nigh (23:00 h-06:59 h), Day (07:00 h-14:59 h), and Evening (15:00 h-22:59 h). We analyzed age by pre-defined strata: <2 years, 2-5, 6-11, 12-18 and 19-25. Perfusion parameters (core, perfusion volume, mismatch ratio) were analyzed using descriptive statistics. Results: 836 patients were included; 52.3% were in the 19-25 category. Median ischemic cores were larger during the Night (23.0cc [10.0 – 58.0]) compared to Day (19.0cc [8.0-42.0]) or Evening (15.0cc [7.0-33.0]), p=0.009. There was a trend towards larger perfusion volumes in the Night epoch. In the 19-25 group, perfusion volumes were significantly larger at Night (127.5cc [51.5 – 203.5]) compared to Day (74.0cc [33.0 – 139.0]) or Evening (76.0cc [38.0 – 157.5]), with larger mismatch volumes at Night. Conclusions: This is the first study to demonstrate diurnal fluctuations in perfusion parameters in a predominantly pediatric cohort.

OBJECTIVES/GOALS: In this study, we aim to report the role of porins and blaCTX-M β-lactamases among Escherichia coli and Klebsiella pneumoniae, focusing on emerging carbapenem resistant Enterobacterales (CRE) subtypes, including non-carbapenemase producing Enterobacterales (NCPE) and ertapenem-resistant but meropenem-susceptible (ErMs) strains. METHODS/STUDY POPULATION: Whole genome sequencing was conducted on 76 carbapenem-resistant isolates across 5 hospitals in San Antonio, U.S. Among these, NCP isolates accounted for the majority of CRE (41/76). Identification and antimicrobial susceptibility testing (AST) results were collected from the clinical charts. Repeat speciation was determined through whole genome sequencing (WGS) analysis and repeat AST, performed with microdilution or ETEST®. Minimum inhibitory concentrations (MIC) were consistent with Clinical and Laboratory Standards Institute (CLSI M100, ED33). WGS and qPCR were used to characterize the resistome of all clinical CRE subtypes, while western blotting and liquid chromatography with tandem mass spectrometry (LC-MS-MS) were used to determine porin expression and carbapenem hydrolysis, respectively. RESULTS/ANTICIPATED RESULTS: blaCTX-Mwas found to be most prevalent among NCP isolates (p = 0.02). LC-MS/MS analysis of carbapenem hydrolysis revealed that blaCTX-M-mediated carbapenem hydrolysis, indicating the need to reappraise the term, “non-carbapenemase (NCP)®” for quantitatively uncharacterized CRE strains harboring blaCTX-M. Susceptibility results showed that 56% of all NCPE isolates had an ErMs phenotype (NCPE vs. CPE, p < 0.001), with E. coli driving the phenotype (E. coli vs. K. pneumoniae, p < 0.001). ErMs strains carrying blaCTX-M, had 4-fold more copies of blaCTX-M than ceftriaxone-resistant but ertapenem-susceptible isolates (3.7 v. 0.9, p < 0.001). Immunoblot analysis demonstrated the absence of OmpC expression in NCP-ErMs E. coli, with 92% of strains lacking full contig coverage ofompC. DISCUSSION/SIGNIFICANCE: Overall, this work provides evidence of a collaborative effort between blaCTX-M and OmpC in NCP strains that confer resistance to ertapenem but not meropenem. Clinically, CRE subtypes are not readily appreciated, potentially leading to mismanagement of CRE infected patients. A greater focus on optimal treatments for CRE subtypes is needed.

OBJECTIVES/GOALS: Irritability, a proneness to anger and frustration, is a transdiagnostic symptom associated with poor mental health outcomes. Levels of irritability vary across development and high-risk trajectories have been observed. This study aims to use machine learning to predict irritability trajectories across the transition to adolescence. METHODS/STUDY POPULATION: Data were from the Adolescent Brain Cognitive Development (ABCD) Study, which is a 10-year longitudinal study that tracks the brain development, cognitive skills, physical health, and psychosocial functioning of a large, national sample starting from preadolescence. The baseline sample consisted of 11,861 9-10-year-old preadolescent youth. Irritability was parent-rated at baseline, 1-year, 2-year, 3-year, and 4-year follow-ups on the Child Behavior Checklist (CBCL) irritability index. Latent class growth analysis (LCGA) was used to determine developmental trajectories of irritability. Two machine learning approaches were applied to develop predictive models of youth irritability developmental trajectories. We used baseline (preadolescent) variables that spanned a wide range of domains. RESULTS/ANTICIPATED RESULTS: Preliminary results fromthe LCGA indicated best support for a four-class model that differentiated growth trajectories in irritability across the transition to adolescence: 1) persistent low irritability (n = 8691, 73.27%), 2) moderate irritability and decreasing (n = 1257, 10.60%), 3) low to moderate irritability and increasing (n = 1295, 10.92%), and 4) chronic high irritability (n = 618, 5.21%). We expect the machine learning analyses to generate predictive models with acceptable accuracy. We hypothesize that the most important predictors in the models will originate from the youth mental health domain, including baseline youth irritability, externalizing symptoms, internalizing symptoms, and oppositional behaviors, and the parent psychopathology domain, particularly parent irritability. DISCUSSION/SIGNIFICANCE: The present study elucidates unique developmental trajectories of irritability and generates predictive models to classify high-risk irritability trajectories using machine learning approaches. Clinicians can use these predictive models to identify at-risk youth and provide early intervention to preadolescents at high risk.

OBJECTIVES/GOALS: Our objective is to develop a Telenephrology dashboard for the 150,000 Veterans that obtain care through the Iowa City Veterans Affairs Health Care System. Our goal is to create a comprehensive and user-friendly tool for monitoring kidney health and facilitating remote nephrology consultations. METHODS/STUDY POPULATION: We structured our intervention according to the five stages of human-centered design: (1) Empathize, (2) Define, (3) Ideate, (4) Prototype and (5) Test. During the empathy stage, the principal investigator spent 10 hours immersed in the clinical setting observing how nephrologists approach a remote nephrology consultation. These observations were augmented by unstructured interviews with clinicians and patients to better understand the process and dynamics. Following this, a rapid ideation workshop was convened to generate creative solutions that balance technical requirements with the needs of clinicians and patients. These led to rapid prototyping and testing to identify what elements of the prototypes worked and which needed improvement. RESULTS/ANTICIPATED RESULTS: Through the empathy and define stages, three needs were identified: (1) clarity in visualizing data, (2) accuracy of information, and (3) balancing standardization with individualization. During the rapid ideation workshop, the concept of a four-frame dashboard was settled upon. This led to the creation of five prototypes, which were tested. These were reconciled and modified to make a final product. This final product, the Telenephrology Dashboard, contains 5 elements that support nephrologists and supporting staff: (1) a graph of kidney function over time, (2) tables synthesizing lab data, (3) options to drill down events to specific times, (4) customization of views, and (5) integration of kidney disease progression models. DISCUSSION/SIGNIFICANCE: A Telenephrology dashboard was created to facilitate remote nephrology consultations through a Human-Centered Design process. Our next steps include determining if this dashboard may improve end-user satisfaction, referring clinician satisfaction, access to specialist care, and patient outcomes.

The reading the mind in the eyes test (RMET) – which assesses the theory of mind component of social cognition – is often used to compare social cognition between patients with schizophrenia and healthy controls. There is, however, no systematic review integrating the results of these studies. We identified 198 studies published before July 2020 that administered RMET to patients with schizophrenia or healthy controls from three English-language and two Chinese-language databases. These studies included 41 separate samples of patients with schizophrenia (total n = 1836) and 197 separate samples of healthy controls (total n = 23 675). The pooled RMET score was 19.76 (95% CI 18.91–20.60) in patients and 25.53 (95% CI 25.19–25.87) in controls (z = 12.41, p < 0.001). After excluding small-sample outlier studies, this difference in RMET performance was greater in studies using non-English v. English versions of RMET (Chi [Q] = 8.54, p < 0.001). Meta-regression analyses found a negative association of age with RMET score and a positive association of years of schooling with RMET score in both patients and controls. A secondary meta-analysis using a spline construction of 180 healthy control samples identified a non-monotonic relationship between age and RMET score – RMET scores increased with age before 31 and decreased with age after 31. These results indicate that patients with schizophrenia have substantial deficits in theory of mind compared with healthy controls, supporting the construct validity of RMET as a measure of social cognition. The different results for English versus non-English versions of RMET and the non-monotonic relationship between age and RMET score highlight the importance of the language of administration of RMET and the possibility that the relationship of aging with theory of mind is different from the relationship of aging with other types of cognitive functioning.