This proof-of-concept study evaluated an optimization strategy for the Community Case Detection Tool (CCDT) aimed at improving community-level mental health detection and help-seeking among children aged 6–18 years. The optimization strategy, CCDT+, combined data-driven supervision with motivational interviewing techniques and behavioural nudges for community gatekeepers using the CCDT. This mixed-methods study was conducted from January to May 2023 in Palorinya refugee settlement in Uganda. We evaluated (1) the added value of the CCDT+ in improving the accuracy of detection and mental health service utilization compared to standard CCDT, and (2) implementation outcomes of the CCDT+. Of the 1026 children detected, 801 (78%) sought help, with 656 needing mental health care (PPV = 0.82; 95% CI: 0.79, 0.84). The CCDT+ significantly increased detection accuracy, with 2.34 times higher odds compared to standard CCDT (95% CI: 1.41, 3.83). Additionally, areas using the CCDT+ had a 2.05-fold increase in mental health service utilization (95% CI: 1.09, 3.83). The CCDT+ shows promise as an embedded quality-optimization process for the detection of mental health problems among children and enhance help-seeking, potentially leading to more efficient use of mental health care resources.

This abstract was presented as the Novel Nutrition Research Methodologies and Technologies

Theme Highlight. Queuosine (Q) is a vital micronutrient crucial for protein translation and cellular function in humans. Deficiencies of Q have been linked to chronic illnesses, such as inflammatory bowel disease, neurodegenerative diseases, and various cancers. Human requirements for this micronutrient have not yet been established. Thus far, there has been no systematic investigation of the human diet to understand typical intakes. It is necessary to measure the levels of Q metabolites in commonly consumed foods to identify the richest dietary sources and determine Q intake. Only then can its role in human health and disease be established.

This study aimed to comprehensively analyse Q distribution in the UK diet by quantifying it in foods, identifying rich sources, and ultimately, enabling the design of dietary intervention studies assessing Q absorption/bioavailability.

Data from the UK National Diet and Nutrition Survey (NDNS 5Y) were processed to identify the most frequently consumed foods in 31 main categories, reflecting the dietary habits of >99.5% of UK consumers. Extraction techniques were developed, including a methanol-based method for extracting free Q metabolites and a specialized approach for isolating tRNA-bound Q metabolites from various food matrices. Quantitative LC-MS/MS (SCIEX 5500+) was utilized to accurately measure queuine (q), Q, Q monophosphates (QMPs), and Q precursor (PreQ1) in food samples. These values were summed to determine Total Q levels. Additionally, four-day food diary data from 93 participants in the Northern Ireland Dietary Assessment Study (NIDAS) were analysed to determine the average daily consumption of Q metabolites in adults. Dairy sources were considered promising, so five commercial probiotic yoghurt brands were compared side-by-side.

Q metabolite levels varied significantly across various food types. Total Q metabolite levels in foods ranged from 0.05ng/g to 80ng/g, with a mean level of 20ng/g. The calculated Q consumption of participants in NIDAS ranged from nil/day in some individuals to 170µg/day in others, with a typical mean intake of 18µg/day. The mean amounts (ng/g) of Total Q metabolites (tRNA-bound + free) measured in food categories were dairy 57.2 ± 9.7, meat 20.1 ± 9.9, poultry 4.9 ± 4, and plant-based milk 15.3 ± 10, fruits 2 ± 1.3, vegetables 5.3 ± 2.8, starchy foods 2.2 ± 0.7. Dairy products emerged as significant sources of Q metabolites based on these findings. Concentrations observed in shortlisted probiotic yoghurts ranged from 32 to 352 ng/g.

This study determined typical Q intakes and is the first to identify Q-rich food sources in the UK diet. The highly Q-enriched probiotic yoghurt products could be used in controlled dietary intervention studies to assess Q absorption/bioavailability and this micronutrient’s role in human health and disease.

The thermal reaction sequence of a synthetic hectorite (Laponite CP) was studied by X-ray diffraction, i.r. spectroscopy and thermal analysis. Although most of the interlayer water is removed at 200°C, a smally steady weight loss occurs until dehydroxylation is complete at about 700°C, indicating that an anhydrous intermediate phase is not formed prior to dehydroxylation. Immediately after dehydroxylation, enstatite and cristobalite can be identified, but lithium silicates are formed only from lithium-saturated hectorite. Around 1200°C a glass is formed by reaction of the alkalis with cristobalite, and removal of silica from the enstatite produces some forsterite. An inhomogeneous mechanism of dehydroxylation is postulated by analogy with that proposed for talc.

Laser-driven neutron sources are routinely produced by the interaction of laser-accelerated protons with a converter. They present complementary characteristics to those of conventional accelerator-based neutron sources (e.g. short pulse durations, enabling novel applications like radiography). We present here results from an experiment aimed at performing a global characterization of the neutrons produced using the Titan laser at the Jupiter Laser Facility (Livermore, USA), where protons were accelerated from 23 $\mathrm {\mu }$m thick plastic targets and directed onto a LiF converter to produce neutrons. For this purpose, several diagnostics were used to measure these neutron emissions, such as CR-39, activation foils, time-of-flight detectors and direct measurement of $^7{\rm Be}$ residual activity in the LiF converters. The use of these different, independently operating diagnostics enables comparison of the various measurements performed to provide a robust characterization. These measurements led to a neutron yield of $2.0\times 10^{9}$ neutrons per shot with a modest angular dependence, close to that simulated.

As the federal government continues to expand upon and improve its data sharing policies over the past 20 years, complex challenges remain. Our interviews with U.S. academic genetic researchers (n=23) found that the burden, translation, industry limitations, and consent structure of data sharing remain major governance challenges.

The Maser Monitoring Parkes Project (M2P2) is an ongoing project to observe masers towards high-mass star-forming regions (HMSFRs) using the 64 m CSIRO Parkes radio telescope, Murriyang. In this paper, we outline the project and introduce Stokes-I data from the first two years of observations. For the 63 sightlines observed in this project we identify a total of 1 514 individual maser features: 14.4% of these (203) towards 27 sightlines show significant variability. Most of these (160/203) are seen in the main-line transitions of OH at 1665 and 1667 MHz, but this data set also includes a significant number of variable features in the satellite lines at 1 612 and 1 720 MHz (33 and 10, respectively), most of which (24 and 9, respectively) appear to be associated with the HMSFRs. We divide these features into 4 broad categories based on the behaviour of their intensity over time: flares (6%), periodic (11%), long-term trends (33%), and ‘other’ (50%). Variable masers provide a unique laboratory for the modelling of local environmental conditions of HMSFRs, and follow-up publications will delve into this in more detail.

Ideophones – imitative words using the stream of speech to simulate/depict the rise and fall of sensory perceptions and emotions and temporal experiences of completiveness, instantaneousness, and repetitiveness – have been characterized as semantically empty and context-dependent. The research reported here tested a simple schematic for the semantic categories of Pastaza Kichwa ideophones by tracking neurological responses to ideophones categorized as VISUAL, MOTION, and SOUND. Seventeen native speakers of Pastaza Kichwa listened to audio clips of ideophones extracted from sentential contexts. Subjects’ neural activity was assessed using functional near-infrared spectroscopy. Results demonstrate that these posited semantic categories activate areas of the brain associated with visualization, motion, and sound processing and production, respectively. This suggests that these ideophones convey semantic information related to these concepts, independent of context. This contrasts with what would be expected by theories suggesting that ideophones on their own are semantically empty. The data give rise to questions regarding whether any language contains only sound ideophones that do not carry additional sensory information and whether ideophones in previous studies treated strictly as sound ideophones might require greater specification of their semantics, specifically from a multisensorial perspective.

The GINI project investigates the dynamics of inequality among populations over the long term by synthesising global archaeological housing data. This project brings archaeologists together from around the world to assess hypotheses concerning the causes and consequences of inequality that are of relevance to contemporary societies globally.

De Neys makes a compelling case that the sacrificial moral dilemmas do not elicit competing “fast and slow” processes. But are there even two processes? Or just two intuitions? There remains strong evidence, most notably from lesion studies, that sacrificial dilemmas engage distinct cognitive processes generating conflicting emotional and rational responses. The dual-process theory gets much right, but needs revision.

Changes in executive function (EF) occur during adolescence with several factors (e.g., parenting styles, socioeconomic status) influencing the development of EF abilities. These changes are important as EF has been strongly linked with a range of outcomes including academic achievement, job performance, and social–emotional well-being. However, few studies have examined variability in EF trajectories during this critical developmental period, or trajectories in samples known to have specific impairments with EF, such as adolescents diagnosed with attention-deficit/hyperactivity disorder (ADHD). The present study examined differential trajectories of three domains of parent-rated EF in 302 adolescents (167 males; Mage = 13.17 years) with and without ADHD (53.6% with ADHD) from grade 8 to 10. The study also explored whether adolescent ADHD, parent ADHD, and parents’ own EF predicted EF trajectories in addition to the longitudinal relation between trajectories and academic outcomes. Findings suggest that adolescence is marked by significant variability in EF development due to factors such as ADHD status, parent ADHD, and parent EF ability. Additionally, adolescents who displayed poor EF abilities throughout middle and high school had significantly lower grade point averages and poorer parent-, teacher-, and self-reported academic outcomes. Implications for interventions targeting EF deficits among adolescents with and without ADHD are discussed.

Bacterial superinfection and antibiotic prescribing in the setting of the current mpox outbreak are not well described in the literature. This retrospective observational study revealed low prevalence (11%) of outpatient antibiotic prescribing for bacterial superinfection of mpox lesions; at least 3 prescriptions (23%) were unnecessary.

OBJECTIVES/GOALS: Adolescence represents a critical period for substance use initiation. Various factors may contribute to trying a sip or single puff of a substance, that could lead to more frequent use. However, less is known about how predictors from multiple domains converge to impact risk for general substance use initiation. METHODS/STUDY POPULATION: The Adolescent Brain Cognitive Development (ABCD) study is a multi-site longitudinal study following youth into early adulthood. The present study included 7,644 ABCD children who reported no lifetime substance use (including any experimentation) at baseline (ages 9–10). Our primary aim was to use a random forest classification model to predict binary substance use initiation, defined as trying any non-prescribed substance (e.g., alcohol, tobacco, cannabis, non-prescribed medications), during a 2-year follow-up after baseline. A total of 402 variables from the following categories were examined as predictors: demographics, peer substance use and availability, mental and physical health, culture and environment, biospecimens, neurocognitive functioning, and structural neuroimaging variables. RESULTS/ANTICIPATED RESULTS: Over a two-year follow-up, 751 (9.8%) of substance-naïve children reported trying a substance by age 11. The most common substance was alcohol, followed by cannabis and tobacco. Mean Decrease Accuracy (MDA) values were used to assess the relative importance of each predictor. The overall accuracy of the model in accurately predicting group membership (no substance use initiation vs. substance use initiation) was 57.66%. Of the top 5 predictors, the most important predictor was intent to use alcohol (MDA = .002). The following top predictors were structural neuroimaging variables: volume and surface area of right lateral occipital lobe (MDA = .0009 and .0008, respectively), surface area of right inferior temporal lobe (MDA = .0007), and surface area of left superior frontal lobe (MDA = .0007). DISCUSSION/SIGNIFICANCE: A combination of intent to use alcohol and structural neuroimaging indices were among the top predictors of substance use initiation. Understanding predictors of early substance use experimentation is important for identifying at-risk youth that may require targeted intervention approaches.

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

We present the development and characterization of a high-stability, multi-material, multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 Hz. The tape surface position was measured to be stable on the sub-micrometre scale, compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers ($>$kHz). Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended periods. The target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team, with the exception of tape replacement, producing the largest data-set of relativistically intense laser–solid foil measurements to date. This tape drive provides robust targetry for the generation and study of high-repetition-rate ion beams using next-generation high-power laser systems, also enabling wider applications of laser-driven proton sources.