Multicenter clinical trials are essential for evaluating interventions but often face significant challenges in study design, site coordination, participant recruitment, and regulatory compliance. To address these issues, the National Institutes of Health’s National Center for Advancing Translational Sciences established the Trial Innovation Network (TIN). The TIN offers a scientific consultation process, providing access to clinical trial and disease experts who provide input and recommendations throughout the trial’s duration, at no cost to investigators. This approach aims to improve trial design, accelerate implementation, foster interdisciplinary teamwork, and spur innovations that enhance multicenter trial quality and efficiency. The TIN leverages resources of the Clinical and Translational Science Awards (CTSA) program, complementing local capabilities at the investigator’s institution. The Initial Consultation process focuses on the study’s scientific premise, design, site development, recruitment and retention strategies, funding feasibility, and other support areas. As of 6/1/2024, the TIN has provided 431 Initial Consultations to increase efficiency and accelerate trial implementation by delivering customized support and tailored recommendations. Across a range of clinical trials, the TIN has developed standardized, streamlined, and adaptable processes. We describe these processes, provide operational metrics, and include a set of lessons learned for consideration by other trial support and innovation networks.

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.

Increased temporal variability in the gut microbiome is associated with intestinal conditions such as ulcerative colitis and Crohn’s disease, leading to the recently established concept of microbial volatility (1). Increased physiological stress has been shown to increase microbial volatility indicating that microbial volatility is susceptible to external interventions(1). Dietary fibre positively affects the gut microbiome, but it is unclear if it impacts microbial volatility. The gut microbiota influences hypertension, and high-fibre intake reduces blood pressure (BP)(2). However, not all individuals exhibit a response to these fibre-based dietary changes, and the reasons for this variability remain unclear. Similarly, it is unknown whether the degree of stability of the gut microbiota consortium could be a determining factor in individual responsiveness to dietary interventions. Here, we aimed to identify: i) whether gut microbiome volatility differs when dietary fibre vs placebo interventions, and ii) whether microbiome volatility discriminates between BP responders and non-responders to a high fibre intervention. Twenty treatment-naive participants with hypertension received either placebo or 40g per day of prebiotic acetylated and butyrylated high amylose maize starch (HAMSAB) supplementation for 3 weeks in a phase II randomised cross-over double-blind placebo-controlled trial(3). Blood pressure was monitored at baseline and each endpoint by 24-hour ambulatory BP monitoring, with those experiencing a reduction between timepoints of ≥ 2 mmHg classified as responders. Baseline stool samples were collected, and the V4 region of the 16S gene was sequenced. Taxonomy was assigned by reference to the SILVA database. Microbial volatility between timepoints (e.g., pre- and post-intervention) was calculated as the Euclidian distance of centred log-ratio transformed genera counts (Aitchison distance). No difference was observed in microbial volatility between individuals when they received the dietary fibre intervention or the placebo (21.5 ± 5.5 vs 20.5 ± 7.7, p = 0.51). There was no significant difference between microbial volatility on the dietary intervention between responders and non-responders (21.8 ± 4.9 vs 20.9 ± 7.2, p = 0.84). There was no association between the change in BP during intervention and microbial volatility during intervention (r2 = −0.09, p = 0.72). These data suggest that temporal volatility of the gut microbiota does not change with fibre intake or contribute to the BP response to dietary fibre intervention trials in people with hypertension.

The marketing of unhealthy foods has been implicated in poor diet and rising levels of obesity. Rapid developments in the digital food marketing ecosystem and associated research mean that contemporary review of the evidence is warranted. This preregistered (CRD420212337091)1 systematic review and meta-analysis aimed to provide an updated synthesis of the evidence for behavioural and health impacts of food marketing on both children and adults, using the 4Ps framework (Promotion, Product, Price, Place). Ten databases were searched from 2014 to 2021 for primary data articles of quantitative or mixed design, reporting on one or more outcome of interest following food marketing exposure compared with a relevant control. Reviews, abstracts, letters/editorials and qualitative studies were excluded. Eighty-two studies were included in the narrative review and twenty-three in the meta-analyses. Study quality (RoB2/Newcastle–Ottawa scale) was mixed. Studies examined ‘promotion’ (n 55), ‘product’ (n 17), ‘price’ (n 15) and ‘place’ (n 2) (some > 1 category). There is evidence of impacts of food marketing in multiple media and settings on outcomes, including increased purchase intention, purchase requests, purchase, preference, choice, and consumption in children and adults. Meta-analysis demonstrated a significant impact of food marketing on increased choice of unhealthy foods (OR = 2·45 (95 % CI 1·41, 4·27), Z = 3·18, P = 0·002, I2 = 93·1 %) and increased food consumption (standardised mean difference = 0·311 (95 % CI 0·185, 0·437), Z = 4·83, P < 0·001, I2 = 53·0 %). Evidence gaps were identified for the impact of brand-only and outdoor streetscape food marketing, and for data on the extent to which food marketing may contribute to health inequalities which, if available, would support UK and international public health policy development.

Yuan and Chan (Psychometrika, 76, 670–690, 2011) recently showed how to compute the covariance matrix of standardized regression coefficients from covariances. In this paper, we describe a method for computing this covariance matrix from correlations. Next, we describe an asymptotic distribution-free (ADF; Browne in British Journal of Mathematical and Statistical Psychology, 37, 62–83, 1984) method for computing the covariance matrix of standardized regression coefficients. We show that the ADF method works well with nonnormal data in moderate-to-large samples using both simulated and real-data examples. R code (R Development Core Team, 2012) is available from the authors or through the Psychometrika online repository for supplementary materials.

A general theory on the use of correlation weights in linear prediction has yet to be proposed. In this paper we take initial steps in developing such a theory by describing the conditions under which correlation weights perform well in population regression models. Using OLS weights as a comparison, we define cases in which the two weighting systems yield maximally correlated composites and when they yield minimally similar weights. We then derive the least squares weights (for any set of predictors) that yield the largest drop in R2 (the coefficient of determination) when switching to correlation weights. Our findings suggest that two characteristics of a model/data combination are especially important in determining the effectiveness of correlation weights: (1) the condition number of the predictor correlation matrix, Rxx, and (2) the orientation of the correlation weights to the latent vectors of Rxx.

In a multiple regression analysis with three or more predictors, every set of alternate weights belongs to an infinite class of “fungible weights” (Waller, Psychometrica, in press) that yields identical SSE (sum of squared errors) and R2 values. When the R2 using the alternate weights is a fixed value, fungible weights (ai) that yield the maximum or minimum cosine with an OLS weight vector (b) are called “fungible extrema.” We describe two methods for locating fungible extrema and we report R code (R Development Core Team, 2007) for one of the methods. We then describe a new approach for populating a class of fungible weights that is derived from the geometry of alternate regression weights. Finally, we illustrate how fungible weights can be profitably used to gauge parameter sensitivity in linear models by locating the fungible extrema of a regression model of executive compensation (Horton & Guerard, Commun. Stat. Simul. Comput. 14:441–448, 1985).

Field experiments were conducted at Clayton and Rocky Mount, NC, during summer 2020 to determine the growth and fecundity of Palmer amaranth plants that survived glufosinate with and without grass competition in cotton. Glufosinate (590 g ai ha−1) was applied to Palmer amaranth early postemergence (5 cm tall), mid-postemergence (7 to 10 cm tall), and late postemergence (>10 cm tall) and at orthogonal combinations of those timings. Nontreated Palmer amaranth was grown in weedy, weed-free in-crop (WFIC) and weed-free fallow (WFNC) conditions for comparisons. Palmer amaranth control decreased as larger plants were treated; no plants survived the sequential glufosinate applications in both experiments. The apical and circumferential growth of Palmer amaranth surviving glufosinate treatments was reduced by more than 44% compared to the WFIC and WFNC Palmer amaranth in both experiments. The biomass of Palmer amaranth plants surviving glufosinate was reduced by more than 62% when compared with the WFIC and WFNC in all experiments. The fecundity of Palmer amaranth surviving glufosinate treatments was reduced by more than 73% compared to WFNC Palmer amaranth in all experiments. Remarkably, the plants that survived glufosinate were fecund as WFIC plants only in the Grass Competition experiment. The results prove that despite decreased vegetative growth of Palmer amaranth surviving glufosinate treatment, plants remain fecund and can be fecund as nontreated plants in cotton. These results suggest that a glufosinate-treated grass weed may not have a significant interspecific competition effect on Palmer amaranth that survives glufosinate. Glufosinate should be applied to 5 to 7 cm Palmer amaranth to cease vegetative and reproductive capacities.

Field experiments were conducted at Clayton and Rocky Mount, North Carolina, during the summer of 2020 to determine the growth and fecundity of Palmer amaranth plants that survived glufosinate with and without grass competition in soybean crops. Glufosinate (590 g ai ha−1) was applied at early postemergence (when Palmer amaranth plants were 5 cm tall), mid-postemergence (7–10 cm), and late postemergence (>10 cm) and at orthogonal combinations of those timings. Nontreated Palmer amaranth was grown in weedy (i.e., intraspecific and grass competition), weed-free in-crop (WFIC), and weed-free fallow (WFNC) conditions for comparisons. No Palmer amaranth plants survived the sequential glufosinate applications and control decreased as the plants were treated at a larger size in both experiments. The apical and circumferential growth rate of Palmer amaranth surviving glufosinate was reduced by more than 44% compared with the WFNC Palmer amaranth. The biomass of Palmer amaranth plants that survived glufosinate was reduced by more than 87% compared with the WFNC Palmer amaranth. The fecundity of Palmer amaranth that survived glufosinate was reduced by more than 70% compared with WFNC Palmer amaranth. Palmer amaranth plants that survived glufosinate were as fecund as the WFIC Palmer amaranth in both experiments in soybean fields. The results prove that despite the significant vegetative growth rate decrease of Palmer amaranth that survived glufosinate, plants can be as fecund as nontreated plants. The trends in growth and fecundity of Palmer amaranth that survives glufosinate with and without grass competition were similar. These results suggest that glufosinate-treated grass weeds may not reduce the growth or fecundity of Palmer amaranth that survives glufosinate.

OBJECTIVES/GOALS: Seeking ways to support teams in the preparation for and the implementation of the new National Institutes of Health (NIH) Policy for Data Management and Sharing (DMSP), the integrated Translational Health Research Institute of Virginia (iTHRIV) partnered with the UVA Health Sciences Library to develop training and resources for researchers. METHODS/STUDY POPULATION: Health sciences librarians and iTHRIV (an NIH-NCATS supported Clinical Translational Research Institute) convened a Working Group, inviting representatives from central and unit-specific research support offices (e.g. the Comprehensive Cancer Center), research compliance, regulatory affairs, sponsored programs, institutional review boards, libraries, and data science to review and discuss the DMSP requirements. After an initial orientation to the policy, the group reviewed existing public resources and solicited feedback about steps to best support UVA researchers in compliance. Leveraging the broad expertise of the group, the team provides guidance to researchers on writing the DMS plan and choosing a data repository, and provides tools and templates to support implementation of the policy. RESULTS/ANTICIPATED RESULTS: A library-created website provided policy guidance, including links to NIH-hosted information, resources created by other institutions, and new UVA-specific templates and suggested proposal language. Librarians led a webinar on the new policy and UVA resources which included a speaker from UVA regulatory affairs to describe the new DMSP requirements, and a tour of the new guide. The guide has been viewed over 5000 times to date and librarians have provided consultations and training to individuals and departments. Current plans include developing a user satisfaction survey, reviewing DMSP feedback from submitted proposals, and incorporating lessons learned into the website and future training. DISCUSSION/SIGNIFICANCE: The collaboration between iTHRIV and the Health Sciences Library to support the NIH Data Management and Sharing Policy was a successful partnership that provided leadership at the institutional level to communicate with and engage researchers and utilized the library’s web presence, expertise, and service model to provide direct support.

OBJECTIVES/GOALS: The COVID-19 pandemic disrupted established social support networks (faith-based, community, family, friends), resulting in unprecedented health-related, financial, and employment challenges among African Americans (AAs). This study explores the psychosocial influences of the pandemic on the health and wellness of AAs. METHODS/STUDY POPULATION: The FAITH! (Fostering African-American Improvement in Total Health!) Program, an academic-community partnership with AA churches, shifted focus to COVID-19 prevention in AA communities. Funded by the Mayo Clinic Center for Clinical and Translation Sciences, this cross-sectional study recruited AA adults from FAITH!-affiliated churches and social media to complete a survey exploring the personal impact of the pandemic from hardships (e.g., food and housing insecurity, paying utilities) on healthy lifestyle (HL). The primary outcome was difficulty maintaining a HL during the pandemic. Logistic regression (odds ratios and associated 95% confidence intervals (CIs)) was used to examine the associations between difficulty maintaining a HL and factors including COVID-19 hardships and mental health. RESULTS/ANTICIPATED RESULTS: Participants (N=169, 71.4% female, 41.4% essential workers) had a mean age [SD] of 49.4 [14.9] years. Over half (91/169, 54%) reported difficulty maintaining a HL. Those reporting unemployment (OR 2.3; 95% CI [1.2,4.4]; p=0.008), difficulty paying rent (OR 4.1; 95% CI [2.1,8.6]; p<0.001), or food/utilities (OR 5.5; 95% CI [2.7,11.5]; p<0.001) all had greater odds of difficulty maintaining a HL. High stress (≥5/10, scale 1-10) was associated with difficulty maintaining a HL (OR 4.1; 95% CI [2.1,8.5]; p<0.001) compared to AAs with low stress. Negative mental health (depression (OR 3.4; 95% CI [1.0,13.7]; p<0.001), anger (OR 2.5; 95% CI [0.5,18.9]; p=0.005), and nervousness (OR 4.1; 95% CI [1.1,19.5]; p=0.003) was associated with difficulty maintaining a HL compared to AAs with positive mental health. DISCUSSION/SIGNIFICANCE: Our study findings revealed that COVID-19 hardships, stress, and negative mental health impacted the ability of AAs to maintain a HL. These issues should be considered in the design and implementation of community-based health programs to promote healthy living during future public health emergencies.

Odd Radio Circles (ORCs) are a class of low surface brightness, circular objects approximately one arcminute in diameter. ORCs were recently discovered in the Australian Square Kilometre Array Pathfinder (ASKAP) data and subsequently confirmed with follow-up observations on other instruments, yet their origins remain uncertain. In this paper, we suggest that ORCs could be remnant lobes of powerful radio galaxies, re-energised by the passage of a shock. Using relativistic hydrodynamic simulations with synchrotron emission calculated in post-processing, we show that buoyant evolution of remnant radio lobes is alone too slow to produce the observed ORC morphology. However, the passage of a shock can produce both filled and edge-brightnened ORC-like morphologies for a wide variety of shock and observing orientations. Circular ORCs are predicted to have host galaxies near the geometric centre of the radio emission, consistent with observations of these objects. Significantly offset hosts are possible for elliptical ORCs, potentially causing challenges for accurate host galaxy identification. Observed ORC number counts are broadly consistent with a paradigm in which moderately powerful radio galaxies are their progenitors.

There are numerous challenges pertaining to epilepsy care across Ontario, including Epilepsy Monitoring Unit (EMU) bed pressures, surgical access and community supports. We sampled the current clinical, community and operational state of Ontario epilepsy centres and community epilepsy agencies post COVID-19 pandemic. A 44-item survey was distributed to all 11 district and regional adult and paediatric Ontario epilepsy centres. Qualitative responses were collected from community epilepsy agencies. Results revealed ongoing gaps in epilepsy care across Ontario, with EMU bed pressures and labour shortages being limiting factors. A clinical network advising the Ontario Ministry of Health will improve access to epilepsy care.