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Understanding the intricate relationship between brain structure and function is a cornerstone challenge in neuroscience, critical for deciphering the mechanisms that underlie healthy and pathological brain function. In this work, we present a comprehensive framework for mapping structural connectivity measured via diffusion-MRI to resting-state functional connectivity measured via magnetoencephalography, utilizing a deep-learning model based on a Graph Multi-Head Attention AutoEncoder. We compare the results to those from an analytical model that utilizes shortest-path-length and search-information communication mechanisms. The deep-learning model outperformed the analytical model in predicting functional connectivity in healthy participants at the individual level, achieving mean correlation coefficients higher than 0.8 in the alpha and beta frequency bands, in comparison to 0.45 for the analytical model. Our results imply that human brain structural connectivity and electrophysiological functional connectivity are tightly coupled. The two models suggested distinct structure-function coupling in people with psychosis compared to healthy participants ( for the deep-learning model, in the delta band for the analytical model). Importantly, the alterations in the structure-function relationship were much more pronounced than any structure-specific or function-specific alterations observed in the psychosis participants. The findings demonstrate that analytical algorithms effectively model communication between brain areas in psychosis patients within the delta and theta bands, whereas more sophisticated models are necessary to capture the dynamics in the alpha and beta band.

The purpose of this non-experimental descriptive study was to measure psychiatric clinical nurses' ( N = 25) perceptions of the Edmonson Psychiatric Falls Risk Assessment Tool © (EPFRAT) compared to the Morse Fall Scale (MFS) and to evaluate patient falls with injury rates 12 months before and after the study. The setting was a 27-bed, adult psychiatric unit in a community-based teaching hospital located in the Northeast region of the United States. The EPFRAT and MFS were used to assess fall risk in 216 patients over 3 months. Findings indicated that the EPFRAT was more user-friendly and relevant; improved nurses' clinical judgment in identifying high-risk patients; and nurses were supportive toward changing practice from using the MFS to EPFRAT for fall risk assessment. Falls with injury rates decreased by 0.52 per 1,000 patient care days post-implementation of the EPFRAT. [ Journal of Psychosocial Nursing and Mental Health Services, 58 (2), 21–26.]

Abstract Background and aims Cerebrovascular reactivity (CVR) is impaired in cerebral small vessel disease (CSVD), commonly assessed using CO₂ inhalation during MRI. However, this is methodologically challenging and uncomfortable. We assessed whether resting-state BOLD may provide a non-invasive alternative. Methods The crossover-design OxHARP trial tested three weeks of sildenafil versus placebo on MRI-CVR, assessed by 6%-CO₂ gas challenge. Resting-state, high-frequency BOLD-MRI (TR=0.4s, multiband 6) was also acquired with concurrent measurement of end-tidal CO2. After motion correction, high-pass filtering, brain extraction and voxel-wise correction for temporal delays, CVR was determined as correlation between standardised BOLD per mmHg change in etCO2, within grey (GM) and white matter (WM). Agreement between scans was determined by ICC and linear regression, and effects of drug treatment by mixed-effects linear models. Results Across 93 scans, there was significant agreement between challenge-CVR and resting-state CVR in GM (r=0.629, p<0.001, ICC=0.773) and WM (r=0.598, p<0.001, ICC=0.749). There was a similar voxel-wise pattern of increased CVR on sildenafil with both acquisitions, but the average difference by ROIs was only significant with challenge-CVR (Challenge: GM p=0.0108, WM p=0.0020; Resting-state: GM p=0.20, WM: p=0.099). Conclusions Optimised resting-state scanning demonstrates strong agreement with CO₂ gas challenge measures of CVR and may provide a feasible alternative for large-scale CVR assessment, or in populations where individuals are less able to tolerate a gas challenge. However, gas challenges remain optimal for cleanly detecting drug-induced CVR changes in clinical trials. Conflict of interest Vanessa Hyde: nothing to disclose Figure 1 - belongs to Results Figure 2 - belongs to Results

This paper introduces the Welsh Advanced Neuroimaging Database (WAND), a multi-scale, multi-modal imaging dataset comprising in vivo brain data from 170 healthy volunteers (aged 18–63 years), including 3 Tesla (3 T) magnetic resonance imaging (MRI) with ultra-strong (300 mT/m) magnetic field gradients, structural and functional MRI and nuclear magnetic resonance spectroscopy at 3 T and 7 T, magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS), together with trait questionnaire and cognitive data. Data are organised using the Brain Imaging Data Structure (BIDS). In addition to raw data, we provide brain-extracted T1-weighted images, and quality reports for diffusion, T1- and T2-weighted structural data, and blood-oxygen level dependent functional tasks. Reasons for participant exclusion are also included. Data are available for download through our GIN repository, a data access management system designed to reduce storage requirements. Users can interact with and retrieve data as needed, without downloading the complete dataset. Given the depth of neuroimaging phenotyping, leveraging ultra-high-gradient, high-field MRI, MEG and TMS, this dataset will facilitate multi-scale and multi-modal investigations of the healthy human brain.

Understanding the intricate relationship between brain structure and function is a cornerstone challenge in neuroscience, critical for deciphering the mechanisms that underlie healthy and pathological brain function. In this work, we present a comprehensive framework for mapping structural connectivity measured via diffusion-MRI to resting-state functional connectivity measured via magnetoencephalography, utilizing a deep-learning model based on a Graph Multi-Head Attention AutoEncoder. We compare the results to those from an analytical model that utilizes shortest-path-length and search-information communication mechanisms. The deep-learning model outperformed the analytical model in predicting functional connectivity in healthy participants at the individual level, achieving mean correlation coefficients higher than 0.8 in the alpha and beta frequency bands. Our results imply that human brain structural connectivity and electrophysiological functional connectivity are tightly coupled. The two models suggested distinct structure-function coupling in people with psychosis compared to healthy participants (p < 2 × 10−4 for the deep-learning model, p < 3 × 10−3 in the delta band for the analytical model). Importantly, the alterations in the structure-function relationship were much more pronounced than any structure-specific or function-specific alterations observed in the psychosis participants. The findings demonstrate that analytical algorithms effectively model communication between brain areas in psychosis patients within the delta and theta bands, whereas more sophisticated models are necessary to capture the dynamics in the alpha and beta band.

BackgroundDespite increasing commitment to patient engagement in research, evaluation of the impact of these efforts on research processes, products, and teams is limited.ObjectiveTo explore the impacts of engaging patients as consultants to research studies by examining the experiences, impacts, and lessons learned from a program facilitating patient engagement at a Veterans Health Administration research center.DesignWe developed a logic model to articulate the activities being implemented to support patient engagement and their anticipated outcomes. Then, we conducted qualitative, semi-structured interviews with participants in the local Veteran Consulting Network to qualitatively explore these outcomes.ParticipantsTwelve researchers and eleven Veteran patients with experience working on at least one grant or funded study.ApproachInterview transcripts were inductively coded using a consensus-based approach. Findings were synthesized using framework analysis and mapped back onto our logic model of expected patient engagement impacts.Key ResultsPatient engagement improved the perceived quality and relevance of research studies as patient consultants challenged researchers’ assumptions about patient populations and clinical contexts and gave feedback that helped improve the feasibility of proposed grants, readability of study materials, comprehensiveness of study assessments, and cultural sensitivity and relevance of interventions. Patient engagement also had personal benefits to researchers and patients. Researchers reported improved communication skills and higher job satisfaction. Patients reported a sense of purpose and satisfaction from their work with greater awareness of and appreciation for research.ConclusionsEngaging patients in research can have multiple benefits to the people and work involved. Our evaluation process can serve as a template for other organizations to plan for and assess the impact of their own patient engagement programs. Creating logic models and updating them based on feedback from program users make engagement goals explicit, help verify expected mechanisms to achieve impact, and facilitate organizational learning.

This paper explores the disconnect between policy rhetoric and implementation at the intersection of sanitation equity and climate change in Nairobi, Kenya. To examine the current sanitation adaptation trajectory, we reviewed Nairobi’s sanitation policies, planning, and investment frameworks, focusing on their integration with climate adaptation strategies and consideration of equity in terms of distribution, recognition and processes. We used a socio-technical regime framework to map the current sanitation service configurations in Nairobi and projected their future under different climate change scenarios. Our findings provide evidence for a disconnection between policy rhetoric and implementation, prioritising sewerage development at the expense of other sanitation regimes. Despite recognising equity issues in policy, substantive action towards equitable sanitation governance is lacking. This imbalance hinders the realisation of the constitutionally recognised right to adequate sanitation in the foreseeable future. The anticipated impact of climate change on Nairobi’s sanitation sector suggests an exacerbation of existing service inequalities. Our projection indicates that by 2030, a sizeable portion of Nairobi’s residents will experience poor sanitation services. Our study emphasizes the critical need for a fundamental paradigm shift. It calls for a robust and honest discussion on delivering high-quality, resilient sanitation services at scale including both sewer and non-sewered sanitation and necessitating substantial public investment and support for all systems. This reappraisal is imperative for ensuring equitable and sustainable sanitation solutions in the face of climate change.

Human milk banks rely on voluntary donations from lactating individuals producing more milk than their baby needs, to make pasteurised donor human milk (PDHM) for preterm babies. Demand for PDHM is increasing, as is the need for donors. Few Australian studies have explored potential donors' awareness and perceived feasibility of donating to a milk bank. We aimed to survey women breastfeeding their own child (< 24 months) or pregnant (and intending to breastfeed), and residing in major metropolitan areas of Australia, to determine their awareness of milk banks, and interest in and perceived feasibility (ease, eligibility) of donating to a milk bank. 1221 participants completed the survey (112 pregnant women, 1109 breastfeeding women). Most (78%) had heard of milk banks, and 81.7% lived in an area eligible to donate to a milk bank, yet only 11% were aware of a milk bank in their area. Most (60%) pregnant women would prefer to use online sources or health professionals to find information about donation. Most breastfeeding women (77%) were interested in donating milk, however only 26% thought it would be easy to meet milk bank requirements, and that they would be eligible to donate. Barriers to donating for breastfeeding women involved having no excess milk to donate, lack of time to express/donate, and lack of space to store milk. Awareness raising of local milk banks, promotion of donation information amongst healthcare professionals, and modifications to improve feasibility of donation will likely engage new potential donors and ensure sustainability of milk banks. Most breastfeeding and pregnant women in Australia had heard of milk banks, and although most lived in an area where they would be eligible to donate, few were aware of a milk bank in their area. There was high interest among breastfeeding women about donating milk. However, only 26% thought donating would be easy, and they would be eligible to donate. Barriers for breastfeeding women who were interested in donating related to not having enough milk for their own baby, and/or not having enough excess milk to donate. Lack of time to express/donate and lack of space to store milk were also key barriers.

Pasteurised donor human milk is a vital resource for vulnerable preterm infants. As demand continues to grow, the sustainability of milk banking services relies not only on recruiting donors but also on fostering positive donor experiences. Satisfied donors are more likely to contribute consistently and advocate for the service, enhancing its visibility and community support. A total of 588 formal milk bank donors who donated to Australian Red Cross Lifeblood milk programme between January 2024 and April 2025 were invited to participate in a survey. The survey aimed to explore factors that make milk donors feel valued, evaluate their satisfaction with different aspects of the donation process, and identify barriers that may hinder continued donation. The survey included Likert‐scale questions and optional open‐text responses. The survey was completed by 257 donors (43.7% response rate). Most (72.4%) felt highly valued by Lifeblood, especially due to receiving milk bags, and having supportive, personal interactions with donor coordinators. However, some donors felt undervalued due to a lack of post‐donation communication. Whilst satisfaction with the donation process was high, some respondents found the screening process repetitive and time‐consuming. The most reported barrier was limited freezer space (67.7%), followed by time constraints, illness in the household, and the burden of cleaning and sterilising equipment for milk expression at home. Milk banks should adopt donor‐centred practices, including streamlining processes to minimise time and effort required for donors, reduce costs incurred by donors where feasible, and enhance post‐donation transparency and engagement. Summary Supportive and respectful interactions with milk bank staff foster donor engagement by making donors feel valued and appreciated. Timely communication and recognition, such as updates and acknowledgements, enhance donor satisfaction and strengthen their connection to the milk bank. Reducing practical and financial barriers for milk donors, including simplifying screening, offering home collection, and providing milk storage supplies, makes donation more accessible and sustainable.