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Metal dyshomeostasis is associated with neurodegenerative disorders, cancers and vascular disease. We report the effects of age (range: 3 to 18 months) on regional copper, iron and zinc levels in the brain of the C57BL/6 mouse, a widely used inbred strain with a permissive background allowing maximal expression of mutations in models that recapitulate these disorders. We present formulae that can be used to determine regional brain metal concentrations in the C57BL/6 mouse at any age in the range of three to eighteen months of life. Copper levels in the C57BL/6 mouse adult brain were highest in the striatum and cerebellum and increased with age, excepting the cortex and hippocampus. Regional iron levels increased linearly with age in all brain regions, while regional zinc concentrations became more homogeneous with age. Knockdown of the copper transporter Ctr1 reduced brain copper, but not iron or zinc, concentrations in a regionally-dependent manner. These findings demonstrate biometals in the brain change with age in a regionally-dependent manner. These data and associated formulae have implications for improving design and interpretation of a wide variety of studies in the C57BL/6 mouse., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Type 2 diabetes is 2 to 3 times more common among people with severe mental illness (SMI). Self-management is crucial, with additional challenges faced by people with SMI. Therefore, it is essential that any diabetes self-management program for people with SMI addresses the unique needs of people living with both conditions and the inequalities they experience within health care services., Objective: We combined theory, empirical evidence, and co-design approaches to develop a type 2 diabetes self-management intervention for people with SMI., Methods: The development process encompassed 4 steps: step 1 involved prioritizing the mechanisms of action (MoAs) and behavior change techniques (BCTs) for the intervention. Using findings from primary qualitative research and systematic reviews, we selected candidate MoAs to target in the intervention and candidate BCTs to use. Expert stakeholders then ranked these MoAs and BCTs using a 2-phase survey. The average scores were used to generate a prioritized list of MoAs and BCTs. During step 2, we presented the survey results to an expert consensus workshop to seek expert agreement with the definitive list of MoAs and BCTs for the intervention and identify potential modes of delivery. Step 3 involved the development of trigger films using the evidence from steps 1 and 2. We used animations to present the experiences of people with SMI managing diabetes. These films were used in step 4, where we used a stakeholder co-design approach. This involved a series of structured workshops, where the co-design activities were informed by theory and evidence., Results: Upon the completion of the 4-step process, we developed the DIAMONDS (diabetes and mental illness, improving outcomes and self-management) intervention. It is a tailored self-management intervention based on the synthesis of the outputs from the co-design process. The intervention incorporates a digital app, a paper-based workbook, and one-to-one coaching designed to meet the needs of people with SMI and coexisting type 2 diabetes., Conclusions: The intervention development work was underpinned by the MoA theoretical framework and incorporated systematic reviews, primary qualitative research, expert stakeholder surveys, and evidence generated during co-design workshops. The intervention will now be tested for feasibility before undergoing a definitive evaluation in a pragmatic randomized controlled trial., (©Claire Carswell, Peter A Coventry, Jennifer V E Brown, Sarah L Alderson, Keith Double, Simon Gilbody, Richard I G Holt, Rowena Jacobs, Jennie Lister, David Osborn, David Shiers, Najma Siddiqi, Johanna Taylor, Ian Kellar, DIAMONDS Research Group. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.05.2023.)

Objectives: The Computer-Aided Risk Score for Mortality (CARM) estimates the risk of in-hospital mortality following acute admission to the hospital by automatically amalgamating physiological measures, blood tests, gender, age and COVID-19 status. Our aims were to implement the score with a small group of practitioners and understand their first-hand experience of interacting with the score in situ., Design: Pilot implementation evaluation study involving qualitative interviews., Setting: This study was conducted in one of the two National Health Service hospital trusts in the North of England in which the score was developed., Participants: Medical, older person and ICU/anaesthetic consultants and specialist grade registrars (n=116) and critical outreach nurses (n=7) were given access to CARM. Nine interviews were conducted in total, with eight doctors and one critical care outreach nurse., Interventions: Participants were given access to the CARM score, visible after login to the patients' electronic record, along with information about the development and intended use of the score., Results: Four themes and 14 subthemes emerged from reflexive thematic analysis: (1) current use (including support or challenge clinical judgement and decision making, communicating risk of mortality and professional curiosity); (2) barriers and facilitators to use (including litigation, resource needs, perception of the evidence base, strengths and limitations), (3) implementation support needs (including roll-out and integration, access, training and education); and (4) recommendations for development (including presentation and functionality and potential additional data). Barriers and facilitators to use, and recommendations for development featured highly across most interviews., Conclusion: Our in situ evaluation of the pilot implementation of CARM demonstrated its scope in supporting clinical decision making and communicating risk of mortality between clinical colleagues and with service users. It suggested to us barriers to implementation of the score. Our findings may support those seeking to develop, implement or improve the adoption of risk scores., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Modern work environments have extensive interactions with technology and greater cognitive complexity of the tasks, which results in human operators experiencing increased mental workload. Air traffic control operators routinely work in such complex environments, and we designed tracking and collision prediction tasks to emulate their elementary tasks. The physiological response to the workload variations in these tasks was elucidated to untangle the impact of workload variations experienced by operators. Electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty. Our findings indicate that variations in task load in both these tasks are sensitively reflected in EEG, eye activity and HRV data. Multiple regression results also show that operators' performance in both tasks can be predicted using the corresponding EEG, eye activity and HRV data. The results also demonstrate that the brain dynamics during each of these tasks can be estimated from the corresponding eye activity, HRV and performance data. Furthermore, the markedly distinct neurometrics of workload variations in the tracking and collision prediction tasks indicate that neurometrics can provide insights on the type of mental workload. These findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just "when" but also "what" to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in complex work environments.

Dyslexia is characterized by difficulties in learning to read and there is some evidence that action video games (AVG), without any direct phonological or orthographic stimulation, improve reading efficiency in Italian children with dyslexia. However, the cognitive mechanism underlying this improvement and the extent to which the benefits of AVG training would generalize to deep English orthography, remain two critical questions. During reading acquisition, children have to integrate written letters with speech sounds, rapidly shifting their attention from visual to auditory modality. In our study, we tested reading skills and phonological working memory, visuo-spatial attention, auditory, visual and audio-visual stimuli localization, and cross-sensory attentional shifting in two matched groups of English-speaking children with dyslexia before and after they played AVG or non-action video games. The speed of words recognition and phonological decoding increased after playing AVG, but not non-action video games. Furthermore, focused visuo-spatial attention and visual-to-auditory attentional shifting also improved only after AVG training. This unconventional reading remediation program also increased phonological short-term memory and phoneme blending skills. Our report shows that an enhancement of visuo-spatial attention and phonological working memory, and an acceleration of visual-to-auditory attentional shifting can directly translate into better reading in English-speaking children with dyslexia.