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Objectives: To assess whether consumption of lean red meat on three exercise training days per week can promote greater improvements than exercise alone in health-related quality of life (HR-QoL) in community-dwelling older adults. Design: This study is a secondary analysis from a 6 month, two-arm, parallel randomized controlled trial conducted in 2014 and 2015. Setting: Community-dwelling older adults living in metropolitan Melbourne, Australia. Participants: One hundred and fifty-four men and women aged ≥65 years. Intervention: All participants were enrolled in a multi-component, resistance-based exercise program (3 d/week) and randomly allocated to either a group asked to consume lean red meat (2x80g cooked servings/day) on each of the three training days (Ex+Meat, n=77) or a control group asked to consume one serving of carbohydrates (1/2 cup rice/pasta or 1 medium potato; Ex+C, n=77). Measurements: HR-QoL was assessed using the Short-Form (SF)-36 health survey. Results: Overall 62% of the participants were female, the mean age was 70.7 years (range 65 to 84 years), approximately 67% of participants were classified as either overweight or obese, and the average number of chronic conditions was two. A total of 145 participants (94%) completed the study. Mean baseline HR-QoL scores were comparable to the mean for the Australian population [Global HR-QoL (mean ± SD): Ex+Meat, 49.99 ± 6.57; Ex+C, 50.49 ± 5.27]. General Linear Mixed Models examining within and between group changes over time revealed that after 6 months, there were no within-group changes in either Ex+Meat or Ex+C nor any between-group differences for any measure of HR-QoL, with the exception that the mental health subscale improved in Ex+C versus Ex+Meat [net difference for change, −2.32 (95% CI), −4.73, 0.09, P=0.048] after adjusting for relevant covariates and the physical function subscale improved in Ex+Meat relative to baseline [mean change (95% CI), 1.88 (0.37, 3.39), P=0.011]. Conclusion: A multi-component resistance-based training program performed with and without the provision of lean red meat in line with current Australian dietary guidelines on each of the three training days, did not improve HR-QoL in healthy community-dwelling older adults. [ABSTRACT FROM AUTHOR]

Psychotic symptoms are typically measured using clinical ratings, but more objective and sensitive metrics are needed. Hence, we will assess thought disorder using the Research Domain Criteria (RDoC) heuristic for language production, and its recommended paradigm of "linguistic corpus-based analyses of language output". Positive thought disorder (e.g., tangentiality and derailment) can be assessed using word-embedding approaches that assess semantic coherence, whereas negative thought disorder (e.g., concreteness, poverty of speech) can be assessed using part-of-speech (POS) tagging to assess syntactic complexity. We aim to establish convergent validity of automated linguistic metrics with clinical ratings, assess normative demographic variance, determine cognitive and functional correlates, and replicate their predictive power for psychosis transition among at-risk youths. This study will assess language production in 450 English-speaking individuals in Australia and Canada, who have recent onset psychosis, are at clinical high risk (CHR) for psychosis, or who are healthy volunteers, all well-characterized for cognition, function and symptoms. Speech will be elicited using open-ended interviews. Audio files will be transcribed and preprocessed for automated natural language processing (NLP) analyses of coherence and complexity. Data analyses include canonical correlation, multivariate linear regression with regularization, and machine-learning classification of group status and psychosis outcome. This prospective study aims to characterize language disturbance across stages of psychosis using computational approaches, including psychometric properties, normative variance and clinical correlates, important for biomarker development. SPEAK will create a large archive of language data available to other investigators, a rich resource for the field. [ABSTRACT FROM AUTHOR]

Background and Hypotheses: Sleep disturbances are increasingly recognized as cooccurring with psychotic symptoms. The potential importance of this relationship is complicated when considering the effects of anxiety and depressive symptoms which commonly present in early-stage illness states. This study aimed to investigate the relationship between self-reported sleep disturbance on the development of attenuated psychotic symptoms (APS) cross-sectionally and longitudinally while adjusting for roles of anxiety and depressive symptoms., Design: Eight-hundred and two help-seeking young people aged 12 to 25 years who engaged with our Australian early intervention services were included in the study (the "Transitions" cohort). Cross sectional mediation and cross-lagged longitudinal (12-month) mediation models were developed with outcomes being different APS domains., Results: Only baseline excessive daytime sleepiness predicted later APS when accounting for previous APS, anxiety and depressive symptomatology. Cross sectionally, self-reported sleep disturbance showed both direct and indirect predictive relationships with all APS domains. Partial mediation through anxiety and depression was shown for unusual thought content, perceptual abnormalities, and disorganised speech, while full mediation through depression was shown for non-bizarre ideas., Conclusions: The specificity of the relationship between self-reported sleep disturbance on APS highlights the potential for different roles in mechanistic models of psychotic symptom expression. This further indicates the need for further experimental research to illuminate potential causal pathways. Future research should continue to use continuous, symptom level approaches across a range of timeframes to more accurately model the complex dynamics present in the sleep-psychosis relationship., Competing Interests: Declaration of competing interest The authors declare that they have no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)