Development of food photographs for use with children aged 18 months to 16 years:comparison against weighed food diaries – The Young Person’s Food Atlas (UK)

Traditional dietary assessment methods, used in the UK, such as weighed food diaries impose a large participant burden, often resulting in difficulty recruiting representative samples and underreporting of energy intakes. One approach to reducing the burden placed on the participant is to use portion size assessment tools to obtain an estimate of the amount of food consumed, removing the need to weigh all foods. An age range specific food atlas was developed for use in assessing children’s dietary intakes. The foods selected and portion sizes depicted were derived from intakes recorded during the UK National Diet and Nutrition Surveys of children aged 1.5 to 16 years. Estimates of food portion sizes using the food atlas were compared against 4-day weighed intakes along with in-school / nursery observations, by the research team. Interviews were conducted with parents the day after completion of the diary, and for children aged 4 to 16 years, also with the child. Mean estimates of portion size consumed were within 7% of the weight of food recorded in the weighed food diary. The limits of agreement were wide indicating high variability of estimates at the individual level but the precision increased with increasing age. For children 11 years and over, agreement with weighed food diaries, was as good as that of their parents in terms of total weight of food consumed and of intake of energy and key nutrients. The age appropriate food photographs offer an alternative to weighed intakes for dietary assessment with children

Are working memory and glutamate concentrations involved in early-life stress and severity of psychosis?

Objective Occurrences of early‐life stress (ELS) are associated with the severity of psychotic symptoms and working memory (WM) deficits in patients with psychosis (PSY). This study investigated potential mediation roles of WM behavioral performance and glutamate concentrations in prefrontal brain regions on the association between ELS and psychotic symptom severity in PSY. Method Forty‐seven patients with PSY (established schizophrenia, n = 30; bipolar disorder, n = 17) completed measures of psychotic symptom severity. In addition, data on ELS and WM performance were collected in both patients with PSY and healthy controls (HC; n = 41). Resting‐state glutamate concentrations in the bilateral dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC) were also assessed with proton magnetic resonance spectroscopy for both PSY and HC groups. t tests, analyses of variance, and regression analyses were utilized. Results Participants with PSY reported significantly more ELS occurrences and showed poorer WM performance than HC. Furthermore, individuals with PSY displayed lower glutamate concentrations in the left DLPFC than HC. Neither ELS nor WM performance were predictive of severity of psychotic symptoms in participants with PSY. However, we found a significant negative correlation between glutamate concentrations in the left DLPFC and ELS occurrence in HC only. Conclusion In individuals with PSY, the current study found no evidence that the association between ELS and psychotic symptoms is mediated by WM performance or prefrontal glutamate concentrations. In HC, the association between ELS experience and glutamate concentrations may indicate a neurometabolite effect of ELS that is independent of an illness effect in psychosis

Rancang Bangun Mobile Robot Pengikut Manusia Berdasarkan Warna Menggunakan Metode Template Matching Berbasis Mini Pc

Penerapan teknologi di bidang robotika telah banyak dimanfaatkan oleh kalangan industri di dunia kerja dalam rangka meningkatkan efisiensi dan efektivitas berbagai aktivitas kerja manusia. Sebuah mobile robot dibuat agar dapat mengikuti pergerakan objek berupa manusia berdasarkan warna menggunakan webcam. Mobile robot yang dibuat dapat melakukan proses pengolahan citra dari warna objek yang ditangkap oleh webcam, sehingga dapat mengenali warna objek yang diikuti. Proses pengolahan citra akan di proses di dalam Raspberry Pi sebagai pusat kontrol, yang akan menggerakkan motor pada mobile robot. Ada beberapa proses pengolahan citra untuk mengikuti pergerakan objek, yaitu: mencari nilai HSV masing-masing warna pada kondisi pencahayaan yang berbeda, menganalisa warna objek yang akan diikuti dengan membandingkan nilai HSV yang didapat dengan nilai HSV pada proses sebelumnya, dan mendeteksi warna lingkaran pada objek yang tujuan dengan menggunakan metode template matching. Mobile robot akan mengikuti pergerakan objek yang telah ditangkap oleh webcam, Dari penelitian yang dilakukan, didapatkan nilai HSV yang tepat untuk semua keadaan pencahayaan untuk masing-masing warna yaitu: nilai H (Hue) untuk warna, merah: 0-66, nilai S (Saturation): 64-169, dan nilai V (Value): 75-124. Dari 11 kali pengujian sistem yang dilakukan pada semua kondisi pencahayaan, diperoleh 5 kali kegagalan dengan persentase kegagalan sebesar 45.4 % dan 6 kali keberhasilan dengan persentase keberhasilan sebesar 54.6 %

Automated Classification of Depression from Structural Brain Measures across Two Independent Community-based Cohorts

ACKNOWLEDGEMENTS: This study was supported and funded by the Wellcome Trust Strategic Award ‘Stratifying Resilience and Depression Longitudinally’ (STRADL) (Reference 104036/Z/14/Z), and the Medical Research Council Mental Health Pathfinder Award ‘Leveraging routinely collected and linked research data to study the causes and consequences of common mental disorders’ (Reference MRC-MC_PC_17209). MAH is supported by research funding from the Dr Mortimer and Theresa Sackler Foundation. The research was conducted using the UK Biobank resource, with application number 4844. Structural brain imaging data from the UK Biobank was processed at the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE) http://www.ccace.ed.ac.uk/), which is a part of the crosscouncil Lifelong Health and Wellbeing Initiative (MR/K026992/1). CCACE received funding from Biotechnology and Biological Sciences Research Council (BBSRC), Medical Research Council (MRC), and was also supported by Age UK as part of The Disconnected Mind project. This work has made use of the resources provided by the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk/)Peer reviewedPublisher PD

Local CpG density affects the trajectory and variance of age-associated DNA methylation changes

Acknowledgements We thank Riccardo Marioni, Chris Haley, Ailith Ewing, David Porteous, Chris Ponting, Rob Illingworth, Tamir Chandra, Sara Hagg, Yunzhang Wang, Chantriolnt-Andreas Kapourani, Nick Gilbert, Hannes Becher and members of the Sproul lab for helpful discussions about the study and the manuscript. This work has made use of the resources provided by the University of Edinburgh digital research services and the MRC IGC compute cluster. We are grateful to all the families who took part in the Generation Scotland study along with the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the entire Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, healthcare assistants, and nurses. Peer review information Anahita Bishop and Kevin Pang were the primary editors of this article and managed its editorial process and peer review in collaboration with the rest of the editorial team. Review history The review history is available as Additional file 3. Funding DS is a Cancer Research UK Career Development fellow (reference C47648/A20837), and work in his laboratory is also supported by an MRC university grant to the MRC Human Genetics Unit. LK is a cross-disciplinary postdoctoral fellow supported by funding from the University of Edinburgh and Medical Research Council (MC_UU_00009/2). S.R.C. and I.J.D. were supported by a National Institutes of Health (NIH) research grant R01AG054628, and S.R.C is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (221890/Z/20/Z). AMM is supported by the Wellcome Trust (104036/Z/14/Z, 216767/Z/19/Z, 220857/Z/20/Z) and UKRI MRC (MC_PC_17209, MR/S035818/1). PMV acknowledges support from the Australian National Health and Medical Research Council (1113400) and the Australian Research Council (FL180100072). DMH is supported by a Sir Henry Wellcome Postdoctoral Fellowship (Reference 213674/Z/18/Z). We thank the LBC1936 participants and team members who contributed to the study. Further study information can be found at https://www.ed.ac.uk/lothian-birth-cohorts. The LBC1936 is supported by a jointly funded grant from the BBSRC and ESRC (BB/W008793/1), and also by Age UK (Disconnected Mind project), the Medical Research Council (G0701120, G1001245, MR/M013111/1, MR/R024065/1), and the University of Edinburgh. Genotyping of LBC1936 was funded by the BBSRC (BB/F019394/1), and methylation typing of LBC1936 was supported by Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, The Wellcome Trust Institutional Strategic Support Fund, The University of Edinburgh, and The University of Queensland. Work on Generation Scotland was supported by a Wellcome Strategic Award “STratifying Resilience and Depression Longitudinally” (STRADL; 104036/Z/14/Z) to AMM, KLE, and others, and an MRC Mental Health Data Pathfinder Grant (MC_PC_17209) to AMM. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates (CZD/16/6) and the Scottish Funding Council (HR03006). DNA methylation profiling and analysis of the GS:SFHS samples was supported by Wellcome Investigator Award 220857/Z/20/Z and Grant 104036/Z/14/Z (PI: AM McIntosh) and through funding from NARSAD (Ref: 27404; awardee: Dr DM Howard) and the Royal College of Physicians of Edinburgh (Sim Fellowship; Awardee: Dr HC Whalley).Peer reviewedPublisher PD

Associations of negative affective biases and depressive symptoms in a community-based sample

Acknowledgements. We thank professor Jonathan Roiser (University College London, UK) and professor emeritus Ian Deary (University of Edinburgh, UK) for their input on task selection and statistical analysis. We also acknowledge all researchers who have contributed to the collection of data for the current study. Most importantly, we would like to thank all participants of Generation Scotland, and particularly those of the STRADL subcohort, for their participation in the research. Financial support. Stratifying Resilience and Depression Longitudinally is supported by the Wellcome Trust through a Strategic Award (Grant No. 104036/Z/14/Z) and through an Investigator Award (Grant No. 220857/Z/ 20/Z). The Chief Scientist Office of the Scottish Government Health Department (Grant No. CZD/16/6), Scottish Funding Council (Grant No. HR03006) and Wellcome Trust (Grant No. 216767/Z/19/Z) provided core support for Generation Scotland.Peer reviewedPublisher PD

Associations of negative affective biases and depressive symptoms in a community-based sample

Background: Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls. Methods: Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. Conclusions: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals

Hair glucocorticoids are associated with childhood adversity, depressive symptoms and reduced global and lobar grey matter in Generation Scotland

ACKNOWLEDGEMENTS We would like to thank all of the Generation Scotland participants for their contribution to this study. We also thank the research assistants, clinicians and technicians for their help in collecting the data. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust [216767/Z/19/Z]. This study was also supported and funded by the Wellcome Trust Strategic Award ‘Stratifying Resilience and Depression Longitudinally’ (STRADL) (Reference 104036/Z/14/Z). We acknowledge the support of the British Heart Foundation (RE/18/5/34216). CG is supported by the Medical Research Council and the University of Edinburgh through the Precision Medicine Doctoral Training Programme. MCB is supported by a Guarantors of Brain Non-Clinical Post-Doctoral Fellowship. JMW is funded by the UK Dementia Research Institute which is funded by the UK Medical Research Council, Alzheimer’s Research UK and Alzheimer’s SocietyPeer reviewedPublisher PD

Blunted Medial Prefrontal Cortico-Limbic Reward-Related Effective Connectivity and Depression

Stratifying Resilience and Depression Longitudinally (STRADL) was supported by the Wellcome Trust through a Strategic Award (Grant No. 104036/Z/14/Z). Parts of the work were supported by a China Scholarship Council (Grant No. 201506040037 to SX), National Institutes of Health (Grant No. DA027764 to MRD), Lister Institute Prize Fellowship 2016–2021 (to DJS), Dr Mortimer and Theresa Sackler Foundation (AMM, HCW, and SML), Centre for Cognitive Ageing and Cognitive Epidemiology (IJD and AMM), Medical Research Council and Biotechnology and Biological Sciences Research Council (Grant No. MR/K026992/1), Royal College of Physicians of Edinburgh John, Margaret, Alfred and Stewart Sim fellowship (to HCW), and University of Edinburgh, Edinburgh Scientific Academic TmPCk College Fellowship (to HCW). The Chief Scientist Office of the Scottish Government Health Department (Grant No. CZD/16/6) and Scottish Funding Council (Grant No. HR03006) provided core support for Generation Scotland. Data acquisition was additionally supported by the Scottish Mental Health Research Network and Scottish Government’s Support for Science initiative. LR, HCW, and AMM, received financial support from Pfizer (formerly Wyeth) in relation to imaging studies of people with schizophrenia and bipolar disorder. AMM has previously received grant support from Lilly and Janssen. SML has received honoraria for lectures, chairing meetings, and consultancy work from Janssen in connection with brain imaging and therapeutic initiatives for psychosis. JDS has received funding via an honorarium associated with a lecture or Wyeth and funding from Indivior for a study on opioid dependency. No other disclosures were reported. The authors declare no conflict of interest.Peer reviewedPublisher PD