Parallel triplet formation pathways in a singlet fission material

Harvesting long-lived free triplets in high yields by utilizing organic singlet fission materials can be the cornerstone for increasing photovoltaic efficiencies potentially. However, except for polyacenes, which are the most studied systems in the singlet fission field, spin-entangled correlated triplet pairs and free triplets born through singlet fission are relatively poorly characterized. By utilizing transient absorption and photoluminescence spectroscopy in supramolecular aggregate thin films consisting of Hamilton-receptor-substituted diketopyrrolopyrrole derivatives, we show that photoexcitation gives rise to the formation of spin-0 correlated triplet pair 1(TT) from the lower Frenkel exciton state. The existence of 1(TT) is proved through faint Herzberg-Teller emission that is enabled by vibronic coupling and correlated with an artifact-free triplet-state photoinduced absorption in the near-infrared. Surprisingly, transient electron paramagnetic resonance reveals that long-lived triplets are produced through classical intersystem crossing instead of 1(TT) dissociation, with the two pathways in competition. Moreover, comparison of the triplet-formation dynamics in J-like and H-like thin films with the same energetics reveals that spin-orbit coupling mediated intersystem crossing persists in both. However, 1(TT) only forms in the J-like film, pinpointing the huge impact of intermolecular coupling geometry on singlet fission dynamics

The association of a novel digital tool for assessment of early childhood cognitive development, 'DEvelopmental assessment on an E-Platform (DEEP)', with growth in rural India: A proof of concept study.

BACKGROUND: There is an urgent need to fill the gap of scalable cognitive assessment tools for preschool children to enable identification of children at-risk of sub-optimal development and to support their timely referral into interventions. We present the associations between growth in early childhood, a well-established marker of cognitive development, and scores on a novel digital cognitive assessment tool called DEvelopmental Assessment on an E-Platform (DEEP) on a sample of 3-year old pre-schoolers from a rural region in north India. METHODS: Between February 2018 and March 2019, 1359 children from the Sustainable Programme Incorporating Nutrition and Games (SPRING) programme were followed up at 3-years age and data on DEEP, anthropometry and a clinical developmental assessment, the Bayley's Scale of Infant and Toddler Development, 3rd edition (BSID-III) was collected. DEEP data from 200 children was used to train a machine learning algorithm to predict their score on the cognitive domain of BSID-III. The DEEP score of the remaining 1159 children was then predicted using this algorithm to examine the cross-sectional and prospective association of growth with the DEEP score. FINDINGS: The magnitude of the concurrent positive association between height-for-age and cognitive z-scores in 3-year olds was similar when cognition was measured by BSID-III (0.20 standard deviations increase for every unit change in specifically age-adjusted height (HAZ), 95% CI = 0.06-0.35) and DEEP (0.26 CI, 0.11-0.41). A similar positive prospective relationship was found between growth at 18 (0.21 CI, 0.17-0.26) and 12-months (0.18 CI, 0.13-0.23) and DEEP score measured at 3-years. Additionally, the relationship between growth and cognitive development was found to be dependant on socioeconomic status (SES). INTERPRETATION: In this study, we suggest the utility of DEEP, a scalable, digital cognitive assessment tool, to measure cognition in preschool children. Further validation in different and larger datasets is necessary to confirm our findings. FUNDING: The SPRING Programme was funded through a Wellcome Trust programme grant and the follow-up study by the Corporate Social Responsibility initiative grant from Madura Microfinance Ltd

Using mobile health technology to assess childhood autism in low-resource community settings in India: an innovation to address the detection gap

A diagnosis of autism typically depends on clinical assessments by highly-trained professionals. This high resource demand poses a challenge in low-resource settings. Digital assessment of neurodevelopmental symptoms by non-specialists provides a potential avenue to address this challenge. In this study, we provide the proof of principle for such a digital assessment, with a cross-sectional case control field study using mixed methods. We developed and tested an app, START, that can assess autism phenotypic domains (social, sensory, motor) through child performance and parent reports. N=131 children (2-7 years old; 48 autistic, 43 intellectually disabled, and 40 non-autistic typically developing) from low-resource settings in India were assessed using START in home settings by non-specialist health workers. The two groups of children with neurodevelopmental disorders manifested lower social preference, higher sensory sensitivity, and lower fine-motor accuracy compared to their typically developing counterparts. Machine-learning analysis combining all START-derived measures demonstrated 78% classification accuracy for the three groups. Qualitative analysis of the interviews with health workers and families of the participants demonstrated high acceptability and feasibility of the app. These results provide feasibility, acceptability, and proof of principle for START, and demonstrate the potential of a scalable, mobile tool for assessing neurodevelopmental conditions in low-resource settings

Lipid metabolic perturbation is an early-onset phenotype in adult spinster mutants: a Drosophila model for lysosomal storage disorders

Intracellular accumulation of lipids and swollen dysfunctional lysosomes are linked to several neurodegenerative diseases, including lysosomal storage disorders (LSD). Detailed characterization of lipid metabolic changes in relation to the onset and progression of neurodegeneration is currently missing. We systematically analyzed lipid perturbations in spinster (spin) mutants, a Drosophila model of LSD-like neurodegeneration. Our results highlight an imbalance in brain ceramide and sphingosine in the early stages of neurodegeneration, preceding the accumulation of endomembranous structures, manifestation of altered behavior, and buildup of lipofuscin. Manipulating levels of ceramidase and altering these lipids in spin mutants allowed us to conclude that ceramide homeostasis is the driving force in disease progression and is integral to spin function in the adult nervous system. We identified 29 novel physical interaction partners of Spin and focused on the lipid carrier protein, Lipophorin (Lpp). A subset of Lpp and Spin colocalize in the brain and within organs specialized for lipid metabolism (fat bodies and oenocytes). Reduced Lpp protein was observed in spin mutant tissues. Finally, increased levels of lipid metabolites produced by oenocytes in spin mutants allude to a functional interaction between Spin and Lpp, underscoring the systemic nature of lipid perturbation in LSD

The neuroscience of respect: insights from cross-cultural perspectives.

Cultural values such as respect influence cognition, emotion, and behavior by modulating brain functioning. This mini-review discusses the cultural differences of respect as an essential human value, and the neural underpinnings accompanying them. Although neuroscientific studies are limited, we outline potential brain structures and networks that contribute to respect and use clinical examples to illustrate how behavior changes when these neural systems fail. A better understanding of the neuroanatomical basis of respect and its neural manifestations across cultures will help to advance current conceptualizations of the biology of human values

Development, feasibility and acceptability of a gamified cognitive DEvelopmental assessment on an E-Platform (DEEP) in rural Indian pre-schoolers – a pilot study

Background: Assessment of cognitive development is essential to identify children with faltering developmental attainment and monitor the impact of interventions. A key barrier to achieving these goals is the lack of standardized, scalable tools to assess cognitive abilities. Objective: This study aimed to develop a tablet-based gamified assessment of cognitive abilities of 3-year-old children which can be administered by non-specialist field workers. Methods: Workshops among domain experts, literature search for established and gamified paradigms of cognitive assessments and rapid review of mobile games for 3-year-old children was done to conceptualize games for this study. Formative household visits (N = 20) informed the design and content of the games. A cross-sectional pilot study (N = 100) was done to assess feasibility of the tool and check if increasing levels of difficulty and the expected variability between children were evident in game metrics. In-depth interviews (N = 9) were conducted with mothers of participating children to assess its acceptability. Results: Six cognitive domains were identified as being integral to learning – divided attention, response inhibition, reasoning, visual form perception and integration and memory. A narrative, musical soundtrack and positive reinforcement were incorporated into the tool to enhance participant engagement. Child performance determined level timers and difficulty levels in each game. Pilot data indicate that children differ in their performance profile on the tool as measured by the number of game levels played and their accuracy and completion time indicating that it might be possible to differentiate children based on these metrics. Qualitative data suggest high levels of acceptability of the tool amongst participants. Conclusions: A DEvelopmental assessment on an E-Platform (DEEP) has been created comprising distinct games woven into a narrative, which assess six cognitive domains, and shows high levels of acceptability and generates metrics which may be used for validation against gold standard cognitive assessments

Digital tools for direct assessment of autism risk during early childhood: a systematic review

Current challenges in early identification of autism spectrum disorder lead to significant delays in starting interventions, thereby compromising outcomes. Digital tools can potentially address this barrier as they are accessible, can measure autism-relevant phenotypes and can be administered in children’s natural environments by non-specialists. The purpose of this systematic review is to identify and characterise potentially scalable digital tools for direct assessment of autism spectrum disorder risk in early childhood. In total, 51,953 titles, 6884 abstracts and 567 full-text articles from four databases were screened using predefined criteria. Of these, 38 met inclusion criteria. Tasks are presented on both portable and non-portable technologies, typically by researchers in laboratory or clinic settings. Gamified tasks, virtual-reality platforms and automated analysis of video or audio recordings of children’s behaviours and speech are used to assess autism spectrum disorder risk. Tasks tapping social communication/interaction and motor domains most reliably discriminate between autism spectrum disorder and typically developing groups. Digital tools employing objective data collection and analysis methods hold immense potential for early identification of autism spectrum disorder risk. Next steps should be to further validate these tools, evaluate their generalisability outside laboratory or clinic settings, and standardise derived measures across tasks. Furthermore, stakeholders from underserved communities should be involved in the research and development process

Annual Research Review: Achieving universal health coverage for young children with autism spectrum disorder in low- and middle-income countries: a review of reviews

Background Autism presents with similar prevalence and core impairments in diverse populations. We conducted a scoping review of reviews to determine key barriers and innovative strategies which can contribute to attaining universal health coverage (UHC), from early detection to effective interventions for autism in low- and middle-income countries (LAMIC). Methods A systematic literature search of review articles was conducted. Reviews relevant to the study research question were included if they incorporated papers from LAMIC and focused on children (under eight years old) with autism or their caregivers. The database search was supplemented with bibliographic search of included articles and key informant suggestions. Data were extracted and mapped onto a Theory of Change model toward achieving UHC for autism in LAMIC. Results We identified 31 articles which reviewed data from over fifty countries across Africa, Latin America, Middle East, and Asia and addressed barriers across one or more of four inter-related domains: (a) the social context and family experience for a child with autism; (b) barriers to detection and diagnosis; (c) access to appropriate evidence-based intervention; and (d) social policy and legislation. Key barriers identified included: lack of appropriate tools for detection and diagnosis; low awareness and experienced stigma impacting demand for autism care; and the prevalence of specialist models for diagnosis and treatment which are not scalable in LAMIC. Conclusions We present a Theory of Change model which describe the strategies and resources needed to realize UHC for children with autism in LAMIC. We highlight the importance of harnessing existing evidence to best effect, using task sharing and adapted intervention strategies, community participation, and technology innovation. Scaling up these innovations will require open access to appropriate detection and intervention tools, systematic approaches to building and sustaining skills in frontline providers to support detection and deliver interventions embedded within a stepped care architecture, and community awareness of child development milestones