A machine-learning tool to predict substrate-adaptive conditions for Pd-catalyzed C-N couplings.

Machine-learning methods have great potential to accelerate the identification of reaction conditions for chemical transformations. A tool that gives substrate-adaptive conditions for palladium (Pd)-catalyzed carbon-nitrogen (C-N) couplings is presented. The design and construction of this tool required the generation of an experimental dataset that explores a diverse network of reactant pairings across a set of reaction conditions. A large scope of C-N couplings was actively learned by neural network models by using a systematic process to design experiments. The models showed good performance in experimental validation: Ten products were isolated in more than 85% yield from a range of couplings with out-of-sample reactants designed to challenge the models. Importantly, the developed workflow continually improves the prediction capability of the tool as the corpus of data grows.

How Do Physical Activity and Sedentary Behaviour Affect Motor Competence in Children with Autism Spectrum Disorder Compared to Typically Developing Children: A Pilot Study.

Older children with Autism Spectrum Disorder (ASD) have high levels of motor impairment, however we are unsure if similar patterns exist in young children. This study aimed to investigate motor competence in four-to-seven-year-old children with (n = 17) and without (n = 17) ASD. A series of ANOVAS indicated children with ASD performed significantly poorer on all measures of motor competence, except MABC-2 manual dexterity and ball skills subscales. Results indicate that moderate-to-vigorous physical activity (PA) and sedentary behaviour (SB) may influence motor competence, regardless of diagnosis. Establishing appropriate levels of engagement in moderate-to-vigorous PA and SB during early school years is important for the development of all children and may be an important early intervention avenue for motor impairment in children with ASD.

Leveraging Machine Learning for Enantioselective Catalysis: From Dream to Reality.

Catalyst optimization for enantioselective transformations has traditionally relied on empirical evaluation of catalyst properties. Although this approach has been successful in the past it is intrinsically limited and inefficient. To address this problem, our laboratory has developed a fully informatics guided workflow to leverage the power of artificial intelligence (AI) and machine learning (ML) to accelerate the discovery and optimization of any class of catalyst for any transformation. This approach is mechanistically agnostic, but also serves as a discovery platform to identify high performing catalysts that can be subsequently investigated with physical organic methods to identify the origins of selectivity.

Dreams, False Starts, Dead Ends, and Redemption: A Chronicle of the Evolution of a Chemoinformatic Workflow for the Optimization of Enantioselective Catalysts.

Catalyst design in enantioselective catalysis has historically been driven by empiricism. In this endeavor, experimentalists attempt to qualitatively identify trends in structure that lead to a desired catalyst function. In this body of work, we lay the groundwork for an improved, alternative workflow that uses quantitative methods to inform decision making at every step of the process. At the outset, we define a library of synthetically accessible permutations of a catalyst scaffold with the philosophy that the library contains every potential catalyst we are willing to make. To represent these chiral molecules, we have developed general 3D representations, which can be calculated for tens of thousands of structures. This defines the total chemical space of a given catalyst scaffold; it is constructed on the basis of catalyst structure only without regard to a specific reaction or mechanism. As such, any algorithmic subset selection method, which is unsupervised (i.e., only considers catalyst structure), should provide an ideal initial screening set for any new reaction that can be catalyzed by that scaffold. Notably, because this design strategy, the same set of catalysts can be used for any reaction that can be catalyzed with that parent catalyst scaffold. These are tested experimentally, and statistical learning tools can be used to create a model relating catalyst structure to catalyst function. Further, this model can be used to predict the performance of each catalyst candidate in the greater database of virtual catalyst candidates. In this way, it is possible estimate the performance of tens of thousands of catalysts by experimentally testing a smaller subset. Using error assessment metrics, it is possible to understand the confidence in new predictions. An experimentalist using this tool can balance the predicted results (reward) with the prediction confidence (risk) when deciding which catalysts to synthesize next in an optimization campaign. These catalysts are synthesized and tested experimentally. At this stage, either the optimization is a success or the predicted values were incorrect and further optimization is required. In the case of the latter, the information can be fed back into the statistical learning model to refine the model, and this iterative process can be used to determine the optimal catalyst. In this body of work, we not only establish this workflow but quantitatively establish how best to execute each step. Herein, we evaluate several 3D molecular representations to determine how best to represent molecules. Several selection protocols are examined to best decide which set of molecules can be used to represent the library of interest. In addition, the number of reactions needed to make accurate, statistical learning models is evaluated. Taken together these components establish a tool ready to progress from the development stage to the utility stage. As such, current research endeavors focus on applying these tools to optimize new reactions.

Effects of classroom-based active breaks on cognition, sitting and on-task behaviour in children with intellectual disability: a pilot study.

BACKGROUND: Classroom-based active breaks can help typically developing children reduce sitting, increase physical activity and improve cognitive functions and on-task behaviour. Yet, this strategy has not been tested in children with intellectual disability (ID) - a population who are insufficiently active. This study aimed to investigate the effects of a 5-week active breaks intervention on cognitive functions and on-task behaviour in schoolchildren with ID. METHODS: Twenty-four children, aged between 8 and 12 years (37.5% girls), were recruited. Children's cognitive functions (response inhibition, lapses of attention, interference and working memory) were measured at baseline and end of trial using computer-based tests. Sitting, standing and movement patterns were assessed with inclinometers, and on-task behaviour was directly observed in the classroom before and after active breaks, at baseline, mid-trial and end of trial. Linear mixed models were used to investigate the intervention effects on cognitive functions and sedentary patterns; generalised linear mixed models were used to analyse on-task behaviour data. RESULTS: A significant time × group interaction was found for working memory favouring the intervention (B = 11.56, 95% confidence interval [1.92, 21.21]). No significant effects were found in relation to the other measures of children's cognition or on-task behaviour. Stepping time and bouts of sitting were positively affected. CONCLUSIONS: Classroom-based active breaks can increase physical activity and reduce sedentary behaviour in children with ID and might also benefit their working memory. Further research is required to clarify the effects on cognition and to investigate whether this strategy has other benefits in this population.

Young Children with ASD Participate in the Same Level of Physical Activity as Children Without ASD: Implications for Early Intervention to Maintain Good Health.

Primary-school-aged children and adolescents with autism spectrum disorder (ASD) are reported to engage in lower levels of moderate-to-vigorous physical activity (MVPA) compared to typically developing (TD) children (Jones et al. in PLoS ONE, 12(2):1-23, 2017). Levels of MVPA in young children with ASD remain unclear. This study aimed to investigate MVPA in 4-to-7-year-old children with (n = 37) and without (n = 40) ASD, to determine if MVPA is related to ASD diagnosis; and examine correlates to better inform interventions. Results indicated children with ASD engage in the same levels of MVPA as TD children. Future studies need to further explore MVPA in children with ASD over time to uncover when the divergence in MVPA levels occur and what factors may be associated.

Attentional Mechanisms in Autism, ADHD, and Autism-ADHD Using a Local-Global Paradigm.

OBJECTIVE: Cognitive flexibility or attentional set-shifting capacity has long been considered a core area of executive dysfunction for individuals with autism. Whether these difficulties are due to higher-level attentional difficulties associated with comorbid ADHD remains unclear. METHOD: The current study compared the performance of 48 participants with autism, ADHD, autism-ADHD, and a comparison group ( N = 12 per group) on a set-shifting task, which included a local-global paradigm. RESULTS: Results of this study revealed that participants with attentional difficulties (autism + ADHD and ADHD alone) exhibited a significant shifting cost (difference between maintaining and shifting attention). CONCLUSION: Attentional difficulties associated with ADHD may be associated with an enhanced attentional shifting cost. Implications of these results were discussed in relation to screening for ADHD symptoms in studies of individuals with autism which seek to determine the neuropsychological profile of this condition.

Does a brief, behavioural intervention, delivered by paediatricians or psychologists improve sleep problems for children with ADHD? Protocol for a cluster-randomised, translational trial.

INTRODUCTION: Up to 70% of children with attention-deficit/hyperactivity disorder (ADHD) experience sleep problems. We have demonstrated the efficacy of a brief behavioural intervention for children with ADHD in a large randomised controlled trial (RCT) and now aim to examine whether this intervention is effective in real-life clinical settings when delivered by paediatricians or psychologists. We will also assess the cost-effectiveness of the intervention. METHODS AND ANALYSIS: Children aged 5-12 years with ADHD (n=320) are being recruited for this translational cluster RCT through paediatrician practices in Victoria and Queensland, Australia. Children are eligible if they meet criteria for ADHD, have a moderate/severe sleep problem and meet American Academy of Sleep Medicine criteria for either chronic insomnia disorder or delayed sleep-wake phase disorder; or are experiencing sleep-related anxiety. Clinicians are randomly allocated at the level of the paediatrician to either receive the sleep training or not. The behavioural intervention comprises 2 consultations covering sleep hygiene and standardised behavioural strategies. The primary outcome is change in the proportion of children with moderate/severe sleep problems from moderate/severe to no/mild by parent report at 3 months postintervention. Secondary outcomes include a range of child (eg, sleep severity, ADHD symptoms, quality of life, behaviour, working memory, executive functioning, learning, academic achievement) and primary caregiver (mental health, parenting, work attendance) measures. Analyses will address clustering at the level of the paediatrician using linear mixed effect models adjusting for potential a priori confounding variables. ETHICS AND DISSEMINATION: Ethics approval has been granted. Findings will determine whether the benefits of an efficacy trial can be realised more broadly at the population level and will inform the development of clinical guidelines for managing sleep problems in this population. We will seek to publish in leading international paediatric journals, present at major conferences and through established clinician networks. TRIAL REGISTRATION NUMBER: ISRCTN50834814, Pre-results.

Exploring factors related to the anger superiority effect in children with Autism Spectrum Disorder.

Despite face and emotion recognition deficits, individuals with Autism Spectrum Disorder (ASD) appear to experience the anger superiority effect, where an angry face in a crowd is detected faster than a neutral face. This study extended past research to examine the impacts of ecologically valid photographic stimuli, gender and anxiety symptoms on the anger superiority effect in children with and without ASD. Participants were 81, 7-12year old children, 42 with ASD matched on age, gender and perceptual IQ to 39 typically developing (TYP) children. The photographic stimuli did not impact on task performance in ASD with both groups exhibiting the anger superiority effect. There were no gender differences and no associations with anxiety. Age was associated with the effect in the TYP but not ASD group. These findings confirm a robust effect of speeded detection of threat in ASD which does not appear to be confounded by gender or anxiety, but may have different underlying age-associated mechanisms.

Synthesis of tetraphosphine macrocycles using copper(i) templates.

The synthesis of phosphine macrocycles is a relatively underdeveloped area and no standard synthetic routes have emerged. Accordingly, two general synthetic routes to tetradentate phosphine macrocycles were investigated. Both routes use Cu(i) ions as template ions because, unlike other metals such as Pd(ii) and Pt(ii), the Cu(i) ions can be removed from the macrocyclic complex without degrading the macrocycle ligand. The first route involves the coupling of two bidentate secondary phosphines bonded to Cu(i) using 1,3-dibromopropane or 1,4-dibromobutane. Using this route, tetradentate phosphine macrocycles with either -(CH2)3OCH3 or Ph groups bonded to the P atoms were synthesized. Macrocycle phosphines containing the -(CH2)3OCH3 groups were investigated for their potential water-solubility, but experiments showed these phosphines were not water soluble. The second synthetic route involved the alkylation of an open-chain, mixed tertiary-secondary, tetradentate phosphine coordinated to Cu(i). Following formation of the macrocyclic ligand, the Cu(i) template was removed by reaction with aqueous KCN to yield the free macrocyclic phosphine. This route was demonstrated for the preparation of the macrocyclic phosphine ligand 1,5,9,13-tetraphenyl-1,5,9,13-tetraphosphacycloheptadecane. Following demetallation, this macrocyclic ligand was coordinated to Fe(ii) and Co(ii) to form the corresponding macrocyclic phosphine complexes.