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\"New danger and enemies are closer than she knows. Can the Lasso of Truth bring light to the dark for Wonder Woman? Coming off the highly anticipated Wonder Woman and Justice League movies and with the success of DC Super Hero Girls, the Amazon Warrior's profile is higher than ever\"-- Provided by publisher.

Typical brain development follows a protracted trajectory throughout childhood and adolescence. Deviations from typical growth trajectories have been implicated in neurodevelopmental and psychiatric disorders. Recently, the use of machine learning algorithms to model age as a function of structural or functional brain properties has been used to examine advanced or delayed brain maturation in healthy and clinical populations. Termed ‘brain age’, this approach often relies on complex, nonlinear models that can be difficult to interpret. In this study, we use model explanation methods to examine the cortical features that contribute to brain age modelling on an individual basis. In a large cohort of n = 768 typically-developing children (aged 3–21 years), we build models of brain development using three different machine learning approaches. We employ SHAP, a model-agnostic technique to identify sample-specific feature importance, to identify regional cortical metrics that explain errors in brain age prediction. We find that, on average, brain age prediction and the cortical features that explain model predictions are consistent across model types and reflect previously reported patterns of regions brain development. However, while several regions are found to contribute to brain age prediction error, we find little spatial correspondence between individual estimates of feature importance, even when matched for age, sex and brain age prediction error. We also find no association between brain age error and cognitive performance in this typically-developing sample. Overall, this study shows that, while brain age estimates based on cortical development are relatively robust and consistent across model types and preprocessing strategies, significant between-subject variation exists in the features that explain erroneous brain age predictions on an individual level.

•The fixel-based analysis framework was proposed for fibre-specific statistical analysis of diffusion MRI data.•A “fixel” represents an individual fibre population in a voxel, allowing for increased specificity over voxel-wise measures.•A state-of-the-art fixel-based analysis pipeline consists of several bespoke steps, but is conceptually similar to a voxel-based analysis.•Fixel-based analysis has seen increased adoption recently, with 75 published studies to date.•The framework has unique benefits and future opportunities, but specific challenges and limitations exist as well. Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple “crossing” fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the “Fixel-Based Analysis” (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities. [Display omitted]

This commentary provides a summary and discussion of the recently published study in Paediatric Research by Hedvig Kvanta et al., “Brain volumes and cortical thickness and associations with cognition in children born extremely preterm”.

Sequencing of circulating tumor DNA from cancer patients is a cost-efficient approach with turnaround time compatible with clinical practice to inform treatment decision-making in a phase 1 trial setting Next-generation sequencing (NGS) of circulating tumor DNA (ctDNA) supports blood-based genomic profiling but is not yet routinely implemented in the setting of a phase I trials clinic. TARGET is a molecular profiling program with the primary aim to match patients with a broad range of advanced cancers to early phase clinical trials on the basis of analysis of both somatic mutations and copy number alterations (CNA) across a 641 cancer-associated-gene panel in a single ctDNA assay. For the first 100 TARGET patients, ctDNA data showed good concordance with matched tumor and results were turned round within a clinically acceptable timeframe for Molecular Tumor Board (MTB) review. When a 2.5% variant allele frequency (VAF) threshold was applied, actionable mutations were identified in 41 of 100 patients, and 11 of these patients received a matched therapy. These data support the application of ctDNA in this early phase trial setting where broad genomic profiling of contemporaneous tumor material enhances patient stratification to novel therapies and provides a practical template for bringing routinely applied blood-based analyses to the clinic.

Background teen Mental Health First Aid (tMHFA) is a universal mental health literacy, stigma reduction, help-seeking, and suicide prevention program designed for adolescents in Years 10–12 of secondary school (16–18 years). tMHFA is delivered by trained instructors, in a regular classroom setting, to increase the knowledge, attitudes and behaviours that adolescents’ require to better support peers with mental health problems or mental health crises. Methods To explore the efficacy of tMHFA, a cluster crossover randomised controlled trial was conducted with Year 10 students in four schools in Victoria, Australia, using physical first aid training as the control intervention. Of the 1942 eligible students, 1,624 completed baseline and 894 completed follow-up surveys. Online surveys, administered one week before training and again 12-months later, included vignettes depicting peers John (depression and suicide risk) and Jeanie (social anxiety/phobia), measures of mental health first aid (quality of first aid intentions, confidence, first aid behaviours provided, and first aid behaviours received), mental health literacy (beliefs about adult help, help-seeking intentions), and stigma (social distance, weak-not-sick, dangerous/unpredictable, and would not tell anyone). Results The primary outcome—quality of first aid intentions towards the John vignette—showed statistically significant group x time interactions, with tMHFA students reporting more helpful and less unhelpful first aid intentions, than PFA students did over time. Confidence in providing first aid also showed significant interactions. First aid behaviours—both those provided to a peer with a mental health problem and those received from a peer—showed null results. Ratings of both beliefs about adult help and help-seeking intentions were found to be significantly improved among tMHFA students at follow-up. A group x time interaction was found on one stigma scale (would not tell anyone). Conclusions This trial showed that, one year after training, tMHFA improves first aid intentions towards peers with depression and suicide risk, confidence in helping peers with mental health problems, willingness to tell someone and seek help from an adult or health professional if experiencing a mental health problem. Trial registration This research was registered with Australia New Zealand Clinical Trials Registry: ACTRN12614000061639 .

Serial regional brain growth from the newborn period to adolescence has not been described. Here, we measured regional brain growth in 216 very preterm (VP) and 45 full-term (FT) children. Brain MRI was performed at term-equivalent age, 7 and 13 years in 82 regions. Brain volumes increased between term-equivalent and 7 years, with faster growth in the FT than VP group. Perinatal brain abnormality was associated with less increase in brain volume between term-equivalent and 7 years in the VP group. Between 7 and 13 years, volumes were relatively stable, with some subcortical and cortical regions increasing while others reduced. Notably, VP infants continued to lag, with overall brain size generally less than that of FT peers at 13 years. Parieto–frontal growth, mainly between 7 and 13 years in FT children, was associated with higher intelligence at 13 years. This study improves understanding of typical and atypical regional brain growth. In this longitudinal study, the authors tracked the course of brain development from birth to adolescence (age 13 years) and examined the effects of very preterm birth. Very preterm children showed slower brain growth from age 0 (term equivalent) to age 7.

In the food-borne pathogen Listeria monocytogenes , SigB is the central regulator of g eneral s tress r esponse (GSR) and it mediates host entry by promoting acid resistance and epithelial cell attachment. However, mutations can readily arise to disable r egulators of S ig B (Rsb proteins), which suggests a considerable genetic plasticity in the GSR. To further investigate this, we defined the complete genome sequence of a clinical isolate and elucidated how sequential mutations within sigB operon ( rsbX N77K and rsbU Q317*) impacted fitness through modulation of SigB activity. To investigate the plasticity of the GSR, we followed its genetic adaptation to lethal acidic challenge (mimicking the selective pressure encountered during entry into the host). Acid resistance developed rapidly and all 6 a cid r esistant d erivatives (ARDs) selected for analysis had acquired mutations in rsbW , which encodes an antagonist of SigB that suppresses SigB activity during non-stress conditions. These mutations resulted in non-canonical start codons ( rsbW ATG to rsbW ATA or rsbW ATT ) or premature translation termination ( rsbW - ) and all were found to result in increased SigB activity. A translational reporter assay demonstrated distinct differences in translation efficiency between three start codons: ATG > ATA > ATT, suggesting that a perturbation of RsbW:SigB stoichiometry alters SigB activity. We then analysed start codon usage for all conserved genes in 60,692 L. monocytogenes genomes. This analysis revealed flexible usage of start codons associated with genetic clades in 39 conserved genes, 13 of which are involved in virulence and stress response. Further, we show that flexible use of canonical start codons (ATG and GTG) can also mediate different levels of expression of virulence and stress response genes. Taken together, we show the genetic plasticity of GSR regulation in a model pathogen, and highlight the importance of translational control as a means of fine-tuning gene expression during short-term adaptation and long-term evolution for optimal fitness.

Background Adults who live or work with children are an important source of support and are gateways to professional help when a child is experiencing a mental health problem. This study aimed to develop consensus‐based guidelines on how adults such as parents, educators or health professionals should approach a child aged 5–12 years to discuss concerns about the child's mental health and seek help. Methods A Delphi consensus method with three rounds was used. Experts were recruited from six countries to form three panels: health professionals, educators and people with lived experience (parents and carers, and young people with mental health problems). Statements to be rated were sourced from an online search of websites designed for adults who live or work with children. Further suggestions for statements came from panellists. Statements that reached 80% consensus across all panels were included in the guidelines. Results 132 participants completed the Round 1 survey, reducing to 54 by Round 3. A total of 248 statements were presented to panel members, with 151 being endorsed and included in the guidelines. Conclusions These guidelines represent the first recommendations developed for members of the public providing mental health first aid to children aged 5–12 years. Patient or Public Contribution Lived experience advocates (i.e. those with lived experience of a mental health problem in childhood and/or caregiving experience of raising a child with a mental health problem) were involved at two stages of this research: As part of the Advisory Group for the project and as expert panel members. Advisory Group members provided input into the conduct of the study and the content and design of the research outputs. Panel members provided their expertise to review every item to be included in the guidelines, proposed new items to be included, and reviewed and approved the finalised output documents.

It is well established that preterm infants have altered brain development compared with full-term (FT; ≥37 weeks' gestational age [GA]) infants, however the perinatal factors associated with brain development in preterm infants have not been fully elucidated. In particular, perinatal predictors of brain development may differ between very preterm infants (VP; <32 weeks' GA) and infants born moderate (MP; 32–33 weeks' GA) and late (LP; 34–36 weeks' GA) preterm, but this has not been studied. This study aimed to investigate the effects of early life predictors on brain volume and microstructure at term-equivalent age (TEA; 38–44 weeks), and whether these effects differ for GA groups (VP, MP, LP or FT). Structural images from 328 infants (91 VP, 63 MP, 104 LP and 70 FT) were segmented into white matter, cortical grey matter, cerebrospinal fluid, subcortical grey matter, brainstem and cerebellum. Cortical grey matter and white matter images were analysed using voxel-based morphometry. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 361 infants (92 VP, 69 MP, 120 LP and 80 FT) were analysed using Tract-Based Spatial Statistics. Relationships between early life predictors (birthweight standard deviation score [BWSDS], multiple birth, sex, postnatal growth and social risk) and global brain volumes were analysed using linear regressions. Relationships between early life predictors and regional brain volumes and diffusion measures were analysed using voxelwise non-parametric permutation testing. Male sex was associated with higher global volumes of all tissues and higher regional volumes throughout much of the cortical grey matter and white matter, particularly in the FT group. Male sex was also associated with lower FA and higher AD, RD and MD in the optic radiation, external and internal capsules and corona radiata, and these associations were generally similar between GA groups. Higher BWSDS was associated with higher global volumes of all tissues and higher regional volumes in much of the cortical grey matter and white matter in all GA groups, as well as higher FA and lower RD and MD in many major tracts (corpus callosum, optic radiation, internal and external capsules and corona radiata), particularly in the MP and LP groups. Multiple birth and social risk also showed associations with global and regional volumes and regional diffusion values which varied by GA group, but these associations were not independent of the other early life predictors. Postnatal growth was not associated with brain volumes or diffusion values. Early life predictors of brain volumes and microstructure at TEA include sex, BWSDS, multiple birth and social risk, which have different effects based on GA group at birth. This study improves knowledge of the perinatal factors associated with brain abnormalities in infants born across the prematurity spectrum. •Early life factors affect regional brain volume and microstructural development.•Effects of early life factors on brain development differ by gestational age.•Males have higher brain volumes but less organised microstructure than females.•Poor prenatal growth is associated with lower volume and less mature white matter.•Multiple birth and social risk may also affect brain development.