Biology subjects

Falconer, S.

Publications and source records attributed to Falconer, S..

12 recordsLinked to original sources

bioRxiv2026

Safety Transparency in Animal Cell-Cultured Ingredients for Pet Food: A Case Study Establishing the Standard for Public Disclosure

Animal cell-cultured ingredients are entering the EU and UK pet food markets under frameworks that do not require pre-market, ingredient-level safety assessments, creating an ethical need for transparent safety disclosure. We present the first public safety dossier for this sector, describing the proprietary mouse embryonic stem cell line PE25 and its derived, non-viable cellular and conditioned media ingredient produced in food and feed-grade media. PE25 characterization confirmed Mus musculus identity, sterility, absence of mycoplasma and replication-competent retroviruses, and stable growth. Doxorubicin-induced p53 stress testing, CD44/BMI1 profiling, and soft agar assays showed no cancer-like traits and a non-tumorigenic profile; the final ingredient contains no viable cells. Independent OECD TG 471 and 487 assays confirmed non-genotoxicity. Heavy metals, biogenic amines, solvents, and chemical residues were below regulatory limits. Given process variability, we recommend case-by-case safety evaluation and propose this dossier as a model for responsible commercialization.

cell biology↗

bioRxiv2023

Objective assessment of visual attention in toddlerhood

Visual attention is an important mechanism through which children learn about their environment, and individual differences could substantially shape later development. Eyetracking provides a sensitive and scalable tool for assessing visual attention that has potential for objective assessment of child development, but to date the majority of studies are small and replication attempts are rare. This study investigates the feasibility of a comprehensive eye-tracking assessment of visual attention and introduces a shared data resource for the scientific community. Data from eight eyetracking tasks were collected from 350 term-born (166 females) 18-month-olds recruited as neonates http://www.developingconnectome.org/). Analyses showed expected condition effects for seven of eight tasks (p-values from <.001 to .04), an important indication of replicability. Consistent with some theoretical models of visual attention, structural equation modelling indicated participants performance could be explained by two factors representing social and non-social attention. Comprehensive eye-tracking batteries can objectively measure individual differences in core components of visual attention in large-scale toddlerhood studies. This is the first large-scale comprehensive study to present high-quality normative eye-tracking data from a large task battery in toddlers and make them freely available to the scientific community.

neuroscience↗

bioRxiv2022

Neonatal brain dynamic functional connectivity: impact of preterm birth and association with early childhood neurodevelopment

Brain dynamic functional connectivity characterises transient connections between brain regions, changing over time. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.

neuroscience↗

bioRxiv2022

Clinical, socio-demographic, and parental correlates of early autism traits

BackgroundAutism traits emerge between the ages of 1 and 2. It is not known if experiences which increase the likelihood of childhood autism are related to early trait emergence, or if other exposures are more important. Identifying factors linked to toddler autism traits in the general population may improve our understanding of the mechanisms underlying atypical neurodevelopment. MethodsClinical, socio-demographic, and parental information was collected at birth from 536 toddlers in London, UK (gestational age at birth, sex, maternal body mass index, age, parental education level, parental first language, parental history of neurodevelopmental disorders) and at 18 months (parent cohabiting status, two measures of social deprivation, three measures of maternal parenting style, and a measure of maternal postnatal depression). General neurodevelopment was assessed with the Bayley Scales of Infant and Toddler Development, 3rd Edition (BSID-III), and autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT). Multivariable models were used to identify associations between variables and Q-CHAT. A model including BSID-III was used to identify factors associated with Q-CHAT independent of general neurodevelopment. Models were also evaluated addressing variable collinearity with principal component analysis (PCA). ResultsA multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). After adding general neurodevelopment into the model 36% of Q-CHAT variance was explained, with three individually significant variables (two measures of parenting style and one measure of language development). After addressing variable collinearity with PCA, parenting style and social deprivation were positively correlated with Q-CHAT score via a single principal component, independently of general neurodevelopment. Neither sex nor family history of autism were associated with Q-CHAT score. LimitationsThe Q-CHAT is parent rated and is therefore a subjective opinion rather than a clinical assessment. We measured Q-CHAT at a single timepoint, and to date no participant has been followed up in later childhood, so we are focused purely on emerging traits rather than clinical autism diagnoses. ConclusionsAutism traits are common at age 18 months, and greater emergence is specifically related to exposure to early life adversity.

neuroscience↗

bioRxiv2022

Development of neonatal brain functional centrality and alterations associated with preterm birth

Formation of the functional connectome in early life underpins future learning and behaviour. However, our understanding of how the functional organisation of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterised voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and decrease within motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive, and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.

neuroscience↗

bioRxiv2021

Neonatal multi-modal cortical profiles predict 18-month developmental outcomes

Developmental delays in infanthood often persist, turning into life-long difficulties, and coming at great cost for the individual and community. By examining the developing brain and its relation to developmental outcomes we can start to elucidate how the emergence of brain circuits is manifested in variability of infant motor, cognitive and behavioural capacities. In this study, we examined if cortical structural covariance at birth, indexing coordinated development, is related to later infant behaviour. We included 193 healthy term-born infants from the Developing Human Connectome Project (dHCP). An individual cortical connectivity matrix derived from morphological and microstructural features was computed for each subject (morphometric similarity networks, MSNs) and was used as input for the prediction of behavioural scores at 18 months using Connectome-Based Predictive Modeling (CPM). Neonatal MSNs successfully predicted social-emotional performance. Predictive edges were distributed between and within known functional cortical divisions with a specific important role for primary and posterior cortical regions. These results reveal that multi-modal neonatal cortical profiles showing coordinated maturation are related to developmental outcomes and that network organization at birth provides an early infrastructure for future functional skills.

neuroscience↗

bioRxiv2021

Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age

IntroductionThe dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors. MethodsWe sought to first map typical cortical micro and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n=270). Then we offer a comprehensive characterisation of the cortical consequences of preterm birth in 78 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months. ResultsIn the term-born neonatal brain, we observed regionally specific age-associated changes in cortical morphology and microstructure, including rapid surface expansion, cortical thickness increase, reduction in cortical anisotropy and increase in neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months. ConclusionWe showed that preterm birth alters cortical micro and macrostructural maturation near the time of fullterm birth. Deviations from normative development were highly variable between individual preterm infants.

neuroscience↗

bioRxiv2021

Effects of gestational age at birth on perinatal structural brain development in healthy term-born babies

Multiple studies have demonstrated less favourable childhood outcomes in infants born in early term (37-38 weeks gestation) compared to those born at full term (40-41 weeks gestation). While this could be due to higher perinatal morbidity, gestational age at birth may also have a direct effect on the brain and subsequent neurodevelopment in term-born babies. Here we characterise structural brain correlates of gestational age at birth in healthy term-born neonates and their relationship to later neurodevelopmental outcome. We used T2 and diffusion weighted Magnetic Resonance Images acquired in the neonatal period from a cohort (n=454) of healthy babies born at term age (>37 weeks gestation) and scanned between 1 and 41 days after birth. Images were analysed using tensor based morphometry (TBM) and tract based spatial statistics (TBSS). Neurodevelopment was subsequently assessed at age 18 months using the Bayley-III Scales of Infant and Toddler Development, and the effects of gestational age at birth and related neuroimaging findings on outcome were analysed with linear regression. Infants born earlier had areas of higher relative ventricular volume, and lower relative brain volume in the basal ganglia, cerebellum and brainstem. Earlier birth was also associated with lower fractional anisotropy, higher mean, axial and radial diffusivity in major white matter tracts. Gestational age at birth was positively associated with all Bayley-III subscales at age 18 months. Linear regression models predicting outcome from gestational age at birth were significantly improved by adding neuroimaging features associated with gestational age at birth. This work adds to the growing body of evidence of the impact of early term birth and highlights the importance of considering the effect of gestational age at birth in future neuroimaging studies including term-born babies.

neuroscience↗

bioRxiv2020

Predicting age and clinical risk from the neonatal connectome

The development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. Diffusion MRI allows the characterisation of subtle inter-individual differences in structural brain connectivity. Individual brain connectivity maps (connectomes) are by nature high in dimensionality and are complex to interpret. Machine learning methods are a powerful tool to uncover properties of the connectome which are not readily visible, and can give us clues as to how and why individual developmental trajectories differ. In this manuscript we used Deep Neural Networks and Random Forests to predict demographic and neurodevelopmental characteristics from neonatal structural connectomes in a large sample of babies (n = 524) from the developing Human Connectome Project. We achieved an accurate prediction of post menstrual age (PMA) at scan in term-born infants (Mean absolute error (MAE) = 0.72 weeks, r = 0.83 and p<0.001). We also achieved good accuracy when predicting gestational age at birth in a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p<0.001). We subsequently used sensitivity analysis to obtain feature relevance from our prediction models, with the most important connections for prediction of PMA and GA found to be predominantly thalamocortical. From our models of PMA at scan for infants born at term, we computed a brain maturation index (predicted age minus actual age) of individual preterm neonates and found a significant correlation between this index and motor outcome at 18 months corrected age. Our results demonstrate the applicability of machine learning techniques in analyses of the neonatal connectome, and suggest that a neural substrate for later developmental outcome is detectable at term equivalent age.

neuroscience↗

bioRxiv2020

Individualized characterization of volumetric development in the preterm brain

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterising brain volumetric development in 274 term-born infants, modelling for age at scan and sex. We then compared 89 preterm infants scanned at termequivalent age to these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalisability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, non-uniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguise a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterisation of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

neuroscience↗

bioRxiv2018

The network properties of the brain at the time of normal birth support the acquisition of language processing

Language acquisition appears to rely at least in part on recruiting pre-existing brain structures. We hypothesized that the neural substrate for language can be characterized by distinct, non-trivial network properties of the brain, that modulate language acquisition early in development. We tested whether these brain network properties present at the normal age of birth predicted later language abilities, and whether these were robust against perturbation by studying infants exposed to the extreme environmental stress of preterm birth.\n\nWe found that brain network controllability and integration predicted respectively phonological, bottom-up and syntactical, top-down language skills at 20 months, and that syntactical but not phonological functions were modulated by premature extrauterine life. These data show that the neural substrate for language acquisition is a network property present at term corrected age. These distinct developmental trajectories may be relevant to the emergence of social interaction after birth.

neuroscience↗

bioRxiv2017

Long-term taxonomic and functional divergence from donor bacterial strains following fecal microbiota transplantation in immunocompromised patients

Immunocompromised individuals are at high risk of developing Clostridium difficile-associated disease (CDAD). Fecal microbiota transplantation (FMT) is a highly effective therapy for refractory or recurrent CDAD and, despite safety concerns, has recently been offered to immunocompromised patients. We investigated the genomics of bacterial composition following FMT in immunocompromised patients over a 1-year period. Metagenomic, strain and gene-level bacterial dynamics were characterized in two CDAD-affected hematopoietic stem cell (HCT) recipients following FMT. We found alterations in gene content, including loss of virulence and antibiotic resistance genes. These alterations were accompanied by long-term bacterial divergence at the species and strain levels. Our findings suggest limited durability of the specific bacterial consortium introduced with FMT and indicate that alterations of the functional potential of the microbiome are more complex than can be inferred by taxonomic information alone. Our observation that FMT alone cannot induce long-term donor-like alterations of the microbiota of HCT recipients suggests that FMT cannot indefinitely supersede environmental and/or host factors in shaping bacterial composition.

genomics↗