Biology subjects

Nelson, C. A.

Publications and source records attributed to Nelson, C. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Time at Home for Whom? Unequal Returns of Paid Family Leave for Infant White Matter and Language Development

Paid family leave (PFL) may give parents more time with infants, ease financial strain, and support stable routines. Although PFL has been linked to child development, little is known about neural pathways that might underpin its benefits or whether associations vary across families. Using data from 274 infants in the HEALthy Brain and Child Development Study, we examined associations of maternal and paternal PFL with language ability at 12 months and white matter microstructure at 6 months. We tested whether associations varied by the corresponding parent's education. Neither maternal nor paternal PFL was directly associated with language scores or fractional anisotropy in the left arcuate, inferior longitudinal, or uncinate fasciculus. Maternal education moderated associations between maternal PFL and fractional anisotropy in the arcuate (p = .014) and inferior longitudinal fasciculus (p = .003; n = 148). In both tracts, PFL was associated with higher fractional anisotropy only among infants whose mothers had relatively high education. No comparable pattern emerged for language, the uncinate fasciculus, or paternal PFL. Findings suggest that the neurodevelopmental correlates of PFL may depend on family resources rather than operate uniformly across families, underscoring the need to pair paid leave with additional supports and resources.

neuroscience↗

bioRxiv2026

Demonstration of periodic and aperiodic EEG reliability between laboratory and clinic settings

Structured AbstractO_ST_ABSObjectiveC_ST_ABSTo facilitate the scalability of EEG research, this paper compares the data quality and evaluates the absolute agreement of EEG features between laboratory and clinic settings. MethodsResting state EEG recordings were obtained from 36 participants (11 infants, 10 children, and 15 adults) from the waiting room of a primary care clinic and a laboratory. Intraclass correlation coefficients (ICC(2,1)) quantified the absolute agreement between laboratory and clinic settings for periodic power bands, alpha peak characteristics, and aperiodic components. The mean absolute difference (MAD) between laboratory and clinic recorded EEGs were calculated to describe signal consistency across settings. ResultsMore components were rejected from clinic-recorded EEGs, though data quality otherwise did not differ between settings. The ICC (2,1) for all EEG measures were generally in the good-to-excellent range across ages and regions of interest. The MAD decreased with age and was largest in the alpha frequency range. ConclusionsHigh quality EEG data can be collected from outpatient clinic settings among infants, children, and adults. There is high reliability in the parameterized periodic and aperiodic EEG features between laboratory and clinic settings. SignificanceFuture research may collect EEG datasets from naturalistic settings with confidence in their reliability relative to laboratory recordings.

physiology↗

bioRxiv2025

Determinants of human versus mosquito cell entry by the Chikungunya virus envelope proteins

Chikungunya virus (CHIKV) infects both humans and mosquitoes during its transmission cycle. How the viruss envelope proteins mediate entry in cells from such different species is unclear. MXRA8 is a receptor for CHIKV in mammalian cells, but the receptor(s) in mosquito cells remains unknown. Here we use pseudovirus deep mutational scanning to measure how nearly all amino-acid mutations to the CHIKV envelope proteins affect entry in MXRA8-expressing human and mosquito cells. Most mutations similarly affect entry in both types of cells, and our comprehensive measurements of these effects define functional constraints related to protein folding and fusion activity. However, some mutations differentially affect entry in MXRA8-expressing human cells versus mosquito cells. Sites where mutations specifically impair entry in MXRA8-expressing human cells are often involved in MXRA8 binding, and we hypothesize sites where mutations specifically impair entry in mosquito cells are involved in binding the unknown mosquito receptor(s). We use the deep mutational scanning data to design loss-of-tropism mutant viruses that are impaired in their ability to infect either mosquito cells or MXRA8-expressing human cells. Our findings provide insights into the species-specific determinants of CHIKV cell entry that can help guide receptor identification and vaccine development.

microbiology↗

bioRxiv2025

Growth charts of infant visual neurodevelopment generalize across global contexts

Normative brain growth charts in early life hold great promise for furthering basic and clinical science. We leverage the rapid, substantial development of visual cortex function that is indexed by visual-evoked potentials (VEP) in electroencephalography to create longitudinal normative growth curves of task-related brain function with 1374 observations contributed by 802 infants (57 to 579 days old) from South Africa, Brazil, and the United States. Site-specific models were cross-validated and showed excellent fits to other sites samples, demonstrating functional growth curves generalize across contexts robustly. Deviations from the normative growth models associated with early environmental and behavioral measures such as prenatal exposures and postnatal cognition. These findings demonstrate the utility of using functional growth charts to understand and potentially act on individual neurodevelopmental trajectories. VEP brain function growth charts represent a new direction for EEG research to support healthy brain development globally.

neuroscience↗

bioRxiv2024

Longitudinal trajectories of aperiodic EEG activity in early to middle childhood

BackgroundEmerging evidence suggests that aperiodic EEG activity may follow a nonlinear growth trajectory in childhood. However, existing studies are limited by small assessment windows and cross-sectional samples that are unable to fully capture these patterns. The current study aimed to characterize the developmental trajectories of aperiodic activity longitudinally from infancy to middle childhood. We examined potential trajectory differences by sex and brain region. We further investigated whether aperiodic activity is associated with maternal anxiety symptoms, and whether these associations vary because of differential development trajectories. MethodsA community sample of children and their parents (N=391) enrolled in a longitudinal study of emotion processing were assessed at infancy, and at ages 3 years, 5 years, and 7 years. Analyses included individual growth curve and mixed effect models. Developmental trajectories of the aperiodic slope and offset were investigated across whole brain, frontal, central, temporal, and posterior regions. Associations of whole brain slope and offset with maternal anxiety symptoms were also examined. ResultsDevelopmental trajectories for both slope and offset were generally characterized by a relative increase in early childhood and a subsequent decrease or stabilization by age 7, with variation by brain region. Females showed relatively steeper slopes at some ages, and males showed relatively greater offset at certain ages. Maternal anxiety was negatively associated with slope at 3 years and positively associated with slope at 7 years. ConclusionsThe longitudinal developmental trajectory of aperiodic slope in early childhood is nonlinear and shows variation by sex and brain region. The magnitude and direction of associations with maternal anxiety varied by age, corresponding with changes in trajectories. Developmental stage should be considered when interpreting findings related to aperiodic activity in childhood.

neuroscience↗

bioRxiv2022

Shedding Light on functional Near Infrared Spectroscopy and Open Science Practices

Open science practices work to increase methodological rigor, transparency, and replicability of published findings. This review aims to reflect and commemorate what the functional Near Infrared Spectroscopy (fNIRS) community has done to promote open science practices in fNIRS research and set goals to accomplish over the next ten years.

scientific communication and education↗

bioRxiv2022

Isolation of a potently neutralizing and protective human monoclonal antibody targeting yellow fever virus

Yellow fever virus (YFV) causes sporadic outbreaks of infection in South America and sub-Saharan Africa. While live-attenuated yellow fever virus vaccines based on three substrains of 17D are considered some of the most effective vaccines in use, problems with production and distribution have created large populations of unvaccinated, vulnerable individuals in endemic areas. To date, specific antiviral therapeutics have not been licensed for human use against YFV or any other related flavivirus. Recent advances in monoclonal antibody (mAb) technology have allowed for identification of numerous candidate therapeutics targeting highly pathogenic viruses, including many flaviviruses. Here, we sought to identify a highly neutralizing antibody targeting YFV envelope (E) protein as a therapeutic candidate. We used human B cell hybridoma technology to isolate mAbs from the circulating memory B cells from human YFV vaccine recipients. These antibodies bound to recombinant YFV E protein and recognized at least five major antigenic sites on E. Two mAbs (designated YFV-136 and YFV-121) recognized a shared antigenic site and neutralized the YFV 17D vaccine strain in vitro. YFV-136 also potently inhibited infection by multiple wild-type YFV strains, in part, at a post-attachment step in the virus replication cycle. YFV-136 showed therapeutic protection in two animal models of YFV challenge including hamsters and immunocompromised mice engrafted with human hepatocytes. These studies define features of the antigenic landscape on YFV E protein recognized by the human B cell response and identify a therapeutic antibody candidate that inhibits infection and disease caused by highly virulent strains of YFV.

immunology↗

bioRxiv2021

Brain Morphometry and Chronic Inflammation in Bangladeshi Children Growing up in Extreme Poverty

Over three hundred million children live in environments of extreme poverty, and the biological and psychosocial hazards endemic to these environments often expose these children to infection, disease, and inflammatory responses. Chronic inflammation in early childhood has been associated with diminished cognitive outcomes, and despite this established relationship, the mechanisms explaining how inflammation affects brain development are not well known. Importantly, the prevalence of chronic inflammation in areas of extreme poverty raises the possibility that it may serve as a mechanism explaining the known relationship between low socioeconomic status (SES) and altered brain development. To examine these potential pathways, seventy-nine children growing up in an extremely poor, urban area of Bangladesh underwent MRI scanning at six years of age. Structural brain images were submitted to Mindboggle software, a Docker-compliant and high-reproducibility tool for regional estimations of volume, surface area, cortical thickness, sulcal depth, and mean curvature. C-reactive protein was assayed at eight time points between infancy and five years of age and the frequency with which children had elevated concentrations of inflammatory marker represented the measure of chronic inflammation. Childhood SES was measured with maternal education and income-to-needs (i.e., monthly household income divided by the number of household members). Chronic inflammation predicted volume in bilateral basal ganglia structures and mediated the link between maternal education and bilateral putamen volumes. These findings suggest that chronic inflammation is associated with brain morphometry in the basal ganglia, predominantly the putamen, and further offers inflammation as a potential mechanism linking SES to brain development.

neuroscience↗

bioRxiv2021

Brain Morphometry and Diminished Physical Growth in Bangladeshi Children Growing up in Extreme Poverty: a Longitudinal Study

Diminished physical growth is a common marker of malnutrition and it affects approximately 200 million children worldwide. Despite its importance and prevalence, it is not clear whether diminished growth affects brain development and neurocognitive outcomes. Further, diminished growth is more common in areas of extreme poverty, raising the possibility that it may serve as a mechanism for previously shown links between poverty and brain development. To address these questions, 79 children growing up in an extremely poor, urban area of Bangladesh underwent MRI at 6 years. Structural brain images were submitted to Mindboggle software, a Docker-compliant and highly reproducible tool for tissue segmentation and regional estimations of volume, surface area, cortical thickness, travel depth, and mean curvature. Diminished growth predicted brain morphometry and mediated the link between poverty and brain morphometry most consistently for white matter and subcortical volumes. Meanwhile, brain volume in left pallidum and right ventral diencephalon mediated the relationship between diminished growth and full-scale IQ. These findings offer malnutrition as one possible mechanism by which poverty affects brain development and neurocognitive outcomes in areas of extreme poverty.

neuroscience↗

bioRxiv2020

SARS-CoV-2 infection severity is linked to superior humoral immunity against the spike

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a global pandemic. The antigen specificity and kinetics of the antibody response mounted against this novel virus are not understood in detail. Here, we report that subjects with a more severe SARS-CoV-2 infection exhibit a larger antibody response against the spike and nucleocapsid protein and epitope spreading to subdominant viral antigens, such as open reading frame 8 and non-structural proteins. Subjects with a greater antibody response mounted a larger memory B cell response against the spike, but not the nucleocapsid protein. Additionally, we revealed that antibodies against the spike are still capable of binding the D614G spike mutant and cross-react with the SARS-CoV-1 receptor binding domain. Together, this study reveals that subjects with a more severe SARS-CoV-2 infection exhibit a greater overall antibody response to the spike and nucleocapsid protein and a larger memory B cell response against the spike.

immunology↗

bioRxiv2020

Neural responses to happy, fearful and angry faces of varying identities in 5- and 7-month-old infants

Facial emotion processing is an important social skill that develops throughout infancy and early childhood. Here we investigate the neural underpinnings of the ability to process facial emotion across changes in facial identity in cross-sectional groups of 5- and 7-month-old infants. We simultaneously measured neural metabolic, behavioral, and autonomic responses to happy, fearful, and angry faces of different female models using functional near-infrared spectroscopy (fNIRS), eye-tracking, and heart rate measures. We observed significant neural activation to these facial emotions in a distributed set of frontal and temporal brain regions, and longer looking to the mouth region of angry faces compared to happy and fearful faces. No differences in looking behavior or neural activations were observed between 5- and 7-month-olds, although several exploratory, age-independent associations between neural activations and looking behavior were noted. Overall, these findings suggest more developmental stability than previously thought in responses to emotional facial expressions of varying identities between 5- and 7-months of age.

neuroscience↗

bioRxiv2020

Temporal dynamics of visual representations in the infant brain

Tools from computational neuroscience have facilitated the investigation of the neural correlates of mental representations. However, access to the representational content of neural activations early in life has remained limited. We asked whether patterns of neural activity elicited by complex visual stimuli (animals, human body) could be decoded from EEG data gathered from 12-15-month-old infants and adult controls. We assessed pairwise classification accuracy at each time-point after stimulus onset, for individual infants and adults. Classification accuracies rose above chance in both groups, within 500 ms. In contrast to adults, neural representations in infants were not linearly separable across visual domains. Representations were similar within, but not across, age groups. These findings suggest a developmental reorganization of visual representations between the second year of life and adulthood and provide a promising proof-of-concept for the feasibility of decoding EEG data within-subject to assess how the infant brain dynamically represents visual objects.

neuroscience↗

bioRxiv2019

Within Visit Test-Retest Reliability of EEG Profiles in Children with Autism Spectrum Disorder and Typical Development

Biomarker development is currently a high priority in neurodevelopmental disorder research. For many types of biomarkers (particularly biomarkers of diagnosis), reliability over short time periods is critically important. In the field of autism spectrum disorder (ASD), resting electroencephalography (EEG) power spectral densities (PSD) are well-studied for their potential as biomarkers. Classically, such data have been decomposed into pre-specified frequency bands (e.g., delta, theta, alpha, beta, and gamma). Recent technical advances, such as the Fitting Oscillations and One-Over-F (FOOOF) algorithm, allow for targeted characterization of the features that naturally emerge within an EEG PSD, permitting a more detailed characterization of the frequency band-agnostic shape of each individuals EEG PSD. Here, using two resting EEGs collected a median of 6 days apart from 22 children with ASD and 25 typically developing (TD) controls during the Feasibility Visit of the Autism Biomarkers Consortium for Clinical Trials, we estimate within visit test-retest reliability based on characterization of the PSD shape in two ways: (1) Using the FOOOF algorithm we estimate six parameters (offset, slope, number of peaks, and amplitude, center frequency and bandwidth of the largest alpha peak) that characterize the shape of the EEG PSD; and (2) using nonparametric functional data analyses, we decompose the shape of the EEG PSD into a reduced set of basis functions that characterize individual power spectrum shapes. We show that individuals exhibit idiosyncratic PSD signatures that are stable over recording sessions using both characterizations. Our data show that EEG activity from a brief two-minute recording provides an efficient window into understanding brain activity at the single-subject level with desirable psychometric characteristics that persist across different analytical decomposition methods. This is a necessary step towards analytical validation of biomarkers based on the EEG PSD, and provides insights into parameters of the PSD that offer short-term reliability (and thus promise as potential biomarkers of trait or diagnosis) versus those that are more variable over the short term (and thus may index state or other rapidly dynamic measures of brain function). Future research should address longer-term stability of the PSD, for purposes such as monitoring development or response to treatment.

neuroscience↗

bioRxiv2019

Developmental Changes in EEG Phase Amplitude Coupling and Phase Preference over the First Three Years After Birth

The coupling of the phase of slower electrophysiological oscillations with the amplitude of faster oscillations, termed phase-amplitude coupling (PAC), is thought to facilitate dynamic connectivity in the brain. Though the brain undergoes dramatic changes in connectivity during the first few years of life, how PAC changes through this developmental period has not been studied. Here, we examined PAC through electroencephalography (EEG) data collected longitudinally during an awake, eyes-open EEG collection paradigm in 98 children between the ages of 3 months and 3 years. We implement a novel technique developed for capturing both PAC strength and phase preference (i.e., where in the slower oscillation waveform the faster oscillation shows increased amplitude) simultaneously, and employed non-parametric clustering methods to evaluate our metrics across a range of frequency pairs and electrode locations. We found that frontal and occipital PAC, primarily between the alpha-beta and gamma frequencies, increased from early infancy to early childhood (p = 1.35 x 10-5). Additionally, we found frontal gamma coupled with the trough of the alpha-beta waveform, while occipital gamma coupled with the peak of the alpha-beta waveform. This opposing trend may reflect each regions specialization towards feedback or feedforward processing, respectively.\n\nSignificance StatementThe brain undergoes significant changes in functional connectivity during infancy and early childhood, enabling the emergence of higher-level cognition. Phase-amplitude coupling (PAC) is thought to support the functional connectivity of the brain. Here, we find PAC increases from 3 months to 3 years of age. We additionally report the frontal and occipital brain areas show opposing forms of PAC; this difference could facilitate each regions tendency towards bottom-up or top-down processing.

neuroscience↗

bioRxiv2019

Structural basis of cowpox evasion of NKG2D immunosurveillance

NKG2D is a key component of cytotoxic antitumor and antiviral responses. Multiple viruses evade NKG2D recognition by blocking NKG2D ligand expression on infected cells. In contrast, cowpox virus targets NKG2D directly by encoding a secreted antagonist, Orthopoxvirus MHC Class I-like Protein (OMCP). We have previously reported that OMCP also binds to the orphan receptor FcRL5 on innate B cells. Here, we demonstrate that mammalian-derived, glycosylated OMCP binds NKG2D but not FcRL5. Cowpox viruses either lacking OMCP, or expressing an NKG2D-binding deficient mutant, are significantly attenuated in wild type and FcRL5-deficient mice but not NKG2D-deficient mice, demonstrating that OMCP is critical in subverting NKG2D-mediated immunity in vivo. Next we determined the structure of OMCP bound to human NKG2D. Despite a structure similar to that of host NKG2D ligands, OMCP uses a drastically different orientation for NKG2D binding. The re-orientation of OMCP is associated with dramatically higher affinity for human NKG2D and the targeted interface is highly conserved in mammalian NKG2Ds, increasing the zoonotic potential of cowpox virus. We also show that cell surface presented OMCP can trigger NKG2D effector functions equivalently to host NKG2D ligands, demonstrating that NKG2D-mediated signaling requires clustering but is insensitive to binding orientation. Thus, in contrast to TCR/MHC interactions, the docking topology of NKG2D with its ligands does not appear to regulate its activation.\n\nAuthor SummaryVirally infected or tumor-transformed cells display NKG2D ligands (NKG2DLs) on their cell surface, which activates NKG2D-bearing lymphocytes to kill the transformed cell. Pathogens are known to counter this by blocking NKG2DL expression and/or surface display. In contrast, some tumor cells cleave endogenous NKG2DLs creating soluble NKG2D antagonists. Unlike other viral pathogens, cowpox virus uses a strategy analogous to cancer cells by targeting NKG2D directly with a soluble, high affinity NKG2D-antagonist named OMCP. We determined that OMCPs virulence in vivo is attributed to blocking NKG2D-mediated NK cell responses with no apparent effect due to binding to other receptors or cell types. We have also determined the crystal structure of cowpox OMCP bound to human NKG2D, revealing that despite conservation of the ligand scaffolding with host NKG2DLs, the viral protein is engaged with a radically altered orientation compared to all host NKG2DLs. Our structure provides key insight into how OMCP binds with an [~]5,000-fold increased affinity compared to human NKG2DLs and show that the OMCP binding site is exceptionally conserved among primates and rodents, suggesting that the ability of OMCP to recognize this conserved interface contributes to the broad zoonotic potential of cowpox virus. Finally, we show that cell membrane-anchored OMCP can trigger equivalent NKG2D-mediated killing as host NKG2DLs, demonstrating that NKG2D signaling is insensitive to ligand binding orientation.

immunology↗

bioRxiv2019

Relating anthropometric indicators to brain structure in 2-month-old Bangladeshi infants growing up in poverty: a pilot study

Anthropometric indicators, including stunting, underweight, and wasting, have previously been associated with poor neurocognitive outcomes. This link may exist because malnutrition and infection, which are known to affect height and weight, also impact brain structure according to animal models. However, a relationship between anthropometric indicators and brain structural measures has not been tested yet, perhaps because stunting, underweight, and wasting are uncommon in higher-resource settings. Further, with diminished anthropomorphic growth prevalent in low-resource settings, where biological and psychosocial hazards are most severe, one might expect additional links between measures of poverty, anthropometry, and brain structure. To begin to examine these relationships, we conducted an MRI study in 2-3-month-old infants growing up in the extremely impoverished urban setting of Dhaka, Bangladesh. The sample size was relatively small because the challenges of investigating infant brain structure in a low-resource setting needed to be realized and resolved before introducing a larger cohort. Initially, fifty-four infants underwent T1 sequences using 3T MRI, and structural images were segmented into gray and white matter maps, which were carefully evaluated for accurate tissue labeling by a pediatric neuroradiologist. Gray and white matter volumes from 29 infants (79 {+/-} 10 days-of-age; F/M = 12/17), whose segmentations were of relatively high quality, were submitted to semi-partial correlation analyses with stunting, underweight, and wasting, which were measured using height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) scores. Positive semi-partial correlations (after adjusting for chronological age and sex and correcting for multiple comparisons) were observed between white matter volume and HAZ and WAZ; however, WHZ was not correlated with any measure of brain volume. In examining the role of poverty, no associations were observed between income-to-needs or maternal education and brain volumetric measures, suggesting that risk factors previously linked with poverty were not associated with total brain tissue volume pre- or peri-natally in this sample. Overall, these results provide the first link between diminished anthropomorphic growth and white matter volume in infancy. Challenges of conducting a developmental neuroimaging study in a low-resource country are described.

neuroscience↗

bioRxiv2019

Early patterns of functional brain development associated with autism spectrum disorder in tuberous sclerosis complex.

Lay AbstractAround half of infants with tuberous sclerosis complex (TSC) develop autism. Here, using EEG, we find that there is a reduction in communication between brain regions during infancy in TSC, and that the infants who show the largest reductions are those who later develop autism. Being able to identify infants who show early signs of disrupted brain development may improve the timing of early prediction and interventions in TSC, and also help us to understand how early brain changes lead to autism.\n\nAbstractTuberous sclerosis complex (TSC) is a rare genetic disorder that confers a high risk for autism spectrum disorders (ASD), with behavioral predictors of ASD emerging early in life. Deviations in structural and functional neuronal connectivity are highly implicated in both TSC and ASD.\n\nFor the first time, we explore whether electroencephalographic (EEG) measures of network function precede or predict the emergence of ASD in TSC. We determine whether altered brain function (1) is present in infancy in TSC, (2) differentiates infants with TSC based on ASD diagnostic status, and (3) is associated with later cognitive function.\n\nWe studied 35 infants with TSC (N=35), and a group of typically developing infants (n=20) at 12 and 24 months of age. Infants with TSC were later subdivided into ASD and non-ASD groups based on clinical evaluation. We measured features of spontaneous alpha oscillations (6-12Hz) that are closely associated with neural network development: alpha power, alpha phase coherence (APC) and peak alpha frequency (PAF).\n\nInfants with TSC demonstrated reduced interhemispheric APC compared to controls at 12 months of age, and these differences were found to be most pronounced at 24 months in the infants who later developed ASD. Across all infants, PAF at 24 months was associated with verbal and non-verbal cognition at 36 months.\n\nAssociations between early network function and later neurodevelopmental and cognitive outcomes highlight the potential utility of early scalable EEG markers to identify infants with TSC requiring additional targeted intervention initiated very early in life.

neuroscience↗

bioRxiv2019

Integrating Biomedical Research and Electronic Health Records to Create Knowledge Based Biologically Meaningful Machine Readable Embeddings

In order to advance precision medicine, detailed clinical features ought to be described in a way that leverages current knowledge. Although data collected from biomedical research is expanding at an almost exponential rate, our ability to transform that information into patient care has not kept at pace. A major barrier preventing this transformation is that multi-dimensional data collection and analysis is usually carried out without much understanding of the underlying knowledge structure. In an effort to bridge this gap, Electronic Health Records (EHRs) of individual patients were connected to a heterogeneous knowledge network called Scalable Precision Medicine Oriented Knowledge Engine (SPOKE). Then an unsupervised machine-learning algorithm was used to create Propagated SPOKE Entry Vectors (PSEVs) that encode the importance of each SPOKE node for any code in the EHRs. We argue that these results, alongside the natural integration of PSEVs into any EHR machine-learning platform, provide a key step toward precision medicine.

systems biology↗