Biology subjects

Barron, A.

Publications and source records attributed to Barron, A..

8 recordsLinked to original sources

bioRxiv2026

Cortical gray matter density at age five associated with preceding early longitudinal language profiles: A Voxel-based morphometry analysis of the FinnBrain Birth Cohort Study

Previous studies exploring the connection between early language development and brain anatomy have shown that cortical areas relating to individual differences in language skills are diverse and vary depending on the age of child. However, due to lack of large longitudinal samples, current literature is limited in answering the extent to which individual differences in language development prior to school age are reflected in areas of the cortex. To fill this gap, we compared gray matter density between participants that belonged to different longitudinally defined language profiles from 14 months to five years of age in a large population-based sample. Participants were 166 children from the FinnBrain Birth Cohort Study who had longitudinal language data from 14 months to five years of age and magnetic resonance imaging data at five years of age. Three groups of language development were used as per our prior study: persistent low, stable average, and stable high. Voxel-based morphometry metrics were calculated using SPM12 and the three language profile groups were compared to one another. Covariates included sex and age at brain scan. The statistics were thresholded at p < 0.01 and false discovery rate corrected at the cluster level. Of the three longitudinal language profiles, the stable high group had higher gray matter density than the persistent low group in the right superior frontal gyrus. No differences were found between the stable average and stable high groups, nor persistent low and stable average groups. The identified superior frontal cortical area belongs to executive functions neural network. This finding adds to the cumulating evidence that individual differences in language development are reflected in growth of gray matter supporting general processing ability rather than specialized language regions. The results suggest that cognitive development and early language development are linked through shared principles of neural growth, identifiable already at age five. Key pointsO_LIAn association between early language development from 14 months to five years of age and gray matter density differences of the right superior frontal gyrus was found at the age of five years. Children following the strongest language trajectory were more likely to exhibit higher gray matter density of the right superior frontal gyrus than children following the weakest trajectory. C_LIO_LIAs the superior frontal gyrus is part of executive functions network, we propose that individual differences in early language development are more defined by general learning mechanisms supported by those networks, rather than language specific pathways. C_LI

neuroscience↗

bioRxiv2026

Functional connectome harmonics capture early brain organization and maturity in neonates

The functional organization of the human brain is established early, yet the ontogeny of its large-scale functional gradients remains unclear. Using resting-state fMRI data from 714 neonates in the Developing Human Connectome Project, we mapped neonatal brain gradients via functional connectome harmonics (FCH). We identified adult-like sensory-to-multimodal and cognitive gradient patterns present at birth. Applying three FCH-derived metrics--entropy, power, and energy--we found that power and energy were higher in term-born compared to preterm neonates, while entropy was elevated in preterms. These metrics predicted up to ~30% of postmenstrual age, indicating their biological relevance. Our findings reveal that the neonatal brain possesses a robust gradient architecture underpinning early functional organization, offering novel biomarkers for assessing brain maturity and the impact of prematurity on neurodevelopment.

neuroscience↗

bioRxiv2026

Functional connectome harmonics and dynamic connectivity maps of the preadolescent brain

The maturation of large-scale functional brain networks during preadolescence underpins critical cognitive and behavioral development. However, the spatial and temporal organization of these networks in this age group remains incompletely characterized. Here we applied Functional Connectome Harmonics (FCH) and Leading Eigenvector Dynamics Analysis (LEiDA) to resting-state fMRI data from over 11,000 children aged 9-10 years in the ABCD Study. FCH revealed hierarchical spatial gradients spanning cortical and subcortical regions, while LEiDA identified recurrent dynamic brain states aligned with canonical intrinsic connectivity networks. Linking these spatial and temporal components, we established a low-dimensional harmonic scaffold constraining brain dynamics during this developmental window. These findings provide a large-scale spatiotemporal reference framework of preadolescent functional brain organization, offering a foundation for characterizing neurodevelopmental benchmarks and early neural markers relevant to adolescent mental health.

neuroscience↗

bioRxiv2026

Investigation of Regulation and Binding Patterns of the Human Cathelicidin Peptide LL-37 in Complexation with Nucleic Acids, and its Impact on Neutrophil Extracellular Traps

The human cathelicidin host defense peptide LL-37 forms complexes with nucleic acids that can have either beneficial or detrimental health effects. We suggest that these differential impacts are directly connected to dsDNA binding by LL-37 and to complex formation between protomers. Here, we show using phage {lambda} DNA that LL-37 binds non-specifically to dsDNA, condensing it, followed by complex formation between LL-37 peptides. We find that complex formation is concentration-dependent, with low LL-37 amounts yielding loosely aggregated DNA structures, while higher LL-37 concentrations lead to well-defined, disc-like structures of about 150 nm in diameter. The condensation of the nucleic acids, which causes a loss of the characteristic B-DNA features, results from interactions of the phosphodiester backbone with protonated amino acid side chains of the peptide at physiological pH, predominantly in A-T rich sequences of the nucleic acid. However, in our studies, electrostatic interactions did not appear to be the driving force for complexation, but rather we found the -helical structure of the peptide with its amphipathic and hydrophobic surfaces to be essential. Further, we show that LL-37 also interacts with nucleic acids from neutrophil extracellular traps (NETs) in a concentration-dependent way, causing a reduction in NET aggregate area, which may offer new biophysical insights into diseases such as systemic lupus erythematosus (SLE), which involve slower-than-normal NET clearance. Our results indicate the key importance of LL-37 expression levels for regulation of the innate immune system for optimal human health, since the relative amounts of expressed LL-37 present to interact with extracellular DNA will determine the extent to which the DNA can be condensed, which in turn will affect the ability of the body to clear the NETs before they can cause inflammatory conditions.

biophysics↗

bioRxiv2025

skiftiTools: An R package for reading, writing, analysing, and visualising, tract-based spatial statistics (TBSS) derived diffusion MR images

skiftiTools processes three- and four-dimensional neuroimaging data, facilitating advanced statistical modelling with voxelwise data in any software of choice. Tract-Based Spatial Statistics (TBSS) is a conventionally used tool to make statistical calculations in voxel space for brain imaging data. While pre-existing software packages provide support for general linear model based statistics, there is a clear need for more sophisticated modeling. skiftiTools writes subject-per-volume NIfTI files as tab-separated value ASCII files, which are easily readable by most commonly used statistical tools such as R language (RStudio), SPSS, SAS, and GraphPad Prism. This facilitates a wide range of voxel-level statistical analyses from TBSS data, including estimation of standardised effect sizes, clustering, dimensionality reduction, non-linear and machine learning predictive modelling, which we showcase in this article using FinnBrain and developing Human Connectome Project diffusion MRI data. After statistical processing, the resulting ASCII data can then be read again for visualization. The package supports NIfTI image format, tab-separated ASCII format, and its own stand-alone format for efficient disk usage. It is open source (https://github.com/haanme/skiftiTools), built on R-language and has easy installation from Rs CRAN package repository. In addition, we provide basic functions available in Docker containers for further platform independence. HighlightsO_LIThe skiftiTools R package is an open-source, user-friendly interface for analysing voxelwise diffusion tensor imaging (DTI) data following tract-based spatial statistics (TBSS) processing C_LIO_LIIt supports reading, writing, visualization, mathematical operations, and data manipulation and thus allows comprehensive conventional and advanced statistics, including machine learning C_LIO_LIskiftiTools bridges a critical gap between statistical tools in R and voxelwise neuroimaging data - including comparable means to perform multiple comparison corrections and much needed possibility to use non-linear statistics C_LI

neuroscience↗

bioRxiv2025

Therapeutic Blockade of Type 2 Cytokines and PD1 Unleashes Anti-Tumor Immunity Through Coordinated Reprogramming of Innate and Adaptive Immune Surveillance

BackgroundCheckpoint inhibitors improve survival in patients with several types of tumors. However, resistance to checkpoint inhibitors creates an opportunity for patients to benefit from novel immunotherapies. The type 2 cytokines IL-4, IL-13 and TSLP have been implicated in suppressing anti-tumor immune responses through T and myeloid cells. Our current study tested whether combined therapeutic blockade of IL-4, IL-13 and TSLP improved anti-tumor immunity alone and in combination with PD1 antagonism. MethodsWe used in vitro experiments with primary cells to identify cell types likely to participate in controlling tumors upon IL-4, IL-13, TSLP and PD1 blockade. Therapeutic blockade in the subcutaneous CT26 model tested in vivo tumor growth inhibition and associated immunological changes. Bioinformatic analysis of human tumor bulk RNA sequencing data probed for survival associations with IL-4/IL-13 and TSLP transcriptional responses. ResultsIn vitro, IL-4 suppressed T cell-mediated tumor growth inhibition and reduced monocyte-derived dendritic cell expression of proteins associated with anti-tumor immunity. In vivo, blocking IL-4, IL-13, TSLP and PD1 improved tumor growth inhibition by creating "hotter" tumors. This was associated with repolarization of CD4 and CD8 T cells and shifts in monocyte, conventional type 1 and type 2 (or monocyte-derived) dendritic cell programs. Transcriptional responses to IL-4/IL-13 and TSLP were associated with poor survival outcomes across patients with several types of cancers. ConclusionTherapeutic blockade of IL-4, IL-13 and TSLP may drive immunological tumor growth inhibition in subsets of cancer patients alone and in combination with checkpoint inhibitors. Improved tumor growth inhibition was likely driven through augmented cytotoxic T cell priming in secondary lymphoid organs and improved reactivation by repolarized monocytes and dendritic cells in tumors.

cancer biology↗

bioRxiv2024

Antiparasitic effect of peptoids against Cryptosporidium parvum

Cryptosporidiosis, caused by Cryptosporidium parvum, poses significant health risks, particularly for children and immunocompromised individuals. Current treatments are ineffective in these vulnerable groups. This study explores the antiparasitic effects of against C. parvum. Out of 14 synthetic peptidomimetics (peptoids) screened, TM9 and TM19 exhibited potent anti-cryptosporidial activity without harming host cells. These findings suggest that peptoids could be a promising new therapeutic avenue for cryptosporidiosis, warranting further investigation.

microbiology↗

bioRxiv2020

A model of resource partitioning between foraging bees

Central place foraging pollinators tend to develop multi-destination routes (traplines) to visit patchily distributed plant resources. While the formation of traplines by individual pollinators has been studied in details, how populations of foragers exploit resources in a common area is an open question, difficult to address experimentally. We explored conditions for the emergence of resource partitioning among traplining bees using agent-based models built from experimental data of bumblebees foraging on artificial flowers. In the models, bees learn to develop routes as a consequence of feedback loops that change their probabilities of moving between flowers. While a positive reinforcement of movements leading to rewarding flowers is sufficient for the emergence of resource partitioning when flowers are evenly distributed, addition of negative reinforcement of movements leading to unrewarding flowers is necessary when flowers are patchily distributed. In environments with more complex spatial structure, the negative experiences of individual bees on flowers favour spatial segregation and efficient collective foraging.

animal behavior and cognition↗