Biology subjects

Callaghan, M.

Publications and source records attributed to Callaghan, M..

10 recordsLinked to original sources

bioRxiv2026

Forward Modelling for Magnetospinography: Systematic Comparison of Boundary Element and Finite Element Methods

Magnetospinography (MSG) enables non-invasive measurement of spinal cord electrophysiology, but accurate interpretation of these signals depends critically on forward modelling assumptions. We compared four vertebral bone representations: continuous, homogeneous-toroidal, inhomogeneous-toroidal, and MRI-derived-realistic, implemented within both boundary element method (BEM) and finite element method (FEM) frameworks. Lead-fields were computed across the full spinal cord for three orthogonal source orientations. When comparing matched model pairs, BEM and FEM produced consistent forward solutions, with median relative errors below 3.1% and median squared correlation coefficients exceeding 0.998 across all bone geometries. Vertebral bone geometry exerted a systematic and orientation-dependent influence on predicted lead fields. The dominant distinction was between continuous and segmented bone representations rather than between simplified and anatomically detailed segmented models. For left-right oriented sources, segmented geometries produced substantially higher field amplitudes (fT/nAm) than the continuous model throughout the cord (35-72%), while toroidal and MRI-derived realistic models produced comparable results across both frameworks, with median r2 exceeding 0.97 between segmented models compared to 0.67-0.85 for continuous versus segmented comparisons. Sensor placement further modulated sensitivity profiles, with posterior arrays exhibiting greater sensitivity lower down the cord, but anterior and posterior sensors showing comparable sensitivity in the cervical region.

neuroscience↗

bioRxiv2022

Nf1 deficiency accelerates mammary development and promotes luminal-basal plasticity

The tumor suppressor NF1 is a critical driver of sporadic breast cancer and NF-related breast cancers. We utilized distinct Nf1-deficient immunocompetent rat models to investigate Nf1 function in mammary development and homeostasis. Here we demonstrate that Nf1 deficiency dramatically accelerates mammary morphogenesis, alters TEB cell organization, and proliferation. Notably, we observed a shift in luminal-basal epithelial lineage commitment within Nf1-deficient lines with early tumor onset. In addition, we detected subpopulations of hybrid EMT cells (Ecad+/CK14+) within the invasive edge and stroma of Nf1-deficient tumors. Nf1 deficiency restricted luminal progenitor potential and resulted in gene expression changes associated with decreased cell adhesion and increased EMT signatures. Together our findings support a model in which Nf1 loss of function results in lineage plasticity throughout mammary morphogenesis and promotes EMT-mediated invasion. This study reveals a previously unknown role for the tumor suppressor neurofibromin in mammary homeostasis and phenotypic plasticity during breast cancer progression.

cancer biology↗

bioRxiv2022

SpheroidAnalyseR - an online platform for analysing data from 3D spheroids or organoids grown in 96-well plates

Spheroids and organoids are increasingly popular three-dimensional (3D) cell culture models. Spheroid models are more physiologically relevant to a tumour compared to two-dimensional (2D) cultures and organoids are a simplified version of an organ with similar composition. Both can be used in cell migration studies, disease modelling and drug discovery. A drawback of these models is, however, the lack of appropriate analytical tools for high throughput imaging and analysis over a time course. To address this, we have developed an R Shiny app called SpheroidAnalyseR: a simple, fast, effective open-source app that allows the analysis of spheroid or organoid size data generated in a 96-well format. SpheroidAnalyseR processes and analyses datasets of image measurements that can be obtained via a bespoke software, described herein, that automates spheroid imaging and quantification using the Nikon A1R Confocal Laser Scanning Microscope. However, templates are provided to enable users to input spheroid image measurements obtained by user-preferred methods. SpheroidAnalyseR facilitates outlier identification and removal followed by graphical visualisation of spheroid measurements across multiple predefined parameters such as time, cell-type and treatment(s). Spheroid imaging and analysis can, thus, be reduced from hours to minutes, removing the requirement for substantial manual data manipulation in a spreadsheet application. The combination of spheroid generation in 96-well ultra-low attachment microplates, imaging using our bespoke software, and analysis using SpheroidAnalyseR toolkit allows high throughput, longitudinal quantification of 3D spheroid growth whilst minimising user input and significantly improving the efficiency and reproducibility of data analysis. Our bespoke imaging software is available from https://github.com/GliomaGenomics. SpheroidAnalyseR is available at https://spheroidanalyser7.azurewebsites.net, and the source code found at https://github.com/GliomaGenomics. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/481039v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1f779fborg.highwire.dtl.DTLVardef@698103org.highwire.dtl.DTLVardef@94f252org.highwire.dtl.DTLVardef@b1180e_HPS_FORMAT_FIGEXP M_FIG Graphical abstract - SpheroidAnalyseR main steps. A summary of the process followed within the SpheroidAnalyseR app. Dotted boxes are the steps required to produce the input data for SpheroidAnalyseR. Solid boxes show the 5 main steps of SpheroidAnalyseR: Data input, Preview, Outlier removal, Merging and Plotting. C_FIG

cell biology↗

bioRxiv2022

Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity

Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and [Formula], proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1 and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the methods sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MTsat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

neuroscience↗

bioRxiv2021

Coherent waves of myelin plasticity during motor-skill learning

Motor skill learning relies on neural plasticity in the motor and limbic systems. However, the spatial and temporal dependencies of these changes--and their microstructural underpinnings--remain unclear. Eighteen healthy males received training in a computer-controlled motion game 4 times a week, for 4 weeks. Performance improvements were observed in all trained participants. Serial myelin-sensitive multiparametric mapping at 3T during this period of intensive motor skill acquisition revealed temporally and spatially distributed, performance-related myelin-sensitive microstructural changes in the grey and white matter across the corticospinal system and hippocampus. Interestingly, analysis of the trajectory of these transient changes revealed a time-shifted choreography across white and grey matter of the corticospinal system as well as with changes in the hippocampus. Crucially, in the cranial corticospinal tracts, myelin-sensitive changes during training in the posterior part of the limb of the internal capsule were of greater magnitude in lower-limb trainees compared to upper limb trainees. Motor skill learning is depended on coherent waves of plasticity within a corticospinal-hippocampal loop.

neuroscience↗

bioRxiv2021

Modulating the left inferior frontal cortex by task domain, cognitive challenge and tDCS

The left inferior frontal cortex (LIFC) is a key region for spoken language processing, but its neurocognitive architecture remains controversial. Here we assess the domain-generality vs. domain-specificity of the LIFC from behavioural, functional neuroimaging and neuromodulation data. Using concurrent fMRI and transcranial direct current stimulation (tDCS) delivered to the LIFC, we investigated how brain activity and behavioural performance are modulated by task domain (naming vs. non-naming), cognitive challenge (low vs. high), and tDCS (anodal vs. sham). The data revealed: (1) co-existence of neural signatures both common and distinct across tasks within the LIFC; (2) domain-preferential effects of task (naming); (3) significant tDCS modulations of activity in a LIFC sub-region selectively during high-challenge naming. The presence of both domain-specific and domain-general signals, and the existence of a gradient of activation where naming relied more on sub-regions within the LIFC, may help reconcile both perspectives on spoken language processing.

neuroscience↗

bioRxiv2018

Defining the toxicity limits on microbial range in a metal-contaminated aquifer

In extreme environments, toxic compounds restrict which microorganisms persist. However, in complex mixtures of inhibitory compounds, it is challenging to determine which specific compounds cause changes in abundance and prevent some microorganisms from growing. We focused on a contaminated aquifer in Oak Ridge, Tennessee, U.S.A. that has low pH and high concentrations of uranium, nitrate and many other inorganic ions. In the most contaminated wells, the microbial community is enriched in the Rhodanobacter genus. Rhodanobacter relative abundance is positively correlated with low pH and high concentrations of U, Mn, Al, Cd, Zn, Ni, Co, Ca, NO3-, Mg, Cl, SO42-, Sr, K and Ba and we sought to determine which of these correlated parameters are selective pressures that favor the growth of Rhodanobacter over other taxa. Using high-throughput cultivation, we determined that of the ions correlated high Rhodanobacter abundance, only low pH and high U, Mn, Al, Cd, Zn, Co and Ni (a) are selectively inhibitory of a sensitive Pseudomonas isolate from a background well versus a representative resistant Rhodanobacter isolate from a contaminated well, and (b) reach toxic concentrations in the most contaminated wells that can inhibit the sensitive Pseudomonas isolate. We prepared mixtures of inorganic ions representative of the most contaminated wells and verified that few other isolates aside from Rhodanobacter can tolerate these 8 parameters. These results clarify which toxic inorganic ions are causal factors that impact the microbial community at this field site and are not merely correlated with taxonomic shifts.

microbiology↗

bioRxiv2018

Dub-seq: dual-barcoded shotgun expression library sequencing for high-throughput characterization of functional traits

A major challenge in genomics is the knowledge gap between sequence and its encoded function. Gain-of-function methods based on gene overexpression are attractive avenues for phenotype-based functional screens, but are not easily applied in high-throughput across many experimental conditions. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a method that greatly increases the throughput of genome-wide overexpression assays. In Dub-seq, a shotgun expression library is cloned between dual random DNA barcodes and the precise breakpoints of DNA fragments are associated to the barcode sequences prior to performing assays. To assess the fitness of individual strains carrying these plasmids, we use DNA barcode sequencing (BarSeq), which is amenable to large-scale sample multiplexing. As a demonstration of this approach, we constructed a Dub-seq library with total Escherichia coli genomic DNA, performed 155 genome-wide fitness assays in 52 experimental conditions, and identified 813 genes with high-confidence overexpression phenotypes across 4,151 genes assayed. We show that Dub-seq data is reproducible, accurately recapitulates known biology, and identifies hundreds of novel gain-of-function phenotypes for E. coli genes, a subset of which we verified with assays of individual strains. Dub-seq provides complementary information to loss-of-function approaches such as transposon site sequencing or CRISPRi and will facilitate rapid and systematic functional characterization of microbial genomes.\n\nImportanceMeasuring the phenotypic consequences of overexpressing genes is a classic genetic approach for understanding protein function; for identifying drug targets, antibiotic and metal resistance mechanisms; and for optimizing strains for metabolic engineering. In microorganisms, these gain-of-function assays are typically done using laborious protocols with individually archived strains or in low-throughput following qualitative selection for a phenotype of interest, such as antibiotic resistance. However, many microbial genes are poorly characterized and the importance of a given gene may only be apparent under certain conditions. Therefore, more scalable approaches for gain-of-function assays are needed. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a strategy that couples systematic gene overexpression with DNA barcode sequencing for large-scale interrogation of gene fitness under many experimental conditions at low cost. Dub-seq can be applied to many microorganisms and is a valuable new tool for large-scale gene function characterization.

microbiology↗

bioRxiv2018

NF1 deficiency correlates with estrogen receptor signaling and diminished survival in breast cancer

The key negative regulatory gene of the RAS pathway, NF1, is mutated or deleted in numerous cancer types and is associated with increased cancer risk and drug resistance. Even though women with neurofibromatosis (germline NF1 mutations) have a substantially increased breast cancer risk at a young age and NF1 is commonly mutated in sporadic breast cancers, we have a limited understanding of the role of NF1 in breast cancer. Much of our understanding of the mechanisms underlying the functional loss of NF1 comes from mouse models that do not completely recapitulate the phenotypes of human NF1. We utilized CRISPR-Cas9 gene editing to create Nf1 rat models to evaluate the effect of Nf1 deficiency on tumorigenesis. The resulting Nf1 indels induced highly penetrant, aggressive mammary adenocarcinomas that express estrogen receptor and progesterone receptor. We identified distinct Nf1 isoforms that were altered during tumorigenesis.\n\nTo evaluate NF1 in human breast cancer, we analyzed genomic changes in a breast cancer dataset of 2,000 clinically annotated breast cancers. We found NF1 shallow deletions in 25% of sporadic breast cancers, which correlated with poor clinical outcome. To identify biological networks impacted by NF1 deficiency, we constructed gene co-expression networks using weighted gene correlation network analysis (WGCNA) and identified a network connected to ESR1 (estrogen receptor). Moreover, NF1-deficient cancers correlated with established RAS activation signatures. Estrogen-dependence was verified by estrogen-ablation in Nf1 rats where rapid tumor regression was observed. These results demonstrated the significant role NF1 plays in both NF1-related breast cancer and sporadic breast cancer.

cancer biology↗

bioRxiv2017

Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion

Head movements are a major source of MRI artefacts that hamper radiological assessment and computer-based morphological and functional measures of the human brain. Prospective motion correction techniques continuously update the MRI scanner based on head position information provided by an external tracking system. While prospective motion correction significantly improves data quality, strong motion artefacts may remain with large head motions or when motion takes place at sensitive times of the acquisition. Here we present a framework that allows the suspension of data acquisition when head motion is predicted to have a strong negative impact on data quality. The predictor, calculated in real-time during the acquisition, accounts for the amplitude of the signal acquired at the time of the motion, thereby offering a re-acquisition strategy more efficient than relying on head speed alone. The suspension of data acquisition is governed by the trade-off between image degradation due to motion and prolonging the scan time. This trade-off can be tuned by the user according to the desired level of image quality and the participant s tolerability. We test the framework using two motion experiments and two head coils. Significant improvements in data quality are obtained with stringent threshold values for the suspension of acquisition. Substantial reductions in motion artefact levels are also achieved with minimal prolongation of scan time. However, high levels of motion artefacts occasionally remain despite stringent thresholds with the 64-channel head coil, an effect that might be attributed to head movement in the sharp sensitivity profile of this coil.

neuroscience↗