Biology subjects

Fitzgerald, P.

Publications and source records attributed to Fitzgerald, P..

15 recordsLinked to original sources

bioRxiv2026

CD11c+ microglia promote dysfunctional T cell activation in diffuse midline glioma

Paediatric diffuse midline glioma (DMG) remains refractory to immunotherapy despite T-cell infiltration, indicating that local mechanisms actively suppress anti-tumour immunity. Using complementary genetic and orthotopic mouse models, we performed lineage-resolved profiling of the DMG immune microenvironment, resolving myeloid ontogeny and microglial states by distinguishing resident microglia from infiltrating bone marrow-derived macrophages. We identified microglia as the predominant tumour-associated myeloid population and discovered selective expansion of CD11c positive; microglia exhibiting enriched antigen-presentation and immune-regulatory transcriptional programs. Tumour-infiltrating CD4+; and CD8+; T cells exhibited chronic activation and exhaustion, while ligand receptor analysis predicted inhibitory microglia T cell communication. Pharmacological CSF1R inhibition depleted CD11c positive; microglia, attenuated antigen-presentation and immune-regulatory programs, and shifted tumour-infiltrating T cells toward a less exhausted phenotype. Together, these findings identify a previously unrecognised CD11 positive; microglia T-cell axis that establishes immune dysfunction in DMG and provide a rationale for combining myeloid- and T cell-targeted immunotherapies.

cell biology↗

bioRxiv2026

Metagenomic prediction of methane emissions in sheep using single- and multi-matrix BLUP models with taxonomic and functional microbial features

BackgroundEnteric methane emissions from ruminant livestock represent a major greenhouse gas contributor, yet identification of high- and low-emitting ruminants remains expensive and logistically challenging for agricultural methane mitigation strategies. Ruminal microbial profiles derived from long-read sequencing technology provide a potential proxy to predict methane production. The optimal bioinformatic pipelines for processing long-read metagenomic data to perform methane predictions have yet to be determined. Here we evaluated how different metagenomic analysis pipelines affect methane predictive model accuracy in grazing sheep. ResultsWe applied three bioinformatic pipelines to characterize the taxonomic and functional features of rumen microbiomes from 396 sheep. Functional abundance features were annotated from Clusters of Orthologous Genes (COG) or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The single-matrix model using COG features achieved the highest microbiability (m2 = 0.942: proportion of variance component explained by microbial features) and predictive accuracy (5-fold cross validation r = 0.609: Pearsons correlation between predicted and observed values). Both functional features outperformed all taxonomic features across all three pipelines in predictive accuracy. The multi-matrix models combined functional and taxonomic features slightly improved methane predictive accuracy across both 5-fold cross-validation and leave-one-day-out validation compared to the models using functional features alone. ConclusionsThese findings demonstrate the potential advantages of using long-read metagenomic data to predict enteric methane emissions in ruminants. COG-based functional features achieved the highest predictive accuracy among all feature types, suggesting that functional annotation of existing long-read sequences is sufficient for accurate methane prediction without requiring complementary taxonomic data.

genomics↗

bioRxiv2025

Mouse Bio-behavioral Phenotyping Using a Digital Homecage Framework for Long-timescale, High-resolution, and Multi-factor Data Collection and Analytics

MOTIVATION Long-term monitoring of behavioral and physiological processes is critical for understanding complex brain-based phenomena and disorders that develop over extended periods, such as chronic stress, circadian disorders, and metabolic conditions. While digital phenotyping is available in humans using smart devices, there remains a deficit in rodent models. To address this lack of long-term rodent phenotyping, we introduce the "Digital Homecage" (DHC) system. Our system uses accessible components and is designed for seamless integration with brain recording technologies. The Digital Homecage (DHC) allows uninterrupted, long-timescale recording of more than 20 behavioral metrics in single-housed mice, captured at sub-second resolution via video, operant interactions, and wheel-running data. This report demonstrates the DHCs capacity to enable continuous, automated tracking of behaviors like actigraphy, sleep, grooming, and food choice options over weeks, thereby opening up new avenues for longitudinal analyses of chronic conditions. Data collected reveal circadian patterns in multiple spontaneous behaviors, aligning with known nocturnal tendencies. The systems potential to facilitate groundbreaking observations on the long-term behavioral correlates of various neuropsychiatric syndromes is aided by open-source software and relatively low cost. The DHC sets the stage for community-driven innovation, potentially transforming our approach to studying complex traits of brain function and behavior in laboratory settings.

animal behavior and cognition↗

bioRxiv2024

Microenvironment Shapes Cell State, Plasticity, and Heterogeneity of Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intra-tumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the tumor microenvironment (TME) exhibits substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAF) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Together, our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLCs adaptable nature, opening possibilities for re-programming the intercellular communications that shape SCLC tumor states.

cancer biology↗

bioRxiv2023

Experienced Meditators Show Multifaceted Attention-Related Differences in Neural Activity

ObjectivesMindfulness meditation (MM) is suggested to improve attention. Research has explored this using the attentional-blink (AB) task, where stimuli are rapidly presented, and a second target stimulus (T2) is often missed if presented [~]300ms after an initial target stimulus (T1). This research showed improved task-accuracy and altered neural activity after an intensive 3-month MM retreat. We tested whether these results replicated in a community sample of typical meditators. MethodsThirty-one mindfulness meditators and 30 non-meditators completed an AB task while electroencephalography (EEG) was recorded. Between-group comparisons were made for task-accuracy, event-related potential activity (posterior-N2 and P3b), theta and alpha oscillatory phase synchronisation to stimuli presentation, and alpha-power. Primary aims examined effects within time windows reported by previous research. Additional exploratory aims assessed effects across broader time windows. ResultsNo differences were detected in task-accuracy or neural activity within our primary hypotheses. However, exploratory analyses showed posterior-N2 and theta phase synchronisation effects indicating meditators prioritised attending to T2 stimuli (p < 0.01). Meditators also showed more alpha-phase synchronisation, and lower alpha-power when processing T2 stimuli (p < 0.025). ConclusionsOur results showed multiple differences in neural activity that suggested enhanced attention in meditators. The neural activity patterns in meditators aligned with theoretical perspectives on activity associated with enhanced cognitive performance. These include enhanced alpha gating mechanisms, increased oscillatory synchronisation to stimuli, and more equal allocation of neural activity across stimuli. However, meditators did not show higher task-accuracy, nor did effects align with our primary hypotheses or previous research. PreregistrationThis study was not preregistered.

neuroscience↗

bioRxiv2022

Meditators probably show increased behaviour-monitoring related neural activity

ObjectivesMindfulness meditation is associated with better attention function. Performance monitoring and error-processing are important aspects of attention. We investigated whether experienced meditators showed different neural activity related to performance monitoring and error-processing. Previous research has produced inconsistent results. This study used more rigorous analyses and a larger sample to resolve the inconsistencies. MethodsWe used electroencephalography (EEG) to measure the error-related negativity (ERN) and error positivity (Pe) following correct and incorrect responses to a Go/Nogo task from 27 experienced meditators and 27 non-meditators. ResultsNo differences were found in the ERN (all p > 0.05). Meditators showed larger global field potentials (GFP) in the Pe after both correct responses and errors, indicating stronger neural responses (p = 0.0190, FDR-p = 0.152, np2 = 0.0951, BFincl = 2.691). This effect did not pass multiple comparison controls. However, single electrode analysis of the Pe did pass multiple comparison controls (p = 0.002, FDR-p = 0.016, np2 = 0.133, BFincl = 220.659). Meditators also showed a significantly larger Pe GFP for errors only, which would have passed multiple comparison controls, but was not a primary analysis (p = 0.0028, np2 = 0.1493, BF10 = 9.999). ConclusionsMeditation may strengthen neural responses related to performance monitoring (measured by the Pe), but not specifically to error monitoring (although measurements of the Pe after errors may be more sensitive to group differences). However, only the single electrode analysis passed multiple comparison controls, while analysis including all electrodes did not, so this conclusion remains tentative.

neuroscience↗

bioRxiv2022

Introducing RELAX (the Reduction of Electroencephalographic Artifacts): A fully automated pre-processing pipeline for cleaning EEG data - Part 1: Algorithm and Application to Oscillations

Electroencephalographic (EEG) data is typically contaminated with non-neural artifacts which can confound the results of experiments. Artifact cleaning approaches are available, but often require time-consuming manual input and significant expertise. Advancements in artifact cleaning often only address a single artifact, are only compared against a small selection of pre-existing methods, and seldom assess whether a proposed advancement improves experimental outcomes. To address these issues, we developed RELAX (the Reduction of Electroencephalographic Artifacts), an automated EEG cleaning pipeline implemented within EEGLAB that reduces all artifact types. RELAX cleans continuous data using Multiple Wiener filtering [MWF] and/or wavelet enhanced independent component analysis [wICA] applied to artifacts identified by ICLabel [wICA_ICLabel]). Several versions of RELAX were tested using three datasets containing a mix of cognitive and resting recordings (N = 213, 60 and 23 respectively). RELAX was compared against six commonly used EEG cleaning approaches across a wide range of artifact cleaning quality metrics, including signal-to-error and artifact-to-residue ratios, measures of remaining blink and muscle activity, and the amount of variance explained by experimental manipulations after cleaning. RELAX with MWF and wICA_ICLabel showed amongst the best performance for cleaning blink and muscle artifacts while still preserving neural signal. RELAX with wICA_ICLabel (and no MWF) may perform better at detecting the effect of experimental manipulations on alpha oscillations in working memory tasks. The pipeline is easy to implement in MATLAB and freely available on GitHub. Given its high cleaning performance, objectivity, and ease of use, we recommend RELAX for data cleaning across EEG studies.

neuroscience↗

bioRxiv2022

Introducing RELAX (the Reduction of Electroencephalographic Artifacts): A fully automated pre-processing pipeline for cleaning EEG data - Part 2: Application to Event-Related Potentials

Electroencephalography (EEG) is commonly used to examine neural activity time-locked to the presentation of a stimulus, referred to as an Event-Related Potential (ERP). However, EEG is also influenced by non-neural artifacts, which can confound ERP comparisons. Artifact cleaning can reduce artifacts, but often requires time-consuming manual decisions. Most automated cleaning methods require frequencies <1Hz to be filtered out of the data, so are not recommended for ERPs (which often contain <1Hz frequencies). In our companion article, we introduced RELAX (the Reduction of Electroencephalographic Artifacts), an automated and modular cleaning pipeline that reduces artifacts with Multiple Wiener Filtering (MWF) and/or wavelet enhanced independent component analysis (wICA) applied to artifact components detected with ICLabel (wICA_ICLabel) (Bailey et al., 2022). To evaluate the suitability of RELAX for data cleaning prior to ERP analysis, multiple versions of RELAX were compared to four commonly used EEG cleaning pipelines. Cleaning performance was compared across a range of artifact cleaning metrics and in the amount of variance in ERPs explained by different conditions in a Go-Nogo task. RELAX with MWF and wICA_ICLabel cleaned the data the most effectively and produced amongst the most dependable ERP estimates. RELAX with wICA_ICLabel only or MWF_only may detect experimental effects better for some ERP measures. Importantly, RELAX can high-pass filter data at 0.25Hz, so is applicable to analyses involving ERPs. The pipeline is easy to implement via EEGLAB in MATLAB and is freely available on GitHub. Given its performance, objectivity, and ease of use, we recommend RELAX for EEG data cleaning. The MATLAB code, the supplementary materials, and a simple instruction manual explaining how to implement the RELAX pipeline can be downloaded from https://github.com/NeilwBailey/RELAX/releases. A condition of use of the pipeline is that the version of the pipeline used is referred to as RELAX_[pipeline], for example "RELAX_MWF_wICA" or "RELAX_wICA_ICLabel", and that the current paper be cited, as well as the dependencies used. These dependencies are likely to include: EEGLAB (Delorme & Makeig, 2004), fieldtrip (Oostenveld et al., 2011), the MWF toolbox (Somers et al., 2019), fastICA (Hyvarinen, 1999), wICA (Castellanos & Makarov, 2006), ICLabel (Pion-Tonachini et al., 2019), and PREP (Bigdely-Shamlo et al., 2015) See our companion article for the application of RELAX to the study of oscillatory power (Bailey et al., 2022).

neuroscience↗

bioRxiv2021

No evidence for changes in GABA concentration, functional connectivity, or working memory following continuous theta burst stimulation over dorsolateral prefrontal cortex

Continuous theta burst stimulation (cTBS) is thought to reduce cortical excitability and modulate functional connectivity, possibly by altering cortical inhibition at the site of stimulation. However, most evidence comes from the motor cortex and it remains unclear whether similar effects occur following stimulation over other brain regions. We assessed whether cTBS over left dorsolateral prefrontal cortex altered gamma aminobutyric acid (GABA) concentration, functional connectivity and brain dynamics at rest, and brain activation and memory performance during a working memory task. Seventeen healthy individuals participated in a randomised, sham-controlled, cross-over experiment. Before and after either real or sham cTBS, magnetic resonance spectroscopy was obtained at rest to measure GABA concentrations. Functional magnetic resonance imaging (fMRI) was also recorded at rest and during an n-back working memory task to measure functional connectivity, regional brain activity (low-frequency fluctuations), and task-related patterns of brain activity. We could not find evidence for changes in GABA concentration (P=0.66, Bayes factor [BF10]=0.07), resting-state functional connectivity (P(FWE)>0.05), resting-state low-frequency fluctuations (P=0.88, BF10=0.04), blood-oxygen level dependent activity during the n-back task (P(FWE) >0.05), or working memory performance (P=0.13, BF10=0.05) following real or sham cTBS. Our findings add to a growing body of literature suggesting the effects of cTBS are highly variable between individuals and question the notion that cTBS is a universal inhibitory paradigm.

neuroscience↗

bioRxiv2020

CTCF is a Barrier for Totipotent-like Reprogramming

Totipotent cells have the ability of generating embryonic and extra-embryonic tissues1,2. Interestingly, a rare population of cells with totipotent-like potential was identified within ESC cultures3. These cells, known as 2 cell (2C)-like cells, arise from ESC and display similar features to those found in the totipotent 2 cell embryo2-4. However, the molecular determinants of 2C-like conversion have not been completely elucidated. Here, we show that CTCF is a barrier for 2C-like reprogramming. Indeed, forced conversion to a 2C-like state by DUX expression was associated with DNA damage at a subset of CTCF binding sites. Endogenous or DUX-induced 2C-like ESC showed decreased CTCF enrichment at known binding sites, suggesting that acquisition of a totipotent-like state is associated with a highly dynamic chromatin architecture. Accordingly, depletion of CTCF in ESC efficiently promoted spontaneous and asynchronous conversion to a totipotent-like state. This phenotypic reprogramming was reversible upon restoration of CTCF levels. Furthermore, we showed that transcriptional activation of the ZSCAN4 cluster was necessary for successful 2C-like reprogramming. In summary, we revealed the intimate relation between CTCF and totipotent-like reprogramming.

developmental biology↗

bioRxiv2019

Mindfulness meditators show enhanced working memory performance concurrent with different brain region engagement patterns during recall

Mindfulness meditation has been shown to improve working memory (WM). However, the altered brain activity underpinning these improvements is underexplored. In non-meditating individuals, modulation of theta and alpha oscillations and 1/f aperiodic activity during WM has been found to be related to WM performance. Resting theta and alpha oscillations have been found to differ in meditators, but WM related oscillation changes and 1/f aperiodic activity have not yet been examined. Additionally, WM event-related-potentials (ERPs) are modulated by attention, which is also enhanced by meditation, so these neural measures are candidates for exploring neural activity underpinning WM improvement in meditators. We recorded EEG from 29 controls and 29 meditators during a modified Sternberg WM task and compared theta, alpha, and 1/f aperiodic activity during the WM delay, and ERPs time-locked to the WM probe. Meditators responded more accurately (p = 0.008, Cohens d = 0.688). Meditators also showed different ERP distributions with earlier left-temporal activation and more frontal distribution of activity (FDR-p = 0.0186, {eta}2 = 0.0903), as well as a reduction in overall neural response strength (FDR-p = 0.0098, {eta}2 = 0.1251). While a higher proportion of meditators showed theta oscillations during the WM delay, no other differences in theta, alpha or 1/f aperiodic activity were present. These results suggest that increased WM performance in meditators might not be the result of higher amplitudes of typical WM activity, but instead due to an alternative neural strategy during WM decision making, which may allow more accurate responses with less neural activation.\n\nHighlights- Long term mindfulness meditators showed improved working memory (WM) accuracy\n- This was concurrent with earlier left temporal activation following probe stimuli\n- As well as a more frontal distribution and reduced overall neural response strength\n- No oscillation differences were present in the working memory delay period\n- Improved WM from altered neural strategy rather than increased neural activity

neuroscience↗

bioRxiv2019

A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the international mouse phenotyping consortium

Mouse knockouts allow studying gene functions. Often, multiple phenotypes are impacted when a gene is inactivated. The International Mouse Phenotyping Consortium (IPMC) has generated thousands of mouse knockouts and catalogued their phenotype data. We have acquired metabolomics data from 220 plasma samples of 30 mouse gene knockouts and corresponding wildtype mice from IMPC. To acquire comprehensive metabolomics data, we have used liquid chromatography (LC) combined with mass spectrometry (MS) for detecting polar and lipophilic compounds in an untargeted approach. We have also used targeted methods to measure bile acids, steroids and oxylipins. In addition, we have used gas chromatography GC-TOFMS for measuring primary metabolites. The metabolomics dataset reports 832 unique structurally identified metabolites from 124 chemical classes as determined by ChemRICH software. The GCMS and LCMS raw data files, intermediate and finalized data matrices, R-Scripts, annotation databases and extracted ion chromatograms are provided in this data descriptor. The dataset can be used for subsequent studies to link genetic variants with molecular mechanisms and phenotypes.\n\nData SetThe dataset is available at the MetabolomicsWorkbench repository (accession ID: ST001154)\n\nData Set Licenselicense under which the data set is made available (CC0).

bioinformatics↗

bioRxiv2018

Mindfulness meditators do not show differences in electrophysiological measures of error processing

Mindfulness meditation may improve attention and self-regulation. One component of attention and self-regulation that may allow these improvements is performance monitoring. Neural correlates of performance monitoring can be objectively measured with electroencephalogram (EEG) via the error related negativity (ERN) and error positivity (Pe). Previous research assessing the ERN and Pe in meditators has resulted in inconsistent findings; some have reported alteration in peak amplitudes from both very brief meditation practice and long-term meditation practice, while others have failed to provide evidence for differences in the ERN or Pe. However, recently developed EEG analysis techniques allow for more rigorous analyses than have been used in past investigations. The current study measured the ERN and Pe, as well as post-error alpha suppression, during a Go/Nogo task, and emotional and colour Stroop tasks. The measures were compared between 22 experienced meditators (mean of 8 years of practice) and 20 healthy controls. The results suggested no differences in the ERN, Pe, or post-error alpha suppression (all p > 0.05), even when varying multiple analysis parameters. The study showed equivalent statistical power to previous research, and > 85% power to detect medium effect sizes present in previous research. Bayes Factor analysis indicated the null hypotheses were > 3.5 more likely than any of the alternative hypotheses for the ERN or Pe. These results suggest that meditation may not alter neural activity related to error processing, despite prior research suggesting that it does.

neuroscience↗

bioRxiv2018

Mindfulness meditators show altered distributions of early and late neural activity markers of attention in a response inhibition task

Attention is a vital executive function, since other executive functions are largely dependent on it. Mindfulness meditation has been shown to enhance attention. However, the components of attention altered by meditation and the related neural activities are underexplored. In particular, the contributions of inhibitory processes and sustained attention are not well understood. Additionally, it is not clear whether improvements in attention are related to increases in the strength of typically activated brain areas, or the recruitment of additional or alternative brain areas. To address these points, 34 meditators were compared to 28 age and gender matched controls during electroencephalography (EEG) recordings of neural activity during a Go/Nogo response inhibition task. This task generates a P3 event related potential, which is related to response inhibition processes in Nogo trials, and attention processes across both trial types. Compared with controls, meditators were more accurate at responding to Go and Nogo trials. Meditators showed a more frontally distributed P3 to both Go and Nogo trials, suggesting more frontal involvement in sustained attention rather than activity specific to response inhibition. Unexpectedly, meditators also showed increased positivity over the right parietal cortex prior to visual information reaching the occipital cortex. Both results were positively related to increased accuracy across both groups. The results suggest that meditators have an increased capacity to modulate a range of neural processes in order to meet task requirements, including higher order processes, and sensory anticipation processes. This increased capacity may underlie the improved attentional function observed in mindfulness meditators.

neuroscience↗

bioRxiv2017

Demonstration of short-term plasticity in the dorsolateral prefrontal cortexwith theta burst stimulation: A TMS-EEG study

ObjectivesTo examine the effects of intermittent TBS (iTBS) and continuous TBS (cTBS) on cortical reactivity in the dorsolateral prefrontal cortex.\n\nMethods10 healthy participants were stimulated with either iTBS, cTBS or sham at F3 electrode. Single- and paired-pulse TMS and concurrent electroencephalography (EEG) were used to assess change in cortical reactivity and long-interval intracortical inhibition (LICI) via TMS-evoked potentials (TEPs) and TMS-evoked oscillations.\n\nResultsSignificant increases in N120 amplitudes (p < 0.01) were observed following iTBS over prefrontal cortex. Changes in TMS-evoked theta oscillations and LICI of theta oscillations were also observed following iTBS (increase) and cTBS (decrease). Change in LICI of theta oscillations correlated with change in N120 amplitude following TBS (r = -0.670, p = 0.001).\n\nConclusionsThis study provides preliminary evidence that TBS produces direct changes in cortical reactivity in the prefrontal cortex. Combining TBS with TMS-EEG may be a useful approach to optimise stimulation paradigms prior to the conduct of clinical trials.\n\nSignificanceTBS is able to modulate cortical reactivity and cortical inhibition in the prefrontal cortex.\n\nHighlightsO_LIEffects of iTBS and cTBS were studied in the DLPFC using TMS-EEG\nC_LIO_LIiTBS increased N120 amplitude, theta power and LICI of theta\nC_LIO_LIcTBS decreased theta power alone\nC_LI

neuroscience↗