Biology subjects

Hardy, S.

Publications and source records attributed to Hardy, S..

10 recordsLinked to original sources

bioRxiv2026

Quantifying Neural Stability: Validation of a New Brain Stability Index

Quantifying longitudinal changes in an individual's brain is central to the development of personalised neural biomarkers in neurology and psychiatry. However, existing approaches for characterising individual neurophysiological signatures focus on discrimination between people rather than the quantification of within-subject change. To address this, we introduce the Brain Stability Index (BSI), a whole-brain metric that quantifies the similarity between two longitudinal neurophysiological scans in a low-dimensional latent space, with reference to a normative magnetoencephalography (MEG) database. Using 276 open resting-state MEG datasets and matched synthetic data, we first characterise how finite test-retest reliability sets a noise floor on the BSI. We then demonstrate that the BSI is sensitive to graded changes in whole-brain neural change that extend beyond measurement variability. Finally, we show that Factor Analysis, by separating shared structure from feature-specific noise, makes the BSI more robust to measurement artefacts. Together, these findings establish the BSI as a robust, bounded measure of neural stability that is well suited to longitudinal monitoring in neurology and psychiatry.

neuroscience↗

bioRxiv2025

Intrinsic electrophysiological activity maps a latent dimension of poor sleep quality and reduced cognitive performance: a magnetoencephalography study using Cam-CAN data.

Sleep quality and cognition vary as functions of lifestyle, genetics, and health. However, poor sleep quality is prevalent, reportedly affecting approximately 38% of the adult population. Poor sleep quality is a significant risk factor for mood disorders, a predictive factor in cognitive decline in later life, and sleep disturbance is a putative precursor to severe cognitive impairment and is predictive of dementia onset. The direct relationship between these factors and intrinsic neural function is poorly understood. Integrating neurophysiology, cognition, and sleep quality to reveal latent factors would help understand the neurophysiology of sleep disturbances and their relation to cognitive performance. Here, we used data from the Cam-CAN dataset with a partial least squares (PLS) approach, producing a multivariate cross-decomposition model to map resting-state magnetoencephalography (MEG) data and cognitive/sleep scores of healthy controls (n = 490, age 18-86). Normative modelling was applied to MEG data, correcting for effects of age, sex, and handedness. We identify a significant relationship between poorer self-reported sleep quality and lower cognitive performance across multiple domains, characterised by excess low-frequency neural activity and reduced high-frequency activity, particularly in the alpha band. Moreover, globally increased low frequency and decreased alpha-beta functional connectivity - the dominant frequency channel in neural connectivity at rest across the brain - contribute significantly to this relationship. Our multivariate mapping approach enabled us to parse the electrophysiological signatures directly related to sleep quality and cognitive performance, independent of the confounding effects of age, and show that neural slowing and dysconnectivity are intrinsically linked to self-reported sleep quality and cognitive performance.

neuroscience↗

bioRxiv2025

The PTPN1 and PTPN2 phosphatases are Cooperative Regulators of Cancer Cell Immune Evasion

Immune evasion by cancer cells remains a major barrier to the success of immune checkpoint blockade (ICB). Here, we identify the phosphatases PTPN1 and PTPN2 as cooperative regulators of tumor immune resistance. Dual genetic ablation of PTPN1/2 in cancer cells enhances Type I and II interferon signaling, MHC-I and CXCL9 expression, and sensitizes tumor cells to cytotoxic T lymphocyte-mediated killing. The small-molecule inhibitor KQ791 phenocopies these effects and synergizes with anti-PD1 therapy to suppress tumor growth in murine models, including immunotherapy-refractory cancers. Mechanistically, PTPN1/2 loss augments STAT1/3/5 signaling and primes cancer cells for immunogenic cell death via IFN{gamma}/TNF-induced pathways. Moreover, PTPN1/2 inhibition enhances antigen release and cross-presentation, promoting robust antigen-specific CD8 T cell responses. These findings highlight PTPN1&2 as essential mediators of cancer immune evasion and support their inhibition as a strategy to broaden the effectiveness of immune checkpoint blockade in solid tumors.

cancer biology↗

bioRxiv2024

Linking candidate causal autoimmune variants to T cell networks using genetic and epigenetic screens in primary human T cells.

Genetic variants associated with autoimmune diseases are highly enriched within putative cis-regulatory regions of CD4+ T cells, suggesting that they alter disease risk via changes in gene regulation. However, very few genetic variants have been shown to affect T cell gene expression or function. We tested >18,000 autoimmune disease-associated variants for allele-specific expression using massively parallel reporter assays in primary human CD4+ T cells. The 545 expression-modulating variants (emVars) identified greatly enrich for likely causal variants. We provide evidence that many emVars are mediated by common upstream regulatory conduits, and that putative target genes of primary T cell emVars are highly enriched within a lymphocyte activation network. Using bulk and single-cell CRISPR-interference screens, we confirm that emVar-containing T cell cis-regulatory elements modulate both known and novel target genes that regulate T cell proliferation, providing plausible mechanisms by which these variants alter autoimmune disease risk.

genetics↗

bioRxiv2024

Predicting brain age across the adult lifespan with spontaneous oscillations and functional coupling in resting brain networks captured with magnetoencephalography

The functional repertoire of the human brain changes dramatically throughout the developmental trajectories of early life and even all the way throughout the adult lifespan into older age. Capturing this arc is important to understand healthy brain ageing, and conversely, how injury and diseased states can lead to accelerated brain ageing. Regression modelling using lifespan imaging data can reliably predict an individuals brain age based on expected arcs of ageing. One feature of brain function that is important in this respect, and understudied to date, is neural oscillations - the rhythmic fluctuations of brain activity that index neural cell assemblies and their functioning, as well as coordinating information flow around networks. Here, we analysed resting-state magnetoencephalography (MEG) recordings from 367 healthy participants aged 18 to 83, using two distinct statistical approaches to link neural oscillations & functional coupling with that of healthy ageing. Spectral power and leakage-corrected amplitude envelope correlations were calculated for each canonical frequency band from delta through gamma ranges. Spatially and spectrally consistent associations between healthy ageing and neurophysiological features were found across the applied methods, showing differential effects on neural oscillations, with decreasing amplitude of low frequencies throughout the adult lifespan, and increasing high frequency amplitude. Functional connectivity within and between resting-state brain networks mediated by alpha coupling generally decreased throughout adulthood and increased in the beta band. Predictive modelling of brain age via regression showed an age dependent prediction bias resulting in overestimating the age of younger people (<40 years old) and underestimating the age of older individuals. These findings evidence strong age-related neurophysiological changes in oscillatory activity and functional networks of the brain as measured by resting-state MEG and that cortical oscillations are moderately reliable markers for predictive modelling. For researchers in the field of predictive brain age modelling with neurophysiological data, we recommend attention is paid to predictive biases for younger and older age ranges and consider using specific models for different age brackets. Nevertheless, these results suggest brain age prediction from MEG data can be used to model arcs of ageing throughout the adult lifespan and predict accelerated ageing in pathological brain states.

neuroscience↗

bioRxiv2023

Development and Evaluation of a Machine Learning Recursive Partitioning Decision Tree Algorithm to Optimize Urinalysis Parameters to Predict Urine Culture Positivity

PittUDT, a recursive partitioning decision tree algorithm for predicting urine culture (UC) positivity based on macroscopic and microscopic urinalysis (UA) parameters, may significantly decrease the number of unnecessary UC. The reflex algorithm derivation included 38,361 paired UA and UC cases; the average patient age was 57.4 years and 70% of samples were from female patients. Receiver operating characteristic (ROC) analysis identified urine WBCs, leukocyte esterase, and bacteria as the best predictors of UC positivity, with area under the ROC curve of 0.79, 0.78, and 0.77, respectively. The test data comprised 9,773 cases, of which 2,571 (26.3%) had a positive UC result. Using the held-out test data set, the PittUDT algorithm met the pre-specified targets of a 30-60% total negative proportion (true negative plus false negative predictions) with a negative predictive value above 90%. These data show that a rule-based algorithm trained on UA data has adequate predictive ability for triaging urine specimens by identifying low risk urine specimens, which are unlikely to grow pathogenic organisms, with a false-negative proportion under 5%. Our study demonstrates the feasibility and performance of using a supervised machine learning approach to develop a human readable machine learning model to optimize UA parameters in a reflex protocol that can be deployed across multiple hospital sites and settings. Our work supports a UA reflex to UC protocol that has the capacity to optimize UA parameters to predict UC positivity and improve antimicrobial stewardship and UC utilization, a potential avenue for cost savings.

microbiology↗

bioRxiv2022

Spatial and social structure of rewilded laboratory mice

Social behavior and social organization have major influences on individual health and fitness. Yet, biomedical research focuses on studying a few genotypes under impoverished social conditions. Understanding how lab conditions have modified social organizations of model organisms, such as lab mice, relative to natural populations is a missing link between socioecology and biomedical science. Using a common garden design, we describe the formation of social structure in the well-studied laboratory mouse strain, C57BL/6J, in replicated mixed-sex populations over 10-day trials compared to control trials with wild-derived outbred house mice in outdoor field enclosures. We focus on three key features of mouse social systems: (i) territory establishment in males, (ii) female social relationships, and (iii) the social networks formed by the populations. Male territorial behaviors were similar but muted in C57 compared to wild-derived mice. Female C57 sharply differed from wild-derived females, showing little social bias toward cage mates and exploring substantially more of the enclosures compared to all other groups. Female behavior consistently generated denser social networks in C57 than in wild-derived mice. The repeatable societies formed under field conditions highlights opportunities to experimentally study the interplay between society and individual biology using model organisms.

animal behavior and cognition↗

bioRxiv2022

EXONIZATION BY THE EMERGENCE OF A CLEAVAGE-POLYADENYLATION SITE

Exonization is the evolutionary process of recruitment of new exonic regions from previously intronic regions. It is a major contributor to the increased complexity of alternative splicing. Here, we explore exonization mediated by the emergence of a novel cleavage-polyadenylation site in an intron. In Xenopus laevis, the tpm1 gene, which encodes muscular tropomyosin, contains alternative terminal exons. In adult muscles and embryonic hearts, exon 9A is joined to the terminal exon 9B. In embryonic somites, it is joined to the exonic region 9, which is transcribed from the intron immediately downstream of exon 9A. Consequently, exon 9A is either an internal exon when ligated to exon 9B, or a part of a terminal exon along with region 9. We show here that region 9 is present only in amphibians and coelacanths. This suggests that it emerged in sarcopterygians and was lost in amniotes. We used antisense morpholino oligonucleotides to mask the regions of tpm1 pre-mRNA that potentially regulate the inclusion of exon 9A9. This revealed that the definition of exon 9A9 relies on a weak cleavage-polyadenylation site and an intronic enhancer, but is independent of the 3 splice site. We demonstrate that RNAs containing exon 9B are toxic in somites. This may have contributed to the evolutionary pressure that led to the exonization of region 9 in sarcopterygians. These findings reveal the emergence of a novel cleavage-polyadenylation site that avoids the accumulation of a toxic RNA as a novel mechanism for exonization-mediated diversification of terminal exons.

evolutionary biology↗

bioRxiv2021

GraviKit: an easy-to-implement microscope add-on for observation of gravitation dependent processes

One of the most important environmental cues for living organisms is gravity and many developmental processes depend on it. However, when it comes to light microscopy, a majority of studies on these processes work with their objects of interest placed perpendicular to their natural orientation. One reason for that is probably that light microscopes with the required horizontal beampath are either costly or require advanced technical skills. To circumvent these obstacles and make imaging of gravity-dependent processes with a horizontal beampath possible for any lab we developed GraviKit. It converts a standard inverted research microscope into an imaging device with a horizontal beampath with a stage that rotates the sample around the optical axis. Like this, the direction of gravity can be freely chosen during an imaging experiment. The system is easy to implement and suitable for multi-user environments.

developmental biology↗

bioRxiv2020

ARL15 modulates magnesium homeostasis through N-glycosylation of CNNMs

Cyclin M (CNNM1-4) proteins maintain cellular and body magnesium (Mg2+) homeostasis. Using various biochemical approaches, we have identified members of the CNNM family as direct interacting partners of ADP-ribosylation factor-like protein 15 (ARL15), a small GTP-binding protein. ARL15 interacts with CNNMs at their carboxyl-terminal conserved cystathionine-{beta}-synthase (CBS) domains. In silico modeling of the interaction using the reported structures of both CNNM2 and ARL15 supports that the small GTPase specifically binds the CBS1 domain. Immunocytochemical experiments demonstrate that CNNM2 and ARL15 co-localize in the kidney, with both proteins showing subcellular localization in the Golgi-apparatus. Most importantly, we found that ARL15 is required for forming complex N-glycosylation of CNNMs. Overexpression of ARL15 promotes complex N-glycosylation of CNNM3. Mg2+ uptake experiments with a stable isotope demonstrate that there is a significant increase of 25Mg2+ uptake upon knockdown of ARL15 in multiple kidney cancer cell lines. Altogether, our results establish ARL15 as a novel negative regulator of Mg2+ transport by promoting the complex N-glycosylation of CNNMs.

biochemistry↗