Biology subjects

Gow, A.

Publications and source records attributed to Gow, A..

5 recordsLinked to original sources

bioRxiv2026

Wildfire emitted particulate matter induces ovarian hyperandrogenism through aryl hydrocarbon receptor activation

Wildfires have become more frequent and intense worldwide. Wildfire emitted particulate matter (WFPM) can be more toxic than urban background PM due to its greater content of nanoscale size (WFPM0.1) and presence of more polar organic compounds, including polycyclic aromatic hydrocarbons (PAHs). While exposure to WFPM has been linked to cardiovascular and respiratory diseases, its impact on female reproduction remains elusive. Here, we used an in vivo mouse intratracheal exposure model and a 3D ovarian follicle culture system, together with molecular, transcriptomic, and computational approaches, to examine the female reproductive effects of lab-synthesized (LS-WFPM0.1) and real-world Canadian WFPM0.1 (C-WFPM0.1), collected from the New York City and New Jersey metropolitan area during the June 2023 wildfire events. Intratracheal exposure to environmentally relevant dose of LS-WFPM0.1 disrupted mouse estrous cycles and elevated serum concentrations of estradiol and testosterone. RT-qPCR and single-follicle RNA-sequencing (RNA-seq) analysis revealed altered steroidogenic genes, transcriptomic changes, and activation of aryl hydrocarbon receptor (AhR) in antral follicles from mice treated with LS-WFPM0.1. LS-WFPM0.1 consistently increased testosterone secretion and stimulated genes related to androgen synthesis and AhR in vitro. Single-follicle and single-oocyte RNA-seq analysis identified differentially expressed genes related to inflammation in somatic cells and mitochondrial respiratory chain in oocytes. Both C-WFPM0.1 and benzo[a]pyrene, a high-molecular-weight PAH, reproduced these ovarian defects. Mechanistically, AhR inhibition reversed hyperandrogenism induced by WFPM0.1. Together, our findings suggest that WFPM0.1, an increasingly pervasive environmental exposure, adversely impacts female reproductive functions by disrupting ovarian steroidogenesis and inducing hyperandrogenism through AhR activation, highlighting an urgent unmet need for further mechanistic studies and epidemiological investigations to define the reproductive risks of wildfire smoke exposure in human populations.

pharmacology and toxicology↗

bioRxiv2025

MyeliMetric: A Python-Based Toolbox for Standardized G-ratio Analysis of Axon-Myelin Integrity

The g-ratio, defined as the ratio of an axons diameter to the total fiber diameter (axon plus myelin), is a key metric for assessing myelin integrity and axonal conduction velocity in both the central and peripheral nervous systems. Deviations from the physiological range often signal underlying pathology. Despite its diagnostic importance, there is currently no standardized, open-source tool for g-ratio analysis from post-segmented electron microscopy images. To address this gap, we developed MyeliMetric, a Python-based, user-friendly toolbox that streamlines g-ratio data preprocessing and integrates biologically informed validation, requiring minimal statistical expertise to operate without introducing common analytical errors. It is built on the principle that g-ratios exhibit relative consistency across varying axon diameters in healthy conditions. To rigorously assess this relationship, MyeliMetric implements a binning strategy that groups axons into biologically relevant diameter cohorts, enabling the detection of size-dependent deviations in g-ratio distributions. This approach addresses common limitations in conventional analyses, including insufficient sampling, pseudo-replication, and artifacts such as misleading regression slopes. Validation using both synthetic and published datasets from rodent models of demyelination demonstrated the tools accuracy, reproducibility, and biological relevance. Synthetic data yielded expected outcomes, and in experimental models, MyeliMetric reliably detected reductions in myelin thickness through g-ratio shifts while minimizing artifacts, thereby providing biologically meaningful insights. It is available on GitHub: https://github.com/Intakhar-Ahmad/NeuroMyelin-G-Ratio-Analysis-Toolkit

neuroscience↗

bioRxiv2025

Demystifying The Myelin g ratio: Its Origin, Derivation and Interpretation

Most studies involving myelin g ratios over the past 120 years assume this metric enumerates changes in myelin thickness (larger g ratio = thinner myelin) with axon or fiber diameter. And, moreover, such changes are directly correlated with internodal function (conduction velocity). However, such assumptions are warranted only in the absence of experimental errors and artifacts (i.e. under theoretical conditions). In reality, g ratios easily under- or overestimate rates of change exceeding 10%, especially for small caliber fibers. Typical analyses of myelin internodes rely on an explicit mathematical model, [Formula], where DA is axon diameter and DF is fiber diameter (myelin plus axon). Shown recently and herein, this model approximates normal physiological conditions only when the axon-fiber diameter relation is directly proportional, whence it is concordant with the axomyelin unit model. However, in transient or non-steady states (development/aging, disease or myelin plasticity) with linear but not directly proportional relations, g ratios poorly describe myelin structure. Acceptance of this counterintuitive assertion is predicated on a detailed understanding of the g ratio - origins, properties and the biology represented - heretofore uncharted. In light of such g ratio limitations, more general and reliable metrics are proposed, the myelin gc ratio and the g cline.

neuroscience↗

bioRxiv2024

A Statistically-Robust Model Of The Axomyelin Unit Under Normal Physiologic Conditions With Application To Disease States

Despite tremendous progress in characterizing the myriad cellular structures in the nervous system, a full appreciation of the interdependent and intricate interactions between these structures is as yet unfulfilled. Indeed, few more so than the interaction between the myelin internode and its ensheathed axon. More than a half-century after the ultrastructural characterization of this axomyelin unit, we lack a reliable understanding of the physiological properties, the significance and consequence of pathobiological processes, and the means to gauge success or failure of interventions designed to mitigate disease. Herein, we highlight shortcomings in the most common statistical procedures used to characterize the axomyelin unit, with particular emphasis on the underlying principles of simple linear regression. These shortcomings lead to insensitive detection and/or ambiguous interpretation of normal physiology, disease mechanisms and remedial methodologies. To address these problems, we syndicate insights from early seminal myelin studies and use a statistical model of the axomyelin unit that is established in the accompanying article. Herein, we develop and demonstrate a statistically-robust analysis pipeline with which to examine and interpret axomyelin physiology and pathobiology in two disease states, experimental autoimmune encephalomyelitis and the rumpshaker mouse model of leukodystrophy. On a cautionary note, our pipeline is a relatively simple and streamlined approach that is not necessarily a panacea for all g ratio analyses. Rather, it approximates a minimum effort needed to elucidate departures from normal physiology and to determine if more comprehensive studies may lead to deeper insights.

neuroscience↗

bioRxiv2024

Understanding The Myelin g ratio From First Principles, Its Derivation, Uses And Artifacts

In light of the increasing importance for measuring myelin g ratios - the ratio of axon-to-fiber (axon + myelin) diameters in myelin internodes - to understand normal physiology, disease states, repair mechanisms and myelin plasticity, there is urgent need to minimize processing and statistical artifacts in current methodologies. Unfortunately, many contemporary studies fall prey to a variety of artifacts, which reduce study outcome robustness and slow development of novel therapeutics. Underlying causes stem from a lack of understanding of the myelin g ratio, which has persisted more than a century. An extended exploratory data analysis from first principles (the axon-fiber diameter relation) is presented herein and has major consequences for interpreting published g ratio studies. Indeed, a model of the myelin internode naturally emerges because of (1) the strong positive correlation between axon and fiber diameters and (2) the demonstration that the relation between these variables is one of direct proportionality. From this model, a robust framework for data analysis, interpretation and understanding allows specific predictions about myelin internode structure under normal physiological conditions. Further, the model establishes that a regression fit to g ratio plots has zero slope, and it identifies the underlying causes of several data processing artifacts that can be mitigated by plotting g ratios against fiber diameter (not axon diameter). Hypothesis testing can then be used for extending the model and evaluating myelin internodal properties under pathophysiological conditions (accompanying article). For without a statistical model as anchor, hypothesis testing is aimless like a rudderless ship on the ocean.

neuroscience↗