Biology subjects

Day, P.

Publications and source records attributed to Day, P..

4 recordsLinked to original sources

bioRxiv2026

Ultrasound-Based Hemodynamic Force Trajectories in a Murine Model of Reversible Pressure Overload

Hemodynamic forces (HDF) quantify intraventricular pressure gradients as integrated vectors derived from myocardial motion and blood flow, providing a sensitive marker of left ventricular pump efficiency beyond conventional metrics such as ejection fraction or strain. Although HDF analysis has been clinically validated in heart failure, it remains underexplored in preclinical models. To determine whether HDF metrics derived from high-resolution murine echocardiography can sensitively track cardiac dysfunction and predict functional recovery, male mice (n = 8) underwent serial echocardiography at baseline, after transverse aortic constriction (TAC), and four weeks after aortic debanding (deTAC). Left ventricular function and interval-specific HDF components were quantified, including longitudinal and transverse forces over predefined systolic and diastolic windows. Longitudinal interval-based parameters emerged as sensitive, integrative markers of LV dysfunction after TAC and DeTAC. Notably, a novel systolic acceleration-to-relaxation longitudinal HDF ratio showed the strongest associations with pressure overload and subsequent functional recovery (baseline vs TAC: p < 0.001; TAC vs deTAC: p < 0.001; baseline vs deTAC: p = 0.043). In contrast, diastolic HDF indices, including the previously proposed longitudinal e-wave ratio, did not significantly differentiate between time points. Transverse HDF over the systolic impulse interval further demonstrated potential for predicting post-surgical recovery following unloading. These findings support systolic HDF metrics, particularly longitudinal and transverse interval-based parameters, as sensitive integrative markers of LV dysfunction and reverse remodeling in preclinical pressure-overload models, and highlight their translational relevance for echocardiography-based HDF analysis. Key pointsHemodynamic force (HDF) analysis evaluate intraventricular pressure gradients as integrated vectors of myocardial motion and blood flow, providing complementary markers of pump (in)efficiency beyond ejection fraction or strain. High-resolution murine echocardiography enables robust derivation of interval-specific HDF metrics. Systolic HDF metrics, particularly transverse components during impulse intervals showed potential for predicting recovery. Systolic HDF reflect key changes in force generation and intraventricular flow during pressure overload, allowing early detection of maladaptive remodeling and treatment response, with strong translational potential for non-invasive risk stratification in aortic stenosis patients.

physiology↗

bioRxiv2023

Exposing the molecular heterogeneity of glycosylated biotherapeutics

Glycosylated biotherapeutics are an emerging class of drugs with high molecular heterogeneity, which can affect their safety and efficacy. Characterizing this heterogeneity is crucial for drug development and quality assessment, but existing methods are limited in their ability to analyze intact glycoproteins. Here, we present a new approach to glycoform fingerprinting that uses proton-transfer charge-reduction with gas-phase fractionation to analyze intact glycoproteins by mass spectrometry. The method provides a detailed landscape of the intact molecular weights present in biotherapeutic protein preparations in a single experiment and offers insights into glycoform composition when coupled with a suitable bioinformatic strategy. We tested the approach on various biotherapeutic molecules, including Fc-fusion, VHH-fusion, and peptide-bound MHC class II complexes to demonstrate efficacy in measuring the proteoform-level diversity of biotherapeutics. Notably, we inferred the glycoform distribution for hundreds of molecular weights for the eight-times glycosylated fusion drug IL22-Fc, enabling correlations between glycoform sub-populations and the drugs pharmacological properties. Our method is broadly applicable and provides a powerful tool to assess the molecular heterogeneity of emerging biotherapeutics.

biochemistry↗

bioRxiv2019

The role and robustness of the Gini coefficient as an unbiased tool for the selection of Gini genes for normalising expression profiling data

We recently introduced the Gini coefficient (GC) for assessing the expression variation of a particular gene in a dataset, as a means of selecting improved reference genes over the cohort ( housekeeping genes) typically used for normalisation in expression profiling studies. Those genes (transcripts) that we determined to be useable as reference genes differed greatly from previous suggestions based on hypothesis-driven approaches. A limitation of this initial study is that a single (albeit large) dataset was employed for both tissues and cell lines.\n\nWe here extend this analysis to encompass seven other large datasets. Although their absolute values differ a little, the Gini values and median expression levels of the various genes are well correlated with each other between the various cell line datasets, implying that our original choice of the more ubiquitously expressed low-Gini-coefficient genes was indeed sound. In tissues, the Gini values and median expression levels of genes showed a greater variation, with the GC of genes changing with the number and types of tissues in the data sets. In all data sets, regardless of whether this was derived from tissues or cell lines, we also show that the GC is a robust measure of gene expression stability. Using the GC as a measure of expression stability we illustrate its utility to find tissue- and cell line-optimised housekeeping genes without any prior bias, that again include only a small number of previously reported housekeeping genes. We also independently confirmed this experimentally using RT-qPCR with 40 candidate GC genes in a panel of 10 cell lines. These were termed the Gini Genes.\n\nIn many cases, the variation in the expression levels of classical reference genes is really quite huge (e.g. 44 fold for GAPDH in one data set), suggesting that the cure (of using them as normalising genes) may in some cases be worse than the disease (of not doing so). We recommend the present data-driven approach for the selection of reference genes by using the easy-to-calculate and robust GC.

molecular biology↗

bioRxiv2019

Involvement of multiple influx and efflux transporters in the accumulation of cationic fluorescent dyes by Escherichia coli

We used high-throughput flow cytometry to assess the ability of individual gene knockout strains of E coli to take up two membrane-permeable, cationic fluorescent dyes, viz the carbocyanine diS-C3(5) and the DNA dye SYBR Green. Individual strains showed a large range of distributions of uptake. The range of modal steady-state uptakes for the carbocyanine between the different strains was 36-fold. Knockouts of the ATP synthase - and {beta}-subunits greatly inhibited uptake, implying that most uptake was ATP-driven rather than being driven by say a membrane potential. Dozens of transporters changed the steady-state uptake of the dye by more than 50% with respect to that of the wild type, in both directions (increased or decreased); knockouts in known influx and efflux transporters behaved as expected, giving confidence in the general strategy. Many of the knockouts with the most reduced uptake were transporter genes of unknown function ( y-genes). Similarly, several overexpression variants in the ASKA collection had the anticipated, opposite effects. Similar findings were made with SYBR Green (the range being some 69-fold), though despite it too containing a benzimidazole motif there was negligible correlation between its uptake and that of the carbocyanine when compared across the various strains. Overall, we conclude that the uptake of these dyes may be catalysed by a great many transporters of possibly broad and presently unknown specificity. This casts serious doubt upon the use of such dyes as quantitative stains for representing either bioenergetic parameters or the amount of cellular DNA in unfixed cells (in vivo). By contrast, it opens up their potential use as transporter assay substrates in high-throughput screening.

microbiology↗