Biology subjects

Albers, D.

Publications and source records attributed to Albers, D..

5 recordsLinked to original sources

bioRxiv2025

Trypstatin as a Novel TMPRSS2 Inhibitor with Broad-Spectrum 1 Efficacy Against Corona and Influenza Viruses

Respiratory viruses, such as SARS-CoV-2 and influenza, exploit host proteases like TMPRSS2 for entry, making TMPRSS2 a prime antiviral target. Here, we report the identification and characterization of Trypstatin, a 61-amino acid Kunitz-type protease inhibitor derived from human hemofiltrate. Trypstatin inhibits TMPRSS2 and related proteases, with IC50 values in the nanomolar range, comparable to the small molecule inhibitor camostat mesylate. In vitro assays demonstrated that Trypstatin effectively blocks spike-driven entry of SARS-CoV-2, SARS-CoV-1, MERS-CoV, and hCoV-NL63, as well as hemagglutinin-mediated entry of influenza A and B viruses. In primary human airway epithelial cultures, Trypstatin significantly reduced SARS-CoV-2 replication and retained activity in the presence of airway mucus. In vivo, intranasal administration of Trypstatin to SARS-CoV-2-infected Syrian hamsters reduced viral titers and alleviated clinical symptoms. These findings highlight Trypstatins potential as a broad-spectrum antiviral agent against TMPRSS2-dependent respiratory viruses. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/632953v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1b90566org.highwire.dtl.DTLVardef@117293org.highwire.dtl.DTLVardef@1794959org.highwire.dtl.DTLVardef@1be9090_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

GPR15LG binds CXCR4 and synergistically modulates CXCL12-induced cell signaling and migration

GPR15LG, a chemokine-like ligand for the G-protein coupled receptor 15 (GPR15), is abundantly expressed in the gastrointestinal mucosa and inflamed skin. Emerging evidence suggests its involvement in inflammatory disorders and cancers. This study investigates the effects of GPR15LG on the signaling and downstream functions of C-X-C chemokine receptor type 4 (CXCR4), which plays a critical role in immune cell trafficking and cancer metastasis. The results demonstrate that GPR15LG binds to the orthosteric site of CXCR4, modulating downstream signaling in a context-dependent manner. Specifically, GPR15LG enhances CXCL12-mediated CXCR4 signaling synergistically, promoting wound healing and cell migration across various cell types, including CD4+ T cells and cancer cells. These findings underscore the role of GPR15LG in inflammation and metastasis, offering potential therapeutic avenues for CXCR4-mediated diseases. TeaserGPR15LG binds CXCR4 thereby modulating CXCL12/CXCR4 signaling and immune and cancer cell trafficking.

cell biology↗

bioRxiv2022

Hypothesis-driven modeling of the human lung-ventilator system for Acute Respiratory Distress Syndrome research

Mechanical ventilation is an essential tool in the management of Acute Respiratory Distress Syndrome (ARDS), but it exposes patients to the risk of ventilator-induced lung injury (VILI). The human lung-ventilator system (LVS) involves the interaction of complex anatomy with a mechanical apparatus, which limits the achievable flexibility and fidelity needed to provide individualized clinical support by modeling lung processes. This work proposes a hypothesis-driven strategy for LVS modeling, in which robust personalization is achieved using a pre-defined parameter basis in a non-physiological model. Model inversion, here via windowed data assimilation, forges observed waveforms into interpretable parameter values that characterize the data rather than quantifying physiological processes. Inference experiments performed on human pressure waveform data indicate the flexible model accurately estimates parameters for a variety of breath types, including breaths of markedly dyssynchronous LVSs. Parameter estimates generate static characterizations of the data that are 50-70% more accurate than breath-wise single-compartment model estimates. They also retain sufficient information to distinguish between the types of breath they represent. However, the fidelity and interpetability of model characterizations are tied to parameter definitions and model resolution. These additional factors must be considered in conjunction with the objectives of specific applications, such as identifying and tracking the development of human VILI.

bioinformatics↗

bioRxiv2020

Delay-Induced Uncertainty in Physiological Systems

AO_SCPLOWBSTRACTC_SCPLOWMedical practice in the intensive care unit is based on the supposition that physiological systems such as the human glucose-insulin system are reliabile. Reliability of dynamical systems refers to response to perturbation: A dynamical system is reliable if it behaves predictably following a perturbation. Here, we demonstrate that reliability fails for an archetypal physiological model, the Ultradian glucose-insulin model. Reliability failure arises because of the presence of delay. Using the theory of rank one maps from smooth dynamical systems, we precisely explain the nature of the resulting delay-induced uncertainty (DIU). We develop a recipe one may use to diagnose DIU in a general dynamical system. Guided by this recipe, we analyze DIU emergence first in a classical linear shear flow model and then in the Ultradian model. Our results potentially apply to a broad class of physiological systems that involve delay.

physiology↗

bioRxiv2020

Estimating intracranial pressure via low-dimensional models: toward a practical tool for clinical decision support at multi-hour timescales

AbstractBroad clinical application of non-invasive intracranial pressure (ICP) monitoring using computational models requires a method of modeling ICP on the basis of easily measured patient data such as radial or brachial arterial blood pressure (ABP). These models may be highly complex, rendering them too slow for clinical and operational use, or may rely on data that is not consistently available. Coupling these models to an upstream vasculature component model decreases data requirements. For the purposes of clinical decision support at multi-hour timescales, two natural choices for model development are to increase intracranial model complexity or to include feedback mechanisms between ICP and vascular model components. We compare the performance of these two approaches by evaluating model estimates against observed ICP in the case of a slow hypertensive event from a publically available dataset. The simpler model with bi-directional feedback requires minimal identifiability and is sufficiently accurate over these timescales, while a more complex is difficult and expensive to identify well enough to be accurate. Furthermore, the bi-directional simple model operates orders of magnitude faster than the more anatomically accurate model when driven by high-resolution ABP. It may also be configured to use lower resolution ABP summary data that is consistently clinically available. The simpler models are fast enough to support future developments such as patient-specific parametrization and assimilation of other clinical data streams which are illustrated during the case of a complex ICP regime for a different patient. We present model comparisons to highlight the advantages of the incorporated simple model and its possible predictive power with further optimization.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioengineering↗