Biology subjects

Ferrara, N.

Publications and source records attributed to Ferrara, N..

3 recordsLinked to original sources

bioRxiv2026

The LIF-LIFR Axis Promotes Liver Regeneration via Modulation of Angiogenesis and HGF Release from LSECs

Liver sinusoidal endothelial cells (LSECs) play essential roles in liver regeneration after injury, but the underlying mechanisms remain incompletely defined. Here we report that leukemia inhibitory factor (LIF), which is rapidly induced after liver injury, acts as a key regulator of LSECs-driven liver regeneration through interaction with LSECs-enriched LIF receptor (LIFR). LIF directly stimulates LSECs proliferation and induces hepatocyte growth factor (HGF) release in a dose-dependent manner via LIFR signaling in LSECs, thereby indirectly promoting hepatocyte proliferation. Systemic LIF neutralization or endothelial cells (ECs)-specific Lifr loss impairs liver regeneration, whereas low-titer AAV-mediated LIF expression increases vascular density, elevates circulating HGF, and improves early liver recovery after partial hepatectomy (PHx) in mice. Together, these findings establish LIF-LIFR as a previously unrecognized endothelial axis to promote hepatocyte proliferation and suggest potential therapeutic strategies to enhance liver repair in patients. HighlightsO_LILIF is upregulated after liver injury and LIF neutralization impairs liver recovery. C_LIO_LILIFR displays the highest expression in ECs; endothelial-specific Lifr deletion delays liver regeneration after injury. C_LIO_LILIF mediates a positive feedback loop including LSECs proliferation as well as HGF release via LIFR pathway. C_LIO_LILIF overexpression increases liver-to-body weight ratio in a dose-dependent manner and accelerates liver regeneration at early stage. C_LI Abstract Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/707802v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@13b42feorg.highwire.dtl.DTLVardef@1ab6390org.highwire.dtl.DTLVardef@115c157org.highwire.dtl.DTLVardef@1486993_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

Vascular tortuosity quantification as an outcome metric of the oxygen-induced retinopathy model of ischemic retinopathy

The murine oxygen-induced retinopathy (OIR) model is one of the most widely used animal models of ischemic retinopathy, mimicking hallmark pathophysiology of initial vaso-obliteration (VO) resulting in ischemia that drives neovascularization (NV). In addition to NV and VO, human ischemic retinopathies including Retinopathy of Prematurity (ROP) are characterized by increased vascular tortuosity. Vascular tortuosity is an indicator of disease severity, need to treat, and treatment response in ROP. Current literature investigating novel therapeutics in the OIR model report their effects on NV and VO, but no standardized quantification of vascular tortuosity exists to date despite this metrics relevance to human disease in clinics. The current proof-of-concept study applied a computer-based image analysis algorithm capable of calculating standardized measurements of vascular tortuosity. Quantification of vascular tortuosity correlated with disease activity in OIR analogously to that observed in infants with ROP. Treatment of OIR mice with anti-Vascular Endothelial Growth Factor (aflibercept) rescued vascular tortuosity in the model. Altogether, these data demonstrated that vascular tortuosity is a quantifiable feature of the OIR model and may be used as an outcome measurement in future studies investigating new treatment modalities for retinal ischemia.

neuroscience↗

bioRxiv2021

Comberons from single cell transcriptomics in endothelial cells

VEGF inhibitor drugs have been successful, especially in ophthalmology, but not all patients respond to them. Combinations of drugs are likely to be needed for more effective therapies of angiogenesis-related diseases. In this paper we describe naturally occurring combinations of receptors in endothelial cells that might help to understand how cells communicate and to identify targets for drug combinations. We also develop and share a new software tool called DECNEO to identify them. Single-cell gene expression data are used to identify a set of co-expressed endothelial cell receptors, conserved among species (mice and humans) and enriched, within a network, of connections to up-regulated genes. This set includes several receptors previously shown to play a role in angiogenesis. Multiple statistical tests from large datasets, including an independent validation set, support the reproducibility, evolutionary conservation and role in angiogenesis of these naturally occurring combinations of receptors. We also show tissue-specific combinations and, in the case of choroid endothelial cells, consistency with both well-established and recent experimental findings, presented in a separate paper. The results and methods presented here advance the understanding of signaling to endothelial cells. The methods are generally applicable to the decoding of intercellular combinations of signals.

systems biology↗