bioRxiv Science⌕ Search

Biology subjects

Woodworth, G. F.

Publications and source records attributed to Woodworth, G. F..

2 recordsLinked to original sources

Polarization Increases Nuclear Stiffness in Macrophages Despite Reduction in Lamin A/C Levels

Macrophages are innate immune cells contributing to tissue homeostasis and various pathologies. Signals from their environment can lead macrophages to adapt distinct functional phenotypes, a process called polarization. Because macrophages have been previously shown to degrade the nuclear envelope proteins lamin A/C upon pro-inflammatory polarization, and lamins are considered key determinants of nuclear deformability, we aimed to address the effect of pro-inflammatory stimulation on nuclear mechanics. We present the surprising finding that polarized bone marrow-derived macrophages have less deformable nuclei than unpolarized macrophages, despite their reduced lamin A/C levels. Furthermore, pro-inflammatory macrophages exhibited altered chromatin dynamics relative to unpolarized macrophages, including redistribution of trimethylated histone H3K9 (H3K9me3) from the nuclear periphery to the interior and increased chromatin compaction. Our findings suggest a model in which pro-inflammatory stimulation of macrophages induces chromatin changes that drive nuclear stiffening, and that in these cells, chromatin, rather than the nuclear lamina, is the major driver for resisting nuclear deformation. These findings may have functional relevance for the physiological function of polarized macrophages, as the mechanical properties of the nucleus can influence how these cells adapt and respond to their environments in the context of cell migration or inflammatory disease pathologies.

cell biology↗

Data-driven feedback augments ultrasound nanotheranostics in brain tumors

The blood-brain barrier (BBB) renders the delivery of nanomedicine in the brain ineffective and the detection of circulating disease-related DNA from the brain unreliable. Here, we show that the acoustic emission content of focused ultrasound-controlled microbubble dynamics (MB-FUS) incorporates precursor signals that allow large-data models to predict sonication regimens for safe and effective BBB opening. Crucially, closed-loop MB-FUS controller augmented by machine learning (ML-CL) expands the treatment window (4-fold), as compared to conventional controllers, by persistently and proactively maximizing the BBB permeability while preventing tissue damage. By successfully scaling up from mice to rats and from healthy to diseased brains (glioma), ML-CL rendered the BBB permeable to large nanoparticles and markedly improved the release and detection of tumor DNA in plasma. Together, our findings reveal the potential of data-driven feedback to support the development of next-generation AI-powered ultrasound systems for safe, robust, and efficient nanotheranostic targeting of brain diseases.

bioengineering↗