Alexandra Pacureanu

The paper optimizes a sample preparation workflow for array tomography volume EM of marine larvae, identifying effective fixation and staining methods.

This paper demonstrates that critical point drying enhances X-ray phase contrast in mouse brain tissue, improving imaging resolution and compatibility with further processing techniques.

The paper presents a high-resolution 3D X-ray nanotomography dataset of the pygmy squid Idiosepius hallami, mapping large-scale neural connectivity.

The paper uses synchrotron X-ray nanotomography to link subcellular anatomy to odor response diversity in mouse olfactory bulb projection neurons.

The paper examines fibre organisation in white matter across species and anatomical scales using diffusion MRI and x-ray synchrotron imaging, finding common structural principles despite species-specific variations.

This paper introduces a self-supervised image restoration method for X-ray holographic nanotomography to improve resolution, contrast, and speed in neuronal imaging.

The paper reconstructs and analyzes the female Drosophila ventral nerve cord connectome, identifying neural circuits that coordinate wings and legs during escape takeoff.

This paper introduces engineering solutions to enable non-destructive X-ray tomography of brain tissue at ultrastructural resolution, validated against electron microscopy.

The paper demonstrates the use of a femtosecond laser to prepare resin-embedded samples for correlative microscopy workflows, enabling precise targeting and trimming for high-resolution imaging techniques.

The paper investigates biomechanical and molecular mechanisms underlying proprioceptor diversity in Drosophila legs, identifying a biomechanical basis for joint angle selectivity and a goniotopic map of joint angle.

The paper shows that axon morphology is influenced by the local environment and affects diffusion MRI estimates of axon diameter and structure-function relationships.

This paper introduces X-ray holographic nano-tomography for imaging dense neuronal structures in Drosophila and mammals, using convolutional neural networks for automated segmentation.