Ali Ertürk

The paper identifies a hypervascular, BBB-compromised state in aging mice linked to cognitive decline and shows pharmacological stabilization improves vascular and cognitive outcomes.

The paper identifies maternal neutrophils as a survival niche for Listeria monocytogenes, facilitating placental and fetal infection during pregnancy.

This study shows that chronic stress accelerates brain aging in young mice but activates age-specific anti-aging programs in old mice.

This paper develops a human brainstem organoid model of H3.3K27M-altered DMG to study GD2 CAR T cell function and identify therapeutic targets.

DISCO-seq enables 3D single-cell transcriptomics of whole tissues and organisms by combining tissue-clearing chemistry with imaging and transcriptomic profiling.

Leonardo corrects sample-induced artifacts in light sheet microscopy images using two modules, validated on diverse biological samples.

LipiGo is a DNA-lipid nanoparticle hybrid that enables efficient delivery of functional mRNA to non-hepatic tissues, particularly the spleen, through passive redistribution and active targeting.

The paper shows that combining progenitor expansion with adhesion-controlled neuronal migration enhances cortex folding in mice, leading to sulci and gyri formation.

Spapros selects optimal probe sets for targeted spatial transcriptomics to improve cell type identification and spatial variation detection across multiple datasets.

This paper introduces MouseMapper, a deep learning tool combined with 3D imaging to analyze whole-body structural changes in obesity, revealing nerve and immune system alterations.

This study compares the biodistribution of Fc-engineered molecules targeting BBB receptors with standard antibodies, showing distinct CNS and peripheral organ targeting.

DELiVR uses VR-generated data to train deep learning models for quantifying c-Fos in cleared mouse brains, revealing new activation patterns in cancer-related brain activity.

The paper introduces an improved open-source light-sheet microscope, mesoSPIM, with enhanced resolution, throughput, and compatibility with cleared samples.

The paper identifies cellular sources of PET signals in glioblastoma by combining radiotracer uptake with 3D-histology and proteomics, showing tumor cells mainly contribute to TSPO enrichment while TAMs have specific PET targets.

This study shows SARS-CoV-2 spike protein accumulates in the skull-meninges-brain axis, causing brain cell death and long-term neurological effects.

This paper evaluates graph neural networks' ability to predict tissue-level phenotypes from spatial molecular data, finding that some phenotypes can be captured without spatial information and that overfitting limits representation learning.

This paper introduces a 3D deep learning network using dual-GAN to recover high-resolution volume images from low-resolution ones in fluorescence microscopy.

The paper develops a deep learning framework to analyze whole brain vasculature in cleared mouse brains, revealing new insights into vascular architecture and collateralization.

This paper introduces DeepMACT, a pipeline for automated detection of cancer metastases and therapeutic antibody targeting in whole-body mouse models using deep learning and enhanced imaging.

The paper introduces a new imaging technique to enhance fluorescent signal in cleared mouse bodies, enabling whole-body visualization of neuronal connectivity and trauma effects.