Biology subjects

Farr, T. D.

Publications and source records attributed to Farr, T. D..

4 recordsLinked to original sources

bioRxiv2026

High-throughput light-sheet 3D microscopy of whole rodent brain microstructure for integration with MRI

Whole-brain cellular mapping is essential for understanding how differences in cellular architecture shape brain organisation and function. Magnetic Resonance Imaging (MRI) provides whole-brain coverage in humans and animal models but is only indirectly sensitive to cellular features. Integrating MRI with whole-brain microscopy is therefore critical for interpreting existing microstructural MRI metrics and developing new, more specific ones. Here, we present a scalable cross-resolution framework that integrates 3D light-sheet microscopy (LSM) of intact rodent brains with diffusion MRI (dMRI) to bridge cellular and macroscopic brain imaging. By combining active electrotransport-based tissue clearing and immunolabelling with accelerated LSM acquisitions, we achieve whole-brain multiplexed mapping of neuronal and glial populations in intact rodent brains on timescales comparable to conventional histology and 2D microscopy. This throughput enables LSM and MRI integration at scale, linking macroscopic MRI contrasts to microscopic cellular features within the same tissue. We apply this framework across eight genetically diverse mouse strains to develop predictive models of 3D microscopy-derived cellular features from multi-shell dMRI-derived contrasts. We demonstrate that data-driven combinations of state-of-the-art dMRI contrasts predict neuronal and astrocytic features better than individual contrasts, across all animals. Our novel approach enables 3D microscopy to guide the development and interpretation of microstructural MRI measures that are ultimately translatable to the living human brain.

neuroscience↗

bioRxiv2026

Pericyte Loss Reprogrammes Capillary Endothelium and Drives White Matter Injury in Small Vessel Disease

Pericytes are critical regulators of cerebrovascular homeostasis, yet their contribution to small vessel disease (SVD) and white matter injury remains incompletely understood. Here, we use an inducible Atp13a5-driven genetic strategy to selectively label and ablate brain pericytes, enabling integrated morphological, functional, and transcriptomic analyses across the neurogliovascular unit. Single-cell RNA sequencing and tissue-level mapping identified distinct pericyte subtypes distributed along the vascular tree and revealed subtype-specific vulnerability following depletion. Moderate pericyte loss induced transient cerebrovascular dysfunction characterised by reduced cerebral blood flow and increased blood-brain barrier (BBB) permeability, accompanied by delayed white matter abnormalities, including altered diffusion MRI metrics, oligodendrocyte progenitor cell responses, and myelin loss. At the molecular level, pericyte depletion reprogrammed capillary endothelial cells toward an activated venular-like state characterised by VCAM-1 induction, reduced expression of the BBB-associated transporter MFSD2A, and activation of type I interferon signalling pathways. Cross-species analyses revealed enrichment of human white matter hyperintensity-associated SVD gene signatures across endothelial subtypes following pericyte depletion. Together, these findings identify pericyte dysfunction as a driver of endothelial inflammatory remodelling and white matter injury and establish mechanistic links between microvascular pericyte loss and human SVD.

neuroscience↗

bioRxiv2022

Prediction of Stroke Outcome in Mice Based on Non-Invasive MRI and Behavioral Testing

BackgroundPrediction of post-stroke outcome using the degree of subacute deficit or magnetic resonance imaging is well studied in humans. While mice are frequently used animals in preclinical stroke research, systematic analysis of outcome predictors is lacking. MethodsWe introduced heterogeneity into our study to broaden the applicability of our prediction tools. We analyzed the effect of 30, 45 and 60 minutes of arterial occlusion on the variance of stroke volumes. Next, we built a heterogeneous cohort of 215 mice using data from 15 studies that included 45 minutes of middle cerebral artery occlusion and various genotypes. Motor function was measured using the staircase test of skilled reaching. Phases of subacute and residual deficit were defined. Magnetic resonance images of stroke lesions were co-registered on the Allen Mouse Brain Atlas to characterize stroke topology. Different random forest prediction models that either used motor-functional deficit or imaging parameters were generated for the subacute and residual deficits. ResultsVariance of stroke volumes was increased by 45 minutes of arterial occlusion compared to 60 minutes and including various genotypes. We detected both a subacute and residual motor-functional deficit after stroke and different recovery trajectories. In mice with small cortical lesions, lesion volume was the best predictor of the subacute deficit. The residual deficit was most accurately predicted by the degree of the subacute deficit. When using imaging parameters for the prediction of the residual deficit, including information about the lesion topology increased prediction accuracy. A subset of anatomical regions within the ischemic lesion had particular impact on the prediction of long-term outcome. ConclusionsWe developed and validated a robust tool for the prediction of functional outcome after stroke in mice using a large heterogeneous cohort. Study design and imaging limitations are discussed. In the future, using outcome prediction can improve the design of preclinical studies and guide intervention decisions.

neuroscience↗

bioRxiv2020

Vascular cognitive impairment in the mouse reshapes visual, spatial network functional connectivity.

Connectome analysis of neuroimaging data is a rapidly expanding field to identify disease specific biomarkers. Structural diffusion MRI connectivity has been useful in individuals with radiological features of small vessel disease, such as white matter hyperintensities. Global efficiency, a network metric calculated from the structural connectome, is an excellent predictor of cognitive decline. To dissect the biological underpinning of these changes, animal models are required. We tested whether the structural connectome is altered in a mouse model of vascular cognitive impairment. White matter damage was more pronounced by 6 compared to 3 months. Global efficiency remained intact, but the visual association cortex exhibited increased structural connectivity with other brain regions. Exploratory resting state functional MRI connectivity analysis revealed diminished default mode network activity in the model compared to shams. Further perturbations were observed in a primarily cortical hub and the retrosplenial and visual cortices, and the hippocampus were the most affected nodes. Behavioural deficits were observed in the cued water maze, supporting the suggestion that the visual and spatial memory networks are affected. We demonstrate specific circuitry is rendered vulnerable to vascular stress in the mouse, and the model will be useful to examine pathophysiological mechanisms of small vessel disease. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

neuroscience↗