Imaging the structure and dynamic activity of retinal microglia and macrophage-like cells in the living human eye

Rui, Y.; Lee, D. M. W.; Zhang, M.; Snyder, V. C.; Raghuraman, R.; Gofas, E.; Mece, P.; Yadav, S.; Grieve, K.; Sahel, J.-A.; Errera, M.-H.; Rossi, E. A.

doi:10.1101/2022.04.30.490173

bioRxiv · 10.1101/2022.04.30.490173

Imaging the structure and dynamic activity of retinal microglia and macrophage-like cells in the living human eye

Rui, Y.·Lee, D. M. W.·Zhang, M.·Snyder, V. C.·Raghuraman, R.·Gofas, E.·Mece, P.·Yadav, S.·Grieve, K.·Sahel, J.-A.·Errera, M.-H.·Rossi, E. A.

View original source ↗Export metadata ↓

Abstract

PurposeWe recently showed how a refined sequential detection pattern and image processing pipeline for multi-offset adaptive optics scanning light ophthalmoscopy (AOSLO) can increase the contrast of weakly scattering inner retinal structures, including microglia. However, sequential detection was still time-consuming, preventing dynamics from being monitored over short intervals (< 3 mins). Here we show that simultaneous fiber-bundle (FB) detection can overcomes this limitation to reveal the structure and dynamic activity of microglia and macrophage-like cells in healthy and diseased retinae. MethodsWe designed and implemented a custom 7-fiber optical FB with one central confocal fiber and six larger fibers for multi-offset detection in AOSLO at a single focal plane. We imaged the ganglion cell layer at several locations at multiple timepoints (from minutes to weeks) in 8 healthy participants and in 4 patients with ocular infections or inflammation, including ocular syphilis and posterior uveitis. Microglia and immune cells were manually segmented to quantify cell morphometry and motility. ResultsFiber-bundle detection reduced single acquisition time to 20-30 seconds, enabling imaging over larger areas and monitoring of dynamics over shorter intervals. Presumed microglia in healthy retinas had an average diameter of 12.8 m and with a spectrum of morphologies including circular cells and elongated cells with visible processes. We also detected the somas of putative macroglia, potentially astrocytes, near the optic nerve head. Microglia moved slowly in normal eyes (0.02m/sec, on average) but speed increased in patients with active infections or inflammation (up to 2.37m/sec). Microglia activity was absent in a patient with chronic uveitis that was quiescent but apparent over short intervals in an active uveitis retina. In a patient with ocular syphilis imaged at multiple timepoints during treatment, macrophage-like cells containing granular internal structures were seen. Decreases in the quantity and motility of these immune cells were correlated with improvements to vision and other structural and systemic biomarkers. ConclusionsFB-AOSLO enable simplified optical setup with easy alignment and implementation. We imaged the fine-scale structure and dynamics of microglia and macrophage-like cells during active infection and inflammation in the living eye for the first time. In healthy eyes we also detected putative glia cell near the optic nerve head. FB-AOSLO offers promise as a powerful tool for detecting and monitoring retinal inflammation and infection in the living eye over short response to treatment.

Explore related subjects

bioengineering Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Rui, Y., Lee, D. M. W., Zhang, M., Snyder, V. C., Raghuraman, R., Gofas, E., Mece, P., Yadav, S., Grieve, K., Sahel, J.-A., Errera, M.-H., Rossi, E. A.. 2022-05-01. Imaging the structure and dynamic activity of retinal microglia and macrophage-like cells in the living human eye. https://doi.org/10.1101/2022.04.30.490173

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Synergy-informed bilevel optimization reveals joint-specific benefits for realistic exoskeleton torque prediction

Simulation-driven optimization can guide exoskeleton control design, but its utility is limited by the accuracy with which muscle coordination is predicted. Strict effort-minimization formulations predict non-physiological muscle shutdown under high exoskeleton assistance, leading to peak assistive torques that exceed values reported in human-in-the-loop experiments. We evaluated the accuracy of synergy-informed simulations at predicting assistance across four single-joint exoskeleton configurations: ankle plantarflexion, knee extension, hip flexion, and hip abduction. We implemented a bilevel optimization to predict a parameterized assistive torque that minimizes metabolic cost, with assisted muscle dynamics estimated via either effort-minimization simulations (minimizing muscle effort only) or synergy-informed simulations (minimizing muscle effort constrained to a synergy structure). We used experimental data from five unimpaired adults walking at their preferred speed and compared results descriptively between the two formulations within each subject. Assistance based on effort-minimization simulations shut down agonist muscle activations and overestimated peak assistive torque compared with experimental values. In contrast, constraining muscle controls to a synergy structure prevented non-physiological muscle shutdown and yielded assistive torques closer to those measured in human-in-the-loop experiments. This benefit was not observed equally across all assisted degrees of freedom or subjects, emerging only where no single synergy could be suppressed to unload the assisted muscles. Synergy weights can therefore be interpreted as joint-specific predictors of when simulations can reliably inform wearable robot design.

bioengineering↗

bioRxiv2026

Engineered microvessel networks -- Longitudinal transcriptomic profiling validates chip-grown tissues as a robust model for studying vasculature

Vascularised Organ-on-Chip (OoC) models are promising New Approach Methodologies (NAMs), but their translation requires validation for defined Contexts of Use (CoU). Here, we combine microfluidic microvessel networks (MVNs) with longitudinal bulk and single-cell RNA sequencing to determine how cell provenance influences engineered vascular phenotype. Stromal cell identity produced distinct network architectures and transcriptional trajectories, demonstrating that support cells, commonly treated as interchangeable, represent an important CoU variable. Primary human pancreatic microvascular endothelial cells failed to form stable perfusable networks, but supplementation with 10% Human Umbilical Vein Endothelial Cells (HUVECs) or Blood Outgrowth Endothelial Cells (BOECs) rescued self-assembly. Single-cell transcriptomics identified specialised endothelial populations associated with vascular morphogenesis, including tip, stalk, phalanx, endothelial to mesenchymal transition (EndMT) and pericyte-like endothelial cells. Failed networks lacked coherent endothelial specialisation, whereas rescued networks restored stabilising cell states and revealed FLRT2--UNC5B signalling within pericyte-like HUVECs, recapitulating a pathway implicated in angiogenic development in vivo. These findings establish cell provenance as a critical determinant of microvascular NAM performance and demonstrate how transcriptomic validation can define and strengthen the biological relevance of microvessel-on-chip models for specific CoUs.

bioengineering↗

bioRxiv2026

Benchmarking foundation models for resting-state functional magnetic resonance imaging time series in cognitive aging research

Foundation models trained on large neuroimaging datasets could help smaller studies investigate cognition from brain recordings. However, whether the foundation model-derived representations improve assessment of current cognition, prediction of follow-up cognition, or characterization of cognitive change remains unclear. We evaluated nine configurations from five model families that process regional resting-state functional magnetic resonance imaging time series, using 3,103 scans from 1,653 participants across two observational and five intervention aging cohorts. Primary frozen representations showed no consistent superiority over conventional functional connectivity for concurrent cognitive associations or diagnostic classification. Changing the readout improved selected concurrent cognitive associations without updating model weights, indicating that performance depended partly on how representations were extracted. Additional post-training and embedding alignment yielded gains in selected settings but did not consistently improve performance across outcomes. In the primary longitudinal analyses, imaging representations did not establish added value beyond baseline clinical measures. These findings show that readout choice influences concurrent cognitive associations, while the added value of these representations for longitudinal outcomes remains unestablished.

bioengineering↗