Neurophotonics

SignificanceLaser speckle contrast imaging (LSCI) is widely used to measure blood flow, but speckle fluctuations may also encode biologically meaningful dynamics beyond perfusion. Foundational studies in dynamic light scattering (DLS) and micro-optical coherence tomography (OCT) have also demonstrated that slow coherent signal fluctuations can arise from energy-dependent intracellular motion in in vitro and ex vivo systems. Building upon these advances, recent work has shown that LSCI has the potential to detect slow speckle dynamics (SSD) correlated with cellular dynamics in vivo. However, the biophysical mechanisms underlying SSD in intact brain tissues remain insufficiently validated. Establishing a mechanistic bridge from controlled ex vivo and in vitro conditions to in vivo brain measurements is critical for translating speckle-based imaging beyond perfusion measurements to enable label-free assessment of cellular and metabolic activity in disease models. AimThe objective of this study is to investigate the biophysical origin of the SSD in vivo and evaluate its sensitivity to intracellular metabolic activity in brain tissue. ApproachWe utilize an epi-illumination LSCI system to measure speckle contrast as a function of camera exposure time and extract characteristic decorrelation time constants. SSD was investigated in acute mouse brain slices, where blood flow is absent, to eliminate vascular confounds. Cellular metabolism was systematically modulated using 2-deoxyglucose and glucose. Complementary in vivo measurements were performed to reveal SSDs response to hyperoxia and normoxia after ischemic stroke. ResultsSSD signals persisted in acute brain slices in the absence of blood flow. Inhibition of glycolysis significantly reduced SSD, while restoration of metabolic substrates partially recovered the signal. In in vivo measurements, SSD increased during hyperoxia compared to normoxia after ischemic stroke, suggesting increased oxygen-supported cellular metabolic activity. ConclusionsThese results indicate that SSD is sensitive to energy-dependent cellular processes closely tied to metabolic activity. SSD represents a previously uncharacterized, label-free in vivo optical contrast that enables assessment of cellular metabolic activity as well as vascular dynamics. This work establishes a mechanistic foundation for using SSD as a general optical marker of cellular viability in in vivo measurements.

Long-Stokes-shift fluorophores enable high sensitivity and multiplexed imaging with single-wavelength excitation. Under single-photon illumination ATTO 490LS exhibits a 165-nm Stokes shift, but its two-photon properties remain uncharacterised. Emission and excitation spectral analyses of ATTO 490LS in ex vivo Drosophila melanogaster brains identified two-photon excitation sensitivity at 940 nm, with peak emission at 640 nm. We demonstrate successful duplexed imaging of ATTO 490LS alongside Alexa Fluor 488 using a single 920-nm fibre laser and dual photomultiplier tubes, enabling distinct measurement of red and green fluorescence signals. These findings establish ATTO 490LS as suitable for multicolour two-photon microscopy with single-laser systems.

Functional near infrared spectroscopy (fNIRS) is increasingly used in hearing and communication research, with advantages such as robustness to movement artifacts, improved spatial resolution, and flexibility of contexts in which it can be applied. At the same time, the field is progressively moving towards more continuous, naturalistic listening paradigms resulting in the widespread adoption of speech tracking analyses such as temporal response functions (TRFs) in electroencephalography (EEG) and magnetoencephalography (MEG) studies. However, it remains unclear whether these analyses can be applied to slower haemodynamic signals measured by fNIRS. In the present study, we investigated whether a TRF framework can similarly be applied to fNIRS data recorded during continuous speech perception. Eight participants listened to speech simultaneously while fNIRS signals were acquired in a hyperscanning setup. Speech features were regressed onto the haemodynamic responses to test the feasibility and interpretability of fNIRS-based TRFs. Prediction correlations between observed and modelled fNIRS signals across speech features were higher than those typically reported for EEG- and comparable to those reported for MEG-TRF studies. Moreover, these correlations did not overlap with a null distribution generated from triallJmismatched fNIRS data, confirming statistical significance and were slightly greater than those obtained from a conventional GLM approach. Our findings support that TRF estimation method can yield meaningful and statistically significant responses from fNIRS data. HighlightsO_LITRF modelling can be meaningfully applied to fNIRS data acquired during speech listening tasks. C_LIO_LIPrediction correlations between actual and modelled fNIRS signals were above chance level, with values comparable to previous EEG/MEG studies. C_LIO_LITRFs explained more fNIRS variance than a conventional GLM approach. C_LI

Motion artifacts remain a barrier to in vivo calcium imaging in Drosophila melanogaster larvae. Here, we evaluate a multimodal immobilization approach that combines a Pluronic F-127 (PF-127) hydrogel with brief diethyl ether vapor exposure (5 minutes, 25{degrees}C) and compare it against hydrogel-only immobilization using custom MATLAB-based analysis software that performs NoRMCorre rigid motion correction. In wide-field GFP recordings at 1 Hz over approximately 60 minutes (N = 15 per group), the multimodal condition significantly reduced motion across all three core metrics after FDR correction (all q < 0.001), with large effect sizes for mean speed (Hedges g = -1.18) and median step size (g = -1.36). In a secondary analysis of the first 30 minutes, uniformly large effect sizes (|g| = 1.10-1.51) were observed, consistent with stronger initial chemical immobilization that partially wanes over the recording period. We implemented a dual-flag quality control system that distinguishes motion data reliability from ROI detection eligibility. Control calcium recordings (33.33 Hz, [~]5 minutes; N = 23) yielded 368 ROIs with a mean SNR 30.4 {+/-} 16.9 and an event rate of 0.228 {+/-} 0.113 Hz. Experimental recordings (N = 21) yielded 295 ROIs with SNR 18.0 {+/-} 10.6 and event rate 0.309 {+/-} 0.188 Hz. SNR was higher in controls (Cliffs{delta} = 0.50, p < 0.001), while event rate was modestly higher in the experimental group at the ROI level ({delta} = -0.22, p < 0.001), though this difference did not reach significance at the sample level, suggesting altered but not suppressed calcium dynamics. These results support a practical, accessible immobilization workflow for larval calcium imaging. HighlightsO_LIBrief ether + hydrogel approach reduces larval motion 85-91% vs. hydrogel alone C_LIO_LIDual-flag QC system separates motion reliability from calcium ROI eligibility C_LIO_LICalcium event rates not suppressed under multimodal immobilization C_LIO_LIComplete MATLAB pipeline for motion analysis and calcium imaging provided C_LIO_LIAccessible protocol requires only standard laboratory supplies C_LI

Astrocytes are crucial mediators of diverse aspects of brain function, including energy metabolism and synapse formation and maturation. Calcium is the primary information carrier in astrocytes, reporting cellular health and activity, and can be measured using fluorescent indicators. However, this readout is not yet widely used to screen and evaluate disease models and drug candidates. Here, we adapted a simple automated calcium imaging pipeline with key output parameters that characterize changes in astrocytic calcium signaling. We compared calcium responses in mouse astrocyte monocultures and astrocyte-neuron cocultures using GFAP-driven membrane-targeted GCaMP6f, with human astrocytes differentiated from two different induced pluripotent stem-cell lines using the calcium dye Cal520-AM. Event-based analysis reported similarities and differences in mean fluorescence, amplitude, frequency, duration, and area of calcium responses. We benchmarked the pipeline using the purinergic receptor agonist ATP to increase astrocyte activity, and the ER calcium pump blocker CPA to decrease activity across all culture models. Glutamatergic and serotonergic receptor function was tested with glutamate and lysergic acid diethylamide (LSD). LSD decreased activity in mouse cocultured astrocytes, but increased activity in human astrocytes. Furthermore, the addition of human recombinant Tau oligomers, an in vitro model of Alzheimers disease pathology, decreased activity in both mouse and human astrocytes. This pipeline can be used to quickly and easily characterize effects of astrocyte-targeting compounds, effects of non-astrocyte-targeting compounds on astrocyte activity, and rescue of disease models that affect astrocyte function, in mouse and human astrocytes and astrocyte-neuron cocultures.

Brain activity comprises both rhythmic (periodic) and arrhythmic (aperiodic) components. These signal elements vary across healthy aging, and disease, and may make distinct contributions to conscious perception. Despite pioneering techniques to parameterize rhythmic and arrhythmic neural components based on power spectra, the methodology for quantifying rhythmic activity remains in its infancy. Previous work has relied on parametric estimates of rhythmic power extracted from specparam, or estimates of rhythmic power obtained after detrending neural spectra. Variation in analytical choices for isolating brain rhythms from background arrhythmic activity makes interpreting findings across studies difficult. Whether these current approaches can accurately recover the independent contribution of these neural signal elements remains to be established. Here, using simulation and parameter recovery approaches, we show that power estimates obtained from detrended spectra conflate these two neurophysiological components, yielding spurious correlations between spectral model parameters. In contrast, modelled rhythmic power obtained from specparam, which detrends the power spectra and parametrizes brain rhythms, independently recovers the rhythmic and arrhythmic components in simulated neural time series, minimising spurious relationships. We validate these methods using resting-state recordings from a large cohort. Based on our findings, we recommend modelled rhythmic power estimates from specparam for the robust independent quantification of rhythmic and arrhythmic signal components for cognitive neuroscience.

Objective detection of evoked potentials (EPs) is central to digital diagnostics in hearing assessment and clinical neurophysiology, yet current approaches remain time-intensive and sensitive to inter-individual noise variability. Many existing detection methods rely on population-based assumptions or computationally demanding procedures, limiting robustness and efficiency in real-world clinical settings. We present Fmpi, a digital EP detection framework enabling individualised, real-time response detection through analytical modelling of the spectral colour and temporal dynamics of background noise within each recording. Using extensive simulations and large-scale human electroencephalography datasets spanning brainstem, steady-state, and cortical EPs recorded in adults and infants, we demonstrate performance comparable or superior to state-of-the-art bootstrapped methods while operating at a fraction of the computational cost and maintaining well-controlled sensitivity with improved specificity. Importantly, Fmpi incorporates a futility detection mechanism enabling early termination of uninformative recordings, reducing testing time without compromising diagnostic reliability.

Bidirectional interfaces combined with neural de-coding algorithms are essential for closed-loop (CL) neuromodulation, enabling simultaneous neural monitoring and responsive optogenetic stimulation. However, implementing these capabilities in compact wireless headstages for freely moving animals remains challenging, as most existing platforms rely on tethered setups and external processors to execute computationally intensive decoders. This work presents the design and optimization of a neural decoder integrated into a bidirectional wireless system for CL optogenetic experiments in rodents. The proposed platform combines 32-channel electrophysiological recording with neuromorphic feature extraction, dimensionality reduction, and a nonlinear support vector machine (NL-SVM) decoder implemented on a resource-constrained Spartan-6 FPGA. Temporal dynamics are captured using spike-count features and leaky integrators, while principal component analysis (PCA) reduces the feature space to six components, enabling sub-millisecond inference with minimal memory and power requirements. Model size is further reduced using k-means clustering during training to limit the number of support vectors. Decoder performance was validated using datasets from non-human primate and rat motor cortex recordings. The proposed decoder achieved accuracy comparable to convolutional neural networks (R2 =0.85 vs. 0.87) and outperformed Wiener filters (R2 = 0.81) while requiring significantly fewer computational resources. The full system was further demonstrated in vivo through wireless closed-loop optogenetic stimulation in rats, achieving a variance accounted for (VAF) of 0.9148. Overall, this work introduces a versatile, fully self-contained, and resource-efficient platform for real-time untethered closed-loop neuroscience experiments.

Inscapes is a low demand abstract animation used as an alternative to eyes open rest in neuroimaging studies, particularly with pediatric and clinical populations prone to head motion. Although prior work has established that functional connectivity patterns during Inscapes closely resemble those during rest, no study has examined whether the two conditions differ in aperiodic neural activity, a broadband feature of the power spectrum linked to excitation/inhibition balance. Here we used magnetoencephalography (MEG) in 54 healthy adults to compare spectrally parameterised aperiodic and periodic measures between eyes open rest and Inscapes viewing (visual component only, without audio). At the sensor level, both the aperiodic exponent and offset were significantly higher during rest than during Inscapes across widespread frontoparietal and occipital distributions in both magnetometers and gradiometers. Source level analyses at both the parcellation and vertex levels largely supported these patterns. The pericalcarine cortex was a notable exception, where both aperiodic measures were higher during Inscapes than during rest, indicating a regionally specific reversal in primary visual cortex. These results demonstrate that Inscapes and eyes open rest produce distinct aperiodic spectral profiles, indicating that the two conditions are not interchangeable for analyses involving broadband spectral dynamics or excitation/inhibition balance estimation.

Saccadic eye movements are established biomarkers in neuroscience and clinical neurology, where video-oculography (VOG) remains the gold standard. However, VOG's high cost, bulky equipment, and poor portability restrict its clinical utility. Electrooculography (EOG) offers a promising alternative by detecting cornea-retinal potential changes during eye movements. To enable quantitative saccadic analysis using EOG as a VOG alternative, this study develops and validates a mathematical transformation model converting EOG data into VOG-equivalent values. A prospective observational study was conducted on 4 healthy adults without neurological or sleep disorders. Horizontal saccades were recorded simultaneously using EOG and VOG during controlled gaze shifts. EOG peak saccadic velocity was derived from voltage change rate, whereas VOG was calculated from angular displacement over time. A derivation dataset of fixed horizontal saccades ({+/-}20{degrees}) formulated the transformation model, achieving a strong correlation coefficient (r = 0.95 rightward, r = 0.93 leftward, p < 0.0001). Multiple filter settings were evaluated, and 0.3 Hz high-pass and 35 Hz low-pass filtering were identified as optimal. The fixed horizontal saccades derived model was applied to a validation dataset of random horizontal saccades, confirming robustness across saccades without significant differences from VOG measurements. These findings establish EOG's feasibility for quantitative analysis of horizontal saccades and provide a validated transformation model. By systematically optimizing filtering parameters, this approach enables EOG as a cost-effective VOG alternative while maintaining high-precision measurement accuracy.

We investigated whether multimodal sensing that combines functional near-infrared spectroscopy (fNIRS) with peripheral physiological signals can improve subject-independent classification of arousal and valence, the fundamental affective dimensions in Russells circumplex model. We developed Japanese emotion-inducing music-video stimuli (60 seconds each) and recorded subjects central nervous system activity using fNIRS, alongside peripheral physiological measures, specifically electrodermal activity (EDA) and photoplethysmography (PPG), during video viewing. To prioritize reproducibility and methodological transparency, we extracted simple, easily computed features from each modality and performed binary (high vs. low) classification separately for arousal and valence using a support vector machine. The combination of fNIRS and EDA yielded the highest performance, with a macro-averaged F1 score of 0.73 for arousal and 0.64 for valence. These findings underscore the utility of integrating fNIRS with peripheral physiological signals for subject-independent emotion classification.

Background and Objectives: We report the first intraoperative deployment of a real-time machine vision system in neurosurgery, derived from our previous anatomical detection work, automatically identifying structures during endoscopic endonasal surgery. Existing systems demonstrate promising performance in offline anatomical recognition, yet so far none have been implemented during live operations. Methods: A real-time anatomy detection model was trained using the YOLOv8 architecture (Ultralytics). Following training completion in the PyTorch environment, the model was exported to ONNX format and further optimized using the NVIDIA TensorRT engine. Deployment was carried out using the NVIDIA Holoscan SDK, the system ran on an NVIDIA Clara AGX developer kit. We used the model for real-time recognition of intraoperative anatomical structures and compared it with the same video labelled manually as reference. Model performance was reported using the average precision at an intersection-over-union threshold of 0.5 (AP50). Furthermore, end-to-end delay from frame acquisition to the display of the annotated output was measured. Results: A mean AP50 of 0.56 was achieved. The model demonstrated reliable detection of the most relevant landmarks in the transsphenoidal corridor. The mean end-to-end latency of the model was 47.81 ms (median 46.57 ms). Conclusion: For the first time, we demonstrate that clinical-grade, real-time machine-vision assistance during neurosurgery is feasible and can provide continuous, automated anatomical guidance from the surgical field. This approach may enhance intraoperative orientation, reduce cognitive load, and offer a powerful tool for surgical training. These findings represent an initial step toward integrating real-time AI support into routine neurosurgical workflows.

Fluorescent proteins (FPs) are essential tools for biological imaging but are limited by photobleaching, a light-induced loss of fluorescence intensity that reduces spatial and temporal resolution. Despite extensive use, the molecular mechanisms underlying FP photobleaching remain poorly understood due to the diversity of FPs and the complexity of their photochemistry. Existing approaches either monitor fluorescence decay in live cells, reflecting imaging conditions but lacking molecular detail, or rely on in vitro spectroscopy of purified proteins, providing mechanistic insight but often limited to individual FPs. We introduce a quantitative workflow bridging these approaches by combining live-cell measurements with in vitro spectroscopy. In vitro measurements are performed on a dedicated setup that simultaneously monitors absorption, emission, and fluorescence decay during photobleaching. Applied to six FPs spanning different chromophores, emission ranges and sequences, this approach reveals that photobleaching strongly depends on FP. It involves multiple chemical pathways, including oxidation, dimerization, and backbone cleavage. Spectroscopic analysis uncovers a heterogeneous ensemble of photoproducts with distinct photophysical properties that can remain optically active during irradiation, including shortened fluorescence lifetimes or altered absorption spectra. These findings demonstrate that FP photobleaching cannot be described as a simple ON-OFF process but involves complex transformations affecting both fluorescence intensity and lifetime. Such transformations can introduce significant biases in quantitative imaging, particularly in advanced techniques such as FLIM and FRET. Finally, we introduce quantitative indicators enabling robust comparison of FP photostability across experimental conditions. This framework provides a comprehensive approach for understanding and quantifying photobleaching and its implications for fluorescence imaging.

Longitudinal electrophysiological recordings of neuronal networks are essential for studying network maturation, plasticity, and pharmacological responses. Yet current microelectrode array (MEA) approaches are limited by evaporation-induced drift in culture conditions, exacerbated by heat dissipation from active recording electronics on CMOS-based high-density MEAs. We present a cell culture lid featuring a water compartment at its interface that eliminates evaporation whilst maintaining gas exchange. Combined with a custom incubator that uses independent temperature control of the MEA to prevent condensation, the system enables stable, un-interrupted recordings for weeks. We show that perturbations in firing rate and functional connectivity following medium exchange are significantly reduced by suppressing evaporation. We demonstrate continuous 35-day recordings of patterned human iPSC-derived neuronal networks with a single medium exchange, revealing the spontaneous emergence and consolidation of spatiotemporal firing patterns during maturation. All design files are provided to facilitate adoption across culturing platforms, enabling un-interrupted longitudinal interfacing with network dynamics for studies of plasticity, chronic pharmacology, and developmental trajectories in individual cultures.

Cerebrovascular reactivity (CVR), the ability of cerebral blood vessels to dilate or constrict in response to a vasoactive stimulus, is an important measure of cerebrovascular health. Accurate CVR estimation requires accounting for the time required for the vasoactive stimulus to reach each brain region and the time it takes for local arterioles to modulate cerebral blood flow. The temporal search range used to calculate this spatially varying offset can substantially impact CVR estimates, and the appropriate search range may vary across populations, acquisition protocols, and even brain regions. Here, we present an iterative approach for automatically determining the appropriate maximum shift, using breath-hold fMRI data acquired in a cohort of stroke survivors. This approach selectively expands the delay search range only for voxels with estimated delays at the boundary (i.e., near the minimum or maximum shift) until the estimated delay is no longer constrained or a predefined value is reached. In the context of stroke, this approach significantly increased the number of voxels with statistically significant CVR among those initially at the boundary. It also resulted in CVR polarity reversals in voxels originally at the early-response boundary and amplified negative CVR values in voxels originally at the late-response boundary, suggesting that using an iterative maximum shift can critically impact CVR interpretation. This approach is broadly applicable beyond stroke, but careful parameter tuning is required, as illustrated by our demonstration of the parameter tuning process for a participant with Moyamoya disease. Together, these findings suggest that iterative delay correction allows for improved CVR assessments in clinical populations.

Light sheet fluorescence microscopy (LSFM) is increasingly appreciated as the gold standard for gentle, volumetric imaging with fast acquisition speeds and/or long imaging durations. However, the often-constrained sample space of these microscopes has precluded a specific class of biological specimens from being studied with these tools: those requiring an air-liquid interface (ALI). Here, we present a device for robust imaging at ALI on an upright light sheet microscope with dipping objectives. We demonstrate the system using three relevant use-cases: ex vivo embryonic mouse salivary glands, human epidermal equivalent cultures, and in vivo adult Drosophila melanogaster brains. While the device presented is engineered for one specific light sheet microscope design, it provides a blueprint for easy adaptation to other systems. In doing so, it can potentially spur the use of LSFM for model systems that have so far been unable to take advantage of this powerful technology.

Study ObjectivesTo evaluate wearable sleep staging across sleep apnea severity, including very severe sleep apnea defined as an apnea-hypopnea index (AHI)[&ge;] 50 events/h, and to assess how training-set composition affects performance in this subgroup. MethodsWe analyzed 552 overnight recordings, 318 from the Sleep Lab Dataset and 234 from the Hospital Dataset. In the Hospital Dataset, 26.5% had very severe sleep apnea. We developed a deep learning model for sleep staging using RR intervals from wrist-worn photoplethysmography and three-axis accelerometry. Baseline performance was assessed by cross-validation under 5-stage and 4-stage staging. We examined night-level associations with AHI severity. We also compared the baseline model with an ablation model trained on the same number of recordings but with more Sleep Lab Dataset and lower-AHI Hospital Dataset recordings, evaluating both models in the very severe subgroup. ResultsIn 5-stage classification, Cohens kappa was 0.586 in the Sleep Lab Dataset and 0.446 in the Hospital Dataset. Under 4-stage staging, the gap narrowed, with kappa values of 0.632 and 0.525, respectively. In the Hospital Dataset, performance declined with increasing AHI severity. Among 62 recordings with very severe sleep apnea, reducing high-AHI representation in training lowered kappa from 0.365 to 0.303. ConclusionsWearable sleep staging performance declined across greater sleep apnea severity in this clinical cohort. Clinical utility may benefit from training data that better represent the target severity spectrum and from selecting staging granularity to match the intended use case. Statement of SignificanceRepeated laboratory polysomnography is impractical for long-term sleep apnea management. Wearable sleep staging could support scalable monitoring, yet its reliability in clinically severe sleep apnea has remained unclear. This study developed and evaluated a wearable sleep staging approach in both sleep-laboratory and hospital cohorts. The hospital cohort included many severe and very severe cases. Performance was lower in the hospital cohort and declined with greater sleep apnea severity. A coarser staging scheme reduced the gap between cohorts, and models trained without representative very severe cases performed worse in this target population. These findings highlight the value of severity-aware model development and motivate future multi-night home validation with reliability cues.

Mitochondrial membrane potential ({Delta}{Psi}m) is central to ATP production, ion homeostasis, and cell survival, reflecting the functional state of the inner mitochondrial membrane and oxidative phosphorylation. Accurate assessment of {Delta}{Psi}m is therefore essential for understanding mitochondrial physiology and dysfunction in health, ageing, and disease. Lipophilic cationic fluorescent dyes, such as TMRM and TMRE, are widely used to monitor {Delta}{Psi}m in live cells, enabling high-temporal-resolution imaging of both steady-state membrane potential and dynamic fluctuations. Beyond stable bioenergetic measurements, live-cell imaging reveals transient, reversible depolarisation events, known as mitochondrial "flickers." These events, observed across multiple cell types and imaging platforms, are often associated with brief openings of the mitochondrial permeability transition pore (mPTP) and may represent regulated mitochondrial excitability, rather than irreversible damage. While excessive or synchronised depolarisations may signal mitochondrial injury, transient flickers are increasingly viewed as potential signalling mechanisms within the mitochondrial network. This work discusses methodological considerations for {Delta}{Psi}m imaging, the biological significance of mitochondrial flickers, and the importance of distinguishing physiological events from probe- and light-induced artefacts, highlighting the emerging concept of mitochondria as dynamic and communicative bioenergetic networks.

Background: Recently, a posterior pathway for fluid drainage from the retina to the meningeal lymphatics in the optic nerve (ON) sheath was identified in rodents using intravitreal imaging tracers directly injected into the ocular-globe. Fluid and solute clearance along this pathway may be associated with many diseases. However, intravitreal tracers are rarely used in clinical imaging. As intravenous Gadolinium-based-contrast-agent (GBCA) can enter the globe via the blood-ocular-barriers, it may provide an alternative approach to image this pathway. Purpose: To establish a clinically feasible intravenous GBCA-based MRI approach for tracking fluid and solute transport along the posterior lymphatic pathway in the ocular glymphatic system. Materials & Methods: This prospective study was conducted from March 2021 to September 2022 in healthy participants. Dynamic-susceptibility-contrast-in-the-CSF (cDSC) MRI was performed before, immediately and 4 hours after intravenous-GBCA administration to track GBCA distribution in aqueous humor (AH) and cerebrospinal fluid (CSF) in regions-of-interest (ROIs) in the globe (anterior-cavity, vitreous-body), in the intraorbital and extraorbital ON, and in the intracranial CSF space proximal to the ON (chiasmatic-cistern, interpeduncular-cistern). Kruskal-Wallis tests with post-hoc Dunn's tests were used for group comparisons. Results: Sixteen healthy participants (mean age +/- SD: 51 +/- 21 years, 5 men) were recruited. Intravenous-GBCA enhancement was observed in all ROIs immediately after injection. At 4-hour-post-GBCA, the vitreous body showed a trend of smaller enhancement area (55 +/- 11% versus 49 +/- 11%, P=.14) and lower GBCA-concentration (0.044 +/- 0.014 versus 0.028 +/- 0.010 mmol/L, P=.07) compared to immediate-post-GBCA. The intraorbital ON showed more widespread enhancement (39 +/- 5% versus 59 +/- 6%, P=.01) and significantly higher GBCA-concentration (0.023 +/- 0.009 versus 0.059 +/- 0.015 mmol/L, P<.001) at 4-hour-post-GBCA. Conclusion: Dynamic fluid and solute transportation along the posterior lymphatic pathway in the ocular glymphatic system in healthy participants was measured by tracking intravenous-GBCAs entering the globe via the blood-ocular-barriers using cDSC-MRI.

Fluorescent in situ hybridization (FISH) enables highly sensitive, high-resolution detection of gene transcripts. Moreover, by employing multiple probes, this technique allows for multiplexed, simultaneous detection of distinct gene expression patterns spatiotemporally, making it a valuable spatial transcriptomics approach. Owing to these advantages, FISH techniques are rapidly being adopted across diverse areas of basic biology. However, conventional protocols often rely on volatile, toxic reagents such as formalin or methanol, posing potential health risks to researchers. Here, we present a safer protocol that replaces these chemicals with low-toxicity alternatives, without compromising the high detection sensitivity of FISH. We validated this protocol using both in situ hybridization chain reaction (HCR) and signal amplification by exchange reaction (SABER)-FISH in frozen sections of various model organisms, including mouse (Mus musculus), amphibians (Xenopus laevis and Pleurodeles waltl), and medaka (Oryzias latipes). Our results demonstrate successful multiplexed detection of morphogenetic and cell-type marker genes in these model animals using this safer protocol. The protocol has the additional advantage of requiring no proteolytic enzyme treatment, thus preserving tissue integrity. Furthermore, we show that this protocol is fully compatible with EGFP immunostaining, allowing for the simultaneous detection of mRNAs and reporter proteins in transgenic animals. This protocol retains the benefits of highly sensitive, multiplexed, and multimodal detection afforded by integrating in situ HCR and SABER-FISH with immunohistochemistry, while providing a safer option for researchers, thereby offering a valuable tool for basic biology.