Fluids and Barriers of the CNS最新文献

Background: The pathology of Alzheimer's Disease (AD) is characterized by aggregates of amyloid beta (Aβ) peptides and neurofibrillary tau tangles. Increased blood-brain barrier (BBB) permeability and reduced Aβ clearance, which signal neurovascular dysfunction, have also been proposed as early markers of AD. Despite intense scrutiny, the mechanisms of AD remain elusive and novel treatments that address core symptoms of dementia are limited. New alternative methods (NAMs) aim to develop in-vitro translational models that recapitulate human pathology more accurately than previous models and could contribute to the development of new therapies.

Methods: Here, we developed a NAM model of the cortical neurovascular unit (NVU) using brain cells derived from human induced pluripotent stem cells (hiPSCs) from a patient with AD and a healthy individual. Differentiated neurons, astrocytes, pericytes, microglia, and brain-like microvascular endothelial cells were cultured in a microphysiological system to create a brain-chip model to evaluate NVU-related endpoints.

Results: Compared to control, AD brain-chips had reduced claudin-5 and ZO-1 expression and increased paracellular permeability. AD brain-chips also had decreased activity of the efflux transporter P-glycoprotein (P-gp), but its expression was unchanged. In AD brain-chips, levels of Aβ42, total tau, and p-tau 181 were decreased in protein lysates from the brain channel, while levels of total tau and p-tau 181 were increased in protein lysates from the vascular channel. Finally, AD brain-chips had increased levels of the proinflammatory markers IL-6 and MCP-1 in effluent from both brain and vascular channels.

Conclusion: In this brain-chip model, we showed Aβ-independent NVU dysfunction that was related to neuroinflammation and vascular tau accumulation. This study demonstrates the utility of the brain-chip model to evaluate changes in NVU functions induced by AD-like pathology and highlights donor-specific responses associated with the use of hiPSC-derived models.

Traditionally, cerebrospinal fluid (CSF) is believed to exit the brain via arachnoid villi, being absorbed into the superior sagittal sinus (SSS), with a net flow towards these exit sites driven by constant CSF turnover. However, measuring these velocities non-invasively in humans is challenging due to their slow nature and the presence of relatively large confounding factors such as physiological CSF pulsations (heartbeat and respiration) and head motion. This study presents a novel magnetic resonance imaging (MRI) method designed to measure the net velocity of CSF whilst accounting for confounding effects, which is called CSF displacement encoding with stimulated echoes (CSF-DENSE). By applying a similar model as used to study sea-level rise, different motion components of CSF were successfully disentangled. Simulations, along with phantom and in vivo experiments, demonstrate the ability of CSF-DENSE combined with time series analysis using unobserved components modeling to detect ultraslow velocities of approximately 1 μm/s, even in the presence of confounding motions that are an order of magnitude larger. Based on CSF flow measurements in the aqueduct, the expected net velocity in the subarachnoid space (SAS) towards the SSS was estimated to be 4.22 ± 0.14 µm/s. However, no significant net velocity toward the SSS was observed (v = -0.18±0.15 µm/s, with positive velocity directed towards the SSS). This questions whether outflow via the SAS towards the SSS is the main exit route of CSF, thereby challenging the classical view of CSF outflow. These findings suggest the need to reconsider traditional models of CSF outflow pathways, with potential implications for understanding and treating neurological disorders. Clinical trial number: Not applicable.

Background: Normal pressure hydrocephalus (NPH) is a potentially treatable neurodegenerative disorder that remains underdiagnosed due to its clinical overlap with other conditions and the labor-intensive nature of manual imaging analyses. Imaging biomarkers, such as the callosal angle (CA), Evans Index (EI), and Disproportionately Enlarged Subarachnoid Space Hydrocephalus (DESH), play a crucial role in NPH diagnosis but are often limited by subjective interpretations. To address these challenges, we developed a fully automated and robust deep learning framework for measuring the CA directly from raw T1 MPRAGE scans.

Methods: Our method integrates two complementary modules. First, a BrainSignsNET model is employed to accurately detect key anatomical landmarks, notably the anterior commissure (AC) and posterior commissure (PC). Preprocessed 3D MRI scans, reoriented to the Right Anterior Superior (RAS) system and resized to standardized cubes while preserving aspect ratios, serve as input for landmark localization. After detecting these landmarks, a coronal slice, perpendicular to the AC-PC line at the PC level, is extracted for subsequent analysis. Second, a UNet-based segmentation network, featuring a pretrained EfficientNetB0 encoder, generates multiclass masks of the lateral ventricles from the coronal slices which then used for calculation of the CA.

Results: Training and internal validation were performed using datasets from the Baltimore Longitudinal Study of Aging (BLSA) and BIOCARD, while external validation utilized 376 clinical MRI scans from Johns Hopkins Bayview Hospital, as well as PENS trial. Our framework achieved high concordance with manual measurements, demonstrating a strong correlation (r = 0.98, p < 0.001) and a mean absolute error (MAE) of 3.26 (SD 1.89) degrees. Moreover, error analysis confirmed that CA measurement performance was independent of patient age, gender, and EI, underscoring the broad applicability of this method.

Conclusions: These results indicate that our fully automated CA measurement framework is a reliable and reproducible alternative to manual methods, outperforms reported interobserver variability in assessing the CA, and offers significant potential to enhance early detection and diagnosis of NPH in both research and clinical settings.

Background: The choroid plexus (CP) plays a critical role in maintaining central nervous system (CNS) homeostasis, producing cerebrospinal fluid, and regulating the entry of specific substances into the CNS from blood. CP dysfunction has been implicated in various neurological and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, and multiple sclerosis.

Methods: This study investigates the relationship between CP structural integrity and cognitive decline in normative aging, using structural and advanced magnetic resonance imaging techniques, including CP volume, diffusion tensor imaging indices (mean diffusivity, MD, and fractional anisotropy, FA) and relaxometry metrics (longitudinal, T₁, and transverse, T₂, relaxation times).

Results: Our results show that lower CP microstructural integrity, as reflected by higher T₁, T₂, and MD values, or lower FA values, is associated with lower cognitive performance in processing speed and fluency. Notably, CP microstructural measures demonstrated greater sensitivity to cognitive decline than macrostructural measures, i.e. CP volume. Longitudinal analysis revealed that individuals with lower CP structural integrity exhibit steeper cognitive decline over time. Furthermore, structural equation modeling revealed that a latent construct representing CP integrity predicts faster overall cognitive decline, with an effect size comparable to that of age.

Conclusions: These findings highlight the importance of CP integrity in maintaining cognitive health and suggest that a holistic approach to assessing CP integrity could serve as a sensitive biomarker for early detection of cognitive decline. Further research is needed to elucidate the mechanisms underlying the relationship between CP structural integrity and clinical decline and to explore the potential therapeutic implications of targeting CP function to prevent or treat age-related cognitive deficits.