Jin, L.-W. | Search bioRxiv

bioRxiv2020

A novel equilibrative nucleoside transporter 1 inhibitor alleviates Tau-mediated neurodegeneration

Tau hyperphosphorylation favors the formation of neurofibrillary tangles and triggers the gradual loss of neuronal functions in tauopathies, including Alzheimers disease. Herein, we demonstrated that chronic treatment with an inhibitor (J4) of equilibrative nucleoside transporter 1 (ENT1), which plays a critical role in controlling adenosine homeostasis and purine metabolism in the brain, exerted beneficial effects in a mouse model of tauopathy (Thy-Tau22, Tau22). Chronic treatment with J4 improved spatial memory deficits, mitochondrial dysfunction, synaptic plasticity impairment, and gliosis. Immunofluorescence assays showed that J4 not only reduced Tau hyperphosphorylation but also normalized the reduction in mitochondrial mass and suppressed the abnormal activation of AMP-activated protein kinase (AMPK), a pathogenic feature that is also observed in the brains of patients with tauopathies. Given that AMPK is an important energy sensor, our findings suggest that energy dysfunction is associated with tauopathy and that J4 may exert its protective effect by improving energy homeostasis. Bulk RNA-seq analysis revealed that J4 also mitigated immune signature associated with Tau pathology including C1q upregulation and A1 astrocyte markers. Collectively, our findings suggest that identifying strategies for normalizing energy and neuroimmune dysfunctions in tauopathies through adenosinergic signaling modulation may pave the way for the development of treatments for Alzheimers disease.

neuroscience↗

bioRxiv2018

Interpretable classification of Alzheimer’s disease pathologies with a convolutional neural network pipeline

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and can lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline identifying specific neuropathologies--amyloid plaques and cerebral amyloid angiopathy--in immunohistochemical-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotated >70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieved strong plaque classification (0.993 and 0.744 areas under the receiver operating characteristic and precision recall curve, respectively) on a 10 WSI hold-out set. Prediction confidence maps visualized morphology distributions from the full-WSI level down to 20x magnification. Resulting plaque-burden scores correlated well with established semi-quantitative scores. Finally, saliency mapping demonstrated that networks learned patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologists ability may suggest a route to neuropathologic deep phenotyping.

pathology↗