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Deep cervical lymph node ligation aggravates AD-like pathology of APP/PS1 mice.

ABSTRACT: The imbalance between production and clearance of amyloid-beta (Aβ) is a key step in the onset and development of Alzheimer's disease (AD). Therefore, reducing Aβ accumulation in the brain is a promising therapeutic strategy for AD. The recently discovered glymphatic system and meningeal lymphatic vasculature have been shown to be critical for the elimination of interstitial waste products, especially Aβ, from the brain. In the present study, ligation of deep cervical lymph nodes was performed to block drainage of this system and explore the consequences on Aβ-related pathophysiology. Five-month-old APP/PS1 mice and their wild-type littermates received deep cervical lymphatic node ligation. One month later, behavioral testing and pathological analysis were conducted. Results demonstrated that ligation of dcLNs exacerbated AD-like phenotypes of APP/PS1 mice, showing more severe brain Aβ accumulation, neuroinflammation, synaptic protein loss, impaired polarization of aquaporin-4 and deficits in cognitive and exploratory behaviors. These results suggest that brain lymphatic clearance malfunction is one of the deteriorating factors in the progression of AD, and restoring its function is a potential therapeutic target against AD.

SUBMITTER: Wang L

PROVIDER: S-EPMC8028636 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Deep cervical lymph node ligation aggravates AD-like pathology of APP/PS1 mice.

Wang Linmei L Zhang Yanli Y Zhao Ying Y Marshall Charles C Wu Ting T Xiao Ming M

Brain pathology (Zurich, Switzerland) 20181010 2

The imbalance between production and clearance of amyloid-beta (Aβ) is a key step in the onset and development of Alzheimer's disease (AD). Therefore, reducing Aβ accumulation in the brain is a promising therapeutic strategy for AD. The recently discovered glymphatic system and meningeal lymphatic vasculature have been shown to be critical for the elimination of interstitial waste products, especially Aβ, from the brain. In the present study, ligation of deep cervical lymph nodes was performed t ...[more]

PMID: 30192999

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Project description:Clinical evidence shows that postmenpausal women are almost twice as likely to develop Alzheimer's disease (AD) as men of the same age, and estrogen is closely related to the occurrence of AD. Estrogen receptor (ER) α is mainly expressed in the mammary gland and other reproductive organs like uterus while ERβ is largely distributed in the hippocampus and cardiovascular system, suggesting that ERβ selective agonist is a valuable drug against neurodegenerative diseases with low tendency in inducing cancers of breast and other reproductive organs. In this study we identified a natural product patchouli alcohol (PTA) as a selective ERβ agonist which improved the cognitive defects in female APP/PS1 mice, and explore the underlying mechanisms. Six-month-old female APP/PS1 mice were administered PTA (20, 40 mg · kg-1 · d-1, i.g.) for 90 days. We first demonstrated that PTA bound to ERβ with a dissociation constant (KD) of 288.9 ± 35.14 nM in microscale thermophoresis. Then we showed that PTA administration dose-dependently ameliorated cognitive defects evaluated in Morris water maze and Y-maze testes. Furthermore, PTA administration reduced amyloid plaque deposition in the hippocampus by promoting microglial phagocytosis; PTA administration improved synaptic integrity through enhancing BDNF/TrkB/CREB signaling, ameliorated oxidative stress by Catalase level, and regulated Bcl-2 family proteins in the hippocampus. The therapeutic effects of PTA were also observed in vitro: PTA (5, 10, 20 μM) dose-dependently increased phagocytosis of o-FAM-Aβ42 in primary microglia and BV2 cells through enhancing ERβ/TLR4 signaling; PTA treatment ameliorated o-Aβ25-35-induced reduction of synapse-related proteins VAMP2 and PSD95 in primary neurons through enhancing ERβ/BDNF/TrkB/CREB pathways; PTA treatment alleviated o-Aβ25-35-induced oxidative stress in primary neurons through targeting ERβ and increasing Catalase expression. Together, this study has addressed the efficacy of selective ERβ agonist in the amelioration of AD and highlighted the potential of PTA as a drug lead compound against the disease.

Project description:ObjectivesPrecise determination of cervical lymph node metastasis (CLNM) involvement in patients with early-stage thyroid cancer is fairly significant for identifying appropriate cervical treatment options. However, it is almost impossible to directly judge lymph node metastasis based on the imaging information of early-stage thyroid cancer patients with clinically negative lymph nodes.MethodsPreoperative US images (BMUS and CDFI) of 1031 clinically node negative PTC patients definitively diagnosed on pathology from two independent hospitals were divided into training set, validation set, internal test set, and external test set. An ensemble deep learning model based on ResNet-50 was built integrating clinical variables, BMUS, and CDFI images using a bagging classifier to predict metastasis of CLN. The final ensemble model performance was compared with expert interpretation.ResultsThe ensemble deep convolutional neural network (DCNN) achieved high performance in predicting CLNM in the test sets examined, with area under the curve values of 0.86 (95% CI 0.78-0.94) for the internal test set and 0.77 (95% CI 0.68-0.87) for the external test set. Compared to all radiologists averaged, the ensemble DCNN model also exhibited improved performance in making predictions. For the external validation set, accuracy was 0.72 versus 0.59 (p = 0.074), sensitivity was 0.75 versus 0.58 (p = 0.039), and specificity was 0.69 versus 0.60 (p = 0.078).ConclusionsDeep learning can non-invasive predict CLNM for clinically node-negative PTC using conventional US imaging of thyroid cancer nodules and clinical variables in a multi-institutional dataset with superior accuracy, sensitivity, and specificity comparable to experts.Critical relevance statementDeep learning efficiently predicts CLNM for clinically node-negative PTC based on US images and clinical variables in an advantageous manner.Key points• A deep learning-based ensemble algorithm for predicting CLNM in PTC was developed. • Ultrasound AI analysis combined with clinical data has advantages in predicting CLNM. • Compared to all experts averaged, the DCNN model achieved higher test performance.

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Dataset Information

Deep cervical lymph node ligation aggravates AD-like pathology of APP/PS1 mice.

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Deep cervical lymph node ligation aggravates AD-like pathology of APP/PS1 mice.

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