Evidence map›Paper›PMID 38261917›Full record

ArticleComputational and structural biotechnology journal2024

Network-based identification and mechanism exploration of active ingredients against Alzheimer's disease via targeting endoplasmic reticulum stress from traditional chinese medicine.

Zhao Dai, Tian Hu, Junwen Wei, Xue Wang, Chuipu Cai, Yong Gu, Yunhui Hu, Wenjia Wang, Qihui Wu, Jiansong Fang

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Zhao DaiScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Tian HuScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Junwen WeiScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Xue WangScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Chuipu CaiScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
Yong GuClinical Research Center, Hainan Provincial Hospital of Traditional Chinese Medicine, Hainan Medical University, Haikou 570100, China.
Yunhui HuTasly Pharmaceutical Group Co., Ltd., Tianjin 300402, China.
Wenjia WangTasly Pharmaceutical Group Co., Ltd., Tianjin 300402, China.
Qihui WuClinical Research Center, Hainan Provincial Hospital of Traditional Chinese Medicine, Hainan Medical University, Haikou 570100, China.
Jiansong FangScience and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease is a neurodegenerative disease that leads to dementia and poses a serious threat to the health of the elderly. Traditional Chinese medicine (TCM) presents as a promising novel therapeutic therapy for preventing and treating dementia. Studies have shown that natural products derived from kidney-tonifying herbs can effectively inhibit AD. Furthermore, endoplasmic reticulum (ER) stress is a critical factor in the pathology of AD. Regulation of ER stress is a crucial approach to prevent and treat AD. Thus, in this study, we first collected kidney-tonifying herbs, integrated chemical ingredients from multiple TCM databases, and constructed a comprehensive drug-target network. Subsequently, we employed the endophenotype network (network proximity) method to identify potential active ingredients in kidney-tonifying herbs that prevented AD via regulating ER stress. By combining the predicted outcomes, we discovered that 32 natural products could ameliorate AD pathology via regulating ER stress. After a comprehensive evaluation of the multi-network model and systematic pharmacological analyses, we further selected several promising compounds for in vitro testing in the APP-SH-SY5Y cell model. Experimental results showed that echinacoside and danthron were able to effectively reduce ER stress-mediated neuronal apoptosis by inhibiting the expression levels of BIP, p-PERK, ATF6, and CHOP in APP-SH-SY5Y cells. Overall, this study utilized the endophenotype network to preliminarily decipher the effective material basis and potential molecular mechanism of kidney-tonifying Chinese medicine for prevention and treatment of AD.

Indexed as

Alzheimer's diseaseAnti-AD ingredientsEndophenotype networkEndoplasmic reticulum stressKidney-tonifying herbs

Identifiers

PMID38261917
PMCPMC10796977

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.