Evidence map›Paper›PMID 35130128›Full record

ArticleAutophagy2022

A synergized machine learning plus cross-species wet-lab validation approach identifies neuronal mitophagy inducers inhibiting Alzheimer disease.

Ruixue Ai, Xu-Xu Zhuang, Alexander Anisimov, Jia-Hong Lu, Evandro F Fang

Open access · greenAbstract readComment
In one paragraph

Article in Autophagy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
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  5. Roles of NADCold Spring Harbor perspectives in medicine · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

Ruixue AiDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.ORCID 0000-0001-9870-3692
Xu-Xu ZhuangState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China.ORCID 0000-0002-2938-5923
Alexander AnisimovDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.ORCID 0000-0003-3127-0639
Jia-Hong LuState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau SAR, China.ORCID 0000-0002-1147-125X
Evandro F FangDepartment of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway.ORCID 0000-0003-0355-7202
University of Oslo · NOUniversity of Macau · MO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Failed recognition and clearance of damaged mitochondria contributes to memory loss as well as Aβ and MAPT/Tau pathologies in Alzheimer disease (AD), for which there is an unmet therapeutic need. Restoring mitophagy to eliminate damaged mitochondria could abrogate metabolic dysfunction, neurodegeneration and may subsequently inhibit or slow down cognitive decline in AD models. We have developed a high-throughput machine-learning approach combined with a cross-species screening platform to discover novel mitophagy-inducing compounds from a natural product library and further experimentally validated the potential candidates. Two lead compounds, kaempferol and rhapontigenin, induce neuronal mitophagy and reduce Aβ and MAPT/Tau pathologies in a PINK1-dependent manner in both

Indexed as

Alzheimer DiseaseAmyloid beta-PeptidesAnimalsAutophagyCaenorhabditis elegansMachine LearningMiceMitophagyAmyloid beta-PeptidesAgingAlzheimer’s diseaseautophagymachine learningmitophagy

Identifiers

PMID35130128
PMCPMC9037405
OpenAlexW4210317308

What OpenQuestion holds

Textmetadata
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.