Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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.
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
7 authors.
Sheng Ye *Engineering Research Center of Autonomous Unmanned System Technology, Ministry of Education, Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology, School of AI, Anhui University, Hefei 230601, China.
BinBin Wang *Engineering Research Center of Autonomous Unmanned System Technology, Ministry of Education, Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology, School of AI, Anhui University, Hefei 230601, China.
Zhipeng Li *Engineering Research Center of Autonomous Unmanned System Technology, Ministry of Education, Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology, School of AI, Anhui University, Hefei 230601, China.
Lvshuai Zhu *Engineering Research Center of Autonomous Unmanned System Technology, Ministry of Education, Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology, School of AI, Anhui University, Hefei 230601, China.ORCID 0009-0006-7726-3556
Chang Yin SunEngineering Research Center of Autonomous Unmanned System Technology, Ministry of Education, Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology, School of AI, Anhui University, Hefei 230601, China.
Shaul MukamelDepartment of Chemistry, University of California, Irvine, CA 92697.ORCID 0000-0002-6015-3135
Jun JiangKey Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei, Anhui 230026, China.ORCID 0000-0002-6116-5605
Funding
Key Laboratory of Precision and Intelligent Chemistry open research fundNational Natural Science Foundation of China 22025304 22033007National Natural Science Foundation of China 22203001| Natural Science Foundation of Anhui Province () 2208085Y04NSF (NSF) CHE-2246379University Synergy Innovation Program of Anhui Province GXXT-2022-062
6 · The paper itself
Abstract
Protein misfolding plays a central role in diseases such as Alzheimer's disease, Parkinson's disease, type 2 diabetes, and transthyretin amyloidosis (ATTR), often driven by specific aggregation-prone segments such as A
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.
A machine learning protocol for predicting structural distributions of amyloid-forming proteins from 2D IR spectra. · full record | OpenQuestion