Deconvolution of molecular mechanisms in di-n-butyl phthalate/mono-n-butyl phthalate induced diabetic kidney disease by integrated machine learning and molecular docking
Wenjie Chen, Suyue Hou, Jijia Hu · 2025
Read Deconvolution of molecular mechanisms in di-n-butyl phthalate/mono-n-butyl phthalate induced diabetic kidney disease by integrated machine learning and molecular docking by Wenjie Chen, Suyue Hou, Jijia Hu (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12859878.txt.
Description
Wenjie Chen, Suyue Hou, and Jijia Hu trace how a common plastic chemical may drive diabetic kidney disease in a 2025 paper. The chemical and its breakdown product reach people through plastics and food wrap. The team blends gene data mining with learning models to find target genes. Docking models then test how the chemicals grip target proteins.
Six core genes emerged from the search. Two of them sorted cases from controls with strong accuracy in checks. Docking and motion models showed stable binding for both chemicals. The gene set touches stress, swelling, and growth signals in kidney tissue. The findings sketch a path for lab work on how plastic exposure harms kidneys.
Catalog record
| CREATOR | Wenjie Chen, Suyue Hou, Jijia Hu |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 69 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |