Dataset for "Reinforcement learning-guided discovery and bivalent engineering of a Toll-like receptor 4 antagonist mitigates UV-induced sterile inflammation and photoaging"

Published: 2 April 2026| Version 1 | DOI: 10.17632/zx89pjfjpg.1
Contributors:
Youngkeun Lee,
, Bokyung Kim,
,

Description

This dataset contains all raw numerical data supporting the findings of the manuscript. Data are provided as a single multi-sheet Microsoft Excel workbook. In vitro data include: (0) ELISA Affinity Test (1) MTS cell viability assay of the R10 TLR4 antagonist; (2) reactive oxygen species (ROS) measurements under TNF-α stimulation; (3) TNF-α ELISA under LPS stimulation for compounds (v1F, v2F, R3, R10) and dexamethasone; and (4) TNF-α ELISA under S100A8/9 stimulation. In vivo data include: (5) histomorphometric analysis of epidermal thickness (H&E staining) and dermal collagen intensity (Masson's Trichrome staining); (6) skin surface measurements (roughness and wrinkle depth from silicone replicas); (7) longitudinal non-invasive biophysical measurements (skin elasticity, moisture, thickness, and transepidermal water loss [TEWL]) recorded weekly from week 1 to week 10; and (8) Western blot densitometry for MAPK pathway activation (p-ERK/ERK, p-JNK/JNK, p-p38/p38 ratios).

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Biochemistry, Molecular Biology, Immunology, Pharmacology

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