Cuproptosis Facilitates Chronic Skin Inflammation by Regulating the α‐Ketoglutarate/H3K4me3/Ferritin Heavy Chain 1 Signaling Pathway‐Mediated Ferroptosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dysregulated copper homeostasis is implicated in inflammatory skin diseases such as psoriasis and atopic dermatitis (AD), but the role of cuproptosis remains poorly defined. This study aimed to elucidate the role and mechanism of cuproptosis in inflammatory skin diseases. Transcriptome analysis of patient lesions revealed significant alterations in cuproptosis-related genes correlating with disease-specific pathological features. These cuproptosis-related gene expression signatures demonstrated strong clinical relevance to therapeutic efficacy in both psoriasis and AD cohorts. Functional validation using disease models showed that pharmacologically inhibiting cuproptosis with the copper chelator tetrathiomolybdate (TTM), or genetically knocking down the copper importer SLC31A1, effectively alleviated chronic skin inflammation and hallmark pathological changes induced by imiquimod (IMQ) or calcipotriol (MC903). Mechanistically, we uncovered that SLC31A1-mediated cuproptosis promotes intracellular α-ketoglutarate (α-KG) accumulation, driving activation of the lysine demethylase KDM5B. Activated KDM5B specifically demethylates H3K4me3 marks at the promoter of the ferroptosis regulator ferritin heavy chain 1 (FTH1), suppressing its transcription and consequently sensitizing keratinocytes to ferroptotic cell death, thereby amplifying inflammatory tissue damage. Our findings establish a fundamental pathogenic SLC31A1/KDM5B/FTH1 molecular axis linking dysregulated copper metabolism and cuproptosis to ferroptosis execution in psoriasis and AD, providing significant mechanistic insights and pinpointing promising therapeutic targets for these refractory skin disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it