Serum markers for mitochondrial dysfunction and cell death are possible predictive indicators for drug‐induced liver injury by direct acting antivirals
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
AIM: We prospectively screened patients treated with direct-acting antivirals (DAA) in order to detect and analyze serum markers that are present prior to the development of drug-induced liver injury (DILI). METHODS: The levels of various serum markers among DILI, non-DILI and control groups were compared. The DILI group consisted of eight patients whose alanine aminotransferase (ALT) levels exceeded 32 IU/L during the DAA treatment. Eight patients without DILI were selected for the non-DILI group via a matched-group design based on age, sex and disease severity. Additionally, eight healthy volunteers were employed as the controls. Serum measurements of cytokines/chemokines, cytokeratin-18 fragment (CK-18F) and super oxidase dismutase-2 (SOD2) were evaluated on the date at which hepatitis C virus RNA was absent (baseline). For patients with DILI, serum measurements taken before treatment, 1 week before pronounced transaminase elevation (prominence-1 W) and on the date at which pronounced elevation of transaminase occurred (prominence) were also evaluated. RESULTS: All patients treated with DAA had normalized transaminase levels at baseline. In patients with DILI, interferon-inducible protein-10 (IP-10) levels were higher at prominence-1 W than at baseline. Those patients also had significantly higher levels of SOD2 and CK-18F at prominence-1 W than at baseline. CONCLUSION: Elevated IP-10 may be a preconditioning chemokine for DAA-induced liver injury, and damage markers associated with cell death and mitochondrial dysfunction are potential predictive serum markers for DILI.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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