Bibliographic record
Abstract
IMPORTANCE: Excess free radical-induced oxidative stress and inflammatory processes are increasingly recognized as causative factors in hearing and balance disorders. Antioxidant micronutrients neutralize free radicals and, at adequate doses, reduce inflammation and demonstrate benefits in animal models and human trials. Therefore, it is reasonable to expect that biomarkers of oxidative damage and inflammation are appropriate correlative biological outcome parameters in clinical hearing intervention studies. OBJECTIVE: To provide the otology investigator a selected panel of biomarkers from the large universe of available tests that can be used as reasonable secondary endpoints in hearing and balance research. BACKGROUND SETTING: The tenets of antioxidant science dictate that there are a great variety of free radicals and that they impact different cellular targets. They also demonstrate varying functions in different cellular environments. In addition, oxidative stress and inflammation may cause direct injury to tissues, cell membrane lipids, proteins and mitochondrial, and nuclear DNA. To accommodate these many pathways, the useful categories of potential biomarkers become extensive. The degree of injury is also reflected by separate markers of inflammation and measures of antioxidant levels. Therefore, to provide a reliable indication of oxidative damage, inflammation and antioxidant level, it is necessary to determine a broad spectrum of lipid peroxidation markers, adducts of DNA, oxidation levels of proteins and pro-inflammatory cytokines. CONCLUSION: This report highlights some of the most clinically relevant and well-studied biomarkers in each category of tissue damage. It also includes those markers with which the authors have had direct positive clinical experience. The outcome from these studies is intended to provide a list of adjunctive measures that can be recommended as a relevant biomarker panel in hearing disorder clinical trials.
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.
How this classification was reachedexpand
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".