WONOEP appraisal: Biomarkers of epilepsy‐associated comorbidities
Bibliographic record
Abstract
Neurologic and psychiatric comorbidities are common in patients with epilepsy. Diagnostic, predictive, and pharmacodynamic biomarkers of such comorbidities do not exist. They may share pathogenetic mechanisms with epileptogenesis/ictogenesis, and as such are an unmet clinical need. The objectives of the subgroup on biomarkers of comorbidities at the XIII Workshop on the Neurobiology of Epilepsy (WONOEP) were to present the state-of-the-art recent research findings in the field that highlighting potential biomarkers for comorbidities in epilepsy. We review recent progress in the field, including molecular, imaging, and genetic biomarkers of comorbidities as discussed during the WONOEP meeting on August 31-September 4, 2015, in Heybeliada Island (Istanbul, Turkey). We further highlight new directions and concepts from studies on comorbidities and potential new biomarkers for the prediction, diagnosis, and treatment of epilepsy-associated comorbidities. The activation of various molecular signaling pathways such as the "Janus Kinase/Signal Transducer and Activator of Transcription," "mammalian Target of Rapamycin," and oxidative stress have been shown to correlate with the presence and severity of subsequent cognitive abnormalities. Furthermore, dysfunction in serotonergic transmission, hyperactivity of the hypothalamic-pituitary-adrenocortical axis, the role of the inflammatory cytokines, and the contributions of genetic factors have all recently been regarded as relevant for understanding epilepsy-associated depression and cognitive deficits. Recent evidence supports the utility of imaging studies as potential biomarkers. The role of such biomarker may be far beyond the diagnosis of comorbidities, as accumulating clinical data indicate that comorbidities can predict epilepsy outcomes. Future research is required to reveal whether molecular changes in specific signaling pathways or advanced imaging techniques could be detected in the clinical settings and correlate with epilepsy-associated comorbidities. A reliable biomarker will allow a more accurate diagnosis and improved treatment of epilepsy-associated comorbidities.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".