Abnormal calcium signalling and the caffeine–halothane contracture test
Bibliographic record
Abstract
Background The variable clinical presentation of malignant hyperthermia (MH), a disorder of calcium signalling, hinders its diagnosis and management. Diagnosis relies on the caffeine–halothane contracture test, measuring contraction forces upon exposure of muscle to caffeine or halothane ( F C and F H , respectively). Patients with above-threshold F C or F H are diagnosed as MH susceptible. Many patients test positive to halothane only (termed ‘HH'). Our objective was to determine the characteristics of these HH patients, including their clinical symptoms and features of cytosolic Ca 2+ signalling related to excitation–contraction coupling in myotubes. Methods After institutional ethics committee approval, recruited patients undergoing contracture testing at Toronto's MH centre were assigned to three groups: HH, doubly positive (HS), and negative patients (HN). A clinical index was assembled from musculoskeletal symptoms and signs. An analogous calcium index summarised four measures in cultured myotubes: resting [Ca 2+ ] cytosol , frequency of spontaneous cytosolic Ca 2+ events, Ca 2+ waves, and cell-wide Ca 2+ spikes after electrical stimulation. Results The highest values of both indexes were found in the HH group; the differences in calcium index between HH and the other groups were statistically significant. The principal component analysis confirmed the unique cell-level features of the HH group, and identified elevated resting [Ca 2+ ] cytosol and spontaneous event frequency as the defining HH characteristics. Conclusions These findings suggest that HH pathogenesis stems from excess Ca 2+ leak through sarcoplasmic reticulum channels. This identifies HH as a separate diagnostic group and opens their condition to treatment based on understanding of pathophysiological mechanisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".