Use of 13C‐labeled mass isotopomer analysis by gas chromatography‐mass spectrometry (GCMS) to assess pyruvate metabolism in fibroblast cell lines: A potential model for diagnosis of metabolic diseases.
Bibliographic record
Abstract
The design of treatments for patients with mitochondrial diseases due to genetic defects would benefit from a better understanding of the metabolic consequences of these diseases. The objective was to develop a model using fibroblast cell lines, to assess pyruvate partitioning between decarboxylation (PDC) and anaplerotic carboxylation (PC), two crucial reactions for tricarboxylic acid (TCA) cycle activity and ATP production. Normal fibroblast cells were incubated for 2 hours at 37 °C in PBS before adding [U‐ 13 C]pyruvate (1mM) for 30 minutes. TCA intermediates and pyruvate were assessed by GCMS. PDC and PC fluxes were calculated from molar percent enrichment (MPE) of citrate and malate. Reproducibility of the model was tested using replicates of control cell lines (CT) and its potential usefulness using cell lines with mild complex I deficiency (CID). Under our conditions, intracellular pyruvate of CT cells was solely enriched in M3 isotopomers (67.0 ± 4.9%; n=5). Absence of M1 and M2 pyruvate demonstrated negligible recycling due to malate decarboxylation. Pyruvate was predominantly decarboxylated, as demonstrated by the flux ratio PDC/PC: 18.7 ± 8.3. CID cells showed a similar 13 C labelling pattern for pyruvate, except MPE M3 was higher (81.4) and PDC/PC flux ratio was lower (4.89). This model is a framework to study the effect of mitochondrial diseases on pyruvate metabolism into the TCA cycle. (CIHR supported)
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".