Aberrations in Plasma Phospholipid Fatty Acids in Lung Cancer Patients
Bibliographic record
Abstract
Abnormalities in lipid metabolism have been frequently observed in cancer and are associated with a poor prognosis. However, a detailed, longitudinal characterization of fatty acid status is lacking. This study aimed to assess plasma phospholipid fatty acids before chemotherapy, immediately after and 1 month following chemotherapy in a group of 50 patients newly diagnosed with lung cancer and explore factors which may contribute to aberrations in fatty acids. Their mean ± SD characteristics: age 64 ± 8.5 years, 75% advanced stage disease, body mass index 27.0 ± 5.4 kg/m², 6 month weight loss -4.6 ± 6.1%. Compared to patients with early stage disease, patients with advanced disease had abnormal fatty acid profiles including significantly lower (P < 0.05) amounts of total phospholipid fatty acids, saturated, and polyunsaturated fatty acids (linoleic, arachidonic, eicosapentaenoic and docosahexaenoic). Longitudinal analysis revealed that patients with advanced disease who completed chemotherapy had stable fatty acid levels and continued to maintain levels 1 month following completion of chemotherapy. Comparatively, patients who did not complete chemotherapy due to toxicity or disease progression had progressive loss of total phospholipid fatty acids, stearic, linoleic and n-6 fatty acids and a trend towards lower docosahexaenoic, arachidonic, palmitic, n-3 and saturated fatty acids. These results suggest that loss of fatty acids is prevalent, progressive and potentially influenced by advanced disease and chemotherapy treatment.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".