The Prognostic Value of Serine and Glycine Levels in Plasma in Patients with Esophageal Cancer: A Case Control Study
Bibliographic record
Abstract
Background and Objective: Serine and glycine are connecting lines for biosynthesis and are essential resources for synthesis of proteins, nucleic acids and lipids that are necessary for cancer cell growth.The purpose of this study was to set a comparison of serine and glycine in patients with esophageal cancer and in healthy people.Materials and Methods: 37 plasma samples were collected from esophageal cancer patients and were referred to Gastrointestinal and Liver Disease Research Center, Firoozgar Hospital, affiliated to Iran University of Medical Sciences, Tehran, Iran.Plasma levels of branched-chain amino acids were measured by HPLC method.Statistics were calculated by SPSS v.16 software.Results: In the patients' group the mean age ± SD was 63±13.64 and 21 (56.8%) were male; while in control group, the mean age ± SD was 64.24±13/08 and %54.1 were male.Glycine levels were significantly increased in esophageal cancer (Pvalue: 0.031) and age (P-value<0.05) but it didn't have significant difference in association with sex (P-value>0.05).However, serine levels in patients with esophageal cancer compared to the healthy group didn't show a significant difference (P-value: 0.610) and also it didn't show a significant difference in association with age (P-value>0.05),sex (P-value>0.05).Conclusion: High concentration of serine and reduced glycine levels in plasma of patients with esophageal cancer could act as a prognostic factor in cancer development.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".