Reduced expression of members of the MHC-I antigen processing machinery in ethnic Uighur women with cervical cancer in the Xinjiang region of China
Bibliographic record
Abstract
OBJECTIVE: Cervical cancer is a major cause of mortality in Uighur women compared with Han women in the Xinjiang region of China. Although a reduction in the class i major histocompatibility complex (mhc-i) antigen processing machinery (apm) is associated with the development of cervical cancer, the mhc-i apm has not been studied in this particular group of women, who have the highest incidence rate of cervical cancer in China. STUDY DESIGN: We used immunohistochemical staining and polymerase chain reaction amplification of viral dna from infection with the human papilloma virus (hpv) to study the expression of members of the mhc-i apm in cervical cancer sections collected from Uighur and Han women and in cervicitis samples from age-matched counterparts. RESULTS: Expression of the molecules of interest was compared between two ethnic groups, and expression of transporter associated with antigen processing 1 and 2, heat shock protein 90, and calnexin were found to be reduced even more significantly in Han women with cervical cancer than in Uighur women with same disease. However, compared with Han women, Uighur women had a higher rate of infection with hpv 16. CONCLUSIONS: The mhc-i apm were reduced in cervical cancer, with heterogeneity in the two ethnic groups. The reduction was more pronounced in Han women, who less frequently had hpv 16 infection, suggesting possible differences in the roles of members of the mhc-i apm and in the mechanisms of cervical cancer development in these two ethnic groups despite residence in the same region of China.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".