Estimation of Serum Alpha Feto-Protein (AFP), Interlukin-6 and Des--Carboxyprothrombin (DCP) in Case of Hepatocellular Carcinoma.
Bibliographic record
Abstract
Background : Hepatocellular carcinoma (HCC) is one the most common primary malignancy of the liver and represents the third leading cause of cancer-related deaths worldwide. Incidence rates are highest in East Asia and Sub-Saharan Africa. A number of evidence suggests a possible role of interleukin-6 (IL-6), α-Fetoprotein (AFP) and Des-γ-carboxyprothrombin (DCP) in the pathogenesis of hepatocellular carcinoma (HCC). The high DCP may be related to increase tumour behaviour, such as the presence of vascular invasion and intrahepatic metastasis of HCC cells. Patients and Methods : We studied IL-6, AFP and DCP in patients with HCC or in healthy controls. AFP was measured by chemiluminescent immunoassay; Serum IL-6 and DCP were measured by enzyme linked immunosorbent assay in 30 patients with primary hepatocellular carcinoma and 30 normal subjects. Results : IL-6, AFP and DCP were found high in the serum of patients initially diagnosed with HCC (18±9.8), (315.99±594.62) and (26.15±5.01) respectively compared with healthy subjects (4.29±2.10), (3.13±1.27) and (4.25±1.22). A significant positive correlation was found between mean levels of IL- 6 & AFP in HCC (P < 0.05), Combination of IL-6, AFP and DCP improved the sensitivity in diagnosing HCC or predicting future HCC development. Conclusions : IL-6, DCP along with AFP could be considered a promising tumor marker for HCC. DCP is a well recognized tumor marker for the screening and diagnosis of HCC. In particular, the diagnostic value of the test is significantly increased when combined with AFP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".