CSIG-10IMMUNIHISTOCHEMICAL STUDY OF THE EXPRESSION LEVELS OF NF-kB AND ITS REGULATORS ING-4, AEG-1 IN GLIOMAS
Bibliographic record
Abstract
BACKROUND: Nuclear factor-kappa B (NF-kB is implicating in many cellular processes and its aberrant levels have been detected in many malignancies. Inhibitor of growth-4 (ING-4) and astrocytes elevated genes (AEG-1) are important regulators of NF-kB activity. This study aimed to evaluate the expression levels of p65, p50 subunits of NF-kB as well as its regulators ING-4 and AEG-1 in human gliomas tissues. METHODS: We examined formalin-fixed, paraffin-embedded tumor samples from 101 gliomas patients with immunohistochemical technique using primary antibodies for p50, p65, ING-4, AEG-1. The mean age of the patients was 56 yo. The tissues were categorized to four grade according to the World Health Organization criteria: 11(10.8%) low grade gliomas, 18(17.8%) grade III gliomas and 72(71.3%) glioblastomas. We used as a control normal brain cortex from 15 autopsy cases. RESULTS: Nuclear, cytoplasmic and total immunoreaction for p65 was significantly higher in grade IV comparing to grade III as well as in grade III comparing to LGG (p = 0.01 for nuclear, p = 0.003 for cytoplasmic, p = 0.001 for total expression). Strong correlations were observed in immunoreactivity for p50 subunit with grades with higher expression in high grade comparing to LGG (P= 0.09). Normal brain tissues didn't display any expression of NF-kB subunits. The expression levels of ING-4 was reversely correlated to tumor grade and was higher in LGG comparing to high grade (p = 0.07) and the normal brain tissue expressed high levels of ING-4. The expression levels of AEG-1 was higher in high grade gliomas comparing with lower grade (0.016) and minimal in normal brain. No correlation noted between age groups and genders and expression levels of all molecules. CONCLUSIONS: The expression of NF-kB and its regulating factors seems to be important role in gliomas behavior. More studies are required in order to evaluate the role of these molecules to gliomagenesis and glioma progression.
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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 | 0.000 |
| 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) | 0.004 | 0.001 |
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".