Data on changes of NF-κB gene expression in liver and lungs as a biomarker and hepatic injury in CLP-induced septic rats
Bibliographic record
Abstract
Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is a ubiquitous transcription factor, which plays a key role in regulating immune response against infection. Increased and/or prolonged activation of NF-κB has been linked to cancer, inflammatory, autoimmune diseases and viral infection. The purpose of this set of data was to evaluate NF-κB gene expression in cecal ligation and puncture (CLP)- induced septic rats and associated hepatic cell changes. Here, we provide the information about the evaluation of NF-κB gene expression using Real-time PCR and histopathological data of liver-related to our study published in the Turkish Journal of Medical Sciences [1]. Also, the information of the primers and more details about gene expression evaluation by real-time PCR of the targeted gene is provided. The data present here introduced another biomarker in liver and lung of CLP- induced septic rats and also confirmed hepatic dysfunction based on the pathological data. The histopathologic assessment showed normal condition in control group, mild infiltration of neutrophils in the liver parenchyma and portal tracts in LAP group (laparotomy) but severe congestion, severe neutrophil infiltration in the liver parenchyma and portal tracts in the CLP group. The data from real-time PCR showed that NF-κB expression was significantly increased in the CLP group compared with the control and LAP group, so it can be a biomarker for (CLP)- induced sepsis. This set of data and our previous study underscored the powerful potential of using the real-time PCR method to determine the involvement of genes such as MPO, CD177, and NF-κB in infectious diseases like sepsis.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".