Whole Exome Sequence Analysis for Inborn Errors of IL‐12/IFN‐<i>γ</i> Axis in Patient with Recurrent Typhoid Fever
Bibliographic record
Abstract
Background . The IL‐12/IFN‐ γ axis pathways play a vital role in the control of intracellular pathogens such as Salmonella typhi . Objective . The study is aimed at using whole exome sequencing (WES) to screen out genetic defects in IL‐12/IFN‐ γ axis in patients with recurrent typhoid fever. Methods . WES using next‐generation sequencing was performed on a single patient diagnosed with recurrent typhoid fever. Following alignment and variant calling, exomes were screened for mutations in 25 genes that are involved in the IL‐12/IFN‐ γ axis pathway. Each variant was assessed by using various bioinformatics mutational analysis tools such as SIFT, Polyphen2, LRT, MutationTaster, and MutationAssessor. Results . Out of 25 possible variations in the IL‐12/IFN‐ γ axis genes, only 2 probable disease‐causing mutations were identified. These variations were rare and include mutations in IL23R and ZNFX I. Other pathogenic mutations were found, but they were not considered likely to cause disease based on various mutation predictors. Conclusion . Applying WES to the patient with recurrent typhoid fever detects variants that are not much important as other genes in the IL‐12/IFN‐ γ axis. Results of the current study suggest that a large population sizes would be needed to examine the functional relevance of IL‐12/IFN‐ γ axis genes with recurrent typhoid fever.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.000 | 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".