Genetics of Infectious and Inflammatory Diseases: Overlapping Discoveries from Association and Exome-Sequencing Studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Genome technologies have defined a complex genetic architecture in major infectious, inflammatory, and autoimmune disorders. High density marker arrays and Immunochips have powered genome-wide association studies (GWAS) that have mapped nearly 450 genetic risk loci in 22 major inflammatory diseases, including a core of common genes that play a central role in pathological inflammation. Whole-exome and whole-genome sequencing have identified more than 265 genes in which mutations cause primary immunodeficiencies and rare forms of severe inflammatory bowel disease. Combined analysis of inflammatory disease GWAS and primary immunodeficiencies point to shared proteins and pathways that are required for immune cell development and protection against infections and are also associated with pathological inflammation. Finally, sequencing of chromatin immunoprecipitates containing specific transcription factors, with parallel RNA sequencing, has charted epigenetic regulation of gene expression by proinflammatory transcription factors in immune cells, providing complementary information to characterize morbid genes at infectious and inflammatory disease loci.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 | 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 it