Fibrotic Response as a Distinguishing Feature of Resistance and Susceptibility to Pulmonary Infection with <i>Mycobacterium tuberculosis</i> in Mice
Bibliographic record
Abstract
The differential susceptibility of inbred mouse strains DBA/2J (susceptible) and C57BL/6J (resistant) to pulmonary tuberculosis following aerosol infection is under complex genetic control. In this report, transcriptional profiling with RNAs from Mycobacterium tuberculosis-infected lungs was used to investigate the physiological response, cell type, and biochemical pathways underlying differential susceptibility to infection. Statistical analysis of cDNA-based microarrays revealed that 1,097 transcripts showed statistically significant changes in abundance (changes of > or = 1.5-fold) in at least one of four experimental group comparisons (C57BL/6J [day 0] versus DBA/2J [day 0] mice, C57BL/6J [day 90] versus DBA/2J [day 90] mice, C57BL/6J [day 90] versus C57BL/6J [day 0] mice, or DBA/2J [day 90] versus DBA/2J [day 0] mice). A group of genes showing very high degrees of significance (changes of > or = 2.0-fold) displayed enrichment for transcripts associated with tissue remodeling and the fibrotic response. The differential expression of fibrotic response genes (Sparc, Col1a1, Col1a2, Col4a1, and Col4a2) in the infected lungs of the two mouse strains was validated by another microarray platform (Affymetrix oligonucleotide chips) and by reverse transcription-PCR. Furthermore, the differential expression of additional genes known to be associated with fibrosis (Mmp2, Timp1, and Arg1) was also validated by these approaches. Overall, these results identify the differential fibrotic response as a pathological basis for the high susceptibility of DBA/2J mice to pulmonary tuberculosis.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".