Bibliographic record
Abstract
Introduction: Mycobacterium avium complex consists of M. intracellulare and the subspecies of M. avium subsp. avium, M. avium subsp. paratuberculosis and M. avium subsp. hominissuis. Despite their taxonomic relationship, these subspecies are organisms with distinct phenotypes, ranging from environmental bacteria that cause infections in immunocompromised hosts to pathogens targeting birds and ruminants. The reasons for the variable pathogenicity and host range of M. avium subspecies are not known. We hypothesize that genotypic differences between M. avium subsp. avium and M. avium subsp. paraturberculosis can explain different pathogenic outcomes. Methods: We used tri-genomic comparisons to look for DNA fragments unique to each subspecies. We also used an acute model of mouse infection to determine different phenotypic outcomes in response to infection with different Mycobacterium subspecies. results: Through tri-genomic comparisons we identified genetic regions of interest that may contain genes to explain phenotypic or pathogenic differences among subspecies. In an 8 week course infection, mice infected with M. avium subspecies avium had the highest bacterial burden in their spleens and livers. at the same time, mice infected with M. avium subspecies paraturberculosis had the lowest bacterial burden. discussion: Differences in the genomic sequences of the M. avium subspecies suggests that these sequences encode pathogenic factors. Consequently, this study shows that the sequencing of M. avium subspecies genomes can be useful for predicting and explaining variation in pathogenesis.
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.
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 | 0.000 | 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) | 0.001 | 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".