Clinical and Laboratory Features of <i>Mycobacterium porcinum</i>
Bibliographic record
Abstract
Recent molecular studies have shown Mycobacterium porcinum, recovered from cases of lymphadenitis in swine, to have complete 16S rDNA sequence identity and >70% DNA-DNA homology with human isolates within the M. fortuitum third biovariant complex. We identified 67 clinical and two environmental isolates of the M. fortuitum third biovariant sorbitol-negative group, of which 48 (70%) had the same PCR restriction enzyme analysis (PRA) profile as the hsp65 gene of M. porcinum (ATCC 33776(T)) and were studied in more detail. Most U.S. patient isolates were from Texas (44%), Florida (19%), or other southern coastal states (15%). Clinical infections included wound infections (62%), central catheter infections and/or bacteremia (16%), and possible pneumonitis (18%). Sequencing of the 16S rRNA gene (1,463 bp) showed 100% identity with M. porcinum ATCC 33776(T). Sequencing of 441 bp of the hsp65 gene showed four sequevars that differed by 2 to 3 bp from the porcine strains. Clinical isolates were positive for arylsulfatase activity at 3 days, nitrate, iron uptake, D-mannitol, i-myo-inositol, and catalase at 68 degrees C. They were negative for L-rhamnose and D-glucitol (sorbitol). Clinical isolates were susceptible to ciprofloxacin, sulfamethoxazole, and linezolid and susceptible or intermediate to cefoxitin, clarithromycin, imipenem, and amikacin. M. porcinum ATCC 33776(T) gave similar results except for being nitrate negative. These studies showed almost complete phenotypic and molecular identity between clinical isolates of the M. fortuitum third biovariant D-sorbitol-negative group and porcine strains of M. porcinum and confirmed that they belong to the same species. Identification of M. porcinum presently requires hsp65 gene PRA or 16S rRNA or hsp65 gene sequencing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".