Differential biocide susceptibility of the multiple genotypes of Mycobacterium immunogenum
Bibliographic record
Abstract
The non-tuberculous mycobacterium Mycobacterium immunogenum colonizes industrial metalworking fluids (MWFs) presumably due to its relative resistance to the currently practiced biocides and has been implicated in occupational respiratory hazards, particularly hypersensitivity pneumonitis. With an aim to understand its inherent biocide susceptibility profile and survival potential in MWF, five different genotypes of this organism, including a reference genotype (700506) and four novel test genotypes (MJY-3, MJY-4, MJY-10 and MJY-12) isolated in our recent study from diverse MWF operations were evaluated. For this, two commercial biocide formulations, Grotan (Hexahydro-1,3,5-tris(2-hydroxyethyl)-s-triazine) and Kathon (5-chloro-2-methyl-4-isothiazolin-3-one) currently practiced for the control of microorganisms, including mycobacteria, in MWF operations were tested. Effect of the fluid matrix on the biocide susceptibility was investigated for the synthetic (S) and semi-synthetic (SS) MWF matrices. In general, the minimum inhibitory concentration values were higher for the HCHO-releasing biocide Grotan than the isothiazolone biocide Kathon. All genotypes (except the reference genotype) showed lower susceptibility in SS as compared to S fluid matrix for Grotan. However, in case of Kathon, a greater susceptibility was observed in SS fluid for majority of the test genotypes (MJY-3, 4 and 10). The test genotypes were more resistant than the reference genotype to either biocide in both fluid types. Furthermore, the individual genotypes showed differential biocidal susceptibility, with MJY-10 being the most resistant. These observations emphasize the importance of using the resistant genotypes of M. immunogenum as the test strains for formulation or development and evaluation of existing and novel biocides, for industrial applications.
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 | 0.001 |
| 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) | 0.000 | 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 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".