Transmission Electron Microscopy of XDR Mycobacterium tuberculosis Isolates Grown on High Dose of Ofloxacin
Bibliographic record
Abstract
The aim of the study was to investigate behavior of resistant Mycobacterium tuberculosis (MTB) isolates under a high dose of ofloxacin and its morphological changes. 19 extensively drug resistant (XDR) clinical isolates of MTB were grown on Löwenstein-Jensen medium containing progressively increasing concentrations of ofloxacin (2, 4, 8, 16, 32 mg/L). Ultra-structure analyses of resistant isolates grown on ofloxacin were conducted by transmission electron microscopy (TEM). Fixation was carried out by 4% glutaraldehyde in 0.1 M sodium cacodylate buffer on 300 mesh carbon formvar copper grid. The samples were negatively stained with uranium acetate suspension. All19XDRMTBisolatesweregrownandformedcoloniessuccessfullyon2,4,8mg/L,sevenisolates on16mg/L,andfourisolateson32mg/Lofloxacin. Morphologicalchangesandunusualformswere detected in 8, 16 and 32 mg/L ofloxacin at 43%, 76.5% and 81% of cells, respectively. Swollen form (protoplast like), ghost-like cell, degraded forms, and in a few cases, detached cytoplasm from cell wall were clearly detected in high drug concentrations in comparison to control. Changes in morphology were increased with increasing ofloxacin concentrations (p < 0.05). Some XDR isolates could be successfully grown on high doses of ofloxacin (32 mg/L), but with changes in morphology. It was concluded that several magnitudes of the drug doses could not prevent growth of drug resistant forms.
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".