Antimycobacterial susceptibility evaluation of rifampicin and isoniazid benz-hydrazone in biodegradable polymeric nanoparticles against Mycobacterium tuberculosis H37Rv strain
Bibliographic record
Abstract
Sushruta S Hakkimane,1 Vishnu Prasad Shenoy,2 Santosh L Gaonkar,3 Indira Bairy,4 Bharath Raja Guru1,5 1Department of Biotechnology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India; 2Department of Microbiology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India; 3Department of Chemistry, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India; 4Department of Microbiology, Melaka Manipal Medical College, Manipal Academy of Higher Education, Manipal, India; 5Manipal McGill Center for Infectious Diseases, Manipal Academy of Higher Education, Manipal, India Introduction: Tuberculosis (TB) is the single largest infectious disease which requires a prolonged treatment regime with multiple drugs. The present treatment for TB includes frequent administration of a combination of four drugs for a duration of 6 months. This leads to patient’s noncompliance, in addition to developing drug-resistant strains which makes treatment more difficult. The formulation of drugs with biodegradable polymeric nanoparticles (NPs) promises to overcome this problem. Materials and methods: In this study, we focus on two important drugs used for TB treatment – rifampicin (RIF) and isoniazid (INH) – and report a detailed study of RIF-loaded poly lactic-co-glycolic acid (PLGA) NPs and INH modified as INH benz-hydrazone (IH2) which gives the same therapeutic effect as INH but is more stable and enhances the drug loading in PLGA NPs by 15-fold compared to INH. The optimized formulation was characterized using particle size analyzer, scanning electron microscopy and transmission electron microscopy. The drug release from NPs and stability of drug were tested in different pH conditions. Results: It was found that RIF and IH2 loaded in NPs release in a slow and sustained manner over a period of 1 month and they are more stable in NPs formulation compared to the free form. RIF- and IH2-loaded NPs were tested for antimicrobial susceptibility against Mycobacterium tuberculosis H37Rv strain. RIF loaded in PLGA NPs consistently inhibited the growth at 70% of the minimum inhibitory concentration (MIC) of pure RIF (MIC level 1 μg/mL), and pure IH2 and IH2-loaded NPs showed inhibition at MIC equivalent to the MIC of INH (0.1 μg/mL). Conclusion: These results show that NP formulations will improve the efficacy of drug delivery for TB treatment. Keywords: rifampicin nanoparticles, isoniazid hydrazone, drug susceptibility, Mycobacterium 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 | 0.000 | 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".