Isoniazid adsorption and release by Cloisite and Laponite: An effect of surface charge
Bibliographic record
Abstract
Two different smectites, Cloisite (CL), a montmorillonite, and Laponite (LP), a synthetic hectorite-like clay, were investigated for their efficiency in isoniazid (INH) adsorption and release mechanisms. Adsorption was conducted at an acidic pH = 2 to leverage the protonation effect of INH. At acidic pH, the clays exhibited different surface charges: −12 mV for CL and −2 mV for LP, indicating a stronger negative charge on CL. These changes affected the INH incorporation and release, increasing the attachment on the clay surface. CL, the clay with the lowest surface charge, manifested a higher incorporation of INH, 115 mg/g, and a more controlled release of INH in the stomach environment (less than 8%, against 25% for LP). These values compared favorably with those cited in the literature and demonstrated a potential for drug delivery. Although X-ray diffraction (XRD) did not show an increase in the basal distance for either clay, Fourier-transform infrared spectroscopy (FTIR) and thermogravimetry analysis (TGA) showed the interaction between clay and drug after the incorporation. Compared to literature, the hybrids developed in this study exhibited higher drug loading and a more effective pH-responsive release, particularly at pH 2. This is especially important for oral drug delivery, where protecting the drug in the stomach and enabling its release in the intestine can enhance bioavailability. These findings underscore the potential of smectite clays as promising candidates for INH-controlled release and contribute to identifying key-clay characteristics for effective oral drug delivery systems.
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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) | 0.001 | 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".