Investigation of α-Cellulose Content of Sugarcane Scrappings and Bagasse as Tablet Disintegrant
Bibliographic record
Abstract
The aim of this study is to investigate the physicochemical and disintegrant properties of α – cellulose obtained from sugarcane scrapings and bagasse. The mechanical and release properties of paracetamol tablets containing the extracted celluloses and two standard disintegrants- corn starch B.P and microcrystalline cellulose – were determined using crushing strength, friability, disintegration time, the time taken for 50% (T50) and 90% (T90) drug dissolution as assessment parameter. α – cellulose obtained from sugarcane scrapings and bagasse possess better flow properties than cornstarch and microcrystalline cellulose and are capable of absorbing up to five times their own weight in water and swell considerably. α – cellulose obtained from sugarcane scrapings and bagasse have high moisture sorption capacity and they formed relatively softer tablets which became increasingly harder as their concentration increased. All the tablets formulated with cellulose derived from sugarcane scrapings and bagasse passed the official disintegration test for uncoated tablets. Cellulose obtained from sugarcane bagasse had superior disintegrant property to cornstarch and microcrystalline cellulose while cellulose obtained from sugarcane scrapings showed comparable disintegrant property to microcrystalline cellulose. Tablets containing 2.5% w/w cellulose derived from sugarcane scrapings and 5.0% w/w cellulose derived from sugarcane bagasse gave more optimum result as tablet disintegrant. Formulations containing cellulose derived from sugarcane scrapings and bagasse show faster drug release (lower T50 and T90) than tablets containing corn starch and microcrystalline cellulose. There was a linear correlation between T90 and disintegration time (r = 0.976, p< 0.05) for tablets formulated with cellulose derived from sugarcane scrapings. Results show that α – cellulose obtained from sugarcane bagasse and scrapings are potentially useful as disintegrants in tablet formulations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".