Anti-Anemic and Anti-Dyspepsia Potential of Yogurt with Carao (Cassia grandis) in Rat Model
Bibliographic record
Abstract
Iron deficiency anemia is a significant health problem in developing countries and this is rising, particularly in children and pregnant women. Several therapeutic properties have been attributed to Cassia grandis (carao), including the treatment against anemia, a laxative effect, and the reduction of bleeding. Yogurt is a vehicle for functional ingredients. As a result, this investigation aims to examine the application of Cassia grandis pulp as an anti-anemic and anti-dyspepsia agent in enriched yogurt. Carao pulp powder was added to milk at 0%, 0.5%, 1%, and 3% to produce yogurt. The bioavailability characteristics of iron deficiency anemia were analyzed in albino rats, which were studied for 4 weeks. Other groups of rats were used to set up the dyspepsia model by being fed a high-fat and high-calorie diet. Intestinal propulsion rate, gastric emptying rate, small intestinal contraction, motilin levels, and intestinal muscle tension were analyzed in rats with dyspepsia. Yogurt with 3% carao pulp powder restored ferritin, hemoglobin, total protein and iron at the end of the 4-week feeding period, with significant competition revealed in calcium and zinc absorbance. Furthermore, yogurt with 3% carao pulp powder improved intestinal propulsion rate, gastric emptying rate, small intestinal contraction, motilin levels, and intestinal muscle tension in dyspepsia rats. Carao can be recommended as an anti-anemia supplement in yogurt fortification.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".