Biological Evaluation of Wheat-Salty Extract, Milk-Wheat Solution and Fermented Soymilk for Treatment of Castor-Oil Induced Diarrhea in Rats
Bibliographic record
Abstract
Functional food or medicinal food is any healthy food claimed to have a health-promoting or disease-preventing property beyond the basic function of supplying nutrients. Three nutritional preparations including wheat powder salt solution (WPSS), milk-wheat solution (MWS), fermented milk (FM) and fermented soymilk (FSM) were evaluated for their anti-diarrheal activity by oral administration in model of Castor oil induced diarrhea in rats. Oral rehydration solution (ORS) was used as positive control. The fermented products were prepared using a mixture of Lactobacillus acidophilus ATCC 4356: and Bifidobacterium bifidum ATCC 700541 (1:1 v/v) to obtain a final level of 107-8 CFU/ml after incubation at 37°C. Beside the gain body weight (BW), certain biochemical parameters such as total protein, albumin, globulin, urea, creatinine, alanine amino-transferase (ALT), aspartate amino-transferase (AST), sodium, potassium, magnesium, iron and phosphorus were determined. According to follow the diarrheal symptoms including stool frequency, stool characteristics and BW, rats administrated with FSM were recovered from diarrhea (on the 3rd day) faster than other groups followed by those subjected with FM and CY. The ORS-positive control group rats were recovered on the 6th day, while diarrheal symptoms still appeared on the negative control rats (subjected with basal diet only; without ORS) with 16% death rate. Minerals, especially sodium, potassium, magnesium and phosphorus, were the most significant biochemical parameters for following recovery from diarrhea. The normal levels of these minerals were recovered in the blood serum at the end of experiment in rats administrated with the fermented products (FSM, FM and CY). Some renal functional parameters were suggested to follow diarrhea, but all studied liver functional parameters were not significantly recommended.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".