HISTOLOGICAL AND BIOCHEMICAL EVALUATION OF WOUND REGENERATION POTENTIAL OF TERMINALIA CHEBULA FRUITS
Bibliographic record
Abstract
The objective of this investigation was to evaluate the histological and biochemical evaluation of wound healing potential of the ethanol extract of Terminalia chebula fruits. Antibacterial activity and in vivo wound healing properties of the ethanol extract on infected lesions by reference strains of Staphylococcus aureus ATCC 25923 and Pseudomonas aeruginosa ATCC 27853 in Wistar rats were investigated. A total of 32 rats were divided into two groups such as control group and Group treated with an extract of T. chebula. Control groups infected, but not treated with any medicine. The ethanol extract has a real healing potential and antibacterial activity against reference strains used. In addition, Histological analysis of Granulated tissue from treated group confirmed the regeneration of dermal wound with well-formed dermis and epidermis in the skin and then a tight bundle of synthesized collagen in the tissue. Therefore, these antibacterial properties and wound healing activities engage T. chebula in the process of developing an improved traditional medicine as alternative for existing therapy. Keywords: Wound infection, In vivo studies, Masson’s trichrome staining and collagen.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".