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Record W2001726875 · doi:10.5539/ijb.v4n1p81

Tamarind Seed Extract Enhances Epidermal Wound Healing

2011· article· en· W2001726875 on OpenAlexvenueno aff
Mohd Yusof Mohamad, Haris B. Akram, Dinie Najwa Bero, Mohammad Tariqur Rahman

Bibliographic record

VenueInternational Journal of Biology · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBee Products Chemical Analysis
Canadian institutionsnot available
FundersInternational Islamic University Malaysia
KeywordsTanninWound healingPhytochemicalSaponinEthanolFlavonoidChemistryTraditional medicineMethanolSalinePhosphate buffered salineAntioxidantPolyphenolFood scienceChromatographyMedicineBiochemistrySurgeryOrganic chemistry

Abstract

fetched live from OpenAlex

Traditional healing power of tamarind fruits and the established antioxidant activity of the seeds drive the present study. Wound healing efficiency of tamarind seed was evaluated. Different solvents: phosphate buffer saline (PBS), water, methanol and ethanol were used to prepare the extract. Circular wound was inflicted on the nape. 10 µl of 5 µg/ml of extract was applied topically twice daily. Wound area was measured using Adobe ®Photoshop C3 Extended version and the percentage of wound reduction was calculated. PBS extract treatment induced complete wound healing in shortest period (10 days) while water extract, methanol extract and Solcoseryl ointment treatment induced complete wound healing in 11 days and control groups without any treatment took 14 days to heal. Phytochemical screening and Bradford method for protein quantification reveals the presence of alkaloid, saponin and tannin in all samples except PBS extract which tested negative to tannin. Flavonoid tested positive in methanol and ethanol extracts.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.042
GPT teacher head0.273
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations37
Published2011
Admission routes1
Has abstractyes

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