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Record W4319053069 · doi:10.1080/j157v04n02_01

Antioxidant Activity of the Aqueous Extracts of Spicy Food Additives—Evaluation and Comparison with Ascorbic Acid in<i>In Vitro</i>Systems

2004· article· en· W4319053069 on OpenAlexaboutno aff
Srinath Satyanarayana, G. S. Sarma, N. Srinivas, G. V. Subba Raju

Bibliographic record

VenueJournal of Herbal Pharmacotherapy · 2004
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsnot available
Fundersnot available
KeywordsAscorbic acidAntioxidantChemistryIn vitroAqueous solutionFood scienceFood additiveBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

AbstractThe antioxidant activity of the aqueous extracts of five umbelliferous fruits-caraway (Carum carvi), coriander (Coriandrum sativum), cumin (Cuminum cyminum), dill (Anethum graveolens) and fennel (Foeniculum vulgare)-were investigated in comparison with the known antioxidant ascorbic acid in in vitro studies. The amount of aqueous extract of these five umbelliferous fruits and ascorbic acid needed for 50% scavenging of superoxide radicals was found to be 105 μg (cara way), 370 μg (coriander), 220 μg (cumin), 190 μg (dill), 205 μg (fennel) and 260 μg (ascorbic acid). The amount needed for 50% inhibition of lipid peroxide was 2100 μg (caraway), 4500 μg (coriander), 4300 μg (cumin), 3100 μg (dill), 4600 μg (fennel) and 5000 μg (ascorbic acid). The quantity needed for 50% inhibition of hydroxyl radicals was 1150 μg (caraway), 1250 μg (coriander), 470 μg (cumin), 575 μg (dill), 700 μg (fennel) and 4500 μg (ascorbic acid). The daily use of the above fruits in various forms is very common in India and the present study revealed strong antioxidant activity of their extracts that was superior to known antioxidant ascorbic acid and indicate their intake may be beneficial as food additives.Key Words: Spicesumbelliferous fruit extractantioxidantfood additivesascorbic acidfree radicals Additional informationNotes on contributorsS. SatyanarayanaF. U. Alakbarov is Head Scientific Officer, expert in the Oriental and Folk Medicine, Institute of Manuscripts of the Azerbaijan Academy of Sciences, 8 Istiglaliyat str., Baku, 370001, Azerbaijan.At the time of writing Liya Davydov was PharmD candidate, College of Pharmacy and Allied Health Professions, St. John's University. Currently, she is Pharmacy Practice Resident, Mount Sinai Medical Center, New York, NY.Ila Mehra Harris is Assistant Professor, Department of Pharmaceutical Care & Health Systems, College of Pharmacy, and Clinical Assistant Professor, Department of Family Practice & Community Health, Medical School, University of Minnesota, Minneapolis, MN.Colin J. Briggs is Professor of Pharmacy, Faculty of Pharmacy, University of Manitoba. Recently he completed a secondment to Health Canada, as Senior Science Advisor in the Therapeutics Products Programme with special responsibility for complementary medicines.Gemma Briggs is Research Assistant, IMPACT, The Injury Prevention Centre of Children's Hospital, 501G-715 John Buhler Research Centre, Winnipeg, MB, Canada.Mary Chavezis Professor of Pharmacy Practice, Director of Complementary Medicine Education and Research, The Center for the Advancement of Pharmacy Practice, Midwestern University, College of Pharmacy Glendale, Glendale, AZ 85308.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.078
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.026
GPT teacher head0.318
Teacher spread0.292 · 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 teacher head, 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

Citations65
Published2004
Admission routes1
Has abstractyes

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