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Record W2810004087 · doi:10.3390/molecules23071561

Morphological Characteristics, Nutrients, and Bioactive Compounds of Zizania latifolia, and Health Benefits of Its Seeds

2018· review· en· W2810004087 on OpenAlexaff
Ning Yan, Yongmei Du, Xinmin Liu, Cheng Chu, John Shi, Hongbo Zhang, Yanhua Liu, Zhongfeng Zhang

Bibliographic record

VenueMolecules · 2018
Typereview
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgricultural Science and Technology Innovation ProgramChinese Academy of Agricultural Sciences
KeywordsNutrientHealth benefitsBotanyBiologyChemistryTraditional medicineEcologyMedicine

Abstract

fetched live from OpenAlex

Zizania latifolia (tribe Oryzeae Dum., subfamily Oryzoideae Care, family Gramineae) is native to East Asian countries. The seeds of Z. latifolia (Chinese wild rice) have been consumed as a cereal in China for >3000 years. Z. latifolia forms swollen culms when infected with Ustilago esculenta, which is the second most-cultivated aquatic vegetable in China. The current review summarizes the nutrients and bioactive compounds of Z. latifolia, and health benefits of its seeds. The seeds of Z. latifolia contain proteins, minerals, vitamins, and bioactive compounds, the activities of which—for example, antioxidant activity—have been characterized. Various health benefits are associated with their consumption, such as alleviation of insulin resistance and lipotoxicity, and protection against cardiovascular disease. Chinese wild rice may be used to prevent and treat metabolic disease, such as diabetes, obesity, and cardiovascular diseases. Various compounds were isolated from the swollen culm, and aerial parts of Z. latifolia. The former suppresses osteoclast formation, inhibits growth of rat glioma cells, and may act as antioxidants and immunomodulators in drugs or foods. The latter exerts anti-fatigue, anti-inflammatory, and anti-allergic effects. Thus, Z. latifolia may be used to produce nutraceuticals and functional foods.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.795
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.066
GPT teacher head0.334
Teacher spread0.269 · 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 designOther design
Domainnot available
GenreReview

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

Citations68
Published2018
Admission routes1
Has abstractyes

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