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Record W4363677663 · doi:10.1002/star.202200281

Antidiabetic Effect of Chinese yam (<i>Dioscorea opposita</i> Thunb.) in High‐Fat Diet/Streptozotocin‐Induced Diabetic Rats

2023· article· en· W4363677663 on OpenAlexaff
Aizhen Zong, Qianqian Guan, Wenxin Ma, Lina Liu, Min Jia, Fangling Du, Tongcheng Xu

Bibliographic record

VenueStarch - Stärke · 2023
Typearticle
Languageen
FieldMedicine
TopicNatural Antidiabetic Agents Studies
Canadian institutionsMinistry of Agriculture
FundersBeijing Technology and Business UniversityShandong Academy of Agricultural SciencesNational Natural Science Foundation of China
KeywordsGlycated hemoglobinInternal medicineEndocrinologyStreptozotocinDiabetes mellitusMedicineInsulinChemistryType 2 diabetes

Abstract

fetched live from OpenAlex

Abstract This study aims to assess the effect of different doses of Chinese yam (CY) on a high‐fat diet (HFD) and a streptozotocin‐induced diabetic rat model, using resistant starch (RS) as a positive control. Rats in the normal control and diabetes model (DM) groups are fed the standard diet and HFD, respectively. The RS and CY‐intervention groups are fed with a special HFD, in which starch, maltodextrin, and sucrose in the HFD are replaced completely with RS or CY powder in different proportions: 33.33% (1/3), 66.67% (2/3), and 100% respectively. The results show that CY powder can decrease serum levels of total triglycerides, total cholesterol, low‐density lipoprotein cholesterol, fasting blood glucose, and glycated hemoglobin, lower abdominal fat weight and abdominal fat index, increase levels of insulin and hepatic glycogen, and improve glucose tolerance and insulin sensitivity in diabetic rats. In addition, CY reduces oxidative stress and inflammation and reduces spleen weight and spleen index in diabetic rats. Notably, CY shows higher efficacy than RS in glucose tolerance and serum insulin and nitric oxide levels. This study suggests that CY powder may replace RS as a functional food in diabetic diets.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.296
Teacher spread0.283 · 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.

Study designObservational
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

Citations4
Published2023
Admission routes1
Has abstractyes

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