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Record W4214650653 · doi:10.51887/jpfi.v10i2.1410

AKTIVITAS ANTIDIABETES EKSTRAK ETANOL DAUN DAN BATANG SIDAGURI (Sida rhombifolia) TERHADAP MODEL HEWAN DIABETES TIPE 2

2021· article· id· W4214650653 on OpenAlexaff
Aulia Nurfazri Istiqomah, Widhya Aligita, Hendra Mahakam Putra, Denny Galang, Hapipah Nurjamilah

Bibliographic record

VenueJurnal Penelitian Farmasi Indonesia · 2021
Typearticle
Languageid
FieldMedicine
TopicNatural Antidiabetic Agents Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsTraditional medicinePhysicsMedicine

Abstract

fetched live from OpenAlex

Diabetes merupakan penyakit yang ditandai dengan meningkatnya kadar glukosa dalam darah yang terjadi karena kurangnya produksi insulin atau berhentinya produksi insulin dalam tubuh. Herba Sidaguri (Sida rhombifolia) diketahui memiliki aktifitas sebagai antidiabetes. Penelitian ini dilakukan untuk mengevaluasi aktivitas antidiabetes ekstrak etanol daun dan batang sidaguri (Sida rhombifolia) terhadap model hewan diabetes tipe 2 dan mencari bagian mana yang paling efektif sebagai antidiabetes. Metode penelitian ini merupakan penelitian eksperimental secara in vivo. Mencit dibagi menjadi 9 Kelompok yaitu kelompok kontrol negative, kontrol positif, Glibenklamid 0,65 mg/KgBB, ekstrak daun sidaguri dosis 3,5; 7; dan 14 mg/KgBB, serta ekstrak batang sidaguri dosis 3,5; 7; dan 14 mg/KgBB. Pengujian dilakukan secara kuratif, hewan uji kecuali kontrol negatif, diberikan induksi aloksan monohidrat 80 mg/KgBB melalui rute intravena, kemudian setelah 3 hari pasca induksi, dilakukan pemeriksaan kadar glukosa darah puasa. Perlakuan dilanjutkan dengan pemberian terapi selama 14 hari melalui rute peroral. Parameter uji pada penelitian ini adalah pengukuran kadar glukosa daraah pada hari ke 0, 7, dan 14, serta histopatologi organ pancreas. Dari hasil pengujian diperoleh bahwa ekstrak yang memberikan efek antidiabetes terbaik adalah ekstrak etanol daun sidaguri dosis 14 mg/KgBB namun belum mampu memperbaiki kondisi sel-sel pankreas sepenuhnya.

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), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.261
Teacher spread0.241 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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