Efek Infusa Daun Salam (Syzygium polyanthum) Terhadap Penurunan Kadar Kolesterol Total Darah Tikus Jantan Galur Wistar Model Dislipidemia
Bibliographic record
Abstract
Latar Belakang. Di seluruh dunia penyakit kardiovaskuler (PKV) merupakan penyebab kematian utama, menurut estimasi para ahli badan kesehatan sedunia (WHO), setiap tahun sekitar 50% penduduk dunia meninggal akibat penyakit jantung dan pembuluh darah. Banyak faktor yang mempengaruhi terjadinya penyakit kardiovaskuler tersebut salah satunya adalah dislipidemia. Selain menggunakan obat penurun kolesterol, tanaman obat seperti daun salam menjadi pilihan dalam mencegah dan mengobati dislipidemia Tujuan Penelitian. Mengetahui efek daun salam dan mengetahui dosis paling optimal dalam menurunkan kadar kolesterol total darah pada tikus jantan galur wistar model dislipidemia. Metode. Hewan coba yaitu tikus jantan galur wistar dengan berat badan 200 – 300 gram, jumlah 25 ekor, dibagi dalam 5 kelompok (n=5), yang kemudian diinduksi diet tinggi lemak dan Propiltiourasil (PTU) 0,01% selama 2 minggu kemudian dilanjutkan dengan pemberian infusa daun salam per oral dengan dosis 5%, 10%, 20% dan simvastatin selama 2 minggu. Pengamatan penurunan kadar kolesterol dilakukan sebelum dan setelah pemberian infusa daun salam selama 2 minggu. Data diuji secara statistik menggunakan uji Anova dan Post Hoc LSD. Hasil. Pada penelitian didapatkan pemberian infusa daun salam pada kelompok perlakuan menyebabkan penurunan kolesterol total secara bermakna (p<0,05) pada semua dosis. Efek tersebut tidak berbeda antara masing-masing dosis infusa daun salam dan simvastatin. Simpulan. Penggunaan infusa daun salam dengan dosis 5%, 10% dan 20% memiliki efek menurunkan kadar kolesterol total darah tikus, dan memiliki efek yang sama dengan simvastatin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".