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Record W2944236765 · doi:10.1139/cjpp-2019-0141

Sorafenib-loaded PAMAM dendrimer attenuates liver fibrosis and its complications in bile-duct-ligated rats

2019· article· en· W2944236765 on OpenAlexvenueno aff
Fatemeh Nabavizadeh, Mehdi Ardestani, Mahshid Panahi, Soheila Adeli, Hedayat Samandari, Ghorbangol Ashabi

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2019
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsSorafenibMedicineHepatocellular carcinomaPharmacologyInternal medicineAscitesLiver cancerChemistryEndocrinology

Abstract

fetched live from OpenAlex

We assessed the effect of sorafenib-loaded polyamidoamine (PAMAM) dendrimer on liver fibrosis induced by bile duct ligation (BDL). Male Wistar rats were divided into 9 groups: intact, sham, DMSO + BDL, BDL, sorafenib (30 mg/kg), sorafenib (60 mg/kg), PAMAM + BDL, sorafenib (30 mg/kg) + PAMAM + BDL, sorafenib (60 mg/kg) + PAMAM + BDL. BDL was induced and then rats were treated daily with sorafenib and (or) PAMAM for 4 weeks. Improvement of liver was detected via assessment of ascites formation, collagen deposition, liver blood flow, vascular endothelial growth factor level, and blood cells count. Sorafenib-loaded PAMAM dendrimer in both 30 and 60 mg/kg doses reduced ascites formation, reduced collagen deposition, and improved drug-induced hematological side effects of sorafenib alone in comparison with sorafenib-alone treatment. Sorafenib-loaded PAMAM dendrimer increased liver blood flow compared with sorafenib-received groups. Sorafenib-loaded PAMAM dendrimer reduced BDL-induced liver injury compared with sorafenib-received groups. Moreover, sorafenib-loaded PAMAM dendrimer decreased vascular endothelial growth factor level in serum and liver tissue in comparison with sorafenib-received groups. Sorafenib-loaded PAMAM dendrimer profoundly improved the therapeutic effects of sorafenib in BDL rats.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.024
GPT teacher head0.281
Teacher spread0.257 · 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 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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and PharmacologySame topicLiver physiology and pathologyFrench-language works237,207