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Record W2316099282 · doi:10.5505/tjtes.2013.65642

The histopathological investigation of the effect on regional and systemic tissues of the application of Medicinal Plant Extract Ankaferd Blood Stopper in deep tissue injuries in Rats

2013· article· en· W2316099282 on OpenAlexaff
Mehmet Okumuş, Kasım Zafer Yüksel, Davut Özbağ, Harun Çıralık, Zeki Yılmaz, Yakup Gümüşalan, Vedat Bakan, Ali Murat Kalender

Bibliographic record

VenueTurkish Journal of Trauma and Emergency Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicHemostasis and retained surgical items
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsMedicineHemostasisConnective tissueHistopathological examinationNeurovascular bundleHistopathologyFemoral veinPathologicalPathologySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: This study was planned to evaluate both the histopathological changes under light microscope as well as the systemic organ effects following application of Ankaferd Blood Stopper® (ABS) (a mixture of five plant extracts) in an animal model of deep tissue hemorrhage. METHODS: A total of 50 Wistar Albino rats were divided into five groups of 10 rats each. The rats underwent femoral vein puncture and were treated with ABS tampon, ABS spray, or Surgicel, and one group was left untreated. After two weeks, each group underwent partial tissue excision from the same femoral region as well as from the brain, heart, kidney, and liver. RESULTS: The specimens from all groups were obtained from the femoral region after two weeks and evaluated under light microscope. The light microscope revealed no histopathological changes in neurovascular structures or in deep connective tissues in any of the groups. CONCLUSION: ABS provided hemostasis and was observed to stop bleeding. There were no histopathological changes at the tissue level and no pathological effects in other organs tissues under light microscope, and the remote organ tissue remained clear.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.000
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 head0.021
GPT teacher head0.265
Teacher spread0.244 · 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 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

Citations7
Published2013
Admission routes1
Has abstractyes

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