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Record W2111707079 · doi:10.25011/cim.v34i6.15893

Histopathological effects of fibrin glue on penile fracture in a rat model

2011· article· en· W2111707079 on OpenAlexvenueno aff
Cemal Taşdemir, Emine Şamdancı, Muhammet Gökhan Turtay, Cemal Fırat, Hakan Oğuztürk, Hulya Ozdemir

Bibliographic record

VenueClinical and investigative medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsnot available
Fundersnot available
KeywordsFibrin glueMedicineGLUEFibrosisPenisFibrinSurgeryWound healingFibrin Tissue AdhesiveInflammationAnatomyPathologyInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate both histopathological effects and potential clinical application of fibrin glue on the penile cavernosal tissue. METHODS: Experimental penile fracture was formed by incising from the proximal dorsal side of the penis in 32 Wistar Albino rats. The rats were randomly assigned to four main groups of eight animals each. In the control group, the incision was not repaired and it was left to secondary healing. In the primary repair group, the incision was primarily repaired. In the fibrin glue group, glue was applied only to the incision. In the final group, fibrin glue was applied to the incision following primary repair. Three weeks later, penectomy tissue was examined histopathologically. RESULTS: When the control group was compared with primary repair+fibrin glue group, the differences in cavernous tissue healing with fibrosis and inflammation were statistically significant (p = 0.04 and 0.01, respectively). The primary repair+fibrin glue group, showed the best cavernous healing with fibrosis observed in only one rat. . There was no significant difference between the control group and the other groups according to cavernous tissue healing with fibrosis and inflammation (p = 0.11 and 0.12). Hyperemia was observed in the all groups of rats. CONCLUSIONS: Fibrin glue can be used in cavernoseal surgeries due to its adhesive and potentially anti-inflammatory features.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
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 head0.178
GPT teacher head0.348
Teacher spread0.170 · 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
Published2011
Admission routes1
Has abstractyes

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