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Record W2035154085

Incidence of Argyrophil Cells in Normal and Dysplastic Conditions of Human Uterine Cervix

2013· article· en· W2035154085 on OpenAlexvenueno aff
Sujatha D’Costa, Raghuveer C’Vasudevarao, Adhikari Prabha, Sampath Madhyasta, Chitra Prakash Rao

Bibliographic record

VenueJournal of Current Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsnot available
Fundersnot available
KeywordsChromogranin APathologySynaptophysinCervixDysplasiaMedicineUterine cervixCervical intraepithelial neoplasiaStainingImmunohistochemistryInternal medicineCervical cancerCarcinomaCancer
DOInot available

Abstract

fetched live from OpenAlex

Background: Cervi cal intraepithelial neoplasia, also known as cervical dysplasia, is the potentially premalignant transformation and abnormal growth of squamous cells on the surface of the cervix. Argyrophil cells occur rarely in the normal human uterine cervix but are found in a variety of invasive tumours arising in the cervix. Methods: In this study, with the Grimelius argyrophilic reaction 317 normal uterine cervices were stained, out of which 158 cases (49.84%) were positive. And 27 dysplastic cases of uterine cervices were stained with Grimelius argyrophilic reaction, out of which 25 (92.59%) showed the argyrophilic positivity. When Normal cervix was compared with Dysplastic cervix the probability value was < 0.001 which was significantly higher. The immunomarkers used in the present study were Chromogranin A and Synaptophysin. Results: Argyrophil cells in ectocervical epithelium are rare. It is the first study which reveals the comparison of the presence of argyrophilic cells in normal and dysplastic human uterine cervix, using Grimelius argyrophilic reaction and Immunohistochemical staining using Chromogranin A and Synaptophysin as argyrophilic markers with larger sample size and higher positivity. Conclusion: From the results of our study it is clear that argyrophilia is a significant marker in dysplasia. doi: http://dx.doi.org/10.4021 /jcs116w

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.000

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 head0.049
GPT teacher head0.369
Teacher spread0.320 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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