MétaCan
Menu
Back to cohort
Record W4405290752 · doi:10.4103/jpbs.jpbs_1190_24

A Comparative Study of Bcl-2 Expression in Oral Leukoplakia with Dysplasia, Verrucous Carcinoma, and Oral Squamous Cell Carcinoma

2024· article· en· W4405290752 on OpenAlexaff
Bireswar Roy, Shivani Saxena, Mridul Sharma, N Pramukh, Miral Mehta

Bibliographic record

VenueJournal of Pharmacy And Bioallied Sciences · 2024
Typearticle
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsVerrucous carcinomaMedicineBasal cellLeukoplakiaDysplasiaCarcinomaOral leukoplakiaDermatologyOncologyP53 expressionPathologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Aim: To study the immunohistochemical expression of Bcl-2 in oral leukoplakia with dysplasia, verrucous carcinoma and oral squamous cell carcinoma(OSCC). Methodology: A total of 80 formalin-fixed , paraffin- embedded specimens were selected , amongst them 30 cases of different grades of dysplasia- 10 mild, 10 moderate and 10 severe and 30 oral squamous cell carcinoma of various grades- 10 well differentiated, 10 moderately differentiated and 10 poorly differentiated, 10 verrucous carcinoma had been included in the study. 10 normal buccal mucosa were used as control group. Results: The immunohistochemical expression of Bcl-2 in oral leukoplakia with different grades of dysplasia, in verrucous carcinoma and in different grades of oral squamous cell carcinoma with normal mucosa were compared. Moreover, the expression of Bcl-2 was found to increase significantly between dysplasia and different grades of oral squamous cell carcinoma. Conclusion: The expression of Bcl-2 has always guided the researchers towards mapping the progression of dysplasia as well as malignant transformation at the molecular level.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.382
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy And Bioallied SciencesSame topicOral Health Pathology and TreatmentFrench-language works237,207