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Record W3165217920 · doi:10.21608/adjg.2021.48100.1315

Effect of Lepidium Sativum Gel as an Adjunct to Non- Surgical Treatment in Management of Periodontitis Patients Stage (II, III) and Grade (A, B)

2021· article· en· W3165217920 on OpenAlexfundno aff
Yusra Bathish, Naglaa El kilani, Aya M. Dawaba, Zienab Farid

Bibliographic record

VenueAl-Azhar Dental Journal for Girls · 2021
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Medicinal Plants
Canadian institutionsnot available
FundersGroupe de recherche interuniversitaire en limnologie
KeywordsLepidium sativumScaling and root planingMedicineBleeding on probingPeriodontitisGroup BSativumBiomarkerInternal medicineDentistryChronic periodontitisGastroenterology

Abstract

fetched live from OpenAlex

Purpose: The current study was conducted to elaborate the clinical and transforming growth factor beta biomarker effect of local application of lepidium sativum gel as an adjunct to scaling and root planing in the therapeutic management of periodontitis patients stage( II, III) and grade(A, B). Subjects and Methods: The current study was conducted on twenty patients were selected in this study with stage (II, III) and grade (A, B) periodontitis. Patients were randomly divided into two group’s ten subjects on each. Group A: (control group) were treated with scaling and root planing alone, group B: (study group) were treated with scaling and root planing with local delivery of lepidium sativum gel. Results: study group showed a significant increase in the clinical parameter like clinical attachment level (CAL), probing depth (PD), bleeding on probing (BOP) and plaque index (PI). Clinical parameters were recorded after one month and three months, transforming growth factor beta biomarker level after one week and four weeks in comparison with control group follow up. Conclusion: Adjunctive use of lepidium sativum with non-surgical therapy showed an improvement in the treatment outcome of periodontitis patient’s stage (II, III) and grade (A, B).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.597

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 integrity0.0000.000
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 head0.011
GPT teacher head0.327
Teacher spread0.316 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

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