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Record W2727721858 · doi:10.5539/gjhs.v9n9p52

Evaluation of the Effect of Platelet Mediators to Increase the Skin's Collagen; A Randomized Clinical Trial

2017· article· en· W2727721858 on OpenAlexvenueno aff
Hamidollah Afarsiabian, Mitra Nourbakhsh, Majid Sadeghizadeh

Bibliographic record

VenueGlobal Journal of Health Science · 2017
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsnot available
FundersTarbiat Modares UniversityIran University of Medical Sciences
KeywordsMedicineLecithinPlatelet-rich plasmaPlaceboRandomized controlled trialPlatelet aggregationPlateletWrinkleFacial rejuvenationSkin thicknessDermatologySurgeryInternal medicinePathologyChromatographyChemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this paper is to evaluate the effect of platelet-rich plasma mediators on the reconstruction of facial skin collagen by a platelet cream. Additionally, the cream was composited with plasma and some herbal compounds, which carried those factors through the skin. This method as a non-invasive skin will help the skin rejuvenation.MATERIALS & METHODS: This study is a randomized clinical trial; patients referred to the clinic with positive cases from skin wrinkles along with 20 MHz frequency ultrasound images of their skin faces. All individual enrolled in the study were randomly divided into two groups.Group A 70cc cream including 60cc basic cream (emulsion of Lecithin and Eucerin) in addition of 5cc platelet-rich plasma and 5ccherbal extracted (Herdahelix, Musk and Genestein) to take a month received. Consequently, instructions for use of this cream is that 2.3g of the cream every night to be affected.Group B (controls) received 70cc of the cream involving 6cc basic cream (emulsion of Lecithin and Eucerin) along with 10cc placebo (glycerin) that every night 2.3g of the cream to be applied on the face.After a month increased the amount of facial skin collagen in each group was calculated and compared by ultrasound 20 MHz. In this project compare numerically and in terms of the amount of reflected energy (RE) was performed. In addition, the idea of using plant extracts and platelet mediators to penetrate into the skin was derived from Iranian traditional medicine.FINDINGS: Statistical analysis of the data collection was done by SPSS 18 software. Further, demographic characteristics including age, sex, occupation, socioeconomic status and education level had no effect on the response to treatment (P=0.221), but demographic indicator of age on response to treatment was effective (P=0.021).Respond to the treatment (increase the amount of collagen in the skin) in group A and group B equal to 72.91% and 12.5% respectively. In group A with group B were significant differences in response to treatment, P = 0.000. The only side effect occurred in group A was mild irritation including redness and mild itching, which happened in 2 patients.CONCLUSION: Employee non-invasive method of platelet cream rebuilds collagen in the skin effectively.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.063
GPT teacher head0.475
Teacher spread0.411 · 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 designRandomized trial
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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