MétaCan
Menu
Back to cohort
Record W2415756798 · doi:10.2310/6620.2011.10082

Antiirritant Properties of Polyols and Amino Acids

2011· article· en· W2415756798 on OpenAlexvenueno aff
Csilla Korponyai, Réka Kovács, Gábor Erős, S. Dikstein, Lajos Kemény

Bibliographic record

VenueDermatitis · 2011
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsnot available
Fundersnot available
KeywordsXylitolIrritationTransepidermal water lossGlycerolPolyolMannitolTaurineGlycineMedicineSorbitolChemistryDermatologyPharmacologyAmino acidBiochemistryOrganic chemistryStratum corneumImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Antiirritants are used in cosmetic products to prevent or to treat skin irritations that arise during daily life. Data were published earlier on the efficacy of the best-known humectant, glycerol, in reducing irritation. OBJECTIVE: The aim of the present study was to examine the effects of different polyols (including glycerol, xylitol, and mannitol) and the amino acids taurine and glycine on sodium lauryl sulfate (SLS)-induced skin irritation. METHODS: Healthy adult volunteers were patch-tested with 0.1% SLS in the presence or absence of one or another polyol or amino acid. Skin reactions were evaluated via measurements of transepidermal water loss (TEWL). RESULTS: Glycerol and xylitol significantly suppressed the SLS-induced increase in TEWL, whereas mannitol had no effect on the SLS-induced skin irritation. Taurine also inhibited the SLS-induced increase in TEWL, but glycine was not effective in reducing the SLS-induced irritative response. CONCLUSION: Similar to the action of the well-known antiirritant glycerol, SLS-induced skin irritation is suppressed by xylitol and taurine. These results suggest that these agents might also be effective in preventing irritative dermatitis.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.865

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)0.0010.000

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 head0.153
GPT teacher head0.367
Teacher spread0.213 · 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 designBench or experimental
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

Citations16
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueDermatitisSame topicAdvancements in Transdermal Drug DeliveryFrench-language works237,207