Development of a Predictive Classification Model for Surfactant-Induced Skin Irritation.

Manuela Lechuga, Pedro A García, Ana I García-López, Cristina Tapia-Navarro, Francisco Ríos

Abstract read

In one paragraph

Article in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Manuela LechugaDepartment of Chemical Engineering, Faculty of Sciences, University of Granada, Campus Fuente Nueva S/N, Granada 18071, Spain.

Pedro A GarcíaDepartment of Statistics and Operations Research, Faculty of Sciences, University of Granada, Campus Fuente Nueva S/N, Granada 18071, Spain.

Ana I García-LópezDepartment of Chemical Engineering, Faculty of Sciences, University of Granada, Campus Fuente Nueva S/N, Granada 18071, Spain.

Cristina Tapia-NavarroDepartment of Chemical Engineering, Faculty of Sciences, University of Granada, Campus Fuente Nueva S/N, Granada 18071, Spain.

Francisco RíosDepartment of Chemical Engineering, Faculty of Sciences, University of Granada, Campus Fuente Nueva S/N, Granada 18071, Spain.ORCID https://orcid.org/0000-0002-7300-6230

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the chemical properties of surfactants that significantly influence skin irritability using a predictive classification approach based on multiple linear regression and conditional inference trees. A data set comprising irritation values (Zein number, ZN) for 20 commercial surfactants and their binary mixtures was generated using an in vitro zein test. Key variables (hydrophilic-lipophilic balance (HLB), surfactant concentration, and ionic character) were evaluated to build robust statistical models. The multiple regression model explained 80% of the variability in skin irritation (adjusted

Identifiers

PMID41322515

DOI10.1021/acsomega.5c07338

PMCPMC12658804

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LicenceCC BY

Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.