How to Act When Research Misconduct Is Not Detected by Software but Revealed by the Author of the Plagiarized Article.

The detection of plagiarism in scholarly articles is a complex process. It requires not just quantitative analysis with the similarity recording by anti-plagiarism software but also assessment of the readers' opinion, pointing to the theft of ideas, methodologies, and graphics. In this article we describe a blatant case of plagiarism by Chinese authors, who copied a Russian article from a non-indexed and not widely visible Russian journal, and published their own report in English in an open-access journal indexed by Scopus and Web of Science and archived in PubMed Central. The details of copying in the translated English article were presented by the Russian author to the chief editor of the index journal, consultants from Scopus, anti-plagiarism experts, and the administrator of the Committee on Publication Ethics (COPE). The correspondents from Scopus and COPE pointed to the decisive role of the editors' of the English journal who may consider further actions if plagiarism is confirmed. After all, the chief editor of the English journal retracted the article on grounds of plagiarism and published a retraction note, although no details of the complexity of the case were reported. The case points to the need for combining anti-plagiarism efforts and actively seeking opinion of non-native English-speaking authors and readers who may spot intellectual theft which is not always detected by software.

Diagnosis of oral lichen planus from analysis of saliva samples using terahertz time-domain spectroscopy and chemometrics.

The ability to diagnose oral lichen planus (OLP) based on saliva analysis using THz time-domain spectroscopy and chemometrics is discussed. The study involved 30 patients (2 male and 28 female) with OLP. This group consisted of two subgroups with the erosive form of OLP (n = 15) and with the reticular and papular forms of OLP (n = 15). The control group consisted of six healthy volunteers (one male and five females) without inflammation in the mucous membrane in the oral cavity and without periodontitis. Principal component analysis was used to reveal informative features in the experimental data. The one-versus-one multiclass classifier using support vector machine binary classifiers was used. The two-stage classification approach using several absorption spectra scans for an individual saliva sample provided 100% accuracy of differential classification between OLP subgroups and control group.