Protection of the human gene research literature from contract cheating organizations known as research paper mills

The undeclared use of third-party service providers in academic publishing is unethical: an epistemic reflection and scoping review

There is a substantial body of scientific literature on the use of third-party services (TPS) by academics to assist as "publication consultants" in scholarly publishing. TPS provide a wide range of scholarly services to research teams that lack the equipment, skills, motivation, or time to produce a paper without external assistance. While services such as language editing, statistical support, or graphic design are common and often legitimate, some TPS also provide illegitimate services and send unsolicited e-mails (spam) to academics offering these services. Such illegitimate types of TPS have the potential to threaten the integrity of the peer-reviewed scientific literature. In extreme cases, for-profit agencies known as "paper mills" even offer fake scientific publications or authorship slots for sale. The use of such illegitimate services as well as the failure to acknowledge their use is an ethical violation in academic publishing, while the failure to declare support for a TPS can be considered a form of contract fraud. We discuss some literature on TPS, highlight services currently offered by ten of the largest commercial publishers and expect authors to be transparent about the use of these services in their publications. From an ethical/moral (i.e., non-commercial) point of view, it is the responsibility of editors, journals, and publishers, and it should be in their best interest to ensure that illegitimate TPS are identified and prohibited, while publisher-employed TPS should be properly disclosed in their publications.

Verification of nucleotide sequence reagent identities in original publications in high impact factor cancer research journals

Human gene research studies that describe wrongly identified nucleotide sequence reagents have been mostly identified in journals of low to moderate impact factor, where unreliable findings could be considered to have limited influence on future research. This study examined whether papers describing wrongly identified nucleotide sequences are also published in high-impact-factor cancer research journals. We manually verified nucleotide sequence identities in original Molecular Cancer articles published in 2014, 2016, 2018, and 2020, including nucleotide sequence reagents that were claimed to target circRNAs. Using keywords identified in some 2018 and 2020 Molecular Cancer papers, we also verified nucleotide sequence identities in 2020 Oncogene papers that studied miRNA(s) and/or circRNA(s). Overall, 3.8% (251/6647) and 4.0% (47/1165) nucleotide sequences that were verified in Molecular Cancer and Oncogene papers, respectively, were found to be wrongly identified. Wrongly identified nucleotide sequences were distributed across 18% (91/500) original Molecular Cancer papers, including 38% (31/82) Molecular Cancer papers from 2020, and 40% (21/52) selected Oncogene papers from 2020. Original papers with wrongly identified nucleotide sequences were therefore unexpectedly frequent in two high-impact-factor cancer research journals, highlighting the risks of employing journal impact factors or citations as proxies for research quality.

Meta-Research: Understudied genes are lost in a leaky pipeline between genome-wide assays and reporting of results

Present-day publications on human genes primarily feature genes that already appeared in many publications prior to completion of the Human Genome Project in 2003. These patterns persist despite the subsequent adoption of high-throughput technologies, which routinely identify novel genes associated with biological processes and disease. Although several hypotheses for bias in the selection of genes as research targets have been proposed, their explanatory powers have not yet been compared. Our analysis suggests that understudied genes are systematically abandoned in favor of better-studied genes between the completion of -omics experiments and the reporting of results. Understudied genes remain abandoned by studies that cite these -omics experiments. Conversely, we find that publications on understudied genes may even accrue a greater number of citations. Among 45 biological and experimental factors previously proposed to affect which genes are being studied, we find that 33 are significantly associated with the choice of hit genes presented in titles and abstracts of -omics studies. To promote the investigation of understudied genes, we condense our insights into a tool, find my understudied genes (FMUG), that allows scientists to engage with potential bias during the selection of hits. We demonstrate the utility of FMUG through the identification of genes that remain understudied in vertebrate aging. FMUG is developed in Flutter and is available for download at fmug.amaral.northwestern.edu as a MacOS/Windows app.

Meta-Research: understudied genes are lost in a leaky pipeline between genome-wide assays and reporting of results

Present-day publications on human genes primarily feature genes that already appeared in many publications prior to completion of the Human Genome Project in 2003. These patterns persist despite the subsequent adoption of high-throughput technologies, which routinely identify novel genes associated with biological processes and disease. Although several hypotheses for bias in the selection of genes as research targets have been proposed, their explanatory powers have not yet been compared. Our analysis suggests that understudied genes are systematically abandoned in favor of better-studied genes between the completion of -omics experiments and the reporting of results. Understudied genes remain abandoned by studies that cite these -omics experiments. Conversely, we find that publications on understudied genes may even accrue a greater number of citations. Among 45 biological and experimental factors previously proposed to affect which genes are being studied, we find that 33 are significantly associated with the choice of hit genes presented in titles and abstracts of - omics studies. To promote the investigation of understudied genes we condense our insights into a tool, find my understudied genes (FMUG), that allows scientists to engage with potential bias during the selection of hits. We demonstrate the utility of FMUG through the identification of genes that remain understudied in vertebrate aging. FMUG is developed in Flutter and is available for download at fmug.amaral.northwestern.edu as a MacOS/Windows app.

Detection of fake papers in the era of artificial intelligence

OBJECTIVES

Paper mills, companies that write scientific papers and gain acceptance for them, then sell authorships of these papers, present a key challenge in medicine and other healthcare fields. This challenge is becoming more acute with artificial intelligence (AI), where AI writes the manuscripts and then the paper mills sell the authorships of these papers. The aim of the current research is to provide a method for detecting fake papers.

METHODS

The method reported in this article uses a machine learning approach to create decision trees to identify fake papers. The data were collected from Web of Science and multiple journals in various fields.

RESULTS

The article presents a method to identify fake papers based on the results of decision trees. Use of this method in a case study indicated its effectiveness in identifying a fake paper.

CONCLUSIONS

This method to identify fake papers is applicable for authors, editors, and publishers across fields to investigate a single paper or to conduct an analysis of a group of manuscripts. Clinicians and others can use this method to evaluate articles they find in a search to ensure they are not fake articles and instead report actual research that was peer reviewed prior to publication in a journal.

Biobanking and research quality: think locally, act globally

Although biobanks can support research across geographic and governance boundaries, biomedical researchers consistently describe preferences for either collaborating with local biobanks or establishing their own biobanks. This article summarizes the potential research impacts of local biobank use and suggests how descriptions of biospecimen provenance can be improved in research publications.