Abstract
Continuous quality improvement has been one of the cardinal features of modern society such that what is one day a bleeding-edge process or technology, rapidly becomes merely state of the art, and then is simply de rigueur. More than any other single aspect of human nature it is the continuous process improvement that has created our complex modern society. It has been termed social selection, as a counterpoint to natural selection, because both processes increase functionality. The conscious adoption of this paradigm cuts across all fields of endeavor from professional sports (Surowiecki, 2014); to culinary arts (García-Segoviaa et al., 2012) and oenology (Friddle, 2009); to manufacturing (Dunning, 2002); and to scientific pursuits and the publication of their results. The classic examples include Dunning's transformation of Japanese manufacturing wherein he applied statistical approaches and incremental process improvement in the post-WWII era that turned a devastated war-torn island nation into a global economic power within a single generation (Dunning, 2002). Similarly, the Six Sigma paradigm developed by Bill Smith at Motorola and then adopted by the Jack Welch-led General Electric Corporation led to similar improvements in manufacturing quality in the West (Zhang et al., 2018).
Scientific Journals, including Genetic Testing and Molecular Biomarkers, are no different and to survive in the ever- and increasingly-competitive peer-reviewed world must also engage in similar bar-raising processes with regard to what we will publish and how. Therefore, going forward we will be adding additional criteria to original full-length scientific articles submitted, such that observational findings will need to be supported by some type of mechanistic studies. These can be either laboratory based using traditional investigative methods, or computationally based using tools such as pathway analyses and machine learning, Thus, it will no longer be sufficient to simply report an association between a clinical phenotype and a particular mutation/polymorphism or other biomarker(s). Rather, the authors will need to perform some type of functional analyses that are mechanistically supportive of the statistical association.
We will continue to publish “simple” associative studies, but only under the guise of a “short report” or “note.” This switchover will not be implemented immediately, or even all at once, to give our authors time to plan their future studies, and to publish current and ongoing studies without undue disruption. We anticipate that this transitional period will extend throughout the current calendar year, such that by the time Volume 24 commences in 2020 we will be fully operating under this new publishing rubric.
I am pleased to note that some of our recent authors have anticipated this raising of the bar and have been submitting and publishing articles that include mechanistic support for their associative studies. For example, in our December 2018 issue, Zhang et al. (2018) delved into the mechanisms by which miR-21 contributes to mesenchymal stem cell proliferation, inhibits apoptosis, and controls their immunoregulatory capabilities (Zhang et al., 2018). Similarly, in the February 2019 issue Han et al. (2019) not only identify genetic polymorphisms of the PAR2 gene associated with inflammation and susceptibility to osteoarthritis, but also demonstrate that the carriers of the risk alleles in this gene have higher mRNA expression levels of this gene and other genes associated with tissue destruction, thereby providing a plausible mechanism for explaining the observed clinical outcomes. Wang et al. (2019), also in the February issue, demonstrate that miR-148a-3p directly targets DNMT1 and that in esophageal cancer cells cultured in vitro that overexpression of miR-148-3p leads to decreased proliferation and invasiveness, thereby providing a potential therapeutic target.
We look forward to our authors accepting this challenge of adding mechanistic studies to support their associative findings.