Point of View: Hypothesis, analysis and synthesis, it's all Greek to me
- University of Crete, Greece
- University of Manchester, United Kingdom
- Hôpital de la Pitié-Salpêtrière, France
- University of Hong Kong, China
- Stanford University, United States
- Erasmus University Medical Center, Netherlands
- Centre for Research & Technology Hellas, Greece
- University of Cyprus, Cyprus
Abstract
The linguistic foundations of science and technology include many terms that have been borrowed from ancient languages. In the case of terms with origins in the Greek language, the modern meaning can often differ significantly from the original one. Here we use the PubMed database to demonstrate the prevalence of words of Greek origin in the language of modern science, and call for scientists to exercise care when coining new terms.
https://doi.org/10.7554/eLife.43514.001Our etymological legacy
Plato once wrote that "the knowledge of names is a great part of knowledge" (Silverman, 1992). However, it is seldom that scientists or engineers think about the deeper origins of many of the names and words they use in their professional lives. These specialized vocabularies are introduced during high school and university to describe concepts, phenomena, methodologies and techniques, and we grow so accustomed to them that we lose sight of where they came from (Banay, 1948; Askitopoulou et al., 2000; Ramoutsaki et al., 2002; Danchin, 2010). For example, the word machine derives from the Greek word 'μηχανή', meaning 'trick', which is quite different from its modern usage. The study of the origins of words is called etymology, which, by the way, is derived from the Greek word 'έτυμος' meaning 'real' and 'genuine'.
It is widely accepted that the Greek language has provided more of these names and words than any other language (Flood, 1960; Silverman, 1992; Russo, 2004). As scientists and native speakers, we humbly urge our colleagues to delve a little deeper into the etymology of scientific terms of Greek origin and examine their meaning (Tamis, 2016). Non-Greek speakers will, we are sure, be surprised by the richness and structure of the Greek language, despite its often inept naturalization in English or other languages, and as a result be better able to understand their own areas of science (Snell, 1960; Montgomery, 2004). Our favorite example is the word 'analysis': everyone uses it, but few fully understand it. 'Lysis' means 'breaking up', while 'ana-' means 'from bottom to top' but also 'again/repetitively': the subtle yet ingenious latter meaning of the term implies that if you break up something once, you might not know how it works; however, if you break up something twice, you must have reconstructed it, so you must understand the inner workings of the system.
Many scientific words end with the suffix -ics, such as mathematics, physics and economics. However, these words were initially adjectives, not nouns, so strictly speaking a word like mathematics is incomplete in ancient Greek: the correct term is mathematical philosophy (words that are derived from Greek words meaning 'learnable' and 'love for wisdom' respectively; Nidditch, 1983). We are not arguing here that we need to use any scientific words and terms differently: rather, we are asking readers to be aware of the origins of the words they use and to think about these issues when proposing new scientific terms (Steffanides, 1965; Jarvis, 1996; Lewis, 2004; Welch, 2009).
Word counts and a way forward
The PubMed database can be used to get an idea of the prevalence of words of Greek origin in the scientific literature: as of July 28, 2018 PubMed contained records for over 28 million scientific articles. We will focus here on frequently used terms (Newman et al., 2009), but that does not mean that the origins and use of other terms are not important. There are 243 distinct words that each appear in more than one million PubMed records (Supplementary file 1). However, when we exclude articles (such as 'the'), prepositions (such as 'to' and 'in') and short verb forms (such as 'is' and 'was'), we are left with 172 terms (Supplementary file 2), and removing terms with fewer that four characters (such as DNA and other abbreviations), leaves us with 152 terms (Supplementary file 3; Supplementary file 4). It is worth noting that no single gene or protein name appears in more than one million records (Seringhaus et al., 2008). When combined into a disjoint query, using the OR operator, these 152 terms retrieve ~27.8M entries, the majority (~97%) of all PubMed records.
From this initial dataset, we used etymological dictionaries to identify 15 terms with Greek origin: analysis, based, clinical, diagnosis, gene, genes, method, period, plasma, protein, proteins, surgery, system, therapy, type. The alert reader will notice that 13 of these words are nouns (with the two exceptions being the words 'clinical' and 'based'). We then constructed a PubMed search for records that contained at least one of the 15 words and it returned more than 23 million records, which is more than 80% of the entire database! We also constructed a PubMed search for records that contained at least one of the 137 non-Greek million-plus words and excluded all 15 words of Greek origin and it returned just 4.7 million records, confirming the prevalence of words of Greek origin in the scientific literature. It should be noted that these searches might underestimate the prevalence of Greek terms because, for example, some of the 137 words (such as mice) might be remotely connected by etymology to Greek words.
Advances in science mean that there is an ongoing need for new words (also known as neologisms). However, when a scientist attempts to introduce a new name for a new concept or idea, we would like him or her to consider both the origins of the new name as well as how it relates to existing names (Jackson, 1961; Trüper, 1999). In the field of genomics, the word epigenomics is an example of a new term being introduced in a thoughtful and meaningful way. However, there are many examples of researchers introducing new variations on the word genomics that are sub-optimal: Jonathan Eisen of the University of California, Davis has coined the term #badomics to describe such words.
A case in point is the term metagenomics, which is the study of genetic material taken from environmental samples. Here the prefix 'meta-' is used in a way that is not consistent with its Greek origins (meta- meaning beyond). Better names might have been endogenomics for the study of environmental samples taken from inside a host organism, and exogenomics for the study of samples taken from the outside (endo- and exo- meaning 'inside' and 'outside' in Greek, respectively). A similar situation might have occurred when looking for a name to describe the search for life elsewhere in the universe: the term exobiology was gradually replaced by astrobiology (Gargaud et al., 2011) – possibly because it had to rhyme with astronauts!
The suffix -some (from 'soma', meaning 'body' in Greek) has been employed in neologisms across the life sciences in recent decades, with varying degrees of success (Table 1). Likewise, the suffix -ome (from '-oma', meaning an undefined set in Greek) has been much used (think biome and genome) in recent times. To exemplify the linguistic richness of the Greek language, we explored the use of Greek prepositions to convey additional meaning within genomics. Epigenome (Murrell et al., 2005) is an excellent example of a scientific term in which a Greek preposition ('epi'-, meaning 'on top of') is combined with the suffix -genome to make a word that is precise and logically consistent. Other (less well known) examples include antigenome (which is used in immunology; Sette et al., 2016), metagenome (Streit and Schmitz, 2004), progenome (Ferreira et al., 2004), and hypergenome (Sgaramella, 2013). We then went on to create new words of this kind (Table 2) that, we feel, remain true to their etymological roots while, at the same time, being potentially useful to the scientific community. (The term pangenome (Tettelin et al., 2005), meaning the full complement of genes in a clade, is also very useful although, strictly speaking, 'pan-' is not a preposition).
Table 1
A selection of terms ending with the suffix -some that appear in the scientific literature.
The term prostasome, which first showed up in PubMed in 1982, appeared in 218 PubMed records as of July 28, 2018. However, other terms ending with -some have proved much less popular.
| Term | Definition | Context | Number of PubMed records | Year of first appearance |
|---|---|---|---|---|
| catansome | catanionic vesicle | synthetic biochemistry, surfactants | 2 | 2008 |
| ejectisome | extrusive organelle | cell biology and physiology | 16 | 1984 |
| histrosome | a type of ejectisome | cell biology and physiology | 1 | 2015 |
| hyposome | cellular structure | dDinoflagellate biology | 7 | 2010 |
| prostasome | prostate gland vesicle | sperm mobility and physiology | 218 | 1982 |
| remosome | remodeled nucleosome | non-canonical chromatin structure | 2 | 2010 |
Table 2
A selection of terms that combine a Greek preposition and the suffix -genome.
Some terms that the authors believe could be useful in genome biology.
| Preposition | Term | Possible definition/interpretation |
|---|---|---|
| ana | anagenome | could be used to describe usage over time, to monitor population variation |
| amphi | amphigenome | could be used to describe polyploid genomes, and sex differences |
| apo | apogenome | could be used to convey non-DNA large scale analysis |
| dia | diagenome | could be a useful concept for comparative genomics |
| eis | eisgenome | could be a useful term for substance use |
| ek | ecgenome | alternative for exo-genomics (see text) |
| en | engenome | alternative for endo-genomics (see text) |
| kata | katagenome | could be a vey useful term to describe developmental processes over time |
| para | paragenome | could be used to describe the genomics of paralogs (although this is not satisfactory from an etymological point of view) |
| peri | perigenome | could be a very useful term to describe developmental processes over space |
| pros | prosgenome | could be used to describe synthetic genomes |
| syn | syngenome | could be used to describe the genomics of symbioses |
| hypo | hypogenome | could be used to describe a synthetic genome with depleted functions – as opposed to hyper-genome to describe a synthetic genome with added functions |
Conclusion and epilogue
It is often forgotten that some of humankind's greatest achievements in science, engineering, literature, philosophy, arts and architecture were communicated in Greek, not only in the ancient world but also more recently: the Greek language greatly contributed to the development of the Renaissance, to the French and American Revolutions, and to modern science. Scholars who spoke and wrote in Greek include Newton, Leibniz, Goethe and Wittgenstein, and Greek lives on (alongside Latin) in the taxonomic names devised by Linnaeus, Darwin and others. Perhaps we can still learn something from them, and from scholars in other fields, empowered by the availability of automated translation, online dictionaries and etymology tools. We hope that this contribution will encourage scientists to think about the terminology used in modern science, technology and medicine (Wulff, 2004), and to be more careful when seeking to introduce new words and phrases into our vocabulary.
Data availability
The supplementary files for this paper and other related information is available at: https://doi.org/10.6084/m9.figshare.5493133.v2. Etymology of the select terms of Greek origin: http://troodos.biol.ucy.ac.cy/Etymology.html.
References
-
Analgesia and anesthesia: etymology and literary history of related Greek wordsAnesthesia & Analgesia 91:486.
-
An introduction to medical terminology I. Greek and Latin derivationsBulletin of the Medical Library Association 36:1.
-
Do older taxa have older proteins?Zeitschrift für Naturforschung C 59:454–458.https://doi.org/10.1515/znc-2004-5-629
-
BookOrigins and Evolution of Life: An Astrobiological PerspectiveCambridge: Cambridge University Press.
-
The language of modern medicine: it's all Greek to meThe American Surgeon 70:91.
-
BookUsing topic models to interpret MEDLINE's medical subject headingsIn: Nicholson A, Li X, editors. AI 2009: Advances in Artificial Intelligence. Melbourne: Springer. pp. 270–279.https://doi.org/10.1007/978-3-642-10439-8_28
-
The first stage of the idea of mathematics: Pythagoreans, Plato, AristotleMidwest Studies in Philosophy 8:3–34.https://doi.org/10.1111/j.1475-4975.1983.tb00458.x
-
Deciphering the human antigenomeExpert Review of Vaccines 15:167–171.https://doi.org/10.1586/14760584.2016.1112743
-
The hypergenome in inheritance and developmentCytogenetic and Genome Research 139:215.https://doi.org/10.1159/000348326
-
Oxford Studies in Ancient PhilosophyPlato's Cratylus: The naming of nature and the nature of naming, Oxford Studies in Ancient Philosophy, Oxford, Clarendon Press.
-
The forging of a language for science in ancient GreeceThe Classical Journal 56:50–60.
-
The role of greek and latin in scienceThe American Biology Teacher 27:785–789.https://doi.org/10.2307/4441190
-
Metagenomics--the key to the uncultured microbesCurrent Opinion in Microbiology 7:492–498.https://doi.org/10.1016/j.mib.2004.08.002
-
How to name a prokaryote?FEMS Microbiology Reviews 23:231–249.https://doi.org/10.1016/S0168-6445(99)00005-4
-
Physiology, physiomics, and biophysics: a matter of wordsProgress in Biophysics and Molecular Biology 100:4–17.https://doi.org/10.1016/j.pbiomolbio.2009.08.001
-
The language of medicineJournal of the Royal Society of Medicine 97:187–188.https://doi.org/10.1177/014107680409700412
Article and author information
Author details
Christos A Ouzounis
Vasilis J Promponas
Acknowledgements
We thank Ben Blencowe (University of Toronto), Georgios Floros (University of Cyprus), Peter Karp (SRI International), Nikos Kyrpides (JGI Berkeley), Nikolas Papanikolaou (University of Crete), Nikos Sarantakos (European Parliament) and Spyros Sfenthourakis (University of Cyprus) for insightful comments and constructive criticisms on earlier versions of this manuscript.
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© 2019, Iliopoulos et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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Point of View: Hypothesis, analysis and synthesis, it's all Greek to me
eLife 8:e43514.
https://doi.org/10.7554/eLife.43514
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