The etymology of microbial nomenclature and the diseases these cause in a historical perspective.

When the hunter-gatherers finally started settling down as farmers, infectious diseases started scourging them. The earlier humans could differentiate sporadic diseases like tooth decay, tumors, etc., from the infectious diseases that used to cause outbreaks and epidemics. The earliest comprehension of infectious diseases was primarily based on religious background and myths, but as human knowledge grew, the causes of these diseases were being probed. Similarly, the taxonomy of infectious diseases gradually changed from superstitious prospects, like influenza, signifying disease infliction due to the "influence of stars" to more scientific ones like tuberculosis derived from the word "tuberculum" meaning small swellings seen in postmortem human tissue specimens. From a historical perspective, we identified five categories for the basis of the microbial nomenclature, namely phenotypic characteristics of microbe, disease name, eponym, body site of isolation, and toponym. This review article explores the etymology of common infectious diseases and microorganisms' nomenclature in a historical context.

Spatiotemporal Hotspots of Study Areas in Research of Gastric Cancer in China Based on Web-Crawled Literature.

Gastric cancer is a common malignancy worldwide and poses a serious threat to human public health. The difficulty in obtaining epidemiological data limits the development of cross-disciplinary related research. In this study, 99,364 publications on gastric cancer from 1991 to 2019 were obtained using web-crawler technology, and a technical framework for extracting toponyms from these publications was constructed to analyze spatiotemporal hotspots of study areas in gastric cancer research in China. The results showed the following: (1) The accuracy of toponym extraction was greatly improved after eliminating the systematic exclusion words and adding historical toponyms, with a precision of 95.31% and a recall of 94.86%. (2) Gastric cancer research (GCR) and gastric cancer research with toponyms (GCRWT) are attracting increasing amounts of attention. The amount of GCR results published in Chinese and English is gradually leveling off, and the imbalance between those of GCRWT is gradually widening. (3) The spatial distribution of gastric cancer research in China is uneven, and the hotspots are mainly located in the eastern coastal areas. There were huge advances in gastric cancer research at the province/city/county scale in Eastern China, while the central region has only increased research at the county scale. We suggest that gastric cancer research should pay more attention to the central region, which has the highest gastric cancer incidence/mortality. This study provides important clues for research on and investigations of gastric cancer.

A pragmatic guide to geoparsing evaluation: Toponyms, Named Entity Recognition and pragmatics.

Empirical methods in geoparsing have thus far lacked a standard evaluation framework describing the task, metrics and data used to compare state-of-the-art systems. Evaluation is further made inconsistent, even unrepresentative of real world usage by the lack of distinction between the different types of toponyms, which necessitates new guidelines, a consolidation of metrics and a detailed toponym taxonomy with implications for Named Entity Recognition (NER) and beyond. To address these deficiencies, our manuscript introduces a new framework in three parts. (Part 1) Task Definition: clarified via corpus linguistic analysis proposing a fine-grained Pragmatic Taxonomy of Toponyms. (Part 2) Metrics: discussed and reviewed for a rigorous evaluation including recommendations for NER/Geoparsing practitioners. (Part 3) Evaluation data: shared via a new dataset called GeoWebNews to provide test/train examples and enable immediate use of our contributions. In addition to fine-grained Geotagging and Toponym Resolution (Geocoding), this dataset is also suitable for prototyping and evaluating machine learning NLP models.

¿Algunos epónimos y topónimos como coincidencias terminológicas? / ¿Some eponyms and toponyms as terminological coincidences?

Los epónimos y los topónimos se han utilizado desde hace siglos en la anatomía para nombrar muchas estructuras corporales, pero curiosamente algunos de estos nombres también figuran en la literatura no morfológica, por lo que se plantea si se trata de meras coincidencias terminológicas. Se analizó el origen etimológico de los términos céfalo, tórax, ilión, meninge, nervios y pedio, que aparecen en la literatura no morfológica desde antes de nuestra era y se comparó con el significado que se les da en la terminología anatómica. Algunos términos usados en la anatomía aparentemente no son considerados como epónimos o topónimos, sin embargo, varios personajes históricos y ciertos lugares geográficos tienen coincidencialmente esos mismos nombres. Por tanto, se plantea la posibilidad que tales términos hayan pasado inadvertidos y que realmente hacen parte de la eponimia morfológica. Por lo tanto, los términos céfalo, tórax, ilión, meninge, nervios y pedio son epónimos y topónimos poco conocidos, aunque cabe la posibilidad que sean simples coincidencias terminológicas.

Eponyms and toponyms have been used in anatomy for centuries, to name many body structures, but interestingly some of these names also appear in the nonmorphological literature, so it is being considered if they are only terminological coincidences. The etymological origin of the terms cephalus, thorax, ilium, meninx, nerves and pedius, which appear in the non-morphological literature of before our era, was analyzed and compared with the meaning given in anatomical terminology. Some terms used in anatomy apparently are not considered as eponyms or place names, however, several historical figures and certain geographic locations coincidentally bear those same names. Therefore, the possibility arises that such terms have gone unnoticed and that they are really part of the morphological eponyms and toponyms. Therefore, the terms cephalo,thorax, ilium, meninge, nerves and pedius are eponyms and little-known toponyms, although it is possible that they are simple terminological coincidences.

MapAffil: A Bibliographic Tool for Mapping Author Affiliation Strings to Cities and Their Geocodes Worldwide.

Bibliographic records often contain author affiliations as free-form text strings. Ideally one would be able to automatically identify all affiliations referring to any particular country or city such as Saint Petersburg, Russia. That introduces several major linguistic challenges. For example, Saint Petersburg is ambiguous (it refers to multiple cities worldwide and can be part of a street address) and it has spelling variants (e.g., St. Petersburg, Sankt-Peterburg, and Leningrad, USSR). We have designed an algorithm that attempts to solve these types of problems. Key components of the algorithm include a set of 24,000 extracted city, state, and country names (and their variants plus geocodes) for candidate look-up, and a set of 1.1 million extracted word n-grams, each pointing to a unique country (or a US state) for disambiguation. When applied to a collection of 12.7 million affiliation strings listed in PubMed, ambiguity remained unresolved for only 0.1%. For the 4.2 million mappings to the USA, 97.7% were complete (included a city), 1.8% included a state but not a city, and 0.4% did not include a state. A random sample of 300 manually inspected cases yielded six incompletes, none incorrect, and one unresolved ambiguity. The remaining 293 (97.7%) cases were unambiguously mapped to the correct cities, better than all of the existing tools tested: GoPubMed got 279 (93.0%) and GeoMaker got 274 (91.3%) while MediaMeter CLIFF and Google Maps did worse. In summary, we find that incorrect assignments and unresolved ambiguities are rare (< 1%). The incompleteness rate is about 2%, mostly due to a lack of information, e.g. the affiliation simply says "University of Illinois" which can refer to one of five different campuses. A search interface called MapAffil has been developed at the University of Illinois in which the longitude and latitude of the geographical city-center is displayed when a city is identified. This not only helps improve geographic information retrieval but also enables global bibliometric studies of proximity, mobility, and other geo-linked data.