Update on IJTLD OPEN: the future is open.

The launch of IJTLD OPEN, which is fully compliant with Plan S, has extended our author base and allowed readers worldwide to access the content for free. PubMed Central (PMC) has recently approved the journal for indexing (including indexing by PubMed), which will further improve visibility and access. Because authors retain copyright they can use their articles without restriction (e.g., to post on free digital repositories), helping to further disseminate their research. All these factors help to ensure that IJTLD OPEN has maximum reach and impact. However, we recognise that fees for open access may present a barrier for authors based in low- to middle-income countries. We call on the international community to ensure funding support for open access is broadly available, with equal opportunity for researchers worldwide.

Computational reproducibility of Jupyter notebooks from biomedical publications.

BACKGROUND: Jupyter notebooks facilitate the bundling of executable code with its documentation and output in one interactive environment, and they represent a popular mechanism to document and share computational workflows, including for research publications. The reproducibility of computational aspects of research is a key component of scientific reproducibility but has not yet been assessed at scale for Jupyter notebooks associated with biomedical publications. APPROACH: We address computational reproducibility at 2 levels: (i) using fully automated workflows, we analyzed the computational reproducibility of Jupyter notebooks associated with publications indexed in the biomedical literature repository PubMed Central. We identified such notebooks by mining the article's full text, trying to locate them on GitHub, and attempting to rerun them in an environment as close to the original as possible. We documented reproduction success and exceptions and explored relationships between notebook reproducibility and variables related to the notebooks or publications. (ii) This study represents a reproducibility attempt in and of itself, using essentially the same methodology twice on PubMed Central over the course of 2 years, during which the corpus of Jupyter notebooks from articles indexed in PubMed Central has grown in a highly dynamic fashion. RESULTS: Out of 27,271 Jupyter notebooks from 2,660 GitHub repositories associated with 3,467 publications, 22,578 notebooks were written in Python, including 15,817 that had their dependencies declared in standard requirement files and that we attempted to rerun automatically. For 10,388 of these, all declared dependencies could be installed successfully, and we reran them to assess reproducibility. Of these, 1,203 notebooks ran through without any errors, including 879 that produced results identical to those reported in the original notebook and 324 for which our results differed from the originally reported ones. Running the other notebooks resulted in exceptions. CONCLUSIONS: We zoom in on common problems and practices, highlight trends, and discuss potential improvements to Jupyter-related workflows associated with biomedical publications.

Continued use of retracted papers: Temporal trends in citations and (lack of) awareness of retractions shown in citation contexts in biomedicine.

We present the first database-wide study on the citation contexts of retracted papers, which covers 7,813 retracted papers indexed in PubMed, 169,434 citations collected from iCite, and 48,134 citation contexts identified from the XML version of the PubMed Central Open Access Subset. Compared with previous citation studies that focused on comparing citation counts using two time frames (i.e., preretraction and postretraction), our analyses show the longitudinal trends of citations to retracted papers in the past 60 years (1960-2020). Our temporal analyses show that retracted papers continued to be cited, but that old retracted papers stopped being cited as time progressed. Analysis of the text progression of pre- and postretraction citation contexts shows that retraction did not change the way the retracted papers were cited. Furthermore, among the 13,252 postretraction citation contexts, only 722 (5.4%) citation contexts acknowledged the retraction. In these 722 citation contexts, the retracted papers were most commonly cited as related work or as an example of problematic science. Our findings deepen the understanding of why retraction does not stop citation and demonstrate that the vast majority of postretraction citations in biomedicine do not document the retraction.

The Journal of Minimally Invasive Surgery is indexed by PubMed Central in 2022.

The Journal of Minimally Invasive Surgery (JMIS) is the official journal of the Korean Society of Endo-Laparoscopic & Robotic Surgery (formerly the Korean Society of Endoscopic and Laparoscopic Surgeons). The editorial board of JMIS has been trying steadily for several years to be indexed by the international literature databases. As a first step, JMIS has been deposited into PubMed Central in 2022. Here I would like to show you the path that JMIS has been following over the years.

Software review: The JATSdecoder package-extract metadata, abstract and sectioned text from NISO-JATS coded XML documents; Insights to PubMed central's open access database.

JATSdecoder is a general toolbox which facilitates text extraction and analytical tasks on NISO-JATS coded XML documents. Its function JATSdecoder() outputs metadata, the abstract, the sectioned text and reference list as easy selectable elements. One of the biggest repositories for open access full texts covering biology and the medical and health sciences is PubMed Central (PMC), with more than 3.2 million files. This report provides an overview of the PMC document collection processed with JATSdecoder(). The development of extracted tags is displayed for the full corpus over time and in greater detail for some meta tags. Possibilities and limitations for text miners working with scientific literature are outlined. The NISO-JATS-tags are used quite consistently nowadays and allow a reliable extraction of metadata and text elements. International collaborations are more present than ever. There are obvious errors in the date stamps of some documents. Only about half of all articles from 2020 contain at least one author listed with an author identification code. Since many authors share the same name, the identification of person-related content is problematic, especially for authors with Asian names. JATSdecoder() reliably extracts key metadata and text elements from NISO-JATS coded XML files. When combined with the rich, publicly available content within PMCs database, new monitoring and text mining approaches can be carried out easily. Any selection of article subsets should be carefully performed with in- and exclusion criteria on several NISO-JATS tags, as both the subject and keyword tags are used quite inconsistently.

The sharing of research data facing the COVID-19 pandemic.

During the previous Ebola and Zika outbreaks, researchers shared their data, allowing many published epidemiological studies to be produced only from open research data, to speed up investigations and control of these infections. This study aims to evaluate the dissemination of the COVID-19 research data underlying scientific publications. Analysis of COVID-19 publications from December 1, 2019, to April 30, 2020, was conducted through the PubMed Central repository to evaluate the research data available through its publication as supplementary material or deposited in repositories. The PubMed Central search generated 5,905 records, of which 804 papers included complementary research data, especially as supplementary material (77.4%). The most productive journals were The New England Journal of Medicine, The Lancet and The Lancet Infectious Diseases, the most frequent keyword was pneumonia, and the most used repositories were GitHub and GenBank. An expected growth in the number of published articles following the course of the pandemics is confirmed in this work, while the underlying research data are only 13.6%. It can be deduced that data sharing is not a common practice, even in health emergencies, such as the present one. High-impact generalist journals have accounted for a large share of global publishing. The topics most often covered are related to epidemiological and public health concepts, genetics, virology and respiratory diseases, such as pneumonia. However, it is essential to interpret these data with caution following the evolution of publications and their funding in the coming months.

A Bibliometric Analysis on Dengue Outbreaks in Tropical and Sub-Tropical Climates Worldwide Since 1950.

Severe dengue outbreaks (DOs) affect the majority of Asian and Latin American countries. Whether all DOs always occurred in sub-tropical and tropical areas (STTA) has not been verified. We downloaded abstracts by searching keywords "dengue (MeSH Major Topic)" from Pubmed Central since 1950, including three collections: country names in abstracts (CNA), no abstracts (WA), and no country names in abstracts (Non-CNA). Visualizations were created to present the DOs across countries/areas in STTA. The percentages of mentioned country names and authors' countries in STTA were computed on the CNA and Non-CNA bases. The social network analysis was applied to highlight the most cited articles and countries. We found that (1) three collections are 3427 (25.48%), 3137 (23.33%), and 6884 (51.19%) in CNA, WA, and Non-CNA, respectively; (2) the percentages of 94.3% and 79.9% were found in the CNA and Non-CNA groups; (3) the most mentioned country in abstracts were India, Thailand, and Brazil; (4) most authors in the Non-CNA collections were from the United States, Brazil, and China; (5) the most cited article (PMID = 23563266) authored by Bhatt et al. had 2604 citations since 2013. Our findings provide in-depth insights into the DO knowledge. The research approaches are recommended for authors in research on other infectious diseases in the future, not just limited to the DO topic.

Interdisciplinary influences in headache literature: A network citation analysis of PubMed Central articles.

BACKGROUND: Non-headache literature inevitably influences headache research, but the way this interdisciplinary interaction occurs has seldom been evaluated. OBJECTIVE: Utilizing network analysis techniques within the PubMed Central (PMC) database, we illustrate a novel method by which to identify and characterize the important non-headache literature with significant impact within the headache world. METHODS: Using the National Center for Biotechnology Information E-utilities application programing interface and custom backend software, all PMC articles containing the words "headache(s)" and/or "migraine(s)" in the title were identified. This generated a list of "seed articles" to represent the body of primary headache literature. Articles referenced by the seeds were then found, generating the list of articles with one degree of separation from the seeds (first-degree neighbors). This was iterated twice more to find the second- and third-degree neighbors. A directed network graph was generated for each level of separation using these articles and their referential connections. The hyperlink-induced topic search (HITS) and PageRank algorithms were used on these graphs to find the top 50 articles in the network (hub and authority rank via HITS, general rank via PageRank). Removing seed articles from the ranked lists left the influential non-headache articles at each level of separation. RESULTS: We extracted 6890 seed articles. The first-, second-, and third-degree models contained 16,451, 105,496, and 431,748 articles, respectively. As expected, most first-degree neighbors were part of the seed group (headache literature). Using HITS, at the second degree, only two seed articles were found in the top 50 hubs (none in the authorities); the majority of non-seed articles were basic neuroscience, involving ion channel function or cell signaling. At the third degree, there were no seeds and all articles involved imaging/structure of brain connectivity networks. PageRank gave more varied results, with 35/50 second-degree articles being seeds, and the remainder a mixture of articles describing rating scales (3), epidemiology/disease burden (3), basic statistical/trial methods (3), and mixed basic science (6). At the third degree, five were seeds; non-seed articles were represented heavily by genomic mapping studies, brain connectivity networks, and ion channel/neurotransmitter studies. CONCLUSION: This work demonstrates the value of network citation analysis in the identification of interdisciplinary influences on headache medicine. Articles found with this technique via HITS identified and grouped basic science applicable to headache medicine at the molecular scale (ion channels/transmitters), and whole-brain scale (connectivity networks). Both groups have direct clinical correlates, with the former implicating pharmacological targets, and the latter implicating functional neuroanatomy and pathophysiology of various headache disorders. Likely, in-depth analysis of the whole network (rather than the top 50) would reveal further clusters where the relationship to headache may not be as immediately obvious. This may not only help to guide ongoing work, but also identify new targets where seemingly unrelated work may have future applications in headache management.

Using Kano diagrams to display the most cited article types, affiliated countries, authors and MeSH terms on spinal surgery in recent 12 years.

BACKGROUND: Citation analysis has been increasingly applied to assess the quantity and quality of scientific research in various fields worldwide. However, these analyses on spinal surgery do not provide visualization of results. This study aims (1) to evaluate the worldwide research citations and publications on spinal surgery and (2) to provide visual representations using Kano diagrams onto the research analysis for spinal surgeons and researchers. METHODS: Article abstracts published between 2007 and 2018 were downloaded from PubMed Central (PMC) in 5 journals, including Spine, European Spine Journal, The Spine Journal, Journal of Neurosurgery: Spine, and Journal of Spinal Disorders and Techniques. The article types, affiliated countries, authors, and Medical subject headings (MeSH terms) were analyzed by the number of article citations using x-index. Choropleth maps and Kano diagrams were applied to present these results. The trends of MeSH terms over the years were plotted and analyzed. RESULTS: A total of 18,808 publications were extracted from the PMC database, and 17,245 were affiliated to countries/areas. The 12-year impact factor for the five spine journals is 5.758. We observed that (1) the largest number of articles on spinal surgery was from North America (6417, 37.21%). Spine earns the highest x-index (= 82.96). Comparative Study has the highest x-index (= 66.74) among all article types. (2) The United States performed exceptionally in x-indexes (= 56.86 and 44.5) on both analyses done on the total 18,808 and the top 100 most cited articles, respectively. The most influential author whose x-index reaches 15.11 was Simon Dagenais from the US. (3) The most cited MeSH term with an x-index of 23.05 was surgery based on the top 100 most cited articles. The most cited article (PMID = 18164449) was written by Dagenais and his colleagues in 2008. The most productive author was Michael G. Fehlings, whose x-index and the author's impact factor are 13.57(= √(13.16*14)) and 9.86(= 331.57/33.64), respectively. CONCLUSIONS: There was a rapidly increasing scientific productivity in the field of spinal surgery in the past 12 years. The US has extraordinary contributions to the publications. Furthermore, China and Japan have increasing numbers of publications on spinal surgery. This study with Kano diagrams provides an insight into the research for spinal surgeons and researchers.

IJPR in PubMed Central: A contribution to the Latin America's Scientific Production and Edition.

This article had two objectives: 1. Identify the Latin American journals in PMC, discriminate them by country, fields of knowledge, and indexations in Scopus and Web of Science (WOS). 2. Identify Colombian journals, especially those that could be potential publications for PMC. To fulfill the objectives, the list of PMC journals, the Scimago Journal & Country Rank (SJR) database, the main WOS collection, the Publindex bibliographic index database were examined and the journals were categorized by field of knowledge, following the classification model of the Organisation for Economic Cooperation and Development (OECD). As a result, it was found that of the 3194 journals indexed in PMC, 40 are from Latin America (1.25%). Of these, 39 are in Scopus and 25 in WOS, 36 are from Brazil and 2 belong to the field of psychology. In Colombia, 275 journals indexed in Publindex were found, 63 belong to the medical and health sciences, biological sciences, and psychology; 27 are found in Scopus, 8 in WOS, and 2 in PMC. It was concluded that there is a low indexation in PMC of Latin American journals and the inclusion of two psychology journals was highlighted. Colombia has quality journals and international recognition that can advance to indexing in MEDLINE and PMC.

Este artículo tuvo dos objetivos: 1. Identificar las revistas latinoamericanas en PMC, discriminarlas por país, áreas de conocimiento e indexaciones en Scopus y Web of Science (WOS). 2. Identificar las revistas colombianas, especialmente aquellas que podrían ser potenciales publicaciones para PMC. Para dar cumplimiento a los objetivos, se minó el listado de revistas de PMC, la base de datos de Scimago Journal & Country Rank (SJR), la colección principal de WOS, la base de datos del índice bibliográfico Publindex y se categorizaron las revistas por área de conocimiento siguiendo el modelo de clasificación de la Organización para la Cooperación y el Desarrollo Económicos (OCDE). Como resultados se encontraron que de las 3194 revistas indexadas en PMC, 40 son de América Latina (1,25%). De estas, 39 se encuentran en Scopus y 25 en WOS, 36 son de Brasil y 2 pertenecen al área de la psicología. En Colombia se encontraron 275 revistas indexadas en Publindex, 63 son de las ciencias médicas y de la salud, ciencias biológicas y de psicología. De estas, 27 se encuentran en Scopus, 8 en WOS y 2 en PMC. Se llegó a la conclusión que hay una baja indexación en PMC de revistas latinoamericanas y se destacó la inclusión de dos revistas de psicología. Colombia cuenta con revistas de calidad y reconocimiento internacional que pueden avanzar a la indexación en MEDLINE y PMC.

Predatory Open Access Journals are Indexed in Reputable Databases: a Revisiting Issue or an Unsolved Problem.

INTRODUCTION: Pseudo journals, hijacked journals, fraudulent journals, fake journals, and predatory journals waste valuable research when authors publish their studies in them. AIM: This article described novel suggested features for the identification of fraudulent journals and aimed to explain this issue to help inexperienced scientists avoid publishing in predatory journals. METHODS: The articles related to this topic in were retrieved from PubMed and trustable Internet sources. RESULTS: Unfortunately, some fake journals have made their way into reputable databases, such as PubMed, PubMed Central, MEDLINE, SCOPUS, and Web of Science; thus, the serious question has been raised regarding how we should address this problematic phenomenon. We recommended 28 suggested characteristics of predatory journals for readers to take into consideration. CONCLUSION: Unaware of the detrimental effects associated with publishing in disreputable journals, inexperienced researchers can fall victim to them. Together, as both readers and writers, we should completely boycott predatory journals.

Using the Kano model to display the most cited authors and affiliated countries in schizophrenia research.

In order to improve individual research achievements (IRA), this study investigates which affiliated countries and authors earn the most cited IRAs and whether those types of articles are associated with the number of cited papers on schizophrenia from a leading journal in the field. The Kano model was used for displaying the IRAs. Clusters of medical subject headings (MeSH) were applied to explore the core concepts of a given journal. This study aimed to apply social network analysis (SNA) and an authorship-weighted scheme (AWS) to inspect the association between MeSH terms and IRA. About 2,008 abstracts published between 2012 and 2016 in the journal Schizophrenia Research were downloaded from Pubmed Central using the keyword (Schizophr Res)[Journal] on September 20, 2018. The MeSH terms were clustered by using SNA to separate the core concepts and compare the differences in bibliometric indices (i.e., h, Ag, x and author impact factor or AIF). Visual dashboards were shown on Google Maps. Results indicate that (1) the US, the UK, and Canada earn the highest x-index; (2) the top one author from the US has the highest x-index (= 5.73 with x-core at cited = 16.44 and citable = 2); (3) the article type of schizophrenic psychology shows distinctly higher frequencies than others; and (4) article types are associated with the number of cited papers. Four approaches of the Kano model, SNA, MeSH terms, and AWS can be accommodated to display IRAs, classify article types, and quantify coauthor contributions in the article byline, respectively, and applied to other scientific disciplines in the future, not just in this specific journal.

Worldwide inequality in access to full text scientific articles: the example of ophthalmology.

BACKGROUND: The problem of access to medical information, particularly in low-income countries, has been under discussion for many years. Although a number of developments have occurred in the last decade (e.g., the open access (OA) movement and the website Sci-Hub), everyone agrees that these difficulties still persist very widely, mainly due to the fact that paywalls still limit access to approximately 75% of scholarly documents. In this study, we compare the accessibility of recent full text articles in the field of ophthalmology in 27 established institutions located worldwide. METHODS: A total of 200 references from articles were retrieved using the PubMed database. Each article was individually checked for OA. Full texts of non-OA (i.e., "paywalled articles") were examined to determine whether they were available using institutional and Hinari access in each institution studied, using "alternative ways" (i.e., PubMed Central, ResearchGate, Google Scholar, and Online Reprint Request), and using the website Sci-Hub. RESULTS: The number of full texts of "paywalled articles" available using institutional and Hinari access showed strong heterogeneity, scattered between 0% full texts to 94.8% (mean = 46.8%; SD = 31.5; median = 51.3%). We found that complementary use of "alternative ways" and Sci-Hub leads to 95.5% of full text "paywalled articles," and also divides by 14 the average extra costs needed to obtain all full texts on publishers' websites using pay-per-view. CONCLUSIONS: The scant number of available full text "paywalled articles" in most institutions studied encourages researchers in the field of ophthalmology to use Sci-Hub to search for scientific information. The scientific community and decision-makers must unite and strengthen their efforts to find solutions to improve access to scientific literature worldwide and avoid an implosion of the scientific publishing model. This study is not an endorsement for using Sci-Hub. The authors, their institutions, and publishers accept no responsibility on behalf of readers.

Open Access Publishing in India: Coverage, Relevance, and Future Perspectives.

Open access (OA) publishing is a recent phenomenon in scientific publishing, enabling free access to knowledge worldwide. In the Indian context, OA to science has been facilitated by government-funded repositories of student and doctoral theses, and many Indian society journals are published with platinum OA. The proportion of OA publications from India is significant in a global context, and Indian journals are increasingly available on OA repositories such as Pubmed Central, and Directory of Open Access Journals. However, OA in India faces numerous challenges, including low-quality or predatory OA journals, and the paucity of funds to afford gold OA publication charges. There is a need to increase awareness amongst Indian academics regarding publication practices, including OA, and its potential benefits, and utilize this modality of publication whenever feasible, as in publicly-funded research, or when platinum OA is available, while avoiding falling prey to poor quality OA journals.

Open Access Publishing in India: Coverage, Relevance, and Future Perspectives

Open access (OA) publishing is a recent phenomenon in scientific publishing, enabling free access to knowledge worldwide. In the Indian context, OA to science has been facilitated by government-funded repositories of student and doctoral theses, and many Indian society journals are published with platinum OA. The proportion of OA publications from India is significant in a global context, and Indian journals are increasingly available on OA repositories such as Pubmed Central, and Directory of Open Access Journals. However, OA in India faces numerous challenges, including low-quality or predatory OA journals, and the paucity of funds to afford gold OA publication charges. There is a need to increase awareness amongst Indian academics regarding publication practices, including OA, and its potential benefits, and utilize this modality of publication whenever feasible, as in publicly-funded research, or when platinum OA is available, while avoiding falling prey to poor quality OA journals.

The Sharing of Research Data in the Cell & Tissue Engineering Area: Is It a Common Practice?

The availability of research data sets is an important milestone because it can enhance the dynamics of research. This study aims to analyze the PubMed Central repository to determine the availability and type of raw data sets in Cell & Tissue Engineering journals indexed in Journal Citation Reports. The number and types of files were registered. The main finding of this study is that, beyond the mandatory deposit of data in specific repositories that some journals require, the exchange of data as supplementary material in the Cell & Tissue Engineering journals is not a common practice since researchers are still reticent to do so.

Semantic relatedness and similarity of biomedical terms: examining the effects of recency, size, and section of biomedical publications on the performance of word2vec.

BACKGROUND: Understanding semantic relatedness and similarity between biomedical terms has a great impact on a variety of applications such as biomedical information retrieval, information extraction, and recommender systems. The objective of this study is to examine word2vec's ability in deriving semantic relatedness and similarity between biomedical terms from large publication data. Specifically, we focus on the effects of recency, size, and section of biomedical publication data on the performance of word2vec. METHODS: We download abstracts of 18,777,129 articles from PubMed and 766,326 full-text articles from PubMed Central (PMC). The datasets are preprocessed and grouped into subsets by recency, size, and section. Word2vec models are trained on these subtests. Cosine similarities between biomedical terms obtained from the word2vec models are compared against reference standards. Performance of models trained on different subsets are compared to examine recency, size, and section effects. RESULTS: Models trained on recent datasets did not boost the performance. Models trained on larger datasets identified more pairs of biomedical terms than models trained on smaller datasets in relatedness task (from 368 at the 10% level to 494 at the 100% level) and similarity task (from 374 at the 10% level to 491 at the 100% level). The model trained on abstracts produced results that have higher correlations with the reference standards than the one trained on article bodies (i.e., 0.65 vs. 0.62 in the similarity task and 0.66 vs. 0.59 in the relatedness task). However, the latter identified more pairs of biomedical terms than the former (i.e., 344 vs. 498 in the similarity task and 339 vs. 503 in the relatedness task). CONCLUSIONS: Increasing the size of dataset does not always enhance the performance. Increasing the size of datasets can result in the identification of more relations of biomedical terms even though it does not guarantee better precision. As summaries of research articles, compared with article bodies, abstracts excel in accuracy but lose in coverage of identifiable relations.

An Improved Forensic Science Information Search.

Although thousands of search engines and databases are available online, finding answers to specific forensic science questions can be a challenge even to experienced Internet users. Because there is no central repository for forensic science information, and because of the sheer number of disciplines under the forensic science umbrella, forensic scientists are often unable to locate material that is relevant to their needs. The author contends that using six publicly accessible search engines and databases can produce high-quality search results. The six resources are Google, PubMed, Google Scholar, Google Books, WorldCat, and the National Criminal Justice Reference Service. Carefully selected keywords and keyword combinations, designating a keyword phrase so that the search engine will search on the phrase and not individual keywords, and prompting search engines to retrieve PDF files are among the techniques discussed.