Search

Background: An article's citations are useful for finding related articles that may not be readily found by keyword searches or textual similarity. Citation analysis is also important for analyzing scientific innovation and the structure of the biomedical literature. We wanted to facilitate citation analysis for the broad community by providing a user-friendly interface for accessing and analyzing citation data for biomedical articles. Case Presentation: We seeded the Citation Cloud dataset with over 465 million open access citations culled from six different sources: PubMed Central, Microsoft Academic Graph, ArnetMiner, Semantic Scholar, Open Citations, and the NIH iCite dataset. We implemented a free, public extension to PubMed that allows any user to visualize and analyze the entire citation cloud around any paper of interest A: the set of articles cited by A, those which cite A, those which are cocited with A, and those which are bibliographically coupled to A. Conclusions: Citation Cloud greatly enables the study of citations by the scientific community, including relatively advanced analyses (co-citations and bibliographic coupling) that cannot be undertaken using other available tools. The tool can be accessed by running any PubMed query on the Anne O'Tate value-added search interface and clicking on the Citations button next to any retrieved article. [ABSTRACT FROM AUTHOR]

Over a decade ago, we introduced Anne O'Tate, a free, public web-based tool http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith%5fuic/AnneOTate.cgi to support user-driven summarization, drill-down and mining of search results from PubMed, the leading search engine for biomedical literature. A set of hotlinked buttons allows the user to sort and rank retrieved articles according to important words in titles and abstracts; topics; author names; affiliations; journal names; publication year; and clustered by topic. Any result can be further mined by choosing any other button, and small search results can be expanded to include related articles. It has been deployed continuously, serving a wide range of biomedical users and needs, and over time has also served as a platform to support the creation of new tools that address additional needs. Here we describe the current, greatly expanded implementation of Anne O'Tate, which has added additional buttons to provide new functionalities: We now allow users to sort and rank search results by important phrases contained in titles and abstracts; the number of authors listed on the article; and pairs of topics that co-occur significantly more than chance. We also display articles according to NLM-indexed publication types, as well as according to 50 different publication types and study designs as predicted by a novel machine learning-based model. Furthermore, users can import search results into two new tools: e) Mine the Gap!, which identifies pairs of topics that are under-represented within set of the search results, and f) Citation Cloud, which for any given article, allows users to visualize the set of articles that cite it; that are cited by it; that are co-cited with it; and that are bibliographically coupled to it. We invite the scientific community to explore how Anne O'Tate can assist in analyzing biomedical literature, in a variety of use cases. [ABSTRACT FROM AUTHOR]

A recent flood of publications has documented serious problems in scientific reproducibility, power, and reporting of biomedical articles, yet scientists persist in their usual practices. Why? We examined a popular and important preclinical assay, the Forced Swim Test (FST) in mice used to test putative antidepressants. Whether the mice were assayed in a naïve state vs. in a model of depression or stress, and whether the mice were given test agents vs. known antidepressants regarded as positive controls, the mean effect sizes seen in the experiments were indeed extremely large (1.5–2.5 in Cohen's d units); most of the experiments utilized 7–10 animals per group which did have adequate power to reliably detect effects of this magnitude. We propose that this may at least partially explain why investigators using the FST do not perceive intuitively that their experimental designs fall short—even though proper prospective design would require ~21–26 animals per group to detect, at a minimum, large effects (0.8 in Cohen's d units) when the true effect of a test agent is unknown. Our data provide explicit parameters and guidance for investigators seeking to carry out prospective power estimation for the FST. More generally, altering the real-life behavior of scientists in planning their experiments may require developing educational tools that allow them to actively visualize the inter-relationships among effect size, sample size, statistical power, and replicability in a direct and intuitive manner. [ABSTRACT FROM AUTHOR]

Many investigators have carried out text mining of the biomedical literature for a variety of purposes, ranging from the assignment of indexing terms to the disambiguation of author names. A common approach is to define positive and negative training examples, extract features from article metadata, and use machine learning algorithms. At present, each research group tackles each problem from scratch, in isolation of other projects, which causes redundancy and a great waste of effort. Here, we propose and describe the design of a generic platform for biomedical text mining, which can serve as a shared resource for machine learning projects and as a public repository for their outputs. We initially focus on a specific goal, namely, classifying articles according to publication type and emphasize how feature sets can be made more powerful and robust through the use of multiple, heterogeneous similarity measures as input to machine learning models. We then discuss how the generic platform can be extended to include a wide variety of other machine learning-based goals and projects and can be used as a public platform for disseminating the results of natural language processing (NLP) tools to endusers as well. [ABSTRACT FROM AUTHOR]

Purpose: The late Don R. Swanson was well appreciated during his lifetime as Dean of the Graduate Library School at University of Chicago, as winner of the American Society for Information Science Award of Merit for 2000, and as author of many seminal articles. In this informal essay, I will give my personal perspective on Don's contributions to science, and outline some current and future directions in literature-based discovery that are rooted in concepts that he developed. Design/methodology/approach: Personal recollections and literature review. Findings: The Swanson A-B-C model of literature-based discovery has been successfully used by laboratory investigators analyzing their findings and hypotheses. It continues to be a fertile area of research in a wide range of application areas including text mining, drug repurposing, studies of scientific innovation, knowledge discovery in databases, and bioinformatics. Recently, additional modes of discovery that do not follow the A-B-C model have also been proposed and explored (e.g. so-called storytelling, gaps, analogies, link prediction, negative consensus, outliers, and revival of neglected or discarded research questions). Research limitations: This paper reflects the opinions of the author and is not a comprehensive nor technically based review of literature-based discovery. Practical implications: The general scientific public is still not aware of the availability of tools for literature-based discovery. Our Arrowsmith project site maintains a suite of discovery tools that are free and open to the public (http://arrowsmith.psych.uic.edu), as does BITOLA which is maintained by Dmitar Hristovski (http://http://ibmi.mf.uni-lj.si/bitola), and Epiphanet which is maintained by Trevor Cohen (http://epiphanet.uth.tmc.edu/). Bringing user-friendly tools to the public should be a high priority, since even more than advancing basic research in informatics, it is vital that we ensure that scientists actually use discovery tools and that these are actually able to help them make experimental discoveries in the lab and in the clinic. Originality/value: This paper discusses problems and issues which were inherent in Don's thoughts during his life, including those which have not yet been fully taken up and studied systematically. [ABSTRACT FROM AUTHOR]

Objective: The researchers assessed prevalence in the clinical case report literature of multiple reports independently reporting the same (or nearly the same) main finding. Methods: Results from forty-five PubMed queries were examined for incidence and features of main findings ("nuggets") shared in at least four case reports. Results: The authors found that nuggets are surprisingly prevalent and large in the case report literature, the largest found so far was reported in seventeen articles. In most cases, the main findings of case reports were evident from examining titles alone. Conclusions: Our curated examples should serve as gold standards for developing specific automated methods for finding nuggets. Nuggets potentially enable finding-based (instead of topic-based) information retrieval. [ABSTRACT FROM AUTHOR]

In the present paper, we have created several novel journal similarity metrics. The MeSH odds ratio measures the topical similarity of any pair of journals, based on the major MeSH headings assigned to articles in MEDLINE. The second metric employed the 2009 Author-ity author name disambiguation dataset as a gold standard for estimating the author odds ratio. This gives a straightforward, intuitive answer to the question: Given two articles in PubMed that share the same author name (lastname, first initial), how does knowing only the identity of the journals (in which the articles were published) predict the relative likelihood that they are written by the same person vs. different persons? The article pair odds ratio detects the tendency of authors to publish repeatedly in the same journal, as well as in specific pairs of journals. The metrics can be applied not only to estimate the similarity of a pair of journals, but to provide novel profiles of individual journals as well. For example, for each journal, one can define the MeSH cloud as the number of other journals that are topically more similar to it than expected by chance, and the author cloud as the number of other journals that share more authors than expected by chance. These metrics for journal pairs and individual journals have been provided in the form of public datasets that can be readily studied and utilized by others. [ABSTRACT FROM AUTHOR]

When a field shares the consensus that a particular phenomenon does NOT occur, this may reflect extensive experimental investigations with negative outcomes, or may represent the “common sense” position based on current knowledge and established ways of thinking. The current consensus of the RNA field is that eukaryotic Argonaute (Ago) proteins employ RNA guides and target other RNAs. The alternative – that eukaryotic Ago has biologically important interactions with DNA in vivo – has not been seriously considered, in part because the only role contemplated for DNA was as a guide strand, and in part because it did not seem plausible that any natural source of suitable DNAs exists in eukaryotic cells. However, eukaryotic Argonaute domains bind DNA in the test tube, and several articles report that small inhibitory double-stranded DNAs do have the ability to silence target RNAs in a sequence-dependent (though poorly characterized) manner. A search of the literature identified potential DNA binding partners for Ago, including (among others) single-stranded DNAs residing in extracellular vesicles, and cytoplasmic satellite-repeat DNA fragments that are associated with the plasma membrane and transcribed by Pol II. It is interesting to note that both cytoplasmic and extracellular vesicle DNA are expressed at greatly elevated levels in cancer cells relative to normal cells. In such a pathological scenario, if not under normal conditions, there may be appreciable binding of Ago to DNA despite its lower affinity compared to RNA. If so, DNA might displace Ago from binding to its normal partners (miRNAs, siRNAs and other short ncRNAs), disrupting tightly controlled post-transcriptional gene silencing processes that are vital to correct functioning of a normal cell. The possible contribution to cancer pathogenesis is a strong motivator for further investigation of Ago-DNA binding. More generally, this case underscores the need for better informatics tools to allow investigators to analyze the state of a given scientific question at a high-level and to identify possible new research directions. [ABSTRACT FROM AUTHOR]

If mRNAs were the only RNAs made by a neuron, there would be a simple mapping of mRNAs to proteins. However, micro RNAs and other non-coding RNAs (ncRNAs; endo-siRNAs, piRNAs, BC1, BC200, antisense and long ncRNAs, repeat-related transcripts, etc.) regulatem RNAs via effects on protein translation as well as transcriptional and epigenetic mechanisms. Not only are genes ON or OFF, but their ability to be translated can be turned ON or OFF at the level of synapses, supporting an enormous increase in information capacity. Here, I review evidence that ncRNAs are expressed pervasively within dendrites in mammalian brain; that some are activity-dependent and highly enriched near synapses; and that synaptic ncRNAs participate in plasticity responses including learning and memory. Ultimately, ncRNAs can be viewed as the post-it notes of the neuron. They have no literal meaning of their own, but derive their functions from where (and to what) they are stuck. This may explain, in part, why ncRNAs differ so dramatically from protein-coding genes, both in terms of the usual indicators of functionality and in terms of evolutionary constraints. ncRNAs do not appear to be direct mediators of synaptic transmission in the manner of neurotransmitters or receptors, yet they orchestrate synaptic plasticity-and may drive species-specific changes in cognition. [ABSTRACT FROM AUTHOR]

Because of the role played by miRNAs in post-transcriptional regulation of an array of genes, their impact in neuropsychiatric disease pathophysiology has increasingly been evident. In the present study, we assessed microRNA expression in prefrontal cortex (Brodmann area 10) of a well-characterized cohort of major depressed, bipolar, and schizophrenia subjects (obtained from Stanley Neuropathology Consortium; n = 15 in each group), using high throughput RT-PCR plates. Discrete miRNA alterations were observed in all disorders, as well as in suicide subjects (pooled across diagnostic categories) compared to all non-suicide subjects. The changes in the schizophrenia group were partially similar to those in the bipolar group, but distinct from changes in depression and suicide. Intriguingly, those miRNAs which were down-regulated in the schizophrenia group tended to be synaptically enriched, whereas up-regulated miRNAs tended not to be. To follow this up, we purified synaptosomes from pooled samples of the schizophrenia vs. control groups and subjected them to Illumina deep sequencing. There was a significant loss of small RNA expression in schizophrenia synaptosomes only for certain sequence lengths within the miRNA range. Moreover, 73 miRNAs were significantly down-regulated whereas only one was up-regulated. Strikingly, across all expressed miRNAs in synaptosomes, there was a significant inverse correlation between the fold-change of a given miRNA seen in schizophrenia and its synaptic enrichment ratio observed in controls. Thus, synaptic miRNAs tended to be down-regulated in schizophrenia, and the more highly synaptically enriched miRNAs tended to show greater down-regulation. These findings point to some deficit in miRNA biogenesis, transport, processing or turnover in schizophrenia that is selective for the synaptic compartment. A novel class of ncRNA-derived small RNAs, shown to be strongly induced during an early phase of learning in mouse, is also expressed in man, and at least one representative (SNORD85) was strongly down-regulated in schizophrenia synaptosomes. [ABSTRACT FROM AUTHOR]

Abstract: A decade ago, RNA interference was proposed to serve as a physiologic means of regulating long-term gene expression in the mammalian brain. However, during the intervening years, this hypothesis appeared to be contradicted by both experimental data and theoretical considerations. More recently, the advent of deep sequencing technology has permitted a re-assessment of this issue. As reviewed here, a large population of small RNAs having features characteristic of endogenous siRNAs are detected within adult mouse hippocampus, which derive from genes involved in synaptic structure and signaling, and which show a significant, though modest (16–22%) up-regulation during olfactory discrimination training. Small RNAs derived from abundant cellular noncoding RNAs are also detected; in particular, a subpopulation of RNAs 25–30 nt. in length shows very large (>100 fold) up-regulation during olfactory discrimination training. Preliminary data suggest that the 25–30 nt. RNAs may associate with MIWI rather than Argonaute 1–4 homologues. I conclude that, despite their apparent low abundance, endogenous siRNAs and noncoding RNA-derived small RNAs are likely to play an important role in regulating synaptic plasticity. [Copyright &y& Elsevier]

Background: Recent studies suggest that alterations in expression of genes, including those which regulate neural and structural plasticity, may be crucial in the pathogenesis of depression. MicroRNAs (miRNAs) are newly discovered regulators of gene expression that have recently been implicated in a variety of human diseases, including neuropsychiatric diseases. Methodology/Principal Findings: The present study was undertaken to examine whether the miRNA network is altered in the brain of depressed suicide subjects. Expression of miRNAs was measured in prefrontal cortex (Brodmann Area 9) of antidepressant-free depressed suicide (n = 18) and well-matched non-psychiatric control subjects (n = 17) using multiplex RT-PCR plates. We found that overall miRNA expression was significantly and globally down-regulated in prefrontal cortex of depressed suicide subjects. Using individual tests of statistical significance, 21 miRNAs were significantly decreased at p = 0.05 or better. Many of the down-regulated miRNAs were encoded at nearby chromosomal loci, shared motifs within the 5'-seeds, and shared putative mRNA targets, several of which have been implicated in depression. In addition, a set of 29 miRNAs, whose expression was not pairwise correlated in the normal controls, showed a high degree of co-regulation across individuals in the depressed suicide group. Conclusions/Significance: The findings show widespread changes in miRNA expression that are likely to participate in pathogenesis of major depression and/or suicide. Further studies are needed to identify whether the miRNA changes lead to altered expression of prefrontal cortex mRNAs, either directly (by acting as miRNA targets) or indirectly (e.g., by affecting transcription factors). [ABSTRACT FROM AUTHOR]

Literature-based discovery (LBD) refers to a particular type of text mining that seeks to identify nontrivial assertions that are implicit, and not explicitly stated, and that are detected by juxtaposing (generally a large body of) documents. In this review, I will provide a brief overview of LBD, both past and present, and will propose some new directions for the next decade. The prevalent ABC model is not 'wrong'; however, it is only one of several different types of models that can contribute to the development of the next generation of LBD tools. Perhaps the most urgent need is to develop a series of objective literature-based interestingness measures, which can customize the output of LBD systems for different types of scientific investigations. [ABSTRACT FROM AUTHOR]

Abstract: The Arrowsmith two-node search is a strategy that is designed to assist biomedical investigators in formulating and assessing scientific hypotheses. More generally, it allows users to identify biologically meaningful links between any two sets of articles A and C in PubMed, even when these share no articles or authors in common and represent disparate topics or disciplines. The key idea is to relate the two sets of articles via title words and phrases (B-terms) that they share. We have created a free, public web-based version of the two-node search tool (http://arrowsmith.psych.uic.edu), have described its development and implementation, and have presented analyses of individual two-node searches. In this paper, we provide an updated tutorial intended for end-users, that covers the use of the tool for a variety of potential scientific use case scenarios. For example, one can assess a recent experimental, clinical or epidemiologic finding that connects two disparate fields of inquiry—identifying likely mechanisms to explain the finding, and choosing promising follow-up lines of investigation. Alternatively, one can assess whether the existing scientific literature lends indirect support to a hypothesis posed by the user that has not yet been investigated. One can also employ two-node searches to search for novel hypotheses. Arrowsmith provides a service that cannot be carried out feasibly via standard PubMed searches or by other available text mining tools. [Copyright &y& Elsevier]

Abstract: Natural antisense transcripts and overlapping sense transcripts are expressed in a variety of tissues, including adult mouse brain. Here we show that a subset of mRNA-like sense–antisense transcript pairs are co-expressed within synaptoneurosomes of adult mouse forebrain, a subcellular fraction that is enriched in pinched-off dendritic spines of pyramidal neurons. Several of these pairs involve mRNAs that have been implicated in synaptic functions and in Alzheimer disease pathways. This study provides evidence that a new class of noncoding RNAs (natural antisense transcripts) are expressed near synapses, and encourages further studies of their roles in neuronal function. [Copyright &y& Elsevier]

Background: PubMed is designed to provide rapid, comprehensive retrieval of papers that discuss a given topic. However, because PubMed does not organize the search output further, it is difficult for users to grasp an overview of the retrieved literature according to non-topical dimensions, to drill-down to find individual articles relevant to a particular individual's need, or to browse the collection. Results: In this paper, we present Anne O'Tate, a web-based tool that processes articles retrieved from PubMed and displays multiple aspects of the articles to the user, according to pre-defined categories such as the "most important" words found in titles or abstracts; topics; journals; authors; publication years; and affiliations. Clicking on a given item opens a new window that displays all papers that contain that item. One can navigate by drilling down through the categories progressively, e.g., one can first restrict the articles according to author name and then restrict that subset by affiliation. Alternatively, one can expand small sets of articles to display the most closely related articles. We also implemented a novel cluster-by-topic method that generates a concise set of topics covering most of the retrieved articles. Conclusion: Anne O'Tate is an integrated, generic tool for summarization, drill-down and browsing of PubMed search results that accommodates a wide range of biomedical users and needs. It can be accessed at [4]. Peer review and editorial matters for this article were handled by Aaron Cohen. [ABSTRACT FROM AUTHOR]

Background: Many cell types have been reported to secrete small vesicles called exosomes, that are derived from multivesicular bodies and that can also form from endocytic-like lipid raft domains of the plasma membrane. Secretory exosomes contain a characteristic composition of proteins, and a recent report indicates that mast cell exosomes harbor a variety of mRNAs and microRNAs as well. Exosomes express cell recognition molecules on their surface that facilitate their selective targeting and uptake into recipient cells. Results: In this review, I suggest that exosomal secretion of proteins and RNAs may be a fundamental mode of communication within the nervous system, supplementing the known mechanisms of anterograde and retrograde signaling across synapses. In one specific scenario, exosomes are proposed to bud from the lipid raft region of the postsynaptic membrane adjacent to the postsynaptic density, in a manner that is stimulated by stimuli that elicit long-term potentiation. The exosomes would then transfer newly synthesized synaptic proteins (such as CAM kinase II alpha) and synaptic RNAs to the presynaptic terminal, where they would contribute to synaptic plasticity. Conclusion: The model is consistent with the known cellular and molecular features of synaptic neurobiology and makes a number of predictions that can be tested in vitro and in vivo. [ABSTRACT FROM AUTHOR]

Recently, we reported that four microRNAs show perfect complementarity with MIR/LINE-2 elements within human mRNAs. This finding raises the question of whether microRNAs might also target other genomic repeats and transposable elements. Here, we demonstrate that almost 30 human microRNAs exhibit typical short-seed complementarity with a specific site within Alu elements that is highly conserved within 3′ untranslated regions of human mRNAs. The results suggest that at least some Alu elements within human mRNAs serve as microRNA targets. [Copyright &y& Elsevier]

Arrowsmith, a computer-assisted process for literature-based discovery, takes as input two disjoint sets of records (A, C) from the Medline database. It produces a list of title words and phrases, B, that are common to A and C, and displays the title context in which each B-term occurs within A and within C. Subject experts then can try to find A–B and B–C title-pairs that together may suggest novel and plausible indirect A–C relationships (via B-terms) that are of particular interest in the absence of any known direct A–C relationship. The list of B-terms typically is so large that it is difficult to find the relatively few that contribute to scientifically interesting connections. The purpose of the present article is to propose and test several techniques for improving the quality of the B-list. These techniques exploit the Medical Subject Headings (MeSH) that are assigned to each input record. A MesH-based concept of literature cohesiveness is defined and plays a key role. The proposed techniques are tested on a published example of indirect connections between migraine and magnesium deficiency. The tests demonstrate how the earlier results can be replicated with a more efficient and more systematic computer-aided process. [ABSTRACT FROM AUTHOR]

Arrowsmith is a unique computer-assisted strategy designed to assist investigators in detecting biologically-relevant connections between two disparate sets of articles in Medline. This paper describes how an inter-institutional consortion of neuroscientists used the UIC Arrowsmith web interface http://arrowsmith.psych.uic.edu in their daily work and guided the development, refinement and expansion of the system into a suite of tools intended for used by the wider scientific community. [ABSTRACT FROM AUTHOR]

This informal tutorial is intended for investigators and students who would like to understand the workings of information retrieval systems, including the most frequently used search engines: PubMed and Google. Having a basic knowledge of the terms and concepts of information retrieval should improve the efficiency and productivity of searches. As well, this knowledge is needed in order to follow current research efforts in biomedical information retrieval and text mining that are developing new systems not only for finding documents on a given topic, but extracting and integrating knowledge across documents. [ABSTRACT FROM AUTHOR]

In this article, we show that a subset of conventional mammalian microRNAs is derived from LINE-2 transposable elements and other genome repeats. These repeat-derived microRNAs arise from conventional precursor hairpins and are distinct from the rasiRNAs, which appear to be processed from long double-stranded RNA precursors. The insertion of transposable elements into new genomic sites appears to be one of the driving-forces that create new microRNAs during mammalian evolution. Two of the LINE-2-derived microRNAs exhibit perfect complementarity to a large family of mRNA and EST transcripts that contain portions of MIR and other LINE-2 elements in their 3′-untranslated regions. [Copyright &y& Elsevier]

Background: MicroRNAs are ~17-24 nt. noncoding RNAs found in all eukaryotes that degrade messenger RNAs via RNA interference (if they bind in a perfect or near-perfect complementarity to the target mRNA), or arrest translation (if the binding is imperfect). Several microRNA targets have been identified in lower organisms, but only one mammalian microRNA target has yet been validated experimentally. Results: We carried out a population-wide statistical analysis of how human microRNAs interact complementarily with human mRNAs, looking for characteristics that differ significantly as compared with scrambled control sequences. These characteristics were used to identify a set of 71 outlier mRNAs unlikely to have been hit by chance. Unlike the case in C. elegans and Drosophila, many human microRNAs exhibited long exact matches (10 or more bases in a row), up to and including perfect target complementarity. Human microRNAs hit outlier mRNAs within the protein coding region about 2/3 of the time. And, the stretches of perfect complementarity within microRNA hits onto outlier mRNAs were not biased near the 5'-end of the microRNA. In several cases, an individual microRNA hit multiple mRNAs that belonged to the same functional class. Conclusions: The analysis supports the notion that sequence complementarity is the basis by which microRNAs recognize their biological targets, but raises the possibility that human microRNA-mRNA target interactions follow different rules than have been previously characterized in Drosophila and C. elegans. [ABSTRACT FROM AUTHOR]

To identify ligands that bind to the N-terminal portion of human amyloid precursor protein (APP), we sought binding partners for a fragment of the ectodomain of human APP695 (sAPP695T). The probe bound to fragments of high molecular weight kininogen (HK) in rat cortical membrane preparations in vitro. Laser confocal microscopy indicated that APP and HK colocalize near cerebral blood vessels, in the neuropil, and in many neurons of rat brain. sAPP695T bound to human activated kininogen (HKa) (Kd=0.3±0.1 nM), but not to inactivated or low molecular weight kininogen. Binding was specific for the light chain sequence of HKa. Biotinylated human HKa also bound to sAPP695 (Kd=0.3±0.5 nM). sAPP695 and HKa form tight complexes in solution that can be coimmunoprecipitated. These results support the hypothesis that forms of APP and kininogen can interact in brain tissue. Considering the implications of APP in neurite outgrowth, the APP–HKa interaction could modulate neurogenesis. [Copyright &y& Elsevier]

Provides methods relevant to information science. Utilization of novel informatics techniques to process the output of Medline searches; Categorization of viruses as potential weapons; Identification of two kinds of virus literatures.

Presents a study which determined the expression of reelin proteins in blood circulation, liver, pituitary pars intermedia and adrenal chromaffin cells of adult mammals. Methods used in the study; Results; Discussion.

Profiles neuroscientist Walter Pitts. Establishment of the notion of brain as a computer; Education at the University of Chicago; Alcoholism and drug addiction; Research on cybernetics.

Addresses the problem of finding interesting but previously unknown implicit information within the scientific literature. Example of two Medline titles in the process of inferring text linkages; Complementarity and noninteractivity properties of sets of scientific articles; Use of Arrowsmith software in creating juxtapositions of Medline records; Synonym recognition and the role of medical subject headings.

Studies the importance of parametric approaches in the analysis of cell behavior. Gene knock-outs in cells and transgenic mice that produce no overt phenotypic alterations; Example of a parametric approach to cell behavior; Theoretical and practical reasons for incorporating systematic variation of parameters into experiments.

The Journal of Biomedical Discovery and Collaboration was created to provide, for the first time, a unified forum to consider all factors that affect scientific practice and scientific discovery - with an emphasis on the changing face of contemporary biomedical science. In this endeavor we are bringing together three different groups of scholars: a) laboratory investigators, who make the discoveries that are the currency of the scientific enterprise; b) computer science and informatics investigators, who devise tools for data analysis, mining, visualization and integration; and c) social scientists, including sociologists, historians, and philosophers, who study scientific practice, collaboration, and information needs. We will publish original research articles, case studies, focus pieces, reviews, and software articles. All articles in the Journal of Biomedical Discovery and Collaboration will be peer reviewed, published immediately upon acceptance, freely available online via open access, and archived in PubMed Central and other international full-text repositories. [ABSTRACT FROM AUTHOR]

Investigates the advantages of RNA interference (RNAi) in brain function. Mechanism of action of RNAi; Functions of RNAi in the regulation of the changes in gene expression in brain; Methods in testing the effectiveness of RNAi in mammalian brain.

Clinical case reports are the 'eyewitness reports' of medicine and provide a valuable, unique, albeit noisy and underutilized type of evidence. Generally a case report has a single main finding that represents the reason for writing up the report in the first place. In the present study, we present the results of manual annotation carried out by two individuals on 500 randomly sampled case reports. This corpus contains main finding sentences extracted from title, abstract and full-text of the same article that can be regarded as semantically related and are often paraphrases. The final reconciled corpus of 416 articles comprises an open resource for further study. This is the first step in establishing text mining models and tools that can identify main finding sentences in an automated fashion, and in measuring quantitatively how similar any two main findings are. We envision that case reports in PubMed may be automatically indexed by main finding, so that users can carry out information queries for specific main findings (rather than general topics)—and given one case report, a user can retrieve those having the most similar main findings. The metric of main finding similarity may also potentially be relevant to the modeling of paraphrasing, summarization and entailment within the biomedical literature. [ABSTRACT FROM AUTHOR]

Abstract: Adult mice were trained to execute a nose-poke in a port containing one of two simultaneously present odors in order to obtain a reward. Hippocampus RNA of trained mice vs. controls was subjected to Illumina deep sequencing. Two mitochondrial RNAs (a tRNA and Mt-1) gave rise to 25–30-nt. small RNAs that showed a dramatic and specific increase with training (>50-fold relative to controls). Mt-1 is encoded within the termination association sequence (TAS) of the mitochondrial DNA control region. Small RNAs may link behavioral plasticity to protein synthesis and replication of mitochondria to support dendritic growth, spine stabilization, and synapse formation. [Copyright &y& Elsevier]

One of the most pressing and timely scientific questions concerns the evolution of man. In 1970, Karl Pribram delivered the James Arthur Lecture at the American Museum of Natural History in New York City. His lecture, "What Makes Man Human," was one of the most eloquent and brilliant syntheses of this problem ever made. The Journal is proud to publish this Lecture for the first time in an open access format that will make its insights available widely to a new generation of students and investigators. Accompanying the lecture is a new commentary written by Prof. Pribram, and four additional commentaries from prominent investigators who were invited to consider the question from their own perspectives. Together, these articles provide a scholarly, yet accessible, snapshot of different approaches to the study of human evolution in 2006. [ABSTRACT FROM AUTHOR]

Whether it's sharing reagents with a laboratory on the other side of the world or working with the postdoc at the neighboring bench, some simple rules of collaboration might help. [ABSTRACT FROM AUTHOR]

The article presents suggested guidelines for negotiating scientific collaboration. The guidelines here are discussed in terms of a collaboration involving a supplier such as of reagents, expertise, specialized equipment, data, methods, or computer code, which is denoted by Party 1 and a receiver denoted as Party 2. The options in each section are listed in order of increasing involvement by Party 1 in the collaboration. The first guideline is on sharing of reagents and data. Reagents or data will be provided that are essentially as described in published description, and Party 1 warrants that these will be prepared, stored, and shipped in a manner that will preserve their value.

The Medical Subject Heading 'Humans' is manually curated and indicates human-related studies within MEDLINE. However, newly published MEDLINE articles may take months to be indexed and non-MEDLINE articles lack consistent, transparent indexing of this feature. Therefore, for up to date and broad literature searches, there is a need for an independent automated system to identify whether a given publication is human-related, particularly when they lack Medical Subject Headings. One million MEDLINE records published in 1987–2014 were randomly selected. Text-based features from the title, abstract, author name and journal fields were extracted. A linear support vector machine was trained to estimate the probability that a given article should be indexed as Humans and was evaluated on records from 2015 to 2016. Overall accuracy was high: area under the receiver operating curve = 0.976, F1 = 95% relative to MeSH indexing. Manual review of cases of extreme disagreement with MEDLINE showed 73.5% agreement with the automated prediction. We have tagged all articles indexed in PubMed with predictive scores and have made the information publicly available at http://arrowsmith.psych.uic.edu/evidence%5fbased%5fmedicine/index.html. We have also made available a web-based interface to allow users to obtain predictive scores for non-MEDLINE articles. This will assist in the triage of clinical evidence for writing systematic reviews. [ABSTRACT FROM AUTHOR]

Neurons, glial, cells, and brain tumor cells tissues release small vesicles (secretory exosomes and microvesicles), which may represent a novel mechanism by which neuronal activity could influence angiogenesis within the embryonic and mature brain. If CNS-derived vesicles can enter the bloodstream as well, they may communicate with endothelial cells in the peripheral circulation and with cells concerned with immune surveillance. [ABSTRACT FROM AUTHOR]

Presents a correction to the article related to a probabilistic similarity metric for Medline records, published in the "Journal of the American Society for Information Science & Technology."

A letter to the editor commented on how bath toys can be the source of gatrointestinal infections.

Purpose: To examine whether National Institutes of Health (NIH) funded articles that were archived in PubMed Central (PMC) after the release of the 2008 NIH Public Access Policy show greater scholarly impact than comparable articles not archived in PMC. Methods: A list of journals across several subject areas was developed from which to collect article citation data. Citation information and cited reference counts of the articles published in 2006 and 2009 from 122 journals were obtained from the Scopus database. The articles were separated into categories of NIH funded, non-NIH funded and whether they were deposited in PubMed Central. An analysis of citation data across a five-year timespan was performed on this set of articles. Results: A total of 45,716 articles were examined, including 7,960 with NIH-funding. An analysis of the number of times these articles were cited found that NIH-funded 2006 articles in PMC were not cited significantly more than NIH-funded non-PMC articles. However, 2009 NIH funded articles in PMC were cited 26% more than 2009 NIH funded articles not in PMC, 5 years after publication. This result is highly significant even after controlling for journal (as a proxy of article quality and topic). Conclusion: Our analysis suggests that factors occurring between 2006 and 2009 produced a subsequent boost in scholarly impact of PubMed Central. The 2008 Public Access Policy is likely to be one such factor, but others may have contributed as well (e.g., growing size and visibility of PMC, increasing availability of full-text linkouts from PubMed, and indexing of PMC articles by Google Scholar). [ABSTRACT FROM AUTHOR]

Clinical case reports are the 'eyewitness reports' of medicine and provide a valuable, unique, albeit noisy and underutilized type of evidence. Generally, a case report has a single main finding that represents the reason for writing up the report in the first place. However, no one has previously created an automatic way of identifying main finding sentences in case reports. We previously created a manual corpus of main finding sentences extracted from the abstracts and full text of clinical case reports. Here, we have utilized the corpus to create a machine learning-based model that automatically predicts which sentence(s) from abstracts state the main finding. The model has been evaluated on a separate manual corpus of clinical case reports and found to have good performance. This is a step toward setting up a retrieval system in which, given one case report, one can find other case reports that report the same or very similar main findings. The code and necessary files to run the main finding model can be downloaded from https://github.com/qi29/main%5f finding_recognition , released under the Apache License, Version 2.0. [ABSTRACT FROM AUTHOR]

Background: Escherichia coli F18 is mainly responsible for post-weaning diarrhea (PWD) in piglets. The molecular regulation of E. coli F18 resistance in Chinese domestic weaned piglets is still obscure. We used Meishan piglets as model animals to test their susceptibility to E. coli F18. Small RNA duodenal libraries were constructed for E. coli F18-sensitive and -resistant weaned piglets challenged with E. coli F18 and sequenced using Illumina Solexa high-throughput sequencing technology. Results: Sequencing results showed that 3,475,231 and 37,198,259 clean reads were obtained, with 311 known miRNAs differently expressed in resistant and sensitive groups, respectively. Twenty-four miRNAs, including 15 up-regulated and 9 down-regulated, demonstrated more than a 2-fold differential expression between the F18-resistant and -sensitive piglets. Stem-loop RT-qPCR showed that miR-136, miR-196b, miR-499-5p and miR-218-3p significantly expressed in intestinal tissue (p < 0.05). KEGG pathway analysis for target genes revealed that differently expressed miRNAs were involved in infectious diseases, signal transduction and immune system pathways. Interestingly, the expression of miR-218-3p in intestinal tissue had a very significant negative correlation with target DLG5 (P < 0.01). Conclusions: Based on the expression correlation between miRNA and target genes analysis, we speculate that miR-218-3p targeting to DLG5, appears to be very promising candidate for miRNAs involved in response to E. coli F18 infection. The present study provides improved database information on pig miRNAs, better understanding of the genetic basis of E. coli F18 resistance in local Chinese pig breeds and lays a new foundation for identifying novel markers of E. coli F18 resistance. [ABSTRACT FROM AUTHOR]

To assess the value of exosomal miRNAs as biomarkers for Alzheimer disease (AD), the expression of microRNAs was measured in a plasma fraction enriched in exosomes by differential centrifugation, using Illumina deep sequencing. Samples from 35 persons with a clinical diagnosis of AD dementia were compared to 35 age and sex matched controls. Although these samples contained less than 0.1 microgram of total RNA, deep sequencing gave reliable and informative results. Twenty miRNAs showed significant differences in the AD group in initial screening (miR-23b-3p, miR-24-3p, miR-29b-3p, miR-125b-5p, miR-138-5p, miR-139-5p, miR-141-3p, miR-150-5p, miR-152-3p, miR-185-5p, miR-338-3p, miR-342-3p, miR-342-5p, miR-548at-5p, miR-659-5p, miR-3065-5p, miR-3613-3p, miR-3916, miR-4772-3p, miR-5001-3p), many of which satisfied additional biological and statistical criteria, and among which a panel of seven miRNAs were highly informative in a machine learning model for predicting AD status of individual samples with 83–89% accuracy. This performance is not due to over-fitting, because a) we used separate samples for training and testing, and b) similar performance was achieved when tested on technical replicate data. Perhaps the most interesting single miRNA was miR-342-3p, which was a) expressed in the AD group at about 60% of control levels, b) highly correlated with several of the other miRNAs that were significantly down-regulated in AD, and c) was also reported to be down-regulated in AD in two previous studies. The findings warrant replication and follow-up with a larger cohort of patients and controls who have been carefully characterized in terms of cognitive and imaging data, other biomarkers (e.g., CSF amyloid and tau levels) and risk factors (e.g., apoE4 status), and who are sampled repeatedly over time. Integrating miRNA expression data with other data is likely to provide informative and robust biomarkers in Alzheimer disease. [ABSTRACT FROM AUTHOR]

Objective It is important to identify separate publications that report outcomes from the same underlying clinical trial, in order to avoid over-counting these as independent pieces of evidence. Methods We created positive and negative training sets (comprised of pairs of articles reporting on the same condition and intervention) that were, or were not, linked to the same clinicaltrials.gov trial registry number. Features were extracted from MEDLINE and PubMed metadata; pairwise similarity scores were modeled using logistic regression. Results Article pairs from the same trial were identified with high accuracy (F1 score = 0.843). We also created a clustering tool, Aggregator, that takes as input a PubMed user query for RCTs on a given topic, and returns article clusters predicted to arise from the same clinical trial. Discussion Although painstaking examination of full-text may be needed to be conclusive, metadata are surprisingly accurate in predicting when two articles derive from the same underlying clinical trial. [ABSTRACT FROM AUTHOR]

We recently designed and deployed a metasearch engine, Metta, that sends queries and retrieves search results from five leading biomedical databases: PubMed, EMBASE, CINAHL, PsycINFO and the Cochrane Central Register of Controlled Trials. Because many articles are indexed in more than one of these databases, it is desirable to deduplicate the retrieved article records. This is not a trivial problem because data fields contain a lot of missing and erroneous entries, and because certain types of information are recorded differently (and inconsistently) in the different databases. The present report describes our rule-based method for deduplicating article records across databases and includes an open-source script module that can be deployed freely. Metta was designed to satisfy the particular needs of people who are writing systematic reviews in evidence-based medicine. These users want the highest possible recall in retrieval, so it is important to err on the side of not deduplicating any records that refer to distinct articles, and it is important to perform deduplication online in real time. Our deduplication module is designed with these constraints in mind. Articles that share the same publication year are compared sequentially on parameters including PubMed ID number, digital object identifier, journal name, article title and author list, using text approximation techniques. In a review of Metta searches carried out by public users, we found that the deduplication module was more effective at identifying duplicates than EndNote without making any erroneous assignments. [ABSTRACT FROM AUTHOR]

In a previous study, we reported that microRNA (mi RNA) precursors are expressed in synaptic fractions within adult mouse forebrain, where they are enriched at post-synaptic densities ( PSDs). However, because that study employed qRT-PCR primers that recognize the hairpin region, it was not able to distinguish between primary micro RNA gene transcripts (pri-miRs) and small hairpin precursors (pre-miRs). Here, using primer sets that selectively measure regions upstream, downstream and flanking the hairpin, we demonstrate that pri-miRs are present in synaptic fractions (enriched several-fold relative to total tissue homogenate) and are especially enriched in isolated PSDs. Drosha and DGCR8 proteins are also expressed in synaptic fractions and PSDs, and are tightly associated with pri-miRs as assessed by coimmunoprecipitation under stringent conditions. Pri-miRs, drosha, and DGCR8 are highly enriched in fractions that contain mRNA transport particles, and cytosolic drosha is associated with kinesin heavy chain; these findings suggest that pri-miRs are transported to synaptic regions in a manner similar to mRNAs. This study supports the notion that mi RNA biogenesis occurs locally near synapses in a regulated fashion. [ABSTRACT FROM AUTHOR]

We have characterized the expression of microRNAs and selected microRNA precursors within several synaptic fractions of adult mouse forebrain, including synaptoneurosomes, synaptosomes and isolated post-synaptic densities (PSDs), using methods of microRNA microarray, real time qRT-PCR, Northern blotting and immunopurification using anti-PSD95 antibody. The majority of brain microRNAs (especially microRNAs known to be expressed in pyramidal neurons) are detectably expressed in synaptic fractions, and a subset of microRNAs is significantly enriched in synaptic fractions relative to total forebrain homogenate. MicroRNA precursors are also detectable in synaptic fractions at levels that are comparable to whole tissue. Whereas mature microRNAs are predominantly associated with soluble components of the synaptic fractions, microRNA precursors are predominantly associated with PSDs. For seven microRNAs examined, there was a significant correlation between the relative synaptic enrichment of the precursor and the relative synaptic enrichment of the corresponding mature microRNA. These findings support the proposal that microRNAs are formed, at least in part, via processing of microRNA precursors locally within dendritic spines. Dicer is expressed in PSDs but is enzymatically inactive until conditions that activate calpain cause its liberation; thus, we propose that synaptic stimulation may lead to local processing of microRNA precursors in proximity to the synapse. [ABSTRACT FROM AUTHOR]

We have hypothesized that small RNAs may participate in learning and memory mechanisms. Because dendritic spines are important in synaptic plasticity and learning, we asked whether dicer, the rate-limiting enzyme in the formation of small RNAs, is enriched within dendritic spines. In adult mouse brain, dicer and the RNA-induced silencing complex (RISC) component eIF2c were expressed in the somatodendritic compartment of principal neurons and some interneurons in many regions, and dicer was enriched in dendritic spines and postsynaptic densities (PSDs). A portion of dicer and eIF2c were associated with each other and with fragile X mental retardation protein (FMRP), as assessed by co-immunoprecipitation. Calpain I treatment of recombinant dicer or immunopurified brain dicer caused a marked increase in RNAse III activity. Purified PSDs did not exhibit RNAse III activity, but calpain caused release of dicer from PSDs in an enzymatically active form, together with eIF2c. NMDA stimulation of hippocampal slices, or calcium treatment of synaptoneurosomes, caused a 75 kDa dicer fragment to appear in a calpain-dependent manner. The findings support a model whereby acute neuronal stimulation at excitatory synapses increases intracellular calcium, which activates calpain, which liberates dicer and eIF2c bound to PSDs. This supports the hypothesis that dicer could be involved in synaptic plasticity. [ABSTRACT FROM AUTHOR]