Pubmed

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, My NCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link(BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genome, Genome Project and related tools, the Trace and Assembly Archives, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Viral Genotyping Tools, Influenza Viral Resources, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus (GEO), Entrez Probe, GENSAT, Online Mendelian Inheritance in Man (OMIM), Online Mendelian Inheritance in Animals (OMIA), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD), the Conserved Domain Architecture Retrieval Tool (CDART) and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. These resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.

The evolution of the electronic age has led to the development of numerous medical databases on the World Wide Web, offering search facilities on a particular subject and the ability to perform citation analysis. We compared the content coverage and practical utility of PubMed, Scopus, Web of Science, and Google Scholar. The official Web pages of the databases were used to extract information on the range of journals covered, search facilities and restrictions, and update frequency. We used the example of a keyword search to evaluate the usefulness of these databases in biomedical information retrieval and a specific published article to evaluate their utility in performing citation analysis. All databases were practical in use and offered numerous search facilities. PubMed and Google Scholar are accessed for free. The keyword search with PubMed offers optimal update frequency and includes online early articles; other databases can rate articles by number of citations, as an index of importance. For citation analysis, Scopus offers about 20% more coverage than Web of Science, whereas Google Scholar offers results of inconsistent accuracy. PubMed remains an optimal tool in biomedical electronic research. Scopus covers a wider journal range, of help both in keyword searching and citation analysis, but it is currently limited to recent articles (published after 1995) compared with Web of Science. Google Scholar, as for the Web in general, can help in the retrieval of even the most obscure information but its use is marred by inadequate, less often updated, citation information.-Falagas, M. E., Pitsouni, E I., Malietzis, G. A., and Pappas, G. Comparison of Pub Med, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. FASEB J. 22, 338 -342 (2008)

Objective: Preclinical evaluation of neuroprotectants fostered high expectations of clinical efficacy. When not matched, the question arises whether experiments are poor indicators of clinical outcome or whether the best drugs were not taken forward to clinical trial. Therefore, we endeavored to contrast experimental efficacy and scope of testing of drugs used clinically and those tested only experimentally. Methods: We identified neuroprotectants and reports of experimental efficacy via a systematic search. Controlled in vivo and in vitro experiments using functional or histological end points were selected for analysis. Relationships between outcome, drug mechanism, scope of testing, and clinical trial status were assessed statistically. Results: There was no evidence that drugs used clinically (114 drugs) were more effective experimentally than those tested only in animal models (912 drugs), for example, improvement in focal models averaged 31.3 ؎ 16.7% versus 24.4 ؎ 32.9%, p > 0.05, respectively. Scope of testing using Stroke Therapy Academic Industry Roundtable (STAIR) criteria was highly variable, and no relationship was found between mechanism and efficacy. Interpretation: The results question whether the most efficacious drugs are being selected for stroke clinical trials. This may partially explain the slow progress in developing treatments. Greater rigor in the conduct, reporting, and analysis of animal data will improve the transition of scientific advances from bench to bedside.

Background Supporting 21st century health care and the practice of evidence-based medicine (EBM) requires ubiquitous access to clinical information and to knowledge-based resources to answer clinical questions. Many questions go unanswered, however, due to lack of skills in formulating questions, crafting effective search strategies, and accessing databases to identify best levels of evidence. Methods This randomized trial was designed as a pilot study to measure the relevancy of search results using three different interfaces for the PubMed search system. Two of the search interfaces utilized a specific framework called PICO, which was designed to focus clinical questions and to prompt for publication type or type of question asked. The third interface was the standard PubMed interface readily available on the Web. Study subjects were recruited from interns and residents on an inpatient general medicine rotation at an academic medical center in the US. Thirty-one subjects were rand...

We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso's two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquely named genes and an interaction term, the ontology confers a 3-fold increase of search efficiency. Textpresso currently focuses on Caenorhabditis elegans literature, with 3,800 full text articles and 16,000 abstracts. The lexicon of the ontology contains 14,500 entries, each of which includes all versions of a specific word or phrase, and it includes all categories of the Gene Ontology database. Textpresso is a useful curation tool, as well as search engine for researchers, and can readily be extended to other organism-specific corpora of text. Textpresso can be accessed at http://www.textpresso.org or via WormBase at http://www.wormbase.org.

Background: Focus group studies are increasingly published in health related journals, but we know little about how researchers use this method, particularly how they determine the number of focus groups to conduct. The methodological literature commonly advises researchers to follow principles of data saturation, although practical advise on how to do this is lacking. Our objectives were firstly, to describe the current status of sample size in focus group studies reported in health journals. Secondly, to assess whether and how researchers explain the number of focus groups they carry out. Methods: We searched PubMed for studies that had used focus groups and that had been published in open access journals during 2008, and extracted data on the number of focus groups and on any explanation authors gave for this number. We also did a qualitative assessment of the papers with regard to how number of groups was explained and discussed.

Artificial neural networks have featured in a wide range of medical journals, often with promising results. This paper reports on a systematic review that was conducted to assess the benefit of artificial neural networks (ANNs) as decision making tools in the field of cancer. The number of clinical trials (CTs) and randomised controlled trials (RCTs) involving the use of ANNs in diagnosis and prognosis increased from 1 to 38 in the last decade. However, out of 396 studies involving the use of ANNs in cancer, only 27 were either CTs or RCTs. Out of these trials, 21 showed an increase in benefit to healthcare provision and 6 did not. None of these studies however showed a decrease in benefit. This paper reviews the clinical fields where neural network methods figure most prominently, the main algorithms featured, methodologies for model selection and the need for rigorous evaluation of results. q

The dominant view in protein science is that a three-dimensional (3-D) structure is a prerequisite for protein function. In contrast to this dominant view, there are many counterexample proteins that fail to fold into a 3-D structure, or that have local regions that fail to fold, and yet carry out function. Protein without ®xed 3-D structure is called intrinsically disordered. Motivated by anecdotal accounts of higher rates of sequence evolution in disordered protein than in ordered protein we are exploring the molecular evolution of disordered proteins. To test whether disordered protein evolves more rapidly than ordered protein, pairwise genetic distances were compared between the ordered and the disordered regions of 26 protein families having at least one member with a structurally characterized region of disorder of 30 or more consecutive residues. For ®ve families, there were no signi®cant dierences in pairwise genetic distances between ordered and disordered sequences. The disordered region evolved signi®cantly more rapidly than the ordered region for 19 of the 26 families. The functions of these disordered regions are diverse, including binding sites for protein, DNA, or RNA and also including¯exible linkers. The functions of some of these regions are unknown. The disordered regions evolved signi®cantly more slowly than the ordered regions for the two remaining families. The functions of these more slowly evolving disordered regions include sites for DNA binding. More work is needed to understand the underlying causes of the variability in the evolutionary rates of intrinsically ordered and disordered protein.

Motivation: Despite the central role of diseases in biomedical research, there have been much fewer attempts to automatically determine which diseases are mentioned in a text-the task of disease name normalization (DNorm)-compared with other normalization tasks in biomedical text mining research. Methods: In this article we introduce the first machine learning approach for DNorm, using the NCBI disease corpus and the MEDIC vocabulary, which combines MeSH Õ and OMIM. Our method is a high-performing and mathematically principled framework for learning similarities between mentions and concept names directly from training data. The technique is based on pairwise learning to rank, which has not previously been applied to the normalization task but has proven successful in large optimization problems for information retrieval. Results: We compare our method with several techniques based on lexical normalization and matching, MetaMap and Lucene. Our algorithm achieves 0.782 micro-averaged F-measure and 0.809 macroaveraged F-measure, an increase over the highest performing baseline method of 0.121 and 0.098, respectively. Availability: The source code for DNorm is available at http://www. ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/DNorm, along with a webbased demonstration and links to the NCBI disease corpus. Results on PubMed abstracts are available in PubTator: http://www.ncbi.nlm. nih.gov/CBBresearch/Lu/Demo/PubTator

The goal of the gene normalization task is to link genes or gene products mentioned in the literature to biological databases. This is a key step in an accurate search of the biological literature. It is a challenging task, even for the human expert; genes are often described rather than referred to by gene symbol and, confusingly, one gene name may refer to different genes (often from different organisms). For BioCreative II, the task was to list the Entrez Gene identifiers for human genes or gene products mentioned in PubMed/MEDLINE abstracts. We selected abstracts associated with articles previously curated for human genes. We provided 281 expert-annotated abstracts containing 684 gene identifiers for training, and a blind test set of 262 documents containing 785 identifiers, with a gold standard created by expert annotators. Inter-annotator agreement was measured at over 90%. The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2008/9/S2/S3 Genome Biology 2008, 9(Suppl 2):S3 http://genomebiology.com/2008/9/S2/S3 Genome Biology 2008, Volume 9, Suppl 2, Article S3 Morgan et al. S3.2

Information encoded in natural language in biomedical literature publications is only useful if efficient and reliable ways of accessing and analyzing that information are available. Natural language processing and text mining tools are therefore essential for extracting valuable information, however, the development of powerful, highly effective tools to automatically detect central biomedical concepts such as diseases is conditional on the availability of annotated corpora. This paper presents the disease name and concept annotations of the NCBI disease corpus, a collection of 793 PubMed abstracts fully annotated at the mention and concept level to serve as a research resource for the biomedical natural language processing community. Each PubMed abstract was manually annotated by two annotators with disease mentions and their corresponding concepts in Medical Subject Headings (MeSH Ò ) or Online Mendelian Inheritance in Man (OMIM Ò ). Manual curation was performed using PubTator, which allowed the use of pre-annotations as a pre-step to manual annotations. Fourteen annotators were randomly paired and differing annotations were discussed for reaching a consensus in two annotation phases. In this setting, a high inter-annotator agreement was observed. Finally, all results were checked against annotations of the rest of the corpus to assure corpus-wide consistency.

Literature Overload Exponential growth of the peer-reviewed literature and the breakdown of disciplinary boundaries heralded by genome-scale instruments have made it harder than ever for scientists to find and assimilate all the publications relevant to their research. The widespread adoption of title/abstract word search, primarily through the National Library of Medicine's PubMed system (http:// www.ncbi.nlm.nih.gov/pubmed), was the first major change in the way bioscientists found relevant publications since the origin of Index Medicus in 1879. (Although it remains useful for locating pre-1966 literature (Hersh, 2003), Index Medicus ceased publication in 2004.) However, PubMed is only the beginning of a revolution in how scientists use the biomedical literature. Computational tools that classify documents, extract factual information, generate summaries, and generally process human language are providing powerful new tools for staying on top of the torrent of publications. The biomedical literature is growing at a doubleexponential pace; over the last 20 years, the total size of MEDLINE (the database searched by PubMed) has grown at a w4.2% compounded annual growth rate, and the number of new entries in MEDLINE each year has grown at a compounded annual growth rate of w3.1% (see Figure 1). There are now more than 16,000,000 publications in MEDLINE; more than three million of those were published in the last 5 years alone. The number of MEDLINE entries with a 2005 publication date was 666,029-more than 1800 per day. Large as MEDLINE is, it captures only bibliographic information and abstracts. Electronic access to the full texts, including graphics and figures, is also on the rise, and sophisticated linkages between publications and data repositories or other supplementary materials increase the amount of information available still further. Although online full-text materials are increasingly prevalent, dramatic increases in subscription prices and decreases in library budgets have paradoxically decreased access for some researchers. Toll-free linking, where copyright owners allow free search but charge per view, is one approach to ameliorating this problem. An alternative strategy toward this goal is the recent establishment of a movement toward a new ''Open Access'' model of scientific publishing. On April 11, 2003, a group of individuals interested in promoting open access to the scientific literature drafted a statement of principles that is now referred to as the Bethesda Statement on Open Access Publishing (

Data from the GAIN genome-wide association study (GWAS) in major depressive disorder (MDD) were used to explore previously reported candidate gene and SNP associations in MDD. A systematic literature search of candidate genes associated with MDD in case-control studies was performed before the results of the GAIN MDD study became available.

Background: The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data mining, including gene name recognition, species-specific document retrieval, and semantic enrichment of biomedical articles. Results: In this paper we describe an open-source species name recognition and normalization software system, LINNAEUS, and evaluate its performance relative to several automatically generated biomedical corpora, as well as a novel corpus of full-text documents manually annotated for species mentions. LINNAEUS uses a dictionary-based approach (implemented as an efficient deterministic finite-state automaton) to identify species names and a set of heuristics to resolve ambiguous mentions. When compared against our manually annotated corpus, LINNAEUS performs with 94% recall and 97% precision at the mention level, and 98% recall and 90% precision at the document level. Our system successfully solves the problem of disambiguating uncertain species mentions, with 97% of all mentions in PubMed Central full-text documents resolved to unambiguous NCBI taxonomy identifiers. Conclusions: LINNAEUS is an open source, stand-alone software system capable of recognizing and normalizing species name mentions with speed and accuracy, and can therefore be integrated into a range of bioinformatics and text-mining applications. The software and manually annotated corpus can be downloaded freely at http://linnaeus.sourceforge.net/.

Systems biology recognizes in particular the importance of interactions between biological components and the consequences of these interactions. Such interactions and their downstream effects are known as events. To computationally mine the literature for such events, text mining methods that can detect, extract and annotate them are required. This review summarizes the methods that are currently available, with a specific focus on protein-protein interactions and pathway or network reconstruction. The approaches described will be of considerable value in associating particular pathways and their components with higher-order physiological properties, including disease states.

Effective access to the vast biomedical knowledge present in the scientific literature is challenging. Semantic relations are increasingly used in knowledge management applications supporting biomedical research to help address this challenge. We describe SemMedDB, a repository of semantic predications (subject-predicate-object triples) extracted from the entire set of PubMed citations. We propose the repository as a knowledge resource that can assist in hypothesis generation and literature-based discovery in biomedicine as well as in clinical decision-making support. Availability and implementation: The SemMedDB repository is available as a MySQL database for non-commercial use at http://skr3. nlm.nih.gov/SemMedDB. An UMLS Metathesaurus license is required. Contact:

Genome-wide techniques such as microarray analysis, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), linkage analysis and association studies are used extensively in the search for genes that cause diseases, and often identify many hundreds of candidate disease genes. Selection of the most probable of these candidate disease genes for further empirical analysis is a significant challenge. Additionally, identifying the genes that cause complex diseases is problematic due to low penetrance of multiple contributing genes. Here, we describe a novel bioinformatic approach that selects candidate disease genes according to their expression profiles. We use the eVOC anatomical ontology to integrate text-mining of biomedical literature and data-mining of available human gene expression data. To demonstrate that our method is successful and widely applicable, we apply it to a database of 417 candidate genes containing 17 known disease genes. We successfully select the known disease gene for 15 out of 17 diseases and reduce the candidate gene set to 63.3% (±18.8%) of its original size. This approach facilitates direct association between genomic data describing gene expression and information from biomedical texts describing disease phenotype, and successfully prioritizes candidate genes according to their expression in disease-affected tissues.

Objectives-We evaluated the epidemiologic evidence that vitamin D may be related to human autoimmune disease risk. Methods-PubMed limited to English from inception through April 2010 was searched using keywords: "vitamin D", "autoimmune" and autoimmune disease names. We summarized in vitro, animal, and genetic association studies of vitamin D in autoimmune disease pathogenesis. We sorted studies by design and disease and performed a systematic review of: a) cross-sectional data concerning vitamin D level and autoimmune disease; b) interventional data on vitamin D supplementation in autoimmune diseases and c) prospective data linking vitamin D level or intake to autoimmune disease risk. Results-Vitamin D has effects on innate and acquired immune systems and vitamin D receptor polymorphisms have been associated with various autoimmune diseases. In experimental animal models, vitamin D supplementation can prevent or forestall autoimmune disease. We identified 76 studies in which vitamin D levels were studied in autoimmune disease patients, particularly with active disease, and compared to controls. Nineteen observational or interventional studies assessed the effect of vitamin D supplementation as therapy for various autoimmune diseases (excluding psoriasis and vitiligo) with a range of study approaches and results. The few prospective human studies performed conflict as to whether vitamin D level or intake is associated with autoimmune disease risk. No interventional trials have investigated whether vitamin D affects human autoimmune disease risk. Conclusions-Cross-sectional data point to a potential role of vitamin D in autoimmune disease prevention, but prospective interventional evidence in humans is still lacking.

Collecting and analysing all available literature before starting an animal experiment is important and it is indispensable when writing a systematic review (SR) of animal research. Writing such review prevents unnecessary duplication of animal studies and thus unnecessary animal use (Reduction). One of the factors currently impeding the production of 'high-quality' SRs in laboratory animal science is the fact that searching for all available literature concerning animal experimentation is rather difficult. In order to diminish these difficulties, we developed a search filter for PubMed to detect all publications concerning animal studies. This filter was compared with the method most frequently used, the PubMed Limit: Animals, and validated further by performing two PubMed topic searches. Our filter performs much better than the PubMed limit: it retrieves, on average, 7% more records. Other important advantages of our filter are that it also finds the most recent records and that it is easy to use. All in all, by using our search filter in PubMed, all available literature concerning animal studies on a specific topic can easily be found and assessed, which will help in increasing the scientific quality and thereby the ethical validity of animal experiments.

We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance-but rather our focus is "relatedness", the probability that a user would want to examine a particular document given known interest in another. We also describe a novel technique for estimating parameters that does not require human relevance judgments; instead, the process is based on the existence of MeSH ® in MEDLINE ® .

The Database of Protein Disorder (DisProt) is a curated database that provides structure and function information about proteins that lack a fixed three-dimensional (3D) structure under putatively native conditions, either in their entirety or in part. Starting from the central premise that intrinsic disorder is an important structural class of protein and in order to meet the increasing interest thereof, DisProt is aimed at becoming a central repository of disorderrelated information. For each disordered protein, the database includes the name of the protein, various aliases, accession codes, amino acid sequence, location of the disordered region(s), and methods used for structural (disorder) characterization. If applicable, most entries also list the biological function(s) of each disordered region, how each region of disorder is used for function, as well as provide links to PubMed abstracts and major protein databases.

The 54 articles represented various descriptive, methodological, and inferential analyses. Although some decision rules for treating data (eg, criteria for minimal wear-time) were consistently applied, cut point definitions used for accelerometer-derived variables (eg, time spent in various intensities of physical activity) were especially diverse.

Tumor suppressor genes (TSGs) are a major type of gatekeeper genes in the cell growth. A knowledgebase with the systematic collection and curation of TSGs in multiple cancer types is critically important for further studying their biological functions as well as for developing therapeutic strategies. Since its development in 2012, the Tumor Suppressor Gene database (TSGene), has become a popular resource in the cancer research community. Here, we reported the TSGene version 2.0, which has substantial updates of contents (e.g. up-to-date literature and pan-cancer genomic data collection and curation), data types (noncoding RNAs and protein-coding genes) and content accessibility. Specifically, the current TSGene 2.0 contains 1217 human TSGs (1018 protein-coding and 199 non-coding genes) curated from over 9000 articles. Additionally, TSGene 2.0 provides thousands of expression and mutation patterns derived from pan-cancer data of The Cancer Genome Atlas. A new web interface is availab...

The purpose is to provide an update the Bone Metastases Guideline published in 2011 based on evidence complemented by expert opinion. The update will discuss new high-quality literature for the 8 key questions from the original guideline and implications for practice. Methods and materials: A systematic PubMed search from the last date included in the original Guideline yielded 414 relevant articles. Ultimately, 20 randomized controlled trials, 32 prospective nonrandomized studies, and 4 meta-analyses/pooled analyses were selected and abstracted into evidence tables. The authors synthesized the evidence and reached consensus on the included recommendations. Results: Available literature continues to support pain relief equivalency between single and multiple fraction regimens for bone metastases. High-quality data confirm single fraction radiation therapy may be delivered to spine lesions with acceptable late toxicity. One prospective, randomized trial confirms both peripheral and spine-based painful metastases can be successfully and safely palliated with retreatment for recurrence pain with adherence to published dosing constraints. Advanced radiation therapy techniques such as stereotactic body radiation therapy lack high-quality data, leading the panel to favor its use on a clinical trial or when results will be collected in a registry. The panel's conclusion remains that surgery, radionuclides, bisphosphonates, and kyphoplasty/vertebroplasty do not obviate the need for Supplementary material for this article (http://dx.doi.org/10.1016/j.prro.2016.08.001) can be found at www.practicalradonc.org. Conflicts of interest. Before initiating work on this guideline, all panelists completed disclosure statements and pertinent disclosures are published within this report. Where potential conflicts are detected, remedial measures to address them are taken and noted here. TB received research funding from Templeton Foundation and leads ongoing bone metastases study. S.Lo. participated in international oligometastases consortium partially funded by Elekta and received honoraria and travel expenses from Accuray and Varian. These disclosures were shared with the panel. The panel and guideline subcommittee chair reviewed these relationships and determined that the disclosure here is sufficient to manage potential conflicts.

Atrophy of the medial temporal lobe, especially the hippocampus and the parahippocampal gyrus, is considered to be the most predictive structural brain biomarker for Alzheimer's Dementia (AD). However, recent neuroimaging studies reported a possible mismatch between structural and metabolic findings, showing medial temporal lobe atrophy and medial parietal hypoperfusion as biomarkers for AD. The role of the parietal lobe in the development of AD is only recently beginning to attract attention. The current review discusses parietal lobe involvement in the early stages of AD, viz. mild cognitive impairment, as reported from structural, functional, perfusion and metabolic neuroimaging studies. The medial and posterior parts of the parietal lobe seem to be preferentially affected, compared to the other parietal lobe parts. On the basis of the reviewed literature we propose a model showing the relationship between the various pathological events, as measured by different neuroimaging techniques, in the development of AD. In this model myelin breakdown is a beginning of the chain of pathological events leading to AD pathology and an AD diagnosis.

Researchers practice science in highly specialized intellectual environments and communities. It takes years of training to contribute new discoveries to the continually growing body of scientific knowledge. The staggering amount of available online knowledge and information, concerning both the personal field of expertise and developments in other disciplines, may overwhelm the individual researcher. Moreover, the latter, relevant, information may be overlooked. Swanson has phrased this particular situation as one of "complementary but disjoint structures within the literature of science." 1 Assume that one set of literature discusses the argument that A relates to B, while a separate literature provides a discussion on how B relates to C. These sets may have no articles in common and are therefore disjoint, yet the arguments are complementary because, when they are combined, there is the inference that A relates to C. Using titles from the bibliographic database MEDLINE, Swanson has made several discoveries in biomedicine by connecting disconnected sets of literature according to this simple ABC model. 2-4 Importantly, the first two literature-based hypotheses of the therapeutic effects of fish oil for patients with Raynaud's disease and the role of magnesium deficiency in migraine were corroborated clinically. 5 For drug discovery, this model is similar to Vos' model, 6 in which discovery is the rapprochement of a drug profile (AB) to a disease profile (BC).

Background. New quantitative magnetic resonance imaging (MRI) techniques are increasingly applied as outcome measures after cartilage repair. Objective. To review the current literature on the use of quantitative MRI biomarkers for evaluation of cartilage repair at the knee and ankle. Methods. Using PubMed literature research, studies on biochemical, quantitative MR imaging of cartilage repair were identified and reviewed. Results. Quantitative MR biomarkers detect early degeneration of articular cartilage, mainly represented by an increasing water content, collagen disruption, and proteoglycan loss. Recently, feasibility of biochemical MR imaging of cartilage repair tissue and surrounding cartilage was demonstrated. Ultrastructural properties of the tissue after different repair procedures resulted in differences in imaging characteristics. T2 mapping, T1rho mapping, delayed gadoliniumenhanced MRI of cartilage (dGEMRIC), and diffusion weighted imaging (DWI) are applicable on most clinical 1.5 T and 3 T MR scanners. Currently, a standard of reference is difficult to define and knowledge is limited concerning correlation of clinical and MR findings. The lack of histological correlations complicates the identification of the exact tissue composition. Conclusions. A multimodal approach combining several quantitative MRI techniques in addition to morphological and clinical evaluation might be promising. Further investigations are required to demonstrate the potential for outcome evaluation after cartilage repair.

Cancer statistics report an increased incidence of OSCC and OPSCC around the world. Though improvements in screening and early diagnosis have dramatically reduced the incidence of this neoplasm in recent years, the 5-yeardisease-free survival, is still poor, specially for oropharyngeal cancer, despite the great scientific and financial efforts. Recently, several papers showed that HPV may be involved at least in the pathogenesis of a subgroup of oral and cervical SCC, leading to distinct molecular characteristics compared with HPV-negative ones. Nevertheless, OPSCCs associated with HPV infection seem to show a better prognosis and affect younger patients (< 40 yrs.), especially females. Therefore, there is the need to properly assess oropharyngeal SCC subgroups: 1) not HPV associated/ classic oral SCC: less responsive to anticancer drugs: needs novel post-surgical treatment; 2) HPV associated/oral SCC: needs several management options and suitable "target" therapy against the virus, and/or immune-stimulating therapy. Further issues are: 1) the disclosure of putative targets for more efficient molecular therapy, which may work as cervical cancer post-surgical treatment, in anticipation of the effects of "global prevention" performed by WHO anti-HPV vaccination programs; 2) careful identification of precancerous lesions in both sites; dysplasia is currently treated by excisional or ablative procedures, which don't consider the concept of field carcinogenesis. In fact, it is probable that near or far from an excised precancerous lesion new foci of cell transformation may exist, which are not yet macroscopically evident, but, if detected, would put the patient into a high risk subgroup. Comparing findings reported in the recent literature, the data of this state of the art about HPV might add useful informations concerning oropharyngeal carcinogenesis. Moreover, our review would be useful in order to define novel perspectives of treatment choice for Head & Neck cancer patients, by combining well known chemotherapeutical drugs with new molecular "target" therapy.

Epigenetics, and more specifically DNA methylation is a fast evolving research area. In almost every cancer type, each month new publications confirm the differentiated regulation of specific genes due to methylation and mention the discovery of novel methylation markers. Therefore, it would be extremely useful to have an annotated, reviewed, sorted and summarized overview of all available data. PubMeth is a cancer methylation database that includes genes that are reported to be methylated in various cancer types. A query can be based either on genes (to check in which cancer types the genes are reported as being methylated) or on cancer types (which genes are reported to be methylated in the cancer (sub) types of interest). The database is freely accessible at http:// www.pubmeth.org. PubMeth is based on text-mining of Medline/ PubMed abstracts, combined with manual reading and annotation of preselected abstracts. The textmining approach results in increased speed and selectivity (as for instance many different aliases of a gene are searched at once), while the manual screening significantly raises the specificity and quality of the database. The summarized overview of the results is very useful in case more genes or cancer types are searched at the same time.

Motivation: With more and more scientific literature published online, the effective management and reuse of this knowledge have become problematic. Natural Language Processing (NLP) may be a potential solution by extracting, structuring, and organizing biomedical information that occurs in online literature in a timely manner. One essential task is to recognize and identify genomic entities in text. "Recognition" can be accomplished using pattern matching and machine learning. But for "identification" these techniques are not adequate. In order to identify genomic entities, NLP needs a comprehensive resource that specifies and classifies genomic entities as they occur in text and that associates them with normalized terms and also unique identifiers so that the extracted entities are well defined. Online organism databases are an excellent resource to create such a lexical resource. However, gene name ambiguity is a serious problem because it affects the appropriate identification of gene entities. In this paper we explore the extent of the problem and suggest ways to address it. Results: We obtained gene information from 21 organisms and quantified naming ambiguities within species, across species, with English words and with medical terms. When the case (of letters) was retained, official symbols displayed negligible intra-species ambiguity (0.02%) and modest ambiguities with general English words (0.57%) and medical terms (1.01%). In contrast, the across-species ambiguity was high (14.20%). The inclusion of gene synonyms increased intra-species ambiguity substantially and full names contributed greatly to gene-medical term ambiguity. A comprehensive lexical resource that covers gene information for the 21 organisms was then created and used to identify gene names by using a straightforward string matching program to process 45,000 abstracts associated with the mouse model organism while ignoring case and gene names that were also English words. We found that 85.1% of correctly retrieved mouse genes were ambiguous with other gene names. When gene names that were also English words were included, 233% additional "gene" instances were retrieved, most of which were false positives. We also found that authors prefer to use synonyms (74.7%) to official symbols (17.7%) or full names (7.6%) in their publications.

Background: Glucocorticoids are widely prescribed for a variety of diseases and are known to cause neuropsychiatric as well as somatic side effects. Objective: This article will review the incidence, clinical characteristics, course, and treatment of neuropsychiatric effects of glucocorticoids. Methods: We performed a literature review of the neuropsychiatric complications of glucocorticoids using the PubMed database. Results: The neuropsychiatric effects of glucocorticoids involve affective, behavioral, and cognitive manifestations. Serious neuropsychiatric effects occur in about 6% of patients who receive steroids. Although the effects of glucocorticoids are unpredictable, the administered dose is the most significant risk factor for the development of neuropsychiatric symptoms. Dosage reduction typically results in clinical recovery. Although evidence from controlled trials is sparse, administration of antipsychotics or mood stabilizers may be beneficial in the prevention and treatment of neuropsychiatric effects of steroids. Conclusion: The neuropsychiatric effects of glucocorticoids are more diverse than the often-misleading term "steroid psychosis" suggests. This label should be limited to those patients who are truly psychotic, and specific designations applied to patients with other effects. The adverse neuropsychiatric effects of glucocorticoids remain poorly characterized in the literature (which consists largely of case reports and case series). Reliable risk factors (other than dose) that identify individuals at risk are lacking; guidelines for the prevention of neuropsychiatric effects are not evidence-based. Further controlled clinical studies are needed to elucidate the optimal management of glucocorticoid-induced neuropsychiatric symptoms.

Awareness of illness is a form of self-knowledge concerning information about the pathological state, its functional consequence, and the way it affects the patient and his interaction with the environment. Unawareness of illness has raised much interest for its consequences on compliance with treatment, prognosis, and the patient&#39;s quality of life. This review highlights the great complexity of this phenomenon both at phenomenological and etiopathogenic levels in stroke, traumatic brain injury, psychosis, dementias, and mood disorders. In particular, the clinical expression is characterized by failure to acknowledge being ill, misattribution of symptoms, and noncompliance with treatment. Unawareness of illness may also be linked with characteristics that are peculiar to each individual disturbance, such as symptom duration and cognitive impairment. Despite a long-lasting interest in the clinical characteristics of unawareness, only recently has the focus of research investigate...

We present an initial analysis of the National Library of Medicine’s (NLM) Gene Indexing initiative. Gene Indexing occurs at the time of indexing for all 4600 journals and over 500,000 articles added to PubMed/MEDLINE each year. Gene Indexing links articles about the basic biology of a gene or protein within eight model organisms to a specific record in the NLM’s LocusLink database of gene products. The result is an entry called a Gene Reference Into Function (GeneRIF) within the LocusLink database. We analyzed the numbers of GeneRIFs produced in the first year of GeneRIF production. 27,645 GeneRIFs were produced, pertaining to 9126 loci over eight model organisms. 60% of these were associated with human genes and 27% with mouse genes. About 80% discuss genes with an established MeSH Heading or other MeSH term. We developed a prototype functional alerting system for researchers based on the GeneRIFs, and a strategy to find all of the literature related to genes. We conclude that the Gene Indexing initiative adds considerable value to the life sciences research community.

The effect of bisphenol A (BPA) exposure on human brain and behavior is a relatively new issue, and particular concerns have been raised about its potential impact on children. The primary objective of this review was to analyze the current state of knowledge on the association of environmental BPA exposure during pregnancy and/or childhood with child cognitive and/or behavior outcomes. All scientific publications until March 2015 that include examination of this relationship have been reviewed using the MEDLINE/PubMed database. Although research on this issue has not been abundant, an association with altered neurobehavior was reported by eight out of the twelve available articles, including aggressive behavior, attention deficit, hyperactivity disorder, depression and anxiety impairments, mostly in children exposed in utero, indicating disruption of the brain during this critical window of development. Despite the reduced number of studies and their heterogeneity, the results suggest that prenatal BPA exposure may have a negative impact on neurobehavioral functioning in children and that the effects may be sex-dependent. It is therefore necessary to be vigilant towards the potential adverse effects of ubiquitous low-level BPA exposure, although more studies in humans are required to convincingly confirm or rule out the association between BPA exposure and health. Meanwhile, it is desirable to inform women planning or undergoing pregnancy about measures to reduce or avoid exposure to BPA. We discuss some key aspects of the relationship between exposure and neurobehavioral outcomes.