Differences in citation frequency of clinical and basic science papers in cardiovascular research

In this article, a critical analysis is performed on differences in citation frequency of basic and clinical cardiovascular papers. It appears that the latter papers are cited at about 40% higher frequency. The differences between the largest number of citations of the most cited papers are even larger. It is also demonstrated that the groups of clinical and basic cardiovascular papers are also heterogeneous concerning citation frequency. It is concluded that none of the existing citation indicators appreciates these differences. At this moment these indicators should not be used for quality assessment of individual scientists and scientific niches with small numbers of scientists.     

The use of bibliometrics to measure research quality in UK higher education institutions

Research assessment in the UK has evolved over a quarter of a century from a loosely structured, peer-review based process to one with a well understood data portfolio and assessment methodology. After 2008, the assessment process will shift again, to the use of indicators based largely on publication and citation data. These indicators will in part follow the format introduced in 2008, with a profiling of assessment outcomes at national and international levels. However, the shift from peer assessment to a quantitative methodology raises critical issues about which metrics are appropriate and informative and how such metrics should be managed to produce weighting factors for funding formulae. The link between publication metrics and other perceptions of research quality needs to be thoroughly tested and reviewed, and may be variable between disciplines. Many of the indicators that drop out of publication data are poorly linked to quality and should not be used at all. There are also issues about which publications are the correct base for assessment, which staff should be included in a review, how subjects should be structured and how the citation data should be normalised to account for discipline-dependent variables. Finally, it is vital to consider the effect that any assessment process will have on the behaviour of those to be assessed.     

New developments in the use of citation analysis in research evaluation

This paper presents an overview of research assessment methodologies developed in the field of evaluative bibliometrics, a subfield of quantitative science and technology studies, aimed to construct indicators of research performance from a quantitative statistical analysis of scientific-scholarly documents. Citation analysis is one of its key methodologies. The paper illustrates the potentialities and limitations of the use of bibliometric indicators in research assessment. It discusses the relationship between metrics and peer review; databases used as sources of bibliometric analysis; the pros and cons of indicators often applied, including journal impact factors, Hirsch indices, and normalized indicators of citation impact; and approaches to the bibliometric measurement of institutional research performance.     

The use of bibliometric indicators to help peer-review assessment

Inserm is the only French public research institution entirely dedicated to human health. Inserm supports research across the biomedical spectrum in all major disease areas, from fundamental lab-based science to clinical trials. To translate its scientists’ findings into tangible health benefits, Inserm has its own affiliated company, Inserm Transfert, which works with industry. Since 2001, Inserm has been setting up on-line file management software for the evaluation of researchers and laboratories, called EVA (). EVA includes all grant applications, assessment reports, evaluation grading evaluation forms and includes automated bibliometric indicator software that enables calculating, for example, the number of publications, journal impact factors, number of citations, citation index, and number of the Top 1 publications for each researcher of the teams. The indicators take into account research fields, the year of publications, and the author’s position among the participants. Bibliometrics is now considered a tool for science policy providing indicators to measure productivity and scientific quality, thereby supplying a basis for evaluating and orienting R&D. It is also a potential tool for evaluation. It is neutral, allows comparative (national and international) assessment, and may select papers in the forefront in all fields. For each team, bibliometric indicators are calculated for all researchers with permanent or long-term positions (3–5 years). The use of bibliometric indicators requires great vigilance, but according to our experience they enrich the committee’s debates without any doubt. We present an analysis of the data of 600 research teams evaluated in 2007–2008.     

Biomedical knowledge navigation by literature clustering

There is an urgent need for a system that facilitates surveys by biomedical researchers and the subsequent formulation of hypotheses based on the knowledge stored in literature. One approach is to cluster papers discussing a topic of interest and reveal its sub-topics that allow researchers to acquire an overview of the topic. We developed such a system called McSyBi. It accepts a set of citation data retrieved with PubMed and hierarchically and non-hierarchically clusters them based on the titles and the abstracts using statistical and natural language processing methods. A novel point is that McSyBi allows its users to change the clustering by entering a MeSH term or UMLS Semantic Type, and therefore they can see a set of citation data from multiple aspects. We evaluated McSyBi quantitatively and qualitatively: clustering of 27 sets of citation data (40643 different papers) and scrutiny of several resultant clusters. While non-hierarchical clustering provides us with an overview of the target topic, hierarchical clustering allows us to see more details and relationships among citation data. McSyBi is freely available at http://textlens.hgc.jp/McSyBi/.     

On the fairness of using relative indicators for comparing citation performance in different disciplines

Relative indicators are commonly used to remove biases due to different citation practices in various scientific fields. Here we extend our recent investigation on the viability of the use of relative indicators for comparing article impact in different disciplines. We consider citation distributions for papers published in 14 of the 172 disciplines categorized by the Journal Citation Reports. The distribution of the number of citations received by publications in a certain discipline divided by the average number for the discipline is a universal function. Based on it, we compute the relative number of citations needed to be among the q percent most-cited publications in a discipline. The effect of finite samples is also discussed. The average number of citations is shown to be strongly correlated with the impact factor, but fluctuations are quite large. A similar universal distribution is found (with exceptions) when citation distributions restricted to papers published in a single journal are considered.     

The proper use of citation data in journal management

Journal impact factors (IF) are often maligned in editorials found in scientific publications, yet citation data can be used appropriately in journal management. The editors of Laboratory Investigation have found that weekly tracking of citation data for this and other highly ranked pathology journals provides valuable feedback on editorial performance and enables us to predict accurate IFs at least six months in advance. Once the IFs are released, it is useful to quantify the contributions of specific article categories, such as reviews and research articles, to the official IFs. In an ongoing attempt to understand the relationship between article downloads and eventual citations, we also analyze the citation rate of papers that had previously been the most frequently accessed on our web site. Finally, as a measure of editorial judgment, the papers that contributed no citations to the journal’s IF are examined as are the papers that were rejected by Laboratory Investigation (Lab. Invest.) but subsequently published elsewhere. Thus the editors of Lab. Invest. use citation data in several ways to measure our progress in elevating the quality of the journal and understand the citation dynamics of papers we publish, while remaining true to the journal’s fundamental operating premise: Publish high-quality original work relating to the mechanisms of disease.     

Expressive genomic hybridisation: gene expression profiling at the cytogenetic level.

AIMS: To describe a cytogenetic technique suitable for the rapid assessment of global gene expression that is based on comparative genomic hybridisation (CGH), and to use it to understand the relation between genetic amplifications and gene expression. METHODS: Whereas traditional CGH uses DNA as test and reference in hybridisations, expressive genomic hybridisation (EGH) uses globally amplified mRNA as test and normal DNA as reference. EGH is a rapid and powerful tool for localising and studying global gene expression profiles and correlating them with loci of genetic amplifications using traditional CGH. RESULTS: EGH was used to correlate genetic amplifications detected by CGH with the expression profile of two independent cell lines-Colo320 and T47D. Although many amplifications resulted in overexpression, other amplifications were partially or completely silenced at the cytogenetic level. CONCLUSION: This technique will assist in the analysis of overexpressed genes within amplicons and could resolve a controversial issue in cancer cytogenetics; namely, the relation between genetic amplifications and overexpression.     

Gastric cancers in young and elderly patients show different genomic profiles

Although most gastric cancers occur in elderly patients, a substantial number of cases of this common disease occur in young patients. Gastric cancer is a heterogeneous disease at the genomic level and different patterns of DNA copy number alterations are associated with different clinical behaviour. The aim of the present study was to explore differences in DNA copy number alterations in relation to age of onset of gastric cancer. DNA isolated from 46 paraffin-embedded gastric cancer tissue samples from 17 patients less than 50 years of age [median 43 (21-49) years] and 29 patients greater than or equal to 70 years of age [median 75 (70-83) years] was analysed by genome-wide microarray comparative genomic hybridization (array CGH) using an array of 5000 BAC clones. Patterns of DNA copy number aberrations were analysed by hierarchical cluster analysis of the mode-normalized and smoothed log(2) ratios of tumour to normal reference fluorescence signal intensities using TMEV software, after which cluster membership was correlated with age group. In addition, supervised analysis was performed using CGH Multi-array. Hierarchical cluster analysis of the array CGH data revealed three clusters with different genomic profiles that correlated significantly with age (p = 0.006). Cluster 1 mainly contained young patients, while elderly patients were divided over clusters 2 and 3. Chromosome regions 11q23.3 and 19p13.3 contributed most to age-related differences in tumour profiles. Gastric cancers of young and old patients belong to groups with different genomic profiles, which likely reflect different pathogenic mechanisms of the disease.     

Type of evidence behind point-of-care clinical information products: a bibliometric analysis

Background

Point-of-care (POC) products are widely used as information reference tools in the clinical setting. Although usability, scope of coverage, ability to answer clinical questions, and impact on health outcomes have been studied, no comparative analysis of the characteristics of the references, the evidence for the content, in POC products is available.

Objective

The objective of this study was to compare the type of evidence behind five POC clinical information products.

Methods

This study is a comparative bibliometric analysis of references cited in monographs in POC products. Five commonly used products served as subjects for the study: ACP PIER, Clinical Evidence, DynaMed, FirstCONSULT, and UpToDate. The four clinical topics examined to identify content in the products were asthma, hypertension, hyperlipidemia, and carbon monoxide poisoning. Four indicators were measured: distribution of citations, type of evidence, product currency, and citation overlap. The type of evidence was determined based primarily on the publication type found in the MEDLINE bibliographic record, as well as the Medical Subject Headings (MeSH), both assigned by the US National Library of Medicine. MeSH is the controlled vocabulary used for indexing articles in MEDLINE/PubMed.

Results

FirstCONSULT had the greatest proportion of references with higher levels of evidence publication types such as systematic review and randomized controlled trial (137/153, 89.5%), although it contained the lowest total number of references (153/2330, 6.6%). DynaMed had the largest total number of references (1131/2330, 48.5%) and the largest proportion of current (2007-2009) references (170/1131, 15%). The distribution of references cited for each topic varied between products. For example, asthma had the most references listed in DynaMed, Clinical Evidence, and FirstCONSULT, while hypertension had the most references in UpToDate and ACP PIER. An unexpected finding was that the rate of citation overlap was less than 1% for each topic across all five products.

Conclusions

Differences between POC products are revealed by examining the references cited in the monographs themselves. Citation analysis extended to include key content indicators can be used to compare the evidence levels of the literature supporting the content found in POC products.     

cDNA microarray analysis and immunohistochemistry reveal a distinct molecular phenotype in serous endometrial cancer compared to endometrioid endometrial cancer

Purpose

The main objective of this study was to refine more precisely the gene expression patterns used to distinguish serous from endometrioid endometrial carcinoma.

Methods

A low-density cDNA microarray containing 492 genes was designed and constructed. The gene expression profiles of 32 endometrioid and 5 serous endometrial cancer tissue samples were compared. The expression of 5 differentially expressed genes: NDC80, BUB1, FUT8, ANXA4 and BBC3 in endometrioid and serous adenocarcinoma samples was further evaluated by quantitative real-time PCR and immunohistochemistry.

Results

Unsupervised cluster analysis revealed that the 5 serous adenocarcinomas clustered together. These were separated from the endometrioid adenocarcinomas which were further sorted into 3 additional clusters. A comparative analysis indicated that there was a significant difference in FIGO stage with no significant difference in depth of myometrial invasion among the 4 clusters. The FIGO ternary grading system could not distinctly separate the 3 clusters of endometrioid adenocarcinomas, but a binary grading system was able to do so. Using a supervised analysis, we have identified 46 genes exhibiting > 2-fold differences that can be used to statistically differentiate serous adenocarcinomas from endometrioid adenocarcinomas. The directions of gene and protein expression change of five differentially expressed genes estimated by real-time PCR and immunohistochemistry are consistent with those estimated from microarray.

Conclusions

Serous adenocarcinoma exhibits distinct gene expression profiles, compared with those of endometrioid adenocarcinoma. These differences make it feasible to validate microarray data by immunohistochemistry, and they will ultimately allow us to identify tumors according to their immunohistochemical phenotype. The accuracy of classifying endometrial tumors using a system based on their gene expression patterns is much higher than the accuracy of the FIGO grading system. Thus, this gene expression pattern-based system may prove to be crucial in developing novel treatment strategies for endometrial cancers at the molecular level in future.     

Correlation between plasma amino acid profiles and the various stages of hepatitis B infection

The amino acid metabolism in patients with hepatitis B virus (HBV) infection is significantly changed. In this study, we analyzed the relationship between the amino acid profiles and varying clinical stages of HBV infection, and investigated their significance. The plasma amino acid concentrations in 115 patients with HBV infection and 32 healthy donors were detected and analyzed, and the main indicators of liver function were measured. Correlation analysis was performed between the amino acid profiles (Fischer's ratio, branched-chain amino acid to tyrosine ratio [BTR]) and the key indicators of liver function in patients with HBV infection. Fisher's ratio and the BTR of patients with HBV infection was found to differ from that of the healthy controls, and was also found to significantly correlate with the stage of HBV infection. Changes in the BTR were closely related to the level of key indicators of liver function, and a significant relationship was detected between the Fischer's ratio and the BTR (r=0.928, p<0.001). These results suggest that Fischer's ratio and the BTR can indirectly reflect the degree of liver cell injury. Determining and tracking the plasma amino acid profiles could, therefore, be used for the diagnosis, treatment selection, and prognosis of patients with varying stages of HBV infection.     

Large-scale analysis of gene clustering in bacteria

An important strategy to study operons and their evolution is to investigate clustering of related genes across multiple bacterial genomes. Although existing algorithms are available that can identify gene clusters across two or more genomes, very few algorithms are efficient enough to study gene clusters across hundreds of genomes. We observe that a querying strategy can be used to analyze gene clusters across a large number of genomes and develop an efficient algorithm to identify all related clusters on a genome from a given query cluster. We use this algorithm to study gene clustering in 400 bacterial genomes by starting from a well-characterized list of operons in Escherichia coli K12 and perform comparative analysis of operon occurrences, gene orientations, and rearrangements both within and across clusters. We show that important biological insights can be obtained by comparing results across these categories. A software program implementing the algorithm (GCQuery) and supplementary data containing detailed results are available at http://faculty.cs.tamu.edu/shsze/gcquery.     

Vitellocyte ultrastructure in the cestode Didymobothrium rudolphii (Monticelli, 1890): possible evidence for the recognition of divergent taxa within the Spathebothriidea

In the spathebothriidean tapeworm Didymobothrium rudolphii (Monticelli, 1890) the fine structure of the vitellocytes at different stages of their development within the vitelline follicles, vitelline ducts and uterus was studied for the first time using transmission electron microscopy. The vitellocyte inclusions of D. rudolphii are shell globule clusters containing tightly packed shell globules associated with a matrix of moderate electron density, glycogen granules, large electron-lucent lipid droplets (up to 3 μm in diameter), and, occasionally, a lipid droplet may occur in the nucleus of the vitellocytes. The diameter of the clusters ranges from 0.4 to 2.5 μm, the number of shell globules in the clusters varies from 8 to 45, and the size of the globules ranges from 0.12 to 0.25 μm and they are of approximately homogeneous sizes within a cluster. Most vitellocyte lipid droplets have a heterogeneous configuration with a ‘cavity’ inside them when they are within vitelline ducts and intrauterine eggs. Vitellocytes of the eggs contain dark concentric bodies and lipid droplets. The interstitial tissue has a syncytial structure. The morphological parameters of the diameter and shape of shell globule clusters, arrangement of shell globules in clusters, number and diameter of globules within clusters, types of lipid droplets and presence of dark concentric bodies are compared with those of two other spathebothriidean genera, Cyathocephalus and Diplocotyle. The comparative data demonstrate that vitelline material morphology has unique features in three spathenothriidean genera and may be used as evidence for the recognition of separate taxa.     

Neuropsychological information in the Wechsler Adult Intelligence Scale-Revised.

The relationships among Wechsler Adult Intelligence Scale-Revised profiles (WAIS-R), Luria-Nebraska Neuropsychological Battery (LNNB) profiles and Halstead Retian Neuropsychological Battery (HRNB) profiles were examined in two samples of patients referred for neuropsychological evaluation. Canonical correlation analysis suggested that the average level of WAIS-R profiles was related to the average level and scatter of LNNB profiles, Overall performance on the HRNB was less strongly related to overall performance on the WAIS-R than was the LNNB. Patients who were similar to a WAIS-R modal profile characterized by relative deficits on performance subtests were more likely to be similar to LNNB modal profiles characterized by relative impairments on sensorimotor subtests. Patients who were similar to a WAIS-R modal profile characterized by relative deficits on verbal subtests were more likely to be similar to LNNB modal profiles characterized by relative impairments on either language subtests or conceptual subtests. Patients classified into an HRNB profile type characterized by strengths on the Aphasia Screening subtest were more likely to show strengths on WAIS-R verbal subtests. However, less than 8 % of the total samples could be jointly classified into both the requisite WAIS-R profile clusters and one of the associated LNNB or HRNB profile clusters. WAIS-R subtest profile level may be a useful statistic to screen for neuropsychological deficits, but WAIS-R patterns are essentially useless for neuropsychological screening. Discussion focuses on the role of the WAIS-R in neuropsychological evaluations.     

Spatial distribution of acetylcholine receptors at developing chick neuromuscular junctions

The development of high-density clusters of acetylcholine receptors (AChRs) and the relationship of these clusters to nerve contacts on embryonic chick wing muscle fibres has been studied. Fluorescent labelling of AChRs with rhodamine-conjugated alpha-bungarotoxin (R-Bgt) revealed the presence of irregularly shaped AChR clusters in wing buds at 4 1/2-5 days of incubation. This is within a day of when myotubes first appear in the wing bud, and close to the time when functional innervation becomes established. At 10 days of incubation AChR clusters present on muscle cells in anterior and posterior latissimus dorsi appear as round or oval, uniformly labelled plaques. At about the time of hatching, however, these plaques break into numerous smaller clusters. Similar changes in the morphology of AChR clusters have been observed previously in mammalian skeletal muscle during development. Using horseradish peroxidase labelled alpha-bungarotoxin (HRP-Bgt), the relationship between AChR clusters and motor nerve terminals was studied at the ultrastructural level. At all stages of development nerve-muscle contacts were labelled with HRP-Bgt. In wing buds, however, the majority (90%) of labelled clusters observed were not in contact with a motor nerve terminal. The incidence of AChR clusters with axon contacts increased sharply during development such that by 10 days more than 50% and by hatching more than 90% of all sections through labelled AChR clusters contained nerve terminal profiles. At all times studied nerve-contacted receptor clusters were longer (about 5 micron) than non-contacted clusters (about 2 micron).     

Light diffraction patterns and sarcomere length variation in striated muscle fibers ofLimulus

Summary Light diffraction patterns produced byLimulus striated muscle fibers were examined. Segments of fibers were glycerinated, fixed or bathed in relaxing solution. Profiles of the intensity of a diffracted order vs. the angle of incidence of the laser beam often exhibited narrow peaks with the fiber at rest length. The incident angles at which the intensity of left and right orders is greatest are used to calculate the sarcomere length, supporting the notion that regions of the fiber are organised into Bragg reflecting planes. These profiles developed subpeaks and broadened upon stretch of the fiber. The broad angle scan profiles are suggested to result from a decrease in the regular packing of myofibrils as the fiber is lengthened. The angular width of the subpeaks is used to estimate the thickness of clusters of myofibrils. The variation in sarcomere length along the fiber, as determined by the 0th to 1st diffraction order spacing, was dependent upon the fiber preparation. Glycerinated fibers and those bathed in relaxing solution showed more variation than fixed fibers. The variation of sarcomere length is compared to the variation in thick filament lengths inLimulus reported by Dewey et al. (1982) lengths inLimulus reported by Dewey et al. (1982). These results are compared to those obtained from frog fiber segments.     

The use of clustering software for the classification of comparative genomic hybridization data. an analysis of 109 malignant fibrous histiocytomas

Malignant fibrous histiocytoma (MFH) is considered the most frequent soft-tissue sarcoma of late adult life. Nevertheless, the validity of this entity has been recurrently questioned by pathologists. Preliminary analyses by comparative genomic hybridization (CGH) of series of MFH have suggested that this tumor group is heterogeneous at the genomic level, and that at least two main genetic subgroups exist. We report an analysis by CGH of a large series of 109 MFH and on the use of clustering software for an objective classification of these tumors. We confirm our preliminary CGH results and demonstrate that two main clusters of tumors are present in the series analyzed.     

Randomized maps for assessing the reliability of patients clusters in DNA microarray data analyses

OBJECTIVE: Clustering algorithms may be applied to the analysis of DNA microarray data to identify novel subgroups that may lead to new taxonomies of diseases defined at bio-molecular level. A major problem related to the identification of biologically meaningful clusters is the assessment of their reliability, since clustering algorithms may find clusters even if no structure is present. METHODOLOGY: Recently, methods based on random "perturbations" of the data, such as bootstrapping, noise injections techniques and random subspace methods have been applied to the problem of cluster validity estimation. In this framework, we propose stability measures that exploits the high dimensionality of DNA microarray data and the redundancy of information stored in microarray chips. To this end we randomly project the original gene expression data into lower dimensional subspaces, approximately preserving the distance between the examples according to the Johnson-Lindenstrauss (JL) theory. The stability of the clusters discovered in the original high dimensional space is estimated by comparing them with the clusters discovered in randomly projected lower dimensional subspaces. The proposed cluster-stability measures may be applied to validate and to quantitatively assess the reliability of the clusters obtained by a large class of clustering algorithms. RESULTS AND CONCLUSION: We tested the effectiveness of our approach with high dimensional synthetic data, whose distribution is a priori known, showing that the stability measures based on randomized maps correctly predict the number of clusters and the reliability of each individual cluster. Then we showed how to apply the proposed measures to the analysis of DNA microarray data, whose underlying distribution is unknown. We evaluated the validity of clusters discovered by hierarchical clustering algorithms in diffuse large B-cell lymphoma (DLBCL) and malignant melanoma patients, showing that the proposed reliability measures can support bio-medical researchers in the identification of stable clusters of patients and in the discovery of new subtypes of diseases characterized at bio-molecular level.