1,721,090 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
High-risk breast cancer: From biology to personalized therapeutic strategies
No full textAdjuvant treatment regimens for breast cancer are primarily based on patient- and tumor-related factors, e.g. patient menopausal status, tumor stage and histological grade, and the status of molecular tumor markers (HER2/neu and the estrogen receptor). Despite improvements in survival rates, about 20% of patients experience recurrence within five years of initial therapy. There is therefore a need to improve patient risk assessment and to personalize therapy according to a combination of patient-specific clinicopathological features and tumor characteristics. This doctoral thesis is a multidisciplinary effort between molecular biologists, clinicians, and pathologists to identify potential therapeutic targets for high-risk breast carcinoma.
This work exploits common knowledge that the accumulation of deleterious genetic and epigenetic modulators contribute to breast cancer risk for recurrence and death by deregulating key cellular processes within a specific tumor. In the first work, we found that tumors from high-risk breast cancer patients were genetically instable, containing a 2-fold increase in genetic alterations, an overrepresentation of alterations on chromosomes 3, 18, and 20, and the recurrent deregulation of a 13-marker transcriptome signature associated with significantly shorter disease-specific survival rates (AZGP1, CBX2, DNALI1, LOC389033, NME5, PIP, S100A8, SCUBE2, SERPINA11, STC2, STK32B, SUSD3, and UBE2C). Second, subsequent validation of the 13-marker signature demonstrated the importance of not only performing external validation in independent breast cancer microarray datasets, but also to assess the biological and clinical relevance of individual markers at the protein level because of frequent poor mRNA-protein correlation. It was shown that breast cancer outcome prediction was improved significantly by combining a four-marker immunohistochemical panel (AZGP1, PIP, S100A8, UBE2C) together with established clinicopathological features. Third, we showed that several putative markers previously identified by us may not only be useful for breast cancer prognostication, but may also be clinically relevant in oral squamous cell carcinoma, a cancer form bearing biological similarities to breast carcinoma. Lastly, we found that the 8p11-p12 genomic region is a hotspot for DNA amplification in breast cancer, where the WHSC1L1 gene may be one of several genes located in region with oncogenic potential and a substantial contributor to the aggressive breast cancer phenotype.
Taken together, these findings further emphasize the importance of complementing established clinicopathological features with tumor-specific molecular markers to improve breast cancer risk assessment and develop more individualized treatment regimens
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
High-risk breast cancer: From biology to personalized therapeutic strategies
No full textAdjuvant treatment regimens for breast cancer are primarily based on patient- and tumor-related factors, e.g. patient menopausal status, tumor stage and histological grade, and the status of molecular tumor markers (HER2/neu and the estrogen receptor). Despite improvements in survival rates, about 20% of patients experience recurrence within five years of initial therapy. There is therefore a need to improve patient risk assessment and to personalize therapy according to a combination of patient-specific clinicopathological features and tumor characteristics. This doctoral thesis is a multidisciplinary effort between molecular biologists, clinicians, and pathologists to identify potential therapeutic targets for high-risk breast carcinoma. This work exploits common knowledge that the accumulation of deleterious genetic and epigenetic modulators contribute to breast cancer risk for recurrence and death by deregulating key cellular processes within a specific tumor. In the first work, we found that tumors from high-risk breast cancer patients were genetically instable, containing a 2-fold increase in genetic alterations, an overrepresentation of alterations on chromosomes 3, 18, and 20, and the recurrent deregulation of a 13-marker transcriptome signature associated with significantly shorter disease-specific survival rates (AZGP1, CBX2, DNALI1, LOC389033, NME5, PIP, S100A8, SCUBE2, SERPINA11, STC2, STK32B, SUSD3, and UBE2C). Second, subsequent validation of the 13-marker signature demonstrated the importance of not only performing external validation in independent breast cancer microarray datasets, but also to assess the biological and clinical relevance of individual markers at the protein level because of frequent poor mRNA-protein correlation. It was shown that breast cancer outcome prediction was improved significantly by combining a four-marker immunohistochemical panel (AZGP1, PIP, S100A8, UBE2C) together with established clinicopathological features. Third, we showed that several putative markers previously identified by us may not only be useful for breast cancer prognostication, but may also be clinically relevant in oral squamous cell carcinoma, a cancer form bearing biological similarities to breast carcinoma. Lastly, we found that the 8p11-p12 genomic region is a hotspot for DNA amplification in breast cancer, where the WHSC1L1 gene may be one of several genes located in region with oncogenic potential and a substantial contributor to the aggressive breast cancer phenotype. Taken together, these findings further emphasize the importance of complementing established clinicopathological features with tumor-specific molecular markers to improve breast cancer risk assessment and develop more individualized treatment regimens
Pan-cancer analyses of human nuclear receptors reveal transcriptome diversity and prognostic value across cancer types
No full textThe human nuclear receptor (NR) superfamily comprises 48 ligand-dependent transcription factors that play regulatory roles in physiology and pathophysiology. In cancer, NRs have long served as predictors of disease stratification, treatment response, and clinical outcome. The Cancer Genome Atlas (TCGA) Pan-Cancer project provides a wealth of genetic data for a large number of human cancer types. Here, we examined NR transcriptional activity in 8,526 patient samples from 33 TCGA 'Pan-Cancer' diseases and 11 'Pan-Cancer' organ systems using RNA sequencing data. The web-based Kaplan-Meier (KM) plotter tool was then used to evaluate the prognostic potential of NR gene expression in 21/33 cancer types. Although, most NRs were significantly underexpressed in cancer, NR expression (moderate to high expression levels) was predominantly restricted (46%) to specific tissues, particularly cancers representing gynecologic, urologic, and gastrointestinal 'Pan-Cancer' organ systems. Intriguingly, a relationship emerged between recurrent positive pairwise correlation of Class IV NRs in most cancers. NR expression was also revealed to play a profound effect on patient overall survival rates, with >= 5 prognostic NRs identified per cancer type. Taken together, these findings highlighted the complexity of NR transcriptional networks in cancer and identified novel therapeutic targets for specific cancer types
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