Survey of the year 2006 commercial optical biosensor literature

We identified 1219 articles published in 2006 that described work performed using commercial optical biosensor platforms. It is interesting to witness how the biosensor market is maturing with an increased number of instrument manufacturers offering a wider variety of platforms. However, it is clear from a review of the results presented that the advances in technology are outpacing the skill level of the average biosensor user. While we can track a gradual improvement in the quality of the published work, we clearly have a long way to go before we capitalize on the full potential of biosensor technology. To illustrate what is right with the biosensor literature, we highlight the work of 10 groups who have their eye on the ball. To help out the rest of us who have the lights on but nobody home, we use the literature to address common myths about biosensor technology.     

Survey of the year 2004 commercial optical biosensor literature

The year 2004 represents a milestone for the biosensor research community: in this year, over 1000 articles were published describing experiments performed using commercially available systems. The 1038 papers we found represent an approximately 10% increase over the past year and demonstrate that the implementation of biosensors continues to expand at a healthy pace. We evaluated the data presented in each paper and compiled a 'top 10' list. These 10 articles, which we recommend every biosensor user reads, describe well-performed kinetic, equilibrium and qualitative/screening studies, provide comparisons between binding parameters obtained from different biosensor users, as well as from biosensor- and solution-based interaction analyses, and summarize the cutting-edge applications of the technology. We also re-iterate some of the experimental pitfalls that lead to sub-optimal data and over-interpreted results. We are hopeful that the biosensor community, by applying the hints we outline, will obtain data on a par with that presented in the 10 spotlighted articles. This will ensure that the scientific community at large can be confident in the data we report from optical biosensors.     

Grading the commercial optical biosensor literature—Class of 2008: ‘The Mighty Binders’

Optical biosensor technology continues to be the method of choice for label‐free, real‐time interaction analysis. But when it comes to improving the quality of the biosensor literature, education should be fundamental. Of the 1413 articles published in 2008, less than 30% would pass the requirements for high‐school chemistry. To teach by example, we spotlight 10 papers that illustrate how to implement the technology properly. Then we grade every paper published in 2008 on a scale from A to F and outline what features make a biosensor article fabulous, middling or abysmal. To help improve the quality of published data, we focus on a few experimental, analysis and presentation mistakes that are alarmingly common. With the literature as a guide, we want to ensure that no user is left behind. Copyright © 2009 John Wiley & Sons, Ltd.     

Survey of the 1999 surface plasmon resonance biosensor literature

The application of surface plasmon resonance biosensors in life sciences and pharmaceutical research continues to increase. This review provides a comprehensive list of the commercial 1999 SPR biosensor literature and highlights emerging applications that are of general interest to users of the technology. Given the variability in the quality of published biosensor data, we present some general guidelines to help increase confidence in the results reported from biosensor analyses.     

Survey of the year 2000 commercial optical biosensor literature.

We have compiled a comprehensive list of the articles published in the year 2000 that describe work employing commercial optical biosensors. Selected reviews of interest for the general biosensor user are highlighted. Emerging applications in areas of drug discovery, clinical support, food and environment monitoring, and cell membrane biology are emphasized. In addition, the experimental design and data processing steps necessary to achieve high-quality biosensor data are described and examples of well-performed kinetic analysis are provided.     

A survey of the year 2002 commercial optical biosensor literature

We have compiled 819 articles published in the year 2002 that involved commercial optical biosensor technology. The literature demonstrates that the technology's application continues to increase as biosensors are contributing to diverse scientific fields and are used to examine interactions ranging in size from small molecules to whole cells. Also, the variety of available commercial biosensor platforms is increasing and the expertise of users is improving. In this review, we use the literature to focus on the basic types of biosensor experiments, including kinetics, equilibrium analysis, solution competition, active concentration determination and screening. In addition, using examples of particularly well-performed analyses, we illustrate the high information content available in the primary response data and emphasize the impact of including figures in publications to support the results of biosensor analyses.     

Survey of the 1998 optical biosensor literature

The utilization of optical biosensors to study molecular interactions continues to expand. In 1998, 384 articles relating to the use of commercial biosensors were published in 130 different journals. While significant strides in new applications and methodology were made, a majority of the biosensor literature is of rather poor quality. Basic information about experimental conditions is often not presented and many publications fail to display the experimental data, bringing into question the credibility of the results. This review provides suggestions on how to collect, analyze and report biosensor data.     

基于CiteSpace分析核酸适体（Aptamer）技术研究现状

利用可视化分析软件,客观、全面地展示和分析适体的研究现状、研究热点和发展趋势,为适体的研究提供指导和参考。以SCI数据库Web of Science平台为数据源,采用CiteSpace 5.5.R2软件对1900年1月1日至2020年12月31日的适体相关文献进行分析。共纳入文献14 939篇。在该领域发表论文最多的作者是WEIHONG TAN、KHALIL ABNOUS等;近年来突现的主题词是“wide linear range”“pg ml”“clinical diagnosis”“early diagnosis”等,是目前该领域的研究热点;作者共被引分析和文献共被引分析表明,该领域的研究主要集中在适体的体外筛选、适体构象的变化、适体在药物靶向治疗中的应用及适体生物传感器。结果表明,利用CiteSpace软件对Web of Science数据库中已发表的适体文献进行分析,揭示了该领域的研究热点从体外筛选和适体构象变化（1992—2002）到适体在药物靶向治疗和适体生物传感器中的应用（2002—2020）。结合近年来突现的主题词预测适体在药物靶向治疗和适体生物传感器中的应用仍将是未来的研究热点。     

The use of new world primates for biomedical research: an overview of the last four decades

Animal experimentation contributes significantly to the progression of science. Nonhuman primates play a particularly important role in biomedical research not only because of their anatomical, physiological, biochemical, and behavioral similarities with humans but also because of their close phylogenetic affinities. In order to investigate the use of New World primates (NWP) in biomedical research over the last four decades (1966–2005), we performed a quantitative study of the literature listed in bibliographic databases from the Health Sciences. The survey was performed for each genus of NWP that has been bred in the National Center of Primates in Brazil. The number of articles published was determined for each genus and sorted according to the country from which the studies originated and the general scientific field. The data obtained suggests that Brazil is a leader in generating knowledge with NWP models for translational medicine. Am. J. Primatol. 72:1055–1061, 2010. © 2010 Wiley‐Liss, Inc.     

Endogenous opiates: 1983

This paper is the sixth in an annual series of reviews of research involving the endogenous opiates, each installment being restricted to work published during the previous year. Although the early articles in the series attempted to be comprehensive and cover the complete range of research with the opiate peptides, in the last two years we have limited our coverage to non-analgesic and behavioral work due to the enormous number of articles published in the field. The specific areas discussed here include stress, tolerance and dependence, consummatory responses, other gastrointestinal functions, interactions with alcohol, mental illness, learning and memory, cardiovascular responses, respiratory effects, thermoregulation, neurological disorders, activity, and miscellaneous other topics. As in previous years, we have attempted to present a relatively complete review of the subjects covered only for the previous year and generally have not tried to evaluate their contributions relative to those of past years.     

Arsenic trioxide versus tetraarsenic oxide in biomedical research: misunderstandings and misinterpretations

This work presents an analytical chemist’s view on the sometimes unconscious use of arsenic trioxide in (bio)medical research. Arsenic trioxide is a frequently used chemical in cancer treatment research and its action to various malignant cells has been extensively studied and published. Unfortunately some research articles show trivial errors with regards to background knowledge of the chemical, handling the chemical, experimental design and interpretation of results like e.g. in a range of articles comparing advantages of tetraarsenic oxide over arsenic trioxide (dimeric/monomeric) although the dissolution of both yields the same active compound (HAsO₂). To fully understand the implications of these errors we will highlight some of them with the intent to harmonize future work in this field.     

The Citation Merit of Scientific Publications

We propose a new method to assess the merit of any set of scientific papers in a given field based on the citations they receive. Given a field and a citation impact indicator, such as the mean citation or the -index, the merit of a given set of articles is identified with the probability that a randomly drawn set of articles from a given pool of articles in that field has a lower citation impact according to the indicator in question. The method allows for comparisons between sets of articles of different sizes and fields. Using a dataset acquired from Thomson Scientific that contains the articles published in the periodical literature in the period 1998–2007, we show that the novel approach yields rankings of research units different from those obtained by a direct application of the mean citation or the -index.     

基于CiteSpace分析铜绿假单胞菌耐药性研究热点与趋势

【背景】铜绿假单胞菌(Pseudomonas aeruginosa)是临床引发感染的主要病原菌之一,对多种抗菌药物均有耐药性,临床治疗难度大,对该病原菌耐药性的研究一直备受关注。【目的】基于CiteSpace可视化功能,探究铜绿假单胞菌耐药性研究现状、热点与发展趋势。【方法】利用文献计量分析法,以2014–2021年中国知网(CNKI)、万方数据库(Wanfang)、Web of Science (WoS)共8 996篇铜绿假单胞菌耐药性的中英文文献为分析样本,运用Citespace软件对文献发文量、作者合作网络、国家和机构合作网络、文献共被引及期刊分析、关键词聚类、突现等方面进行分析,以探究该研究主题的研究热点及趋势。【结果】英文文献发文量增长速度高于中文文献;我国文献发文量仅次于美国、印度,在该领域科研成果贡献度较高,国际学术影响力较大;中英文文献中均对院内感染疾病和耐碳青霉烯类铜绿假单胞菌持高关注度。然而,中文文献较关注铜绿假单胞菌耐药性的临床防治问题,英文文献则较关注铜绿假单胞菌耐药性的基础研究。【结论】国内外铜绿假单胞菌耐药性研究对院内感染疾病及新型耐药菌的产生与防治关注度最高,暗示以上研究主题是该领域的研究热点与趋势。     

Open by default: a proposed copyright license and waiver agreement for open access research and data in peer-reviewed journals

ABSTRACT: Copyright and licensing of scientific data, internationally, are complex and present legal barriers to data sharing, integration and reuse, and therefore restrict the most efficient transfer and discovery of scientific knowledge. Much data are included within scientific journal articles, their published tables, additional files (supplementary material) and reference lists. However, these data are usually published under licenses which are not appropriate for data. Creative Commons CC0 is an appropriate and increasingly accepted method for dedicating data to the public domain, to enable data reuse with the minimum of restrictions. BioMed Central is committed to working towards implementation of open data-compliant licensing in its publications. Here we detail a protocol for implementing a combined Creative Commons Attribution license (for copyrightable material) and Creative Commons CC0 waiver (for data) agreement for content published in peer-reviewed open access journals. We explain the differences between legal requirements for attribution in copyright, and cultural requirements in scholarship for giving individuals credit for their work through citation. We argue that publishing data in scientific journals under CC0 will have numerous benefits for individuals and society, and yet will have minimal implications for authors and minimal impact on current publishing and research workflows. We provide practical examples and definitions of data types, such as XML and tabular data, and specific secondary use cases for published data, including text mining, reproducible research, and open bibliography. We believe this proposed change to the current copyright and licensing structure in science publishing will help clarify what users -- people and machines -- of the published literature can do, legally, with journal articles and make research using the published literature more efficient. We further believe this model could be adopted across multiple publishers, and invite comment on this article from all stakeholders in scientific research.     

Mapping the knowledge structure of research on patient adherence: knowledge domain visualization based co-word analysis and social network analysis

Background

Patient adherence is an important issue for health service providers and health researchers. However, the knowledge structure of diverse research on treatment adherence is unclear. This study used co-word analysis and social network analysis techniques to analyze research literature on adherence, and to show their knowledge structure and evolution over time.

Methods

Published scientific papers about treatment adherence were retrieved from Web of Science (2000 to May 2011). A total of 2308 relevant articles were included: 788 articles published in 2000–2005 and 1520 articles published in 2006–2011. The keywords of each article were extracted by using the software Biblexcel, and the synonym and isogenous words were merged manually. The frequency of keywords and their co-occurrence frequency were counted. High frequency keywords were selected to yield the co-words matrix. Finally the decomposition maps were used to comb the complex knowledge structures.

Results

Research themes were more general in the first period (2000 to 2005), and more extensive with many more new terms in the second period (2006 to 2011). Research on adherence has covered more and more diseases, populations and methods, but other diseases/conditions are not as hot as HIV/AIDS and have not become specialty themes/sub-directions. Most studies originated from the United States.

Conclusion

The dynamic of this field is mainly divergent, with increasing number of new sub-directions of research. Future research is required to investigate specific directions and converge as well to construct a general paradigm in this field.     

Citation advantage of open access articles

Open access (OA) to the research literature has the potential to accelerate recognition and dissemination of research findings, but its actual effects are controversial. This was a longitudinal bibliometric analysis of a cohort of OA and non-OA articles published between June 8, 2004, and December 20, 2004, in the same journal (PNAS: Proceedings of the National Academy of Sciences). Article characteristics were extracted, and citation data were compared between the two groups at three different points in time: at “quasi-baseline” (December 2004, 0–6 mo after publication), in April 2005 (4–10 mo after publication), and in October 2005 (10–16 mo after publication). Potentially confounding variables, including number of authors, authors' lifetime publication count and impact, submission track, country of corresponding author, funding organization, and discipline, were adjusted for in logistic and linear multiple regression models. A total of 1,492 original research articles were analyzed: 212 (14.2% of all articles) were OA articles paid by the author, and 1,280 (85.8%) were non-OA articles. In April 2005 (mean 206 d after publication), 627 (49.0%) of the non-OA articles versus 78 (36.8%) of the OA articles were not cited (relative risk = 1.3 [95% Confidence Interval: 1.1–1.6]; p = 0.001). 6 mo later (mean 288 d after publication), non-OA articles were still more likely to be uncited (non-OA: 172 [13.6%], OA: 11 [5.2%]; relative risk = 2.6 [1.4–4.7]; p < 0.001). The average number of citations of OA articles was higher compared to non-OA articles (April 2005: 1.5 [SD = 2.5] versus 1.2 [SD = 2.0]; Z = 3.123; p = 0.002; October 2005: 6.4 [SD = 10.4] versus 4.5 [SD = 4.9]; Z = 4.058; p < 0.001). In a logistic regression model, controlling for potential confounders, OA articles compared to non-OA articles remained twice as likely to be cited (odds ratio = 2.1 [1.5–2.9]) in the first 4–10 mo after publication (April 2005), with the odds ratio increasing to 2.9 (1.5–5.5) 10–16 mo after publication (October 2005). Articles published as an immediate OA article on the journal site have higher impact than self-archived or otherwise openly accessible OA articles. We found strong evidence that, even in a journal that is widely available in research libraries, OA articles are more immediately recognized and cited by peers than non-OA articles published in the same journal. OA is likely to benefit science by accelerating dissemination and uptake of research findings.     

Genetic Programming as a tool for identification of analyte-specificity from complex response patterns using a non-specific whole-cell biosensor

Whole-cell biosensors are mostly non-specific with respect to their detection capabilities for toxicants, and therefore offering an interesting perspective in environmental monitoring. However, to fully employ this feature, a robust classification method needs to be implemented into these sensor systems to allow further identification of detected substances. Substance-specific information can be extracted from signals derived from biosensors harbouring one or multiple biological components. Here, a major task is the identification of substance-specific information among considerable amounts of biosensor data. For this purpose, several approaches make use of statistical methods or machine learning algorithms. Genetic Programming (GP), a heuristic machine learning technique offers several advantages compared to other machine learning approaches and consequently may be a promising tool for biosensor data classification. In the present study, we have evaluated the use of GP for the classification of herbicides and herbicide classes (chemical classes) by analysis of substance-specific patterns derived from a whole-cell multi-species biosensor. We re-analysed data from a previously described array-based biosensor system employing diverse microalgae (Podola and Melkonian, 2005), aiming on the identification of five individual herbicides as well as two herbicide classes. GP analyses were performed using the commercially available GP software 'Discipulus', resulting in classifiers (computer programs) for the binary classification of each individual herbicide or herbicide class. GP-generated classifiers both for individual herbicides and herbicide classes were able to perform a statistically significant identification of herbicides or herbicide classes, respectively. The majority of classifiers were able to perform correct classifications (sensitivity) of about 80-95% of test data sets, whereas the false positive rate (specificity) was lower than 20% for most classifiers. Results suggest that a higher number of data sets may lead to a better classification performance. In the present paper, GP-based classification was combined with a biosensor for the first time. Our results demonstrate GP was able to identify substance-specific information within complex biosensor response patterns and furthermore use this information for successful toxicant classification in unknown samples. This suggests further research to assess perspectives and limitations of this approach in the field of biosensors.     

Who Shares? Who Doesn't? Factors Associated with Openly Archiving Raw Research Data

Many initiatives encourage investigators to share their raw datasets in hopes of increasing research efficiency and quality. Despite these investments of time and money, we do not have a firm grasp of who openly shares raw research data, who doesn''t, and which initiatives are correlated with high rates of data sharing. In this analysis I use bibliometric methods to identify patterns in the frequency with which investigators openly archive their raw gene expression microarray datasets after study publication.Automated methods identified 11,603 articles published between 2000 and 2009 that describe the creation of gene expression microarray data. Associated datasets in best-practice repositories were found for 25% of these articles, increasing from less than 5% in 2001 to 30%–35% in 2007–2009. Accounting for sensitivity of the automated methods, approximately 45% of recent gene expression studies made their data publicly available.First-order factor analysis on 124 diverse bibliometric attributes of the data creation articles revealed 15 factors describing authorship, funding, institution, publication, and domain environments. In multivariate regression, authors were most likely to share data if they had prior experience sharing or reusing data, if their study was published in an open access journal or a journal with a relatively strong data sharing policy, or if the study was funded by a large number of NIH grants. Authors of studies on cancer and human subjects were least likely to make their datasets available.These results suggest research data sharing levels are still low and increasing only slowly, and data is least available in areas where it could make the biggest impact. Let''s learn from those with high rates of sharing to embrace the full potential of our research output.     

Scientific publications in nephrology and urology journals from Chinese authors in East Asia: a 10-year survey of the literature

Background

Diseases of the kidneys and genitourinary tract are common health problems that affect people of all ages and demographic backgrounds. In this study, we compared the quantity and quality of nephrological and urological articles published in international journals from the three major regions of China: the mainland (ML), Hong Kong (HK), and Taiwan (TW).

Methods

Nephrological and urological articles originating from ML, TW, and HK that were published in 61 journals from 1999–2008 were retrieved from the PubMed database. We recorded the numbers of total articles, clinical trials, randomized controlled trials, case reports, impact factors (IF), citations, and articles published in the leading general-medicine journals. We used these data to compare the quantity and quality of publication output from the three regions.

Results

The total number of articles increased significantly from 1999 to 2008 in the three regions. The number of articles from ML has exceeded that from HK since 2004, and surpassed that from TW in 2008. Publications from TW had the highest accumulated IF, total citations of articles, and the most articles published in leading general-medicine journals. However, HK publications had the highest average IF. Although ML produced the largest quantity of articles, it exhibited the lowest quality among the three regions.

Conclusion

The number of nephrological and urological publications originating from the three major regions of China increased significantly from 1999 to 2008. The annual number of publications by ML researchers exceeded those from TW and HK. However, the quality of articles from TW and HK was higher than that from ML.