1,721,071 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
Artificial surface-modified Si3N4 nanopores for single surface-modified gold nanoparticle scanning
No full textSi3N4 nanopores functionalized with 4–4’ bipyridyl, 3.2–6.5 nm in diameter and 30–50 nm in length, are shown to interact with single, negatively charged, coated gold nanoparticles from 2.4 to 8.9 nm diameter. It is possible to detect the interactions through alterations in the ionic current, whether or not the electric-field driven nanoparticle threads through the pore
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Furthering Advances in Liquid Biopsy by Harnessing Machine Learning and Extracellular Vesicles
No full textLiquid biopsy provides a transformative approach for cancer diagnostics, offering minimally invasive sampling, rapid processing, and potential for early-stage detection, monitoring treatment response, and identifying minimal residual disease. However, current omics-based approaches are expensive, slow, and suffer from lengthy processing times and the need for highly specialized staff. They typically rely primarily on circulating tumor cells (CTCs) and cell-free DNA (cfDNA), which are inherently low in concentrations in peripheral circulation in early-stage cancer.To address these challenges, this thesis integrates multiple label-free and biophysical approaches for high-throughput analysis of extracellular vesicles (EVs), key mediators of cancer progression and intercellular communication.We first developed a machine learning-enhanced spectroscopic pipeline combining Raman and Fourier-transform infrared (FTIR) spectroscopy. Using a novel convolutional neural network (CNN) approach and rapid sample liquid drop-cast method, a diagnostic accuracy >85% is achieved for early-stage detection of head and neck cancer (HNC), while significantly reducing the processing time to mere hours in comparison to omics-based study.To further address EV heterogeneity, we engineered a microfluidic device that exploits electrophoretic mobility to separate EV subpopulations. This enabled downstream analysis of vesicle size, charge, and biochemical composition, laying the groundwork for functionally distinct EV phenotyping. Atomic force microscopy (AFM) was employed to characterize mechanical and topographical features of isolated EV subsets, while spatial biology analysis contextualized EV localization and interactions within tumor microenvironments.Together, this body of work advances a multimodal platform for EV-based cancer diagnostics, bridging functional biophysics with clinical utility and providing new insights into vesicle diversity, biogenesis, and translational potential
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
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Laser trapping Raman spectroscopy (LTRS) of clinical extracellular vesicles (EVs): accounting for heterogeneity at single particle resolution
Full text linkExtracellular vesicles (EVs) are membrane-bound nano-assemblies shed from all cells and reflect cellular state, giving them incredible clinical biomarker potential for monitoring disease progression or a patient’s response to certain drugs. EVs also have unique qualities that are of interest for drug delivery application due to their ability to cross the blood-brain barrier, as well as target specific organs and tumor sites. The specific mechanisms and interactions that allow EVs such abilities are ever-elusive, in large part due to complexity arising from their inherent heterogeneity. EVs come in many different shapes, sizes, and molecular compositions, even leading to controversy about how exactly EVs are defined. In addition, studies often examine EVs in bulk, which does not account for EV heterogeneity at single vesicle resolution. Not accounting for EV heterogeneity results in an underrepresentation of EV subpopulations. In the case of recent work to apply EVs as next-generation drug delivery vehicles, this leads to a danger of drug off-targeting. Thus, it is imperative to capture native EV heterogeneity by single-particle analysis to maximize EVs’ clinical potential. Current single-particle detection techniques, including nanoparticle tracking analysis (NTA), flow cytometry, and enzyme-linked immunosorbent assay (ELISA), which are typically used for EV characterization, lack sufficient sensitivity and are diffraction-limited. Hence, current single-particle detection techniques do not completely or accurately characterize EV populations. Here, an optimized single-molecule detection technique, laser trapping Raman spectroscopy (LTRS) that combines optical tweezers and Raman spectroscopy, is introduced and evaluated by its capacity to better capture native EV heterogeneity. I apply LTRS in two major test cases, to distinguish EVs from structurally similarly composed contaminating lipoprotein complexes and to characterize loaded EVs with relevance to drug delivery
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
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Multiscale Raman Spectroscopy for Liquid Biopsy Cancer Diagnostics
Full text linkFor more effective early-stage cancer diagnostics, there is a need to develop sensitive and specific, non- or minimally invasive, and cost-effective methods for identifying circulating tumor-associated biomolecules, including extracellular vesicles (EVs). As a rapid, label-free, non-destructive analytical measurement requiring little to no sample preparation, Raman spectroscopy shows great promise for liquid biopsy cancer detection and diagnosis. While many studies have demonstrated the promise of Raman spectroscopy to provide value for clinical diagnostics, the sensitivity and specificity of such platforms typically drops when applied to larger patient cohorts. Additionally, Raman can suffer from low signal due to the number of inelastically scattered photons (~1 in a million) produced after a sample is interrogated with a laser. Surface enhanced Raman scattering (SERS) is a powerful extension of this technique, providing orders of magnitude increase in chemical sensitivity compared to spontaneous Raman scattering. Yet it remains a challenge to synthesize robust, uniform SERS substrates quickly and easily. Raman technology has not been successfully moved into the clinic and is hindered by the need to develop more miniaturized and automated systems that are integrated with inexpensive and useful SERS materials. Thus, the objective of this dissertation work is three-fold: 1) to carry out experiments on large clinical datasets to validate Raman and SERS diagnostics; 2) to examine the value of spectroscopic analysis of EVs; and 3) to develop novel SERS materials that are robust, biocompatible, and inexpensive.To address these objectives, we carried out Raman analysis of plasma, serum, and saliva from hundreds of cancer patients and benign controls (from patients undergoing similar procedures or screenings without cancer), including patients diagnosed with head and neck, ovarian, and endometrial cancers. Several notable findings were reported arising from this analysis, ranging from optimization of Raman data collection and data analysis, discovery and application of new plasmonic materials, and applied clinical testing of EVs.
First, we showed that a simple data augmentation routine of fusing plasma and saliva spectra provided significantly higher clinical value than either biofluid alone, pushing forward the potential of clinical translation of Raman spectroscopy for liquid biopsy cancer diagnostics.
Next, we reported the utilization of a simple plasmonic scaffold composed of a microscale biosilicate substrate embedded with silver nanoparticles for SERS analysis of ovarian and endometrial cancer EVs. We observed a major loss of sensitivity for ovarian and endometrial cancer following enzymatic cleavage of EVs’ extraluminal domain, suggesting its critical significance for diagnostic platforms. Using SERS, we also confirmed that three common EV isolation methods (differential ultracentrifugation, density gradient ultracentrifugation, and size exclusion chromatography) yield variable lipoprotein content. However, in combining SERS analysis with machine learning assisted classification, we showed that the disease state is the main driver of distinction between EV samples, and largely unaffected by choice of isolation.
Finally, we demonstrated the synthesis and characterization of a new homogeneous gold nanofoam (AuNF) substrate produced by a rapid, one-pot, four-ingredient synthetic approach. These novel AuNFs were rapidly nucleated with macroscale porosity and then chemically roughened to produce nanoscale features that confer homogeneous and high signal enhancement (~10^9) across large areas, a comparable performance to lithographically produced substrates, with high utility for application in low-resource settings
The work presented below comprehensively shows the promise of Raman as a clinical diagnostic tool and takes measured steps toward validating the technology in the context of cancer disease states. The technique has high disease discrimination in whole biofluids and isolated EV populations, and the addition of novel nanomaterials increases the sensitivity and specificity to reach clinically necessary levels. This work is foundational in promoting the continued emphasis on translating Raman to be a clinically relevant diagnostic tool
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