1,721,083 research outputs found
Anisotropic 2D and 3D averaging of fMRI signals
No full textSole, Andres Fco.; Ngan, Shing-Chung; Guillermo, Sapiro; Hu, Xiaoping; Lopez, Antonio. (2000). Anisotropic 2D and 3D averaging of fMRI signals. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/3476
Exosomal Non-coding RNAs: A New Approach to Melanoma Diagnosis and Therapeutic Strategy
No full textAbstract: Malignant melanoma (MM) is a highly aggressive cancer with a poor prognosis. Currently, although a variety of therapies are available for treating melanoma, MM is still a serious threat to the patient’s life due to numerous factors, such as the recurrence of tumors, the emergence of drug resistance, and the lack of effective therapeutic agents. Exosomes are biologically active lipid-bilayer extracellular vesicles secreted by diverse cell types that mediate intercellular signal communication. Studies found that exosomes are involved in cancer by carrying multiple bioactive molecules, including non-- coding RNAs (ncRNAs). The ncRNAs have been reported to play an important role in regulating proliferation, angiogenesis, immune regulation, invasion, metastasis, and treatment resistance of tumors. However, the functional role of exosomal ncRNAs in MM remains unknown. Therefore, this review summarizes the current state of melanoma diagnosis, treatment, and the application of exosomal ncRNAs in MM patients, which may provide new insights into the mechanisms involved in melanoma progression and serve as biomarkers for diagnosis and therapeutic targets
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
Recommended from our members
Exploring the Use of MRI Reporters as Therapeutic Agents
Full text linkMagnetic resonance imaging (MRI) is a non-invasive and non-ionizing imaging modality used to study cellular and molecular events as well as track disease progression in tissues. Due to limited sensitivity, genes, proteins and other molecules can be utilized to increase contrast in specifically labeled tissues and cells for MRI images. MRI reporters are able to provide information on gene expression, cell tracking and migration, and cellular energy metabolism. Additionally, many genes and molecules used to produce contrast may yield therapeutic benefit. Here, we take a closer look at two established MRI reporter genes: creatine and mms6, and determine their therapeutic potential.We tested the efficacy of creatine (Cr) supplementation on the brain. Recent studies suggest that Cr supplementation may improve cognitive function and memory, but the major hurdle is bypassing the blood brain barrier. Initially, we developed a creatine nasal spray and hypothesized that we could increase creatine and phosphocreatine (pCr) concentration in mouse brain. Despite multiple rounds of experiments with varying creatine concentration and duration of administrations, we did not confirm an increase in Cr or pCr in experimental groups. Due to issues resolving Cr and pCr on small tissue samples, we developed a novel pre-incubation technique to convert Cr and pCr to creatinine (Crn) and calculate the concentration of total creatine using commercially available creatine and creatinine assay kits. This technique was demonstrated on Cr and pCr standards as well as mouse muscle and brain tissue.
We tested the ability of MRI reporter mms6 to enhance gemcitabine cytotoxicity on pancreatic tumor cell line, PANC-1. Mms6 is an iron binding protein found in magnetotactic bacteria. When the mms6 gene is expressed in mammalian cells, they increase iron uptake and storage producing measurable contrast in T2-weighted MRI images. We created a PANC-mms6 cell line capable of producing MRI contrast, and treated them with a common pancreatic cancer drug, gemcitabine. Given its resistant nature in PANC-1 cells, we hypothesized that we could increase cytotoxicity and cell death in PANC-mms6 cells over non-expressing PANC-WT cells. The results revealed a significant reduction in viability of PANC-mms6 cells after treatment with gemcitabine while PANC-WT cells remained viable under the same conditions
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
Recommended from our members
Model Fitting and Machine Learning in MRI
No full textThis dissertation addresses two critical challenges in medical imaging by developing physics-based computational frameworks: resolving the rapid signal decay and chemical shift complexities in hyperpolarized gas MRI, and mitigating susceptibility artifacts to enable precise localization of surgical robots in MRI-guided interventions.First, we develop a two-point Dixon method to disentangle dissolved-phase hyperpolarized 129Xe MRI signals into tissue/plasma (TP) and red blood cell (RBC) components. By integrating global parameter estimation through model fitting from free induction decay (FID) signals and algebraic decomposition, this method eliminates reliance on error-prone third-echo acquisitions. Clinical validation across 26 subjects demonstrates equivalence to traditional three-point Dixon approaches, with enhanced RBC signal-to-noise ratios (SNR), particularly in patients with COPD. The framework leverages chemical shift dynamics, T∗2 relaxation modeling, and field inhomogeneity correction to streamline breath-hold durations while preserving diagnostic fidelity.Second, we introduce a simulation-driven machine learning framework for surgical needle localization under susceptibility artifacts. By synthesizing MRI training data via dipolar field modeling and Fourier encoding principles, we generate artifact-corrupted images of nitinol needles in varied orientations. A U-Net model trained exclusively on synthetic data achieves submillimeter accuracy in segmenting needle segments from experimental MRI scans. Validated on curved and straight needles, the method demonstrates robustness against geometric distortions, enabling precise 3D reconstruction of MR-conditional nitinol robots in phantom and in vitro setups.Unifying these advances is the systematic integration of MRI physics into model fitting and machine learning workflows. For hyperpolarized gas imaging, signal separation is governed by chemical shift and relaxation priors. For surgical navigation, spatial encoding physics and susceptibility simulations underpin synthetic data generation. Both methodologies highlight how domain-specific physical laws resolve ill-posed imaging problems, enhancing clinical precision in pulmonary diagnostics and MRI-guided interventions. This work establishes reproducible paradigms for physics based model fitting and machine learning, bridging theoretical models with real-world medical challenges
- …
