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Pubmed Article
A patient-centered methodology that improves the accuracy of prognostic predictions in cancer.
PLoS ONE
PUBLISHED: 01-10-2013
Individualized approaches to prognosis are crucial to effective management of cancer patients. We developed a methodology to assign individualized 5-year disease-specific death probabilities to 1,222 patients with melanoma and to 1,225 patients with breast cancer. For each cancer, three risk subgroups were identified by stratifying patients according to initial stage, and prediction probabilities were generated based on the factors most closely related to 5-year disease-specific death. Separate subgroup probabilities were merged to form a single composite index, and its predictive efficacy was assessed by several measures, including the area (AUC) under its receiver operating characteristic (ROC) curve. The patient-centered methodology achieved an AUC of 0.867 in the prediction of 5-year disease-specific death, compared with 0.787 using the AJCC staging classification alone. When applied to breast cancer patients, it achieved an AUC of 0.907, compared with 0.802 using the AJCC staging classification alone. A prognostic algorithm produced from a randomly selected training subsample of 800 melanoma patients preserved 92.5% of its prognostic efficacy (as measured by AUC) when the same algorithm was applied to a validation subsample containing the remaining patients. Finally, the tailored prognostic approach enhanced the identification of high-risk candidates for adjuvant therapy in melanoma. These results describe a novel patient-centered prognostic methodology with improved predictive efficacy when compared with AJCC stage alone in two distinct malignancies drawn from two separate populations.
Authors: Virginia Espina, Kirsten H. Edmiston, Lance A. Liotta.
Published: 11-08-2014
ABSTRACT
Breast ductal carcinoma in situ (DCIS), by definition, is proliferation of neoplastic epithelial cells within the confines of the breast duct, without breaching the collagenous basement membrane. While DCIS is a non-obligate precursor to invasive breast cancers, the molecular mechanisms and cell populations that permit progression to invasive cancer are not fully known. To determine if progenitor cells capable of invasion existed within the DCIS cell population, we developed a methodology for collecting and culturing sterile human breast tissue at the time of surgery, without enzymatic disruption of tissue. Sterile breast tissue containing ductal segments is harvested from surgically excised breast tissue following routine pathological examination. Tissue containing DCIS is placed in nutrient rich, antibiotic-containing, serum free medium, and transported to the tissue culture laboratory. The breast tissue is further dissected to isolate the calcified areas. Multiple breast tissue pieces (organoids) are placed in a minimal volume of serum free medium in a flask with a removable lid and cultured in a humidified CO2 incubator. Epithelial and fibroblast cell populations emerge from the organoid after 10 - 14 days. Mammospheres spontaneously form on and around the epithelial cell monolayer. Specific cell populations can be harvested directly from the flask without disrupting neighboring cells. Our non-enzymatic tissue culture system reliably reveals cytogenetically abnormal, invasive progenitor cells from fresh human DCIS lesions.
22 Related JoVE Articles!
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
50341
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
50427
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
50476
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The Goeckerman Regimen for the Treatment of Moderate to Severe Psoriasis
Authors: Rishu Gupta, Maya Debbaneh, Daniel Butler, Monica Huynh, Ethan Levin, Argentina Leon, John Koo, Wilson Liao.
Institutions: University of Southern California, University of California, San Francisco , University of California Irvine School of Medicine, University of Arizona College of Medicine, Chicago College of Osteopathic Medicine.
Psoriasis is a chronic, immune-mediated inflammatory skin disease affecting approximately 2-3% of the population. The Goeckerman regimen consists of exposure to ultraviolet B (UVB) light and application of crude coal tar (CCT). Goeckerman therapy is extremely effective and relatively safe for the treatment of psoriasis and for improving a patient's quality of life. In the following article, we present our protocol for the Goeckerman therapy that is utilized specifically at the University of California, San Francisco. This protocol details the preparation of supplies, administration of phototherapy and application of topical tar. This protocol also describes how to assess the patient daily, monitor for adverse effects (including pruritus and burning), and adjust the treatment based on the patient's response. Though it is one of the oldest therapies available for psoriasis, there is an absence of any published videos demonstrating the process in detail. The video is beneficial for healthcare providers who want to administer the therapy, for trainees who want to learn more about the process, and for prospective patients who want to undergo treatment for their cutaneous disease.
Medicine, Issue 77, Infection, Biomedical Engineering, Anatomy, Physiology, Immunology, Dermatology, Skin, Dermis, Epidermis, Skin Diseases, Skin Diseases, Eczematous, Goeckerman, Crude Coal Tar, phototherapy, psoriasis, Eczema, Goeckerman regimen, clinical techniques
50509
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Authors: Johannes Felix Buyel, Rainer Fischer.
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
51216
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Adaptation of Semiautomated Circulating Tumor Cell (CTC) Assays for Clinical and Preclinical Research Applications
Authors: Lori E. Lowes, Benjamin D. Hedley, Michael Keeney, Alison L. Allan.
Institutions: London Health Sciences Centre, Western University, London Health Sciences Centre, Lawson Health Research Institute, Western University.
The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with the presence of circulating tumor cells (CTCs). These rare cells have been demonstrated to be of clinical significance in metastatic breast, prostate, and colorectal cancers. The current gold standard in clinical CTC detection and enumeration is the FDA-cleared CellSearch system (CSS). This manuscript outlines the standard protocol utilized by this platform as well as two additional adapted protocols that describe the detailed process of user-defined marker optimization for protein characterization of patient CTCs and a comparable protocol for CTC capture in very low volumes of blood, using standard CSS reagents, for studying in vivo preclinical mouse models of metastasis. In addition, differences in CTC quality between healthy donor blood spiked with cells from tissue culture versus patient blood samples are highlighted. Finally, several commonly discrepant items that can lead to CTC misclassification errors are outlined. Taken together, these protocols will provide a useful resource for users of this platform interested in preclinical and clinical research pertaining to metastasis and CTCs.
Medicine, Issue 84, Metastasis, circulating tumor cells (CTCs), CellSearch system, user defined marker characterization, in vivo, preclinical mouse model, clinical research
51248
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Voluntary Breath-hold Technique for Reducing Heart Dose in Left Breast Radiotherapy
Authors: Frederick R. Bartlett, Ruth M. Colgan, Ellen M. Donovan, Karen Carr, Steven Landeg, Nicola Clements, Helen A. McNair, Imogen Locke, Philip M. Evans, Joanne S. Haviland, John R. Yarnold, Anna M. Kirby.
Institutions: Royal Marsden NHS Foundation Trust, University of Surrey, Institute of Cancer Research, Sutton, UK, Institute of Cancer Research, Sutton, UK.
Breath-holding techniques reduce the amount of radiation received by cardiac structures during tangential-field left breast radiotherapy. With these techniques, patients hold their breath while radiotherapy is delivered, pushing the heart down and away from the radiotherapy field. Despite clear dosimetric benefits, these techniques are not yet in widespread use. One reason for this is that commercially available solutions require specialist equipment, necessitating not only significant capital investment, but often also incurring ongoing costs such as a need for daily disposable mouthpieces. The voluntary breath-hold technique described here does not require any additional specialist equipment. All breath-holding techniques require a surrogate to monitor breath-hold consistency and whether breath-hold is maintained. Voluntary breath-hold uses the distance moved by the anterior and lateral reference marks (tattoos) away from the treatment room lasers in breath-hold to monitor consistency at CT-planning and treatment setup. Light fields are then used to monitor breath-hold consistency prior to and during radiotherapy delivery.
Medicine, Issue 89, breast, radiotherapy, heart, cardiac dose, breath-hold
51578
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Tumor Treating Field Therapy in Combination with Bevacizumab for the Treatment of Recurrent Glioblastoma
Authors: Ayman I. Omar.
Institutions: Southern Illinois University School of Medicine.
A novel device that employs TTF therapy has recently been developed and is currently in use for the treatment of recurrent glioblastoma (rGBM). It was FDA approved in April 2011 for the treatment of patients 22 years or older with rGBM. The device delivers alternating electric fields and is programmed to ensure maximal tumor cell kill1. Glioblastoma is the most common type of glioma and has an estimated incidence of approximately 10,000 new cases per year in the United States alone2. This tumor is particularly resistant to treatment and is uniformly fatal especially in the recurrent setting3-5. Prior to the approval of the TTF System, the only FDA approved treatment for rGBM was bevacizumab6. Bevacizumab is a humanized monoclonal antibody targeted against the vascular endothelial growth factor (VEGF) protein that drives tumor angiogenesis7. By blocking the VEGF pathway, bevacizumab can result in a significant radiographic response (pseudoresponse), improve progression free survival and reduce corticosteroid requirements in rGBM patients8,9. Bevacizumab however failed to prolong overall survival in a recent phase III trial26. A pivotal phase III trial (EF-11) demonstrated comparable overall survival between physicians’ choice chemotherapy and TTF Therapy but better quality of life were observed in the TTF arm10. There is currently an unmet need to develop novel approaches designed to prolong overall survival and/or improve quality of life in this unfortunate patient population. One appealing approach would be to combine the two currently approved treatment modalities namely bevacizumab and TTF Therapy. These two treatments are currently approved as monotherapy11,12, but their combination has never been evaluated in a clinical trial. We have developed an approach for combining those two treatment modalities and treated 2 rGBM patients. Here we describe a detailed methodology outlining this novel treatment protocol and present representative data from one of the treated patients.
Medicine, Issue 92, Tumor Treating Fields, TTF System, TTF Therapy, Recurrent Glioblastoma, Bevacizumab, Brain Tumor
51638
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A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies
Authors: Inti Zlobec, Guido Suter, Aurel Perren, Alessandro Lugli.
Institutions: University of Bern.
Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a ‘donor’ block into a ‘recipient’ block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 ‘recipient’ blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research.
Medicine, Issue 91, tissue microarray, biomarkers, prognostic, predictive, digital pathology, slide scanning
51893
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
50319
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Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Authors: Fijoy Vadakkumpadan, Hermenegild Arevalo, Natalia A. Trayanova.
Institutions: Johns Hopkins University.
Patient-specific simulations of heart (dys)function aimed at personalizing cardiac therapy are hampered by the absence of in vivo imaging technology for clinically acquiring myocardial fiber orientations. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4 °. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.The new insights obtained from the project will pave the way for the development of patient-specific models of the heart that can aid physicians in personalized diagnosis and decisions regarding electrophysiological interventions.
Bioengineering, Issue 71, Biomedical Engineering, Medicine, Anatomy, Physiology, Cardiology, Myocytes, Cardiac, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, MRI, Diffusion Magnetic Resonance Imaging, Cardiac Electrophysiology, computerized simulation (general), mathematical modeling (systems analysis), Cardiomyocyte, biomedical image processing, patient-specific modeling, Electrophysiology, simulation
50125
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Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Authors: Dana Faratian, Jason Christiansen, Mark Gustavson, Christine Jones, Christopher Scott, InHwa Um, David J. Harrison.
Institutions: University of Edinburgh, HistoRx Inc..
Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ. We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7. To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.
Medicine, Issue 56, quantitative immunofluorescence, heterogeneity, cancer, biomarker, targeted therapy, immunohistochemistry, proteomics, histopathology
3334
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Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples
Authors: Chen Lu, Joshua L. Wonsidler, Jianwei Li, Yanming Du, Timothy Block, Brian Haab, Songming Chen.
Institutions: Institute for Hepatitis and Virus Research, Thomas Jefferson University , Drexel University College of Medicine, Van Andel Research Institute, Serome Biosciences Inc..
In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed. Introduction Glycosylation of protein, which is the most ubiquitous post-translational modification on proteins, modifies the physical, chemical, and biological properties of a protein, and plays a fundamental role in various biological processes1-6. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases 7-12. In fact, most current cancer biomarkers, such as the L3 fraction of α-1 fetoprotein (AFP) for hepatocellular carcinoma 13-15, and CA199 for pancreatic cancer 16, 17 are all aberrant glycan moieties on glycoproteins. However, methods to study protein glycosylation have been complicated, and not suitable for routine laboratory and clinical settings. Chen et al. has recently invented a chemically blocked antibody microarray with a glycan-binding protein (GBP) detection method for high-throughput and multiplexed profile glycosylation of native glycoproteins in a complex sample 18. In this affinity based microarray method, multiple immobilized glycoprotein-specific antibodies capture and isolate glycoproteins from the complex mixture directly on the microarray slide, and the glycans on each individual captured protein are measured by GBPs. Because all normal antibodies contain N-glycans which could be recognized by most GBPs, the critical step of this method is to chemically block the glycans on the antibodies from binding to GBP. In the procedure, the cis-diol groups of the glycans on the antibodies were first oxidized to aldehyde groups by using NaIO4 in sodium acetate buffer avoiding light. The aldehyde groups were then conjugated to the hydrazide group of a cross-linker, 4-(4-N-MaleimidoPhenyl)butyric acid Hydrazide HCl (MPBH), followed by the conjugation of a dipeptide, Cys-Gly, to the maleimide group of the MPBH. Thus, the cis-diol groups on glycans of antibodies were converted into bulky none hydroxyl groups, which hindered the lectins and other GBPs bindings to the capture antibodies. This blocking procedure makes the GBPs and lectins bind only to the glycans of captured proteins. After this chemically blocking, serum samples were incubated with the antibody microarray, followed by the glycans detection by using different biotinylated lectins and GBPs, and visualized with Cy3-streptavidin. The parallel use of an antibody panel and multiple lectin probing provides discrete glycosylation profiles of multiple proteins in a given sample 18-20. This method has been used successfully in multiple different labs 1, 7, 13, 19-31. However, stability of MPBH and Cys-Gly, complicated and extended procedure in this method affect the reproducibility, effectiveness and efficiency of the method. In this new protocol, we replaced both MPBH and Cys-Gly with one much more stable reagent glutamic acid hydrazide (Glu-hydrazide), which significantly improved the reproducibility of the method, simplified and shorten the whole procedure so that the it can be completed within one working day. In this new protocol, we describe the detailed procedure of the protocol which can be readily adopted by normal labs for routine protein glycosylation study and techniques which are necessary to obtain reproducible and repeatable results.
Molecular Biology, Issue 63, Glycoproteins, glycan-binding protein, specific protein glycosylation, multiplexed high-throughput glycan blocked antibody microarray
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Detection and Isolation of Circulating Melanoma Cells using Photoacoustic Flowmetry
Authors: Christine M. O'Brien, Kyle Rood, Shramik Sengupta, Sagar K. Gupta, Thiago DeSouza, Aaron Cook, John A. Viator.
Institutions: University of Missouri.
Circulating tumor cells (CTCs) are those cells that have separated from a macroscopic tumor and spread through the blood and lymph systems to seed secondary tumors1,2,3. CTCs are indicators of metastatic disease and their detection in blood samples may be used to diagnose cancer and monitor a patient′s response to therapy. Since CTCs are rare, comprising about one tumor cell among billions of normal blood cells in advanced cancer patients, their detection and enumeration is a difficult task. We exploit the presence of pigment in most melanoma cells to generate photoacoustic, or laser induced ultrasonic waves in a custom flow cytometer for detection of circulating melanoma cells (CMCs)4,5. This process entails separating a whole blood sample using centrifugation and obtaining the white blood cell layer. If present in whole blood, CMCs will separate with the white blood cells due to similar density. These cells are resuspended in phosphate buffered saline (PBS) and introduced into the flowmeter. Rather than a continuous flow of the blood cell suspension, we induced two phase flow in order to capture these cells for further study. In two phase flow, two immiscible liquids in a microfluidic system meet at a junction and form alternating slugs of liquid6,7. PBS suspended white blood cells and air form microliter slugs that are sequentially irradiated with laser light. The addition of a surfactant to the liquid phase allows uniform slug formation and the user can create different sized slugs by altering the flow rates of the two phases. Slugs of air and slugs of PBS with white blood cells contain no light absorbers and hence, do not produce photoacoustic waves. However, slugs of white blood cells that contain even single CMCs absorb laser light and produce high frequency acoustic waves. These slugs that generate photoacoustic waves are sequestered and collected for cytochemical staining for verification of CMCs.
Bioengineering, Issue 57, cancer, circulating tumor cell, CTCs, melanoma, metastasis, optoacoustic
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Nerve Excitability Assessment in Chemotherapy-induced Neurotoxicity
Authors: Susanna B. Park, Cindy S-Y. Lin, Matthew C. Kiernan.
Institutions: University of New South Wales , University of New South Wales , University of New South Wales .
Chemotherapy-induced neurotoxicity is a serious consequence of cancer treatment, which occurs with some of the most commonly used chemotherapies1,2. Chemotherapy-induced peripheral neuropathy produces symptoms of numbness and paraesthesia in the limbs and may progress to difficulties with fine motor skills and walking, leading to functional impairment. In addition to producing troubling symptoms, chemotherapy-induced neuropathy may limit treatment success leading to dose reduction or early cessation of treatment. Neuropathic symptoms may persist long-term, leaving permanent nerve damage in patients with an otherwise good prognosis3. As chemotherapy is utilised more often as a preventative measure, and survival rates increase, the importance of long-lasting and significant neurotoxicity will increase. There are no established neuroprotective or treatment options and a lack of sensitive assessment methods. Appropriate assessment of neurotoxicity will be critical as a prognostic factor and as suitable endpoints for future trials of neuroprotective agents. Current methods to assess the severity of chemotherapy-induced neuropathy utilise clinician-based grading scales which have been demonstrated to lack sensitivity to change and inter-observer objectivity4. Conventional nerve conduction studies provide information about compound action potential amplitude and conduction velocity, which are relatively non-specific measures and do not provide insight into ion channel function or resting membrane potential. Accordingly, prior studies have demonstrated that conventional nerve conduction studies are not sensitive to early change in chemotherapy-induced neurotoxicity4-6. In comparison, nerve excitability studies utilize threshold tracking techniques which have been developed to enable assessment of ion channels, pumps and exchangers in vivo in large myelinated human axons7-9. Nerve excitability techniques have been established as a tool to examine the development and severity of chemotherapy-induced neurotoxicity10-13. Comprising a number of excitability parameters, nerve excitability studies can be used to assess acute neurotoxicity arising immediately following infusion and the development of chronic, cumulative neurotoxicity. Nerve excitability techniques are feasible in the clinical setting, with each test requiring only 5 -10 minutes to complete. Nerve excitability equipment is readily commercially available, and a portable system has been devised so that patients can be tested in situ in the infusion centre setting. In addition, these techniques can be adapted for use in multiple chemotherapies. In patients treated with the chemotherapy oxaliplatin, primarily utilised for colorectal cancer, nerve excitability techniques provide a method to identify patients at-risk for neurotoxicity prior to the onset of chronic neuropathy. Nerve excitability studies have revealed the development of an acute Na+ channelopathy in motor and sensory axons10-13. Importantly, patients who demonstrated changes in excitability in early treatment were subsequently more likely to develop moderate to severe neurotoxicity11. However, across treatment, striking longitudinal changes were identified only in sensory axons which were able to predict clinical neurological outcome in 80% of patients10. These changes demonstrated a different pattern to those seen acutely following oxaliplatin infusion, and most likely reflect the development of significant axonal damage and membrane potential change in sensory nerves which develops longitudinally during oxaliplatin treatment10. Significant abnormalities developed during early treatment, prior to any reduction in conventional measures of nerve function, suggesting that excitability parameters may provide a sensitive biomarker.
Neuroscience, Issue 62, Chemotherapy, Neurotoxicity, Neuropathy, Nerve excitability, Ion channel function, Oxaliplatin, oncology, medicine
3439
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Multispectral Real-time Fluorescence Imaging for Intraoperative Detection of the Sentinel Lymph Node in Gynecologic Oncology
Authors: Lucia M.A. Crane, George Themelis, K. Tim Buddingh, Niels J. Harlaar, Rick G. Pleijhuis, Athanasios Sarantopoulos, Ate G.J. van der Zee, Vasilis Ntziachristos, Gooitzen M. van Dam.
Institutions: University Medical Center Groningen, Technical University Munich, University Medical Center Groningen.
The prognosis in virtually all solid tumors depends on the presence or absence of lymph node metastases.1-3 Surgical treatment most often combines radical excision of the tumor with a full lymphadenectomy in the drainage area of the tumor. However, removal of lymph nodes is associated with increased morbidity due to infection, wound breakdown and lymphedema.4,5 As an alternative, the sentinel lymph node procedure (SLN) was developed several decades ago to detect the first draining lymph node from the tumor.6 In case of lymphogenic dissemination, the SLN is the first lymph node that is affected (Figure 1). Hence, if the SLN does not contain metastases, downstream lymph nodes will also be free from tumor metastases and need not to be removed. The SLN procedure is part of the treatment for many tumor types, like breast cancer and melanoma, but also for cancer of the vulva and cervix.7 The current standard methodology for SLN-detection is by peritumoral injection of radiocolloid one day prior to surgery, and a colored dye intraoperatively. Disadvantages of the procedure in cervical and vulvar cancer are multiple injections in the genital area, leading to increased psychological distress for the patient, and the use of radioactive colloid. Multispectral fluorescence imaging is an emerging imaging modality that can be applied intraoperatively without the need for injection of radiocolloid. For intraoperative fluorescence imaging, two components are needed: a fluorescent agent and a quantitative optical system for intraoperative imaging. As a fluorophore we have used indocyanine green (ICG). ICG has been used for many decades to assess cardiac function, cerebral perfusion and liver perfusion.8 It is an inert drug with a safe pharmaco-biological profile. When excited at around 750 nm, it emits light in the near-infrared spectrum around 800 nm. A custom-made multispectral fluorescence imaging camera system was used.9. The aim of this video article is to demonstrate the detection of the SLN using intraoperative fluorescence imaging in patients with cervical and vulvar cancer. Fluorescence imaging is used in conjunction with the standard procedure, consisting of radiocolloid and a blue dye. In the future, intraoperative fluorescence imaging might replace the current method and is also easily transferable to other indications like breast cancer and melanoma.
Medicine, Issue 44, Image-guided surgery, multispectral fluorescence, sentinel lymph node, gynecologic oncology
2225
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A Protocol for Computer-Based Protein Structure and Function Prediction
Authors: Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang.
Institutions: University of Michigan , University of Kansas.
Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.
Biochemistry, Issue 57, On-line server, I-TASSER, protein structure prediction, function prediction
3259
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
1988
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Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
Authors: Cila Herman, Muge Pirtini Cetingul.
Institutions: The Johns Hopkins University.
In 2010 approximately 68,720 melanomas will be diagnosed in the US alone, with around 8,650 resulting in death 1. To date, the only effective treatment for melanoma remains surgical excision, therefore, the key to extended survival is early detection 2,3. Considering the large numbers of patients diagnosed every year and the limitations in accessing specialized care quickly, the development of objective in vivo diagnostic instruments to aid the diagnosis is essential. New techniques to detect skin cancer, especially non-invasive diagnostic tools, are being explored in numerous laboratories. Along with the surgical methods, techniques such as digital photography, dermoscopy, multispectral imaging systems (MelaFind), laser-based systems (confocal scanning laser microscopy, laser doppler perfusion imaging, optical coherence tomography), ultrasound, magnetic resonance imaging, are being tested. Each technique offers unique advantages and disadvantages, many of which pose a compromise between effectiveness and accuracy versus ease of use and cost considerations. Details about these techniques and comparisons are available in the literature 4. Infrared (IR) imaging was shown to be a useful method to diagnose the signs of certain diseases by measuring the local skin temperature. There is a large body of evidence showing that disease or deviation from normal functioning are accompanied by changes of the temperature of the body, which again affect the temperature of the skin 5,6. Accurate data about the temperature of the human body and skin can provide a wealth of information on the processes responsible for heat generation and thermoregulation, in particular the deviation from normal conditions, often caused by disease. However, IR imaging has not been widely recognized in medicine due to the premature use of the technology 7,8 several decades ago, when temperature measurement accuracy and the spatial resolution were inadequate and sophisticated image processing tools were unavailable. This situation changed dramatically in the late 1990s-2000s. Advances in IR instrumentation, implementation of digital image processing algorithms and dynamic IR imaging, which enables scientists to analyze not only the spatial, but also the temporal thermal behavior of the skin 9, allowed breakthroughs in the field. In our research, we explore the feasibility of IR imaging, combined with theoretical and experimental studies, as a cost effective, non-invasive, in vivo optical measurement technique for tumor detection, with emphasis on the screening and early detection of melanoma 10-13. In this study, we show data obtained in a patient study in which patients that possess a pigmented lesion with a clinical indication for biopsy are selected for imaging. We compared the difference in thermal responses between healthy and malignant tissue and compared our data with biopsy results. We concluded that the increased metabolic activity of the melanoma lesion can be detected by dynamic infrared imaging.
Medicine, Issue 51, Infrared imaging, quantitative thermal analysis, image processing, skin cancer, melanoma, transient thermal response, skin thermal models, skin phantom experiment, patient study
2679
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
3871
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A New Single Chamber Implantable Defibrillator with Atrial Sensing: A Practical Demonstration of Sensing and Ease of Implantation
Authors: Dietmar Bänsch, Ralph Schneider, Ibrahim Akin, Cristoph A. Nienaber.
Institutions: University Hospital of Rostock, Germany.
Implantable cardioverter-defibrillators (ICDs) terminate ventricular tachycardia (VT) and ventricular fibrillation (VF) with high efficacy and can protect patients from sudden cardiac death (SCD). However, inappropriate shocks may occur if tachycardias are misdiagnosed. Inappropriate shocks are harmful and impair patient quality of life. The risk of inappropriate therapy increases with lower detection rates programmed in the ICD. Single-chamber detection poses greater risks for misdiagnosis when compared with dual-chamber devices that have the benefit of additional atrial information. However, using a dual-chamber device merely for the sake of detection is generally not accepted, since the risks associated with the second electrode may outweigh the benefits of detection. Therefore, BIOTRONIK developed a ventricular lead called the LinoxSMART S DX, which allows for the detection of atrial signals from two electrodes positioned at the atrial part of the ventricular electrode. This device contains two ring electrodes; one that contacts the atrial wall at the junction of the superior vena cava (SVC) and one positioned at the free floating part of the electrode in the atrium. The excellent signal quality can only be achieved by a special filter setting in the ICD (Lumax 540 and 740 VR-T DX, BIOTRONIK). Here, the ease of implantation of the system will be demonstrated.
Medicine, Issue 60, Implantable defibrillator, dual chamber, single chamber, tachycardia detection
3750
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Interview: Glycolipid Antigen Presentation by CD1d and the Therapeutic Potential of NKT cell Activation
Authors: Mitchell Kronenberg.
Institutions: La Jolla Institute for Allergy and Immunology.
Natural Killer T cells (NKT) are critical determinants of the immune response to cancer, regulation of autioimmune disease, clearance of infectious agents, and the development of artheriosclerotic plaques. In this interview, Mitch Kronenberg discusses his laboratory's efforts to understand the mechanism through which NKT cells are activated by glycolipid antigens. Central to these studies is CD1d - the antigen presenting molecule that presents glycolipids to NKT cells. The advent of CD1d tetramer technology, a technique developed by the Kronenberg lab, is critical for the sorting and identification of subsets of specific glycolipid-reactive T cells. Mitch explains how glycolipid agonists are being used as therapeutic agents to activate NKT cells in cancer patients and how CD1d tetramers can be used to assess the state of the NKT cell population in vivo following glycolipid agonist therapy. Current status of ongoing clinical trials using these agonists are discussed as well as Mitch's prediction for areas in the field of immunology that will have emerging importance in the near future.
Immunology, Issue 10, Natural Killer T cells, NKT cells, CD1 Tetramers, antigen presentation, glycolipid antigens, CD1d, Mucosal Immunity, Translational Research
635
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