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Pubmed Article
Heart rate variability dynamics for the prognosis of cardiovascular risk.
PUBLISHED: 01-17-2011
Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis.
Authors: Nick Reed, James Murphy, Talia Dick, Katie Mah, Melissa Paniccia, Lee Verweel, Danielle Dobney, Michelle Keightley.
Published: 09-25-2014
Concussion is one of the most commonly reported injuries amongst children and youth involved in sport participation. Following a concussion, youth can experience a range of short and long term neurobehavioral symptoms (somatic, cognitive and emotional/behavioral) that can have a significant impact on one’s participation in daily activities and pursuits of interest (e.g., school, sports, work, family/social life, etc.). Despite this, there remains a paucity in clinically driven research aimed specifically at exploring concussion within the youth sport population, and more specifically, multi-modal approaches to measuring recovery. This article provides an overview of a novel and multi-modal approach to measuring recovery amongst youth athletes following concussion. The presented approach involves the use of both pre-injury/baseline testing and post-injury/follow-up testing to assess performance across a wide variety of domains (post-concussion symptoms, cognition, balance, strength, agility/motor skills and resting state heart rate variability). The goal of this research is to gain a more objective and accurate understanding of recovery following concussion in youth athletes (ages 10-18 years). Findings from this research can help to inform the development and use of improved approaches to concussion management and rehabilitation specific to the youth sport community.
26 Related JoVE Articles!
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
Authors: Jennifer J. Heisz, Anthony R. McIntosh.
Institutions: Baycrest.
When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain signal. Typically, researchers represent the brain's response as the mean across repeated experimental trials and disregard signal fluctuations over time as "noise". However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics. This article describes the novel method of multiscale entropy (MSE) for quantifying brain signal variability. MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.
Neuroscience, Issue 76, Neurobiology, Anatomy, Physiology, Medicine, Biomedical Engineering, Electroencephalography, EEG, electroencephalogram, Multiscale entropy, sample entropy, MEG, neuroimaging, variability, noise, timescale, non-linear, brain signal, information theory, brain, imaging
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Evaluation of Respiratory Muscle Activation Using Respiratory Motor Control Assessment (RMCA) in Individuals with Chronic Spinal Cord Injury
Authors: Sevda C. Aslan, Manpreet K. Chopra, William B. McKay, Rodney J. Folz, Alexander V. Ovechkin.
Institutions: University of Louisville, Shepherd Center, University of Louisville.
During breathing, activation of respiratory muscles is coordinated by integrated input from the brain, brainstem, and spinal cord. When this coordination is disrupted by spinal cord injury (SCI), control of respiratory muscles innervated below the injury level is compromised1,2 leading to respiratory muscle dysfunction and pulmonary complications. These conditions are among the leading causes of death in patients with SCI3. Standard pulmonary function tests that assess respiratory motor function include spirometrical and maximum airway pressure outcomes: Forced Vital Capacity (FVC), Forced Expiratory Volume in one second (FEV1), Maximal Inspiratory Pressure (PImax) and Maximal Expiratory Pressure (PEmax)4,5. These values provide indirect measurements of respiratory muscle performance6. In clinical practice and research, a surface electromyography (sEMG) recorded from respiratory muscles can be used to assess respiratory motor function and help to diagnose neuromuscular pathology. However, variability in the sEMG amplitude inhibits efforts to develop objective and direct measures of respiratory motor function6. Based on a multi-muscle sEMG approach to characterize motor control of limb muscles7, known as the voluntary response index (VRI)8, we developed an analytical tool to characterize respiratory motor control directly from sEMG data recorded from multiple respiratory muscles during the voluntary respiratory tasks. We have termed this the Respiratory Motor Control Assessment (RMCA)9. This vector analysis method quantifies the amount and distribution of activity across muscles and presents it in the form of an index that relates the degree to which sEMG output within a test-subject resembles that from a group of healthy (non-injured) controls. The resulting index value has been shown to have high face validity, sensitivity and specificity9-11. We showed previously9 that the RMCA outcomes significantly correlate with levels of SCI and pulmonary function measures. We are presenting here the method to quantitatively compare post-spinal cord injury respiratory multi-muscle activation patterns to those of healthy individuals.
Medicine, Issue 77, Anatomy, Physiology, Behavior, Neurobiology, Neuroscience, Spinal Cord Injuries, Pulmonary Disease, Chronic Obstructive, Motor Activity, Analytical, Diagnostic and Therapeutic Techniques and Equipment, Respiratory Muscles, Motor Control, Electromyography, Pulmonary Function Test, Spinal Cord Injury, SCI, clinical techniques
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Pulse Wave Velocity Testing in the Baltimore Longitudinal Study of Aging
Authors: Melissa David, Omar Malti, Majd AlGhatrif, Jeanette Wright, Marco Canepa, James B. Strait.
Institutions: National Institute of Aging.
Carotid-femoral pulse wave velocity is considered the gold standard for measurements of central arterial stiffness obtained through noninvasive methods1. Subjects are placed in the supine position and allowed to rest quietly for at least 10 min prior to the start of the exam. The proper cuff size is selected and a blood pressure is obtained using an oscillometric device. Once a resting blood pressure has been obtained, pressure waveforms are acquired from the right femoral and right common carotid arteries. The system then automatically calculates the pulse transit time between these two sites (using the carotid artery as a surrogate for the descending aorta). Body surface measurements are used to determine the distance traveled by the pulse wave between the two sampling sites. This distance is then divided by the pulse transit time resulting in the pulse wave velocity. The measurements are performed in triplicate and the average is used for analysis.
Medicine, Issue 84, Pulse Wave Velocity (PWV), Pulse Wave Analysis (PWA), Arterial stiffness, Aging, Cardiovascular, Carotid-femoral pulse
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Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies
Authors: Patrick De Boever, Tijs Louwies, Eline Provost, Luc Int Panis, Tim S. Nawrot.
Institutions: Flemish Institute for Technological Research (VITO), Hasselt University, Hasselt University, Leuven University.
The microcirculation consists of blood vessels with diameters less than 150 µm. It makes up a large part of the circulatory system and plays an important role in maintaining cardiovascular health. The retina is a tissue that lines the interior of the eye and it is the only tissue that allows for a non-invasive analysis of the microvasculature. Nowadays, high-quality fundus images can be acquired using digital cameras. Retinal images can be collected in 5 min or less, even without dilatation of the pupils. This unobtrusive and fast procedure for visualizing the microcirculation is attractive to apply in epidemiological studies and to monitor cardiovascular health from early age up to old age. Systemic diseases that affect the circulation can result in progressive morphological changes in the retinal vasculature. For example, changes in the vessel calibers of retinal arteries and veins have been associated with hypertension, atherosclerosis, and increased risk of stroke and myocardial infarction. The vessel widths are derived using image analysis software and the width of the six largest arteries and veins are summarized in the Central Retinal Arteriolar Equivalent (CRAE) and the Central Retinal Venular Equivalent (CRVE). The latter features have been shown useful to study the impact of modifiable lifestyle and environmental cardiovascular disease risk factors. The procedures to acquire fundus images and the analysis steps to obtain CRAE and CRVE are described. Coefficients of variation of repeated measures of CRAE and CRVE are less than 2% and within-rater reliability is very high. Using a panel study, the rapid response of the retinal vessel calibers to short-term changes in particulate air pollution, a known risk factor for cardiovascular mortality and morbidity, is reported. In conclusion, retinal imaging is proposed as a convenient and instrumental tool for epidemiological studies to study microvascular responses to cardiovascular disease risk factors.
Medicine, Issue 92, retina, microvasculature, image analysis, Central Retinal Arteriolar Equivalent, Central Retinal Venular Equivalent, air pollution, particulate matter, black carbon
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Isolation and Functional Characterization of Human Ventricular Cardiomyocytes from Fresh Surgical Samples
Authors: Raffaele Coppini, Cecila Ferrantini, Alessandro Aiazzi, Luca Mazzoni, Laura Sartiani, Alessandro Mugelli, Corrado Poggesi, Elisabetta Cerbai.
Institutions: University of Florence, University of Florence.
Cardiomyocytes from diseased hearts are subjected to complex remodeling processes involving changes in cell structure, excitation contraction coupling and membrane ion currents. Those changes are likely to be responsible for the increased arrhythmogenic risk and the contractile alterations leading to systolic and diastolic dysfunction in cardiac patients. However, most information on the alterations of myocyte function in cardiac diseases has come from animal models. Here we describe and validate a protocol to isolate viable myocytes from small surgical samples of ventricular myocardium from patients undergoing cardiac surgery operations. The protocol is described in detail. Electrophysiological and intracellular calcium measurements are reported to demonstrate the feasibility of a number of single cell measurements in human ventricular cardiomyocytes obtained with this method. The protocol reported here can be useful for future investigations of the cellular and molecular basis of functional alterations of the human heart in the presence of different cardiac diseases. Further, this method can be used to identify novel therapeutic targets at cellular level and to test the effectiveness of new compounds on human cardiomyocytes, with direct translational value.
Medicine, Issue 86, cardiology, cardiac cells, electrophysiology, excitation-contraction coupling, action potential, calcium, myocardium, hypertrophic cardiomyopathy, cardiac patients, cardiac disease
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Assessment of Vascular Function in Patients With Chronic Kidney Disease
Authors: Kristen L. Jablonski, Emily Decker, Loni Perrenoud, Jessica Kendrick, Michel Chonchol, Douglas R. Seals, Diana Jalal.
Institutions: University of Colorado, Denver, University of Colorado, Boulder.
Patients with chronic kidney disease (CKD) have significantly increased risk of cardiovascular disease (CVD) compared to the general population, and this is only partially explained by traditional CVD risk factors. Vascular dysfunction is an important non-traditional risk factor, characterized by vascular endothelial dysfunction (most commonly assessed as impaired endothelium-dependent dilation [EDD]) and stiffening of the large elastic arteries. While various techniques exist to assess EDD and large elastic artery stiffness, the most commonly used are brachial artery flow-mediated dilation (FMDBA) and aortic pulse-wave velocity (aPWV), respectively. Both of these noninvasive measures of vascular dysfunction are independent predictors of future cardiovascular events in patients with and without kidney disease. Patients with CKD demonstrate both impaired FMDBA, and increased aPWV. While the exact mechanisms by which vascular dysfunction develops in CKD are incompletely understood, increased oxidative stress and a subsequent reduction in nitric oxide (NO) bioavailability are important contributors. Cellular changes in oxidative stress can be assessed by collecting vascular endothelial cells from the antecubital vein and measuring protein expression of markers of oxidative stress using immunofluorescence. We provide here a discussion of these methods to measure FMDBA, aPWV, and vascular endothelial cell protein expression.
Medicine, Issue 88, chronic kidney disease, endothelial cells, flow-mediated dilation, immunofluorescence, oxidative stress, pulse-wave velocity
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A Murine Model of Myocardial Ischemia-reperfusion Injury through Ligation of the Left Anterior Descending Artery
Authors: Zhaobin Xu, Jenna Alloush, Eric Beck, Noah Weisleder.
Institutions: The Ohio State University.
Acute or chronic myocardial infarction (MI) are cardiovascular events resulting in high morbidity and mortality. Establishing the pathological mechanisms at work during MI and developing effective therapeutic approaches requires methodology to reproducibly simulate the clinical incidence and reflect the pathophysiological changes associated with MI. Here, we describe a surgical method to induce MI in mouse models that can be used for short-term ischemia-reperfusion (I/R) injury as well as permanent ligation. The major advantage of this method is to facilitate location of the left anterior descending artery (LAD) to allow for accurate ligation of this artery to induce ischemia in the left ventricle of the mouse heart. Accurate positioning of the ligature on the LAD increases reproducibility of infarct size and thus produces more reliable results. Greater precision in placement of the ligature will improve the standard surgical approaches to simulate MI in mice, thus reducing the number of experimental animals necessary for statistically relevant studies and improving our understanding of the mechanisms producing cardiac dysfunction following MI. This mouse model of MI is also useful for the preclinical testing of treatments targeting myocardial damage following MI.
Medicine, Issue 86, Myocardial Ischemia/Reperfusion, permanent ligation, left anterior descending artery, myocardial infarction, LAD, ligation, Cardiac troponin I
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Protocol for Relative Hydrodynamic Assessment of Tri-leaflet Polymer Valves
Authors: Sharan Ramaswamy, Manuel Salinas, Rob Carrol, Karla Landaburo, Xavier Ryans, Cynthia Crespo, Ailyn Rivero, Faris Al-Mousily, Curt DeGroff, Mark Bleiweis, Hitomi Yamaguchi.
Institutions: Florida International University, University of Florida , University of Florida , Jeddah, Saudi Arabia.
Limitations of currently available prosthetic valves, xenografts, and homografts have prompted a recent resurgence of developments in the area of tri-leaflet polymer valve prostheses. However, identification of a protocol for initial assessment of polymer valve hydrodynamic functionality is paramount during the early stages of the design process. Traditional in vitro pulse duplicator systems are not configured to accommodate flexible tri-leaflet materials; in addition, assessment of polymer valve functionality needs to be made in a relative context to native and prosthetic heart valves under identical test conditions so that variability in measurements from different instruments can be avoided. Accordingly, we conducted hydrodynamic assessment of i) native (n = 4, mean diameter, D = 20 mm), ii) bi-leaflet mechanical (n= 2, D = 23 mm) and iii) polymer valves (n = 5, D = 22 mm) via the use of a commercially available pulse duplicator system (ViVitro Labs Inc, Victoria, BC) that was modified to accommodate tri-leaflet valve geometries. Tri-leaflet silicone valves developed at the University of Florida comprised the polymer valve group. A mixture in the ratio of 35:65 glycerin to water was used to mimic blood physical properties. Instantaneous flow rate was measured at the interface of the left ventricle and aortic units while pressure was recorded at the ventricular and aortic positions. Bi-leaflet and native valve data from the literature was used to validate flow and pressure readings. The following hydrodynamic metrics were reported: forward flow pressure drop, aortic root mean square forward flow rate, aortic closing, leakage and regurgitant volume, transaortic closing, leakage, and total energy losses. Representative results indicated that hydrodynamic metrics from the three valve groups could be successfully obtained by incorporating a custom-built assembly into a commercially available pulse duplicator system and subsequently, objectively compared to provide insights on functional aspects of polymer valve design.
Bioengineering, Issue 80, Cardiovascular Diseases, Circulatory and Respiratory Physiological Phenomena, Fluid Mechanics and Thermodynamics, Mechanical Engineering, valve disease, valve replacement, polymer valves, pulse duplicator, modification, tri-leaflet geometries, hydrodynamic studies, relative assessment, medicine, bioengineering, physiology
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A Novel Stretching Platform for Applications in Cell and Tissue Mechanobiology
Authors: Dominique Tremblay, Charles M. Cuerrier, Lukasz Andrzejewski, Edward R. O'Brien, Andrew E. Pelling.
Institutions: University of Ottawa, University of Ottawa, University of Calgary, University of Ottawa, University of Ottawa.
Tools that allow the application of mechanical forces to cells and tissues or that can quantify the mechanical properties of biological tissues have contributed dramatically to the understanding of basic mechanobiology. These techniques have been extensively used to demonstrate how the onset and progression of various diseases are heavily influenced by mechanical cues. This article presents a multi-functional biaxial stretching (BAXS) platform that can either mechanically stimulate single cells or quantify the mechanical stiffness of tissues. The BAXS platform consists of four voice coil motors that can be controlled independently. Single cells can be cultured on a flexible substrate that can be attached to the motors allowing one to expose the cells to complex, dynamic, and spatially varying strain fields. Conversely, by incorporating a force load cell, one can also quantify the mechanical properties of primary tissues as they are exposed to deformation cycles. In both cases, a proper set of clamps must be designed and mounted to the BAXS platform motors in order to firmly hold the flexible substrate or the tissue of interest. The BAXS platform can be mounted on an inverted microscope to perform simultaneous transmitted light and/or fluorescence imaging to examine the structural or biochemical response of the sample during stretching experiments. This article provides experimental details of the design and usage of the BAXS platform and presents results for single cell and whole tissue studies. The BAXS platform was used to measure the deformation of nuclei in single mouse myoblast cells in response to substrate strain and to measure the stiffness of isolated mouse aortas. The BAXS platform is a versatile tool that can be combined with various optical microscopies in order to provide novel mechanobiological insights at the sub-cellular, cellular and whole tissue levels.
Bioengineering, Issue 88, cell stretching, tissue mechanics, nuclear mechanics, uniaxial, biaxial, anisotropic, mechanobiology
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Isolation, Culture, and Functional Characterization of Adult Mouse Cardiomyoctyes
Authors: Evan Lee Graham, Cristina Balla, Hannabeth Franchino, Yonathan Melman, Federica del Monte, Saumya Das.
Institutions: Beth Israel Deaconess Medical Center, Harvard Medical School, Sapienza University.
The use of primary cardiomyocytes (CMs) in culture has provided a powerful complement to murine models of heart disease in advancing our understanding of heart disease. In particular, the ability to study ion homeostasis, ion channel function, cellular excitability and excitation-contraction coupling and their alterations in diseased conditions and by disease-causing mutations have led to significant insights into cardiac diseases. Furthermore, the lack of an adequate immortalized cell line to mimic adult CMs, and the limitations of neonatal CMs (which lack many of the structural and functional biomechanics characteristic of adult CMs) in culture have hampered our understanding of the complex interplay between signaling pathways, ion channels and contractile properties in the adult heart strengthening the importance of studying adult isolated cardiomyocytes. Here, we present methods for the isolation, culture, manipulation of gene expression by adenoviral-expressed proteins, and subsequent functional analysis of cardiomyocytes from the adult mouse. The use of these techniques will help to develop mechanistic insight into signaling pathways that regulate cellular excitability, Ca2+ dynamics and contractility and provide a much more physiologically relevant characterization of cardiovascular disease.
Cellular Biology, Issue 79, Medicine, Cardiology, Cellular Biology, Anatomy, Physiology, Mice, Ion Channels, Primary Cell Culture, Cardiac Electrophysiology, adult mouse cardiomyocytes, cell isolation, IonOptix, Cell Culture, adenoviral transfection, patch clamp, fluorescent nanosensor
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Psychophysiological Stress Assessment Using Biofeedback
Authors: Inna Khazan.
Institutions: Cambridge Health Alliance, Harvard Medical School.
In the last half century, research in biofeedback has shown the extent to which the human mind can influence the functioning of the autonomic nervous system, previously thought to be outside of conscious control. By letting people observe signals from their own bodies, biofeedback enables them to develop greater awareness of their physiological and psychological reactions, such as stress, and to learn to modify these reactions. Biofeedback practitioners can facilitate this process by assessing people s reactions to mildly stressful events and formulating a biofeedback-based treatment plan. During stress assessment the practitioner first records a baseline for physiological readings, and then presents the client with several mild stressors, such as a cognitive, physical and emotional stressor. Variety of stressors is presented in order to determine a person's stimulus-response specificity, or differences in each person's reaction to qualitatively different stimuli. This video will demonstrate the process of psychophysiological stress assessment using biofeedback and present general guidelines for treatment planning.
Neuroscience, Issue 29, Stress, biofeedback, psychophysiological, assessment
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Authors: Marc N. Coutanche, Sharon L. Thompson-Schill.
Institutions: University of Pennsylvania.
It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain activity, even for conditions with similar levels of univariate activation. Multi-voxel pattern (MVP) analysis has been used to decode this information with great success. FMRI investigators also often seek to understand how brain regions interact in interconnected networks, and use functional connectivity (FC) to identify regions that have correlated responses over time. Just as univariate analyses can be insensitive to information in MVPs, FC may not fully characterize the brain networks that process conditions with characteristic MVP signatures. The method described here, informational connectivity (IC), can identify regions with correlated changes in MVP-discriminability across time, revealing connectivity that is not accessible to FC. The method can be exploratory, using searchlights to identify seed-connected areas, or planned, between pre-selected regions-of-interest. The results can elucidate networks of regions that process MVP-related conditions, can breakdown MVPA searchlight maps into separate networks, or can be compared across tasks and patient groups.
Neuroscience, Issue 89, fMRI, MVPA, connectivity, informational connectivity, functional connectivity, networks, multi-voxel pattern analysis, decoding, classification, method, multivariate
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Measuring Ascending Aortic Stiffness In Vivo in Mice Using Ultrasound
Authors: Maggie M. Kuo, Viachaslau Barodka, Theodore P. Abraham, Jochen Steppan, Artin A. Shoukas, Mark Butlin, Alberto Avolio, Dan E. Berkowitz, Lakshmi Santhanam.
Institutions: Johns Hopkins University, Johns Hopkins University, Johns Hopkins University, Macquarie University.
We present a protocol for measuring in vivo aortic stiffness in mice using high-resolution ultrasound imaging. Aortic diameter is measured by ultrasound and aortic blood pressure is measured invasively with a solid-state pressure catheter. Blood pressure is raised then lowered incrementally by intravenous infusion of vasoactive drugs phenylephrine and sodium nitroprusside. Aortic diameter is measured for each pressure step to characterize the pressure-diameter relationship of the ascending aorta. Stiffness indices derived from the pressure-diameter relationship can be calculated from the data collected. Calculation of arterial compliance is described in this protocol. This technique can be used to investigate mechanisms underlying increased aortic stiffness associated with cardiovascular disease and aging. The technique produces a physiologically relevant measure of stiffness compared to ex vivo approaches because physiological influences on aortic stiffness are incorporated in the measurement. The primary limitation of this technique is the measurement error introduced from the movement of the aorta during the cardiac cycle. This motion can be compensated by adjusting the location of the probe with the aortic movement as well as making multiple measurements of the aortic pressure-diameter relationship and expanding the experimental group size.
Medicine, Issue 94, Aortic stiffness, ultrasound, in vivo, aortic compliance, elastic modulus, mouse model, cardiovascular disease
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Ultrasound Assessment of Endothelial-Dependent Flow-Mediated Vasodilation of the Brachial Artery in Clinical Research
Authors: Hugh Alley, Christopher D. Owens, Warren J. Gasper, S. Marlene Grenon.
Institutions: University of California, San Francisco, Veterans Affairs Medical Center, San Francisco, Veterans Affairs Medical Center, San Francisco.
The vascular endothelium is a monolayer of cells that cover the interior of blood vessels and provide both structural and functional roles. The endothelium acts as a barrier, preventing leukocyte adhesion and aggregation, as well as controlling permeability to plasma components. Functionally, the endothelium affects vessel tone. Endothelial dysfunction is an imbalance between the chemical species which regulate vessel tone, thombroresistance, cellular proliferation and mitosis. It is the first step in atherosclerosis and is associated with coronary artery disease, peripheral artery disease, heart failure, hypertension, and hyperlipidemia. The first demonstration of endothelial dysfunction involved direct infusion of acetylcholine and quantitative coronary angiography. Acetylcholine binds to muscarinic receptors on the endothelial cell surface, leading to an increase of intracellular calcium and increased nitric oxide (NO) production. In subjects with an intact endothelium, vasodilation was observed while subjects with endothelial damage experienced paradoxical vasoconstriction. There exists a non-invasive, in vivo method for measuring endothelial function in peripheral arteries using high-resolution B-mode ultrasound. The endothelial function of peripheral arteries is closely related to coronary artery function. This technique measures the percent diameter change in the brachial artery during a period of reactive hyperemia following limb ischemia. This technique, known as endothelium-dependent, flow-mediated vasodilation (FMD) has value in clinical research settings. However, a number of physiological and technical issues can affect the accuracy of the results and appropriate guidelines for the technique have been published. Despite the guidelines, FMD remains heavily operator dependent and presents a steep learning curve. This article presents a standardized method for measuring FMD in the brachial artery on the upper arm and offers suggestions to reduce intra-operator variability.
Medicine, Issue 92, endothelial function, endothelial dysfunction, brachial artery, peripheral artery disease, ultrasound, vascular, endothelium, cardiovascular disease.
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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
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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
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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
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
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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
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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
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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
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Cross-Modal Multivariate Pattern Analysis
Authors: Kaspar Meyer, Jonas T. Kaplan.
Institutions: University of Southern California.
Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5 or, analogously, the content of speech from activity in early auditory cortices6. Here, we present an extension of the classical MVPA paradigm, according to which perceptual stimuli are not predicted within, but across sensory systems. Specifically, the method we describe addresses the question of whether stimuli that evoke memory associations in modalities other than the one through which they are presented induce content-specific activity patterns in the sensory cortices of those other modalities. For instance, seeing a muted video clip of a glass vase shattering on the ground automatically triggers in most observers an auditory image of the associated sound; is the experience of this image in the "mind's ear" correlated with a specific neural activity pattern in early auditory cortices? Furthermore, is this activity pattern distinct from the pattern that could be observed if the subject were, instead, watching a video clip of a howling dog? In two previous studies7,8, we were able to predict sound- and touch-implying video clips based on neural activity in early auditory and somatosensory cortices, respectively. Our results are in line with a neuroarchitectural framework proposed by Damasio9,10, according to which the experience of mental images that are based on memories - such as hearing the shattering sound of a vase in the "mind's ear" upon seeing the corresponding video clip - is supported by the re-construction of content-specific neural activity patterns in early sensory cortices.
Neuroscience, Issue 57, perception, sensory, cross-modal, top-down, mental imagery, fMRI, MRI, neuroimaging, multivariate pattern analysis, MVPA
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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
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Methods for ECG Evaluation of Indicators of Cardiac Risk, and Susceptibility to Aconitine-induced Arrhythmias in Rats Following Status Epilepticus
Authors: Steven L. Bealer, Cameron S. Metcalf, Jason G. Little.
Institutions: University of Utah.
Lethal cardiac arrhythmias contribute to mortality in a number of pathological conditions. Several parameters obtained from a non-invasive, easily obtained electrocardiogram (ECG) are established, well-validated prognostic indicators of cardiac risk in patients suffering from a number of cardiomyopathies. Increased heart rate, decreased heart rate variability (HRV), and increased duration and variability of cardiac ventricular electrical activity (QT interval) are all indicative of enhanced cardiac risk 1-4. In animal models, it is valuable to compare these ECG-derived variables and susceptibility to experimentally induced arrhythmias. Intravenous infusion of the arrhythmogenic agent aconitine has been widely used to evaluate susceptibility to arrhythmias in a range of experimental conditions, including animal models of depression 5 and hypertension 6, following exercise 7 and exposure to air pollutants 8, as well as determination of the antiarrhythmic efficacy of pharmacological agents 9,10. It should be noted that QT dispersion in humans is a measure of QT interval variation across the full set of leads from a standard 12-lead ECG. Consequently, the measure of QT dispersion from the 2-lead ECG in the rat described in this protocol is different than that calculated from human ECG records. This represents a limitation in the translation of the data obtained from rodents to human clinical medicine. Status epilepticus (SE) is a single seizure or series of continuously recurring seizures lasting more than 30 min 11,12 11,12, and results in mortality in 20% of cases 13. Many individuals survive the SE, but die within 30 days 14,15. The mechanism(s) of this delayed mortality is not fully understood. It has been suggested that lethal ventricular arrhythmias contribute to many of these deaths 14-17. In addition to SE, patients experiencing spontaneously recurring seizures, i.e. epilepsy, are at risk of premature sudden and unexpected death associated with epilepsy (SUDEP) 18. As with SE, the precise mechanisms mediating SUDEP are not known. It has been proposed that ventricular abnormalities and resulting arrhythmias make a significant contribution 18-22. To investigate the mechanisms of seizure-related cardiac death, and the efficacy of cardioprotective therapies, it is necessary to obtain both ECG-derived indicators of risk and evaluate susceptibility to cardiac arrhythmias in animal models of seizure disorders 23-25. Here we describe methods for implanting ECG electrodes in the Sprague-Dawley laboratory rat (Rattus norvegicus), following SE, collection and analysis of ECG recordings, and induction of arrhythmias during iv infusion of aconitine. These procedures can be used to directly determine the relationships between ECG-derived measures of cardiac electrical activity and susceptibility to ventricular arrhythmias in rat models of seizure disorders, or any pathology associated with increased risk of sudden cardiac death.
Medicine, Issue 50, cardiac, seizure disorders, QTc, QTd, cardiac arrhythmias, rat
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.