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Pubmed Article
The role of surgery in global health: analysis of United States inpatient procedure frequency by condition using the Global Burden of Disease 2010 framework.
PUBLISHED: 01-01-2014
The role of surgical care in promoting global health is the subject of much debate. The Global Burden of Disease 2010 study (GBD 2010) offers a new opportunity to consider where surgery fits amongst global health priorities. The GBD 2010 reinforces the DALY as the preferred methodology for determining the relative contribution of disease categories to overall global burden of disease without reference to the likelihood of each category requiring surgery. As such, we hypothesize that the GBD framework underestimates the role of surgery in addressing the global burden of disease.
Authors: Lee-Hwa Tai, Christiano Tanese de Souza, Shalini Sahi, Jiqing Zhang, Almohanad A Alkayyal, Abhirami Anu Ananth, Rebecca A.C. Auer.
Published: 03-12-2014
Surgical resection is an essential treatment for most cancer patients, but surgery induces dysfunction in the immune system and this has been linked to the development of metastatic disease in animal models and in cancer patients. Preclinical work from our group and others has demonstrated a profound suppression of innate immune function, specifically NK cells in the postoperative period and this plays a major role in the enhanced development of metastases following surgery. Relatively few animal studies and clinical trials have focused on characterizing and reversing the detrimental effects of cancer surgery. Using a rigorous animal model of spontaneously metastasizing tumors and surgical stress, the enhancement of cancer surgery on the development of lung metastases was demonstrated. In this model, 4T1 breast cancer cells are implanted in the mouse mammary fat pad. At day 14 post tumor implantation, a complete resection of the primary mammary tumor is performed in all animals. A subset of animals receives additional surgical stress in the form of an abdominal nephrectomy. At day 28, lung tumor nodules are quantified. When immunotherapy was given immediately preoperatively, a profound activation of immune cells which prevented the development of metastases following surgery was detected. While the 4T1 breast tumor surgery model allows for the simulation of the effects of abdominal surgical stress on tumor metastases, its applicability to other tumor types needs to be tested. The current challenge is to identify safe and promising immunotherapies in preclinical mouse models and to translate them into viable perioperative therapies to be given to cancer surgery patients to prevent the recurrence of metastatic disease.
23 Related JoVE Articles!
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A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
Authors: Antonio G. Zippo, Sara Nencini, Gian Carlo Caramenti, Maurizio Valente, Riccardo Storchi, Gabriele E.M. Biella.
Institutions: National Research Council, National Research Council, University of Manchester.
Current neurophysiological research has the aim to develop methodologies to investigate the signal route from neuron to neuron, namely in the transitions from spikes to Local Field Potentials (LFPs) and from LFPs to spikes. LFPs have a complex dependence on spike activity and their relation is still poorly understood1. The elucidation of these signal relations would be helpful both for clinical diagnostics (e.g. stimulation paradigms for Deep Brain Stimulation) and for a deeper comprehension of neural coding strategies in normal and pathological conditions (e.g. epilepsy, Parkinson disease, chronic pain). To this aim, one has to solve technical issues related to stimulation devices, stimulation paradigms and computational analyses. Therefore, a custom-made stimulation device was developed in order to deliver stimuli well regulated in space and time that does not incur in mechanical resonance. Subsequently, as an exemplification, a set of reliable LFP-spike relationships was extracted. The performance of the device was investigated by extracellular recordings, jointly spikes and LFP responses to the applied stimuli, from the rat Primary Somatosensory cortex. Then, by means of a multi-objective optimization strategy, a predictive model for spike occurrence based on LFPs was estimated. The application of this paradigm shows that the device is adequately suited to deliver high frequency tactile stimulation, outperforming common piezoelectric actuators. As a proof of the efficacy of the device, the following results were presented: 1) the timing and reliability of LFP responses well match the spike responses, 2) LFPs are sensitive to the stimulation history and capture not only the average response but also the trial-to-trial fluctuations in the spike activity and, finally, 3) by using the LFP signal it is possible to estimate a range of predictive models that capture different aspects of the spike activity.
Neuroscience, Issue 85, LFP, spike, tactile stimulus, Multiobjective function, Neuron, somatosensory cortex
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Determining Soil-transmitted Helminth Infection Status and Physical Fitness of School-aged Children
Authors: Peiling Yap, Thomas Fürst, Ivan Müller, Susi Kriemler, Jürg Utzinger, Peter Steinmann.
Institutions: Swiss Tropical and Public Health Institute, Basel, Switzerland, University of Basel, Basel, Switzerland.
Soil-transmitted helminth (STH) infections are common. Indeed, more than 1 billion people are affected, mainly in the developing world where poverty prevails and hygiene behavior, water supply, and sanitation are often deficient1,2. Ascaris lumbricoides, Trichuris trichiura, and the two hookworm species, Ancylostoma duodenale and Necator americanus, are the most prevalent STHs3. The estimated global burden due to hookworm disease, ascariasis, and trichuriasis is 22.1, 10.5, and 6.4 million disability-adjusted life years (DALYs), respectively4. Furthermore, an estimated 30-100 million people are infected with Strongyloides stercoralis, the most neglected STH species of global significance which arguably also causes a considerable public health impact5,6. Multiple-species infections (i.e., different STHs harbored in a single individual) are common, and infections have been linked to lowered productivity and thus economic outlook of developing countries1,3. For the diagnosis of common STHs, the World Health Organization (WHO) recommends the Kato-Katz technique7,8, which is a relatively straightforward method for determining the prevalence and intensity of such infections. It facilitates the detection of parasite eggs that infected subjects pass in their feces. With regard to the diagnosis of S.stercoralis, there is currently no simple and accurate tool available. The Baermann technique is the most widely employed method for its diagnosis. The principle behind the Baermann technique is that active S.stercoralis larvae migrate out of an illuminated fresh fecal sample as the larvae are phototactic9. It requires less sophisticated laboratory materials and is less time consuming than culture and immunological methods5. Morbidities associated with STH infections range from acute but common symptoms, such as abdominal pain, diarrhea, and pruritus, to chronic symptoms, such as anemia, under- and malnutrition, and cognitive impairment10. Since the symptoms are generally unspecific and subtle, they often go unnoticed, are considered a normal condition by affected individuals, or are treated as symptoms of other diseases that might be more common in a given setting. Hence, it is conceivable that the true burden of STH infections is underestimated by assessment tools relying on self-declared signs and symptoms as is usually the case in population-based surveys. In the late 1980s and early 1990s, Stephenson and colleagues highlighted the possibility of STH infections lowering the physical fitness of boys aged 6-12 years11,12. This line of scientific inquiry gained new momentum recently13,14,15. The 20-meter (m) shuttle run test was developed and validated by Léger et al.16 and is used worldwide to measure the aerobic fitness of children17. The test is easy to standardize and can be performed wherever a 20-m long and flat running course and an audio source are available, making its use attractive in resource-constrained settings13. To facilitate and standardize attempts at assessing whether STH infections have an effect on the physical fitness of school-aged children, we present methodologies that diagnose STH infections or measure physical fitness that are simple to execute and yet, provide accurate and reproducible outcomes. This will help to generate new evidence regarding the health impact of STH infections.
Infection, Issue 66, Immunology, Medicine, Infectious Diseases, Soil-transmitted helminths, physical fitness, Kato-Katz technique, Baermann technique, 20-meter shuttle run test, children
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Intra-Operative Behavioral Tasks in Awake Humans Undergoing Deep Brain Stimulation Surgery
Authors: John T. Gale, Clarissa Martinez-Rubio, Sameer A. Sheth, Emad N. Eskandar.
Institutions: Harvard Medical School, Massachusetts General Hospital.
Deep brain stimulation (DBS) is a surgical procedure that directs chronic, high frequency electrical stimulation to specific targets in the brain through implanted electrodes. Deep brain stimulation was first implemented as a therapeutic modality by Benabid et al. in the late 1980s, when he used this technique to stimulate the ventral intermediate nucleus of the thalamus for the treatment of tremor 1. Currently, the procedure is used to treat patients who fail to respond adequately to medical management for diseases such as Parkinson's, dystonia, and essential tremor. The efficacy of this procedure for the treatment of Parkinson's disease has been demonstrated in well-powered, randomized controlled trials 2. Presently, the U.S. Food and Drug Administration has approved DBS as a treatment for patients with medically refractory essential tremor, Parkinson's disease, and dystonia. Additionally, DBS is currently being evaluated for the treatment of other psychiatric and neurological disorders, such as obsessive compulsive disorder, major depressive disorder, and epilepsy. DBS has not only been shown to help people by improving their quality of life, it also provides researchers with the unique opportunity to study and understand the human brain. Microelectrode recordings are routinely performed during DBS surgery in order to enhance the precision of anatomical targeting. Firing patterns of individual neurons can therefore be recorded while the subject performs a behavioral task. Early studies using these data focused on descriptive aspects, including firing and burst rates, and frequency modulation 3. More recent studies have focused on cognitive aspects of behavior in relation to neuronal activity 4,5. This article will provide a description of the intra-operative methods used to perform behavioral tasks and record neuronal data with awake patients during DBS cases. Our exposition of the process of acquiring electrophysiological data will illuminate the current scope and limitations of intra-operative human experiments.
Medicine, Issue 47, Intra-Operative Physiology, Cognitive Neuroscience, Behavioral Neuroscience, Subthalamic Nucleus, Single-Unit Activity, Parkinson Disease, Deep Brain Stimulation
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Capsular Serotyping of Streptococcus pneumoniae Using the Quellung Reaction
Authors: Maha Habib, Barbara D. Porter, Catherine Satzke.
Institutions: Murdoch Childrens Research Institute, The University of Melbourne.
There are over 90 different capsular serotypes of Streptococcus pneumoniae (the pneumococcus). As well as being a tool for understanding pneumococcal epidemiology, capsular serotyping can provide useful information for vaccine efficacy and impact studies. The Quellung reaction is the gold standard method for pneumococcal capsular serotyping. The method involves testing a pneumococcal cell suspension with pooled and specific antisera directed against the capsular polysaccharide. The antigen-antibody reactions are observed microscopically. The protocol has three main steps: 1) preparation of a bacterial cell suspension, 2) mixing of cells and antisera on a glass slide, and 3) reading the Quellung reaction using a microscope. The Quellung reaction is reasonably simple to perform and can be applied wherever a suitable microscope and antisera are available.
Immunology, Issue 84, Streptococcus pneumoniae, Quellung, serotyping, Neufeld, pneumococcus
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Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation
Authors: Amanda K. Rizk, Rima Wardini, Emilie Chan-Thim, Barbara Trutschnigg, Amélie Forget, Véronique Pepin.
Institutions: Concordia University, Concordia University, Hôpital du Sacré-Coeur de Montréal.
Pulmonary rehabilitation (PR) is an important component in the management of respiratory diseases. The effectiveness of PR is dependent upon adherence to exercise training recommendations. The study of exercise adherence is thus a key step towards the optimization of PR programs. To date, mostly indirect measures, such as rates of participation, completion, and attendance, have been used to determine adherence to PR. The purpose of the present protocol is to describe how continuous data tracking technology can be used to measure adherence to a prescribed aerobic training intensity on a second-by-second basis. In our investigations, adherence has been defined as the percent time spent within a specified target heart rate range. As such, using a combination of hardware and software, heart rate is measured, tracked, and recorded during cycling second-by-second for each participant, for each exercise session. Using statistical software, the data is subsequently extracted and analyzed. The same protocol can be applied to determine adherence to other measures of exercise intensity, such as time spent at a specified wattage, level, or speed on the cycle ergometer. Furthermore, the hardware and software is also available to measure adherence to other modes of training, such as the treadmill, elliptical, stepper, and arm ergometer. The present protocol, therefore, has a vast applicability to directly measure adherence to aerobic exercise.
Medicine, Issue 81, Data tracking, exercise, rehabilitation, adherence, patient compliance, health behavior, user-computer interface.
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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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Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale
Authors: Valentina Gandin, Kristina Sikström, Tommy Alain, Masahiro Morita, Shannon McLaughlan, Ola Larsson, Ivan Topisirovic.
Institutions: McGill University, Karolinska Institutet, McGill University.
mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. Accordingly, dysregulation of mRNA translation is considered to play a major role in a variety of pathological states including cancer. Ribosomes also host chaperones, which facilitate folding of nascent polypeptides, thereby modulating function and stability of newly synthesized polypeptides. In addition, emerging data indicate that ribosomes serve as a platform for a repertoire of signaling molecules, which are implicated in a variety of post-translational modifications of newly synthesized polypeptides as they emerge from the ribosome, and/or components of translational machinery. Herein, a well-established method of ribosome fractionation using sucrose density gradient centrifugation is described. In conjunction with the in-house developed “anota” algorithm this method allows direct determination of differential translation of individual mRNAs on a genome-wide scale. Moreover, this versatile protocol can be used for a variety of biochemical studies aiming to dissect the function of ribosome-associated protein complexes, including those that play a central role in folding and degradation of newly synthesized polypeptides.
Biochemistry, Issue 87, Cells, Eukaryota, Nutritional and Metabolic Diseases, Neoplasms, Metabolic Phenomena, Cell Physiological Phenomena, mRNA translation, ribosomes, protein synthesis, genome-wide analysis, translatome, mTOR, eIF4E, 4E-BP1
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Simultaneous Scalp Electroencephalography (EEG), Electromyography (EMG), and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
Authors: Thomas C. Bulea, Atilla Kilicarslan, Recep Ozdemir, William H. Paloski, Jose L. Contreras-Vidal.
Institutions: National Institutes of Health, University of Houston, University of Houston, University of Houston, University of Houston.
Recent studies support the involvement of supraspinal networks in control of bipedal human walking. Part of this evidence encompasses studies, including our previous work, demonstrating that gait kinematics and limb coordination during treadmill walking can be inferred from the scalp electroencephalogram (EEG) with reasonably high decoding accuracies. These results provide impetus for development of non-invasive brain-machine-interface (BMI) systems for use in restoration and/or augmentation of gait- a primary goal of rehabilitation research. To date, studies examining EEG decoding of activity during gait have been limited to treadmill walking in a controlled environment. However, to be practically viable a BMI system must be applicable for use in everyday locomotor tasks such as over ground walking and turning. Here, we present a novel protocol for non-invasive collection of brain activity (EEG), muscle activity (electromyography (EMG)), and whole-body kinematic data (head, torso, and limb trajectories) during both treadmill and over ground walking tasks. By collecting these data in the uncontrolled environment insight can be gained regarding the feasibility of decoding unconstrained gait and surface EMG from scalp EEG.
Behavior, Issue 77, Neuroscience, Neurobiology, Medicine, Anatomy, Physiology, Biomedical Engineering, Molecular Biology, Electroencephalography, EEG, Electromyography, EMG, electroencephalograph, gait, brain-computer interface, brain machine interface, neural decoding, over-ground walking, robotic gait, brain, imaging, clinical techniques
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Quantification of Atherosclerotic Plaque Activity and Vascular Inflammation using [18-F] Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT)
Authors: Nehal N. Mehta, Drew A. Torigian, Joel M. Gelfand, Babak Saboury, Abass Alavi.
Institutions: University of Pennsylvania, Perelman School of Medicine, University of Pennsylvania, Perelman School of Medicine, University of Pennsylvania, Perelman School of Medicine.
Conventional non-invasive imaging modalities of atherosclerosis such as coronary artery calcium (CAC)1 and carotid intimal medial thickness (C-IMT)2 provide information about the burden of disease. However, despite multiple validation studies of CAC3-5, and C-IMT2,6, these modalities do not accurately assess plaque characteristics7,8, and the composition and inflammatory state of the plaque determine its stability and, therefore, the risk of clinical events9-13. [18F]-2-fluoro-2-deoxy-D-glucose (FDG) imaging using positron-emission tomography (PET)/computed tomography (CT) has been extensively studied in oncologic metabolism14,15. Studies using animal models and immunohistochemistry in humans show that FDG-PET/CT is exquisitely sensitive for detecting macrophage activity16, an important source of cellular inflammation in vessel walls. More recently, we17,18 and others have shown that FDG-PET/CT enables highly precise, novel measurements of inflammatory activity of activity of atherosclerotic plaques in large and medium-sized arteries9,16,19,20. FDG-PET/CT studies have many advantages over other imaging modalities: 1) high contrast resolution; 2) quantification of plaque volume and metabolic activity allowing for multi-modal atherosclerotic plaque quantification; 3) dynamic, real-time, in vivo imaging; 4) minimal operator dependence. Finally, vascular inflammation detected by FDG-PET/CT has been shown to predict cardiovascular (CV) events independent of traditional risk factors21,22 and is also highly associated with overall burden of atherosclerosis23. Plaque activity by FDG-PET/CT is modulated by known beneficial CV interventions such as short term (12 week) statin therapy24 as well as longer term therapeutic lifestyle changes (16 months)25. The current methodology for quantification of FDG uptake in atherosclerotic plaque involves measurement of the standardized uptake value (SUV) of an artery of interest and of the venous blood pool in order to calculate a target to background ratio (TBR), which is calculated by dividing the arterial SUV by the venous blood pool SUV. This method has shown to represent a stable, reproducible phenotype over time, has a high sensitivity for detection of vascular inflammation, and also has high inter-and intra-reader reliability26. Here we present our methodology for patient preparation, image acquisition, and quantification of atherosclerotic plaque activity and vascular inflammation using SUV, TBR, and a global parameter called the metabolic volumetric product (MVP). These approaches may be applied to assess vascular inflammation in various study samples of interest in a consistent fashion as we have shown in several prior publications.9,20,27,28
Medicine, Issue 63, FDG-PET/CT, atherosclerosis, vascular inflammation, quantitative radiology, imaging
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2-Vessel Occlusion/Hypotension: A Rat Model of Global Brain Ischemia
Authors: Thomas H. Sanderson, Joseph M. Wider.
Institutions: Wayne State University School of Medicine, Wayne State University School of Medicine, Wayne State University School of Medicine.
Cardiac arrest followed by resuscitation often results in dramatic brain damage caused by ischemia and subsequent reperfusion of the brain. Global brain ischemia produces damage to specific brain regions shown to be highly sensitive to ischemia 1. Hippocampal neurons have higher sensitivity to ischemic insults compared to other cell populations, and specifically, the CA1 region of the hippocampus is particularly vulnerable to ischemia/reperfusion 2. The design of therapeutic interventions, or study of mechanisms involved in cerebral damage, requires a model that produces damage similar to the clinical condition and in a reproducible manner. Bilateral carotid vessel occlusion with hypotension (2VOH) is a model that produces reversible forebrain ischemia, emulating the cerebral events that can occur during cardiac arrest and resuscitation. We describe a model modified from Smith et al. (1984) 2, as first presented in its current form in Sanderson, et al. (2008) 3, which produces reproducible injury to selectively vulnerable brain regions 3-6. The reliability of this model is dictated by precise control of systemic blood pressure during applied hypotension, the duration of ischemia, close temperature control, a specific anesthesia regimen, and diligent post-operative care. An 8-minute ischemic insult produces cell death of CA1 hippocampal neurons that progresses over the course of 6 to 24 hr of reperfusion, while less vulnerable brain regions are spared. This progressive cell death is easily quantified after 7-14 days of reperfusion, as a near complete loss of CA1 neurons is evident at this time. In addition to this brain injury model, we present a method for CA1 damage quantification using a simple, yet thorough, methodology. Importantly, quantification can be accomplished using a simple camera-mounted microscope, and a free ImageJ (NIH) software plugin, obviating the need for cost-prohibitive stereology software programs and a motorized microscopic stage for damage assessment.
Medicine, Issue 76, Biomedical Engineering, Neurobiology, Neuroscience, Immunology, Anatomy, Physiology, Cardiology, Brain Ischemia, ischemia, reperfusion, cardiac arrest, resuscitation, 2VOH, brain injury model, CA1 hippocampal neurons, brain, neuron, blood vessel, occlusion, hypotension, animal model
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Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Authors: Natalia J. Sumi, Eydis Lima, John Pizzonia, Sean P. Orton, Vinicius Craveiro, Wonduk Joo, Jennie C. Holmberg, Marta Gurrea, Yang Yang-Hartwich, Ayesha Alvero, Gil Mor.
Institutions: Yale University School of Medicine, NatureMost Laboratories, Bruker Preclinical Imaging.
Epithelial ovarian cancer is the most lethal gynecologic malignancy in the United States. Although patients initially respond to the current standard of care consisting of surgical debulking and combination chemotherapy consisting of platinum and taxane compounds, almost 90% of patients recur within a few years. In these patients the development of chemoresistant disease limits the efficacy of currently available chemotherapy agents and therefore contributes to the high mortality. To discover novel therapy options that can target recurrent disease, appropriate animal models that closely mimic the clinical profile of patients with recurrent ovarian cancer are required. The challenge in monitoring intra-peritoneal (i.p.) disease limits the use of i.p. models and thus most xenografts are established subcutaneously. We have developed a sensitive optical imaging platform that allows the detection and anatomical location of i.p. tumor mass. The platform includes the use of optical reporters that extend from the visible light range to near infrared, which in combination with 2-dimensional X-ray co-registration can provide anatomical location of molecular signals. Detection is significantly improved by the use of a rotation system that drives the animal to multiple angular positions for 360 degree imaging, allowing the identification of tumors that are not visible in single orientation. This platform provides a unique model to non-invasively monitor tumor growth and evaluate the efficacy of new therapies for the prevention or treatment of recurrent ovarian cancer.
Cancer Biology, Issue 93, ovarian cancer, recurrence, in vivo imaging, tumor burden, cancer stem cells, chemotherapy
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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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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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Combined In vivo Optical and µCT Imaging to Monitor Infection, Inflammation, and Bone Anatomy in an Orthopaedic Implant Infection in Mice
Authors: Nicholas M. Bernthal, Brad N. Taylor, Jeffrey A. Meganck, Yu Wang, Jonathan H. Shahbazian, Jared A. Niska, Kevin P. Francis, Lloyd S. Miller.
Institutions: David Geffen School of Medicine at University of California, Los Angeles (UCLA), PerkinElmer, Johns Hopkins University School of Medicine, Johns Hopkins University School of Medicine.
Multimodality imaging has emerged as a common technological approach used in both preclinical and clinical research. Advanced techniques that combine in vivo optical and μCT imaging allow the visualization of biological phenomena in an anatomical context. These imaging modalities may be especially useful to study conditions that impact bone. In particular, orthopaedic implant infections are an important problem in clinical orthopaedic surgery. These infections are difficult to treat because bacterial biofilms form on the foreign surgically implanted materials, leading to persistent inflammation, osteomyelitis and eventual osteolysis of the bone surrounding the implant, which ultimately results in implant loosening and failure. Here, a mouse model of an infected orthopaedic prosthetic implant was used that involved the surgical placement of a Kirschner-wire implant into an intramedullary canal in the femur in such a way that the end of the implant extended into the knee joint. In this model, LysEGFP mice, a mouse strain that has EGFP-fluorescent neutrophils, were employed in conjunction with a bioluminescent Staphylococcus aureus strain, which naturally emits light. The bacteria were inoculated into the knee joints of the mice prior to closing the surgical site. In vivo bioluminescent and fluorescent imaging was used to quantify the bacterial burden and neutrophil inflammatory response, respectively. In addition, μCT imaging was performed on the same mice so that the 3D location of the bioluminescent and fluorescent optical signals could be co-registered with the anatomical μCT images. To quantify the changes in the bone over time, the outer bone volume of the distal femurs were measured at specific time points using a semi-automated contour based segmentation process. Taken together, the combination of in vivo bioluminescent/fluorescent imaging with μCT imaging may be especially useful for the noninvasive monitoring of the infection, inflammatory response and anatomical changes in bone over time.
Infection, Issue 92, imaging, optical, CT, bioluminescence, fluorescence, staphylococcus, infection, inflammation, bone, orthopaedic, implant, biofilm
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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Authors: Joel Ramirez, Christopher J.M. Scott, Alicia A. McNeely, Courtney Berezuk, Fuqiang Gao, Gregory M. Szilagyi, Sandra E. Black.
Institutions: Sunnybrook Health Sciences Centre, University of Toronto.
Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g. Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs. LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors. While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.
Medicine, Issue 86, Brain, Vascular Diseases, Magnetic Resonance Imaging (MRI), Neuroimaging, Alzheimer Disease, Aging, Neuroanatomy, brain extraction, ventricles, white matter hyperintensities, cerebrovascular disease, Alzheimer disease
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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 (, 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
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
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A Mouse Model for Pathogen-induced Chronic Inflammation at Local and Systemic Sites
Authors: George Papadopoulos, Carolyn D. Kramer, Connie S. Slocum, Ellen O. Weinberg, Ning Hua, Cynthia V. Gudino, James A. Hamilton, Caroline A. Genco.
Institutions: Boston University School of Medicine, Boston University School of Medicine.
Chronic inflammation is a major driver of pathological tissue damage and a unifying characteristic of many chronic diseases in humans including neoplastic, autoimmune, and chronic inflammatory diseases. Emerging evidence implicates pathogen-induced chronic inflammation in the development and progression of chronic diseases with a wide variety of clinical manifestations. Due to the complex and multifactorial etiology of chronic disease, designing experiments for proof of causality and the establishment of mechanistic links is nearly impossible in humans. An advantage of using animal models is that both genetic and environmental factors that may influence the course of a particular disease can be controlled. Thus, designing relevant animal models of infection represents a key step in identifying host and pathogen specific mechanisms that contribute to chronic inflammation. Here we describe a mouse model of pathogen-induced chronic inflammation at local and systemic sites following infection with the oral pathogen Porphyromonas gingivalis, a bacterium closely associated with human periodontal disease. Oral infection of specific-pathogen free mice induces a local inflammatory response resulting in destruction of tooth supporting alveolar bone, a hallmark of periodontal disease. In an established mouse model of atherosclerosis, infection with P. gingivalis accelerates inflammatory plaque deposition within the aortic sinus and innominate artery, accompanied by activation of the vascular endothelium, an increased immune cell infiltrate, and elevated expression of inflammatory mediators within lesions. We detail methodologies for the assessment of inflammation at local and systemic sites. The use of transgenic mice and defined bacterial mutants makes this model particularly suitable for identifying both host and microbial factors involved in the initiation, progression, and outcome of disease. Additionally, the model can be used to screen for novel therapeutic strategies, including vaccination and pharmacological intervention.
Immunology, Issue 90, Pathogen-Induced Chronic Inflammation; Porphyromonas gingivalis; Oral Bone Loss; Periodontal Disease; Atherosclerosis; Chronic Inflammation; Host-Pathogen Interaction; microCT; MRI
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Investigating the Immunological Mechanisms Underlying Organ Transplant Rejection
Authors: Sang Mo Kang.
Institutions: University of California, San Francisco - UCSF.
Issue 7, Immunology, Heterotopic Heart Transplant, Small Bowel Transplant, Transplant Rejection, T regs, Diabetes, Autoimmune Disease, Translational Research
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Principles of Rodent Surgery for the New Surgeon
Authors: Kathleen R. Pritchett-Corning, Guy B. Mulder, Yiying Luo, William J. White.
Institutions: Research Models and Services.
For both scientific and animal welfare reasons, training in basic surgical concepts and techniques should be undertaken before ever seeking to perform surgery on a rodent. Students, post-doctoral scholars, and others interested in performing surgery on rodents as part of a research protocol may not have had formal surgical training as part of their required coursework. Surgery itself is a technical skill, and one that will improve with practice. The principles of aseptic technique, however, often remain unexplained or untaught. For most new surgeons, this vital information is presented in piecemeal fashion or learned on the job, neither of which is ideal. It may also make learning how to perform a particular surgery difficult, as the new surgeon is learning both a surgical technique and the principles of asepsis at the same time. This article summarizes and makes recommendations for basic surgical skills and techniques necessary for successful rodent surgery. This article is designed to supplement hands-on training by the user's institution.
Basic Protocols, Issue 47, Surgery, aseptic technique, rodent, training, rat, mouse,
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Collecting And Measuring Wound Exudate Biochemical Mediators In Surgical Wounds
Authors: Brendan Carvalho, David J Clark, David Yeomans, Martin S Angst.
Institutions: Stanford University School of Medicine .
We describe a methodology by which we are able to collect and measure biochemical inflammatory and nociceptive mediators at the surgical wound site. Collecting site-specific biochemical markers is important to understand the relationship between levels in serum and surgical wound, determine any associations between mediator release, pain, analgesic use and other outcomes of interest, and evaluate the effect of systemic and peripheral drug administration on surgical wound biochemistry. This methodology has been applied to healthy women undergoing elective cesarean delivery with spinal anesthesia. We have measured wound exudate and serum mediators at the same time intervals as patient's pain scores and analgesics consumption for up to 48 hours post-cesarean delivery. Using this methodology we have been able to detect various biochemical mediators including nerve growth factor (NGF), prostaglandin E2 (PG-E2) substance P, IL-1β, IL-2, IL-4, IL-6, IL-7, IL-8, IL-10, IL-12, IL-13, IL-17, TNFα, INFγ, G-CSF, GM-CSF, MCP-1 and MIP-1β. Studies applying this human surgical wound bioassay have found no correlations between wound and serum cytokine concentrations or their time-release profile (J Pain. 2008; 9(7):650-7).1 We also documented the utility of the technique to identify drug-mediated changes in wound cytokine content (Anesth Analg 2010; 111:1452-9).2
Medicine, Issue 68, Biochemistry, Anatomy, Physiology, Cytokines, Cesarean Section, Wound Healing, Wounds and Injuries, Surgical Procedures, Operative, Surgical wound, Exudate, cytokines, Substance P, Interleukin 10, Interleukin 6, Nerve growth factor, Prostaglandin E2, Cesarean, Analgesia
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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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Microsurgical Clip Obliteration of Middle Cerebral Aneurysm Using Intraoperative Flow Assessment
Authors: Bob S. Carter, Christopher Farrell, Christopher Owen.
Institutions: Havard Medical School, Massachusetts General Hospital.
Cerebral aneurysms are abnormal widening or ballooning of a localized segment of an intracranial blood vessel. Surgical clipping is an important treatment for aneurysms which attempts to exclude blood from flowing into the aneurysmal segment of the vessel while preserving blood flow in a normal fashion. Improper clip placement may result in residual aneurysm with the potential for subsequent aneurysm rupture or partial or full occlusion of distal arteries resulting in cerebral infarction. Here we describe the use of an ultrasonic flow probe to provide quantitative evaluation of arterial flow before and after microsurgical clip placement at the base of a middle cerebral artery aneurysm. This information helps ensure adequate aneurysm reconstruction with preservation of normal distal blood flow.
Medicine, Issue 31, Aneurysm, intraoperative, brain, surgery, surgical clipping, blood flow, aneurysmal segment, ultrasonic flow probe
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

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.