Efforts to detect and investigate key oncogenic mutations have proven valuable to facilitate the appropriate treatment for cancer patients. The establishment of high-throughput, massively parallel "next-generation" sequencing has aided the discovery of many such mutations. To enhance the clinical and translational utility of this technology, platforms must be high-throughput, cost-effective, and compatible with formalin-fixed paraffin embedded (FFPE) tissue samples that may yield small amounts of degraded or damaged DNA. Here, we describe the preparation of barcoded and multiplexed DNA libraries followed by hybridization-based capture of targeted exons for the detection of cancer-associated mutations in fresh frozen and FFPE tumors by massively parallel sequencing. This method enables the identification of sequence mutations, copy number alterations, and select structural rearrangements involving all targeted genes. Targeted exon sequencing offers the benefits of high throughput, low cost, and deep sequence coverage, thus conferring high sensitivity for detecting low frequency mutations.
24 Related JoVE Articles!
Physical, Chemical and Biological Characterization of Six Biochars Produced for the Remediation of Contaminated Sites
Institutions: Royal Military College of Canada, Queen's University.
The physical and chemical properties of biochar vary based on feedstock sources and production conditions, making it possible to engineer biochars with specific functions (e.g.
carbon sequestration, soil quality improvements, or contaminant sorption). In 2013, the International Biochar Initiative (IBI) made publically available their Standardized Product Definition and Product Testing Guidelines (Version 1.1) which set standards for physical and chemical characteristics for biochar. Six biochars made from three different feedstocks and at two temperatures were analyzed for characteristics related to their use as a soil amendment. The protocol describes analyses of the feedstocks and biochars and includes: cation exchange capacity (CEC), specific surface area (SSA), organic carbon (OC) and moisture percentage, pH, particle size distribution, and proximate and ultimate analysis. Also described in the protocol are the analyses of the feedstocks and biochars for contaminants including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), metals and mercury as well as nutrients (phosphorous, nitrite and nitrate and ammonium as nitrogen). The protocol also includes the biological testing procedures, earthworm avoidance and germination assays. Based on the quality assurance / quality control (QA/QC) results of blanks, duplicates, standards and reference materials, all methods were determined adequate for use with biochar and feedstock materials. All biochars and feedstocks were well within the criterion set by the IBI and there were little differences among biochars, except in the case of the biochar produced from construction waste materials. This biochar (referred to as Old biochar) was determined to have elevated levels of arsenic, chromium, copper, and lead, and failed the earthworm avoidance and germination assays. Based on these results, Old biochar would not be appropriate for use as a soil amendment for carbon sequestration, substrate quality improvements or remediation.
Environmental Sciences, Issue 93, biochar, characterization, carbon sequestration, remediation, International Biochar Initiative (IBI), soil amendment
Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
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
Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
Institutions: University of Houston.
Estrogen plays vital roles in mammary gland development and breast cancer progression. It mediates its function by binding to and activating the estrogen receptors (ERs), ERα, and ERβ. ERα is frequently upregulated in breast cancer and drives the proliferation of breast cancer cells. The ERs function as transcription factors and regulate gene expression. Whereas ERα's regulation of protein-coding genes is well established, its regulation of noncoding microRNA (miRNA) is less explored. miRNAs play a major role in the post-transcriptional regulation of genes, inhibiting their translation or degrading their mRNA. miRNAs can function as oncogenes or tumor suppressors and are also promising biomarkers. Among the miRNA assays available, microarray and quantitative real-time polymerase chain reaction (qPCR) have been extensively used to detect and quantify miRNA levels. To identify miRNAs regulated by estrogen signaling in breast cancer, their expression in ERα-positive breast cancer cell lines were compared before and after estrogen-activation using both the µParaflo-microfluidic microarrays and Dual Labeled Probes-low density arrays. Results were validated using specific qPCR assays, applying both Cyanine dye-based and Dual Labeled Probes-based chemistry. Furthermore, a time-point assay was used to identify regulations over time. Advantages of the miRNA assay approach used in this study is that it enables a fast screening of mature miRNA regulations in numerous samples, even with limited sample amounts. The layout, including the specific conditions for cell culture and estrogen treatment, biological and technical replicates, and large-scale screening followed by in-depth confirmations using separate techniques, ensures a robust detection of miRNA regulations, and eliminates false positives and other artifacts. However, mutated or unknown miRNAs, or regulations at the primary and precursor transcript level, will not be detected. The method presented here represents a thorough investigation of estrogen-mediated miRNA regulation.
Medicine, Issue 84, breast cancer, microRNA, estrogen, estrogen receptor, microarray, qPCR
Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
Institutions: University of California Merced, University of California Merced.
Spring-like materials are ubiquitous in nature and of interest in nanotechnology for energy harvesting, hydrogen storage, and biological sensing applications. For predictive simulations, it has become increasingly important to be able to model the structure of nanohelices accurately. To study the effect of local structure on the properties of these complex geometries one must develop realistic models. To date, software packages are rather limited in creating atomistic helical models. This work focuses on producing atomistic models of silica glass (SiO2
) nanoribbons and nanosprings for molecular dynamics (MD) simulations. Using an MD model of “bulk” silica glass, two computational procedures to precisely create the shape of nanoribbons and nanosprings are presented. The first method employs the AWK programming language and open-source software to effectively carve various shapes of silica nanoribbons from the initial bulk model, using desired dimensions and parametric equations to define a helix. With this method, accurate atomistic silica nanoribbons can be generated for a range of pitch values and dimensions. The second method involves a more robust code which allows flexibility in modeling nanohelical structures. This approach utilizes a C++ code particularly written to implement pre-screening methods as well as the mathematical equations for a helix, resulting in greater precision and efficiency when creating nanospring models. Using these codes, well-defined and scalable nanoribbons and nanosprings suited for atomistic simulations can be effectively created. An added value in both open-source codes is that they can be adapted to reproduce different helical structures, independent of material. In addition, a MATLAB graphical user interface (GUI) is used to enhance learning through visualization and interaction for a general user with the atomistic helical structures. One application of these methods is the recent study of nanohelices via MD simulations for mechanical energy harvesting purposes.
Physics, Issue 93, Helical atomistic models; open-source coding; graphical user interface; visualization software; molecular dynamics simulations; graphical processing unit accelerated simulations.
Tumor Treating Field Therapy in Combination with Bevacizumab for the Treatment of Recurrent Glioblastoma
Institutions: Southern Illinois University School of Medicine.
A novel device that employs TTF therapy has recently been developed and is currently in use for the treatment of recurrent glioblastoma (rGBM). It was FDA approved in April 2011 for the treatment of patients 22 years or older with rGBM. The device delivers alternating electric fields and is programmed to ensure maximal tumor cell kill1
Glioblastoma is the most common type of glioma and has an estimated incidence of approximately 10,000 new cases per year in the United States alone2
. This tumor is particularly resistant to treatment and is uniformly fatal especially in the recurrent setting3-5
. Prior to the approval of the TTF System, the only FDA approved treatment for rGBM was bevacizumab6
. Bevacizumab is a humanized monoclonal antibody targeted against the vascular endothelial growth factor (VEGF) protein that drives tumor angiogenesis7
. By blocking the VEGF pathway, bevacizumab can result in a significant radiographic response (pseudoresponse), improve progression free survival and reduce corticosteroid requirements in rGBM patients8,9
. Bevacizumab however failed to prolong overall survival in a recent phase III trial26
. A pivotal phase III trial (EF-11) demonstrated comparable overall survival between physicians’ choice chemotherapy and TTF Therapy but better quality of life were observed in the TTF arm10
There is currently an unmet need to develop novel approaches designed to prolong overall survival and/or improve quality of life in this unfortunate patient population. One appealing approach would be to combine the two currently approved treatment modalities namely bevacizumab and TTF Therapy. These two treatments are currently approved as monotherapy11,12
, but their combination has never been evaluated in a clinical trial. We have developed an approach for combining those two treatment modalities and treated 2 rGBM patients. Here we describe a detailed methodology outlining this novel treatment protocol and present representative data from one of the treated patients.
Medicine, Issue 92, Tumor Treating Fields, TTF System, TTF Therapy, Recurrent Glioblastoma, Bevacizumab, Brain Tumor
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
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
Cortical Source Analysis of High-Density EEG Recordings in Children
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1
. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2
, because the composition and spatial configuration of head tissues changes dramatically over development3
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
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
Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
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
gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair
Institutions: Centre Georges-François Leclerc.
The widespread use of Next Generation Sequencing has opened up new avenues for cancer research and diagnosis. NGS will bring huge amounts of new data on cancer, and especially cancer genetics. Current knowledge and future discoveries will make it necessary to study a huge number of genes that could be involved in a genetic predisposition to cancer. In this regard, we developed a Nextera design to study 11 complete genes involved in DNA damage repair. This protocol was developed to safely study 11 genes (ATM
, and TP53
) from promoter to 3'-UTR in 24 patients simultaneously. This protocol, based on transposase technology and gDNA enrichment, gives a great advantage in terms of time for the genetic diagnosis thanks to sample multiplexing. This protocol can be safely used with blood gDNA.
Genetics, Issue 92, gDNA enrichment, Nextera, NGS, DNA damage, BRCA1, BRCA2
Generation of Enterobacter sp. YSU Auxotrophs Using Transposon Mutagenesis
Institutions: Youngstown State University.
Prototrophic bacteria grow on M-9 minimal salts medium supplemented with glucose (M-9 medium), which is used as a carbon and energy source. Auxotrophs can be generated using a transposome. The commercially available, Tn5
-derived transposome used in this protocol consists of a linear segment of DNA containing an R6Kγ
replication origin, a gene for kanamycin resistance and two mosaic sequence ends, which serve as transposase binding sites. The transposome, provided as a DNA/transposase protein complex, is introduced by electroporation into the prototrophic strain, Enterobacter
sp. YSU, and randomly incorporates itself into this host’s genome. Transformants are replica plated onto Luria-Bertani agar plates containing kanamycin, (LB-kan) and onto M-9 medium agar plates containing kanamycin (M-9-kan). The transformants that grow on LB-kan plates but not on M-9-kan plates are considered to be auxotrophs. Purified genomic DNA from an auxotroph is partially digested, ligated and transformed into a pir+ Escherichia coli
) strain. The R6Kγ
replication origin allows the plasmid to replicate in pir+ E. coli
strains, and the kanamycin resistance marker allows for plasmid selection. Each transformant possesses a new plasmid containing the transposon flanked by the interrupted chromosomal region. Sanger sequencing and the Basic Local Alignment Search Tool (BLAST) suggest a putative identity of the interrupted gene. There are three advantages to using this transposome mutagenesis strategy. First, it does not rely on the expression of a transposase gene by the host. Second, the transposome is introduced into the target host by electroporation, rather than by conjugation or by transduction and therefore is more efficient. Third, the R6Kγ
replication origin makes it easy to identify the mutated gene which is partially recovered in a recombinant plasmid. This technique can be used to investigate the genes involved in other characteristics of Enterobacter
sp. YSU or of a wider variety of bacterial strains.
Microbiology, Issue 92, Auxotroph, transposome, transposon, mutagenesis, replica plating, glucose minimal medium, complex medium, Enterobacter
Barnes Maze Testing Strategies with Small and Large Rodent Models
Institutions: University of Missouri, Food and Drug Administration.
Spatial learning and memory of laboratory rodents is often assessed via navigational ability in mazes, most popular of which are the water and dry-land (Barnes) mazes. Improved performance over sessions or trials is thought to reflect learning and memory of the escape cage/platform location. Considered less stressful than water mazes, the Barnes maze is a relatively simple design of a circular platform top with several holes equally spaced around the perimeter edge. All but one of the holes are false-bottomed or blind-ending, while one leads to an escape cage. Mildly aversive stimuli (e.g.
bright overhead lights) provide motivation to locate the escape cage. Latency to locate the escape cage can be measured during the session; however, additional endpoints typically require video recording. From those video recordings, use of automated tracking software can generate a variety of endpoints that are similar to those produced in water mazes (e.g.
distance traveled, velocity/speed, time spent in the correct quadrant, time spent moving/resting, and confirmation of latency). Type of search strategy (i.e.
random, serial, or direct) can be categorized as well. Barnes maze construction and testing methodologies can differ for small rodents, such as mice, and large rodents, such as rats. For example, while extra-maze cues are effective for rats, smaller wild rodents may require intra-maze cues with a visual barrier around the maze. Appropriate stimuli must be identified which motivate the rodent to locate the escape cage. Both Barnes and water mazes can be time consuming as 4-7 test trials are typically required to detect improved learning and memory performance (e.g.
shorter latencies or path lengths to locate the escape platform or cage) and/or differences between experimental groups. Even so, the Barnes maze is a widely employed behavioral assessment measuring spatial navigational abilities and their potential disruption by genetic, neurobehavioral manipulations, or drug/ toxicant exposure.
Behavior, Issue 84, spatial navigation, rats, Peromyscus, mice, intra- and extra-maze cues, learning, memory, latency, search strategy, escape motivation
Optimization of High Grade Glioma Cell Culture from Surgical Specimens for Use in Clinically Relevant Animal Models and 3D Immunochemistry
Institutions: Henry Ford Hospital.
Glioblastomas, the most common and aggressive form of astrocytoma, are refractory to therapy, and molecularly heterogeneous. The ability to establish cell cultures that preserve the genomic profile of the parental tumors, for use in patient specific in vitro
and in vivo
models, has the potential to revolutionize the preclinical development of new treatments for glioblastoma tailored to the molecular characteristics of each tumor.
Starting with fresh high grade astrocytoma tumors dissociated into single cells, we use the neurosphere assay as an enrichment method for cells presenting cancer stem cell phenotype, including expression of neural stem cell markers, long term self-renewal in vitro
, and the ability to form orthotopic xenograft tumors. This method has been previously proposed, and is now in use by several investigators. Based on our experience of dissociating and culturing 125 glioblastoma specimens, we arrived at the detailed protocol we present here, suitable for routine neurosphere culturing of high grade astrocytomas and large scale expansion of tumorigenic cells for preclinical studies. We report on the efficiency of successful long term cultures using this protocol and suggest affordable alternatives for culturing dissociated glioblastoma cells that fail to grow as neurospheres. We also describe in detail a protocol for preserving the neurospheres 3D architecture for immunohistochemistry. Cell cultures enriched in CSCs, capable of generating orthotopic xenograft models that preserve the molecular signatures and heterogeneity of GBMs, are becoming increasingly popular for the study of the biology of GBMs and for the improved design of preclinical testing of potential therapies.
Medicine, Issue 83, Primary Cell Culture, animal models, Nervous System Diseases, Neoplasms, glioblastoma, neurosphere, surgical specimens, long-term self-renewal
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Institutions: University of Washington.
Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e
., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g
., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori
, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources.
Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising the sensor data from environmental and physiological contaminants. We will then outline the procedure for combining and mapping MEG/EEG sensor data onto the cortical space, thereby producing a family of time-series of cortical dipole activation on the brain surface (or "brain movies") related to each experimental condition. Finally, we will highlight a few statistical techniques that enable us to make scientific inference across a subject population (i.e
., perform group-level analysis) based on a common cortical coordinate space.
Neuroscience, Issue 68, Magnetoencephalography, MEG, Electroencephalography, EEG, audition, attention, inverse imaging
A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
Institutions: University of Nevada, Reno, St. Joseph's Medical Center, University of Rochester Medical Center .
Each year, an estimated 785,000 Americans will have a new coronary attack, or acute coronary syndrome (ACS). The pathophysiology of ACS involves rupture of an atherosclerotic plaque; hence, treatment is aimed at plaque stabilization in order to prevent cellular death. However, there is considerable debate among clinicians, about which treatment pathway is best: early invasive using percutaneous coronary intervention (PCI/stent) when indicated or a conservative approach (i.e.
, medication only with PCI/stent if recurrent symptoms occur).
There are three types of ACS: ST elevation myocardial infarction (STEMI), non-ST elevation MI (NSTEMI), and unstable angina (UA). Among the three types, NSTEMI/UA is nearly four times as common as STEMI. Treatment decisions for NSTEMI/UA are based largely on symptoms and resting or exercise electrocardiograms (ECG). However, because of the dynamic and unpredictable nature of the atherosclerotic plaque, these methods often under detect myocardial ischemia because symptoms are unreliable, and/or continuous ECG monitoring was not utilized.
Continuous 12-lead ECG monitoring, which is both inexpensive and non-invasive, can identify transient episodes of myocardial ischemia, a precursor to MI, even when asymptomatic. However, continuous 12-lead ECG monitoring is not usual hospital practice; rather, only two leads are typically monitored. Information obtained with 12-lead ECG monitoring might provide useful information for deciding the best ACS treatment.
Therefore, using 12-lead ECG monitoring, the COMPARE Study (electroC
n of ischeM
sive to phaR
atment) was designed to assess the frequency and clinical consequences of transient myocardial ischemia, in patients with NSTEMI/UA treated with either early invasive PCI/stent or those managed conservatively (medications or PCI/stent following recurrent symptoms). The purpose of this manuscript is to describe the methodology used in the COMPARE Study.
Permission to proceed with this study was obtained from the Institutional Review Board of the hospital and the university. Research nurses identify hospitalized patients from the emergency department and telemetry unit with suspected ACS. Once consented, a 12-lead ECG Holter monitor is applied, and remains in place during the patient's entire hospital stay. Patients are also maintained on the routine bedside ECG monitoring system per hospital protocol. Off-line ECG analysis is done using sophisticated software and careful human oversight.
Medicine, Issue 70, Anatomy, Physiology, Cardiology, Myocardial Ischemia, Cardiovascular Diseases, Health Occupations, Health Care, transient myocardial ischemia, Acute Coronary Syndrome, electrocardiogram, ST-segment monitoring, Holter monitoring, research methodology
Movement Retraining using Real-time Feedback of Performance
Institutions: University of British Columbia .
Any modification of movement - especially movement patterns that have been honed over a number of years - requires re-organization of the neuromuscular patterns responsible for governing the movement performance. This motor learning can be enhanced through a number of methods that are utilized in research and clinical settings alike. In general, verbal feedback of performance in real-time or knowledge of results following movement is commonly used clinically as a preliminary means of instilling motor learning. Depending on patient preference and learning style, visual feedback (e.g.
through use of a mirror or different types of video) or proprioceptive guidance utilizing therapist touch, are used to supplement verbal instructions from the therapist. Indeed, a combination of these forms of feedback is commonplace in the clinical setting to facilitate motor learning and optimize outcomes.
Laboratory-based, quantitative motion analysis has been a mainstay in research settings to provide accurate and objective analysis of a variety of movements in healthy and injured populations. While the actual mechanisms of capturing the movements may differ, all current motion analysis systems rely on the ability to track the movement of body segments and joints and to use established equations of motion to quantify key movement patterns. Due to limitations in acquisition and processing speed, analysis and description of the movements has traditionally occurred offline after completion of a given testing session.
This paper will highlight a new supplement to standard motion analysis techniques that relies on the near instantaneous assessment and quantification of movement patterns and the display of specific movement characteristics to the patient during
a movement analysis session. As a result, this novel technique can provide a new method of feedback delivery that has advantages over currently used feedback methods.
Medicine, Issue 71, Biophysics, Anatomy, Physiology, Physics, Biomedical Engineering, Behavior, Psychology, Kinesiology, Physical Therapy, Musculoskeletal System, Biofeedback, biomechanics, gait, movement, walking, rehabilitation, clinical, training
Telomere Length and Telomerase Activity; A Yin and Yang of Cell Senescence
Institutions: Albert Einstein College of Medicine , Albert Einstein College of Medicine , Albert Einstein College of Medicine .
Telomeres are repeating DNA sequences at the tip ends of the chromosomes that are diverse in length and in humans can reach a length of 15,000 base pairs. The telomere serves as a bioprotective mechanism of chromosome attrition at each cell division. At a certain length, telomeres become too short to allow replication, a process that may lead to chromosome instability or cell death. Telomere length is regulated by two opposing mechanisms: attrition and elongation. Attrition occurs as each cell divides. In contrast, elongation is partially modulated by the enzyme telomerase, which adds repeating sequences to the ends of the chromosomes. In this way, telomerase could possibly reverse an aging mechanism and rejuvenates cell viability. These are crucial elements in maintaining cell life and are used to assess cellular aging. In this manuscript we will describe an accurate, short, sophisticated and cheap method to assess telomere length in multiple tissues and species. This method takes advantage of two key elements, the tandem repeat of the telomere sequence and the sensitivity of the qRT-PCR to detect differential copy numbers of tested samples. In addition, we will describe a simple assay to assess telomerase activity as a complementary backbone test for telomere length.
Genetics, Issue 75, Molecular Biology, Cellular Biology, Medicine, Biomedical Engineering, Genomics, Telomere length, telomerase activity, telomerase, telomeres, telomere, DNA, PCR, polymerase chain reaction, qRT-PCR, sequencing, aging, telomerase assay
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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
A Chemical Screening Procedure for Glucocorticoid Signaling with a Zebrafish Larva Luciferase Reporter System
Institutions: Karlsruhe Institute of Technology - Campus North, Karlsruhe Institute of Technology - Campus North, Karlsruhe Institute of Technology - Campus South.
Glucocorticoid stress hormones and their artificial derivatives are widely used drugs to treat inflammation, but long-term treatment with glucocorticoids can lead to severe side effects. Test systems are needed to search for novel compounds influencing glucocorticoid signaling in vivo
or to determine unwanted effects of compounds on the glucocorticoid signaling pathway. We have established a transgenic zebrafish assay which allows the measurement of glucocorticoid signaling activity in vivo
and in real-time, the GRIZLY assay (Glucocorticoid Responsive In vivo
Zebrafish Luciferase activitY). The luciferase-based assay detects effects on glucocorticoid signaling with high sensitivity and specificity, including effects by compounds that require metabolization or affect endogenous glucocorticoid production. We present here a detailed protocol for conducting chemical screens with this assay. We describe data acquisition, normalization, and analysis, placing a focus on quality control and data visualization. The assay provides a simple, time-resolved, and quantitative readout. It can be operated as a stand-alone platform, but is also easily integrated into high-throughput screening workflows. It furthermore allows for many applications beyond chemical screening, such as environmental monitoring of endocrine disruptors or stress research.
Developmental Biology, Issue 79, Biochemistry, Vertebrates, Zebrafish, environmental effects (biological and animal), genetics (animal), life sciences, animal biology, animal models, biochemistry, bioengineering (general), Hormones, Hormone Substitutes, and Hormone Antagonists, zebrafish, Danio rerio, chemical screening, luciferase, glucocorticoid, stress, high-throughput screening, receiver operating characteristic curve, in vivo, animal model
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Institutions: Princeton University.
The aim of de novo
protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo
protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.
To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
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
Basics of Multivariate Analysis in Neuroimaging Data
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