Showing papers in "Critical Reviews in Biomedical Engineering in 2012"
TL;DR: The fundamentals of bone tissue engineering are discussed, highlighting the current state of this field, and the recent advances of biomaterial and cell-based research, as well as approaches used to enhance bone regeneration.
Abstract: The worldwide incidence of bone disorders and conditions has trended steeply upward and is expected to double by 2020, especially in populations where aging is coupled with increased obesity and poor physical activity. Engineered bone tissue has been viewed as a potential alternative to the conventional use of bone grafts, due to their limitless supply and no disease transmission. However, bone tissue engineering practices have not proceeded to clinical practice due to several limitations or challenges. Bone tissue engineering aims to induce new functional bone regeneration via the synergistic combination of biomaterials, cells, and factor therapy. In this review, we discuss the fundamentals of bone tissue engineering, highlighting the current state of this field. Further, we review the recent advances of biomaterial and cell-based research, as well as approaches used to enhance bone regeneration. Specifically, we discuss widely investigated biomaterial scaffolds, micro- and nano-structural properties of these scaffolds, and the incorporation of biomimetic properties and/or growth factors. In addition, we examine various cellular approaches, including the use of mesenchymal stem cells (MSCs), embryonic stem cells (ESCs), adult stem cells, induced pluripotent stem cells (iPSCs), and platelet-rich plasma (PRP), and their clinical application strengths and limitations. We conclude by overviewing the challenges that face the bone tissue engineering field, such as the lack of sufficient vascularization at the defect site, and the research aimed at functional bone tissue engineering. These challenges will drive future research in the field.
1,742 citations
TL;DR: This review presents the complex issues governing efficient penetration of nanoscale therapies into solid tumors and provides an overview of the important nanoparticle design parameters governing their tumor penetration, as well as highlighting critical directions in this field.
Abstract: Poor penetration of anticancer drags into solid tumors significantly limits their efficacy. This phenomenon has long been observed for small-molecule chemotherapeutics, and it can be even more pronounced for nanoscale therapies. Nanoparticles have enormous potential for the treatment of cancer due to their wide applicability as drug delivery and imaging vehicles and their size-dependent accumulation into solid tumors by the enhanced permeability and retention (EPR) effect. Further, synthetic nanoparticles can be engineered to overcome barriers to drag delivery. Despite their promise for the treatment of cancer, relatively little work has been done to study and improve their ability to diffuse into solid tumors following passive accumulation in the tumor vasculature. In this review, we present the complex issues governing efficient penetration of nanoscale therapies into solid tumors. The current methods available to researchers to study nanoparticle penetration into malignant tumors are described, and the most recent works studying the penetration of nanoscale materials into solid tumors are summarized. We conclude with an overview of the important nanoparticle design parameters governing their tumor penetration, as well as by highlighting critical directions in this field.
144 citations
TL;DR: Together with an integration of functional data in the navigation such as diffusion tensor imaging (DTI)-based fiber tracking or functional MRI, there is evidence that iMRI contributes to maximize extent of resection in glioma surgery with a preservation of neurological function.
Abstract: Navigation systems are commonly used in neurosurgical operating theaters. Generally, they either rely on the use of preoperative or intraoperative image data. Using preoperative image data, the phenomenon of brain shift contributes most to errors, in addition to various other sources of decreased reliability, such as image-related errors or registration inaccuracy. Updating navigation after intraoperative magnetic resonance imaging (iMRI) serves as immediate feedback on the surgical result and furthermore compensates for the effects of brain shift. Together with an integration of functional data in the navigation such as diffusion tensor imaging (DTI)-based fiber tracking or functional MRI, there is evidence that iMRI contributes to maximize extent of resection in glioma surgery with a preservation of neurological function. The following article summarizes the work flow and clinical impact of iMRI and functional navigation, as well as current problems and possible solutions.
68 citations
TL;DR: This review presents the current state of the theoretical debate about the origins of 1/f fluctuations, with special focus on recent hypotheses that establish a direct link between complexity and fractal fluctuations.
Abstract: Complexity is maybe one of the less understood concepts, even within the scientific community Recent theoretical and experimental advances, however, based on the close relationship between the complexity of the system and the presence of 1/f fluctuations in its macroscopic behavior, have opened new domains of investigation, which consider fundamental questions as well as more applied perspectives These approaches allow a better understanding of how essential macroscopic functions could emerge from complex interactive networks In this review we present the current state of the theoretical debate about the origins of 1/f fluctuations, with a special focus on recent hypotheses that establish a direct link between complexity and fractal fluctuations, and clarify some lines of opposition, especially between idiosyncratic vs nomothetic conceptions, and global vs componential approaches Finally, we discuss the deep questioning that this approach can generate with regard to current theories of motor control and psychological processes, and some future developments which may be evoked, especially in the domain of physical medicine and rehabilitation
59 citations
TL;DR: This review summarizes and discusses the three principal sources of motion: the beating heart, the breathing lungs, and bulk patient movement and a comprehensive overview of commonly used compensation strategies for these different types of motion.
Abstract: Image quality in magnetic resonance imaging (MRI) is considerably affected by motion. Therefore, motion is one of the most common sources of artifacts in contemporary cardiovascular MRI. Such artifacts in turn may easily lead to misinterpretations in the images and a subsequent loss in diagnostic quality. Hence, there is considerable research interest in strategies that help to overcome these limitations at minimal cost in time, spatial resolution, temporal resolution, and signal-to-noise ratio. This review summarizes and discusses the three principal sources of motion: the beating heart, the breathing lungs, and bulk patient movement. This is followed by a comprehensive overview of com- monly used compensation strategies for these different types of motion. Finally, a summary and an outlook are provided.
55 citations
TL;DR: A multitude of strategies to reduce the impact of intrafractional target motion in RT have been developed and are increasingly being used clinically, with the clinical introduction of advanced strategies currently under development imminent.
Abstract: Image-guided radiotherapy (IGRT) has helped to dramatically reduce safety margins compensating for positioning uncertainties in radiotherapy A remaining issue posing problems for photon radiotherapy (RT), but even more so for particle RT, is target motion during treatment delivery This review outlines the various strategies currently being developed or already in clinical use to compensate for organ motion, predominantly breathing-induced motion of liver and lung targets Several motion compensation strategies have recently been introduced clinically Among these are optimized margins encompassing the individual range of target motion, treatment under breath hold, gated treatments, and tumor tracking with a dedicated treatment device A variety of surveillance strategies for gating and tracking, such as indirect tracking with external fiducial markers and surface scanning devices, direct tracking with implanted electromagnetic markers, fiducial markers, and fluoroscopy, and ultrasound-based tracking are already in clinical use or are under development Tracked treatment with linear accelerators based on tumor-synchronous MLC- or treatment-table adaptation are moving toward clinical use A multitude of strategies to reduce the impact of intrafractional target motion in RT have been developed and are increasingly being used clinically The clinical introduction of advanced strategies currently under development is imminent After IGRT minimized treatment margins for static tumors, the implementation of motion compensation strategies will achieve the same for targets being subject to intrafractional breathing-induced motion
37 citations
TL;DR: Only through a thorough synthesis of the anatomic, biomechanical, and clinical knowledge regarding first MTP joint sprains can appropriate countermeasures be designed to reduce the prevalence and severity of these injuries.
Abstract: Sprains of the first metatarsophalangeal (MTP) joint, referred to colloquially as "turf toe," are a debilitating sports injury because the hallux is pivotal to an athletes' ability to accelerate and cut. Severe sprains may require weeks to full recovery, and injuries requiring surgery may prevent an athlete from full athletic participation for months. Whereas the diagnosis and treatment of turf toe are well documented in the literature, less is known about the biomechanics of this joint and the mechanical properties of the structures that compose it. Nevertheless, this information is vital to those, such as equipment designers, who attempt to develop athletic footwear and surfaces intended to reduce the likelihood of injury. To that end, this review summarizes the literature on the anatomy of the first MTP joint, on biomechanical studies of the first MTP joint, and on the incidence, mechanisms, and treatment of turf toe. Furthermore, gaps in the literature are identified and opportunities for future research are discussed. Only through a thorough synthesis of the anatomic, biomechanical, and clinical knowledge regarding first MTP joint sprains can appropriate countermeasures be designed to reduce the prevalence and severity of these injuries.
34 citations
TL;DR: The use of elastography for quantitative mechanical characterization is particularly emphasized, and original applications of these methods to several biomedical research fields are reviewed.
Abstract: Elasticity imaging methods aim at measuring the mechanical behavior of soft tissues by using medical imaging modalities, such as ultrasonography or magnetic resonance imaging. The initial motivation behind these techniques, and still the main one, is the need for new diagnostic tools based on the visualization of tissue stiffness. Recent developments have demonstrated the potential that elasticity imaging methods can offer in new fields other than direct medical diagnosis, such as the field of in vivo biomechanical characterization. After a short description of the general principles behind elasticity imaging, this review illustrates some of the most original clinical applications. The use of elastography for quantitative mechanical characterization is particularly emphasized, and original applications of these methods to several biomedical research fields are reviewed.
32 citations
TL;DR: The technical limitations of the imaging method within the spinal cord are discussed, possible solutions are reviewed, and the current uses and the potential clinical application of this technique are highlighted.
Abstract: Diffusion tensor imaging (DTI) is currently the only non-invasive in vivo assessment of white matter tract integrity. Capitalizing on the diffusion properties of water within an axon, DTI enables the visualization of tissue structure at a microscopic scale. Furthermore, measurements of anisotropy and diffusivity enable the detection of subtle details of the effects of injury that cannot be detected using conventional magnetic resonance techniques. Recently, DTI has been applied to the spinal cord, and results have demonstrated it to be a valuable tool for assessing the extent of white matter damage in numerous spinal cord-related conditions including multiple sclerosis, spinal cord injury, amyotrophic lateral sclerosis, myelitis, and spinal cord tumors. The purpose of this review is to discuss the technical limitations of the imaging method within the spinal cord, review possible solutions, and highlight the current uses and the potential clinical application of this technique.
31 citations
TL;DR: There is a need for a mechanistic understanding that links the clinical phenomenon of physiologic variability with the underlying patterns of the biology of inflammation, and it is asserted that this can be facilitated through the use of dynamic mathematical and computational modeling.
Abstract: Sepsis is a clinical entity in which complex inflammatory and physiological processes are mobilized, not only across a range of cellular and molecular interactions, but also in clinically relevant physiological signals accessible at the bedside. There is a need for a mechanistic understanding that links the clinical phenomenon of physiologic variability with the underlying patterns of the biology of inflammation, and we assert that this can be facilitated through the use of dynamic mathematical and computational modeling. An iterative approach of laboratory experimentation and mathematical/computational modeling has the potential to integrate cellular biology, physiology, control theory, and systems engineering across biological scales, yielding insights into the control structures that govern mechanisms by which phenomena, detected as biological patterns, are produced. This approach can represent hypotheses in the formal language of mathematics and computation, and link behaviors that cross scales and domains, thereby offering the opportunity to better explain, diagnose, and intervene in the care of the septic patient.
28 citations
TL;DR: 4D organ models to compensate for respiratory motion during therapy, which predict the location of structures of interest from surrogates measured during therapy are discussed in detail.
Abstract: Minimal invasive tumor therapies are getting ever more sophisticated with novel treatment approaches and new devices allowing for improved targeting precision. Applying these effectively requires precise localization of the structures of interest. Vital processes, such as respiration and heartbeat, induce organ motion, which cannot be neglected during therapy. This review focuses on 4D organ models to compensate for respiratory motion during therapy. An overview is given on the effects of motion on the therapeutical outcome, methods required to capture and quantify respiratory motion, range of reported tumor motion, types of surrogates used when tumors are not directly observable, and methods for temporal prediction of surrogate motion. Organ motion models, which predict the location of structures of interest from surrogates measured during therapy, are discussed in detail.
TL;DR: The state of the art in modeling the effects of diverse drugs for treating inflammation is illustrated, relevant biomarkers amenable to modeling are described, and major advantages and limitations of the published pharmacokinetic/ pharmacodynamic (PK/PD) models are summarized.
Abstract: Inflammation is an array of immune responses to infection and injury. It results from a complex immune cascade and is the basis of many chronic diseases such as arthritis, diabetes, and cancer. Numerous mathematical models have been developed to describe the disease progression and effects of anti-inflammatory drugs. This review illustrates the state of the art in modeling the effects of diverse drugs for treating inflammation, describes relevant biomarkers amenable to modeling, and summarizes major advantages and limitations of the published pharmacokinetic/ pharmacodynamic (PK/PD) models. Simple direct inhibitory models are often used to describe in vitro effects of anti-inflammatory drugs. Indirect response models are more mechanism based and have been widely applied to the turnover of symptoms and biomarkers. These, along with target-mediated and transduction models, have been successfully applied to capture the PK/PD of many anti-inflammatory drugs and describe disease progression of inflammation. Biologics have offered opportunities to address specific mechanisms of action, and evolve small systems models to quantitatively capture the underlying physiological processes. More advanced mechanistic models should allow evaluation of the roles of some key mediators in disease progression, assess drug interactions, and better translate drug properties from in vitro and animal data to patients.
TL;DR: There is substantial evidence that suggests that chronic intermittent hypoxia (CIH) leads to sustained sympathoexcitation during the day and changes in vasculature resulting in hypertension in patients with OSA.
Abstract: Obstructive sleep apnea (OSA) is characterized by episodes of repeated airway obstruction resulting in cessation (apnea) or reduction (hypopnea) in airflow during sleep. These events lead to intermittent hypoxia and hypercapnia, sleep fragmentation, and changes in intrathoracic pressure, and are associated with a marked surge in sympathetic activity and an abrupt increase in blood pressure. Blood pressure remains elevated during wakefulness despite the absence of obstructive events resulting in a high prevalence of hypertension in patients with OSA. There is substantial evidence that suggests that chronic intermittent hypoxia (CIH) leads to sustained sympathoexcitation during the day and changes in vasculature resulting in hypertension in patients with OSA. Mechanisms of sympathoexcitation include augmentation of peripheral chemoreflex sensitivity and a direct effect on central sites of sympathetic regulation. Interestingly, the vascular changes that occur with CIH have been ascribed to the same molecules that have been implicated in the augmented sympathetic tone in CIH. This review will discuss the hypothesized molecular mechanisms involved in the development of hypertension with CIH, will build a conceptual model for the development of hypertension following CIH, and will propose a systems biology approach in further elucidating the relationship between CIH and the development of hypertension.
TL;DR: Clinical background information on indications and techniques for the treatment of liver tumors, the technological contributions addressing the problem of organ motion during navigated surgery on a deforming organ are reviewed, and an overview of the clinical experience in computer-assisted liver surgery and interventions are presented.
Abstract: Oncological liver surgery and interventions aim for removal of tumor tissue while preserving a sufficient amount of functional tissue to ensure organ regeneration. This requires detailed understanding of the patient-specific internal organ anatomy (blood vessel system, bile ducts, tumor location). The introduction of computer support in the surgical process enhances anatomical orientation through patient-specific 3D visualization and enables precise reproduction of planned surgical strategies though stereotactic navigation technology. This article provides clinical background information on indications and techniques for the treatment of liver tumors, reviews the technological contributions addressing the problem of organ motion during navigated surgery on a deforming organ, and finally presents an overview of the clinical experience in computer-assisted liver surgery and interventions. The review concludes that several clinically applicable solutions for computer aided liver surgery are available and small-scale clinical trials have been performed. Further developments will be required more accurate and faster handling of organ deformation and large clinical studies will be required for demonstrating the benefits of computer aided liver surgery.
TL;DR: This review discusses the work with the late Stephen F. Lowry to investigate systemic inflammation through systems biology of human endotoxemia, and presents the efforts in modeling the human endotoxin response with a particular focus on physiologic variability.
Abstract: The control and management of inflammation is a key aspect of clinical care for critical illnesses such as sepsis In an ideal reaction to injury, the inflammatory response provokes a strong enough response to heal the injury and then restores homeostasis When inflammation becomes dysregulated, a persistent inflammatory state can lead to significant deleterious effects and clinical challenges Thus, gaining a better biological understanding of the mechanisms driving the inflammatory response is of the utmost importance In this review, we discuss our work with the late Stephen F Lowry to investigate systemic inflammation through systems biology of human endotoxemia We present our efforts in modeling the human endotoxemia response with a particular focus on physiologic variability Through modeling, with a focus ultimately on translational applications, we obtain more fundamental understanding of relevant physiological processes And by taking advantage of the information embedded in biological rhythms, ranging in time scale from high-frequency autonomic oscillations reflected in heart rate variability to circadian rhythms in inflammatory mediators, we gain insight into the underlying physiology
TL;DR: It is highlighted that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated, and that distinctions between biological and cognitive systems from physical systems are pretheoretical and thus optional.
Abstract: The neurobiological sciences have struggled to resolve the physical foundations for biological and cognitive phenomena with a suspicion that biological and cognitive systems, capable of exhibiting and contributing to structure within themselves and through their contexts, are fundamentally distinct or autonomous from purely physical systems. Complexity science offers new physics-based approaches to explaining biological and cognitive phenomena. In response to controversy over whether complexity science might seek to "explain away" biology and cognition as "just physics," we propose that complexity science serves as an application of recent advances in physics to phenomena in biology and cognition without reducing or undermining the integrity of the phenom- ena to be explained. We highlight that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated. We propose that distinctions between biological and cognitive systems from physi- cal systems are pretheoretical and thus optional. We review our own work applying insights from post-classical physics regarding turbulence and fractal fluctuations to the problems of developing cognitive structure. Far from hoping to reduce biology and cognition to "nothing but" physics, we present our view that complexity science of- fers new explanatory frameworks for considering physical foundations of biological and cognitive phenomena.
TL;DR: This article provides an overview of the works that have been accomplished in the past few decades and aims to study the dynamics of RBCs under different flow conditions.
Abstract: The dynamics of red blood cells (RBCs) is one of the major aspects of the cardiovascular system that has been studied intensively in the past few decades. The dynamics of biconcave RBCs are thought to have major influences in cardiovascular diseases, the problems associated with cardiovascular assistive devices, and the determination of blood rheology and properties. This article provides an overview of the works that have been accomplished in the past few decades and aim to study the dynamics of RBCs under different flow conditions. While significant progress has been made in both experimental and numerical studies, a detailed understanding of the behavior of RBCs is still faced with many challenges. Experimentally, the size of RBCs is considered to be a major limitation that allows measurements to be performed under conditions similar to physiological conditions. In numerical computations, researchers still are working to develop a model that can cover the details of the RBC mechanics as it deforms and moves in the bloodstream. Moreover, most of reported computational models have been confined to the behavior of a single RBC in 2-dimensional domains. Advanced models are yet to be devel-oped for accurate description of RBC dynamics under physiological flow conditions in 3-dimensional regimes.
TL;DR: Recent developments in dissecting the complex and diverse immune responses associated with melanoma are discussed through both computational and experimental means, and the significance of devising new, improved approaches that can better serve as models of immune interactions and therapies are shown.
Abstract: Malignant melanoma, the most lethal skin cancer, is considered as a representative model for cross talk between immune responses and malignancy. Efforts to elucidate the nature of these interactions have translated into immunotherapeutic strategies. Adjuvant therapeutics such as IL-2 and IFNα2b have reached clinical application, and emerging therapies targeting key immunomodulatory molecules such as CTLA-4 have renewed excitement in the field, highlighting the potential of manipulating immune responses in the clinical setting, but also the merits for further elucidating complex underlying immunological pathways. Screening technologies have yielded new insights leading to identification of biomarkers for disease prognosis and applied clinical immunotherapies. The promise of systems biology is to integrate diverse biomedical characterizations into detailed models of underlying mechanisms and therapies through suitable computational and mathematical formalisms. In this review, we discuss recent developments in dissecting the complex and diverse immune responses associated with melanoma through both computational and experimental means. We show the significance of devising new, improved approaches that can better serve as models of immune interactions and therapies. We propose that efforts in this direction may realize the potential of personalized medicine and facilitate development of the next generation of efficacious tools to treat patients.
TL;DR: MRI has excellent soft-tissue visualization characteristics and has been used extensively to characterize the myocardial tissue as scar or fibrosis, and is increasingly being used, along with the three-dimensional structural information in the ablation procedures, with the goal of improving the outcome.
Abstract: Radiofrequency ablation is routinely used to treat numerous cardiac arrhythmias originating in the atrium and the ventricle. The process of ablation was pioneered to treat supraventricular tachycardias originating from fixed electrical circuits. These circuits could be identified using innovative electrophysiological maneuvers, which have been refined over the years to achieve excellent cure rates using fluoroscopy. More recently, electrophysiology ablation procedures have been greatly expanded to treat more diffuse arrhythmias like atrial fibrillation and ventricular tachycardia that are sustained by a remodeled myocardium or scar tissue. Given that there is no fixed circuit to target during most of these ablations, especially atrial fibrillation, there is a need to better visualize the substrate or the remodeling in the myocardium. Currently, when ablating atrial fibrillation or ventricular tachycardias, it is routine to use a cardiac CT or intra-cardiac echocardiogram to provide a three-dimensional anatomical structural map of the heart. This approach does not provide any substrate information like fibrosis or scar tissue in the myocardium. MRI has excellent soft-tissue visualization characteristics and has been used extensively to characterize the myocardial tissue as scar or fibrosis. This structural remodeling information of the myocardium is increasingly being used, along with the three-dimensional structural information in the ablation procedures, with the goal of improving the outcome. In addition MRI can also be used to visualize radiofrequency ablation lesions, potentially leading to significant improvement in procedural outcomes.
TL;DR: The case for the studying complexity with a perspective of understanding the macroscopic stability in biological systems by focusing on component processes at extended spatial and temporal scales is made.
Abstract: This article serves as an introduction to the themed special issue on "Complex Systems in Neurobiology." The study of complexity in neurobiology has been sensitive to the stochastic processes that dominate the micro-level architecture of neurobiological systems and the deterministic processes that govern the macroscopic behavior of these systems. A large body of research has traversed these scales of interest, seeking to determine how noise at one spatial or temporal scale influences the activity of the system at another scale. In introducing this special issue, we pay special attention to the history of inquiry in complex systems and why scientists have tended to favor linear, causally driven, reductionist approaches in Neurobiology. We follow this with an elaboration of how an alternative approach might be formulated. To illustrate our position on how the sciences of complexity and the study of noise can inform neurobiol- ogy, we use three systematic examples from the study of human motor control and learning: 1) phase transitions in bimanual coordination; 2) balance, intermittency, and discontinuous control; and 3) sensorimotor synchronization and timing. Using these examples and showing that noise is adaptively utilized by the nervous system, we make the case for the studying complexity with a perspective of understanding the macroscopic stability in biological systems by focusing on component processes at extended spatial and temporal scales. This special issue continues this theme with contributions in topics as diverse as neural network models, physical biology, motor learning, and statistical physics.
TL;DR: The state of the art of liver applications, the tremendous challenges of this field, and approaches to overcome these challenges are reviewed.
Abstract: Focused ultrasound surgery is an outstanding novel technique for cancer treatment because it is completely noninvasive with the potential for complete and controlled local tumor destruction. Because focused ultrasound surgery is applied from outside of the patient's body, imaging such as ultrasound or magnetic resonance imaging is required to plan and monitor the intervention. For the treatment of liver tumors, several complexities have to be taken into account, including accessibility of the target and protection of structures at risk. To allow for safe and efficient treatment under free respiration, in which the liver moves significantly, both planning and execution have to be performed specifically according to the patient's individual breathing. This article reviews the state of the art of liver applications, the tremendous challenges of this field, and approaches to overcome these challenges. This includes modeling of the patient-individual breathing cycle, detection of and adaptation to the actual breathing, and simulation and monitoring of the therapy.
TL;DR: Current developments in breast image registration techniques are reviewed, and comment on their clinical relevance, individual capabilities, and open challenges are commented on.
Abstract: Image-based examination of the breast facilitates the detection of breast diseases, particularly of present benign and malignant lesions. For computer-aided processing of serial and multimodal clinical data, both for visual correlation and quantitative analysis, automated image-registration methods are an indispensable tool. The wide range of modalities and the high variability of breast appearance have led to a large diversity of proposed approaches for tissue deformation modeling and image registration. In this article, we review current developments in breast image registration techniques, and comment on their clinical relevance, individual capabilities, and open challenges.
TL;DR: Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation and a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large is introduced.
Abstract: Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large.
TL;DR: It is concluded that cognitive science and neuroscience have much to gain from investigating the adaptive aspects of complex spike dynamics for neural and cognitive function.
Abstract: Complexity is widespread in neuronal spike trains and propagation of spike activity, in that variations in measurements of neural activity are irregular, heterogeneous, non-stationary, transient, and scale-free. There are numerous possible reasons for this complexity, and numerous possible consequences for neural and behavioral function. The present review is focused on relationships among neural plasticity, learning, and complex spike dynamics in animal nervous systems, including those of humans. The literature on complex spike dynamics and mechanisms of synaptic plasticity are reviewed for the purpose of considering the roles that each might play for the other. That is, the roles of complex spike dynamics in learning and regulatory functions are considered, as well as the roles of learning and regulatory functions in generating complex spike dynamics. Experimental and computational studies from a range of disciplines and perspectives are discussed, and it is concluded that cognitive science and neuroscience have much to gain from investigating the adaptive aspects of complex spike dynamics for neural and cognitive function.
TL;DR: Examples of time scales distinguishing properties of motor learning and development are presented, including the direction of change in the complexity of motor behavior, the transient and persistent processes of learning, scaling and transition properties of change, and consolidation effects of motorlearning.
Abstract: Learning and development over the lifespan influence the dynamics of the human motor system. Our ideas about the dynamics of motor learning and development are grounded in the phenomena of the continuous evolution of movement patterns and outcomes over multiple time scales. In this review, we present examples of time scales distinguishing properties of motor learning and development, including the direction of change in the complexity of motor behavior, the transient and persistent processes of learning, scaling and transition properties of change, and consolidation effects of motor learning. The pathways of changes in movement dynamics over the lifespan are channelled by the confluence of constraints to action embedded in the interaction of the individual with the environment and with tasks at hand.
TL;DR: This report focuses on techniques that are amenable to simulating highly resolved meshes, which for instance can be generated from computed tomography or magnetic resonance images, and reviews the so-called corotated finite element method that has shown a high potential in recent years.
Abstract: Simulation techniques for deformable bodies are of major relevance for a broad range of medical applications. In recent decades, a lot of work has been performed to improve simulation methods, allowing interactivity or even real time. However, this work often focused on applications such as computer games or virtual environments, where physical accuracy is not a primary goal. The goal of this report is to give an overview of efficient physics-based techniques for deformable objects, focusing on finite element methods, and to discuss the applicability of these techniques in medical scenarios. As a result, we focus on techniques that are amenable to simulating highly resolved meshes, which for instance can be generated from computed tomography (CT) or magnetic resonance (MR) images, and we review the so-called corotated finite element method that has shown a high potential in recent years. Specifically, we will capture in detail the related work in this field and demonstrate the current state of the art in efficient deformable bodies simulations.
TL;DR: A comprehensive review to demonstrate the advantages of time-frequency approaches in analyzing and extracting pathological structures from speech signals and to explain a framework that holds the existing methods of disordered voice analysis schemes.
Abstract: Acoustical measures of vocal function are important in the assessments of disordered voice, and for monitoring patients' progress over the course of voice therapy. In the last 2 decades, a variety of techniques for automatic pathological voice detection have been proposed, ranging from traditional temporal or spectral approaches to advanced time-frequency techniques. However, comparison of these methods is a difficult task because of the diversity of approaches. In this article, we explain a framework that holds the existing methods. In the light of this framework, the methodologic principles of disordered voice analysis schemes are compared and discussed. In addition, this article presents a comprehensive review to demonstrate the advantages of time-frequency approaches in analyzing and extracting pathological structures from speech signals. This information may have an important role in the development of new approaches to this problem.
TL;DR: The authors examined the history of sepsis science through an engineering lens and proposed a way forward using the logic of systems engineering and network science, using a model system from the engineering canon.
Abstract: The sepsis syndrome is an old phenomenon. A destructive response to a system disturbance, it manifests as widespread inflammation. Over the past two centuries, biomedical research has identified triggers and described components of the pathways that underlie the sepsis syndrome. Attempts at translating these findings into preventive and therapeutic interventions have met with varying levels of success. In this chapter, we examine the history of sepsis science through an engineering lens. Patterned attempts to intervene in the natural history of the sepsis syndrome will be discussed in parallel with similar, hypothetical adjustments made to a model system from the engineering canon. This juxtaposition will facilitate our review of the history of sepsis science. Using the logic of systems engineering and network science, we propose a way forward.