The biomechanical principles underlying the organization of muscle activation patterns during standing balance are poorly understood. The goal of this study was to understand the influence of biomechanical inter-joint coupling on endpoint forces and accelerations induced by the activation of individual muscles during postural tasks. We calculated induced endpoint forces and accelerations of 31 muscles in a 7 degree-of-freedom, three-dimensional model of the cat hindlimb. To test the effects of inter-joint coupling, we systematically immobilized the joints (excluded kinematic degrees of freedom) and evaluated how the endpoint force and acceleration directions changed for each muscle in 7 different conditions. We hypothesized that altered inter-joint coupling due to joint immobilization of remote joints would substantially change the induced directions of endpoint force and acceleration of individual muscles. Our results show that for most muscles crossing the knee or the hip, joint immobilization altered the endpoint force or acceleration direction by more than 90° in the dorsal and sagittal planes. Induced endpoint forces were typically consistent with behaviorally observed forces only when the ankle was immobilized. We then activated a proximal muscle simultaneous with an ankle torque of varying magnitude, which demonstrated that the resulting endpoint force or acceleration direction is modulated by the magnitude of the ankle torque. We argue that this simple manipulation can lend insight into the functional effects of co-activating muscles. We conclude that inter-joint coupling may be an essential biomechanical principle underlying the coordination of proximal and distal muscles to produce functional endpoint actions during motor tasks.
Semiconductor quantum dots (QDs) are light-emitting particles on the nanometer scale that have emerged as a new class of fluorescent labels for chemical analysis, molecular imaging, and biomedical diagnostics. Compared with traditional fluorescent probes, QDs have unique optical and electronic properties such as size-tunable light emission, narrow and symmetric emission spectra, and broad absorption spectra that enable the simultaneous excitation of multiple fluorescence colors. QDs are also considerably brighter and more resistant to photobleaching than are organic dyes and fluorescent proteins. These properties are well suited for dynamic imaging at the single-molecule level and for multiplexed biomedical diagnostics at ultrahigh sensitivity. Here, we discuss the fundamental properties of QDs; the development of next-generation QDs; and their applications in bioanalytical chemistry, dynamic cellular imaging, and medical diagnostics. For in vivo and clinical imaging, the potential toxicity of QDs remains a major concern. However, the toxic nature of cadmium-containing QDs is no longer a factor for in vitro diagnostics, so the use of multicolor QDs for molecular diagnostics and pathology is probably the most important and clinically relevant application for semiconductor QDs in the immediate future.
Numerical estimation of the size of the kidney is useful in evaluating conditions of the kidney, especially, when serial MR imaging is performed to evaluate the kidney function. This paper presents a new method for automatic segmentation of the kidney in three-dimensional (3D) MR images, by extracting texture features and statistical matching of geometrical shape of the kidney. A set of Wavelet-based support vector machines (W-SVMs) is trained on the MR images. The W-SVMs capture texture priors of MRI for classification of the kidney and non-kidney tissues in different zones around the kidney boundary. In the segmentation procedure, these W-SVMs are trained to tentatively label each voxel around the kidney model as a kidney or non-kidney voxel by texture matching. A probability kidney model is created using 10 segmented MRI data. The model is initially localized based on the intensity profiles in three directions. The weight functions are defined for each labeled voxel for each Wavelet-based, intensity-based, and model-based label. Consequently, each voxel has three labels and three weights for the Wavelet feature, intensity, and probability model. Using a 3D edge detection method, the model is re-localized and the segmented kidney is modified based on a region growing method in the model region. The probability model is re-localized based on the results and this loop continues until the segmentation converges. Experimental results with mouse MRI data show the good performance of the proposed method in segmenting the kidney in MR images.
Non-specific distribution of chemotherapeutic drugs (such as paclitaxel) is a major factor contributing to side effects and poor clinical outcomes in the treatment of human head and neck cancer. To develop novel drug delivery systems with enhanced efficacy and minimized adverse effects, we synthesized a ternary conjugate heparin-folic acid-paclitaxel (HFT), loaded with additional paclitaxel (T). The resulting nanoparticle, HFT-T, is expected to retain the antitumor activity of paclitaxel and specifically target folate receptor (FR)-expressing tumors, thereby increasing the bioavailability and efficacy of paclitaxel. In vitro experiments found that HFT-T selectively recognizes FR-positive human head and neck cancer cell line KB-3-1, displaying higher cytotoxicity compared to the free form of paclitaxel. In a subcutaneous KB-3-1 xenograft model, HFT-T administration enhanced the specific delivery of paclitaxel into tumor tissues and remarkably improved antitumor efficacy of paclitaxel. The average tumor volume in the HFT-T treatment group was 92.9±78.2mm3 vs 1670.3±286.1mm3 in the mice treated with free paclitaxel. Furthermore, paclitaxel tumors showed a resurgence of growth after several weeks of treatment, but this was not observed with HFT-T. This indicates that HFT-T could be more effective in preventing tumors from developing drug resistance. No significant acute in vivo toxicity was observed. These results indicate that specific delivery of paclitaxel with a ternary structured nanoparticle (HFT-T) targeting FR-positive tumor is a promising strategy to enhance chemotherapy efficacy and minimize adverse effects.
We present a 3D non-rigid registration algorithm for the potential use in combining PET/CT and transrectal ultrasound (TRUS) images for targeted prostate biopsy. Our registration is a hybrid approach that simultaneously optimizes the similarities from point-based registration and volume matching methods. The 3D registration is obtained by minimizing the distances of corresponding points at the surface and within the prostate and by maximizing the overlap ratio of the bladder neck on both images. The hybrid approach not only capture deformation at the prostate surface and internal landmarks but also the deformation at the bladder neck regions. The registration uses a soft assignment and deterministic annealing process. The correspondences are iteratively established in a fuzzy-to-deterministic approach. B-splines are used to generate a smooth non-rigid spatial transformation. In this study, we tested our registration with pre- and post-biopsy TRUS images of the same patients. Registration accuracy is evaluated using manual defined anatomic landmarks, i.e. calcification. The root-mean-squared (RMS) of the difference image between the reference and floating images was decreased by 62.6±9.1% after registration. The mean target registration error (TRE) was 0.88±0.16 mm, i.e. less than 3 voxels with a voxel size of 0.38×0.38×0.38 mm3 for all five patients. The experimental results demonstrate the robustness and accuracy of the 3D non-rigid registration algorithm.
We developed wavelet-based functional ANOVA (wfANOVA) as a novel approach for comparing neurophysiological signals that are functions of time. Temporal resolution is often sacrificed by analyzing such data in large time bins, increasing statistical power by reducing the number of comparisons. We performed ANOVA in the wavelet domain because differences between curves tend to be represented by a few temporally localized wavelets, which we transformed back to the time domain for visualization. We compared wfANOVA and ANOVA performed in the time domain (tANOVA) on both experimental electromyographic (EMG) signals from responses to perturbation during standing balance across changes in peak perturbation acceleration (3 levels) and velocity (4 levels) and on simulated data with known contrasts. In experimental EMG data, wfANOVA revealed the continuous shape and magnitude of significant differences over time without a priori selection of time bins. However, tANOVA revealed only the largest differences at discontinuous time points, resulting in features with later onsets and shorter durations than those identified using wfANOVA (P < 0.02). Furthermore, wfANOVA required significantly fewer (∼¼×; P < 0.015) significant F tests than tANOVA, resulting in post hoc tests with increased power. In simulated EMG data, wfANOVA identified known contrast curves with a high level of precision (r2 = 0.94 ± 0.08) and performed better than tANOVA across noise levels (P < <0.01). Therefore, wfANOVA may be useful for revealing differences in the shape and magnitude of neurophysiological signals (e.g., EMG, firing rates) across multiple conditions with both high temporal resolution and high statistical power.
Understanding the dynamics of redox elements in biologic systems remains a major challenge for redox signaling and oxidative stress research. Central redox elements include evolutionarily conserved subsets of cysteines and methionines of proteins which function as sulfur switches and labile reactive oxygen species (ROS) and reactive nitrogen species (RNS) which function in redox signaling. The sulfur switches depend upon redox environments in which rates of oxidation are balanced with rates of reduction through the thioredoxins, glutathione/glutathione disulfide and cysteine/cystine redox couples. These central couples, which we term redox control nodes, are maintained at stable but non-equilibrium steady states, are largely independently regulated in different subcellular compartments and are quasi-independent from each other within compartments. Disruption of the redox control nodes can differentially affect sulfur switches, thereby creating a diversity of oxidative stress responses. Systems biology provides approaches to address the complexity of these responses. In the present review, we summarize thiol/disulfide pathway, redox potential and rate information as a basis for kinetic modeling of sulfur switches. The summary identifies gaps in knowledge especially related to redox communication between compartments, definition of redox pathways and discrimination between types of sulfur switches. A formulation for kinetic modeling of GSH/GSSG redox control indicates that systems biology could encourage novel therapeutic approaches to protect against oxidative stress by identifying specific redox-sensitive sites which could be targeted for intervention.
BACKGROUND
Examination of spontaneously occurring phasic muscle activity from the human polysomnogram may have considerable clinical importance for patient care, yet most attempts to quantify the detection of such activity have relied upon laborious and intensive visual analyses. We describe in this study innovative signal processing approaches to this issue.
METHODS
We examined multiple features of surface electromyographic signals based on 16,200 individual 1-second intervals of low impedance sleep recordings. We validated which of those features most closely mirrored the careful judgments of trained human observers in making discriminations of the presence of short-lived (100-500 msec) phasic activity, and also examined which features provided maximal differences across 1-second intervals and which features were least susceptible to residual levels of amplifier noise.
RESULTS
Our data suggested particularly promising and novel features (e.g., Non-linear energy, 95th percentile of Spectral Edge Frequency) for developing automated systems for quantifying muscle activity during human sleep.
CONCLUSIONS
The EMG signals recorded from surface electrodes during sleep can be processed with techniques that reflect the visually based analyses of the human scorer but also offer potential for discerning far more subtle effects, Future studies will explore both the clinical utility of these techniques and their relative susceptibility to and/or independence from signal artifacts.
Fibrin is an extracellular matrix protein that is responsible for maintaining the structural integrity of blood clots. Much research has been done on fibrin in the past years to include the investigation of synthesis, structure-function, and lysis of clots. However, there is still much unknown about the morphological and structural features of clots that ensue from patients with disease. In this research study, experimental techniques are presented that allow for the examination of morphological differences of abnormal clot structures due to diseased states such as diabetes and sickle cell anemia. Our study focuses on the preparation and evaluation of fibrin clots in order to assess morphological differences using various experimental assays and confocal microscopy. In addition, a method is also described that allows for continuous, real-time calculation of lysis rates in fibrin clots. The techniques described herein are important for researchers and clinicians seeking to elucidate comorbid thrombotic pathologies such as myocardial infarctions, ischemic heart disease, and strokes in patients with diabetes or sickle cell disease.