Targeted Sensitization of Glioblastoma Multiforme Using AAAPT Technology

Glioblastoma Multiforme (GBM) is the most malignant type of all brain tumors. Current GBM treatment options include surgery, followed by radiation and chemotherapy. However, GBM can become resistant to therapy, resulting in tumor recurrence. GBM cells develop resistance to treatments by either downregulating cell death pathways (CD95) or upregulating cell survival pathways (NF-κB (p65)). Healthy tissues can be affected by the increased therapeutic dose. Therefore, it is important to develop a method that can only target GBM tumor cells, thereby reducing the non-specific uptake which will reduce the side effects. Here we demonstrate an application of novel priori activation of apoptosis pathways of tumor technology (AAAPT), which has been used to demonstrate the effect of targeted tumor sensitizers to make chemotherapy work at lower doses in breast, lung and prostate cancers. Treatment of GBM spheroids with AAAPT in 3D PEGDA microwells, showed an increase in cell death, an upregulation of cell death pathways, and a downregulation of cell survival pathways, in comparison to Temozolomide (TMZ), an oral alkylating agent, which is a commonly used chemotherapy in the treatment of GBM. The dose of AAAPT sensitizers may provide a promising method to increase treatment efficacy and reduce off-target toxicity, as an alternative to existing methods which cause significant off-target damage.

Investigating the Influence of Morphine and Cocaine on the Mesolimbic Pathway Using a Novel Microimaging Platform

Dopamine (DA)'s relationship with addiction is complex, and the related pathways in the mesocorticolimbic system are used to deliver DA, regulating both behavioral and perceptual actions. Specifically, the mesolimbic pathway connecting the ventral tegmental area (VTA) and the nucleus accumbens (NAc) is crucial in regulating memory, emotion, motivation, and behavior due to its responsibility to modulate dopamine. To better investigate the relationship between DA and addiction, more advanced mapping methods are necessary to monitor its production and propagation accurately and efficiently. In this study, we incorporate dLight1.2 adeno-associated virus (AAV) into our latest CMOS (complementary metal-oxide semiconductor) imaging platform to investigate the effects of two pharmacological substances, morphine and cocaine, in the NAc using adult mice. By implanting our self-fabricated CMOS imaging device into the deep brain, fluorescence imaging of the NAc using the dLight1.2 AAV allows for the visualization of DA molecules delivered from the VTA in real time. Our results suggest that changes in extracellular DA can be observed with this adapted system, showing potential for new applications and methods for approaching addiction studies. Additionally, we can identify the unique characteristic trend of DA release for both morphine and cocaine, further validating the underlying biochemical mechanisms used to modulate dopaminergic activation.

Processes for Designing Innovative Biomedical Hardware to Use in Space and on Earth

The new era of space exploration is increasing the astronaut's number and diversity in low orbit and beyond. The influx of such a diverse crew population will also increase the need for medical technologies to ensure safe and productive missions. Such a need represents a unique opportunity to innovate and develop diagnostics and treatment tools to meet future needs. Historically, terrestrial regulatory oversight of biomedical design processes was considered separate from spaceflight regulatory processes because it did not address spaceflight constraints. These constraints challenge the creative development of unique solutions for use in space. Translation between healthcare innovation in spaceflight to healthcare on Earth and vice versa requires understanding the commonalities, unique needs and constraints. This manuscript provides a framework for comparing Earth-space design processes and a perspective on the best practices to improve healthcare equity and health outcomes.

The Role of Neurons in Human Health and Disease

Neurons are the functional units of the nervous system [...].

Multi-Region Microdialysis Imaging Platform Revealed Dorsal Raphe Nucleus Calcium Signaling and Serotonin Dynamics during Nociceptive Pain

In this research, we combined our ultralight micro-imaging device for calcium imaging with microdialysis to simultaneously visualize neural activity in the dorsal raphe nucleus (DRN) and measure serotonin release in the central nucleus of the amygdala (CeA) and the anterior cingulate cortex (ACC). Using this platform, we observed brain activity following nociception induced by formalin injection in the mouse’s hind paw. Our device showed that DRN fluorescence intensity increased after formalin injection, and the increase was highly correlated with the elevation in serotonin release in both the CeA and ACC. The increase in calcium fluorescence intensity occurred during the acute and inflammatory phases, which suggests the biphasic response of nociceptive pain. Furthermore, we found that the increase in fluorescence intensity was positively correlated with mouse licking behavior. Lastly, we compared the laterality of pain stimulation and found that DRN fluorescence activity was higher for contralateral stimulation. Microdialysis showed that CeA serotonin concentration increased only after contralateral stimulation, while ACC serotonin release responded bilaterally. In conclusion, our study not only revealed the inter-regional serotonergic connection among the DRN, the CeA, and the ACC, but also demonstrated that our device is feasible for multi-site implantation in conjunction with a microdialysis system, allowing the simultaneous multi-modal observation of different regions in the brain.

Prenatal nicotine exposure alters gene expression profiles of neurons in the sub-regions of the VTA during early postnatal development

Brain growth occurs during the first 2 weeks of postnatal development in rats. This developmental period is equivalent to the third trimester of human gestation. Dendritic arborization, axonal growth, and gliogenesis are observed along with a strong maturation of neurotransmission during this critical development period. Furthermore, nicotine exposure during early development causes deficiencies in sensory and cognitive processing in adults. In this study, we further investigated the gene expression of neuron groups and the influence of perinatal nicotine exposure on gene expressions of neurons within the sub-regions of the ventral tegmental area (VTA) in 1 week, 2 week and 3-week-old rat pups. We exposed pregnant rats to nicotine perinatally on gestational day 7 through postnatal day 14. Pups are exposed to nicotine during pregnancy and through breastfeeding to investigate its effect in rat pups during early neuronal development. Real time PCR was used to find the relative expressions of gamma-aminobutyric acid (GABA), dopamine, and glutamate neuron markers within the three sub-regions of the VTA including the parabrachial pigmented nucleus (PBP), parainterfascicular (PIF), and paranigral nucleus (PN). Our results indicated that during early maturation, the dopamine marker tyrosine hydroxylase (TH) showed a consistently increased significance in PN sub-region compared to PIF and PBP. These results suggest that following perinatal nicotine exposure, VTA dopamine neurons, especially within the PN sub-region, are significantly excited starting from birth.

Automatic Upper-Limb Brunnstrom Recovery Stage Evaluation via Daily Activity Monitoring

Motor function assessment is crucial for post-stroke rehabilitation. Conventional evaluation methods are subjective, heavily depending on the experience of therapists. In light of the strong correlation between the stroke severity level and the performance of activities of daily living (ADLs), we explored the possibility of automatically evaluating the upper-limb Brunnstrom Recovery Stage (BRS) via three typical ADLs (tooth brushing, face washing and drinking). Multimodal data (acceleration, angular velocity, surface electromyography) were synchronously collected from 5 upper-limb-worn sensor modules. The performance of BRS evaluation system is known to be variable with different system parameters (e.g., number of sensor modules, feature types and classifiers). We systematically searched for the optimal parameters from different data segmentation strategies (five window lengths and four overlaps), 42 types of features, 12 feature optimization techniques and 9 classifiers with the leave-one-subject-out cross-validation. To achieve reliable and low-cost monitoring, we further explored whether it was possible to obtain a satisfactory result using a relatively small number of sensor modules. As a result, the proposed approach can correctly recognize the stages of all 27 participants using only three sensor modules with the optimized data segmentation parameters (window length: 7s, overlap: 50%), extracted features (simple square integral, slope sign change, modified mean absolute value 1 and modified mean absolute value 2), the feature optimization method (principal component analysis) and the logistic regression classifier. According to the literature, this is the first study to comprehensively optimize sensor configuration and parameters in each stage of the BRS classification framework. The proposed approach can serve as a factor-screening tool towards the automatic BRS classification and is promising to be further used at home.

Investigating miRNA-mRNA interactions and gene regulatory networks from VTA dopaminergic neurons following perinatal nicotine and alcohol exposure using Bayesian network analysis

MicroRNAs play an important role in gene regulation for many biological systems, including nicotine and alcohol addiction. However, the underlying mechanism behind miRNAs and mRNA interaction is not well characterized. Microarrays are commonly used to quantify the expression levels of mRNAs and/or miRNAs simultaneously. In this study, we performed a Bayesian network analysis to identify mRNA and miRNA interactions following perinatal exposure to nicotine and/or alcohol. We utilized three sets of microarray data to predict the regulation relationship between mRNA and miRNAs. Following perinatal alcohol exposure, we identified two miRNAs: miR-542-5p and miR-874-3p, that exhibited a strong mutual influence on several mRNA in gene regulatory pathways, mainly Axon guidance and Dopaminergic synapses. Finally, we confirmed our predicted addiction pathways based on the Bayesian network analysis with the widely used Kyoto Encyclopedia of Genes and Genomes (KEGG)-based database and identified comparable relevant miRNA-mRNA pairs. We believe the Bayesian network can provide insight into the complexity biological process related to addiction and can potentially be applied to other diseases.

Investigating the Influence of GABA Neurons on Dopamine Neurons in the Ventral Tegmental Area Using Optogenetic Techniques

Dopamine (DA) is the key regulator of reward behavior. The DA neurons in the ventral tegmental area (VTA) and their projection areas, which include the prefrontal cortex (PFC), nucleus accumbens (NAc), and amygdala, play a primary role in the process of reward-driven behavior induced by the drugs of addiction, including nicotine and alcohol. In our previous study, we developed a novel platform consisting of micro-LED array devices to stimulate a large area of the brain of rats and monkeys with photo-stimulation and a microdialysis probe to estimate the DA release in the PFC. Our results suggested that the platform was able to detect the increased level of dopamine in the PFC in response to the photo-stimulation of both the PFC and VTA. In this study, we used this platform to photo-stimulate the VTA neurons in both ChrimsonR-expressing (non-specific) wild and dopamine transporter (DAT)-Cre (dopamine specific) mice, and measured the dopamine release in the nucleus accumbens shell (NAcShell). We measured the DA release in the NAcShell in response to optogenetic stimulation of the VTA neurons and investigated the effect of GABAergic neurons on dopaminergic neurons by histochemical studies. Comparing the photo-stimulation frequency of 2 Hz with that of 20 Hz, the change in DA concentration at the NAcShell was greater at 20 Hz in both cases. When ChrimsonR was expressed specifically for DA, the release of DA at the NAcShell increased in response to photo-stimulation of the VTA. In contrast, when ChrimsonR was expressed non-specifically, the amount of DA released was almost unchanged upon photo-stimulation. However, for nonspecifically expressed ChrimsonR, intraperitoneal injection of bicuculline, a competitive antagonist at the GABA-binding site of the GABA_A receptor, also significantly increased the release of DA at the NAcShell in response to photo-stimulation of the VTA. The results of immunochemical staining confirm that GABAergic neurons in the VTA suppress DA activation, and also indicate that alterations in GABAergic neurons may have serious downstream effects on DA activity, NAcShell release, and neural adaptation of the VTA. This study also confirms that optogenetics technology is crucial to study the relationship between the mesolimbic dopaminergic and GABAergic neurons in a neural-specific manner.

Investigating the effects of chronic perinatal alcohol and combined nicotine and alcohol exposure on dopaminergic and non-dopaminergic neurons in the VTA

The ventral tegmental area (VTA) is the origin of dopaminergic neurons and the dopamine (DA) reward pathway. This pathway has been widely studied in addiction and drug reinforcement studies and is believed to be the central processing component of the reward circuit. In this study, we used a well-established rat model to expose mother dams to alcohol, nicotine-alcohol, and saline perinatally. DA and non-DA neurons collected from the VTA of the rat pups were used to study expression profiles of miRNAs and mRNAs. miRNA pathway interactions, putative miRNA-mRNA target pairs, and downstream modulated biological pathways were analyzed. In the DA neurons, 4607 genes were differentially upregulated and 4682 were differentially downregulated following nicotine-alcohol exposure. However, in the non-DA neurons, only 543 genes were differentially upregulated and 506 were differentially downregulated. Cell proliferation, differentiation, and survival pathways were enriched after the treatments. Specifically, in the PI3K/AKT signaling pathway, there were 41 miRNAs and 136 mRNAs differentially expressed in the DA neurons while only 16 miRNAs and 20 mRNAs were differentially expressed in the non-DA neurons after the nicotine-alcohol exposure. These results depicted that chronic nicotine and alcohol exposures during pregnancy differentially affect both miRNA and gene expression profiles more in DA than the non-DA neurons in the VTA. Understanding how the expression signatures representing specific neuronal subpopulations become enriched in the VTA after addictive substance administration helps us to identify how neuronal functions may be altered in the brain.

Deep Learning Classification of Systemic Sclerosis Skin Using the MobileNetV2 Model

Goal: Systemic sclerosis (SSc) is a rare autoimmune, systemic disease with prominent fibrosis of skin and internal organs. Early diagnosis of the disease is crucial for designing effective therapy and management plans. Machine learning algorithms, especially deep learning, have been found to be greatly useful in biology, medicine, healthcare, and biomedical applications, in the areas of medical image processing and speech recognition. However, the need for a large training data set and the requirement for a graphics processing unit (GPU) have hindered the wide application of machine learning algorithms as a diagnostic tool in resource-constrained environments (e.g., clinics). Methods: In this paper, we propose a novel mobile deep learning network for the characterization of SSc skin. The proposed network architecture consists of the UNet, a dense connectivity convolutional neural network (CNN) with added classifier layers that when combined with limited training data, yields better image segmentation and more accurate classification, and a mobile training module. In addition, to improve the computational efficiency and diagnostic accuracy, the highly efficient training model called “MobileNetV2,” which is designed for mobile and embedded applications, was used to train the network. Results: The proposed network was implemented using a standard laptop (2.5 GHz Intel Core i7). After fine tuning, our results showed the proposed network reached 100% accuracy on the training image set, 96.8% accuracy on the validation image set, and 95.2% on the testing image set. The training time was less than 5 hours. We also analyzed the same normal vs SSc skin image sets using the CNN using the same laptop. The CNN reached 100% accuracy on the training image set, 87.7% accuracy on the validation image set, and 82.9% on the testing image set. Additionally, it took more than 14 hours to train the CNN architecture. We also utilized the MobileNetV2 model to analyze an additional dataset of images and classified them as normal, early (mid and moderate) SSc or late (severe) SSc skin images. The network reached 100% accuracy on the training image set, 97.2% on the validation set, and 94.8% on the testing image set. Using the same normal, early and late phase SSc skin images, the CNN reached 100% accuracy on the training image set, 87.7% accuracy on the validation image set, and 82.9% on the testing image set. These results indicated that the MobileNetV2 architecture is more accurate and efficient compared to the CNN to classify normal, early and late phase SSc skin images. Conclusions: Our preliminary study, intended to show the efficacy of the proposed network architecture, holds promise in the characterization of SSc. We believe that the proposed network architecture could easily be implemented in a clinical setting, providing a simple, inexpensive, and accurate screening tool for SSc.

Astrocytes Decreased the Sensitivity of Glioblastoma Cells to Temozolomide and Bay 11-7082

Glioblastoma multiforme (GBM) is the most common malignant type of astrocytic tumors. GBM patients have a poor prognosis with a median survival of approximately 15 months despite the "Stupp" Regimen and high tumor recurrence due to the tumor resistance to chemotherapy. In this study, we co-cultured GBM cells with human astrocytes in three-dimensional (3D) poly(ethylene glycol) dimethyl acrylate (PEGDA) microwells to mimic the tumor microenvironment. We treated 3D co- and mono-cultured cells with Temozolomide (TMZ) and the nuclear factor-κB (NF-κB) inhibitor Bay 11-7082 and investigated the combined effect of the drugs. We assessed the expressions of glial fibrillary acidic protein (GFAP) and vimentin that play a role in the tumor malignancy and activation of the astrocytes as well as Notch-1 and survivin that play a role in GBM malignancy after the drug treatment to understand how astrocytes induced GBM drug response. Our results showed that in the co-culture, astrocytes increased GBM survival and resistance after combined drug treatment compared to mono-cultures. These data restated the importance of 3D cell culture to mimic the tumor microenvironment for drug screening.

Investigating the influence of perinatal nicotine and alcohol exposure on the genetic profiles of dopaminergic neurons in the VTA using miRNA-mRNA analysis

Nicotine and alcohol are two of the most commonly used and abused recreational drugs, are often used simultaneously, and have been linked to significant health hazards. Furthermore, patients diagnosed with dependence on one drug are highly likely to be dependent on the other. Several studies have shown the effects of each drug independently on gene expression within many brain regions, including the ventral tegmental area (VTA). Dopaminergic (DA) neurons of the dopamine reward pathway originate from the VTA, which is believed to be central to the mechanism of addiction and drug reinforcement. Using a well-established rat model for both nicotine and alcohol perinatal exposure, we investigated miRNA and mRNA expression of dopaminergic (DA) neurons of the VTA in rat pups following perinatal alcohol and joint nicotine-alcohol exposure. Microarray analysis was then used to profile the differential expression of both miRNAs and mRNAs from DA neurons of each treatment group to further explore the altered genes and related biological pathways modulated. Predicted and validated miRNA-gene target pairs were analyzed to further understand the roles of miRNAs within these networks following each treatment, along with their post transcription regulation points affecting gene expression throughout development. This study suggested that glutamatergic synapse and axon guidance pathways were specifically enriched and many miRNAs and genes were significantly altered following alcohol or nicotine-alcohol perinatal exposure when compared to saline control. These results provide more detailed insight into the cell proliferation, neuronal migration, neuronal axon guidance during the infancy in rats in response to perinatal alcohol/ or nicotine-alcohol exposure.

NF-κB inhibitor with Temozolomide results in significant apoptosis in glioblastoma via the NF-κB(p65) and actin cytoskeleton regulatory pathways

Glioblastoma (GBM) is the most malignant brain tumor characterized by intrinsic or acquired resistance to chemotherapy. GBM tumors show nuclear factor-κB (NF-κB) activity that has been associated with tumor formation, growth, and increased resistance to therapy. We investigated the effect of NF-κB inhibitor BAY 11-7082 with Temozolomide (TMZ) on the signaling pathways in GBM pathogenesis. GBM cells and patient-derived GBM cells cultured in 3D microwells were co-treated with BAY 11-7082 and TMZ or BAY 11-7082 and TMZ alone, and combined experiments of cell proliferation, apoptosis, wound healing assay, as well as reverse-phase protein arrays, western blot and immunofluorescence staining were used to evaluate the effects of drugs on GBM cells. The results revealed that the co-treatment significantly altered cell proliferation by decreasing GBM viability, suppressed NF-κB pathway and enhanced apoptosis. Moreover, it was found that the co-treatment of BAY 11-7082 and TMZ significantly contributed to a decrease in the migration pattern of patient-derived GBM cells by modulating actin cytoskeleton pathway. These findings suggest that in addition to TMZ treatment, NF-κB can be used as a potential target to increase the treatment's outcomes. The drug combination strategy, which is significantly improved by NF-κB inhibitor could be used to better understand the underlying mechanism of GBM pathways in vivo and as a potential therapeutic tool for GBM treatment.

Noise Reduction Technique for Single-Color Video Plethysmography Using Singular Spectrum Analysis

Recently, a contactless method for measuring a biological signal using a video camera has garnered attention. Especially, video plethysmography, a technique for obtaining a pulse wave from a video, is useful for managing the health of people on a daily basis. However, any body movement of a person subjected to the measurement leads to the generation of irregular noise in video plethysmography and reduces the accuracy of the recorded biological information, e.g., heart rate, during the measurement. Blind source separation is a popular technique for eliminating noise from the results of video plethysmography comprising different multiple-color channels. However, it is difficult to apply this technique to a single-color video such as a near-infrared video. Herein, a new method that combines singular spectrum analysis with the circular autocorrelation function is introduced to eliminate irregular noise in single-color video plethysmography. Applying the proposed method on videos collected from 39 individuals improved the estimation accuracy of instantaneous heart rate by approximately 44% over a conventional method using a linear filter. Furthermore, the proposed method also enabled more precise estimations of the heart rate than that achieved using multi-color video plethysmography.

Investigating the Effect of Perinatal Nicotine Exposure on Dopaminergic Neurons in the VTA Using miRNA Expression Profiles

Maternal smoking during pregnancy is associated with developmental, cognitive, and behavioral disorders, including low birth weight, attention deficit hyperactivity disorder, learning disabilities, and drug abuse later in life. Nicotine activates the reward-driven behavior characteristic of drug abuse. Dopaminergic (DA) neurons originating from the ventral tegmental area (VTA) of the brain, which are stimulated by nicotine and other stimuli, are widely implicated in the natural reward pathway that is known to contribute to addiction. In recent years, microRNAs have been implicated in disrupting regulatory mechanisms due to their capability of targeting multiple genes and thus inducing downstream effects along many pathways. In order to investigate miRNA expression of dopaminergic neurons from the VTA, we employed patch clamping to identify and harvest both DA and non-DA neurons from rats perinatally exposed to nicotine for use in single-cell RT-qPCR. Our data indicated that miR-140-5p and miR-140-3p were upregulated in DA neurons; while miR-140-3p and miR-212 were differentially expressed in non-DA neurons. A functional enrichment analysis was also performed on our miRNA-gene prediction network and predicted that our miRNAs target genes involved in drug response and neuroplasticity.

Investigating the genetic profile of dopaminergic neurons in the VTA in response to perinatal nicotine exposure using mRNA-miRNA analyses

Maternal smoking during pregnancy is associated with an increased risk of developmental, behavioral, and cognitive deficits. Nicotine, the primary addictive component in tobacco, has been shown to modulate changes in gene expression when exposure occurs during neurodevelopment. The ventral tegmental area (VTA) is believed to be central to the mechanism of addiction because of its involvement in the reward pathway. The purpose of this study was to build a genetic profile for dopamine (DA) neurons in the VTA and investigate the disruptions to the molecular pathways after perinatal nicotine exposure. Initially, we isolated the VTA from rat pups treated perinatally with either nicotine or saline (control) and collected DA neurons using fluorescent-activated cell sorting. Using microarray analysis, we profiled the differential expression of mRNAs and microRNAs from DA neurons in the VTA in order to explore potential points of regulation and enriched pathways following perinatal nicotine exposure. Furthermore, mechanisms of miRNA-mediated post-transcriptional regulation were investigated using predicted and validated miRNA-gene targets in order to demonstrate the role of miRNAs in the mesocorticolimbic DA pathway. This study provides insight into the genetic profile as well as biological pathways of DA neurons in the VTA of rats following perinatal nicotine exposure.

Ventral Tegmental Area Dopamine Neurons Firing Model Reveals Prenatal Nicotine Induced Alterations

The dopamine (DA) neurons found in the ventral tegmental area (VTA) are widely involved in the addiction and natural reward circuitry of the brain. Their firing patterns were shown to be important modulators of dopamine release and repetitive burst-like firing activity was highlighted as a major firing pattern of DA neurons in the VTA. In the present study we use a state space model to characterize the DA neurons firing patterns, and trace transitions of neural activity through bursting and non-bursting states. The hidden semi-Markov model (HSMM) framework, which we use, offers a statistically principled inference of bursting states and considers VTA DA firing patterns to be generated according to a Gamma process. Additionally, the explicit Gamma-based modeling of state durations allows efficient decoding of underlying neural information. Consequently, we decode and segment our single unit recordings from DA neurons in VTA according to the sequence of statistically discriminated HSMM states. The segmentation is used to study bursting state characteristics in data recorded from rats prenatally exposed to nicotine (6 mg/kg/day starting with gestational day 3) and rats from saline treated dams. Our results indicate that prenatal nicotine exposure significantly alters burst firing patterns of a subset of DA neurons in adolescent rats, suggesting nicotine exposure during gestation may induce severe effects on the neural networks involved in addiction and reward.

The Assessment of Stent Effectiveness Using a Wearable Beamforming MEMS Microphone Array System

Studies involving turbulent flow have been carried out in many parts of the cardiovascular system, and it has been widely reported that turbulence related to stenosis (narrowing) of arteries creates audible sounds, which may be analyzed to yield information about the nature and severity of the blockage. Results so far indicate that the high frequency content of the sounds generally increases with the degree of stenosis. In this paper, we designed and built an MEMs microphone array and a signal acquisition board to improve the detection of coronary occlusions using an approach based on the recording and analysis of isolated diastolic heart sounds associated with turbulent blood flow in occluded coronary arteries. The nonlinear dynamic analysis method based on approximate entropy has been proposed for the analysis of diastolic heart sounds from patients with single coronary occlusions, before and after stent placement procedures. The nonlinear dynamic analysis (approximate entropy) measures of the diastolic heart sounds recorded from eight patients with single coronary occlusions and two normal subjects were estimated. In addition, a spectral analysis based on the fast Fourier transform was used to estimate the energy content of the recorded signals. Results suggest the presence of high nonlinear (approximate entropy) values of diastolic heart sounds associated with coronary artery disease (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.01$ \end{document}) as well as significant differences in the energy content of the heart sound signals above and below 150 Hz (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.05$ \end{document}).

Gene expression profiling of midbrain dopamine neurons upon gestational nicotine exposure

Maternal smoking during pregnancy is associated with low birth weight, increased risk of stillbirth, conduct disorder, attention-deficit/hyperactivity disorder and neurocognitive deficits. Ventral tegmental area dopamine (DA) neurons in the mesocorticolimbic pathway were suggested to play a critical role in these pathological mechanisms induced by nicotine. Nicotine-mediated changes in genetic expression during pregnancy are of great interest for current researchers. We used patch clamp methods to identify and harvest DA and non-DA neurons separately and assayed them using oligonucleotide arrays to elucidate the alterations in gene expressions in these cells upon gestational nicotine exposure. Microarray analysis identified a set of 135 genes as significantly differentially expressed between DA and non-DA neurons. Some of the genes were found to be related to neurological disease pathways, such as Alzheimer's disease, Parkinson's disease and Huntington's disease. Significantly up-/down-regulated genes found in DA neurons were mostly related to G-protein-coupled protein receptor signaling and developmental processes. These alterations in gene expressions may explain, partially at least, the possible pathological mechanisms for the diseases induced by maternal smoking.

Engineering a Three-Dimensional In Vitro Drug Testing Platform for Glioblastoma

Three-dimensional (3D) in vivo cell culture modeling is quickly emerging as a platform to replace two-dimensional (2D) monolayer cell culture in vitro tests. Three-dimensional tumor models mimic physiological conditions and provide valuable insight of the tumor cell response to drug discovery application. In this study, we used poly(ethylene glycol) (PEG) hydrogel microwells to generate 3D brain cancer spheroids and studied their treatment with anticancer drugs in single or combination treatment. Glioblastoma (GBM) spheroids were grown through 14 days before infecting with two drugs: Pitavastatin and Irinotecan at various concentrations. A significant cell lysis was observed and cell viability decreased to lower than 7% when drugs were combined at the concentration Pitavastatin 10 μM and Irinotecan 50 μM to infect after 7 days. These findings demonstrate a promising platform—PEG hydrogel microwells—that should be an efficient way to test the drug sensitivity in vitro as well as application in different studies.

Investigating Glioblastoma Angiogenesis Using A 3D in Vitro GelMA Microwell Platform

Angiogenesis is an indispensable mechanism in physiological and pathological development of tumors that requires an adequate blood supply. Therefore, understanding the angiogenesis mechanism of tumors has become an important research area to develop reliable and effective therapies for the treatment of tumors. Although several in vivo and in vitro models were developed and used to study the underlying mechanism of angiogenesis, they showed limited success. Therefore, there is an urgent need to build a stable and cost-effective three-dimensional (3D) in vitro angiogenesis model to investigate the tumor formation. In this study, we designed a 3D in vitro angiogenesis model based on gelatin methacrylate (GelMA) hydrogel microwells to mimic an in vivo-like microenvironment for co-cultured glioblastoma and endothelial cells. Our results confirmed the in vitro formation of microtubules during the angiogenic process. We believe that our cost-effective platform can be used for the high-throughput screening of anti-angiogenesis drugs and even for the development of better treatment strategies.

Delta-24-RGD Induces Cytotoxicity of Glioblastoma Spheroids in Three Dimensional PEG Microwells

Glioblastoma (GBM) is the most aggressive brain tumor, with 12-15 months median survival time despite current treatment efforts. Among the alternative treatment approaches that have gained acceptance over the last decade is the use of replication-competent oncolytic adenoviruses, which are promising due to their relatively low toxicity and tumor-specific targeting. Three-dimensional (3D) tumor models can mimic the physiological microenvironment of GBM tumors and provide valuable information about the interaction between tumor cells and adenoviruses. Therefore, robust in vitro 3D tumor models are critical to investigate the mechanisms underlying tumor progression and explore the cytotoxicity effect of the adenovirus on tumor cells. In this study, we used a hydrogel microwell platform to generate in vitro 3D GBM spheroids and studied their interactions with the Delta-24-RGD adenovirus. The results showed that the cultured 3D spheroids were successfully infected by the Delta-24-RGD. A significant cell lysis was observed. Cell viability was decreased approximately 37%, 54% and 65% with 10, 50, and 100 MOIs, respectively. The infection of the Delta-24-RGD was found more effective on 3D spheroids when compared to 2D monolayer cell culture. These results implicate that our hydrogel microwell platform could provide a promising 3D model to investigate the oncolytic potential of the viruses in vitro.

Investigating the Influence of HUVECs in the Formation of Glioblastoma Spheroids in High-Throughput Three-Dimensional Microwells

Glioblastoma (GBM) is the most common form of primary brain tumor with a high infiltrative capacity, increased vascularity, and largely elusive tumor progression mechanism. The current GBM treatment methods do not increase the patient survival rate and studies using two-dimensional (2D) cell cultures and in vivo animal models to investigate GBM behavior and mechanism have limitations. Therefore, there is an increasing need for in vitro three-dimensional (3D) models that closely mimic in vivo microenvironment of the GBM tumors to understand the underlying mechanisms of the tumor progression. In this study we propose to use a 3D in vitro model to overcome these limitations, using poly (ethylene glycol) dimethyl acrylate (PEGDA) hydrogel-based microwells and co-culture GBM (U87) cells and endothelial cells (HUVEC) in the 3D microwells to provide a 3D in vitro simulation of the tumor microenvironment. Furthermore, we investigated the gene expression differences of co-cultures by quantitative real-time PCR. Our results suggested that the relative expression profiles of tumor angiogenesis markers, PECAM1/CD31, and VEGFR2, in co-cultures are consistent with in vivo GBM studies. Furthermore, we suggest that our microwell platform could provide robust and useful 3D co-culture models for high-throughput drug screening and treatment of the GBM.

Engineering a High-Throughput 3-D In Vitro Glioblastoma Model

Glioblastoma multiforme (GBM) is the most common and malignant primary brain tumor in adults because of its highly invasive behavior. The existing treatment for GBM, which involves a combination of resection, chemotherapy, and radiotherapy, has a very limited success rate with a median survival rate of <1 year. This is mainly because of the failure of early detection and effective treatment. We designed a novel 3-D GBM cell culture model based on microwells that could mimic in vitro environment and help to bypass the lack of suitable animal models for preclinical toxicity tests. Microwells were fabricated from simple and inexpensive polyethylene glycol material for the control of in vitro 3-D culture. We applied the 3-D micropatterning system to GBM (U-87) cells using the photolithography technique to control the cell spheroids' shape, size, and thickness. Our preliminary results suggested that uniform GBM spheroids can be formed in 3-D, and the size of these GBM spheroids depends on the size of microwells. The viability of the spheroids generated in this manner was quantitatively evaluated using live/dead assay and shown to improve over 21 days. We believe that in vitro 3-D cell culture model could help to reduce the time of the preclinical brain tumor growth studies. The proposed novel platform could be useful and cost-effective for high-throughput screening of cancer drugs and assessment of treatment responses.

Nicotine exposure increases the complexity of dopamine neurons in the parainterfascicular nucleus (PIF) sub-region of VTA

Background

Recent publications highlight differences within the sub-regions of the ventral tegmental area (VTA) including the parabrachial pigmented nucleus (PBP), parainterfascicular nucleus (PIF) and paranigral nucleus (PN) in the projections to the prefrontal cortex (PFC) and the glutamatergic pathway.

Methods

In order to characterize the effects of prenatal nicotine exposure on the mesocorticolimbic system of the rat offspring, local field potentials were recorded from 27 sites across the VTA of 9 rats aged 40–55 days. The extracellular VTA neural activities were analyzed using Approximate Entropy (ApEn) method. Approximate entropy values were then grouped according to each anatomic location including the PBP, PIF and PN.

Results

Our results have shown that the local field potentials corresponding to the neurons located in the PIF region of the VTA have ApEn values significantly higher (p = 2x10-4) in the maternal nicotine cases when compared to the saline.

Conclusion

Therefore, we speculate that the dopamine neurons located in the PIF sub-region of the VTA are very likely involved with the nicotine addiction.

Complexity of VTA DA neural activities in response to PFC transection in nicotine treated rats

Background

The dopaminergic (DA) neurons in the ventral tegmental area (VTA) are widely implicated in the addiction and natural reward circuitry of the brain. These neurons project to several areas of the brain, including prefrontal cortex (PFC), nucleus accubens (NAc) and amygdala. The functional coupling between PFC and VTA has been demonstrated, but little is known about how PFC mediates nicotinic modulation in VTA DA neurons. The objectives of this study were to investigate the effect of acute nicotine exposure on the VTA DA neuronal firing and to understand how the disruption of communication from PFC affects the firing patterns of VTA DA neurons.

Methods

Extracellular single-unit recordings were performed on Sprague-Dawley rats and nicotine was administered after stable recording was established as baseline. In order to test how input from PFC affects the VTA DA neuronal firing, bilateral transections were made immediate caudal to PFC to mechanically delete the interaction between VTA and PFC.

Results

The complexity of the recorded neural firing was subsequently assessed using a method based on the Lempel-Ziv estimator. The results were compared with those obtained when computing the entropy of neural firing. Exposure to nicotine triggered a significant increase in VTA DA neurons firing complexity when communication between PFC and VTA was present, while transection obliterated the effect of nicotine. Similar results were obtained when entropy values were estimated.

Conclusions

Our findings suggest that PFC plays a vital role in mediating VTA activity. We speculate that increased firing complexity with acute nicotine administration in PFC intact subjects is due to the close functional coupling between PFC and VTA. This hypothesis is supported by the fact that deletion of PFC results in minor alterations of VTA DA neural firing when nicotine is acutely administered.

Modeling carbachol-induced hippocampal network synchronization using hidden Markov models

In this work we studied the neural state transitions undergone by the hippocampal neural network using a hidden Markov model (HMM) framework. We first employed a measure based on the Lempel-Ziv (LZ) estimator to characterize the changes in the hippocampal oscillation patterns in terms of their complexity. These oscillations correspond to different modes of hippocampal network synchronization induced by the cholinergic agonist carbachol in the CA1 region of mice hippocampus. HMMs are then used to model the dynamics of the LZ-derived complexity signals as first-order Markov chains. Consequently, the signals corresponding to our oscillation recordings can be segmented into a sequence of statistically discriminated hidden states. The segmentation is used for detecting transitions in neural synchronization modes in data recorded from wild-type and triple transgenic mice models (3xTG) of Alzheimer's disease (AD). Our data suggest that transition from low-frequency (delta range) continuous oscillation mode into high-frequency (theta range) oscillation, exhibiting repeated burst-type patterns, occurs always through a mode resembling a mixture of the two patterns, continuous with burst. The relatively random patterns of oscillation during this mode may reflect the fact that the neuronal network undergoes re-organization. Further insight into the time durations of these modes (retrieved via the HMM segmentation of the LZ-derived signals) reveals that the mixed mode lasts significantly longer (p < 10(-4)) in 3xTG AD mice. These findings, coupled with the documented cholinergic neurotransmission deficits in the 3xTG mice model, may be highly relevant for the case of AD.

Investigating the synchronization of hippocampal neural network in response to acute nicotine exposure

Previous studies suggested that γ oscillations in the brain are associated with higher order cognitive function including selective visual attention, motor task planning, sensory perception, working memory and dreaming REM sleep. These oscillations are mainly observed in cortical regions and also occur in neocortical and subcortical areas and the hippocampus. In this paper, we investigate the influence of acute exposure to nicotine on the complexity of hippocampal γ oscillations.

Using the approximate entropy method, the influence of acute nicotine exposure on the hippocampal γ oscillations was investigated. The hippocampal γ oscillations have been generated in response to the 100 Hz stimulus and isolated using the visual inspection and spectral analysis method. Our central hypothesis is that acute exposure to nicotine significantly reduces the complexity of hippocampal γ oscillations. We used brain-slice recordings and the approximate entropy method to test this hypothesis. The approximate entropy (complexity) values of the hippocampal γ oscillations are estimated from the 14 hippocampal slices. Our results show that it takes at least 100 msec to see any hippocampal activities in response to the 100 Hz stimulus. These patterns noticeably changed after 100 msec until 300 msec after the stimulus Finally, they were less prominent after 300 msec. We have analyzed the isolated hippocampal γ oscillations (between 150 and 250 msec after the stimulus) using the approximate entropy (ApEn) method. Our results showed that the ApEn (complexity) values of hippocampal γ oscillations during nicotine exposure were reduced compared to those of hippocampal γ oscillations during control, and washout. This reduction was much more significant in response to acute nicotine exposure (p < 0.05) compared to those during control and washout conditions. These results suggest that the neural firing becomes regular and the hippocampal networks become synchronized in response to nicotine exposure.

Decoding state transitions in hippocampal oscillatory activity in mice

Understanding the intricate dynamics of the hippocampal neural network, from which several types of neural oscillation rhythms arise, is an important step in uncovering the role of the hippocampus in the formation of memory. The different oscillation types commonly recorded in the hippocampus are thought to correspond to several states of neural network synchronization. Therefore, accurate segmentation and decoding of these underlying states provide useful insight on the rhythms' generation. In this study we use a framework based on Hidden Markov Models, coupled with a nonlinear dynamics method based on the Lempel-Ziv estimator. The method allows us to decode and model the neural state transitions. Network synchronization was induced by acute exposure to cholinergic agonist carbachol and oscillations were recorded from the Cornu Ammonis (CA1) region of the mouse hippocampus. Our results prove that deficits in cholinergic neuro-transmission found in triple transgenic mice (3xTG, as Alzheimer's disease animal model) lead to increased instability in the hippocampal neural network synchronization.

The effects of 2-APB on the time-frequency distributions of gamma oscillations in rat hippocampal slices

We investigated the influence of 2-APB (2-aminoethoxy-diphenylborate) acute exposure on hippocampal oscillations using time-frequency analysis methods including continuous wavelet transform and short-time Fourier transform. We hypothesized that acute exposure to 2-APB drastically reduced the hippocampal gamma oscillations. We estimated the hippocampal oscillations' time-frequency representations from 24 hippocampal slices in five rats. Our results indicated that it took at least 100 ms to see any hippocampal activities in response to the 100 Hz stimulus. The hippocampal oscillations' spectral energies dominated in the 31-60 Hz and 61-90 Hz frequency bands in the early time (100-200 ms) segment post-stimulus and in the 31-60 Hz and 61-90 Hz frequency bands after 200 ms until 400 ms post-stimulus. They were noticeably reduced in the late time segment (above 400 ms). The hippocampal oscillations' spectral energies in the 31-60 and 61-90 Hz frequency bands still dominated the early time segment after the acute 2-APB exposure. The 2-APB exposure never changed the energy content in all three frequency bands in the early time segment (p > 0.01). The exposure significantly reduced the energy content in both the mid-time segment and in the 31-60 Hz frequency band (p < 0.001) and in both the second time segment and in the 61-90 Hz frequency band (p < 0.01). Additionally, in the late time segment, the energy content in all three frequency bands was notably reduced post-drug exposure (p < 0.001).

Nonlinear dynamical analysis of carbachol induced hippocampal oscillations in mice

AIM

Hippocampal neuronal network and synaptic impairment underlie learning and memory deficit in Alzheimer's disease (AD) patients and animal models. In this paper, we analyzed the dynamics and complexity of hippocampal neuronal network synchronization induced by acute exposure to carbachol, a nicotinic and muscarinic receptor co-agonist, using the nonlinear dynamical model based on the Lempel-Ziv estimator. We compared the dynamics of hippocampal oscillations between wild-type (WT) and triple-transgenic (3xTg) mice, as an AD animal model. We also compared these dynamic alterations between different age groups (5 and 10 months). We hypothesize that there is an impairment of complexity of CCh-induced hippocampal oscillations in 3xTg AD mice compared to WT mice, and that this impairment is age-dependent.

METHODS

To test this hypothesis, we used electrophysiological recordings (field potential) in hippocampal slices.

RESULTS

Acute exposure to 100 micromol/L CCh induced field potential oscillations in hippocampal CA1 region, which exhibited three distinct patterns: (1) continuous neural firing, (2) repeated burst neural firing and (3) the mixed (continuous and burst) pattern in both WT and 3xTg AD mice. Based on Lempel-Ziv estimator, pattern (2) was significantly lower than patterns (1) and (3) in 3xTg AD mice compared to WT mice (P<0.001), and also in 10-month old WT mice compared to those in 5-month old WT mice (P<0.01).

CONCLUSION

These results suggest that the burst pattern (theta oscillation) of hippocampal network is selectively impaired in 3xTg AD mouse model, which may reflect a learning and memory deficit in the AD patients.

The effects of elevated body temperature on the complexity of the diaphragm EMG signals during maturation

In this paper, we examine the effect of elevated body temperature on the complexity of the diaphragm electromyography (EMGdia), the output of the respiratory neural network--using the approximate entropy method. The diaphragm EMG, EEG, EOG as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) in chronically instrumented rats were recorded at two postnatal ages: 25-35 days age (juvenile, n = 5) and 36-44 days age (early adult, n = 6) groups during control (36-37 degrees C), mild elevated body temperature (38 degrees C) and severe elevated body temperature (39-40 degrees C). Three to five trials of the recordings were performed at normal body temperature before raising the animal's core temperature by 1-4 degrees C with an electric heating pad. At the elevated temperature, another 3-5 trials were performed. Finally, the animal was cooled to the original temperature, and trials were again repeated. Complexity values of the diaphragm EMG signal were estimated and evaluated using the approximate entropy method (ApEn) over the ten consecutive breaths. Our results suggested that the mean approximate entropy values for the juvenile age group were 1.01 +/- 0.01 (standard error) during control, 0.91 +/- 0.02 during mild elevated body temperature and 0.81 +/- 0.02 during severe elevated body temperature. For the early adult age group, these values were 0.94 +/- 0.01 during control, 0.93 +/- 0.01 during mild elevated body temperature and 0.92 +/- 0.01 during severe elevated body temperature. Our results show that the complexity values and the durations of the diaphragm EMG (EMGdia) were significantly decreased when the elevated body temperature was shifted from control or mild to severe body temperature (p < 0.05) for the juvenile age group. However, for the early adult age group, an increase in body temperature slightly reduced the complexity measures and the duration of the EMGdia. But, these changes were not statistically significant. These results furthermore suggest that during maturation, the output of the central pattern generator becomes less complex probably because the elevated body temperature reduces the neural activity and alters the behavior of the central respiratory controller, making it more susceptible to sudden infant death syndrome (SIDS).

2-APB reduces the complexity of hippocampal gamma oscillations in rats

Previous studies suggested that gamma oscillations in the brain are associated with higher order cognitive function including selective visual attention, motor task planning, sensory perception, working memory and dreaming REM sleep. These oscillations are mainly observed in cortical regions and also occurs in neocortical and subcortical areas and the hippocampus. In this paper, we investigate the influence of acute exposure to 2-APB exposure on the complexity of hippocampal gamma gamma oscillations. Our central hypothesis is that acute exposure to 2 APB significantly reduce the hippocampal gamma oscillations. In order to test this hypothesis, we use brain-slice recordings and the advanced nonlinear dynamical analysis method based on the Lempel-Ziv estimator. Our nonlinear dynamical analysis of brain slice recordings results suggested that 2-APB exposure significantly reduces the hippocampal gamma oscillations.

Donor strand complementation governs intersubunit interaction of fimbriae of the alternate chaperone pathway

Fimbrial filaments assembled by distinct chaperone pathways share a common mechanism of intersubunit interaction, as elucidated for colonization factor antigen I (CFA/I), archetype of enterotoxigenic Escherichia coli (ETEC) Class 5 fimbriae. We postulated that a highly conserved beta-strand at the major subunit N-terminus represents the donor strand, analogous to interactions within Class I pili. We show here that CFA/I fimbriae utilize donor strand complementation to promote proper folding of and interactions between CFA/I subunits. We constructed a series of genetic variants of CfaE, the CFA/I adhesin, incorporating a C-terminal extension comprising a flexible linker and 10-19 of the N-terminal residues of CfaB, the major subunit. Variants with a donor strand complement (dsc) of >or= 12 residues were recoverable from periplasmic fractions. Genetic disruption of the donor beta-strand reduced CfaE recovery. A hexahistidine-tagged variant of dsc19CfaE formed soluble monomers, folded into beta-sheet conformation, displayed adhesion characteristic of CFA/I, and elicited antibodies that inhibited mannose-resistant haemagglutination by ETEC expressing CFA/I, CS4 and CS14 fimbriae. Immunoelectron microscopy indicated that CfaE was confined to the distal fimbrial tip. Our findings provide the basis to elucidate structure and function of this class of fimbrial adhesins and assess the feasibility of an adhesin-based vaccine.

The effects of morphine on the relationship between fetal EEG, breathing and blood pressure signals using fast wavelet transform

In this study, we introduce the fast wavelet transform (WT) as a method for investigating the effects of morphine on the electroencephalogram (EEG), respiratory activity and blood pressure in fetal lambs. Morphine was infused intravenously at 25 mg/h. The EEG, respiratory activity and blood pressure signals were analyzed using WT. We performed wavelet decomposition for five sets of parameters D2j where -1 < j < -5. The five series WTs represent the detail signal bandwidths: 1, 16-32 Hz; 2, 8-16 Hz; 3, 4-8 Hz; 4, 2-4 Hz; 5, 1-2 Hz. Before injection of the high-dose morphine, power in the EEG was high in all six frequency bandwidths. The respiratory and blood pressure signals showed common frequency components with respect to time and were coincident with the low-voltage fast activity (LVFA) EEG signal. Respiratory activity was observed during only some of the LVFA periods, and was completely absent during high-voltage slow activity (HVSA) EEG. The respiratory signal showed dominant power in the fourth wavelet band, and less power in the third and fifth bands. The blood pressure signal was also characterized by dominant power in the fourth wavelet band. This power was significantly increased during periods of respiratory activity. There was a strong relationship between fetal EEG, blood pressure and breathing movements. However, the injection of high-dose morphine resulted in a disruption of the normal cyclic pattern between the two EEG states and a significant increase in power in the first wavelet band. In addition, the high-dose drug resulted in a significant increase in the power of respiratory signal in the fourth and fifth wavelet bands, while power was reduced in the third wavelet band. Breathing activity was also continuous after the drug. The high-dose morphine also caused a temporary power shift from the third wavelet band to the fourth wavelet band for the 30-min period after injection of drug. Finally, high-dose morphine completely destroyed the correlation between EEG, breathing and blood pressure signals.

Investigating the effects of opioid drugs on electrocortical activity using wavelet transform

Fetal electrocortical activity (ECoG) is characterized by two distinct patterns: HVSA (high voltage, slow activity) and LVFA (low voltage, fast activity). Using the wavelet transform (WT), we recently reported that the frequency characteristics of these two ECoG patterns undergo significant maturational changes prior to birth (Akay et al. 1994a). We now report that fetal ECoG can also be significantly affected by pharmacological agents. In this paper, we compared the effects of two opioid drugs (morphine and [D-Pen2, D-Pen5]-enkephalin, DPDPE) on fetal ECoG, using the chronically instrumented fetal lamb model. Morphine was infused intravenously (i.v.) at 2.5 mg/h, while DPDPE was infused into the lateral cerebroventricle (i.c.v.) at 30 micrograms/h. The ECoG was analyzed using WT. We performed multi-resolution decomposition for four sets of parameters D2j where -1 < j < -4. The four series WTs represent the detail signal bandwidths: (1) 16-32 Hz, (2) 8-16 Hz, (3) 4-8 Hz, (4) 2-4 Hz. The data were subjected to statistical analysis using the Kolmogorov-Smirnov (KS) test. Both morphine and DPDPE resulted in a significant increase in power in the first wavelet band, while power was reduced in the second, third and fourth wavelet bands. In addition, both drugs resulted in a disruption of the normal cyclic pattern between the two ECoG patterns. There was a difference in the time course of action between morphine and DPDPE. This is the first occasion in which continuous ECoG has been subjected to rigorous statistical analysis. The results suggest that the WT-KS method is most suitable for quantitating changes in the ECoG induced by pharmacological agents.

Investigating the effects of vasodilator drugs on the turbulent sound caused by femoral artery stenosis using short-term Fourier and wavelet transform methods

In this study, the effects of vasodilator drugs on the turbulent sound generation mechanisms during femoral artery stenoses were investigated using the wavelet analysis of the turbulent sounds to characterize these sounds before and after the injection of vasodilator drugs. Results showed that the injection of drugs drastically improved the diagnostic performance of the turbulent sounds in detecting stenoses by increasing the signal-to-noise ratio of the sounds. Results also suggested that the sound above 250 Hz was drastically increased in response to the injection of the vasodilator drug for the partially occluded cases. The turbulence sounds caused by partially occluded femoral arteries are directly related to the slope of baseline of blood flow and to the velocity of the flow. For the 0% occlusion case, initially, sounds were produced with the injection of drugs. However, the sounds totally disappeared when the slope of average blood flow was zero. These results show that the diagnostic performance of diastolic heart sounds associated with occluded arteries can be improved by using vasodilator drugs, which increase the acoustic energy in the first and second wavelet bandwidths due to the turbulence. The short-term Fourier transform (STFT) method was also applied to the same data base. Results using the STFT showed somewhat similar power distributions in that the acoustical power above 250 Hz was increased after the injection of drugs for the occluded cases. However, the WT method provided better time-frequency resolution than the STFT method, showing details of the change in the frequency characteristics with respect to time after the injection of drug.

Dynamics of the sounds caused by partially occluded femoral arteries in dogs

Previous studies have indicated that partially occluded arteries produce sounds due to turbulence. If these sounds from the coronary arteries could be detected externally, they would provide a simple approach to the detection of coronary artery disease. To confirm the hypothesis that coronary stenosis produces detectable acoustic correlates, sounds caused by a controlled occlusion of the femoral artery of dogs were detected and analyzed using both the fast Fourier transform (FFT) and the autoregressive (AR) methods. The femoral artery was chosen, since its size and flow approximate those of coronary arteries in humans. The poles of the AR spectra and the power ratios of different sections of the FFT and AR spectra were used to differentiate the degree of the stenosis. The results showed that high frequency acoustical power between 200 and 800 Hz is associated with the turbulence produced by the partially occluded femoral arteries of the dogs. Using the AR method, high acoustic power above 200 Hz increased when the degree of the occlusions increased. The poles and power ratios of the AR spectra differed according to the degree of stenosis. However, the high frequency acoustical power above 200 Hz did not increase above the 85% occlusion.

Time-frequency analysis of the electrocortical activity during maturation using wavelet transform

In this study, we introduce the wavelet transform (WT) as a method for characterizing the maturational changes in electrocortical activity in 24 fetal lambs ranging from 110-144 days gestation (term 145 days). The WT, based on multiresolution signal decomposition, is free of assumptions regarding the characteristics of the signal. The approximation of the electrocortical activity at resolutions varying from 2j+1 to 2j can be extracted by decomposing the signal on a wavelet orthonormal basis of L2(R). We performed multiresolution decomposition for four sets of parameters D2j, where -1 < j < -4. The four series WT represent the detail signal band-widths: (1) 16-32 Hz, (2) 8-16 Hz, (3) 4-8 Hz, (4) 2-4 Hz. The data were divided into three groups according to gestational age: 110-122 days (early), 123-135 days (middle), and 136-144 days (late). In the early group, the power was highest in the fourth signal bandwidth, with relatively low power in the other bands. Increase in gestational age was characterized by increased power in all four bandwidths. Comparison of the cumulative distribution function of the power in the four wavelet bands confirmed the presence of two statistically different patterns in all three age groups. These two patterns correspond to the visually identified patterns of HVSA (high-voltage slow activity) and LVFA (low-voltage fast activity). The earliest development change occurred in HVSA, with progressive increase in power in the 2-8 Hz band. Later changes occurred in LVFA, with a significant increase in power in the 16-32 Hz band.(ABSTRACT TRUNCATED AT 250 WORDS)

Noninvasive acoustical detection of coronary artery disease: a comparative study of signal processing methods

Previous studies have indicated heart sounds may contain information useful in the detection of occluded coronary arteries. During diastole, coronary blood flow is maximum, and the sounds associated with turbulent blood flow through partially occluded coronary arteries should be detectable. In order to detect such sounds, recordings of diastolic heart sound segments were analyzed by using four signal processing techniques; the Fast Fourier Transform (FFT), the Autoregressive (AR), the Autoregressive Moving Average (ARMA), and the Minimum-Norm (Eigen-vector) methods. To further enhance the diastolic heart sounds and reduce background noise, an Adaptive filter was used as a preprocessor. The power ratios of the FFT method and the poles of the AR, ARMA, and Eigen-vector methods were used to diagnose patients as diseased or normal arteries using a blind protocol without prior knowledge of the actual disease states of the patients to guard against human bias. Results showed that normal and abnormal records were correctly distinguished in 56 of 80 cases using the Fast Fourier Transform (FFT), in 63 of 80 cases using the AR, in 62 of 80 cases using the ARMA method, and in 67 of 80 cases using the Eigenvector method. Among all four methods, the Eigenvector methods showed the best diagnostic performance when compared with the FFT, AR, and ARMA methods. These results confirm that high frequency acoustic energy between 300 and 800 Hz is associated with coronary stenosis.

Noninvasive characterization of the sound pattern caused by coronary artery stenosis using FTF/FAEST zero tracking filters: normal/abnormal study

In this article, a new approach has been proposed to investigate the extraction of useful information from diastolic heart sounds caused by partially occluded coronary arteries. This method, which estimates and tracks the zeros (poles) of the diastolic heart sounds directly, takes advantage of the FTF/FAEST (Fast Transversal Filters/Fast a Posteriori Error Sequential) technique which possesses the fast convergence property of the Recursive Least Square (RLS) method and the computational simplicity of the Least Mean Square (LMS) method. In previous studies, the main assumption was that the diastolic heart sounds were a stationary process. Since the production of the heart sounds were a stationary process. Since the production of the heart sounds is not a stationary process, a new approach that performs well not only for stationary but also for nonstationary processes can be required. This requirement can be satisfied by the adaptive FTF/FAEST zero tracking method which provides fast and stable convergence as well as computational efficiency since the adaptive FTF/FAEST zero tracking method is based on the exact minimization of least squares criteria and the filter weights of this method are optimal at each time instant. The zero trajectories of the diastolic heart sounds were used to diagnose patients as diseased or normal. Results showed that the normal and abnormal records were incorrectly distinguished in only 6 of 35 cases using a blind protocol where analysis was done without knowledge of the actual disease states of the patients. The most discriminant time region of the zero trajectories of the diastolic heart sounds associated with coronary artery disease was between 200 and 300 msec after the second heart sound during the diastolic period.

Carotid-cardiac interaction: heart rate variability during the unblocking of the carotid artery

Multiresolution representations of the heart rate variability (HRV) using the wavelet transforms are proposed to characterize the autonomic nervous system regulation of cardio-vascular activity during carotid surgery. Results suggest that the power in all frequency bands was low during the surgery and increased after the declamping of the carotid artery.

Application of adaptive FTF/FAEST zero tracking filters to noninvasive characterization of the sound pattern caused by coronary artery stenosis before and after angioplasty

This article presents a new signal processing application that can be used for acoustical detection of coronary artery disease before and after angioplasty. The adaptive Autoregressive (AR) method based on the FTF/FAEST (Fast transversal filters/Fast a posteriori error sequential techniques) is used to track acoustical behavior associated with coronary occlusions. Using the amplitude trajectory of the second pole pair of this method, 9 out of 10 angioplasty patients were correctly identified using a blind protocol without prior knowledge of whether a given recording was made before and after angioplasty. These results were obtained from signals located between 200 and 300 msec after the end of the second heart sound during the diastolic period.

Noninvasive acoustical detection of coronary artery disease using the adaptive line enhancer method

Previous studies have indicated that heart sounds may contain information which is useful in the detection of occluded coronary arteries. Specifically, previous work based on analysing heart sounds recorded during the diastolic portion of the cardiac cycle, when blood flow through the coronary arteries is maximum, has shown that additional frequency components are present in patients with coronary artery disease. To further explore the application of advanced signal processing techniques to the noninvasive detection of coronary artery disease, a new signal-processing approach is presented using adaptive line enhancing (ALE) and spectral estimation of diastolic heart sounds taken from recordings made at the patient's bedside. This approach comprises two cascaded processes. In the first the ALE method is used to enhance the diastolic heart sounds and eliminate background noise. In the second process, either autoregressive (AR) or autoregressive moving average (ARMA) spectral methods are used to estimate the model parameters. Model parameters (the power spectral density (PSD) functions and the poles of the AR or ARMA method) were used to diagnose patients as diseased or normal. Results showed that normal and abnormal recordings were correctly identified in 39 of 43 cases using the new method. These results also confirm that high-frequency energy above 400 Hz is associated with coronary stenosis.