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A Multilevel Computational Characterization of Endophenotypes in Addiction
(Society for Neuroscience) Fiore, Vincenzo G.; Ognibene, D.; Adinoff, B.; Gu, Xiaosi; Fiore, Vincenzo G.; Gu, Xiaosi
Addiction is characterized by a profound intersubject (phenotypic) variability in the expression of addictive symptomatology and propensity to relapse following treatment. However, laboratory investigations have primarily focused on common neural substrates in addiction and have not yet been able to identify mechanisms that can account for the multifaceted phenotypic behaviors reported in the literature. To fill this knowledge gap theoretically, here we simulated phenotypic variations in addiction symptomology and responses to putative treatments, using both a neural model, based on cortico-striatal circuit dynamics, and an algorithmic model of reinforcement learning (RL). These simulations rely on the widely accepted assumption that both the ventral, model-based, goal-directed system and the dorsal, model-free, habitual system are vulnerable to extra-physiologic dopamine reinforcements triggered by addictive rewards. We found that endophenotypic differences in the balance between the two circuit or control systems resulted in an inverted-U shape in optimal choice behavior. Specifically, greater unbalance led to a higher likelihood of developing addiction and more severe drug-taking behaviors. Furthermore, endophenotypes with opposite asymmetrical biases among cortico-striatal circuits expressed similar addiction behaviors, but responded differently to simulated treatments, suggesting personalized treatment development could rely on endophenotypic rather than phenotypic differentiations. We propose our simulated results, confirmed across neural and algorithmic levels of analysis, inform on a fundamental and, to date, neglected quantitative method to characterize clinical heterogeneity in addiction. © 2018 Fiore et al.
Access to High School Arts Education: Why Student Participation Matters as much as Course Availability
(2013-11-04) Thomas, M. K.; Singh, Priyanka; Klopfenstein, K.; Henry, T.
There is renewed interest in the role of arts education in the curriculum of U.S. public schools not only because of the intrinsic value of the arts and its believed impact on achievement, but because cultivating creativity is thought to promote innovation and fuel economic growth. Still, we know little about basic access to arts education. Using individual-level administrative data from The University of Texas at Dallas Education Research Center (UTD-ERC), we develop several distinct indices of access to identify high schools rich in the arts. We find that high schools offering an extensive number of courses in the arts do not necessarily enjoy high rates of student participation. Policymakers who examine access based only on course counts in the arts will identify predominately large, non-rural high schools as having arts-rich environments. Evaluating arts programs along a single dimension, as is common in federal reports and other studies, fails to provide an accurate representation of access to arts education. Any examination of access to arts education should jointly consider course availability and student engagement in the arts. Policymakers can follow our approach and develop similar indices to assess the current state of arts education in their states.
Age-Related Similarities and Differences in Brain Activity Underlying Reversal Learning
(2013-05-29) Nashiro, Kaoru; Sakaki, Michiko; Nga, Lin; Mather, Mara
The ability to update associative memory is an important aspect of episodic memory and a critical skill for social adaptation. Previous research with younger adults suggests that emotional arousal alters brain mechanisms underlying memory updating; however, it is unclear whether this applies to older adults. Given that the ability to update associative information declines with age, it is important to understand how emotion modulates the brain processes underlying memory updating in older adults. The current study investigated this question using reversal learning tasks, where younger and older participants (age ranges 19-35 and 61-78, respectively) learn a stimulus-outcome association and then update their response when contingencies change. We found that younger and older adults showed similar patterns of activation in the frontopolar OFC and the amygdala during emotional reversal learning. In contrast, when reversal learning did not involve emotion, older adults showed greater parietal cortex activity than did younger adults. Thus, younger and older adults show more similarities in brain activity during memory updating involving emotional stimuli than during memory updating not involving emotional stimuli.;
Altered Amygdala Connectivity in Individuals with Chronic Traumatic Brain Injury and Comorbid Depressive Symptoms
(Frontiers Media S.A.) Han, Kihwan; Chapman, Sandra Bond; Krawczyk, Daniel C.; 0000 0003 5170 3614 (Chapman, SB); 0000-0002-4574-7306 (Han, K); Han, Kihwan; Chapman, Sandra Bond; Krawczyk, Daniel C.
Depression is one of the most common psychiatric conditions in individuals with chronic traumatic brain injury (TBI). Though depression has detrimental effects in TBI and network dysfunction is a "hallmark" of TBI and depression, there have not been any prior investigations of connectivity-based neuroimaging biomarkers for comorbid depression in TBI. We utilized resting-state functional magnetic resonance imaging to identify altered amygdala connectivity in individuals with chronic TBI (8 years post injury on average) exhibiting comorbid depressive symptoms (N = 31), relative to chronic TBI individuals having minimal depressive symptoms (N = 23). Connectivity analysis of these participant sub-groups revealed that the TBI-plus-depressive symptoms group showed relative increases in amygdala connectivity primarily in the regions that are part of the salience, somatomotor, dorsal attention, and visual networks P(voxel) < 0.01, P(cluster) < 0.025). Relative increases in amygdala connectivity in the TBI-plus-depressive symptoms group were also observed within areas of the limbic cortical mood regulating circuit (the left dorsomedial and right dorsolateral prefrontal cortices and thalamus) and the brainstem. Further analysis revealed that spatially dissociable patterns of correlation between amygdala connectivity and symptom severity according to subtypes (Cognitive and Affective) of depressive symptoms (p(voxel) < 0.01, p(duster) < 0.025). Taken together, these results suggest that amygdala connectivity may be a potentially effective neuroimaging biomarker for comorbid depressive symptoms in chronic TBI.
Altered Cerebellar Connectivity in Parkinson's Patients ON and OFF L-DOPA Medication
(Frontiers Research Foundation, 2015-04-21) Festini, Sara B.; Bernard, Jessica A.; Kwak, Youngbin; Peltier, Scott; Bohnen, Nicolaas I.; Müller, Martijn,L.T.M.; Dayalu, Praveen; Seidler, Rachael D.
Although nigrostriatal changes are most commonly affiliated with Parkinson's disease, the role of the cerebellum in Parkinson's has become increasingly apparent. The present study used lobule-based cerebellar resting state functional connectivity to (1) compare cerebellar-whole brain and cerebellar-cerebellar connectivity in Parkinson's patients both ON and OFF L-DOPA medication and controls, and to (2) relate variations in cerebellar connectivity to behavioral performance. Results indicated that, when contrasted to the control group, Parkinson's patients OFF medication had increased levels of cerebellar-whole brain and cerebellar-cerebellar connectivity, whereas Parkinson's patients ON medication had decreased levels of cerebellar-whole brain and cerebellar-cerebellar connectivity. Moreover, analyses relating levels of cerebellar connectivity to behavioral measures demonstrated that, within each group, increased levels of connectivity were most often associated with improved cognitive and motor performance, but there were several instances where increased connectivity was related to poorer performance. Overall, the present study found medication-variant cerebellar connectivity in Parkinson's patients, further demonstrating cerebellar changes associated with Parkinson's disease and the moderating effects of medication.;
An Auroral Boundary-Oriented Model of Subauroral Polarization Streams (SAPS)
(Amer Geophysical Union) Landry, Russell G.; Anderson, Phillip C.; 0000-0003-1320-4064 (Landry, RG); Landry, Russell G.; Anderson, Phillip C.
An empirical model of subauroral polarization stream (SAPS) electric fields has been developed using measurements of ion drifts and particle precipitation made by the Defense Meteorological Satellite Program from 1987 to 2012 and Dynamics Explorer 2 as functions of magnetic local time (MLT), magnetic latitude, the auroral electrojet index (AE), hemisphere, and day of year. Over 500,000 subauroral passes are used. This model is oriented in degree magnetic latitude equatorward of the aurora and takes median values instead of the mean to avoid the contribution of low occurrence frequency subauroral ion drifts so that the model is representative of the much more common, latitudinally broad, low-amplitude SAPS field. The SAPS model is in broad agreement with previous statistical efforts in the variation of the SAPS field with MLT and magnetic activity level, although the median field is weaker. Furthermore, we find that the median SAPS field is roughly conjugate in both hemispheres for all seasons, with a maximum in SAPS amplitude and width found for 1800-2000 MLT. The SAPS amplitude is found to vary seasonally only from about 1800-2000 MLT, maximizing in both hemispheres during equinox months. Because this feature exists despite controlling for the AE index, it is suggested that this is due to a seasonal variation in the flux tube averaged ionospheric conductance at MLT sectors where it is more likely that one flux tube footprint is in darkness while the other is in daylight.
Anaerobic Cysteine Degradation and Potential Metabolic Coordination in Salmonella Enterica and Escherichia Coli
(2018-08-24) Loddeke, Melissa; Schneider, Barbara; Oguri, Tamiko; Mehta, Iti; Xuan, Zhenyu; Reitzer, Lawrence J.; Loddeke, Melissa; Schneider, Barbara; Oguri, Tamiko; Mehta, Iti; Xuan, Zhenyu; Reitzer, Lawrence J.
Salmonella enterica has two CyuR-activated enzymes that degrade cysteine, i.e., the aerobic CdsH and an unidentified anaerobic enzyme; Escherichia coli has only the latter. To identify the anaerobic enzyme, transcript profiling was performed for E. coli without cyuR and with overexpressed cyuR. Thirty-seven genes showed at least 5-fold changes in expression, and the cyuPA (formerly yhaOM) operon showed the greatest difference. Homology suggested that CyuP and CyuA represent a cysteine transporter and an iron-sulfur-containing cysteine desulfidase, respectively. E. coli and S. enterica Delta cyuA mutants grown with cysteine generated substantially less sulfide and had lower growth yields. Oxygen affected the CyuR-dependent genes reciprocally; cyuP-lacZ expression was greater anaerobically, whereas cdsH-lacZ expression was greater aerobically. In E. coli and S. enterica, anaerobic cyuP expression required cyuR and cysteine and was induced by L-cysteine, D-cysteine, and a few sulfur-containing compounds. Loss of either CyuA or RidA, both of which contribute to cysteine degradation to pyruvate, increased cyuP-lacZ expression, which suggests that CyuA modulates intracellular cysteine concentrations. Phylogenetic analysis showed that CyuA homologs are present in obligate and facultative anaerobes, confirming an anaerobic function, and in archaeal methanogens and bacterial acetogens, suggesting an ancient origin. Our results show that CyuA is the major anaerobic cysteine-catabolizing enzyme in both E. coli and S. enterica, and it is proposed that anaerobic cysteine catabolism can contribute to coordination of sulfur assimilation and amino acid synthesis. IMPORTANCE Sulfur-containing compounds such as cysteine and sulfide are essential and reactive metabolites. Exogenous sulfur-containing compounds can alter the thiol landscape and intracellular redox reactions and are known to affect several cellular processes, including swarming motility, antibiotic sensitivity, and biofilm formation. Cysteine inhibits several enzymes of amino acid synthesis; therefore, increasing cysteine concentrations could increase the levels of the inhibited enzymes. This inhibition implies that control of intracellular cysteine levels, which is the immediate product of sulfide assimilation, can affect several pathways and coordinate metabolism. For these and other reasons, cysteine and sulfide concentrations must be controlled, and this work shows that cysteine catabolism contributes to this control.
Applying Deep Neural Networks and Ensemble Machine Learning Methods To Forecast Airborne Ambrosia Pollen
(MDPI AG, 2019-06-04) Zewdie, Gebreab K.; Lary, David J.; Levetin, E.; Garuma, G. F.; Zewdie, Gebreab K.; Lary, David J.
Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely alerts. This study presents a method for the robust estimation of the concentration of airborne Ambrosia pollen using a suite of machine learning approaches including deep learning and ensemble learners. Each of these machine learning approaches utilize data from the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric weather and land surface reanalysis. The machine learning approaches used for developing a suite of empirical models are deep neural networks, extreme gradient boosting, random forests and Bayesian ridge regression methods for developing our predictive model. The training data included twenty-four years of daily pollen concentration measurements together with ECMWF weather and land surface reanalysis data from 1987 to 2011 is used to develop the machine learning predictive models. The last six years of the dataset from 2012 to 2017 is used to independently test the performance of the machine learning models. The correlation coefficients between the estimated and actual pollen abundance for the independent validation datasets for the deep neural networks, random forest, extreme gradient boosting and Bayesian ridge were 0.82, 0.81, 0.81 and 0.75 respectively, showing that machine learning can be used to effectively forecast the concentrations of airborne pollen.
Are There Multiple Kinds of Episodic Memory? An fMRI Investigation Comparing Autobiographical and Recognition Memory Tasks
(Society for Neuroscience, 2018-08-20) Chen, H. -Y; Gilmore, A. W.; Nelson, Steven M.; McDermott, K. B.; Nelson, Steven M.
What brain regions underlie retrieval from episodic memory? The bulk of research addressing this question with fMRI has relied upon recognition memory for materials encoded within the laboratory. Another, less dominant tradition has used autobiographical methods, whereby people recall events from their lifetime, often after being cued with words or pictures. The current study addresses how the neural substrates of successful memory retrieval differed as a function of the targeted memory when the experimental parameters were held constant in the two conditions (except for instructions). Human participants studied a set of scenes and then took two types of memory test while undergoing fMRI scanning. In one condition (the picture memory test), participants reported for each scene (32 studied, 64 nonstudied) whether it was recollected from the prior study episode. In a second condition (the life memory test), participants reported for each scene (32 studied, 64 nonstudied) whether it reminded them of a specific event from their preexperimental lifetime. An examination of successful retrieval (yes responses) for recently studied scenes for the two test types revealed pronounced differences; that is, autobiographical retrieval instantiated with the life memory test preferentially activated the default mode network, whereas hits in the picture memory test preferentially engaged the parietal memory network as well as portions of the frontoparietal control network. When experimental cueing parameters are held constant, the neural underpinnings of successful memory retrieval differ when remembering life events and recently learned events.
ASL-MRICloud: An Online Tool for the Processing of ASL MRI Data
(Wiley, 2018-12-26) Li, Yang; Liu, Peiying; Li, Yue; Fan, Hongli; Su, Pan; Peng, Shin-Lei; Park, Denise C.; Rodrigue, Karen M.; Jiang, Hangyi; Faria, Andreia V.; Ceritoglu, Can; Miller, Michael; Mori, Susumu; Lu, Hanzhang; 74141364 (Park, DC); Park, Denise C.; Rodrigue, Karen M.
Arterial spin labeling (ASL) MRI is increasingly used in research and clinical settings. The purpose of this work is to develop a cloud-based tool for ASL data processing, referred to as ASL-MRICloud, which may be useful to the MRI community. In contrast to existing ASL toolboxes, which are based on software installation on the user's local computer, ASL-MRICloud uses a web browser for data upload and results download, and the computation is performed on the remote server. As such, this tool is independent of the user's operating system, software version, and CPU speed. The ASL-MRICloud tool was implemented to be compatible with data acquired by scanners from all major MRI manufacturers, is capable of processing several common forms of ASL, including pseudo-continuous ASL and pulsed ASL, and can process single-delay and multi-delay ASL data. The outputs of ASL-MRICloud include absolute and relative values of cerebral blood flow, arterial transit time, voxel-wise masks indicating regions with potential hyper-perfusion and hypo-perfusion, and an image quality index. The ASL tool is also integrated with a T₁-based brain segmentation and normalization tool in MRICloud to allow generation of parametric maps in standard brain space as well as region-of-interest values. The tool was tested on a large data set containing 309 ASL scans as well as on publicly available ASL data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study.
Assembly and Validation of Versatile Transcription Activator-Like Effector Libraries
(Nature Publishing Group, 2014-05-06) Li, Yi; Ehrhardt, Kristina; Zhang, Michael Q.; Bleris, Leonidas; 0000 0001 2535 9739 (Bleris, L); 0000 0001 1707 1372 (Zhang, MQ); 2012076942‏ (Bleris, L); 99086074‏ ‎(Zhang, MQ); Zhang, Michael Q.
The ability to perturb individual genes in genome-wide experiments has been instrumental in unraveling cellular and disease properties. Here we introduce, describe the assembly, and demonstrate the use of comprehensive and versatile transcription activator-like effector (TALE) libraries. As a proof of principle, we built an 11-mer library that covers all possible combinations of the nucleotides that determine the TALE-DNA binding specificity. We demonstrate the versatility of the methodology by constructing a constraint library, customized to bind to a known p53 motif. To verify the functionality in assays, we applied the 11-mer library in yeast-one-hybrid screens to discover TALEs that activate human SCN9A and miR-34b respectively. Additionally, we performed a genome-wide screen using the complete 11-mer library to confirm known genes that confer cycloheximide resistance in yeast. Considering the highly modular nature of TALEs and the versatility and ease of constructing these libraries we envision broad implications for high-throughput genomic assays. ;
Assessment of Unconstrained Cerebrovascular Reactivity Marker for Large Age-Range fMRI Studies
(Public Library of Science) Kannurpatti, S. S.; Motes, Michael A.; Biswal, B. B.; Rypma, Bart
Breath hold (BH), a commonly used task to measure cerebrovascular reactivity (CVR) in fMRI studies varies in outcome among individuals due to subject-physiology and/or BH-inspiration/expiration differences (i.e., performance). In prior age-related fMRI studies, smaller task-related BOLD response variability is observed among younger than older individuals. Also, a linear CVR versus task relationship exists in younger individuals which maybe useful to test the accuracy of CVR responses in older groups. Hence we hypothesized that subject-related physiological and/or BH differences, if present, may compromise CVR versus task linearity in older individuals. To test the hypothesis, empirical BH versus task relationships from motor and cognitive areas were obtained in younger (mean age = 26 years) and older (mean age = 58 years) human subjects. BH versus task linearity was observed only in the younger group, confirming our hypothesis. Further analysis indicated BH responses and its variability to be similar in both younger and older groups, suggesting that BH may not accurately represent CVR in a large age range. Using the resting state fluctuation of amplitude (RSFA) as an unconstrained alternative to BH, subject-wise correspondence between BH and RSFA was tested. Correlation between BH versus RSFA was significant within the motor but was not significant in the cognitive areas in the younger and was completely disrupted in both areas in the older subjects indicating that BH responses are constrained by subject-related physiology and/or performance-related differences. Contrasting BH to task, RSFA-task relationships were independent of age accompanied by age-related increases in CVR variability as measured by RSFA, not observed with BH. Together the results obtained indicate that RSFA accurately represents CVR in any age range avoiding multiple and yet unknown physiologic and task-related pitfalls of BH.
Automatic and Reproducible Positioning of Phase-Contrast MRI for the Quantification of Global Cerebral Blood Flow
(Public Library of Science) Liu, Peiying; Lu, Hanzhang; Filbey, Francesca M.; Pinkham, Amy E.; McAdams, Carrie J.; Adinoff, Bryon; Daliparthi, Vamsi; Cao, Yan; 0000 0001 3618 6298 (Filbey, FM); 0000 0001 2904 8428 (Cao, Y); 11522796 (Cao, Y); Filbey, Francesca M.; Cao, Yan
Phase-Contrast MRI (PC-MRI) is a noninvasive technique to measure blood flow. In particular, global but highly quantitative cerebral blood flow (CBF) measurement using PC-MRI complements several other CBF mapping methods such as arterial spin labeling and dynamic susceptibility contrast MRI by providing a calibration factor. The ability to estimate blood supply in physiological units also lays a foundation for assessment of brain metabolic rate. However, a major obstacle before wider applications of this method is that the slice positioning of the scan, ideally placed perpendicular to the feeding arteries, requires considerable expertise and can present a burden to the operator. In the present work, we proposed that the majority of PC-MRI scans can be positioned using an automatic algorithm, leaving only a small fraction of arteries requiring manual positioning. We implemented and evaluated an algorithm for this purpose based on feature extraction of a survey angiogram, which is of minimal operator dependence. In a comparative test-retest study with 7 subjects, the blood flow measurement using this algorithm showed an inter-session coefficient of variation (CoV) of 4.07 ± 3.03%. The Bland-Altman method showed that the automatic method differs from the manual method by between -8% and 11%, for 95% of the CBF measurements. This is comparable to the variance in CBF measurement using manually-positioned PC MRI alone. In a further application of this algorithm to 157 consecutive subjects from typical clinical cohorts, the algorithm provided successful positioning in 89.7% of the arteries. In 79.6% of the subjects, all four arteries could be planned using the algorithm. Chi-square tests of independence showed that the success rate was not dependent on the age or gender, but the patients showed a trend of lower success rate (p = 0.14) compared to healthy controls. In conclusion, this automatic positioning algorithm could improve the application of PC-MRI in CBF quantification.
Automatic Speech Activity Recognition from MEG Signals Using Seq2Seq Learning
(IEEE Computer Society, 2019-03) Dash, Debadatta; Ferrari, P.; Malik, S.; Wang, Jun; 0000-0001-7265-217X (Wang, J); Dash, Debadatta; Wang, Jun
Accurate interpretation of speech activity from brain signals is critical for understanding the relationship between neural patterns and speech production. Current research on speech activity recognition from the brain activity heavily relies on the region of interest (ROI) based functional connectivity analysis or source separation strategies to map the activity as a spatial localization of a brain function. Albeit effective, these methods require prior knowledge of the brain and expensive computational effort. In this study, we investigated automatic speech activity recognition from brain signals using machine learning. Neural signals of four subjects during four stages of a speech task (i.e., rest, perception, preparation, and production) were recorded using magnetoencephalography (MEG), which has an excellent temporal and spatial resolution. First, a deep neural network (DNN) was used to classify the four whole tasks from the MEG signals. Further, we trained a sequence to sequence (Seq2Seq) long short-term memory-recurrent neural network (LSTM-RNN) for continuous (sample by sample) prediction of the speech stages/tasks by leveraging its sequential pattern learning paradigm. Experimental results indicate the effectiveness of both DNN and LSTM-RNN for automatic speech activity recognition from MEG signals. © 2019 IEEE.
Basal Suppression of the Sonic Hedgehog Pathway by the G-Protein-Coupled Receptor Gpr161 Restricts Medulloblastoma Pathogenesis
(Cell Press, 2018-11-05) Shimada, Issei S.; Hwang, Sun-Hee; Somatilaka, Bandarigoda N.; Wang, Xin; Skowron, Patryk; Kim, Jiwoong; Kim, Min; Shelton, John M.; Rajaram, Veena; Xuan, Zhenyu; Taylor, Michael D.; Mukhopadhyay, Saikat; Xuan, Zhenyu
Sonic hedgehog (Shh) determines cerebellar granule cell (GC) progenitor proliferation and medulloblastoma pathogenesis. However, the pathways regulating GC progenitors during embryogenesis before Shh production by Purkinje neurons and their roles in tumorigenesis remain unclear. The cilium-localized G-protein-coupled receptor Gpr161 suppresses Shh-mediated signaling in the neural tube. Here, by deleting Gpr161 in mouse neural stem cells or GC progenitors, we establish Gpr161 as a tumor suppressor in Shh subtype medulloblastoma. Irrespective of Shh production in the cerebellum, Gpr161 deletion increased downstream activity of the Shh pathway by restricting Gli3-mediated repression, causing more extensive generation and proliferation of GC progenitors. Moreover, earlier deletion of Gpr161 during embryogenesis increased tumor incidence and severity. GC progenitor overproduction during embryogenesis from Gpr161 deletion was cilium dependent, unlike normal development. Low GPR161 expression correlated with poor survival of SHH subtype medulloblastoma patients. Gpr161 restricts GC progenitor production by preventing premature and Shh-dependent pathway activity, highlighting the importance of basal pathway suppression in tumorigenesis.
Better Speech and Hearing Month Proclamation
(12/8/2011) Newman, Eloyce; Callier Center for Communication Disorders
Bio-Inspired, Moisture-Powered Hybrid Carbon Nanotube Yarn Muscles
Kim, Shi Hyeong; Kwon, Cheong Hoon; Park, Karam; Mun, Tae Jin; Lepro, Xavier; Baughman, Ray H.; Spinks, Geoffrey M.; Kim, Seon Jeong; 0000 0003 5232 4253 (Baughman, RH); 0000-0002-0166-3127 (Lepró, X); Lepró, Xavier; Baughman, Ray H.
Hygromorph artificial muscles are attractive as self-powered actuators driven by moisture from the ambient environment. Previously reported hygromorph muscles have been largely limited to bending or torsional motions or as tensile actuators with low work and energy densities. Herein, we developed a hybrid yarn artificial muscle with a unique coiled and wrinkled structure, which can be actuated by either changing relative humidity or contact with water. The muscle provides a large tensile stroke (up to 78%) and a high maximum gravimetric work capacity during contraction (2.17 kJ kg⁻¹), which is over 50 times that of the same weight human muscle and 5.5 times higher than for the same weight spider silk, which is the previous record holder for a moisture driven muscle. We demonstrate an automatic ventilation system that is operated by the tensile actuation of the hybrid muscles caused by dew condensing on the hybrid yarn. This self-powered humidity-controlled ventilation system could be adapted to automatically control the desired relative humidity of an enclosed space.
Biothermal Sensing of a Torsional Artificial Muscle
(Royal Soc Chemistry, 2016-01-25) Lee, Sung-Ho; Kim, Tae Hyeob; Lima, M©rcio D.; Baughman, Ray H.; Kim, Seon Jeong; 0000 0003 5232 4253 (Baughman, RH); Lima, M©rcio D.; Baughman, Ray H.
Biomolecule responsive materials have been studied intensively for use in biomedical applications as smart systems because of their unique property of responding to specific biomolecules under mild conditions. However, these materials have some challenging drawbacks that limit further practical application, including their speed of response and mechanical properties, because most are based on hydrogels. Here, we present a fast, mechanically robust biscrolled twist-spun carbon nanotube yarn as a torsional artificial muscle through entrapping an enzyme linked to a thermally sensitive hydrogel, poly(N-isopropylacrylamide), utilizing the exothermic catalytic reaction of the enzyme. The induced rotation reached an equilibrated angle in less than 2 min under mild temperature conditions (25-37 ⁰C) while maintaining the mechanical properties originating from the carbon nanotubes. This biothermal sensing of a torsional artificial muscle offers a versatile platform for the recognition of various types of biomolecules by replacing the enzyme, because an exothermic reaction is a general property accompanying a biochemical transformation.
Building AuD externships
Cokely, Carol Lynn Geltman
Evaluation and analysis of externship program, which has been incorporated into Audiology curricula in the School of Behavioral and Brain Sciences at the University of Texas at Dallas.
A Carbon Nanotube-based Raman-imaging Immunoassay For Evaluating Tumor Targeting Ligands
(Royal Society of Chemistry, 2014-04-16) Bajaj, Pooja; Mikoryak, Carole; Wang, Ruhung; Bushdiecker II, David K.; Memon, Pauras; Draper, Rockford K.; Dieckmann, Gregg R.; Pantano, Paul; Musselman, Inga H.; Pantano, Paul; Musselman, Inga H.
Herein, we describe a versatile immunoassay that uses biotinylated single-walled carbon nanotubes (SWNTs) as a Raman label, avidin-biotin chemistry to link targeting ligands to the label, and confocal Raman microscopy to image whole cells. Using a breast tumor cell model, we demonstrate the usefulness of the method to assess membrane receptor/ligand systems by evaluating a monoclonal antibody, Her-66, known to target the Her2 receptors that are overexpressed on these cells. We present two-dimensional Raman images of the cellular distribution of the SWNT labels corresponding to the distribution of the Her2 receptors in different focal planes through the cell with validation of the method using immunofluorescence microscopy, demonstrating that the Her-66-SWNT complexes were targeted to Her2 cell receptors.;

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