• K →π matrix elements of the chromomagnetic operator on the lattice

      Constantinou, M; Costa, M; Frezzotti, R; Lubicz, V; Martinelli, G; Meloni, D; Panagopoulos, H; Simula, S (2018-04-01)
      © 2018 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the »https://creativecommons.org/licenses/by/4.0/» Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Funded by SCOAP 3 . We present the results of the first lattice QCD calculation of the K→π matrix elements of the chromomagnetic operator OCM=gsσμνGμνd, which appears in the effective Hamiltonian describing ΔS=1 transitions in and beyond the standard model. Having dimension five, the chromomagnetic operator is characterized by a rich pattern of mixing with operators of equal and lower dimensionality. The multiplicative renormalization factor as well as the mixing coefficients with the operators of equal dimension have been computed at one loop in perturbation theory. The power divergent coefficients controlling the mixing with operators of lower dimension have been determined nonperturbatively, by imposing suitable subtraction conditions. The numerical simulations have been carried out using the gauge field configurations produced by the European Twisted Mass Collaboration with Nf=2+1+1 dynamical quarks at three values of the lattice spacing. Our result for the B parameter of the chromomagnetic operator at the physical pion and kaon point is BCMOKπ=0.273(69), while in the SU(3) chiral limit we obtain BCMO=0.076(23). Our findings are significantly smaller than the model-dependent estimate BCMO∼1-4, currently used in phenomenological analyses, and improve the uncertainty on this important phenomenological quantity.
    • Kids Safe and Smokefree (KiSS) multilevel intervention to reduce child tobacco smoke exposure: Long-term results of a randomized controlled trial

      Lepore, SJ; Collins, BN; Coffman, DL; Winickoff, JP; Nair, US; Moughan, B; Bryant-Stephens, T; Taylor, D; Fleece, D; Godfrey, M; Lepore, Stephen J.|0000-0001-7370-6280; Coffman, Donna L|0000-0001-6305-6579 (2018-06-12)
      © 2018 by the authors. Licensee MDPI, Basel, Switzerland. Background: Pediatricians following clinical practice guidelines for tobacco intervention (“Ask, Advise, and Refer” [AAR]) can motivate parents to reduce child tobacco smoke exposure (TSE). However, brief clinic interventions are unable to provide the more intensive, evidence-based behavioral treatments that facilitate the knowledge, skills, and confidence that parents need to both reduce child TSE and quit smoking. We hypothesized that a multilevel treatment model integrating pediatric clinic-level AAR with individual-level, telephone counseling would promote greater long-term (12-month) child TSE reduction and parent smoking cessation than clinic-level AAR alone. Methods: Pediatricians were trained to implement AAR with parents during clinic visits and reminded via prompts embedded in electronic health records. Following AAR, parents were randomized to intervention (AAR + counseling) or nutrition education attention control (AAR + control). Child TSE and parent quit status were bioverified. Results: Participants (n = 327) were 83% female, 83% African American, and 79% below the poverty level. Child TSE (urine cotinine) declined significantly in both conditions from baseline to 12 months (p = 0.001), with no between-group differences. The intervention had a statistically significant effect on 12-month bioverified quit status (p = 0.029): those in the intervention group were 2.47 times more likely to quit smoking than those in the control. Child age was negatively associated with 12-month log-cotinine (p = 0.01), whereas nicotine dependence was positively associated with 12-month log-cotinine levels (p = 0.001) and negatively associated with bioverified quit status (p = 0.006). Conclusions: Pediatrician advice alone may be sufficient to increase parent protections of children from TSE. Integrating clinic-level intervention with more intensive individual-level smoking intervention is necessary to promote parent cessation.
    • Land use change in four landscapes in the Peruvian Amazon

      Center for International Forestry Research (CIFOR) (2020)
      This working paper uses remote sensing data and methods to characterize land cover change in four sites in the lowland Peruvian Amazon over a period of three decades (1987-2017). Multi-village landscapes were purposefully selected to include road accessible sites and others only accessible by river. Landscape analysis focused on buffers around the selected villages used to approximate the areas of influence of farmers in these communities. Deforestation in the Peruvian Amazon has been commonly attributed to agriculture expansion by smallholders. This belief falls short in acknowledging that the contribution of smallholder deforestation is mediated by others decisions around infrastructure development. In this analysis, road connected landscapes experienced greater loss of closed-canopy forest while closed canopy forest remained mostly stable in the river sites over the thirty year study period. Results indicated that closed canopy forest loss occurred in parallel with agricultural expansion at the road sites. The findings contribute to a more nuanced understanding of local land use dynamics and the role of regional infrastructure development as a driver of forest loss.
    • Land-use dynamics influence estimates of carbon sequestration potential in tropical second-growth forest

      Schwartz, Naomi B.; Uriarte, María; DeFries, Ruth; Gutiérrez-Vélez, Víctor Hugo; Pinedo-Vasquez, Miguel A. (2017-06-11)
      Many countries have made major commitments to carbon sequestration through reforestation under the Paris Climate Agreement, and recent studies have illustrated the potential for large amounts of carbon sequestration in tropical second-growth forests. However, carbon gains in second-growth forests are threatened by non-permanence, i.e. release of carbon into the atmosphere from clearing or disturbance. The benefits of second-growth forests require long-term persistence on the landscape, but estimates of carbon potential rarely consider the spatio-temporal landscape dynamics of second-growth forests. In this study, we used remotely sensed imagery from a landscape in the Peruvian Amazon to examine patterns of second-growth forest regrowth and permanence over 28 years (1985–2013). By 2013, 44% of all forest cover in the study area was second growth and more than 50% of second-growth forest pixels were less than 5 years old. We modeled probabilities of forest regrowth and clearing as a function of landscape factors. The amount of neighboring forest and variables related to pixel position (i.e. distance to edge) were important for predicting both clearing and regrowth. Forest age was the strongest predictor of clearing probability and suggests a threshold response of clearing probability to age. Finally, we simulated future trajectories of carbon sequestration using the parameters from our models. We compared this with the amount of biomass that would accumulate under the assumption of second-growth permanence. Estimates differed by 900 000 tonnes, equivalent to over 80% of Peru's commitment to carbon sequestration through 'community reforestation' under the Paris Agreement. Though the study area has more than 40 000 hectares of second-growth forest, only a small proportion is likely to accumulate significant carbon. Instead, cycles between forest and non-forest are common. Our results illustrate the importance of considering landscape dynamics when assessing the carbon sequestration potential of second-growth forests.
    • Landscape genetics reveals focal transmission of a human macroparasite

      Criscione, CD; Anderson, JD; Sudimack, D; Subedi, J; Upadhayay, RP; Jha, B; Williams, KD; Williams-Blangero, S; Anderson, TJC (2010-04-01)
      Macroparasite infections (e.g., helminths) remain a major human health concern. However, assessing transmission dynamics is problematic because the direct observation of macroparasite dispersal among hosts is not possible. We used a novel landscape genetics approach to examine transmission of the human roundworm Ascaris lumbricoides in a small human population in Jiri, Nepal. Unexpectedly, we found significant genetic structuring of parasites, indicating the presence of multiple transmission foci within a small sampling area (~14 km2). We analyzed several epidemiological variables, and found that transmission is spatially autocorrelated around households and that transmission foci are stable over time despite extensive human movement. These results would not have been obtainable via a traditional epidemiological study based on worm counts alone. Our data refute the assumption that a single host population corresponds to a single parasite transmission unit, an assumption implicit in many classic models of macroparasite transmission. Newer models have shown that the metapopulation-like pattern observed in our data can adversely affect targeted control strategies aimed at community-wide impacts. Furthermore, the observed metapopulation structure and local mating patterns generate an excess of homozygotes that can accelerate the spread of recessive traits such as drug resistance. Our study illustrates how molecular analyses complement traditional epidemiological information in providing a better understanding of parasite transmission. Similar landscape genetic approaches in other macroparasite systems will be warranted if an accurate depiction of the transmission process is to be used to inform effective control strategies. © 2010 Criscione et al.
    • Landscape of X chromosome inactivation across human tissues

      Tukiainen, T; Villani, AC; Yen, A; Rivas, MA; Marshall, JL; Satija, R; Aguirre, M; Gauthier, L; Fleharty, M; Kirby, A; Cummings, BB; Castel, SE; Karczewski, KJ; Aguet, F; Byrnes, A; Gelfand, ET; Getz, G; Hadley, K; Handsaker, RE; Huang, KH; Kashin, S; Lek, M; Li, X; Nedzel, JL; Nguyen, DT; Noble, MS; Segrè, AV; Trowbridge, CA; Abell, NS; Balliu, B; Barshir, R; Basha, O; Battle, A; Bogu, GK; Brown, A; Brown, CD; Chen, LS; Chiang, C; Conrad, DF; Cox, NJ; Damani, FN; Davis, JR; Delaneau, O; Dermitzakis, ET; Engelhardt, BE; Eskin, E; Ferreira, PG; Frésard, L; Gamazon, ER; Garrido-Martín, D; Gewirtz, ADH; Gliner, G; Gloudemans, MJ; Guigo, R; Hall, IM; Han, B; He, Y; Hormozdiari, F; Howald, C; Im, HK; Jo, B; Kang, EY; Kim, Y; Kim-Hellmuth, S; Lappalainen, T; Li, G; Li, X; Liu, B; Mangul, S; McCarthy, MI; McDowell, IC; Mohammadi, P; Monlong, J; Montgomery, SB; Muñoz-Aguirre, M; Ndungu, AW; Nicolae, DL; Nobel, AB; Oliva, M; Ongen, H; Palowitch, JJ; Panousis, N; Papasaikas, P; Park, Y; Parsana, P; Payne, AJ; Peterson, CB; Quan, J; Reverter, F; Sabatti, C; Saha, A; Sammeth, M; Scott, AJ; Shabalin, AA; Sodaei, R; Stephens, M; Stranger, BE; Strober, BJ; Sul, JH; Tsang, EK; Siminoff, Laura|0000-0002-6775-665X; Gardiner, Heather Marie|0000-0003-2017-991X (2017-10-11)
      © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of 'escape' from inactivation varying between genes and individuals1,2. The extent to which XCI is shared between cells and tissues remains poorly characterized3,4, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression5 and phenotypic traits6. Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 individuals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic diversity6,7. Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.
    • Large-Scale Discovery of Disease-Disease and Disease-Gene Associations

      Gligorijevic, D; Stojanovic, J; Djuric, N; Radosavljevic, V; Grbovic, M; Kulathinal, RJ; Obradovic, Z; Kulathinal, Rob|0000-0003-1907-2744 (2016-08-31)
      © 2016 The Author(s). Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies.
    • Large-scale network coupling with the fusiform cortex facilitates future social motivation

      Utevsky, AV; Smith, DV; Young, JS; Huettel, SA (2017-09-01)
      © 2017 Utevsky et al. Large-scale functional networks, as identified through the coordinated activity of spatially distributed brain regions, have become central objects of study in neuroscience because of their contributions to many processing domains. Yet, it remains unclear how these domain-general networks interact with focal brain regions to coordinate thought and action. Here, we investigated how the default-mode network (DMN) and executive control network (ECN), two networks associated with goal-directed behavior, shape task performance through their coupling with other cortical regions several seconds in advance of behavior. We measured these networks’ connectivity during an adaptation of the monetary incentive delay (MID) response-time task in which human participants viewed social and nonsocial images (i.e., pictures of faces and landscapes, respectively) while brain activity was measured using fMRI. We found that participants displayed slower reaction times (RTs) subsequent to social trials relative to nonsocial trials. To examine the neural mechanisms driving this subsequent-RT effect, we integrated independent components analysis (ICA) and a network-based psychophysiological interaction (nPPI) analysis; this allowed us to investigate task-related changes in network coupling that preceded the observed trial-to-trial variation in RT. Strikingly, when subjects viewed social rewards, an area of the fusiform gyrus (FG) consistent with the functionally-defined fusiform face area (FFA) exhibited increased coupling with the ECN (relative to the DMN), and the relative magnitude of coupling tracked the slowing of RT on the following trial. These results demonstrate how large-scale, domain-general networks can interact with focal, domain-specific cortical regions to orchestrate subsequent behavior.
    • Laser controlled charge-transfer reaction at low temperatures

      Petrov, A; Makrides, C; Kotochigova, S (2017-02-28)
      © 2017 Author(s). We study the low-temperature charge transfer reaction between a neutral atom and an ion under the influence of near-resonant laser light. By setting up a multi-channel model with field-dressed states, we demonstrate that the reaction rate coefficient can be enhanced by several orders of magnitude with laser intensities of 106 W/cm2 or larger. In addition, depending on laser frequency, one can induce a significant enhancement or suppression of the charge-exchange rate coefficient. For our intensities, multi-photon processes are not important.
    • Latitudinal clines of the human vitamin D receptor and skin color genes

      Tiosano, D; Audi, L; Climer, S; Zhang, W; Templeton, AR; Fernández-Cancio, M; Gershoni-Baruch, R; Sánchez-Muro, JM; El Kholy, M; Hochberg, Z (2016-05-01)
      © 2016 Tiosano et al. The well-documented latitudinal clines of genes affecting human skin color presumably arise from the need for protection from intense ultraviolet radiation (UVR) vs. the need to use UVR for vitamin D synthesis. Sampling 751 subjects from a broad range of latitudes and skin colors, we investigated possible multilocus correlated adaptation of skin color genes with the vitamin D receptor gene (VDR), using a vector correlation metric and network method called BlocBuster. We discovered two multilocus networks involving VDR promoter and skin color genes that display strong latitudinal clines as multilocus networks, even though many of their single gene components do not. Considered one by one, the VDR components of these networks show diverse patterns: no cline, a weak declining latitudinal cline outside of Africa, and a strong in- vs. out-of-Africa frequency pattern. We confirmed these results with independent data from HapMap. Standard linkage disequilibrium analyses did not detect these networks. We applied BlocBuster across the entire genome, showing that our networks are significant outliers for interchromosomal disequilibrium that overlap with environmental variation relevant to the genes' functions. These results suggest that these multilocus correlations most likely arose from a combination of parallel selective responses to a common environmental variable and coadaptation, given the known Mendelian epistasis among VDR and the skin color genes.
    • Learning atoms for materials discovery

      Zhou, Q; Tang, P; Liu, S; Pan, J; Yan, Q; Zhang, SC (2018-07-10)
      © 2018 National Academy of Sciences. All Rights Reserved. Exciting advances have been made in artificial intelligence (AI) during recent decades. Among them, applications of machine learning (ML) and deep learning techniques brought human-competitive performances in various tasks of fields, including image recognition, speech recognition, and natural language understanding. Even in Go, the ancient game of profound complexity, the AI player has already beat human world champions convincingly with and without learning from the human. In this work, we show that our unsupervised machines (Atom2Vec) can learn the basic properties of atoms by themselves from the extensive database of known compounds and materials. These learned properties are represented in terms of high-dimensional vectors, and clustering of atoms in vector space classifies them into meaningful groups consistent with human knowledge. We use the atom vectors as basic input units for neural networks and other ML models designed and trained to predict materials properties, which demonstrate significant accuracy.
    • Learning pair-wise gene functional similarity by multiplex gene expression maps

      An, L; Ling, H; Obradovic, Z; Smith, DJ; Megalooikonomou, V (2012-03-21)
      Background: The relationships between the gene functional similarity and gene expression profile, and between gene function annotation and gene sequence have been studied extensively. However, not much work has considered the connection between gene functions and location of a gene's expression in the mammalian tissues. On the other hand, although unsupervised learning methods have been commonly used in functional genomics, supervised learning cannot be directly applied to a set of normal genes without having a target (class) attribute.Results: Here, we propose a supervised learning methodology to predict pair-wise gene functional similarity from multiplex gene expression maps that provide information about the location of gene expression. The features are extracted from expression maps and the labels denote the functional similarities of pairs of genes. We make use of wavelet features, original expression values, difference and average values of neighboring voxels and other features to perform boosting analysis. The experimental results show that with increasing similarities of gene expression maps, the functional similarities are increased too. The model predicts the functional similarities between genes to a certain degree. The weights of the features in the model indicate the features that are more significant for this prediction.Conclusions: By considering pairs of genes, we propose a supervised learning methodology to predict pair-wise gene functional similarity from multiplex gene expression maps. We also explore the relationship between similarities of gene maps and gene functions. By using AdaBoost coupled with our proposed weak classifier we analyze a large-scale gene expression dataset and predict gene functional similarities. We also detect the most significant single voxels and pairs of neighboring voxels and visualize them in the expression map image of a mouse brain. This work is very important for predicting functions of unknown genes. It also has broader applicability since the methodology can be applied to analyze any large-scale dataset without a target attribute and is not restricted to gene expressions. © 2012 An et al.; licensee BioMed Central Ltd.
    • Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval

      Yuan, L; Woodard, A; Ji, S; Jiang, Y; Zhou, ZH; Kumar, S; Ye, J; Kumar, Sudhir|0000-0002-9918-8212 (2012-05-23)
      Background: Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.Results: In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.Conclusions: We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results. © 2012 Yuan et al.; licensee BioMed Central Ltd.
    • Learning to interpret topographic maps: Understanding layered spatial information

      Atit, K; Weisberg, SM; Newcombe, NS; Shipley, TF (2016-12-01)
      © 2016, The Author(s). Abstract: Novices struggle to interpret maps that show information about continuous dimensions (typically latitude and longitude) layered with information that is inherently continuous but segmented categorically. An example is a topographic map, used in earth science disciplines as well as by hikers, emergency rescue operations, and other endeavors requiring knowledge of terrain. Successful comprehension requires understanding that continuous elevation information is categorically encoded using contour lines, as well as skill in visualizing the three-dimensional shape of the terrain from the contour lines. In Experiment 1, we investigated whether novices would benefit from pointing and tracing gestures that focus attention on contour lines and/or from three-dimensional shape gestures used in conjunction with three-dimensional models. Pointing and tracing facilitated understanding relative to text-only instruction as well as no instruction comparison groups, but shape gestures only helped understanding relative to the no instruction comparison group. Directing attention to the contour lines may help both in code breaking (seeing how the lines encode elevation) and in shape inference (seeing how the overall configuration of lines encodes shape). In Experiment 2, we varied the language paired with pointing and tracing gestures; key phrases focused either on elevation information or on visualizing shape. Participants did better on items regarding elevation when language highlighted elevation and better on items requiring shape when language highlighted shape. Thus, focusing attention using pointing and tracing gestures on contour lines may establish the foundation on which language can build to support learning.
    • Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton

      Koller, JR; Jacobs, DA; Ferris, DP; Remy, CD (2015-11-04)
      © 2015 Koller et al. Background: Robotic ankle exoskeletons can provide assistance to users and reduce metabolic power during walking. Our research group has investigated the use of proportional myoelectric control for controlling robotic ankle exoskeletons. Previously, these controllers have relied on a constant gain to map user's muscle activity to actuation control signals. A constant gain may act as a constraint on the user, so we designed a controller that dynamically adapts the gain to the user's myoelectric amplitude. We hypothesized that an adaptive gain proportional myoelectric controller would reduce metabolic energy expenditure compared to walking with the ankle exoskeleton unpowered because users could choose their preferred control gain. Methods: We tested eight healthy subjects walking with the adaptive gain proportional myoelectric controller with bilateral ankle exoskeletons. The adaptive gain was updated each stride such that on average the user's peak muscle activity was mapped to maximal power output of the exoskeleton. All subjects participated in three identical training sessions where they walked on a treadmill for 50 minutes (30 minutes of which the exoskeleton was powered) at 1.2 ms-1. We calculated and analyzed metabolic energy consumption, muscle recruitment, inverse kinematics, inverse dynamics, and exoskeleton mechanics. Results: Using our controller, subjects achieved a metabolic reduction similar to that seen in previous work in about a third of the training time. The resulting controller gain was lower than that seen in previous work (β=1.50±0.14 versus a constant β=2). The adapted gain allowed users more total ankle joint power than that of unassisted walking, increasing ankle power in exchange for a decrease in hip power. Conclusions: Our findings indicate that humans prefer to walk with greater ankle mechanical power output than their unassisted gait when provided with an ankle exoskeleton using an adaptive controller. This suggests that robotic assistance from an exoskeleton can allow humans to adopt gait patterns different from their normal choices for locomotion. In our specific experiment, subjects increased ankle power and decreased hip power to walk with a reduction in metabolic cost. Future exoskeleton devices that rely on proportional myolectric control are likely to demonstrate improved performance by including an adaptive gain.
    • Left-Brain versus Right-Brain: Competing Conceptions of Creativity in Intellectual Property Law

      Mandel, Gregory N. (2010)
      An ongoing debate at the heart of intellectual property law pits those who argue for efficiency objectives against those who seek to advance other social goals. Proponents of the former model focus on the need for intellectual property regimes to provide incentives to creators, while proponents of the latter aspire to protect creators’ natural rights or secure an environment for greater human flourishing. Both observers and participants in these disputes typically lose sight of a common ambition underlying these competing conceptions of intellectual property law — the desire to promote creativity. Promoting creativity can serve both the incentive goals of intellectual property and advance more holistic personal, cultural, and social interests. Psychological, neurobiological, and cultural research now provides a wealth of information on how to promote creativity. Unfortunately, intellectual property law has failed to recognize these insights and instead remains moored in doctrine derived from archaic stereotypes about creativity and the creative process. These distorting stereotypes appear, for example, in the laws concerning joint authors and joint inventors. Based on historical and comparative law evidence, this Article argues that joint creator law has evolved, at least in part, not from its traditionally identified sources, but from commonly held stereotypes about left-brain scientists versus right-brain artists engaging in fundamentally distinct creative processes. Modern research shows that these creativity stereotypes are false. As a result, joint creator law specifically, and intellectual property law more generally, likely do not promote progress to the fullest extent feasible. Stereotype-driven doctrine appears to hinder creativity and valuable collaboration in both artistic and technological endeavors. Leveraging these interdisciplinary teachings yields valuable insight for how to revise patent and copyright law to promote creativity more effectively.
    • Length-dependent prediction of protein in intrinsic disorder

      Peng, K; Radivojac, P; Vucetic, S; Dunker, AK; Obradovic, Z (2006-04-17)
      Background: Due to the functional importance of intrinsically disordered proteins or protein regions, prediction of intrinsic protein disorder from amino acid sequence has become an area of active research as witnessed in the 6th experiment on Critical Assessment of Techniques for Protein Structure Prediction (CASP6). Since the initial work by Romero et al. (Identifying disordered regions in proteins from amino acid sequences, IEEE Int. Conf. Neural Netw., 1997), our group has developed several predictors optimized for long disordered regions (>30 residues) with prediction accuracy exceeding 85%. However, these predictors are less successful on short disordered regions (≤30 residues). A probable cause is a length-dependent amino acid compositions and sequence properties of disordered regions. Results: We proposed two new predictor models, VSL2-M1 and VSL2-M2, to address this length-dependency problem in prediction of intrinsic protein disorder. These two predictors are similar to the original VSL1 predictor used in the CASP6 experiment. In both models, two specialized predictors were first built and optimized for short (≤30 residues) and long disordered regions (>30 residues), respectively. A meta predictor was then trained to integrate the specialized predictors into the final predictor model. As the 10-fold cross-validation results showed, the VSL2 predictors achieved well-balanced prediction accuracies of 81% on both short and long disordered regions. Comparisons over the VSL2 training dataset via 10-fold cross-validation and a blind-test set of unrelated recent PDB chains indicated that VSL2 predictors were significantly more accurate than several existing predictors of intrinsic protein disorder. Conclusion: The VSL2 predictors are applicable to disordered regions of any length and can accurately identify the short disordered regions that are often misclassified by our previous disorder predictors. The success of the VSL2 predictors further confirmed the previously observed differences in amino acid compositions and sequence properties between short and long disordered regions, and justified our approaches for modelling short and long disordered regions separately. The VSL2 predictors are freely accessible for non-commercial use at http://www.ist.temple.edu/disprot/predictorVSL2.php. © 2006 Peng et al; licensee BioMed Central Ltd.
    • Leptin/HER2 crosstalk in breast cancer: In vitro study and preliminary in vivo analysis

      Fiorio, E; Mercanti, A; Terrasi, M; Micciolo, R; Remo, A; Auriemma, A; Molino, A; Parolin, V; Di Stefano, B; Bonetti, F; Giordano, A; Cetto, GL; Surmacz, E; Giordano, Antonio|0000-0002-5959-016X (2008-10-22)
      Background: Obesity in postmenopausal women is associated with increased breast cancer risk, development of more aggressive tumors and resistance to certain anti-breast cancer treatments. Some of these effects might be mediated by obesity hormone leptin, acting independently or modulating other signaling pathways. Here we focused on the link between leptin and HER2. We tested if HER2 and the leptin receptor (ObR) can be coexpressed in breast cancer cell models, whether these two receptors can physically interact, and whether leptin can transactivate HER2. Next, we studied if leptin/ObR can coexist with HER2 in breast cancer tissues, and if presence of these two systems correlates with specific clinicopathological features. Methods: Expression of ObR, HER2, phospo-HER2 was assessed by immonoblotting. Physical interactions between ObR and HER2 were probed by immunoprecipitation and fluorescent immunostaining. Expression of leptin and ObR in breast cancer tissues was detected by immunohistochemistry (IHC). Associations among markers studied by IHC were evaluated using Fisher's exact test for count data. Results: HER2 and ObR were coexpressed in all studied breast cancer cell lines. In MCF-7 cells, HER2 physically interacted with ObR and leptin treatment increased HER2 phosphorylation on Tyr 1248. In 59 breast cancers, the presence of leptin was correlated with ObR (the overall association was about 93%). This result was confirmed both in HER2-positive and in HER2-negative subgroups. The expression of leptin or ObR was numerically more frequent in larger (> 10 mm) tumors. Conclusion: Coexpression of HER2 and the leptin/ObR system might contribute to enhanced HER2 activity and reduced sensitivity to anti-HER2 treatments. © 2008 Fiorio et al; licensee BioMed Central Ltd.
    • Lessons from the Cambodian Experience with Truth and Reconciliation

      Ciorciari, John D.; Ramji-Nogales, Jaya (2013-04)
      Written for a symposium on truth and reconciliation in South Korea, this article offers lessons from the Cambodian experience with truth and reconciliation. Cambodia might be a counter-intuitive case study given that it has never convened a formal truth and reconciliation commission, yet offers important lessons for South Korea and other states seeking to meet the needs of survivors of abusive regimes. We present two central claims drawn from the Cambodian experience of truth and reconciliation. First, local civil society should be engaged as a central player in truth and reconciliation initiatives. Second, the Cambodian example offers lessons about the role of institutional sequencing in transitional justice efforts, particularly the sometimes unexpected ways in which more traditional institutions create political space for more innovative and effective mechanisms.
    • Leveraging elastic instabilities for amplified performance: Spine-inspired high-speed and high-force soft robots

      Tang, Y; Chi, Y; Sun, J; Huang, TH; Maghsoudi, OH; Spence, A; Zhao, J; Su, H; Yin, J; Spence, Andrew|0000-0001-7352-0128 (2020-05-01)
      Copyright © 2020 The Authors, Soft machines typically exhibit slow locomotion speed and low manipulation strength because of intrinsic limitations of soft materials. Here, we present a generic design principle that harnesses mechanical instability for a variety of spine-inspired fast and strong soft machines. Unlike most current soft robots that are designed as inherently and unimodally stable, our design leverages tunable snap-through bistability to fully explore the ability of soft robots to rapidly store and release energy within tens of milliseconds. We demonstrate this generic design principle with three high-performance soft machines: High-speed cheetah-like galloping crawlers with locomotion speeds of 2.68 body length/s, high-speed underwater swimmers (0.78 body length/s), and tunable low-to-high-force soft grippers with over 1 to 103 stiffness modulation (maximum load capacity is 11.4 kg). Our study establishes a new generic design paradigm of next-generation high-performance soft robots that are applicable for multifunctionality, different actuation methods, and materials at multiscales.