Miracle-dz/UniFAR-FTUs huggingface dataset:
Colocalization of l-Phenylalanine Ammonia-Lyase and Cinnamate 4-Hydroxylase for Metabolic Channeling in Phenylpropanoid Biosynthesis

Metabolic channeling has been proposed to occur at the entry point into plant phenylpropanoid biosynthesis. To determine whether isoforms of l-Phe ammonia-lyase (PAL), the first enzyme in the pathway, can associate with the next enzyme, the endomembrane-bound cinnamate 4-hydroxylase (C4H), to facilitate channeling, we generated transgenic tobacco (Nicotiana tabacum) plants independently expressing epitope-tagged versions of two PAL isoforms (PAL1 and PAL2) and C4H. Subcellular fractionation and protein gel blot analysis using epitope- and PAL isoform-specific antibodies indicated both microsomal and cytosolic locations of PAL1 but only cytosolic localization of PAL2. However, both PAL isoforms were microsomally localized in plants overexpressing C4H. These results, which suggest that C4H itself may organize the complex for membrane association of PAL, were confirmed using PAL-green fluorescent protein (GFP) fusions with localization by confocal microscopy. Coexpression of unlabeled PAL1 with PAL2-GFP resulted in a shift of fluorescence localization from endomembranes to cytosol in C4H overexpressing plants, whereas coexpression of unlabeled PAL2 with PAL1-GFP did not affect PAL1-GFP localization, indicating that PAL1 has a higher affinity for its membrane localization site than does PAL2. Dual-labeling immunofluorescence and fluorescence energy resonance transfer (FRET) studies confirmed colocalization of PAL and C4H. However, FRET analysis with acceptor photobleaching suggested that the colocalization was not tight.
Integration of multiscale dendritic spine structure and function data into systems biology models

Comprising 1011 neurons with 1014 synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement.
Beyond the Lines: Pictorial Reporting, Everyday Life, and the Crisis of Gilded Age America

Brown, Joshua. Beyond the Lines: Pictorial Reporting, Everyday Life, and the Crisis of Gilded Age America. Berkeley: University of California Press, 2002.361 pp. $49.95. Henry Carter changed American journalism. This immigrant wood engraver, born in 1821 in Suffolk, learned his trade at the Illustrated London News, where he distinguished himself by displaying, in author Joshua Brown's words, "the kind of speed, dexterity, inventiveness, and self-exploitation that were indispensable in running an illustrated newspaper. " By 1855, these qualities were evident in New York, where Carter, now reinvented as Frank Leslie, founded America's first pictorial weekly, a sometimes sensational publication that inspired Fletcher Harper to start a more genteel rival weekly and, more importantly, that changed the way Americans understood the world. As Frederic Hudson observed in 1873, the illustrated papers were "object-teaching" the multitudes, making the battlefields, the coronations, the corruptions of politicians, the balls, the race-course, the yacht race, the military, and naval heroes "familiar to every one. " Brown has written an illuminating-and long overdue-social history of Frank Leslie's Illustrated Newspaper, focusing on the shifting economic, racial, and class relations that helped shape the new practice of pictorial reporting. "The illustrated weeklies," Brown writes, "were an arena for contending representations of Gilded Age life, their wood-engraved pictures constituted by a complicated social negotiation among artists, editors, engravers, and readers. " Explaining such matters is tricky business, yet Brown offers detailed explorations of the ways that Leslie's illustrators attempted to construct representations of an increasingly fractured urban landscape and "balance the unbalanceable"-that is, to produce images that told a compelling story, projected Leslie 's own interests, and yet remained responsive to the desires and prejudices of its readers. The paper's coverage of Pennsylvania coal strikes in the 1870s demonstrates Brown's method. Many early images depicted the militant Irish strikers as ignorant and lazy. Later, however, the paper recognized some of its readers among the striking classes and began to restrain its anti-union line. Thus, Leslie's was compelled, as Brown puts it, "to follow a treacherous course, attempting to bridge the increasing political, social, and cultural differences among its varied reading public. …
Interactions between Obesity Status and Dietary Intake of Monounsaturated and Polyunsaturated Oils on Human Gut Microbiome Profiles in the Canola Oil Multicenter Intervention Trial (COMIT)

Long-term dietary fatty acid intake is believed to induce changes in the human gut microbiome which might be associated with human health or obesity status; however, considerable debate remains regarding the most favorable ratios of fatty acids to optimize these processes. The objective of this sub-study of a double-blinded randomized crossover clinical study, the canola oil multi-center intervention trial, was to investigate effects of five different novel oil blends fed for 30 days each on the intestinal microbiota in 25 volunteers with risk of metabolic syndrome. The 60 g treatments included three MUFA-rich diets: (1) conventional canola oil (Canola); (2) DHA-enriched high oleic canola oil (CanolaDHA); (3) high oleic canola oil (CanolaOleic); and two PUFA-rich diets: (4) a blend of corn/saﬄower oil (25:75) (CornSaff); and (5) a blend of flax/saﬄower oil (60:40) (FlaxSaff). Stool samples were collected at the end of each period. DNA was extracted and amplified for 16S rRNA gene pyrosequencing. A total of 17 phyla and 187 genera were identified. While five novel oil treatments failed to alter bacterial phyla composition, obese participants resulted in a higher proportion of Firmicutes to Bacteroidetes than overweight or normal weight groups (P = 0.01). Similarly at the genus level, overall bacterial distribution was highly associated with subjects’ body mass index (BMI). Treatment effects were observed between MUFA- and PUFA-rich diets, with the three MUFA diets elevating Parabacteroides, Prevotella, Turicibacter, and Enterobacteriaceae’s populations, while the two PUFA-rich diets favored the higher abundance of Isobaculum. High MUFA content feedings also resulted in an increase of Parabacteroides and a decrease of Isobaculum in obese, but not overweight subjects. Data suggest that BMI is a predominant factor in characterization of human gut microbiota profile, and that MUFA-rich and PUFA-rich diets impact the composition of gut microbiota at lower taxonomical levels mainly in obese subjects.
Deep Bottleneck Features for Spoken Language Identification

A key problem in spoken language identification (LID) is to design effective representations which are specific to language information. For example, in recent years, representations based on both phonotactic and acoustic features have proven their effectiveness for LID. Although advances in machine learning have led to significant improvements, LID performance is still lacking, especially for short duration speech utterances. With the hypothesis that language information is weak and represented only latently in speech, and is largely dependent on the statistical properties of the speech content, existing representations may be insufficient. Furthermore they may be susceptible to the variations caused by different speakers, specific content of the speech segments, and background noise. To address this, we propose using Deep Bottleneck Features (DBF) for spoken LID, motivated by the success of Deep Neural Networks (DNN) in speech recognition. We show that DBFs can form a low-dimensional compact representation of the original inputs with a powerful descriptive and discriminative capability. To evaluate the effectiveness of this, we design two acoustic models, termed DBF-TV and parallel DBF-TV (PDBF-TV), using a DBF based i-vector representation for each speech utterance. Results on NIST language recognition evaluation 2009 (LRE09) show significant improvements over state-of-the-art systems. By fusing the output of phonotactic and acoustic approaches, we achieve an EER of 1.08%, 1.89% and 7.01% for 30 s, 10 s and 3 s test utterances respectively. Furthermore, various DBF configurations have been extensively evaluated, and an optimal system proposed.
GeneGazer: A Toolkit Integrating Two Pipelines for Personalized Profiling and Biosignature Identification.

BACKGROUND Next-generation sequencing provides useful information about gene mutations, gene expression, epigenetic modification, microRNA expression, and copy number variations. More and more computing tools have been developed to analyze this large quantity of information. However, to test and find suitable analytical tools and integrate their results is tedious and challenging for users with little bioinformatics training. In the present study, we assembled the computing tools into a convenient toolkit to simplify the analysis and integration of data between bioinformatics tools. MATERIALS AND METHODS The toolkit, GeneGazer, comprises of two parts: the first, named Gaze_Profiler, was designed for personalized molecular profiling from next-generation sequencing data of paired samples; the other, named Gaze_BioSigner, was designed for the discovery of disease-associated biosignatures from expressional and mutational profiles of a cohort study. RESULTS To demonstrate the capabilities of Gaze_Profiler, we analyzed a pair (colon cancer and adjacent normal tissues) of RNA-sequencing data from one patient downloaded from the Sequencing Read Archive database and used them to profile somatic mutations and digital gene expression. In this case, alterations in the RAS/RAF/MEK/ERK signaling pathway (activated by KRAS G13D mutation) and canonical WNT signaling pathway (activated by truncated APC) were identified; no EGFR mutation or overexpression was found. These data suggested a limited efficacy of cetuximab in the patient. To demonstrate the ability of Gazer_BioSigner, we analyzed gene-expression data from 192 cancer tissues downloaded from The Cancer Genome Atlas and found that the activation of cAMP/PKA signaling, OCT-3/4 and SRF were associated with colon cancer progression and could be potential therapeutic targets. CONCLUSION GeneGazer is a reliable and robust toolkit for the analysis of data from high-throughput platforms and has potential for clinical application and biomedical research.
Communication Interface Generation For HW/SW Architecture In The STARSoC Environment

Mapping the application functionality to software and hardware requires automated methods to specify, generate and optimize the hardware, software and the interface architectures between them. In this paper, we present a methodology flow to hardware-software communication synthesis for system-on-a-chip (SoC) design through STARSoC (synthesis tool for adaptive and reconfigurable system-on-a-chip) tool for rapid prototyping. Our concept consists of a set of hardware and software processes, described in C-code, communicates through the streams channels. This methodology consists in analyzing dependences of data between processes and synthesis a custom architecture to interface it. Firstly, we presented our reference platform design proposed and the programming model supported. Secondly, we discussed the communication synthesis flow and we presented our architecture models synthesized. Finally, we presented the experimental results of our methodology and demonstrate the effectiveness of our automatic model generation for SoC through the image processing applications
Map-based vs. knowledge-based toponym disambiguation

Toponym Disambiguation, i.e. the task of assigning to place name their correct reference in the world, is getting more attention from many researchers. Many methods have been proposed since now, making use of different resources, techniques and sense inventories. Unfortunately, a gold standard for the evaluation of those methods is not yet available; therefore, it is difficult to verify the performance of such methods. Recently, a georeferenced version of WordNet has been developed, a resource that can be used to compare methods that are based on geographical data with methods that use textual information. In this paper we carry out a comparison between two of these methods. The results show that the knowledge-based method allowed us to obtain better results with a smaller context size. On the other hand, we observed that the map-based method needs a large context to obtain a good accuracy.
An Information-Controlled Transmission Power Adjustment Scheme for Collaborative Target Tracking

For target tracking applications, small wireless sensors provide accurate information since they can be deployed and operated near the phenomenon. These sensing devices have the opportunity of collaboration amongst themselves to improve the target localization and tracking accuracies. Distributed data fusion architecture provides a collaborative tracking framework. Due to the energy constraints of these small, sensing and wireless communicating devices, a common trend is to put some of them into a dormant state. In addition to a selective sensor activation strategy based on the maximum mutual information metric, in this paper, we devise the Information-Controlled Transmission Power (ICTP) adjustment in order to improve the energy savings. The essence of the proposed ICTP scheme for collaborative target tracking lies behind the idea that the sensors with more information use higher transmission powers than the sensors with less information in order to share their target state information with the neighboring sensors.
Smooth centile curves for skew and kurtotic data modelled using the Box–Cox power exponential distribution

The Box–Cox power exponential (BCPE) distribution, developed in this paper, provides a model for a dependent variable Y exhibiting both skewness and kurtosis (leptokurtosis or platykurtosis). The distribution is defined by a power transformation Yν having a shifted and scaled (truncated) standard power exponential distribution with parameter τ. The distribution has four parameters and is denoted BCPE (µ,σ,ν,τ). The parameters, µ, σ, ν and τ, may be interpreted as relating to location (median), scale (approximate coefficient of variation), skewness (transformation to symmetry) and kurtosis (power exponential parameter), respectively.
Ancient Origin and Molecular Features of the Novel Human T-Lymphotropic Virus Type 3 Revealed by Complete Genome Analysis

ABSTRACT Human T-lymphotropic virus type 3 (HTLV-3) is a new virus recently identified in two primate hunters in Central Africa. Limited sequence analysis shows that HTLV-3 is distinct from HTLV-1 and HTLV-2 but is genetically similar to simian T-lymphotropic virus type 3 (STLV-3). We report here the first complete HTLV-3 sequence obtained by PCR-based genome walking using uncultured peripheral blood lymphocytes from an HTLV-3-infected person. The HTLV-3(2026ND) genome is 8,917 bp long and is genetically equidistant from HTLV-1 and HTLV-2, sharing about 62% identity. Phylogenetic analysis of all gene regions confirms this relationship and shows that HTLV-3 falls within the diversity of STLV-3, suggesting a primate origin. However, HTLV-3(2026ND) is unique, sharing only 87% to 92% sequence identity with STLV-3. SimPlot and phylogenetic analysis did not reveal any evidence of genetic recombination with either HTLV-1, HTLV-2, or STLV-3. Molecular dating estimates that the ancestor of HTLV-3 is as old as HTLV-1 and HTLV-2, with an inferred divergence time of 36,087 to 54,067 years ago. HTLV-3 has a prototypic genomic structure, with all enzymatic, regulatory, and structural proteins preserved. Like STLV-3, HTLV-3 is missing a third 21-bp transcription element found in the long terminal repeats of HTLV-1 and HTLV-2 but instead contains a unique activator protein-1 transcription factor upstream of the 21-bp repeat elements. A PDZ motif, like that in HTLV-1, which is important for cellular signal transduction and transformation, is present in the C terminus of the HTLV-3 Tax protein. A basic leucine zipper region located in the antisense strand of HTLV-1, believed to play a role in viral replication and oncogenesis, was also found in the complementary strand of HTLV-3. The ancient origin of HTLV-3, the broad distribution of STLV-3 in Africa, and the propensity of STLVs to cross species into humans all suggest that HTLV-3 may be prevalent and support the need for expanded surveillance for this virus.
Bullying the media: Cultural and climato-economic readings of press repression versus press freedom

Journalists and media assistants in many places are murdered, imprisoned, censored, threatened, and similarly harrassed. Here I document that, and explain why, there are three climato-economic niches of press repression versus press freedom as part of broader syndromes of national culture. A 175-nation coding of documents by scientific analysts, survey responses from top executives in 123 countries, and participative observations by journalists in 155 countries led to basically the same findings. Cultures of press repression, survival values, and collectivism are most prevalent in poor countries with demanding cold or hot climates. Cultures of press freedom, self-expression values, and individualism are most prevalent in rich countries with demanding cold or hot climates. Intermediate cultures are most prevalent in poor and rich countries with temperate climates. Rival explanations in terms of a country's historic roots, population diversity, and societal inequality are ruled out and discussed.
Creating connections: Strategies to improve adolescent boys’ access and engagement with school-based health services

Abstract The aim of this grounded theory study was to investigate strategies used by school-based nurses to promote adolescent boys’ access to and engagement with school-based health services. Interviews were conducted with 10 school nurses in South-East Queensland, Australia. The central process identified was creating connections, encompassing three inter-related sub-processes: facilitating communication, mediating contextual issues and bridging cultural issues. These processes incorporate strategies that highlight ways school nurses can engage with boys, individually and collectively, to promote and facilitate help-seeking from school-based health services. Findings inform practice and guidelines for improving boys’ access to school-based health services.
Sensing Pressure Distribution on a Lower-Limb Exoskeleton Physical Human-Machine Interface

A sensory apparatus to monitor pressure distribution on the physical human-robot interface of lower-limb exoskeletons is presented. We propose a distributed measure of the interaction pressure over the whole contact area between the user and the machine as an alternative measurement method of human-robot interaction. To obtain this measure, an array of newly-developed soft silicone pressure sensors is inserted between the limb and the mechanical interface that connects the robot to the user, in direct contact with the wearer’s skin. Compared to state-of-the-art measures, the advantage of this approach is that it allows for a distributed measure of the interaction pressure, which could be useful for the assessment of safety and comfort of human-robot interaction. This paper presents the new sensor and its characterization, and the development of an interaction measurement apparatus, which is applied to a lower-limb rehabilitation robot. The system is calibrated, and an example its use during a prototypical gait training task is presented.
A smartphone prototype for touch interaction on the whole device surface

Previous research proposed a wide range of interaction methods and use cases based on the previously unused back side and edge of a smartphone. Common approaches to implementing Back-of-Device (BoD) interaction include attaching two smartphones back to back and building a prototype completely from scratch. Changes in the device's form factor can influence hand grip and input performance as shown in previous work. Further, the lack of an established operating system and SDK requires more effort to implement novel interaction methods. In this work, we present a smartphone prototype that runs Android and has a form factor nearly identical to an off-the-shelf smartphone. It further provides capacitive images of the hand holding the device for use cases such as grip-pattern recognition. We describe technical details and share source files so that others can re-build our prototype. We evaluated the prototype with 8 participants to demonstrate the data that can be retrieved for an exemplary grip classification.
Affine invariant surface evolutions for 3D image segmentation

In this paper we present an algorithm for 3D medical image segmentation based on an affine invariant flow. The algorithm is simple to implement and semi-automatic. The technique is based on active contours evolving in time according to intrinsic geometric measures of the image. The surface flow is obtained by minimizing a global energy with respect to an affine invariant metric. Affine invariant edge detectors for 3-dimensional objects are also computed which have the same qualitative behavior as the Euclidean edge detectors. Results on artificial and real MRI images show that the algorithm performs well, both in terms of accuracy and robustness to noise.