Miracle-dz/UniFAR-FTUs huggingface dataset:
Competition of Hydrophobic Peptides, Cytotoxic Drugs, and Chemosensitizers on a Common P-glycoprotein Pharmacophore as Revealed by Its ATPase Activity (*)

The aim of the present study was to demonstrate that the modulation of P-glycoprotein (Pgp) ATPase activity by peptides, drugs, and chemosensitizers takes place on a common drug pharmacophore. To this end, a highly emetine-resistant Chinese hamster ovary cell line was established, in which Pgp constituted 18% of plasma membrane protein. Reconstituted proteoliposomes, the Pgp content of which was up to 40%, displayed a basal activity of 2.6 ± 0.45 μmol of P/min/mg of protein, suggesting the presence of an endogenous Pgp substrate. This basal ATPase activity was stimulated (up to 5.2 μmol of P/min/mg of protein) by valinomycin and various Pgp substrates, whereas, to our surprise, gramicidin D, an established Pgp substrate, was inhibitory. Taking advantage of this novel inhibition of Pgp ATPase activity by gramicidin D, a drug competition assay was devised in which gramicidin D-inhibited Pgp ATPase was coincubated with increasing concentrations of various substrates that stimulate its ATPase activity. Gramicidin D inhibition of Pgp ATPase was reversed by Pgp substrates, including various cytotoxic agents and chemosensitizers. The inhibition of the basal ATPase activity and the reversal of gramicidin D inhibition of Pgp ATPase by its various substrates conformed to classical Michaelis-Menten competition. This competition involved an endogenous substrate, the inhibitory drug gramicidin D, and a stimulatory substrate. We conclude that the various MDR type substrates and chemosensitizers compete on a common drug binding site present in Pgp.
Effective Extraction of Visual Event-Related Pattern by Combining Template Matching With Ensemble Empirical Mode Decomposition

In the field of signal processing, it is always a major challenge to extract event-based weak or low signal in the presence of high background noise. Conventionally, this is achieved by trigger-based averaging, which suppresses uncorrelated background noise and unmasks the event related pattern. In some of the previouspapers, extraction of weak event related pattern is also achieved by decomposing the signal into a set of predefined basis functions, such as wavelets. We present here, a novel approach by combining template matching with the ensemble empirical mode decomposition (EEMD). The EEMD technique is applied to decompose the noisy data corresponding to single-trial event related potentials into the so-called intrinsic mode functions (IMFs). These functions are of the same length and in the same time domain as the original signal. Therefore, the EEMD technique preserves varying frequency content along the time axis. The effective extraction of the event-related pattern proposed in this paper relies on the elimination of IMFs, which capture the features corresponding to artifacts and brain signals, based on cross-correlation with a suitable template extracted from the evoked potential obtained by the conventional unrestricted averaging across a large number of trials. We illustrate the method and compare it with conventionally used single channel wavelet-based approach for denoising visual evoked potentials during the measurement of visual evoked electroencephalogram response.
Inferring relevance and presence of evidence in service-oriented and SaaS architectures

Gathering forensic evidence in distributed or cloud environments poses a number of legal, administrative, and technical challenges even at relatively coarse levels of granularity. For Software-as-a-Service (SaaS) and related Service-Oriented Architectures (SOA), however, the addition of loose binding lending such architectures their important flexibility and adaptability renders even identifying possible loci of evidence problematic. Moreover, even where the existence of evidence is known, its relevance for a given hypothesis may vary. We describe an approach to identify the existence of potential evidence based on a causality model of control flow, and seek to prioritise relevance based on a probabilistic graph model. This allows not only the explicit formulation of hypotheses and derivation of criteria for locating and retrieving evidence to be evaluated by Bayesian belief networks (BBN), but to minimise the otherwise highly problematic complexity of maximum a posteriori (MAP) hypotheses based on service orchestration and choreography semantics.
Expression of bovine lactoferrin N-lobe by the green alga, Chlorella vulgaris

The purpose of this study was to express bovine lactoferrin N-lobe in Chlorella vulgaris, a green microalga, using the pCAMBIA1304 vector. Chlorella-codon-optimized bovine lactoferrin N-lobe (Lfb-N gene) was cloned in the expression vector pCAMBIA1304, creating the plasmid pCAMLfb-N. pCAMLfb-N was then introduced into C. vulgaris by electro-transformation. Transformants were separated from BG-11 plates containing 20 hygromycin. Polymerase chain reaction was used to screen transformants harboring Lfb-N gene. Finally, total soluble protein was extracted from the transformants, and the expression of Lfb-N protein was detected using western blotting. Using this method, we successfully expressed bovine lactoferrin in C. vulgaris. Therefore, our results suggested that recombinant lactoferrin N-lobe, which has many uses in the biomedical and pharmaceutical industries, can be produced economically.
A System of Calibrating Microtomography for Use in Caries Research

Desktop microcomputed tomography (micro-CT) offers a non-invasive 3-dimensional analysis of structures and their physical properties. To date, the use of micro-CT has mostly involved qualitative observations, with the extent of quantitative analysis relying on automated internal calibration by the micro-CT control software. However, the value of such calibration is limited by machine drift. For an accurate quantitative use of micro-CT, it is recognized that external means of calibration are needed. A novel system of calibration standards, also known as ‘phantoms’, is presented. A range of low mineral concentration phantoms involving triethylene glycol dimethacrylate/glycerolate dimethacrylate resin mixed with commercial pure hydroxyapatite (HAP), from 0.07 to 1.05 g/cm3, was fabricated. Sintered HAP was impregnated with the same resin, producing phantoms with medium-level mineral concentrations up to 1.90 g/cm3. These phantoms were easy to create, proved accurate and stable with repeated use, and were found to mimic the composite nature of dental enamel and dentine structures under investigation.
Hemispheric balance in coding speech and non-speech sounds in Chinese participants

To study the role of neuromagnetic auditory ∼100-ms responses (N100m) in phonetic processing, we recorded N100m in 24 right-handed Chinese participants using a whole-head neuromagnetometer. The stimuli included vowel /a/ and consonant–vowels /ba/ and /da/, spoken by one Chinese speaker, and a 1-kHz tone. N100m to tones was larger in the right hemisphere, whereas that to speech sounds was bilaterally similar. The amplitude ratio of speech to non-speech N100m was larger in the left hemisphere. N100m dipoles in the left hemisphere were ∼2 mm more anterior for speech than for tone stimuli. The results suggest that N100m reflects both acoustics and phonetic processing. Moreover, the ratio of speech to non-speech activation in individual hemispheres may be useful for language lateralization.
Electric field Monte Carlo simulation of focused stimulated emission depletion beam, radially and azimuthally polarized beams for in vivo deep bioimaging

Abstract. An electric field Monte Carlo method is used to study the focal spot of a stimulated emission depletion (STED) beam, radially and azimuthally polarized beams in a turbid medium as a function of the scattering coefficient. To consider the diffraction of light of the wave nature, the wavefront is decomposed into a set of secondary spherical subwaves according to the Huygens principle. From the simulation results, we can find that the STED beam can still form a doughnut focal spot inside the turbid medium. These simulation results are important for the feasibility study of STED microscopy for in vivo deep bioimaging. Similarly, the focal spot for an azimuthally polarized beam can also keep a doughnut spot at the focal plane in a turbid medium.
Cloudet: A Cloud-Driven Visual Cognition of Large Streaming Data

Streaming data cognition has become a dominant problem in interactive visual analytics for event detection, meteorology, cosmology, security, and smart city applications. In order to interact with streaming data patterns in an elastic cloud environment, we present a new elastic framework for big data visual analytics in the cloud, the Cloudet. The Cloudet is a self-adaptive cloud-based platform that treats both data and compute nodes as elastic objects. The main objective is to readily achieve the scalability and elasticity of cloud computing platforms in order to process large streaming data and adapt to potential interactions between data stream features. Our main contributions include a robust cloud-based framework called the Cloudet. This is a cloud profile manager that attempts to optimize resource parameters in order to achieve expressivity, scalability, reliability, and the proper aggregation of the compute nodes and data streams into several density maps for the purpose of dynamic visualization.
Predicting Fault-Prone Modules in Embedded Systems Using Analogy-Based Classification Models

Embedded systems have become ubiquitous and essential entities in our ever growing high-tech world. The backbone of today's information-highway infrastructure are embedded systems such as telecommunication systems. They demand high reliability, so as to prevent severe consequences of failures including costly repairs at remote sites. Technology changes mandate that embedded systems evolve, resulting in a demand for techniques for improving reliability of their future system releases. Reliability models based on software metrics can be effective tools for software engineering of embedded systems, because quality improvements are so resource-consuming that it is not feasible to apply them to all modules. Identification of the likely fault-prone modules before system testing, can be effective in reducing the likelihood of faults discovered during operations. A software quality classification model is calibrated using software metrics from a past release, and is then applied to modules currently under development to estimate which modules are likely to be fault-prone. This paper presents and demonstrates an effective case-based reasoning approach for calibrating such classification models. It is attractive for software engineering of embedded systems, because it can be used to develop software reliability models using a faster, cheaper, and easier method. We illustrate our approach with two large-scale case studies obtained from embedded systems. They involve data collected from telecommunication systems including wireless systems. It is indicated that the level of classification accuracy observed in both case studies would be beneficial in achieving high software reliability of subsequent releases of the embedded systems.
Variation and infectivity neutralization in influenza

Worldwide epidemics of influenza are caused by viruses that normally infect other species, particularly waterfowl, and that contain haemagglutinin membrane glycoproteins (HAs) to which the human population has no immunity. Anti‐HA immunoglobulins neutralize influenza virus infectivity. In this review we outline structural differences that distinguish the HAs of the 16 antigenic subtypes (H1–16) found in viruses from avian species. We also describe structural changes in HA required for the effective transfer to humans of viruses containing three of them, H1, H2 and H3, in the 1918 (Spanish), the 1957 (Asian) and the 1968 (Hong Kong) pandemics, respectively. In addition, we consider changes that may be required before the current avian H5 viruses could pass from human to human.
Efficient Reduced-Reference Video Quality Meter

We present an efficient reduced-reference video quality assessment method based on local harmonic strength (LHS) feature. LHS is based on harmonics gain and loss information derived through the discriminative analysis of harmonics strength computed from gradient pictures. Harmonics gain and loss correspond with the two most prominent compression artifacts, namely blockiness and blurriness. To make the method effective for continuous monitoring of video quality, it is necessary to minimize the reduced-reference overhead data whilst keeping the accuracy of the quality meter sufficiently high. For the LHS-based method, we recommend quantization of the LHS feature, temporal sampling, and block selection method, either with or without segmentation-based block classification. A typical reduced-reference low overhead data rate (around 160-400 bps) with good prediction performance (0.86-0.88 Pearson correlations against mean opinion score) for broadcast type video sequences in VQEG Test Phase-I data sets has been achieved by the proposed method.
Plasmid stability is enhanced by higher-frequency pulses of positive selection

Plasmids accelerate bacterial adaptation by sharing ecologically important traits between lineages. However, explaining plasmid stability in bacterial populations is challenging owing to their associated costs. Previous theoretical and experimental studies suggest that pulsed positive selection may explain plasmid stability by favouring gene mobility and promoting compensatory evolution to ameliorate plasmid cost. Here we test how the frequency of pulsed positive selection affected the dynamics of a mercury-resistance plasmid, pQBR103, in experimental populations of Pseudomonas fluorescens SBW25. Plasmid dynamics varied according to the frequency of Hg2+ positive selection: in the absence of Hg2+ plasmids declined to low frequency, whereas pulses of Hg2+ selection allowed plasmids to sweep to high prevalence. Compensatory evolution to ameliorate the cost of plasmid carriage was widespread across the entire range of Hg2+ selection regimes, including both constant and pulsed Hg2+ selection. Consistent with theoretical predictions, gene mobility via conjugation appeared to play a greater role in promoting plasmid stability under low-frequency pulses of Hg2+ selection. However, upon removal of Hg2+ selection, plasmids which had evolved under low-frequency pulse selective regimes declined over time. Our findings suggest that temporally variable selection environments, such as those created during antibiotic treatments, may help to explain the stability of mobile plasmid-encoded resistance.
Oropharyngeal Colonization of HIV-Infected Outpatients in Taiwan by Yeast Pathogens

ABSTRACT Among 234 isolates comprising 26 different Candida species colonizing the oropharynx of 181 (54.3% of 399 surveyed) HIV-infected outpatients, 27 (11.7%) were fluconazole resistant. Antibacterial treatment was associated with increased rates of yeast colonization, while antiretroviral therapy and pneumococcal vaccination protected patients from yeast colonization.
Transition near the edge of a rotating disk

Abstract The rotating-disk boundary layer is generally considered as an example of a flow that displays a robust transition from laminar to turbulent régimes. By taking into account disks of finite radius, Healey (J. Fluid Mech., vol. 663, 2010, pp. 148–159) has predicted a stabilizing effect of the boundary condition, but Imayama et al. (J. Fluid Mech., vol. 716, 2013, pp. 638–657) were unable to confirm this prediction experimentally. Following these contradictory results, the present experimental investigation revisits the rotating-disk boundary layer, without any artificially imposed excitation, and studies in further detail the dynamics prevailing in the region closely surrounding the edge of the disk, as well as the flow beyond the disk. Azimuthal mean velocities and fluctuation amplitudes are recorded with small steps in radial and axial directions for a wide range of disk sizes. An objective criterion is used to define the onset of fluctuations consistently over a large data set. Two distinct mechanisms for the onset of fluctuations are identified. In particular, it is found that the flow over the edge of the disk acts as a strong source of fluctuations. Explanations and suggestions for a possible reconciliation of previous studies are given.
Robust Bayesian learning for wireless RF energy harvesting networks

In this paper, the problem of adversarial learning is studied for a wireless powered communication network (WPCN) in which a hybrid access point (HAP) seeks to learn the transmission power consumption profile of an associated wireless transmitter. The objective of the HAP is to use the learned estimate in order to determine the transmission power of the energy signal to be supplied to its associated device. However, such a learning scheme is subject to attacks by an adversary who tries to alter the HAP's learned estimate of the transmission power distribution in order to minimize the HAP's supplied energy. To build a robust estimate against such attacks, an unsupervised Bayesian learning method is proposed allowing the HAP to perform its estimation based only on the advertised transmisson power computed in each time slot. The proposed robust learning method relies on the assumption that the device's true transmission power is greater than or equal to advertised value. Then, based on the robust estimate, the problem of power selection of the energy signal by the HAP is formulated. The HAP optimal power selection problem is shown to be a discrete convex optimization problem, and a closed-form solution of the HAP's optimal transmission power is obtained. The results show that the proposed robust Bayesian learning scheme yields significant performance gains, by reducing the percentage of dropped transmitter's packets of about 85% compared to a conventional Bayesian learning approach. The results also show that these performance gains are achieved without jeopardizing the energy consumption of the HAP.
Melanin-concentrating hormone receptor 1 polymorphisms are associated with components of energy balance in the Complex Diseases in the Newfoundland Population: Environment and Genetics (CODING) study.

BACKGROUND The melanin-concentrating hormone receptor 1 (MCHR1) is a G protein-coupled receptor that regulates energy balance and body composition in animal models. Inconsistent effects of MCHR1 polymorphisms on energy homeostasis in humans may partly be attributable to environmental factors. OBJECTIVES We examined the effect of 4 single nucleotide polymorphisms (rs133073, rs133074, rs9611386, and rs882111) in the MCHR1 gene on body composition as well as energy-related lifestyle factors (diet and physical activity). We also examined the effect of gene-lifestyle interactions on body composition. DESIGN A total of 1153 participants (248 men and 905 women) from the cross-sectional Complex Diseases in the Newfoundland Population: Environment and Genetics (CODING) study were genotyped by using probe-based chemistry validated assays. Diet and physical activity were estimated by using validated frequency questionnaires, and body composition was assessed by using dual-energy X-ray absorptiometry. RESULTS Three polymorphisms (rs9611386, rs882111, and rs133073) were associated with differences in body-composition measurements (all P < 0.05). There was an interaction between rs9611386 and carbohydrate intake on total mass and waist circumference (both P ≤ 0.01). There was also an interaction between rs9611386 and body mass index categories (normal weight, overweight, and obese) on energy intakes (P = 0.02). A similar interaction was shown with rs882111 (P = 0.02). Interactions were also observed between each of these polymorphisms (rs9611386, rs882111, and rs133073) and physical activity score on body-composition measurements (all P < 0.05). CONCLUSION These findings suggest that polymorphisms in the MCHR1 gene are associated with differences in body composition and interact with physiologic and energy-related lifestyle factors.
Swimming and diving energetics in dolphins: a stroke-by-stroke analysis for predicting the cost of flight responses in wild odontocetes

ABSTRACT Exponential increases in hydrodynamic drag and physical exertion occur when swimmers move quickly through water, and underlie the preference for relatively slow routine speeds by marine mammals regardless of body size. Because of this and the need to balance limited oxygen stores when submerged, flight (escape) responses may be especially challenging for this group. To examine this, we used open-flow respirometry to measure the energetic cost of producing a swimming stroke during different levels of exercise in bottlenose dolphins (Tursiops truncatus). These data were then used to model the energetic cost of high-speed escape responses by other odontocetes ranging in mass from 42 to 2738 kg. The total cost per stroke during routine swimming by dolphins, 3.31±0.20 J kg−1 stroke−1, was doubled during maximal aerobic performance. A comparative analysis of locomotor costs (LC; in J kg−1 stroke−1), representing the cost of moving the flukes, revealed that LC during routine swimming increased with body mass (M) for odontocetes according to LC=1.46±0.0005M; a separate relationship described LC during high-speed stroking. Using these relationships, we found that continuous stroking coupled with reduced glide time in response to oceanic noise resulted in a 30.5% increase in metabolic rate in the beaked whale, a deep-diving odontocete considered especially sensitive to disturbance. By integrating energetics with swimming behavior and dive characteristics, this study demonstrates the physiological consequences of oceanic noise on diving mammals, and provides a powerful tool for predicting the biological significance of escape responses by cetaceans facing anthropogenic disturbances. Highlighted Article: Elevated locomotor costs during high-speed stroking by swimming dolphins demonstrate the energetic challenge of escape responses due to anthropogenic noise in the ocean.
The Scored Rule Engine: Next-Generation Social Physics

Despite being central to many game stories, dynamic social relationships in video games are difficult to make playable in meaningful ways. To help address this issue, this paper presents the Ensemble Engine (EE), the first publicly available “social physics” engine. The Ensemble Engine is inspired by the lessons learned from more than five years building the Comme il Faut ( CiF ) social physics engine, and a number of games employing it (including Prom Week ). The Ensemble Engine retains the most successful aspects of CiF, while also making major improvements in areas such as the flexibility of its action structure and expressivity of its rules. The system is authored in an open-standard language (JavaScript) and includes an authoring tool to increase accessibility for game researchers and creators. Through these improvements and this dissemination strategy, the Ensemble Engine represents an opportunity for the potential of social physics to become much more broadly explored.
Robot learning of upper-body human motion by active imitation

This paper presents a general architecture that allows a humanoid robot to imitate upper-body movements of a human demonstrator. This architecture integrates a mechanism to memorize novel behaviours executed by a human demonstrator, with a module to recognize and generate its own interpretation of already observed behaviours. Our imitator includes three biologically plausible components: i) an attention mechanism to autonomously extract relevant information from the visual input; ii) a supra-modal representation of the motion of observed body parts to map visual and motor domains; and iii) an active imitation module which involves the motor systems in the behaviour recognition process. Experimental results with a real humanoid robot demonstrate the ability of the proposed architecture to acquire novel behaviours and to recognize and reproduce previously memorized ones