Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Immunodeficiency Virus Type 1 Vpr Inhibits Axonal Outgrowth through Induction of Mitochondrial Dysfunction

ABSTRACT Human immunodeficiency virus type 1 (HIV-1)-infected macrophages damage mature neurons in the brain, although their effect on neuronal development has not been clarified. In this study, we show that HIV-1-infected macrophages produce factors that impair the development of neuronal precursor cells and that soluble viral protein R (Vpr) is one of the factors that has the ability to suppress axonal growth. Cell biological analysis revealed that extracellularly administered recombinant Vpr (rVpr) clearly accumulated in mitochondria where a Vpr-binding protein adenine nucleotide translocator localizes and also decreased the mitochondrial membrane potential, which led to ATP synthesis. The depletion of ATP synthesis reduced the transportation of mitochondria within neurites. This mitochondrial dysfunction inhibited axonal growth even when the frequency of apoptosis was not significant. We also found that point mutations of arginine (R) residues to alanine (A) residues at positions 73, 77, and 80 rendered rVpr incapable of causing mitochondrial membrane depolarization and axonal growth inhibition. Moreover, the Vpr-induced inhibition was suppressed after treatment with a ubiquinone analogue (ubiquinone-10). Our results suggest that soluble Vpr is a major viral factor that causes a disturbance in neuronal development through the induction of mitochondrial dysfunction. Since ubiquinone-10 protects the neuronal plasticity in vitro, it may be a therapeutic agent that can offer defense against HIV-1-associated neurological disease.
Model Checking MITL Formulae on Timed Automata

Timed Automata (TA) is de facto a standard modelling formalism to represent systems when the interest is the analysis of their behaviour as time progresses. This modelling formalism is mostly used for checking whether the behaviours of a system satisfy a set of properties of interest. Even if efficient model-checkers for Timed Automata exist, these tools are not easily configurable. First, they are not designed to easily allow adding new Timed Automata constructs, such as new synchronization mechanisms or communication procedures, but they assume a fixed set of Timed Automata constructs. Second, they usually do not support the Metric Interval Temporal Logic (MITL) and rely on a precise semantics for the logic in which the property of interest is specified, which cannot be easily modified and customized. Finally, they do not easily allow using different solvers that may speed up verification in different contexts. This article presents a novel technique to perform model checking of Metric Interval Temporal Logic (MITL) properties on TA. The technique relies on the translation of both the TA and the MITL formula into an intermediate Constraint LTL over clocks (CLTLoc) formula, which is verified through an available decision procedure. The technique is flexible, since the intermediate logic allows the encoding of new semantics as well as new TA constructs, by just adding new CLTLoc formulae. Furthermore, our technique is not bound to a specific solver as the intermediate CLTLoc formula can be verified using different procedures.
Contrast Enhanced Ultrasound Imaging with Nanobubbles: Unique Second-Wave Phenomenon

Investigation of nanobubble (NB) pharmacokinetics in contrast-enhanced ultrasound (CEUS) at the pixel level shows a unique phenomenon where the first pass of the contrast agent bolus is accompanied by a second wave. This effect has not been previously observed in CEUS with microbubbles. The objective of this study was to investigate this second-wave phenomenon and its potential clinical applications. Seven mice with a total of fourteen subcutaneously-implanted tumors were included in the experiments. After injecting a bolus of NBs, the NB-CEUS images were acquired to record the time-intensity curves (TICs) at each pixel. These TICs are fitted to a pharmacokinetic model which we designed to describe the observed second-wave phenomenon. The estimated model parameters are presented as parametric maps to visualize the characteristics of tumor lesions. Histological analysis was also conducted in one mouse to compare the molecular features of tumor tissue with the obtained parametric maps. The second-wave phenomenon is evidently shown in a series of pixel-based TICs extracted from either tumor or tissues. The value of two model parameters, the ratio of the peak intensities of the second over the first wave, and the decay rate of the wash-out process are significantly different between malignant and tissue (Kolmogorov–Smirnov statistic D > 0.25). The occurrence of a second wave is a unique phenomenon that we have observed in NB-CEUS imaging of both mouse tumor and tissue. As the characteristics of the second wave are different between tumor and tissue, this phenomenon has the potential to support the diagnosis of cancerous lesions.
NF- (cid:1) B Protects Cells from Gamma Interferon-Induced RIP1-Dependent Necroptosis (cid:1)

Interferons (IFNs) are cytokines with well-described immunomodulatory and antiviral properties, but less is known about the mechanisms by which they promote cell survival or cell death. Here, we show that IFN- (cid:1) induces RIP1 kinase-dependent necroptosis in mammalian cells deﬁcient in NF- (cid:2) B signaling. Induction of necroptosis by IFN- (cid:1) was found to depend on Jak1 and partially on STAT1. We also demonstrate that IFN- (cid:1) activates I (cid:2) B kinase (cid:3) (IKK (cid:3) )-dependent NF- (cid:2) B to regulate a transcriptional program that protects cells from necroptosis. IFN- (cid:1) induced progressive accumulation of reactive oxygen species (ROS) and eventual loss of mitochondrial membrane potential in cells lacking the NF- (cid:2) B subunit RelA. Whole-genome microarray analyses identiﬁed sod2 , encoding the antioxidant enzyme manganese superoxide dismutase (MnSOD), as a RelA target and potential antinecroptotic gene. Overexpression of MnSOD inhibited IFN- (cid:1) -mediated ROS accumulation and partially rescued RelA-deﬁcient cells from necroptosis, while RNA interference (RNAi)- mediated silencing of sod2 expression increased susceptibility to IFN- (cid:1) -induced cell death. Together, these studies demonstrate that NF- (cid:2) B protects cells from IFN- (cid:1) -mediated necroptosis by transcriptionally activating a survival response that quenches ROS to preserve mitochondrial integrity.
Antigen Expression Peripheral Induction of Tolerance by Retinal

The contribution of peripheral expression of tissue-speciﬁc CNS Ags to the generation of tolerance is uncertain. To study this question, we examined mice transgenic (Tg) for expression of (cid:1) -galactosidase ( (cid:1) gal) on the retinal photoreceptor cell arrestin promoter, in conjunction with TCR Tg mice producing CD4 (cid:2) T cells speciﬁc for (cid:1) gal ( (cid:1) galTCR). Several strategies were used to test the hypothesis that (cid:1) gal expressed in the retina supported thymus-independent tolerance and regulatory T cell development. Retinal expression generated an immunoregulatory response that depressed development of immune responses to (cid:1) gal following systemic immunization with (cid:1) gal. This regulation was transferable to naive mice by CD3 (cid:2) 4 (cid:2) 25 (cid:2) T cells from naive retinal (cid:1) gal (cid:2) donors. Experiments that removed the (cid:1) gal (cid:2) retina by enucleation showed that subsequent development of a regulatory response was lost. Adoptive transfer of CD25 (cid:3) (cid:1) galTCR T cells into retinal (cid:1) gal Tg mice on the Rag (cid:3) / (cid:3) background led to regulatory activity that limited lymphopenia-induced proliferation of (cid:1) galTCR T cells in mice with retinal expression of (cid:1) gal and inhibited the ear-swelling assay for delayed type hypersensitivity. These results show that retinal expression of very small amounts of a tissue-speciﬁc Ag can generate tolerance that includes regulatory T cells. The Journal of Immunology, 2009, 183: 0000–0000.
Spatial control and cell guidance in evolving biological tissues

Tissue geometry is an important influence on the evolution of many biological tissues. The local curvature of an evolving tissue induces cell crowding or spreading, which leads to differential tissue growth rates, and to changes in cellular tension, which can influence cell behaviour. In this thesis, a cell-based mathematical model for the curvature control of evolving biological tissues is presented to investigate how this control mechanism interacts with directed cell guidance mechanisms. First, the mathematical model is derived from conservation principles applied to the density of tissue synthesising cells at or near the tissue’s moving boundary. The resulting partial differential equation is then solved numerically using a hybrid front-tracking method called the cell-based particle method. We apply this model to understand how angled bone tissue formation may generate anisotropies in tissue material properties, and to understand the role of tangential cell motion in the bone resorption process. Finally, ongoing work is presented on the application of the model to experimental bone pore infilling data available through collaboration with experimental bone biologists. This work involves exploring mechanisms which could cause irregular tissue growth behaviour in bone, where the infilling of bone pores is asymmetric.
Cloud Computing System Based on a DHT Structured Using an Hyperbolic Tree

—During the last decade, Cloud Computing (CC) has been quickly adopted worldwide, and several solutions have emerged. Cloud computing is used to provide storage service, computing power and ﬂexibility to end-users, in order to access data from anywhere at any time. Thus, Cloud Computing is a subscription-based service where you can obtain networked storage space and computer resources. The cloud makes it possible for you to access your information from anywhere at any time. Distributed Hash Table (DHT) plays an important role in distributed systems and applications, particularly in environments distributed on a large scale. In the model of normal Client/Server (C/S model), as we centralize most of the resources on the server, it becomes the most important part as well as the bottleneck and the weak point of the system. On the contrary, distributed model (a typical is Peer-to-Peer (P2P) model) distributes the resources on the nodes in the system. In this paper, we propose a new system of Cloud Computing based on our DHT structured using an hyperbolic tree, which organizes the distributed services so well that peers only need to know part of the system they can get services efﬁciently. DHT provides two basic operations: retrieves service from DHT and stores service into DHT, which is so simple and graceful, but is suitable for a great variety of resources (Applications, Infrastructures, Platforms), and provides good robustness and high efﬁciency, especially in large-scale systems. Resources as services are distributed by using virtual coordinates taken in the hyperbolic plane. We use the Poincar´e disk model and we perform and evaluate our cloud structure performances. First, we show that our solution is scalable, consistent, reliable. Next, we compare the performances realized by the substitution strategy, which we propose with the strategy of classic replication in a dynamic context.
Preparation of Fluorescent-Magnetic Silica Nanoprobes for Recognition and Separation of Human Lung Cancer Cells

In this work, we have prepared fluorescent-magnetic silica nanoparticles (NPs) based on RuBpy-doped silica NPs and super paramagnetic Fe 3 O 4 NPs using coating method. RuBpy-doped silica NPs (~60 nm) and Fe 3 O 4 NPs (~10 nm) are first prepared using the reverse micro emulsion method (W/O) and the high temperature oil cracking method, respectively. Polyethyleneimine (PEI) is then conjugated to the surface of RuBpy-doped silica NPs. Coordination reaction between amines of PEI modified RuBpy-doped silica NPs and Fe 3 O 4 is further performed in the n-hexanol to realize magnetic materials coating. After silanization and carboxylation of prepared fluorescent-magnetic silica nanoparticles (FMNPs), wheat germ agglutinin (WGA) molecules are conjugated to carboxyl-modified fluorescent-magnetic silica NPs (FMNPs-COOH, 100 nm). To demonstrate the biological application of as-prepared fluorescent-magnetic silica NPs, WGA-conjugated fluorescent-magnetic silica NPs (FMNPs-WGA) are incubated with human lung cancer A549 cells and separated by a magnetic field and then imaged using fluorescence microscopy. The results of fluorescence imaging show that fluorescent-magnetic-bifunctional nanoprobes prepared by this method could be used for highly efficient recognition and separation of cancer cells.
Studies of t ¯ t / t W interference eﬀects in b ¯ b + ﬁnal states with Powheg and MadGraph5_aMC@NLO setups The

The precise simulation of t ¯ t processes is crucial for precision tests of the Standard Model and in the search for new physics at the Large Hadron Collider. Up to now, the interference eﬀects between t ¯ t and tW production were taken into account by using either a diagram-removal (DR) or a diagram-subtraction (DS) method in the generation of the tW events. The “ bb 4 (cid:96) ” generator is a NLO matrix-element generator for pp → b ¯ b (cid:96) + (cid:96) − (cid:48) ν ¯ ν (cid:48) ﬁnal states implemented in the Powheg Box. It includes theoretical improvements in the simulation of t ¯ t processes, which allows the production of t ¯ t and tW events including interference, oﬀ-shell eﬀects, and top-quark decays at NLO. The events simulated with the bb 4 (cid:96) generator are interfaced with Pythia 8 for the simulation of the Parton Shower (PS) and hadronisation and compared to diﬀerent t ¯ t + tW generator setups. In addition, diﬀerent DR and DS models implemented in MadGraph5_aMC@NLO are studied. Their NLO predictions are compared to unfolded ATLAS data and to the bb 4 (cid:96) predictions. The studies are performed in a phase-space for typical t ¯ t precision measurements as well as in phase-spaces relevant for searches.
CALL FOR PAPERS Integrative and Translational Physiology: Inﬂammation and Immunity in Organ System Physiology Life without TTP: apparent absence of an important anti-inﬂammatory protein in birds

apparent absence of an important anti-inﬂammatory protein in birds. Am Physiol 305: 2013. 2013; innate and adaptive immunity in birds are different from their mammalian counterparts. Understanding bird immunity is important because of the enormous potential impact of avian infectious diseases, both in their role as food animals and as potential carriers of zoonotic diseases in man. The anti-inﬂammatory protein tristetraprolin (TTP) is an important component of the mammalian innate immune response, in that it binds to and destabilizes key cytokine mRNAs. TTP knockout mice exhibit a severe systemic inﬂammatory syndrome, and they are abnormally sensitive to innate immune stimuli such as LPS. TTP orthologs have been found in most vertebrates studied, including frogs. Here, we attempted to identify TTP orthologs in chicken and other birds, using database searches and deep mRNA sequencing. Although sequences encoding the two other widely expressed TTP family members, ZFP36L1 and ZFP36L2, were identiﬁed, we did not ﬁnd sequences corresponding to TTP in any bird species. Sequences corresponding to TTP were identiﬁed in both lizards and alligators, close evolutionary relatives of birds. The induction kinetics of Zfp36l1 and Zfp36l2 mRNAs in LPS-stimulated chicken macrophages or serum-stimulated chick embryo ﬁbroblasts did not resemble the normal mammalian TTP response to these stimuli, suggesting that the other two family members might not compensate for the TTP deﬁciency in regulating rapidly induced mRNA targets. Several mammalian TTP target transcripts have chicken counterparts that contain one or more potential TTP binding sites, raising the possibility that birds express other proteins that subsume TTP’s function as a rapidly inducible regulator of AU-rich element (ARE)-dependent mRNA turnover. peptide database. As positive controls, searches were performed on full-length ZFP36 family member protein sequences from multiple species, using their respective family proﬁle HMM, to conﬁrm that the alignments correctly discriminated among the different proteins. Alignments and phylogenetic comparisons. Full-length protein alignments were conducted with ClustalW, using the default parameters for protein multiple comparisons, on either the MacVector 11.1. 2 or MEGA5.05 platforms. We used the Gonnet matrix for multiple comparisons, with an open gap penalty of 10 and an extended gap penalty of 0.2 (default options in this version of ClustalW). Phylogenetic comparisons were performed using MEGA5.05 (30) on the ClustalW alignment, and we used the maximum parsimony bootstrap method to infer the evolutionary history of the full length proteins.
Forecast the In ﬂ uenza Pandemic Using Machine Learning

: Forecasting future outbreaks can help in minimizing their spread. In ﬂ uenza is a disease primarily found in animals but transferred to humans through pigs. In 1918, in ﬂ uenza became a pandemic and spread rapidly all over the world becoming the cause behind killing one-third of the human population and killing one-fourth of the pig population. Afterwards, that in ﬂ uenza became a pandemic several times on a local and global levels. In 2009, in ﬂ uenza ‘ A ’ subtype H1N1 again took many human lives. The disease spread like in a pandemic quickly. This paper proposes a forecasting modeling system for the in ﬂ uenza pandemic using a feed-forward propagation neural network (MSDII-FFNN). This model helps us predict the outbreak, and determines which type of in ﬂ uenza becomes a pandemic, as well as which geographical area is infected. Data collec-tion for the model is done by using IoT devices. This model is divided into 2 phases: The training phase and the validation phase, both being connected through the cloud. In the training phase, the model is trained using FFNN and is updated on the cloud. In the validation phase, whenever the input is submitted through the IoT devices, the system model is updated through the cloud and pre-dicts the pandemic alert. In our dataset, the data is divided into an 85% training ratio and a 15% validation ratio. By applying the proposed model to our dataset, the predicted output precision is 90%.
Addressing the Grid size Sensitivity Issue in Large eddy Simulations of Stable Boundary Layers

In current study, several fundamental and inherent problems in original Deardorff subgrid model are identified under stably stratified condition. It is found that the mixing length parameterization in this subgrid model is at the root of a long trouble problem of grid size sensitivity in large-eddy simulation (LES). A new formulation of mixing length is proposed under the consideration of some basic elements including the presence of surface, the dependence of grid size Δ and a smoothing interpolation. The performance of this modified scheme is remarkable regarding the improvement of the simulation quality and accuracy. In other words, not only is the convergence of the simulated results from a range of grid size achieved but also in the precise intensity of physical variables are modelled. The only discrepancies display in the variance of temperature in the middle of boundary layer and high turbulent kinetic energy near the surface. To further experiment the performance of the new scheme under different scenarios, the cases of different stability condition, an independent LES code with same modification, the cases of different advection schemes and different prescribed parameters are explored. In very stable condition, the first order variables from the modified scheme are in reasonable range but with some spreads compared to the results from a dynamic code. The deviation of second order statistics shows that the proposed formulation of mixing length meets limitations due to the complex interaction between the surface and turbulent flow in shallower boundary layer. The modified scheme is model system independent based on the similar improvement of simulation results in an independent LES code system. The sensitivity of advection schemes is surprisingly hardly found in new proposed SGS model. The cases of tested parameters further verifies the limitation of original Deardroff subgrid model.
Investigating nurses’ intention to use electronic health records: The Unified theory of acceptance and use of technology approach

: Technology integration into the public healthcare sector is considered one of the pipeline projects to enhance healthcare proficiency and productivity. As such, there has been huge investment in the health domain geared towards successfully integrating health technology among health professionals all in the quest to achieve better health delivery services and universal health coverage. User acceptance of such technology as electronic health records has become necessary for the productive deployment of the health sector innovations. The study adopted the Unified theory of acceptance and use of technology and additional constructs of attitude and design aesthetics to investigate nurses’ intention to use electronic health records, as they form part of the direct users of the technology. A field investigation was carried out with 381 nurses from diverse medical institutions in Ghana. The study used a quantitative approach anchored on the structural equation modeling (SEM) analysis to verify that, performance expectancy, effort expectancy, social influence, attitude, and design aesthetics, all have a substantial positive impact on nurse's electronic health records adoption intention. The results of the analysis indicated the behavioral intention (BI) of nurses to use electronic health records was predictable by Performance Expectancy (PE) (β = .194**, p < 0.01), Effort Expectancy (EE) (β = .261***, p < 0.001), Social Influence (SI) (β = .377***, p < 0.001), Attitude (ATT) (β = .380***, p < 0.001) and Design Aesthetics (β = .217**, p < 0.01). The findings confirm that the UTAUT model has predictive potential and viability. The study implications are discussed based on empirical findings.