Miracle-dz/UniFAR-FTUs huggingface dataset:
Cellular Transcription Factor Oct-1 Interacts with the Epstein-Barr Virus BRLF1 Protein To Promote Disruption of Viral Latency

ABSTRACT The Epstein-Barr virus (EBV) latent-to-lytic switch is an essential part of the viral life cycle, but the cellular factors that promote viral reactivation are not well defined. In this report, we demonstrate that the cellular transcription factor Oct-1 cooperates with the EBV immediate-early protein BRLF1 (R, Rta) to induce lytic viral reactivation. We show that cotransfected Oct-1 enhances the ability of BRLF1 to activate lytic gene expression in 293 cells stably infected with a BRLF1-defective EBV mutant (BRLF1-stop) and that Oct-1 increases BRLF1-mediated activation of lytic EBV promoters in reporter gene assays. We find that Oct-1 interacts directly with BRLF1 in vitro and that a mutant BRLF1 protein (the M140A mutant) attenuated for the ability to interact with Oct-1 in vitro is also resistant to Oct-1-mediated transcriptional enhancement in 293 BRLF1-stop cells. Furthermore, we show that cotransfected Oct-1 augments BRLF1 binding to a variety of lytic EBV promoters in chromatin immunoprecipitation (ChIP) assays (including the BZLF1, BMRF1, and SM promoters) and that BRLF1 tethers Oct-1 to lytic EBV promoters. In addition, we demonstrate that an Oct-1 mutant defective in DNA binding (the S335D mutant) still retains the ability to enhance BRLF1 transcriptional effects. Finally, we show that knockdown of endogenous Oct-1 expression reduces the level of constitutive lytic EBV gene expression in both EBV-positive B-cell and EBV-positive epithelial cell lines. These results suggest that Oct-1 acts as a positive regulator of EBV lytic gene expression and that this effect is at least partially mediated through its interaction with the viral protein BRLF1.
Participatory mapping in low-resource settings: Three novel methods used to engage Kenyan youth and other community members in community-based HIV prevention research

ABSTRACT Understanding the link between health and place can strengthen the design of health interventions, particularly in the context of HIV prevention. Individuals who might one day participate in such interventions – including youth – may further improve the design if engaged in a meaningful way in the formative research process. Increasingly, participatory mapping methods are being used to achieve both aims. We describe the development of three innovative mapping methods for engaging youth in formative community-based research: ‘dot map’ focus groups, geocaching games, and satellite imagery-assisted daily activity logs. We demonstrate that these methods are feasible and acceptable in a low-resource, rural African setting. The discussion outlines the merits of each method and considers possible limitations.
Tyrosine-Nitrated Proteins: Proteomic and Bioanalytical Aspects.

SIGNIFICANCE "Nitroproteomic" is under active development, as 3-nitrotyrosine in proteins constitutes a footprint left by the reactions of nitric oxide-derived oxidants that are usually associated to oxidative stress conditions. Moreover, protein tyrosine nitration can cause structural and functional changes, which may be of pathophysiological relevance for human disease conditions. Biological protein tyrosine nitration is a free radical process involving the intermediacy of tyrosyl radicals; in spite of being a nonenzymatic process, nitration is selectively directed toward a limited subset of tyrosine residues. Precise identification and quantitation of 3-nitrotyrosine in proteins has represented a "tour de force" for researchers. Recent Advances: A small number of proteins are preferential targets of nitration (usually less than 100 proteins per proteome), contrasting with the large number of proteins modified by other post-translational modifications such as phosphorylation, acetylation, and, notably, S-nitrosation. Proteomic approaches have revealed key features of tyrosine nitration both in vivo and in vitro, including selectivity, site specificity, and effects in protein structure and function. CRITICAL ISSUES Identification of 3-nitrotyrosine-containing proteins and mapping nitrated residues is challenging, due to low abundance of this oxidative modification in biological samples and its unfriendly behavior in mass spectrometry (MS)-based technologies, that is, MALDI, electrospray ionization, and collision-induced dissociation. FUTURE DIRECTIONS The use of (i) classical two-dimensional electrophoresis with immunochemical detection of nitrated proteins followed by protein ID by regular MS/MS in combination with (ii) immuno-enrichment of tyrosine-nitrated peptides and (iii) identification of nitrated peptides by a MIDAS™ experiment is arising as a potent methodology to unambiguously map and quantitate tyrosine-nitrated proteins in vivo. Antioxid. Redox Signal. 26, 313-328.
Malware classification based on API calls and behaviour analysis

This study presents the runtime behaviour-based classification procedure for Windows malware. Runtime behaviours are extracted with a particular focus on the determination of a malicious sequence of application programming interface (API) calls in addition to the file, network and registry activities. Mining and searching n-gram over API call sequences is introduced to discover episodes representing behaviour-based features of a malware. Voting Experts algorithm is used to extract malicious API patterns over API calls. The classification model is built by applying online machine learning algorithms and compared with the baseline classifiers. The model is trained and tested with a fairly large set of 17,400 malware samples belonging to 60 distinct families and 532 benign samples. The malware classification accuracy is reached at 98%.
Mobile Text Messaging to Improve Medication Adherence and Viral Load in a Vulnerable Canadian Population Living With Human Immunodeficiency Virus: A Repeated Measures Study

Background Combination antiretroviral therapy (cART) as treatment for human immunodeficiency virus (HIV) infection is effective and available, but poor medication adherence limits benefits, particularly in vulnerable populations. In a Kenyan randomized controlled trial, a weekly text-messaging intervention (WelTel) improved cART adherence and HIV viral load (VL). Despite growing evidence for short message service (SMS) text-message interventions in HIV care, there is a paucity of data utilizing these interventions in marginalized or female cohorts. Objective This study was undertaken to assess whether the standardized WelTel SMS text-message intervention applied to a vulnerable, predominantly female, population improved cART adherence and VL. Methods We conducted a repeated measures study of the WelTel intervention in high-risk HIV-positive persons by measuring change in VL, CD4 count, and self-reported adherence 12 months before and 12 months after the WelTel intervention was introduced. Inclusion criteria included VL ≥200 copies/mL, indication for treatment, and meeting vulnerability criteria. Participants were given a mobile phone with unlimited texting (where required), and weekly check-in text messages were sent for one year from the WelTel computer platform. Clinical data were collected for control and intervention years. Participants were followed by a multidisciplinary team in a clinical setting. Outcomes were assessed using Wilcoxon signed ranks tests for change in CD4 and VL from control year to study end and mixed-effects logistic regressions for change in cART adherence and appointment attendance. A secondary analysis was conducted to assess the effect of response rate on the outcome by modeling final log10 VL by number of responses while controlling for mean log10 VL in the control year. Results Eighty-five participants enrolled in the study, but 5 withdrew (final N=80). Participants were predominantly female (90%, 72/80) with a variety of vulnerabilities. Mean VL decreased from 1098 copies/mL in the control year to 439 copies/mL at study end (P=.004). Adherence to cART significantly improved (OR 1.14, IQR 1.10-1.18; P<.001), whereas appointment attendance decreased slightly with the intervention (OR 0.81, IQR 0.67-0.99; P=.03). A response was received for 46.57% (1753/3764) of messages sent and 9.62% (362/3764) of text messages sent were replied to with a problem. An outcome analysis examining relationship between reply rate and VL did not meet statistical significance (P=.07), but may be worthy of investigating further in a larger study. Conclusions WelTel may be an effective tool for improving cART adherence and reducing VLs among high-risk, vulnerable HIV-positive persons. Trial Registration Clinicaltrials.gov NCT02603536; https://clinicaltrials.gov/ct2/show/NCT02603536 (Archived by WebCite at http://www.webcitation.org/6qK57zCwv)
Does the Tempo of Music Impact Human Behavior Behind the Wheel?

Objective: Assess the influence of background music tempo on driving performance. Background: Music with a fast tempo is known to increase the level of arousal, whereas the reverse is observed for slow music. The relationship between driving performance and level of arousal was expected to take the form of an inverted U-curve. Method: Three experiments were undertaken to manipulate the musical background during driving. In Experiment 1, the driver’s preferred music track played at its original and modified (plus or minus 30%) tempo were used together with the simple ticking of a metronome. In Experiment 2, music tracks of different tempos were played during driving. In Experiment 3, music tracks were categorized as arousing or relaxing based on the associated perceived level of arousal. Results: Listening to music tended to influence drivers’ performances in a car-following task by improving coherence and gain adjustments relative to the followed vehicle but simultaneously shortened the intervehicular time. Although the tempo of the music per se did not directly affect driving behavior, arousing music tracks improved drivers’ adjustments to the followed vehicle (Experiment 3). Conclusion: The tempo of the music listened to behind the wheel was not found to influence driving behaviors. However, arousing music improved drivers’ responsiveness to changes in the speed of the followed vehicle. However, this benefit was canceled out by a reduction in the drivers’ intervehicle safety margin. Application: Listening to arousing music while driving cannot be considered to improve road safety, at least in a car-following task without attentional impairments.
Multiple Target Counting and Localization Using Variational Bayesian EM Algorithm in Wireless Sensor Networks

Localization technologies play an increasingly important role in pervasive applications of wireless sensor networks. Since the number of targets is usually limited, localization benefits from compressed sensing (CS): measurements number can be greatly reduced. Despite many CS-based localization schemes, existing solutions implicitly assume that all targets fall on a fixed grid exactly. When the assumption is violated, the mismatch between the assumed and actual sparsifying dictionaries can deteriorate the localization performance significantly. To address such a problem, in this paper, we propose a novel and iterative multiple target counting and localization framework. The key idea behind the framework is to dynamically adjust the grid to alleviate or even eliminate dictionary mismatch. The contribution of this paper is twofold. First, we consider the off-grid target issue in CS-based localization and formulate multiple target counting and localization as a joint sparse signal recovery and parameter estimation problem. Second, we solve the joint optimization problem using a variational Bayesian expectation-maximization algorithm where the sparse signal and parameter are iteratively updated in the variational Bayesian expectation-step and variational Bayesian maximization-step, respectively. Extensive simulation results highlight the superior performance of the proposed framework in terms of probability of correct counting and average localization error.
GeSn/SiGeSn photonic devices for mid-infrared applications: experiments and calculations

In this work, a fully strained GeSn photodetector with Sn atom percent of 8% is fabricated on Ge buffer on Si(001) substrate. The wavelength λ of light signals with obvious optical response for Ge0.92Sn0. 08 photodetector is extended to 2 μm. The impacts of compressive strain introduced during the epitaxial growth of GeSn on Ge/Si are studied by simulation. Besides, the tensile strain engineering of GeSn photonic devices is also investigated. Lattice-matched GeSn/SiGeSn double heterostructure light emitting diodes (LEDs) with Si3N4 tensile liner stressor are designed to promote the further mid-infrared applications of GeSn photonic devices. With the releasing of the residual stress in Si3N4 liner, a large biaxial tensile strain is induced in GeSn active layer. Under biaxial tensile strain, the spontaneous emission rate rsp and internal quantum efficiency ηIQE for GeSn/SiGeSn LED are significantly improved.
Associating risks of getting strokes with data from health checkup records using Dempster-Shafer Theory

Prediction of future diseases from historical data of medical patients is a topic that has gained increasing interest given the growing availability of such data in electronic format. Most of the developed systems are based on machine learning techniques, which are good to find relations between data but do not help explaining causalities. In particular, it would be difficult to get a meaningful medical explanation for the relationship between a patient's health checkup data and the risk of developing a certain disease. On the other hand, expert system approaches, like Bayesian networks, are based on medical knowledge but have trouble dealing with high levels of uncertainty, which is crucial in this kind of scenario. In this work we present a prediction system for the risk of a patient having a (heart or brain) stroke based on past medical checkup data. The system is based on the Dempster-Shafer Theory of plausibility which is good for handling uncertainty. The data used belongs to a rural hospital in Okayama, Japan, where people are compelled to undergo annual health checkups by law. The model also produces rules that are able to relate data from exam results with the aforementioned risk, thus proposing a cause from the medical point of view. Experiments comparing the results of the Dempster-Shafer method with other machine learning methods like Multilayer perceptron, Quadratic discriminant analysis and Naive Bayes show that our approach performed the best in general, with an overall prediction accuracy of 61% and with the best precision value on true positive cases of stroke.
Precipitation estimation over radar gap areas based on satellite and adjacent radar observations

Abstract. Continuous rainfall measurements from ground-based radars are crucial for monitoring and forecasting heavy rainfall-related events such as floods and landslides. However, complete coverage by ground-based radars is often hampered by terrain blockage and beam-related errors. In this study, we presented a method to fill the radar gap using surrounding radar-estimated precipitation and observations from a geostationary satellite. The method first estimated the precipitation over radar gap areas using data from the Communication, Ocean, and Meteorological Satellite (COMS); the first geostationary satellite of Korea. The initial precipitation estimation from COMS was based on the rain rate-brightness temperature relationships of a priori databases. The databases were built with temporally and spatially collocated brightness temperatures at four channels (3.7, 6.7, 10.8, and 12 μm) and Jindo (126.3° E, 34.5° N) radar rain rate observations. The databases were updated with collocated data sets in a timespan of approximately one hour prior to the designated retrieval. Then, bias correction based on an ensemble bias factor field (Tesfagiorgis et al., 2011b) from radar precipitation was applied to the estimated precipitation field. Over the radar gap areas, this method finally merged the bias-corrected satellite precipitation with the radar precipitation obtained by interpolating the adjacent radar observation data. The merging was based on optimal weights determined from the root-mean-square error (RMSE) with the reference sensor observation or equal weights in the absence of reference data. This method was tested for major precipitation events during the summer of 2011 with assumed radar gap areas. The results suggested that successful merging appears to be closely related to the quality of the satellite precipitation estimates.
Changes in the cellular immune system and circulating inflammatory markers of stroke patients

This study was designed to investigate dynamic changes in the cellular immune system and circulating inflammatory markers after ischemic stroke. Blood was collected from 96 patients and 99 age-matched control subjects for detection of lymphocyte subpopulations and inflammatory markers. We observed decreases in B cells, Th cells, cytotoxic T cells, and NK cells and an increase in regulatory T (Treg) cells in stroke patients on days 1, 3, and 7. Serum levels of TNF-a, C-reactive protein (CRP), IL-4, IL-6, IL-10, IL-17, IL-23, and TGF-β increased, whereas serum level of IFN-? decreased at all time points after stroke. Stroke patients with infection exhibited a similar tendency toward changes in some lymphocyte subpopulations and inflammatory markers as stroke patients without infection. After controlling for NIH Stroke Scale (NIHSS), we observed no differences in lymphocyte subpopulations between patients with anterior circulation stroke and those with posterior circulation stroke at any time point. The splenic volume correlated positively with the percentages of B cells, Th cells, and cytotoxic T cells, but negatively with Treg cells on day 3 after stroke. Infections were associated with splenic volume, leukocyte counts, percentage of Treg cells, and serum levels of CRP, IL-10, and IFN-? on day 3. Lesion volume correlated positively with CRP, IL-6, and IL-23, but negatively with IFN-? on day 3. The NIHSS showed a positive relation with IL-6 and IL-10 on day 3. Ischemic stroke has a profound effect on the systemic immune system that might explain the increased susceptibility of stroke patients to infection.
Hydrogen Embrittlement of Industrial Components: Prediction, Prevention, and Models

Hydrogen embrittlement is a common, dangerous, and poorly understood cause of failure in many metal alloys. In practice, it is observed that different types of damage to industrial components have been tied to the presence and localization of hydrogen in metals. Many efforts have been made at understanding the effects of hydrogen on materials, resulting in an abundance of theoretical models and papers. However, a fully developed and practically-applicable predictive physical model still does not exist industrially for predicting and preventing hydrogen embrittlement. The connection of microstructure-based behaviors of materials and effects on the macroscopic measurable characteristics (stress levels, hardness, strength, and impact toughness) is of the utmost importance to achieve a unified model for hydrogen embrittlement. This paper gives an overview of the application of a model for structural integrity analysis of boiler tubes made of plain carbon steel exposed during operation to a local corrosion pro.
Regulated Release of Cryptococcal Polysaccharide Drives Virulence and Suppresses Immune Cell Infiltration into the Central Nervous System

ABSTRACT Cryptococcus neoformans is a common environmental yeast and opportunistic pathogen responsible for 15% of AIDS-related deaths worldwide. Mortality primarily results from meningoencephalitis, which occurs when fungal cells disseminate to the brain from the initial pulmonary infection site. A key C. neoformans virulence trait is the polysaccharide capsule. Capsule shields C. neoformans from immune-mediated recognition and destruction. The main capsule component, glucuronoxylomannan (GXM), is found both attached to the cell surface and free in the extracellular space (as exo-GXM). Exo-GXM accumulates in patient serum and cerebrospinal fluid at microgram/milliliter concentrations, has well-documented immunosuppressive properties, and correlates with poor patient outcomes. However, it is poorly understood whether exo-GXM release is regulated or the result of shedding during normal capsule turnover. We demonstrate that exo-GXM release is regulated by environmental cues and inversely correlates with surface capsule levels. We identified genes specifically involved in exo-GXM release that do not alter surface capsule thickness. The first mutant, the liv7Δ strain, released less GXM than wild-type cells when capsule was not induced. The second mutant, the cnag_00658Δ strain, released more exo-GXM under capsule-inducing conditions. Exo-GXM release observed in vitro correlated with polystyrene adherence, virulence, and fungal burden during murine infection. Additionally, we found that exo-GXM reduced cell size and capsule thickness under capsule-inducing conditions, potentially influencing dissemination. Finally, we demonstrated that exo-GXM prevents immune cell infiltration into the brain during disseminated infection and highly inflammatory intracranial infection. Our data suggest that exo-GXM performs a distinct role from capsule GXM during infection, altering cell size and suppressing inflammation.
A fairness algorithm for high-speed networks based on a resilient packet ring architecture

IEEE is currently standardizing a spatial reuse ring topology network called the Resilient Packet Ring (RPR, IEEE P802.17). The goal of the RPR development is to make a LAN/MAN standard, but also WANs are discussed. A ring network needs a fairness algorithm that controls each stations access to the ring. The RPR fairness algorithm is currently being developed with mostly long distances between stations in mind. In this paper we discuss how the algorithm needs to be changed in order to give good performance if and when RPR is used for high-speed networks and LANs with shorter distances between stations. We discuss different architectural parameters including buffers sizes and distance between stations. We suggest the use of triggers instead of timers to meet the tighter latency requirements of highspeed networks. The proposed improvements are compared and evaluated using a ring network simulator that we have built in the Java programming language.
Acquisition of multiband signals with minimum sub-Nyquist sampling

It is widely known that signals with sparse spectrums may be properly acquired when using specific sub-Nyquist sampling frequencies. This alleviates the sampling requirements in advanced acquisition systems, such as the direct-sampling solution to the software-defined radio paradigm. Unfortunately, beyond the theorem of bandpass sampling, analytical expressions for these valid sub-sampling rates are unavailable. Previously, the authors derived the analytical rules which guarantee that the minimum sub-Nyquist sampling frequency avoids aliasing. However, these equations are only valid for the restricted case of evenly-spaced equal-bandwidth multichannel systems, being useless in a broader framework with arbitrary-bandwidth channels. In this work, the general dual-band case is exhaustively analyzed. Given the channel bandwidths, the spectrum parameters which assure that the minimum sub-Nyquist frequency does not give rise to aliasing may be found. For more-than-two channels, some simple guidelines are also provided. Finally, simulation examples are shown to confirm the correctness of the deduced equations.